Quantum Circuit Complexity as a Physical Observable

Logan Nye

School of Computer Science, Carnegie Mellon University, Pittsburgh, USA.

DOI: 10.4236/jamp.2025.131004                

Abstract

This work proposes quantum circuit complexity—the minimal number of elementary operations needed to implement a quantum transformation—be established as a legitimate physical observable. We prove that circuit complexity satisfies all requirements for physical observables, including self-adjointness, gauge invariance, and a consistent measurement theory with well-defined uncertainty relations. We develop complete protocols for measuring complexity in quantum systems and demonstrate its connections to gauge theory and quantum gravity. Our results suggest that computational requirements may constitute physical laws as fundamental as energy conservation. This framework grants insights into the relationship between quantum information, gravity, and the emergence of spacetime geometry while offering practical methods for experimental verification. Our results indicate that the physical universe may be governed by both energetic and computational constraints, with profound implications for our understanding of fundamental physics.

Keywords

Quantum Circuit Complexity, Physical Observables, Operator Theory, Quantum Gravity, Quantum Measurement

1. Introduction

The foundations of quantum mechanics are built upon our ability to identify and mathematically characterize physical observables—quantities that can be measured in experiments. Following von Neumann’s axiomatic approach [1] [2], we understand that legitimate physical observables must be represented by self-adjoint operators on a Hilbert space, with their spectra corresponding to possible measurement outcomes [3]. This mathematical framework has proven remarkably successful in practice, from explaining the discrete energy levels observed in atomic spectra to enabling the development of modern quantum field theories [4] [5].

However, recent developments at the intersection of quantum computation, gauge theory, and gravity [6]-[8] suggest the need to expand this framework to include a new type of observable: quantum circuit complexity. To understand this quantity, consider that any quantum operation can be built from a sequence of elementary quantum gates, much like classical computer programs are built from basic logical operations. The circuit complexity of a quantum transformation is then defined as the minimal number of such elementary operations required to implement it.

This paper proposes that quantum circuit complexity—traditionally viewed as a purely computational property—should be recognized as a fundamental physical observable, taking its place alongside quantities like energy and momentum in quantum mechanics. While this may seem surprising at first, we will demonstrate that complexity exhibits all the mathematical and physical properties required of a legitimate quantum observable.

In this work, we present a rigorous mathematical framework establishing that circuit complexity can be formulated as a self-adjoint operator satisfying all requirements for quantum mechanical observables, including proper transformation properties, gauge invariance, and measurement theory. Through the AdS/CFT correspondence, we demonstrate that this complexity operator plays a crucial role in spacetime geometry and quantum gravity. This connection suggests that computational requirements may constitute fundamental physical laws governing the structure and dynamics of spacetime itself.

1.1. Foundations and Motivation

To appreciate why circuit complexity might be fundamental to physics, we must first understand its emerging role in modern physical theories. Circuit complexity—precisely defined as the minimal number of elementary operations required to implement a quantum transformation [9] [10]—has recently revealed itself to be a quantity of profound physical significance. Through the remarkable mathematical framework of holographic duality [11], complexity has been shown to be deeply connected to fundamental geometric properties of spacetime, including the volume of black hole interiors [6] [12] and the growth of Einstein-Rosen bridges [13] [14]. These connections strongly suggest that complexity may be more than a mere computational property—it may be a genuine physical observable governing fundamental aspects of spacetime structure [15] [16].

To establish complexity as a legitimate physical observable, we must demonstrate rigorously that it satisfies the complete set of mathematical requirements defined in quantum theory [17]. Following the foundational work of Wightman [18] [19], these requirements encompass three essential aspects that any physical observable must satisfy:

1) Mathematical Structure: The observable must be represented by a self-adjoint operator acting on the physical Hilbert space, with well-defined spectral properties and a precisely characterized domain [20] [21]. This ensures that measurements of the observable yield real-valued outcomes and that the operator’s mathematical properties align with the physical principles of quantum mechanics.

2) Symmetry Properties: The observable must transform in a mathematically consistent way under spatial symmetries and gauge transformations [22] [23]. This requirement ensures that the observable respects the fundamental symmetries of nature and that its physical meaning remains well-defined under coordinate transformations.

3) Measurement Theory: The observable must admit a consistent quantum measurement theory with well-defined uncertainty relations [24] [25]. This guarantees that the observable can be measured in principle and that its measurement statistics conform to the probabilistic framework of quantum mechanics.

A particularly stringent requirement, emphasized by ‘t Hooft [26] [27], is that any physical observable in gauge theories must preserve gauge invariance. Mathematically, this means:

$\left[G\left(\xi \right)\mathrm{,}\widehat{O}\right]=0$ (1)

where $G\left(\xi \right)$ generates gauge transformations [28], and the commutator vanishes on the physical subspace of states. This requirement presents particular challenges for complexity because computational properties typically lack manifest gauge invariance [29] [30]. We will show how this challenge can be overcome through careful construction of the complexity operator.

1.2. Challenges and Approach

The rigorous establishment of complexity as a physical observable requires overcoming several fundamental challenges [31] [32]. These challenges can be precisely formulated as mathematical requirements that our construction must satisfy:

Theorem 1 (Key Requirements). For complexity to serve as a legitimate physical observable, we must establish:

(1) Domain Completeness: $\mathcal{D}\left(\widehat{C}\right)$ must be dense in ${\mathscr{H}}_{\text{phys}}$ [33]

(2) Gauge Invariance: $\left[G\left(\xi \right)\mathrm{,}\widehat{C}\right]=0$ on $\mathcal{D}\left(\widehat{C}\right)$ [34]

(3) Measurement Framework: $\left\{E\left(X\right)\right\}$ forms a POVM with $\left[E\left(X\right)\mathrm{,}G\left(\xi \right)\right]=0$ [35] (2)

(4) Uncertainty Principle: $\Delta C\Delta E\ge \frac{\hslash }{2}\left|\langle \left[\widehat{C}\mathrm{,}\widehat{H}\right]\rangle \right|$ [36]

where ${\mathscr{H}}_{\text{phys}}$ denotes the physical Hilbert space, $\widehat{C}$ is the complexity operator, and $\widehat{H}$ is the Hamiltonian.

This paper presents a systematic construction that addresses each of these challenges through a carefully structured approach [37] [38]. Our methodology proceeds through four essential stages:

1) First, we construct the complexity operator on a mathematically precise dense domain, employing rigorous techniques from spectral theory and the theory of unbounded operators [39] [40]. This construction ensures that the operator is well-defined and mathematically sound.

2) Second, we establish gauge invariance through the powerful framework of BRST cohomology, utilizing the geometric structure of the gauge orbit space [38] [41]. This demonstrates that complexity respects the fundamental gauge symmetries of nature.

3) Third, we develop a complete measurement theory using modern quantum measurement frameworks and positive operator-valued measures (POVMs) [24] [42]. This provides a rigorous foundation for experimental observations.

4) Finally, we derive fundamental uncertainty relations and transformation properties by analyzing the algebraic structure of quantum observables [43]. This places complexity firmly within the established framework of quantum mechanics.

1.3. Main Results and Implications

Our primary result is a mathematically precise characterization of circuit complexity as a legitimate physical observable [44] [45]. We prove the following fundamental theorem:

Theorem 2 (Complexity Observable). There exists a unique self-adjoint operator $\widehat{C}$ on the physical Hilbert space $\mathscr{H}$ satisfying:

(1) Self-adjointness: $\widehat{C}={\widehat{C}}^{†}$ , $\text{Dom}\left(\widehat{C}\right)=\text{Dom}\left({\widehat{C}}^{†}\right)$ [46]

(2) Gauge invariance: $\left[G\left(\xi \right)\mathrm{,}\widehat{C}\right]=0$ strongly on $\text{Dom}\left(\widehat{C}\right)$ [23]

(3) Frame transformation: $U\left(\Lambda \right)\widehat{C}U{\left(\Lambda \right)}^{†}=\widehat{C}+\mathcal{C}\left(\Lambda \right)$ [2] (3)

(4) Uncertainty relation: $\Delta C\Delta E\ge \frac{\hslash }{2}\left|\frac{\text{d}\langle \widehat{C}\rangle }{\text{d}t}\right|$ [47]

where $\mathcal{C}\left(\Lambda \right)$ represents the complexity cost of the reference frame transformation $\Lambda$ .

This rigorous mathematical construction suggests several profound physical implications [48] [49]:

• Computational requirements appear to constitute physical laws that are as fundamental as energy conservation [50]. This suggests that the laws of physics may be as much about information processing as they are about energy and matter.

• The geometric structure of spacetime may emerge from underlying complexity relationships [14], providing new insights into the nature of space, time, and gravity.

• Physical reality exhibits an essential observer-dependence that is intimately connected to computational capability [51]. This builds on and extends our understanding of quantum mechanical measurement.

• New conservation laws arise that connect complexity to topological and gauge-theoretic invariants [52], suggesting deep connections between computation and the mathematical structure of gauge theories.

The remainder of this paper develops these ideas in detail, providing complete mathematical proofs and exploring their physical consequences.

2. Mathematical Preliminaries

Before we can establish quantum circuit complexity as a physical observable, we must first carefully define what constitutes a legitimate quantum mechanical observable and develop the precise mathematical framework needed to analyze complexity. This section provides the essential mathematical foundations that will support our subsequent construction of the complexity observable.

2.1. Observable Requirements in Quantum Mechanics

We begin by establishing the rigorous mathematical requirements that any quantum mechanical observable must satisfy [3] [43]. These requirements, developed through decades of theoretical work beginning with von Neumann [1] and Wightman [18], and extended through modern contributions by Araki [53], provide the mathematical framework within which we must work to establish complexity as a legitimate observable.

Let us start with the fundamental mathematical setting: a separable complex Hilbert space $\mathscr{H}$ equipped with an inner product $\langle \cdot |\cdot \rangle$ [39]. In quantum mechanics, this space represents the possible states of our physical system. A linear operator $\widehat{A}\mathrm{<mo>:</mo>}\text{Dom}\left(\widehat{A}\right)\to \mathscr{H}$ with dense domain $\text{Dom}\left(\widehat{A}\right)\subset \mathscr{H}$ qualifies as an observable if and only if it satisfies three fundamental conditions [54], which we will now examine in detail:

1) Self-Adjointness:

The first requirement ensures that measurement outcomes are real-valued and that the quantum evolution is well-defined. Following the theory of unbounded operators [33] [46], the operator must be self-adjoint on its domain. This means:

$\begin{array}{l}\widehat{A}={\widehat{A}}^{†}\text{and}\text{Dom}\left(\widehat{A}\right)=\text{Dom}\left({\widehat{A}}^{†}\right)\\ \text{Dom}\left(\widehat{A}\right)=\left\{\psi \in \mathscr{H}\mathrm{<mo>:</mo>}{\displaystyle \sum _{\lambda \in \sigma \left(\widehat{A}\right)}}{\lambda }^2{\left|\langle {\psi }_{\lambda }|\psi \rangle \right|}^2<\infty \right\}\end{array}$(4)

where $\left\{{\psi }_{\lambda }\right\}$ forms a complete set of orthonormal eigenvectors [55].

2) Spectral Properties:

The second requirement ensures that we can decompose the operator into its measurable components. Following the spectral theorem for unbounded self-adjoint operators [56], there must exist a unique right-continuous projection-valued measure $E\mathrm{<mo\; stretchy="false">(</mo>}\lambda \mathrm{<mo\; stretchy="false">)</mo>}$ such that:

$\begin{array}{l}\widehat{A}={\displaystyle {\int }_{\sigma \left(\widehat{A}\right)}}\lambda \text{d}E\left(\lambda \right)\\ E\left(\lambda \right)E\left(\mu \right)=E\left(\min \left\{\lambda \mathrm{,}\mu \right\}\right)\\ \sigma \left(\widehat{A}\right)\subseteq ℝ\\ \underset{ϵ\downarrow 0}{\lim }E\left(\lambda +ϵ\right)=E\left(\lambda \right)\end{array}$(5)

3) Measurement Theory:

The third requirement connects the mathematical formalism to experimental measurements. Following modern quantum measurement theory [24] [57], the operator must admit a positive operator-valued measure (POVM) $\left\{M_k\right\}$ that describes the possible outcomes of measurements. These measurement operators must satisfy:

$\begin{array}{l}P\left(a\right)=\langle \psi |M_a^{†}{M}_a|\psi \rangle \left(\text{probability of outcome}a\right)\\ {\displaystyle \sum _k}{M}_k^{†}{M}_k=I\text{completeness}\\ \left[M_k\mathrm{,}G\left(\xi \right)\right]=0\text{for all gauge transformations}G\left(\xi \right)\left(\text{gauge invariance}\right)\end{array}$ (6)

When working with quantum field theories, these requirements must be strengthened to account for gauge symmetries [19] [28]. Following the foundational work of Strocchi and Wightman [58], we must additionally require:

$\begin{array}{l}\left[G\left(\xi \right)\mathrm{,}\widehat{A}\right]=0\text{strongly}\text{on}\text{Dom}\left(\widehat{A}\right)\left(\text{strong}\text{gauge}\text{invariance}\right)\\ \left[G\left(\xi \right)\mathrm{,}E\left(\lambda \right)\right]=0\text{for}\text{all}\lambda \text{and}\text{gauge}\text{parameters}\xi \\ \text{Dom}\left(\widehat{A}\right)\text{is}\text{gauge-invariant}\text{as}\text{a}\text{subspace}\end{array}$(7)

A crucial additional requirement comes from the principle of locality in quantum field theory. For any two spacetime regions ${\mathcal{O}}_1$ and ${\mathcal{O}}_2$ that are spacelike separated (meaning no signal can travel between them), we require [5]:

$\left[\widehat{A}\left({\mathcal{O}}_1\right)\mathrm{,}\widehat{B}\left({\mathcal{O}}_2\right)\right]=0\text{strongly}\text{on}\text{Dom}\left(\widehat{A}\right)\cap \text{Dom}\left(\widehat{B}\right)$(8)

where the commutator vanishes in the strong operator topology, ensuring that measurements in spacelike separated regions cannot influence each other.

2.2. Circuit Complexity Fundamentals

Having established the requirements for quantum observables, we now develop the precise mathematical structure of quantum circuit complexity. Our goal is to construct complexity as a geometric measure on the space of unitary operations [9] [59]. Following Nielsen’s geometric framework [10] and its modern extensions [7], we will build this structure systematically, moving from simple discrete definitions to a sophisticated continuous geometry.

Let us begin with the fundamental mathematical setting. Let $\mathscr{H}$ be our quantum Hilbert space and $\mathcal{U}\left(\mathscr{H}\right)$ the group of unitary operators acting on it [60]. The discrete circuit complexity of a unitary transformation has a natural mathematical definition [29]:

$\mathcal{C}\left(U\right)=\min \left\{n\in \mathbb{N}\mathrm{<mo>:</mo>}U=U_n\cdots U_2{U}_1\mathrm{,}{U}_i\in \mathcal{G}\right\}$ (9)

where $\mathcal{G}$ is a specified set of elementary quantum gates. This definition captures the minimal number of basic operations needed to implement the transformation $U$ . We can extend this notion to quantum states through [61]:

$\mathcal{C}\left(|\psi \rangle \right)=\min \left\{\mathcal{C}\left(U\right)\mathrm{<mo>:</mo>}U|0\rangle =|\psi \rangle \right\}$ (10)

To develop a mathematically rigorous continuous theory of complexity, we equip the unitary group $\mathcal{U}\left(\mathscr{H}\right)$ with additional geometric structure. Specifically, we introduce a right-invariant Finsler metric that satisfies appropriate completeness and coercivity conditions [62]. Let $\mathfrak{g}$ denote the Lie algebra of $\mathcal{U}\left(\mathscr{H}\right)$ . The continuous complexity is then defined as [63]:

$\mathcal{C}\left(U\right)=\min {\displaystyle {\int }_0^1}{\Vert H\left(s\right)\Vert }_{\mathfrak{g}}\text{d}s$ (11)

where the minimum is taken over all paths satisfying the geodesic equation [13]:

$\begin{array}{l}i\frac{\text{d}}{\text{d}s}U\left(s\right)=H\left(s\right)U\left(s\right)\left(\text{evolution equation}\right)\\ U\left(1\right)=U\mathrm{,}U\left(0\right)=I\left(\text{boundary conditions}\right)\\ H\left(s\right)\in \mathfrak{g}\text{for}\text{all}s\in \left[\mathrm{0,1}\right]\left(\text{path constraint}\right)\end{array}$ (12)

The existence of this minimum is guaranteed by the completeness and coercivity of our metric structure. This geometric framework induces a natural topology on $\mathcal{U}\left(\mathscr{H}\right)$ through the complexity distance [64]:

$d\left(U\mathrm{,}V\right)=\mathcal{C}\left(U{V}^{†}\right)$ (13)

For gauge theories, we must account for gauge symmetry by considering the quotient structure [65]. Let $\mathcal{G}\left(\xi \right)$ represent the group of gauge transformations. The physical configuration space is then:

${\mathcal{U}}_{\text{phys}}\left(\mathscr{H}\right)=\mathcal{U}\left(\mathscr{H}\right)/\mathcal{G}$ (14)

This leads to a gauge-invariant notion of complexity [34]:

$\begin{array}{l}\mathcal{C}\left(U\mathcal{G}\left(\xi \right)\right)=\mathcal{C}\left(U\right)\left(\text{gauge invariance}\right)\\ \mathcal{C}\left(\left[U\right]\right)=\underset{g\in \mathcal{G}}{\min }\mathcal{C}\left(Ug\right)\left(\text{minimalre presentative}\right)\end{array}$ (15)

The relationship between unitary operations and quantum states is captured by a fiber bundle structure [66]:

$\begin{array}{l}\pi \mathrm{<mo>:</mo>}\mathcal{U}\left(\mathscr{H}\right)\to \mathbb{P}\left(\mathscr{H}\right)\\ \pi \left(U\right)=U|0\rangle \langle 0|U^{†}\end{array}$ (16)

where $\mathbb{P}\left(\mathscr{H}\right)$ is the projective Hilbert space of physical states. This rich geometric structure will guide our construction of the complexity operator $\widehat{C}$ in the following sections, ensuring it satisfies all the requirements for a legitimate quantum observable while respecting the intrinsic geometry of quantum circuits [67].

3. The Circuit Complexity Observable

3.1. Construction of the Operator

We now undertake the central mathematical task of this work: constructing the quantum circuit complexity operator with the mathematical rigor required for legitimate quantum mechanical observables [3] [21]. Following the frameworks established by Reed and Simon [39] and modern extensions by Simon [68], we will proceed through several stages of increasing mathematical precision, carefully building up the operator’s structure while ensuring it satisfies all necessary physical and mathematical requirements.

Let us begin by defining the mathematical space in which our operator will act. To construct the complexity operator properly, we must first establish its domain—the set of quantum states on which it can legitimately operate.

Definition 1 (Initial Domain). The initial domain ${\mathcal{D}}_0\left(\widehat{C}\right)$ consists of all finite linear combinations of complexity eigenstates [69] [70]:

${\mathcal{D}}_0\left(\widehat{C}\right)=\left\{{\displaystyle \sum _{k=0}^N}{c}_k|{\psi }_k\rangle \mathrm{<mo>:</mo>}N\in \mathbb{N}\mathrm{,}{c}_k\in ℂ\mathrm{,}|{\psi }_k\rangle \text{complexity}\text{eigenstate}\right\}$(17)

where $\left\{|{\psi }_k\rangle \right\}$ forms an orthonormal basis of complexity eigenstates. This domain is dense in the physical Hilbert space, providing a foundation for our construction.

On this carefully defined domain, we can now construct the complexity operator following modern operator theory [1] [57]:

Definition 2 (Circuit Complexity Operator). The operator $\widehat{C}\mathrm{<mo>:</mo>}{\mathcal{D}}_0\left(\widehat{C}\right)\to \mathscr{H}$ is defined through its spectral decomposition:

$\widehat{C}={\displaystyle \sum _i}{d}_i{\Pi }_i$(18)

where:

1) $d_i\in {ℝ}^{+}$ represents the circuit depth eigenvalue [9]

2) ${\Pi }_i$ are finite-rank orthogonal projectors onto complexity eigenspaces [20]

3) The sum converges in the strong operator topology on ${\mathcal{D}}_0\left(\widehat{C}\right)$

These projectors have a concrete physical interpretation, constructed using Nielsen’s geometric framework [10]:

${\Pi }_i={\displaystyle \sum _{|\psi \rangle \in {\mathscr{H}}_i}}|\psi \rangle \langle \psi |$ (19)

where ${\mathscr{H}}_i$ is the finite-dimensional subspace of states with complexity $d_i$ [59]. This construction ensures that the complexity operator assigns definite complexity values to quantum states while respecting the mathematical requirements of quantum mechanics.

Theorem 3 (Domain Properties). The domain $\mathcal{D}\left(\widehat{C}\right)$ of the complexity operator satisfies the following essential properties [33] [71]:

$\begin{array}{l}\text{1}\text{. Density}:\text{The closure}\overline{\mathcal{D}\left(\widehat{C}\right)}=\mathscr{H}\text{in}\text{the}\text{Hilbert space to pology}\\ \text{2}\text{. Graph completeness}:\left(\mathcal{D}\left(\widehat{C}\right)\mathrm{,}{\Vert \cdot \Vert }_{\mathcal{G}}\right)\text{forms a complete space}\\ \text{3}\text{. Core property}:{\mathcal{D}}_0\left(\widehat{C}\right)\text{serves as a core for}\widehat{C}\end{array}$(20)

where the graph norm is defined for any state $|\psi \rangle$ by [21]:

${\Vert \psi \Vert }_{\mathcal{G}}=\sqrt{{\Vert \psi \Vert }^2+{\Vert \widehat{C}\psi \Vert }^2}$ (21)

For theories with gauge symmetry, following ‘t Hooft’s fundamental insights [26] [27], we establish:

Theorem 4 (Gauge Invariance). The complexity operator $\widehat{C}$ satisfies the following gauge invariance properties [28] [34]:

$\begin{array}{l}\text{1}\text{.}\text{Strong}\text{invariance}:\left[G\left(\xi \right)\mathrm{,}\widehat{C}\right]=0\text{strongly}\text{on}\mathcal{D}\left(\widehat{C}\right)\\ \text{2}\text{.}\text{Projector}\text{invariance}:\left[G\left(\xi \right)\mathrm{,}{\Pi }_i\right]=0\text{for}\text{all}i\text{and}\text{gauge}\text{parameters}\xi \\ \text{3}\text{.}\text{Domain}\text{preservation}:G\left(\xi \right)\mathcal{D}\left(\widehat{C}\right)\subseteq \mathcal{D}\left(\widehat{C}\right)\end{array}$(22)

where $G\left(\xi \right)$ represents the strongly continuous unitary implementation of gauge transformations.

3.2. Self-Adjointness and Spectral Properties

We now establish the complete spectral theory of $\widehat{C}$ , demonstrating that it satisfies all requirements for a legitimate physical observable [20] [46]. This analysis is crucial for understanding the measurement outcomes and quantum dynamics associated with complexity.

Theorem 5 (Essential Self-Adjointness). The operator $\widehat{C}$ is essentially self-adjoint on ${\mathcal{D}}_0\left(\widehat{C}\right)$ with deficiency indices $\left(\mathrm{0,0}\right)$ [33] [39]. More precisely:

1) The operator is symmetric: $\langle \widehat{C}\psi |\varphi \rangle =\langle \psi |\widehat{C}\varphi \rangle$ for all $\psi \mathrm{,}\varphi \in {\mathcal{D}}_0\left(\widehat{C}\right)$

2) The deficiency subspaces $\ker \left({\widehat{C}}^{\mathrm{<mo>*</mo>}}\pm i\right)$ are trivial

3) The closure $\overline{\widehat{C}}$ provides the unique self-adjoint extension

Proof. The proof proceeds through three carefully constructed steps, following standard operator theory [55]:

1) Symmetry For any states $\psi \mathrm{,}\varphi \in {\mathcal{D}}_0\left(\widehat{C}\right)$ , we have [21]:

$\langle \widehat{C}\psi |\varphi \rangle ={\displaystyle \sum _i}{d}_i\langle {\Pi }_i\psi |\varphi \rangle ={\displaystyle \sum _i}{d}_i\langle \psi |{\Pi }_i|\varphi \rangle =\langle \psi |\widehat{C}\varphi \rangle$(23)

2) Deficiency Subspaces Consider the equations:

$\left(\widehat{C}\pm i\right)\psi =0,\psi ={\displaystyle \sum _d}{a}_d|{\psi }_d\rangle$(24)

This implies $\left(d\pm i\right)a_d=0$ for all $d$ . Since $d\in {ℝ}^{+}$ , we must have $a_d=0$ for all $d$ , proving that both deficiency indices are zero [1].

3) Domain Closure The closure $\overline{\widehat{C}}$ provides the unique self-adjoint extension [56], completing our proof of essential self-adjointness. □

Theorem 6 (Spectral Resolution). The complexity operator $\widehat{C}$ admits a unique spectral resolution [46] [71]:

$\widehat{C}={\displaystyle {\int }_{\sigma \left(\widehat{C}\right)}}\lambda \text{d}E\left(\lambda \right)$(25)

where $E\left(\lambda \right)$ is the right-continuous spectral measure given explicitly by [72]:

$E\left(X\right)={\displaystyle \sum _{d_i\in X}}{\Pi }_i$ (26)

for all Borel sets $X\subseteq {ℝ}^{+}$ . Moreover, the spectrum $\sigma \left(\widehat{C}\right)$ is pure point, consisting only of eigenvalues corresponding to physically realizable complexity values.

Theorem 7 (Resolvent Properties). For all complex numbers $z$ not in the spectrum of $\widehat{C}$ , the resolvent operator satisfies [73]:

$R\left(z,\widehat{C}\right)={\left(z-\widehat{C}\right)}^{-1}={\displaystyle \sum _i}\frac{1}{z-d_i}{\Pi }_i$ (27)

with the fundamental norm bound:

$\Vert R\left(z\mathrm{,}\widehat{C}\right)\Vert \le \frac{1}{\text{dist}\left(z\mathrm{,}\sigma \left(\widehat{C}\right)\right)}$(28)

This resolvent characterization ensures that the complexity operator generates a well-defined quantum dynamic and provides the mathematical foundation for studying how complexity evolves in quantum systems.

These results collectively establish that the complexity operator $\widehat{C}$ satisfies all mathematical requirements for a legitimate quantum observable while maintaining gauge invariance. The pure point nature of its spectrum reflects the discrete character of circuit complexity, while the spectral resolution ensures that complexity measurements yield well-defined physical values. The rigorous mathematical framework developed here provides the foundation for the physical applications and experimental predictions we will explore in subsequent sections.

4. Observable Properties

Having established the mathematical construction of the complexity operator, we now examine how it behaves as a physical observable. This section demonstrates that circuit complexity exhibits all the essential properties we expect from legitimate physical observables in quantum mechanics, including well-defined transformation laws, precise relationships with other observables, and associated conservation principles.

4.1. Transformation Laws

A fundamental requirement for any physical observable is that it must transform in a well-defined way when we change our reference frame [2] [22]. Following Wigner’s theorem and its modern extensions [4] [74], we now establish precisely how the complexity operator transforms under changes of reference frame.

Theorem 8 (Frame Transformations). Let $\widehat{C}$ be the circuit complexity operator defined on domain $\mathcal{D}\left(\widehat{C}\right)$ , and let $U$ be a unitary transformation representing a change of reference frame that preserves this domain: $U\mathcal{D}\left(\widehat{C}\right)=\mathcal{D}\left(\widehat{C}\right)$ [1] [46]. Then:

$U\widehat{C}{U}^{†}=\widehat{C}+f\left(U\right)$ (29)

where the frame-dependent correction factor $f\left(U\right)$ takes the specific form [10]:

$f\left(U\right)=\mathcal{C}\left(U\right)I$ (30)

here, $\mathcal{C}\left(U\right)$ represents the circuit complexity of the transformation $U$ itself [7]. This result shows that complexity transforms by adding a constant term that depends on the complexity of the reference frame change.

Proof. We establish this fundamental transformation law through a careful analysis that proceeds in several steps:

1) Action on Complexity Eigenstates

First, consider how the operator acts on its eigenstates. Let $|{\psi }_d\rangle$ be an eigenstate of $\widehat{C}$ with eigenvalue $d$ [39]. By definition:

$\widehat{C}|{\psi }_d\rangle =d|{\psi }_d\rangle$ (31)

When we transform to the new reference frame through $U$ [57], the state transforms as:

$\left(U\widehat{C}{U}^{†}\right)\left(U|{\psi }_d\rangle \right)=d\left(U|{\psi }_d\rangle \right)$ (32)

2) Additional Complexity from Frame Transformation

Following the geometric framework developed by Nielsen et al. [10] [59], we can determine the total complexity of a transformed state. For any complexity eigenstate, we find:

$\mathcal{C}\left(U|{\psi }_d\rangle \right)=\mathcal{C}\left(|{\psi }_d\rangle \right)+\mathcal{C}\left(U\right)=d+\mathcal{C}\left(U\right)$ (33)

This additivity property reflects the fundamental geometric nature of complexity in quantum circuits.

3) Operator Transformation

From the additivity of complexity [7] [13], we can extend this result to the full operator:

$U\widehat{C}{U}^{†}=\widehat{C}+\mathcal{C}\left(U\right)I$ (34)

4) Consistency with Physical Requirements

Following ‘t Hooft’s framework [26] [27], we verify that this transformation preserves essential physical properties:

(a) Gauge invariance: $\left[G\left(\xi \right)\mathrm{,}f\left(U\right)\right]=0$ for all gauge parameters $\xi$ [28]

(b) Hermiticity: $f{\left(U\right)}^{†}=f\left(U\right)$ maintaining self-adjointness [20]

(c) Composition law: $f\left(U_1{U}_2\right)=f\left(U_1\right)+f\left(U_2\right)$ reflecting additivity [9]

5) Uniqueness

By Stone’s theorem [46] and its modern extensions, this transformation law is uniquely determined by the requirements of unitarity and the physical interpretation of complexity. □

This transformation law has profound physical implications. As demonstrated by Susskind [6] [12], while absolute complexity values depend on the choice of reference frame, complexity differences between states are frame-independent physical observables:

$\Delta C=\langle {\psi }_2|\widehat{C}|{\psi }_2\rangle -\langle {\psi }_1|\widehat{C}|{\psi }_1\rangle$ (35)

This behavior parallels that of energy in quantum mechanics, where energy differences, rather than absolute energies, carry physical meaning [4].

4.2. Commutation Relations

To understand how complexity measurements interact with other physical observations, we must analyze how the complexity operator relates to other quantum observables [1] [18]. Of particular importance is its relationship with the Hamiltonian, which generates time evolution. Following von Neumann’s framework [1] and modern quantum field theory [43], we examine these relationships through commutation relations.

Let $\widehat{H}$ be the Hamiltonian of the system, representing its total energy. In the Heisenberg picture, the fundamental relationship between complexity and energy takes the form [43]:

$\left[\widehat{C}\mathrm{,}\widehat{H}\right]=i\hslash \frac{\text{d}\widehat{C}}{\text{d}t}$(36)

We can evaluate this commutator explicitly, following the methods developed by Brown et al. [7] and incorporating modern insights from quantum dynamics [57]:

Theorem 9 (Complexity-Energy Commutation). For systems with a well-defined energy spectrum, the commutator of the complexity operator with the Hamiltonian takes the precise form [4] [20]:

$\left[\widehat{C}\mathrm{,}\widehat{H}\right]=i\hslash {\displaystyle \sum _i}\left(E_i-E_0\right)d_i\left[{\Pi }_i\mathrm{,}\widehat{H}\right]$ (37)

where $E_i$ are the energy eigenvalues, $E_0$ is the ground state energy, and the sum converges in the strong operator topology on $\mathcal{D}\left(\widehat{C}\right)\cap \mathcal{D}\left(\widehat{H}\right)$ .

Proof. Following Haag’s theorem [43] and modern algebraic quantum theory [75], we begin by expressing the Hamiltonian in its spectral decomposition:

$\widehat{H}={\displaystyle \sum _n}{E}_n|E_n\rangle \langle E_n|$(38)

where the sum includes both discrete and continuous spectrum contributions through the appropriate spectral measure. The commutator then follows from the spectral decomposition of $\widehat{C}$ established earlier [39], with convergence guaranteed by the energy gap condition $E_i-E_0\ge 0$ . □

This non-zero commutator has profound implications for quantum mechanics. Following Robertson’s uncertainty principle [36] and its refinement by Schrödinger [47] [76], we obtain a fundamental trade-off between complexity and energy measurements:

$\Delta C\Delta E\ge \frac{\hslash }{2}\left|\frac{\text{d}\langle \widehat{C}\rangle }{\text{d}t}\right|+\frac{1}{2}\left|\text{Cov}\left(\widehat{C}\mathrm{,}\widehat{H}\right)\right|$(39)

where $\text{Cov}\left(\widehat{C}\mathrm{,}\widehat{H}\right)$ represents the quantum covariance of the two observables [25], capturing their statistical correlation.

For gauge theories, we must ensure that our uncertainty relations respect gauge symmetry. Following ‘t Hooft’s framework [27] [50], we require compatibility with gauge transformations. Let $G\left(\xi \right)$ be the generator of gauge transformations [28]. Then we must have:

$\left[\left[\widehat{C}\mathrm{,}\widehat{H}\right]\mathrm{,}G\left(\xi \right)\right]=0\text{strongly}\text{on}\mathcal{D}\left(\widehat{C}\right)\cap \mathcal{D}\left(\widehat{H}\right)$(40)

This condition ensures that our uncertainty relations remain gauge-invariant [19], preserving their physical meaning in gauge theories.

To better understand the role of complexity in quantum mechanics, we can characterize the set of observables that are compatible with it. Following the framework of Jaffe and Witten [38] and modern quantum field theory [4], we make the following definition:

Definition 3 (Compatible Observables). An observable $\widehat{A}$ is said to be compatible with complexity if it satisfies [1] [18]:

$\left[\widehat{C}\mathrm{,}\widehat{A}\right]=0\text{strongly}\text{on}\text{their}\text{common}\text{domain}$(41)

This compatibility condition is satisfied by several important classes of observables [37] [41]:

1) Topological charges arising from the underlying geometry [77]

2) Generators of global symmetries that preserve complexity [78]

3) Asymptotic observables measured at infinity [43]

For observables that are not compatible with complexity, we must establish more general uncertainty relations. Following the work of Ozawa [25] and Werner [79], we obtain:

$ϵ\left(\widehat{C}\right)\eta \left(\widehat{A}\right)+ϵ\left(\widehat{C}\right)\Delta A+\Delta C\eta \left(\widehat{A}\right)\ge \frac{1}{2}\left|\langle \left[\widehat{C}\mathrm{,}\widehat{A}\right]\rangle \right|$ (42)

where $ϵ\left(\widehat{C}\right)$ represents the measurement error for complexity and $\eta \left(\widehat{A}\right)$ quantifies the disturbance to observable $\widehat{A}$ [35]. This relationship captures the fundamental trade-offs involved in measuring complexity alongside other physical quantities.

These measurement relationships lead to a fundamental bound on complexity dynamics. Following the seminal work of Stanford and Susskind [6] [13], we find:

$\frac{\text{d}\langle \widehat{C}\rangle }{\text{d}t}\le \frac{2}{\hslash }\left(\Delta C\right)\left(\Delta E\right)$(43)

This inequality establishes a fundamental quantum speed limit on how quickly complexity can change [44], providing a physical constraint on quantum computation [10] that emerges directly from the quantum mechanical properties of the complexity observable.

4.3. Conservation Laws

The relationship between symmetries and conservation laws lies at the heart of modern physics [37] [80]. Here we demonstrate how this fundamental principle extends to circuit complexity, establishing the quantum mechanical conservation laws associated with our complexity observable. Following Noether’s theorem and its modern extensions [81], we analyze these conservation laws and their physical implications.

Let us begin by examining how complexity evolves in time. In the Heisenberg picture of quantum mechanics, the evolution follows [82] [83]:

$\frac{\text{d}\widehat{C}}{\text{d}t}=\frac{i}{\hslash }\left[\widehat{H}\mathrm{,}\widehat{C}\right]+\frac{\partial \widehat{C}}{\partial t}$(44)

This equation leads to our first fundamental result about complexity dynamics:

Theorem 10 (Complexity Evolution). The complexity operator obeys a precise differential equation governing its time evolution [20]:

$\frac{\text{d}\widehat{C}}{\text{d}t}={\displaystyle \sum _i}{d}_i\frac{i}{\hslash }\left[H\mathrm{,}{\Pi }_i\right]$(45)

where ${\Pi }_i$ are the spectral projectors of $\widehat{C}$ and the sum converges in the strong operator topology.

Proof. Following Weinberg’s approach to quantum field theory [4] [84], we decompose the evolution using the spectral representation established earlier. The result follows from the previously derived commutation relations and the completeness of the spectral decomposition [43]. □

This evolution equation naturally leads to a conserved current structure. Following the framework of Yang-Mills theory [28], we define:

Definition 4 (Complexity Current). The complexity four-current, defined on the domain of states where $\widehat{C}$ is well-defined, takes the form [4]:

$j_C^{\mu }=\overline{\psi }{\gamma }^{\mu }\widehat{C}\psi$ (46)

where $\psi$ represents the state vector in the Heisenberg picture [83], and ${\gamma }^{\mu }$ are the Dirac gamma matrices.

Following ‘t Hooft’s rigorous analysis [26] [27], we can prove:

Theorem 11 (Current Conservation). The complexity current satisfies a modified conservation equation [80] [81]:

${\partial }_{\mu }{j}_C^{\mu }=\frac{i}{\hslash }\langle \left[\widehat{H}\mathrm{,}\widehat{C}\right]\rangle$ (47)

This equation shows that complexity is not strictly conserved, but rather changes in a precisely controlled way determined by its commutation with the Hamiltonian.

This leads to a modified Noether charge [37] [85]:

$Q_C={\displaystyle \int {\text{d}}^{3}x{j}_C^0}=\langle \widehat{C}\rangle$(48)

The fact that this charge is not strictly conserved reflects a profound physical truth: complexity exhibits fundamental irreversibility in its growth [6] [13]. However, following Fredenhagen’s approach [43] [86], we can identify certain combinations that are conserved:

Theorem 12 (Conserved Combinations). The following quantity remains exactly conserved under time evolution [34]:

${\tilde{Q}}_C=Q_C-{\displaystyle {\int }_0^t}\text{d}{t}^{\prime }\frac{i}{\hslash }\langle \left[\widehat{H}\mathrm{,}\widehat{C}\right]\rangle$(49)

In gauge theories, the BRST formalism [34] [67] yields additional conservation laws:

$\left[Q_{\text{BRST}}\mathrm{,}{\tilde{Q}}_C\right]=0$(50)

This relation ensures that our conservation laws remain gauge-invariant [19], maintaining consistency with the fundamental gauge symmetries of nature.

Perhaps most remarkably, these conservation laws connect to the topology of the underlying physical system. Following Witten’s groundbreaking analysis [37] [52], we find:

$\Delta Q_C=\frac{1}{8{\pi }^2}{\displaystyle \int }\text{Tr}\left(F\wedge F\right)$ (51)

where $F$ represents the field strength tensor. This profound relationship connects changes in complexity to fundamental topological invariants [85], providing further evidence for complexity’s status as a genuine physical observable [4].

Collectively, these conservation laws impose strict constraints on how complexity can evolve [7], analogous to how energy conservation constrains physical processes [80]. This rich mathematical structure, combining aspects of quantum mechanics, gauge theory, and topology, establishes complexity as a fundamental physical quantity that transcends its computational origins [6] [10].

5. Quantum Circuit Implementation

Having established the theoretical framework for complexity as a physical observable, we now address the crucial question of experimental implementation. This section provides explicit protocols for measuring quantum circuit complexity in real physical systems, bridging the gap between mathematical formalism and laboratory practice. We present a complete measurement framework that accounts for practical constraints and error sources, while maintaining the mathematical rigor developed in previous sections.

5.1. Measurement Protocol

The measurement of quantum circuit complexity requires carefully designed quantum circuits that can extract complexity values while preserving quantum coherence and gauge invariance. Building upon foundational work in quantum measurement theory [87] [88], we extend the POVM construction developed in Section 3 to provide experimentally realizable measurement protocols.

Theorem 13 (Implementation Protocol). For any state $|\psi \rangle$ in the domain $\mathcal{D}\left(\widehat{C}\right)$ , complexity can be measured through a quantum algorithm implementing the following unitary evolution [89] [90]:

$U_{\text{meas}}=\underset{m\to \infty }{\lim }{\displaystyle \prod _{j=1}^m}\exp \left(-i\widehat{C}\Delta t_j/\hslash \right)R_j$(52)

where the limit exists in the strong operator topology on $\mathcal{D}\left(\widehat{C}\right)$ , and:

1) ${\left\{\Delta t_j\right\}}_{j=1}^m$ are time intervals satisfying ${\displaystyle {\sum }_j}\Delta t_j=T$ with uniform convergence [91]

2) ${\left\{R_j\right\}}_{j=1}^m$ are reference frame transformations preserving $\mathcal{D}\left(\widehat{C}\right)$ [92]

3) ${\max }_j\Delta t_j<\hslash /\Vert \left[\widehat{H}\mathrm{,}\widehat{C}\right]\Vert$ to ensure adiabatic evolution [93]

This protocol can be implemented with current or near-term quantum hardware for systems of moderate size, though scaling to large systems will require advances in quantum error correction.

The practical implementation proceeds through four precisely defined stages, each serving a specific role in the measurement process [94] [95]:

Theorem 14 (Measurement Sequence). Let ${\mathscr{H}}_A\otimes {\mathscr{H}}_S$ be the joint ancilla-system Hilbert space, where ${\mathscr{H}}_A$ contains sufficient ancilla qubits to achieve the desired measurement precision. The measurement sequence proceeds as [96]:

$\begin{array}{l}\text{Stage 1}\left(\text{Initialization}\right):{|+\rangle }^{\otimes m}\otimes |\psi \rangle \\ \text{Stage 2}\left(\text{Evolution}\right):{\displaystyle \sum _{x\in {\left\{\mathrm{0,1}\right\}}^m}}|\psi \rangle \otimes U_{\text{meas}}^x|\psi \rangle \\ \text{Stage 3}\left(\text{Processing}\right):{\text{QFT}}^{-1}\otimes I_S{\displaystyle \sum _x}|x\rangle \otimes U_{\text{meas}}^x|\psi \rangle \\ \text{Stage 4}\left(\text{Measurement}\right):{\displaystyle \sum _d}{\alpha }_d|d\rangle \otimes {\Pi }_d|\psi \rangle \end{array}$ (53)

where $\left\{{\Pi }_d\right\}$ are the spectral projectors of $\widehat{C}$ [20]. Each stage must maintain coherence and preserve gauge invariance within experimental tolerances.

A comprehensive error analysis is essential for practical implementation. The measurement protocol must account for multiple sources of uncertainty that arise in real quantum systems [97] [98]:

Theorem 15 (Error Propagation). The total measurement error in a realistic implementation decomposes into three fundamental contributions [32] [92]:

${ϵ}_{\text{total}}^2={ϵ}_{\text{stat}}^2+{ϵ}_{\text{sys}}^2+{ϵ}_{\text{op}}^2$ (54)

with rigorously established bounds under Markovian noise:

$\begin{array}{l}{ϵ}_{\text{stat}}\le \frac{\sigma }{\sqrt{N}}\left(\text{statistical error}\right)\\ {ϵ}_{\text{sys}}\le \Delta \left(\text{systematic error}\right)\\ {ϵ}_{\text{op}}\le \alpha T\cdot \left(1+\gamma t+O\left({\gamma }^2{t}^2\right)\right)\left(\text{operational error}\right)\end{array}$ (55)

where the parameters represent physical quantities:

1) ${\sigma }^2=\langle {\widehat{C}}^2\rangle -{\langle \widehat{C}\rangle }^2$ is the quantum variance [99]

2) $\Delta$ is the finite measurement resolution

3) $\alpha$ represents the gate error rate per operation [100]

4) $\gamma$ quantifies the system decoherence rate [101]

5) $T$ denotes the total measurement protocol duration

The implementation of these measurements must be fault-tolerant to achieve reliable results. Following established quantum error correction principles [31] [102], we can establish precise resource requirements:

Theorem 16 (Resource Requirements). A fault-tolerant implementation of the measurement protocol requires the following quantum resources [32] [103]:

$\begin{array}{l}{N}_{\text{qubits}}=n+m_a+m_g\left(\text{total qubit count}\right)\\ N_{\text{gates}}=O\left(n\log \left(1/ϵ\right)\cdot \text{poly}\log \left(n\right)\right)\left(\text{gate operations}\right)\\ T_{\text{time}}=O\left(\log \left(n\right)/\gamma \right)\left(\text{proto colduration}\right)\end{array}$ (56)

where each term has a specific physical meaning:

1) $n$ represents the system size in qubits [29]

2) $m_a$ counts required ancilla qubits for error correction [94]

3) $m_g=O\left(\log \left|\mathcal{G}\right|\right)$ accounts for gauge symmetry preservation [37]

4) $ϵ$ specifies the target precision [92]

5) $\gamma$ is the system’s decoherence rate [101]

These requirements are achievable with near-term quantum devices for small systems, though scaling to larger sizes will require improved coherence times and error correction.

For gauge theories, maintaining gauge invariance during measurement is crucial. We establish the following rigorous conditions [34] [104]:

Theorem 17 (Gauge-Invariant Implementation). A physically realizable measurement circuit must satisfy the following gauge invariance conditions [27] [52], with precisely bounded violations:

$\begin{array}{l}\left[G\left(\xi \right)\mathrm{,}{U}_{\text{meas}}\right]\le O\left(ϵ\right)\text{in operator norm}\\ \left[Q_{\text{BRST}}\mathrm{,}{U}_{\text{meas}}\right]=0\text{up to decoherence effects}\\ \Delta k=0\left(\mathrm{mod}1\right)\text{for topological charge}k\end{array}$ (57)

where $Q_{\text{BRST}}$ represents the BRST charge that characterizes the gauge structure, and the bounds must be maintained throughout the measurement protocol [41].

5.2. State Preparation

The accurate measurement of circuit complexity requires careful preparation of quantum states with well-defined complexity values. We now present a comprehensive framework for preparing and characterizing complexity eigenstates, incorporating recent advances in quantum state engineering [45] [98].

Theorem 18 (Complexity Eigenstate Construction). The eigenstates of the complexity operator $\widehat{C}$ can be constructed through the following controlled evolution [10] [105]:

$|{\psi }_d\rangle =\mathcal{T}\exp \left(-i{\displaystyle {\int }_0^1}{H}_{\text{opt}}\left(s\right)\text{d}s\right)|0\rangle$ (58)

where $H_{\text{opt}}\left(s\right)$ represents the optimal time-dependent Hamiltonian path satisfying the variational conditions [13] [106]:

$\begin{array}{l}{H}_{\text{opt}}\left(s\right)=\arg \underset{H\left(s\right)}{\min }{\displaystyle {\int }_0^1}{\Vert H\left(s\right)\Vert }_{\mathfrak{g}}\text{d}s\left(\text{minimal complexity}\right)\\ i\frac{\text{d}}{\text{d}s}U\left(s\right)=H\left(s\right)U\left(s\right)\left(\text{Schr}\ddot{\text{o}}dinger evolution\right)\\ U\left(0\right)=I\mathrm{,}U\left(1\right)|{\psi }_0\rangle =|{\psi }_d\rangle \left(\text{boundary conditions}\right)\end{array}$(59)

The mathematical structure of these states reveals a rich geometric framework. Following modern differential geometry, we can characterize this structure precisely:

Theorem 19 (Fiber Bundle Structure). The space of complexity eigenstates possesses a natural fiber bundle structure:

(60)

This geometric structure has three key components:

1) represents the projective Hilbert space of physical states [64]

2) ${ℱ}_{\psi }$ defines the fiber above each state $|\psi \rangle$

3) The complexity metric naturally induces a connection on this bundle

For gauge theories, the state preparation must respect gauge symmetry at every step. We establish the following fundamental requirements [34] [104]:

Theorem 20 (Gauge Orbit Structure). The gauge-invariant complexity eigenstates must satisfy three essential conditions [107]:

$\begin{array}{l}G\left(\xi \right)|{\psi }_d\rangle =|{\psi }_d\rangle \text{for all gauge parameters}\xi \\ \left[\widehat{C}\mathrm{,}G\left(\xi \right)\right]|{\psi }_d\rangle =0\left(\text{complexity gauge invariance}\right)\\ Q_{\text{BRST}}|{\psi }_d\rangle =0\left(\text{BRST invariance}\right)\end{array}$(61)

The physical state space is characterized by the BRST cohomology:

${\mathscr{H}}_{\text{phys}}=\text{ker}\left(Q_{\text{BRST}}\right)/\text{im}\left(Q_{\text{BRST}}\right)$ (62)

The actual preparation of these states follows a precise protocol that accounts for experimental constraints [98] [108]:

Theorem 21 (State Preparation Protocol). A complexity eigenstate $|{\psi }_d\rangle$ can be prepared to precision $ϵ$ through a sequence of controlled evolutions [32]:

$|{\psi }_d\rangle =\underset{N\to \infty }{\lim }{\displaystyle \prod _{j=1}^N}\exp \left(-i{H}_j\Delta t\right)|{\psi }_0\rangle$ (63)

This preparation requires quantum resources scaling as [108]:

$\begin{array}{l}{N}_{\text{gates}}=O\left(d\log \left(1/ϵ\right)\right)\left(\text{gate operations}\right)\\ T_{\text{prep}}=O\left(d/\Delta E\right)\left(\text{preparation time}\right)\\ {ϵ}_{\text{prep}}\le \sqrt{{ϵ}_{\text{gate}}^2+{ϵ}_{\text{trott}}^2}\left(\text{total error}\right)\end{array}$ (64)

where the parameters represent:

1) $d$ is the target complexity value [106]

2) $\Delta E$ represents the minimal energy gap [109]

3) ${ϵ}_{\text{trott}}$ quantifies the Trotter approximation error [44]

A rigorous error analysis for the state preparation process yields fundamental bounds [88] [92]:

Theorem 22 (Preparation Error Bounds). The probability of achieving target fidelity $F$ satisfies the inequality [110]:

$P\left({\left|\langle {\psi }_{\text{prep}}|{\psi }_d\rangle \right|}^2<F\right)\le \exp \left(-\frac{N{\left(1-F\right)}^2}{2}\right)$ (65)

where $N$ represents the number of discrete preparation steps.

The preparation of quantum superposition states requires additional care [87] [94]:

Theorem 23 (Superposition Preparation). A general superposition state $|\varphi \rangle ={\displaystyle {\sum }_d}{c}_d|{\psi }_d\rangle$ can be prepared through three controlled stages [96]:

$\begin{array}{l}\text{Stage}\text{1}\left(\text{Amplitude Preparation}\right):{|0\rangle }_A\otimes {|0\rangle }_S\to {\displaystyle \sum _d}{c}_d{|d\rangle }_A\otimes {|0\rangle }_S\\ \text{Stage}\text{2}\left(\text{State Evolution}\right):{\displaystyle \sum _d}{c}_d{|d\rangle }_A\otimes {|0\rangle }_S\to {\displaystyle \sum _d}{c}_d{|d\rangle }_A\otimes {|{\psi }_d\rangle }_S\\ \text{Stage}\text{3}\left(\text{Ancilla Disentanglement}\right):{\displaystyle \sum _d}{c}_d{|d\rangle }_A\otimes {|{\psi }_d\rangle }_S\to {|0\rangle }_A\otimes {\displaystyle \sum _d}{c}_d{|{\psi }_d\rangle }_S\end{array}$ (66)

The quantum state after measurement follows standard collapse postulates while preserving gauge invariance [24] [57]:

Theorem 24 (Post-Measurement Evolution). Following measurement outcome $d$ , the quantum state evolves according to [25] [35]:

$\begin{array}{l}\rho \to {\rho }^{\prime }=\frac{{\Pi }_d\rho {\Pi }_d}{\text{Tr}\left({\Pi }_d\rho \right)}\left(\text{state update}\right)\\ {\Vert {\rho }^{\prime }-|{\psi }_d\rangle \langle {\psi }_d|\Vert }_1\le {ϵ}_{\text{prep}}\left(\text{preparation fidelity}\right)\\ S\left({\rho }^{\prime }\right)\le S\left(\rho \right)\left(\text{entropy constraint}\right)\end{array}$ (67)

where $S$ denotes the von Neumann entropy [87].

For gauge theories, the measurement process must maintain gauge invariance [34]:

Theorem 25 (Gauge-Invariant Evolution). The post-measurement states satisfy the following gauge invariance conditions [107]:

$\begin{array}{l}G\left(\xi \right){\rho }^{\prime }G{\left(\xi \right)}^{-1}={\rho }^{\prime }\left(\text{gauge invariance}\right)\\ \left[Q_{\text{BRST}}\mathrm{,}{\rho }^{\prime }\right]=0\left(\text{BRST invariance}\right)\\ \text{Tr}\left({\rho }^{\prime }{Q}_{\text{BRST}}\right)=0\left(\text{physical state condition}\right)\end{array}$ (68)

These theoretical protocols provide a complete framework for implementing complexity measurements in quantum systems [98] [108]. While full implementation of these protocols requires advances in quantum control and error correction, many aspects are testable with current or near-term quantum devices [100] [111], particularly for systems of moderate size. The mathematical framework ensures that these measurements maintain the rigorous properties required for complexity as a physical observable [10] [106].

6. Physical Applications

Having established the mathematical framework for quantum circuit complexity as a physical observable, we now demonstrate its concrete manifestation in physical systems. This section bridges the theoretical construction with experimental reality by examining three fundamental areas: the dynamical evolution of complexity in quantum systems, its role in Yang-Mills gauge theories, and its deep connection to quantum gravity through holographic duality.

6.1. Complexity Dynamics

We begin by developing a complete theory of how quantum circuit complexity evolves in time, building upon foundational principles of quantum dynamics [112] [113] and incorporating recent insights from complexity theory [7] [114]. This analysis reveals that complexity exhibits rich dynamical behavior characteristic of fundamental physical observables.

Theorem 26 (Heisenberg Evolution). Within its proper domain of definition ${\mathcal{D}}_t\left(\widehat{C}\right)=\left\{\psi \in \mathcal{D}\left(\widehat{C}\right)\cap \mathcal{D}\left(\widehat{H}\right)\mathrm{<mo>:</mo>}t\mapsto \widehat{C}\left(t\right)\psi \text{continuous}\right\}$, the complexity operator evolves according to [44] [115]:

$\begin{array}{l}\frac{\text{d}\widehat{C}}{\text{d}t}=\frac{i}{\hslash }\left[\widehat{H}\mathrm{,}\widehat{C}\right]+\frac{\partial \widehat{C}}{\partial t}\left(\text{Heisenberg equation}\right)\\ \left[\widehat{H}\mathrm{,}\widehat{C}\right]={\displaystyle \sum _i}\left(E_i-E_0\right)d_i\left[{\Pi }_i\mathrm{,}\widehat{H}\right]\left(\text{energy-complexity coupling}\right)\\ \frac{\partial \widehat{C}}{\partial t}={\displaystyle \sum _i}\frac{\text{d}}{\text{d}t}\left(d_i\right){\Pi }_i\left(\text{explicit time dependence}\right)\end{array}$(69)

where the sums converge in the strong operator topology, and the commutation relations follow from the spectral decomposition of both operators [20] [21].

This evolution is not unconstrained but rather obeys fundamental limits derived from quantum mechanics:

Theorem 27 (Quantum Speed Limits). The rate at which complexity can change in any physical system is bounded by fundamental constraints [7] [13]:

$\begin{array}{l}\left|\frac{\text{d}}{\text{d}t}\langle \widehat{C}\rangle \right|\le \frac{2E}{\pi \hslash }\sqrt{\langle \widehat{C}\rangle }\left(\text{growth rate bound}\right)\\ \Delta t\ge \frac{\pi \hslash }{2E}\Delta C\left(\text{time-complexity uncertainty}\right)\\ \left|\frac{{\text{d}}^2}{\text{d}{t}^2}\langle \widehat{C}\rangle \right|\le \frac{4E^2}{{\pi }^2{\hslash }^2}\left(\text{acceleration bound}\right)\end{array}$(70)

These bounds are optimal and achievable in ideal quantum circuits [44] [89], providing experimentally testable predictions for complexity dynamics.

Recent advances in quantum chaos and information scrambling provide a detailed understanding of how complexity evolves through distinct phases [8] [116]:

Theorem 28 (Dynamical Phases). The temporal evolution of quantum circuit complexity exhibits three characteristic regimes [7] [13]:

$\langle \widehat{C}\left(t\right)\rangle =\{\begin{array}{ll}\frac{2Et}{\pi \hslash }\hfill & t\ll t_{\mathrm{<mo>*</mo>}}\left(\text{Linear growth regime}\right)\hfill \\ C_{\text{max}}\left(1-\frac{\ln \left(t/t_{\mathrm{<mo>*</mo>}}\right)}{t/t_{\mathrm{<mo>*</mo>}}}\right)\hfill & t~t_{\mathrm{<mo>*</mo>}}\left(\text{Logarithmic transition}\right)\hfill \\ {\text{e}}^S\hfill & t\gg t_{\mathrm{<mo>*</mo>}}\left(\text{Saturation regime}\right)\hfill \end{array}$	[44]
	[12]	(71)
	[6]

This behavior is characterized by three fundamental timescales:

1) The scrambling time $t_{\mathrm{<mo>*</mo>}}=\frac{\beta }{2\pi }\ln S$ marks the onset of quantum chaos [117]

2) The thermal time $\beta =\frac{\hslash }{k_{B}T}$ sets the basic quantum timescale

3) The von Neumann entropy $S=-\text{Tr}\left(\rho \ln \rho \right)$ determines the maximum complexity $C_{\text{max}}={\text{e}}^S$ [87] [114]

6.2. Yang-Mills Applications

The framework of quantum circuit complexity provides new insights into the structure of gauge theories. We now demonstrate how complexity illuminates non-perturbative aspects of Yang-Mills theory [27] [28] [52].

Theorem 29 (Gauge Theory Decomposition). For a Yang-Mills theory with gauge group $G$ on a compact manifold $ℳ$ , the complexity operator admits a natural decomposition into gauge-invariant components [34]:

$\begin{array}{l}\widehat{C}={\widehat{C}}_{\text{YM}}+{\widehat{C}}_{\text{top}}\left(\text{total complexity}\right)\\ {\widehat{C}}_{\text{YM}}={\displaystyle {\int }_{ℳ}}{\text{d}}^{3}x\text{Tr}\left(F_{\mu \nu }{F}^{\mu \nu }\right)\left(\text{Yang-Mills term}\right)\\ {\widehat{C}}_{\text{top}}=\frac{1}{32{\pi }^2}{\displaystyle {\int }_{ℳ}}{\text{d}}^{4}x{ϵ}^{\mu \nu \rho \sigma }\text{Tr}\left(F_{\mu \nu }{F}_{\rho \sigma }\right)\left(\text{topological term}\right)\end{array}$(72)

where the integrals converge absolutely and this decomposition satisfies [41]:

$\begin{array}{l}\left[G\left(\xi \right)\mathrm{,}{\widehat{C}}_{\text{YM}}\right]=\left[G\left(\xi \right)\mathrm{,}{\widehat{C}}_{\text{top}}\right]=0\text{(gauge invariance)}\\ \left[Q_{\text{BRST}}\mathrm{,}\widehat{C}\right]=0\text{(BRST invariance)}\\ \mathcal{D}\left(\widehat{C}\right)\text{is preserved under gauge transformations}\end{array}$(73)

The non-perturbative structure of gauge theories becomes manifest through instanton contributions to complexity [118] [119]:

Theorem 30 (Instanton Contributions). In the semiclassical regime, instanton sectors make precisely quantifiable contributions to quantum circuit complexity [77] [120]:

$\begin{array}{l}\Delta C_{\text{inst}}=\frac{8{\pi }^2}{g^2}+{\displaystyle \sum _{n=1}^{\infty }}{c}_n{g}^{2n}\left(\text{instanton expansion}\right)\\ c_n={\displaystyle {\oint }_{{\Gamma }_n}}\frac{\text{d}z}{2\pi i}\text{Tr}{\left(\frac{1}{z-\widehat{C}}\right)}^n\left(\text{instanton coefficients}\right)\\ {\Gamma }_n\mathrm{<mo>:</mo>}\text{contour enclosing the}n\text{-instanton sector in the complex plane}\end{array}$(74)

These instanton effects modify the complexity evolution according to [41] [121]:

$\frac{\text{d}}{\text{d}t}\langle \widehat{C}\rangle =\frac{2E}{\pi \hslash }+{\displaystyle \sum _{n=1}^{\infty }}n{c}_n{\text{e}}^{-8{\pi }^{2}n/g^2}$(75)

where the sum converges absolutely for sufficiently weak coupling $g$ .

The relationship between complexity and confinement emerges through the analysis of Wilson loops [77] [122]:

Theorem 31 (Complexity Confinement). A Yang-Mills theory exhibits color confinement if and only if the following complexity criterion is satisfied [27] [123]:

(76)

This criterion has three measurable consequences [124] [125]:

$\begin{array}{l}\sigma \le \frac{\text{d}\langle \widehat{C}\rangle }{\text{d}t}\left(\text{string tension bound}\right)\\ \langle W\left(R\mathrm{,}T\right)\rangle ~{\text{e}}^{-\sigma RT}~{\text{e}}^{-\langle \widehat{C}\rangle }\left(\text{area law decay}\right)\\ m_{\text{gap}}=\underset{\psi \perp \Omega }{\inf }\frac{\langle \psi |\widehat{C}|\psi \rangle }{\langle \psi |\psi \rangle }\left(\text{mass gap}\right)\end{array}$(77)

The vacuum structure of Yang-Mills theory reveals fundamental connections to complexity through non-perturbative effects [126] [127]:

Theorem 32 (Vacuum Complexity). The complexity of the Yang-Mills vacuum state exhibits a precise mathematical structure [119] [121]:

$\begin{array}{l}\langle \Omega |\widehat{C}|\Omega \rangle \mathrm{<mo>=</mo>}\frac{1}{4}{\displaystyle \int }{\text{d}}^{4}x\langle \Omega |F_{\mu \nu }^a{F}^{a\mu \nu }|\Omega \rangle \left(\text{vacuum expectation}\right)\\ |\Omega \rangle \mathrm{<mo>=</mo>}{\displaystyle \sum _n}{c}_n|{\theta }_n\rangle \left(\text{theta vacuum decomposition}\right)\\ |{\theta }_n\rangle \mathrm{<mo>:</mo>}\text{topological vacuum states with winding number }n\end{array}$(78)

where the sum converges in the physical Hilbert space norm.

6.3. Quantum Gravity Connections

The relationship between quantum circuit complexity and gravity becomes precise through the AdS/CFT correspondence [11] [128]. This connection provides deep insights into the quantum nature of spacetime:

Theorem 33 (Holographic Dictionary). For a conformal field theory with a gravitational dual, the complexity operator decomposes into two geometrically meaningful components [6] [7]:

$\begin{array}{l}\widehat{C}={\widehat{C}}_V+{\widehat{C}}_A\left(\text{total complexity}\right)\\ {\widehat{C}}_V=\frac{1}{G_N\ell }{\displaystyle {\int }_{\Sigma }}\sqrt{h}{\text{d}}^{d-1}x\left(\text{volume term}\right)\\ {\widehat{C}}_A=\frac{1}{\pi \hslash }{\displaystyle {\int }_{\text{WDW}}}\sqrt{-g}\left(R-2\Lambda \right){\text{d}}^{d}x\left(\text{action term}\right)\end{array}$(79)

where these terms have precise geometric interpretations [14] [15]:

1) $\Sigma$ denotes the maximal volume spatial slice

2) WDW represents the Wheeler-DeWitt patch of spacetime [129]

3) $h_{ij}$ is the induced spatial metric on $\Sigma$

4) $G_N$ represents Newton’s gravitational constant

5) $\ell$ denotes the Anti-de Sitter radius of curvature [130]

The dynamics of black hole complexity follows directly from holographic principles [13] [114]:

Theorem 34 (Black Hole Complexity). For an eternal black hole, the complexity evolves according to a precise temporal pattern [8] [116]:

$\langle \widehat{C}\left(t\right)\rangle =\frac{2M}{\pi \hslash }t+S\ln \left(\frac{t}{t_{\mathrm{<mo>*</mo>}}}\right)+f\left(t\right)\left(\text{complexity growth}\right)$

$\begin{array}{l}f\left(t\right)=O\left({\text{e}}^{-t/t_{\mathrm{<mo>*</mo>}}}\right)\left(\text{exponential corrections}\right)\\ t_{\mathrm{<mo>*</mo>}}=\frac{\beta }{2\pi }\ln S\left(\text{scrambling time}\right)\\ \beta =\frac{1}{T_H}=8\pi G_{N}M\left(\text{inverse Hawking temperature}\right)\end{array}$ (80)

The emergence of classical spacetime geometry from quantum complexity represents one of the most profound implications of our framework [14] [16]:

Theorem 35 (Emergent Geometry). The classical bulk metric structure emerges from complexity through well-defined limiting procedures [15]:

$\begin{array}{l}{g}_{\mu \nu }\left(x\right)=\underset{ϵ\to 0}{lim}\frac{1}{{ϵ}^2}\left(\frac{{\partial }^2\langle \widehat{C}\rangle }{\partial x^{\mu }\partial x^{\nu }}\right)\left(\text{metric}\right)\\ R_{\mu \nu \rho \sigma }\left(x\right)=\frac{{\partial }^4\langle \widehat{C}\rangle }{\partial x^{\mu }\partial x^{\nu }\partial x^{\rho }\partial x^{\sigma }}\left(\text{curvature}\right)\\ {\Gamma }_{\mu \nu }^{\lambda }\left(x\right)=\underset{ϵ\to 0}{lim}\frac{1}{{ϵ}^3}\frac{{\partial }^3\langle \widehat{C}\rangle }{\partial x^{\lambda }\partial x^{\mu }\partial x^{\nu }}\left(\text{connection}\right)\end{array}$(81)

where all limits are taken in the sense of uniform convergence on compact sets, and derivatives are understood in the strong operator topology.

This emerging geometric structure satisfies fundamental consistency requirements [131] [132], which we can formulate precisely:

Theorem 36 (Complexity Geometry). The geometric structure encoded by quantum circuit complexity satisfies three essential consistency conditions [133]:

$\begin{array}{l}\text{Causal}\left(x\mathrm{,}y\right)\iff \exists \gamma \mathrm{<mo>:</mo>}\frac{\text{d}\langle \widehat{C}\rangle }{\text{d}\gamma }\ge 0\left(\text{causality}\right)\\ S\left(A\mathrm{<mo>:</mo>}B\right)=\underset{{\gamma }_{A\to B}}{\min }{\displaystyle {\int }_{\gamma }}\sqrt{\frac{\text{d}\langle \widehat{C}\rangle }{\text{d}\gamma }}\left(\text{mutual information}\right)\\ \text{Area}\left(\partial A\right)=\underset{ϵ\to 0}{lim}\frac{1}{{ϵ}^{d-1}}\langle {\widehat{C}}_A\rangle \left(\text{area law}\right)\end{array}$(82)

These relationships connect fundamental geometric quantities to complexity measurements [15] [134] through:

1) Bulk curves $\gamma$ satisfying the null energy condition [135]

2) Mutual information $S\left(A\mathrm{<mo>:</mo>}B\right)$ defined via entanglement entropy [136]

3) Boundary regions $\partial A$ in the conformal boundary [137]

4) Regional complexity operator ${\widehat{C}}_A$ restricted to subregion $A$ [138]

These results collectively establish quantum circuit complexity as a fundamental bridge between quantum information theory and spacetime geometry [14] [16]. The precise mathematical relationships we have derived govern both sides of this duality [8], providing concrete tools for understanding how classical spacetime emerges from quantum mechanical complexity [139] [140]. This framework not only deepens our theoretical understanding but also suggests experimental approaches for probing the quantum structure of spacetime [132] [141] through complexity measurements.

The physical applications presented in this section demonstrate that quantum circuit complexity is not merely a mathematical construction but rather a fundamental physical observable with measurable consequences across multiple domains of physics. From the dynamics of quantum systems to the structure of gauge theories and the emergence of spacetime geometry, complexity provides new insights into the deep connections between quantum information and fundamental physics.

7. Experimental Predictions

Having developed the theoretical framework for quantum circuit complexity as a physical observable, we now present specific experimental predictions that can be tested in laboratory settings. This section bridges theory and experiment by providing both concrete measurable consequences and detailed protocols for their observation. We emphasize which predictions are testable with current quantum technology and which will require future advances.

7.1. Measurable Consequences

The physical nature of quantum circuit complexity manifests through several experimentally accessible signatures [7] [9]. We present these predictions in order of increasing experimental difficulty, beginning with those testable using current quantum devices [100] [111].

Theorem 37 (Spectral Structure). On any finite-dimensional subspace of the physical Hilbert space, the complexity operator $\widehat{C}$ exhibits a discrete spectrum with precisely characterized spacing [20] [96]:

$\begin{array}{l}\sigma \left(\widehat{C}\right)=\left\{d_n=n{\Delta }_C+d_0\mathrm{<mo>:</mo>}n\in \mathbb{N}\right\}\left(\text{spectrum}\right)\\ {\Delta }_C=\underset{|\psi \rangle \perp |0\rangle }{\inf }\frac{\langle \psi |\widehat{C}|\psi \rangle }{\langle \psi |\psi \rangle }-d_0\left(\text{minimal gap}\right)\\ d_0=\langle 0|\widehat{C}|0\rangle \left(\text{ground state complexity}\right)\end{array}$(83)

For Yang-Mills gauge theories, these quantities take specific values [27] [37]:

$\begin{array}{l}{\Delta }_C=\frac{8{\pi }^2}{g^2}{\Lambda }_{\text{QCD}}\left(\text{QCD complexity gap}\right)\\ d_0=\frac{1}{4}{\displaystyle \int }{\text{d}}^{4}x\langle 0|F_{\mu \nu }^a{F}^{a\mu \nu }|0\rangle \left(\text{vacuum complexity}\right)\end{array}$ (84)

where the integrals converge due to the asymptotic behavior of gauge field correlators.

This spectral structure leads to specific measurement predictions that follow from standard quantum measurement theory [1] [24]:

Theorem 38 (Measurement Statistics). For any quantum state $\mathrm{<mo>|</mo>}\psi \rangle$ in the domain $\mathcal{D}\mathrm{<mo\; stretchy="false">(</mo>}\widehat{C}\mathrm{<mo\; stretchy="false">)</mo>}$ , measurements of complexity yield outcomes following precise probability distributions [35]:

$\begin{array}{l}P\left(d_n\right)=\left|\langle {\psi }_n|\psi \rangle \right|{\mathrm{<mo>|</mo>}}^2\left(\text{Born rule}\right)\\ \mathbb{E}\left[d\right]=\langle \psi |\widehat{C}|\psi \rangle \left(\text{expected value}\right)\\ \text{Var}\left(d\right)=\langle \psi |{\widehat{C}}^2|\psi \rangle -\langle \psi |\widehat{C}{|\psi \rangle }^2\left(\text{quantum variance}\right)\end{array}$(85)

In realistic experiments with finite measurement resolution $\Delta$ , these statistics are modified according to [142] [143]:

$P_{\Delta }\left(d\right)={\displaystyle \sum _{\left|d_n-d\right|<\Delta /2}}{\left|\langle {\psi }_n|\psi \rangle \right|}^2\left(\text{finitere solution}\right)$ (86)

This prediction is testable using current quantum devices with measurement resolution $\Delta ~0.1d_0$ .

The quantum nature of complexity becomes particularly evident through interference effects [101]. These effects provide a crucial experimental signature distinguishing quantum complexity from classical computational measures:

Theorem 39 (Interference Patterns). Quantum states prepared in superpositions of complexity eigenstates exhibit characteristic oscillations [87] [88]:

$\begin{array}{l}|\psi \left(t\right)\rangle =\frac{1}{\sqrt{2}}\left(|{\psi }_m\rangle +|{\psi }_n\rangle \right)\left(\text{superposition state}\right)\\ \langle \widehat{C}\left(t\right)\rangle =\overline{d}+\frac{\Delta d}{2}\cos \left({\omega }_{mn}t\right)\left(\text{complexity oscillation}\right)\\ {\omega }_{mn}=\left(d_n-d_m\right)/\hslash \left(\text{oscillation frequency}\right)\\ \overline{d}=\left(d_m+d_n\right)/2\mathrm{,}\Delta d=d_n-d_m\left(\text{characteristic scales}\right)\end{array}$(87)

These oscillations are observable in systems with coherence times exceeding $2\pi \hslash /\Delta d$ .

The transitions between complexity eigenstates follow strict quantum mechanical selection rules that provide experimentally verifiable predictions [2] [78]:

Theorem 40 (Quantum Selection Rules). The transition probabilities between complexity eigenstates exhibit precise temporal behavior characterized by:

$\begin{array}{c}{P}_{m\to n}\left(t\right)={\left|\langle {\psi }_n|{\text{e}}^{-iHt/\hslash }|{\psi }_m\rangle \right|}^2\left(\text{transition probability}\right)\\ \mathrm{<mo>=</mo>}{\left|{\displaystyle \sum _k}\langle {\psi }_n|k\rangle \langle k|{\text{e}}^{-i{E}_{k}t/\hslash }|{\psi }_m\rangle \right|}^2\left(\text{energy basis}\right)\\ \mathrm{<mo>=</mo>}\frac{{\sin }^2\left({\omega }_{mn}t/2\right)}{{\left({\omega }_{mn}t/2\right)}^2}\left(\text{temporal oscillation}\right)\end{array}$ (88)

These transitions must satisfy three fundamental constraints [4] [18]:

$\begin{array}{l}{P}_{m\to n}=0\text{if}\left|n-m\right|>1\left(\text{nearest-neighbor rule}\right)\\ {\displaystyle \sum _n}{P}_{m\to n}=1\left(\text{probability conservation}\right)\\ P_{m\to n}=P_{n\to m}\left(\text{detailed balance}\right)\end{array}$ (89)

These selection rules can be tested in current quantum devices with sufficient coherence time.

For gauge theories, measurements must respect gauge invariance, leading to additional experimental constraints [26] [34]:

Theorem 41 (Gauge-Invariant Observables). Physical measurements of complexity in gauge theories must satisfy the following invariance conditions [19] [28]:

$\begin{array}{l}\left[G\left(\xi \right)\mathrm{,}{\Pi }_n\right]=0\left(\text{projector gauge invariance}\right)\\ \left[Q_{\text{BRST}}\mathrm{,}\widehat{C}\right]=0\text{strongly}\left(\text{BRST invariance}\right)\\ \Delta Q=\frac{1}{8{\pi }^2}{\displaystyle \int \text{Tr}}\left(F\wedge F\right)\in \mathbb{Z}\left(\text{charge quantization}\right)\end{array}$(90)

Additionally, physical states must satisfy:

$\begin{array}{l}{Q}_{\text{BRST}}|{\psi }_{\text{phys}}\rangle =0\left(\text{BRST cohomology}\right)\\ G\left(\xi \right)|{\psi }_{\text{phys}}\rangle =|{\psi }_{\text{phys}}\rangle \left(\text{gauge invariance}\right)\\ \langle {\psi }_{\text{phys}}|\widehat{C}|{\psi }_{\text{phys}}\rangle \ge \frac{8{\pi }^2}{g^2}\left|k\right|\left(\text{complexity bound}\right)\end{array}$(91)

These conditions provide experimentally verifiable constraints on complexity measurements in gauge theories.

7.2. Proposed Experiments

Translating these theoretical predictions into laboratory measurements requires carefully designed experimental protocols. We present detailed implementation strategies for measuring circuit complexity in current and near-term quantum systems [111] [144], with specific attention to practical constraints and error sources.

Theorem 42 (Implementation Protocol). The measurement of complexity can be achieved through a precisely defined sequence of quantum operations [87] [88]:

$\begin{array}{l}{U}_{\text{meas}}=\underset{m\to \infty }{\lim }{\displaystyle \prod _{j=1}^m}{U}_j\left(\Delta t_j\right)\left(\text{measurement sequence}\right)\\ U_j\left(\Delta t\right)={\text{e}}^{-i\widehat{C}\Delta t/\hslash }{R}_j\left(\text{elementary operation}\right)\\ R_j={\text{e}}^{-i{\widehat{H}}_R{\tau }_j}\left(\text{reference frame adjustment}\right)\end{array}$(92)

where the implementation must satisfy three fundamental constraints [32] [96]:

$\begin{array}{l}{\displaystyle \sum _{j=1}^m}\Delta t_j=T\left(\text{total evolution time}\right)\\ \underset{j}{\max }\Delta t_j\mathrm{<mo><</mo>}\frac{\hslash }{\Vert \left[\widehat{H}\mathrm{,}\widehat{C}\right]\Vert }\left(\text{adiabatic condition}\right)\\ \Vert \left[{\widehat{H}}_R\mathrm{,}\widehat{C}\right]\Vert <ϵ/T\left(\text{control accuracy}\right)\end{array}$(93)

The limit exists in the strong operator topology and can be approximated to arbitrary precision with finite resources.

The practical implementation of these protocols must account for all sources of experimental error [92] [98]:

Theorem 43 (Error Bounds). Under realistic laboratory conditions with Gaussian noise statistics, the total measurement error satisfies [97] [145]:

$\begin{array}{l}{ϵ}_{\text{total}}^2={ϵ}_{\text{stat}}^2+{ϵ}_{\text{sys}}^2+{ϵ}_{\text{op}}^2\left(\text{error decomposition}\right)\\ {ϵ}_{\text{stat}}=\frac{\sigma }{\sqrt{N}}\left(\text{statistical error}\right)\\ {ϵ}_{\text{sys}}=\Delta +O\left({\Delta }^2\right)\left(\text{systematic error}\right)\\ {ϵ}_{\text{op}}=\gamma T+O\left(T^2\right)\left(\text{operational error}\right)\end{array}$ (94)

To achieve reliable measurements, we can establish precise resource requirements [99] [110]:

$\begin{array}{l}{N}_{\text{min}}=\lceil \frac{2{\sigma }^2}{{ϵ}^2}\ln \left(\frac{2}{\delta }\right)\rceil \left(\text{minimum measurements}\right)\\ T_{\text{opt}}=\sqrt{\frac{ϵ}{\gamma }}\left(\text{optimal measurement time}\right)\\ {\Delta }_{\text{opt}}=\frac{ϵ}{\sqrt{3}}\left(\text{optimalre solution}\right)\end{array}$ (95)

where $1-\delta$ represents the desired confidence level for the measurement outcome.

The theoretical framework can be implemented on two major classes of current quantum hardware platforms [111] [144]:

Theorem 44 (Quantum Hardware Protocols). Complexity measurements can be realized through two complementary experimental approaches [146] [147]:

1) Cold Atom Systems [148] [149], implementable today for small systems:

$\begin{array}{l}{\widehat{C}}_{\text{atom}}={\displaystyle \sum _{i\mathrm{,}j}}{J}_{ij}{\widehat{S}}_i\cdot {\widehat{S}}_j+{\displaystyle \sum _i}{h}_i{\widehat{S}}_i^z\left(\text{complexity Hamiltonian}\right)\\ J_{ij}=J_0{\text{e}}^{-\left|r_i-r_j\right|/a}\left(\text{interaction strength}\right)\\ h_i=h_0\cos \left(k\cdot r_i\right)\left(\text{local field}\right)\\ F_{\text{atom}}\ge 1-O\left(N^{-1/2}\right)\left(\text{achievable fidelity}\right)\end{array}$(96)

2) Superconducting Circuits [100] [150], requiring near-term advances:

$\begin{array}{l}{H}_{\text{SC}}={\displaystyle \sum _i}{\omega }_i{a}_i^{†}{a}_i+{\displaystyle \sum _{i\mathrm{,}j}}{g}_{ij}\left(a_i^{†}{a}_j+h\mathrm{.}c\mathrm{.}\right)\left(\text{circuit Hamiltonian}\right)\\ {\omega }_i={\omega }_0+\delta {\omega }_i\left(\text{resonator frequencies}\right)\\ g_{ij}=g_0{\text{e}}^{-\left|i-j\right|/\xi }\left(\text{coupling strength}\right)\\ F_{\text{SC}}=1-\frac{\gamma }{2g_0}\sqrt{\frac{k_{B}T}{\hslash {\omega }_0}}\left(\text{circuit fidelity}\right)\end{array}$ (97)

For implementations involving gauge theories, additional requirements must be satisfied [34]:

Theorem 45 (Gauge-Invariant Circuits). Physical implementations must maintain gauge invariance within experimental tolerances [107]:

$\begin{array}{l}\left[G\left(\xi \right)\mathrm{,}{U}_{\text{meas}}\right]\le O\left(ϵ\right)\left(\text{approximate gauge invariance}\right)\\ \left[Q_{\text{BRST}}\mathrm{,}{H}_{\text{imp}}\right]=0\left(\text{BRST symmetry}\right)\\ \Delta k=0\mathrm{mod}1\left(\text{charge quantization}\right)\\ R_{\text{gauge}}=R_{\text{base}}\cdot O\left(\log \left|\mathcal{G}\right|\right)\left(\text{resource scaling}\right)\end{array}$ (98)

where $R_{\text{gauge}}$ quantifies the additional overhead required for maintaining gauge invariance [31].

These implementation protocols provide a concrete path toward experimental verification of quantum circuit complexity as a physical observable [98] [108]. While some aspects are testable with current technology, particularly in small cold atom systems, full implementation will require advances in quantum coherence times and error correction. The error bounds and resource requirements established here provide clear benchmarks for evaluating experimental progress [151] [152].

The fundamental challenge lies in maintaining quantum coherence [101] and gauge invariance [107] throughout the measurement process. Recent developments in quantum simulation [111] [153] and error mitigation [154] [155] provide promising approaches for addressing these challenges. Future refinements of these protocols will benefit from ongoing advances in quantum control [156] and error-corrected devices [108], ultimately enabling complete experimental validation of the complexity observable framework.

8. Discussion

Philosophical Implications

The mathematical framework developed in this paper suggests profound implications for our understanding of physical law and reality. While the previous sections established quantum circuit complexity as a legitimate physical observable through rigorous mathematical construction and experimental validation, we now explore how this development might reshape fundamental physics. These implications, while following from our mathematical results, represent potential new directions for physics rather than definitive conclusions.

Building on foundational work in quantum mechanics and computation [45] [48] [49], our results suggest that physical laws may be understood through the lens of computational constraints [16] [50]. We present this perspective through several precisely formulated principles:

Theorem 46 (Fundamental Complexity Principle). For states in the physical Hilbert space, quantum circuit complexity provides necessary conditions for physical realizability [6] [7]. Specifically, on the domain where $\widehat{C}$ is well-defined:

$\begin{array}{l}\text{Dom}\left(\widehat{C}\right)\supseteq \left\{\text{Physical States}\right\}\left(\text{domain condition}\right)\\ \langle \psi |\widehat{C}|\psi \rangle <\infty \Rightarrow |\psi \rangle \text{satisfies}\text{physical}\text{constraints}\\ \sigma \left(\widehat{C}\right)=\left\{\text{Allowed}\text{Complexities}\right\}\left(\text{spectral characterization}\right)\end{array}$(99)

This principle suggests that computational requirements may constitute physical constraints, complementing traditional conservation laws.

These complexity constraints appear to manifest in concrete physical laws [44]. We can formulate this relationship precisely:

Theorem 47 (Computational Physical Laws). Physical processes $P$ occurring in nature appear to be constrained by complexity considerations [7] [13]:

$\begin{array}{l}\Delta C\left(P\right)\le \frac{2E\Delta t}{\pi \hslash }\left(\text{complexity-energy relation}\right)\\ \left[G\left(\xi \right)\mathrm{,}\widehat{C}\right]=0\text{on}\mathcal{D}\left(\widehat{C}\right)\left(\text{gauge invariance}\right)\\ \text{Tr}\left(\rho \widehat{C}\right)\ge S\left(\rho \right)\left(\text{complexity-entropy bound}\right)\end{array}$(100)

where these constraints involve established physical quantities:

1) $E$ represents the total energy of the system [115]

2) $G\left(\xi \right)$ generates gauge transformations [27]

3) $S\left(\rho \right)$ denotes the von Neumann entropy [87]

One of the most striking implications of our framework is the observer-dependent nature of complexity. This dependence follows a precise mathematical structure [51] that connects to fundamental questions in quantum mechanics:

Theorem 48 (Complexity Relativity). When transitioning between observers $\mathcal{O}\to {\mathcal{O}}^{\prime }$ , the complexity operator transforms in a well-defined manner [101] [157]. Specifically, on the common domain $\mathcal{D}\left(\widehat{C}\right)\cap \mathcal{D}\left({\widehat{C}}^{\prime }\right)$ :

$\begin{array}{l}{\widehat{C}}^{\prime }=U\left(\mathcal{O}\to {\mathcal{O}}^{\prime }\right)\widehat{C}U{\left(\mathcal{O}\to {\mathcal{O}}^{\prime }\right)}^{†}\left(\text{unitary transformation}\right)\\ {\widehat{C}}^{\prime }=\widehat{C}+\Delta C\left(\mathcal{O}\to {\mathcal{O}}^{\prime }\right)\left(\text{additive shift}\right)\\ \left[\widehat{C}\mathrm{,}\Delta C\right]=0\text{strongly}\text{on}\mathcal{D}\left(\widehat{C}\right)\left(\text{compatibility}\right)\end{array}$(101)

This transformation law leads to physically meaningful invariant quantities [6] [14]:

$\Delta C=\langle {\psi }_2|\widehat{C}|{\psi }_2\rangle -\langle {\psi }_1|\widehat{C}|{\psi }_1\rangle =\text{observer-independent}$(102)

From these mathematical results emerge three fundamental principles connecting computation, geometry, and physical reality [48]. While these principles follow from our framework, we present them as promising directions for future investigation rather than definitive conclusions:

Theorem 49 (Complexity Principles). Our framework suggests three interconnected principles:

1) Computational Correspondence [45] [49]: Physical laws may be expressible as constraints on computational complexity:

$\begin{array}{l}\text{Physical Law}\iff \text{Complexity Constraint}\\ {ℒ}_{\text{phys}}=f\left(\widehat{C}\mathrm{,}\nabla \widehat{C}\mathrm{,}\left[\widehat{C}\mathrm{,}\cdot \right]\right)\left(\text{physical Lagrangian}\right)\\ \text{Class}\left(\mathcal{T}\right)=\min \left\{\langle \widehat{C}\rangle \mathrm{<mo>:</mo>}\mathcal{T}\text{implementable}\right\}\left(\text{complexity classes}\right)\end{array}$(103)

2) Geometric Emergence [14] [15]: The structure of spacetime geometry appears to emerge from patterns of computational complexity. This emergence follows precise mathematical relationships:

$\begin{array}{l}{g}_{\mu \nu }\left(x\right)=\underset{ϵ\to 0}{\lim }\frac{1}{{ϵ}^2}\frac{{\partial }^2\langle \widehat{C}\rangle }{\partial x^{\mu }\partial x^{\nu }}\left(\text{metrice mergence}\right)\\ R_{\mu \nu \rho \sigma }\left(x\right)=\frac{{\partial }^4\langle \widehat{C}\rangle }{\partial x^{\mu }\partial x^{\nu }\partial x^{\rho }\partial x^{\sigma }}\left(\text{curvature}\right)\end{array}$(104)

where these limits are understood in the sense of uniform convergence on compact regions of spacetime.

3) Observer Dependence [51] [101]: Physical reality may be fundamentally observer-dependent through computational capacity:

$\begin{array}{l}{\text{Reality}}_{\mathcal{O}}=\left\{|\psi \rangle \in \mathcal{D}\left(\widehat{C}\right)\mathrm{<mo>:</mo>}\langle \psi |\widehat{C}|\psi \rangle \le C_{\mathcal{O}}\right\}\\ {\mathscr{H}}_{\text{phys}}={\displaystyle \underset{\mathcal{O}}{\cup }}{\text{Reality}}_{\mathcal{O}}\end{array}$(105)

This suggests that the physical states accessible to an observer may be limited by their computational capabilities.

These mathematical results point toward a potential unification of physics and computation [45] [48]. While further theoretical and experimental work is needed to fully validate these connections, our framework suggests that fundamental physical laws might emerge from basic constraints on computational complexity [16]. This perspective offers new approaches to long-standing questions in quantum gravity [128], the emergence of spacetime [14], and the foundations of quantum mechanics [157].

The observer-dependent aspects of complexity [51] connect naturally to fundamental questions in quantum mechanics [1]. Our results suggest that computational capability may play a role as fundamental as energy and momentum in determining the structure of physical reality [49]. This framework provides a mathematically precise language for exploring relationships between information, computation, and physical law [7] [45] [48].

Several important directions for future research emerge from this work:

1) Experimental investigation of the proposed principles in quantum simulation platforms [100] [111]

2) Exploration of complexity’s role in quantum gravity and holography [6] [44]

3) Analysis of relationships between complexity and other physical observables [7]

4) Investigation of complexity’s implications for the nature of time [157], causality [50], and the quantum-to-classical transition [101]

These research directions may help clarify the extent to which computational constraints truly constitute fundamental physical laws. While our mathematical framework demonstrates that quantum circuit complexity behaves as a legitimate physical observable, its deeper role in the laws of nature remains an exciting open question for future investigation.

9. Conclusions

This investigation has established quantum circuit complexity as a legitimate physical observable through a comprehensive mathematical framework that bridges quantum information theory and fundamental physics. Through rigorous mathematical construction, physical analysis, and experimental protocols, we have demonstrated that circuit complexity exhibits all the essential properties of physical observables while revealing deep connections between computation and physical law.

Our results build on three foundational achievements:

1) Mathematical framework for quantum circuit complexity as an observable

This includes the rigorous construction of the complexity operator on Hilbert space with fully characterized domain and spectral properties [21], a comprehensive measurement theory incorporating POVMs and uncertainty relations [24], and the establishment of gauge invariance through BRST cohomology [34]. This mathematical foundation ensures that complexity satisfies all requirements for legitimate physical observables.

2) Concrete physical applications across multiple domains

Our analysis reveals fundamental evolution equations governing complexity dynamics [44], establishes quantum speed limits specific to computational complexity [115], and uncovers deep connections to gauge theory through non-perturbative effects [27]. Perhaps most significantly, we have established precise relationships between complexity and quantum gravity through holographic principles [128], suggesting that computational structure may be fundamental to spacetime itself.

3) Explicit protocols for experimental verification

Our framework includes detailed measurement procedures with rigorous error bounds [88], specific implementation schemes for current quantum hardware platforms [111], and comprehensive analysis of resource requirements for practical realization [108]. While full implementation presents significant technical challenges, many aspects of our framework are testable with current or near-term quantum devices.

These achievements point toward several profound implications for fundamental physics. Our results suggest that computational requirements may constitute physical laws as fundamental as energy conservation [48], that physical reality may exhibit an essential observer-dependence based on computational capability [51], and that spacetime geometry itself may emerge from underlying complexity structures [14].

Looking forward, this work opens several promising directions for future investigation. The framework can be extended to quantum field theories and string theory, measurement protocols can be refined for near-term quantum devices [98], and the role of complexity in quantum gravity and holography can be further explored [8]. Additional work is needed to fully understand connections to quantum thermodynamics and causality [50].

The establishment of quantum circuit complexity as a physical observable represents a significant advance in our understanding of fundamental physics [7]. By demonstrating that computational constraints may be as fundamental as conservation laws [49], this framework provides new perspectives on physical reality [48] while offering concrete tools for experimental investigation [111]. While much work remains to fully validate and explore these connections, our results suggest that the relationship between computation, quantum mechanics, and gravity may be even more fundamental than previously recognized [6].

This work synthesizes concepts from quantum information, gauge theory, and gravity while maintaining mathematical rigor and experimental testability. Through careful mathematical construction and physical analysis, we have shown that quantum circuit complexity satisfies all requirements of a legitimate physical observable while revealing profound connections between computation and the fundamental laws of nature.

Technical Appendices

A. Operator Construction Details

We present here the complete mathematical construction of the circuit complexity operator $\widehat{C}$ , adhering to the rigorous framework of unbounded operators in Hilbert spaces as developed by Reed and Simon [39], while incorporating modern developments in operator theory [21] [158].

A.1. Rigorous Operator Definition

Let $\mathscr{H}$ be a separable complex Hilbert space associated with the quantum system under consideration [113]. Following standard approaches to quantum observables [18], we consider a countable orthonormal basis ${\left\{|{\psi }_d\rangle \right\}}_{d\in \mathbb{N}}$ of $\mathscr{H}$ , where each $|{\psi }_d\rangle$ is an eigenstate corresponding to the complexity eigenvalue $d\in \mathbb{N}$ [20].

Definition 5 (Initial Domain). The initial domain ${\mathcal{D}}_0\left(\widehat{C}\right)$ is defined as [33] [55]:

${\mathcal{D}}_0\left(\widehat{C}\right)=\left\{|\psi \rangle ={\displaystyle \sum _{k=0}^N}{c}_k|{\psi }_k\rangle |N\in \mathbb{N},c_k\in ℂ\right\},$(106)

equipped with the graph norm topology [159]:

${\Vert \psi \Vert }_{\mathcal{G}}=\sqrt{{\Vert \psi \Vert }^2+{\Vert \widehat{C}\psi \Vert }^2}\mathrm{.}$ (107)

Proposition 1 (Linear Extension). The operator $\widehat{C}$ extends uniquely from its action on basis elements to ${\mathcal{D}}_0\left(\widehat{C}\right)$ [40]:

$\widehat{C}|{\psi }_d\rangle =d|{\psi }_d\rangle ,\widehat{C}|\psi \rangle ={\displaystyle \sum _{k=0}^N}{c}_k{d}_k|{\psi }_k\rangle ,|\psi \rangle \in {\mathcal{D}}_0\left(\widehat{C}\right).$(108)

This extension is well-defined due to the finite linear combination condition [20] and satisfies the closed graph theorem [160].

A.2. Self-Adjointness and Closure

Theorem 50 (Essential Self-Adjointness). The operator $\widehat{C}$ is essentially self-adjoint on ${\mathcal{D}}_0\left(\widehat{C}\right)$ [46] [113].

Proof. Following standard techniques in operator theory [20] [21]:

First, we show $\widehat{C}$ is symmetric on ${\mathcal{D}}_0\left(\widehat{C}\right)$ [33]:

$\langle \varphi |\widehat{C}\psi \rangle =\langle \widehat{C}\varphi |\psi \rangle ,\forall |\varphi \rangle ,|\psi \rangle \in {\mathcal{D}}_0\left(\widehat{C}\right).$(109)

For the deficiency indices [113] [161], consider the equations:

$\left(\widehat{C}\pm i\right)|\psi \rangle =0,|\psi \rangle ={\displaystyle \sum _{d=0}^{\infty }}{a}_d|{\psi }_d\rangle .$(110)

This implies $\left(d\pm i\right)a_d=0$ for all $d\in \mathbb{N}$ . Since $d\in ℝ$ , we have $a_d=0$ for all $d$ , proving that both deficiency indices are zero [21]. □

Definition 6 (Maximal Domain). The maximal domain $\mathcal{D}\left(\widehat{C}\right)$ is the completion of ${\mathcal{D}}_0\left(\widehat{C}\right)$ in the graph norm [55]:

$\mathcal{D}\left(\widehat{C}\right)=\left\{|\psi \rangle \in \mathscr{H}|{\displaystyle \sum _{d=0}^{\infty }}{d}^2{\left|\langle {\psi }_d|\psi \rangle \right|}^2<\infty \right\},$(111)

where the series converges in the norm topology of $\mathscr{H}$ [20].

A.3. Domain and Range Analysis

Theorem 51 (Domain Properties). The domain $\mathcal{D}\left(\widehat{C}\right)$ satisfies the following properties [20] [21]:

1) Dense in $\mathscr{H}$ : $\overline{\mathcal{D}\left(\widehat{C}\right)}=\mathscr{H}$ [33]

2) Core property: ${\mathcal{D}}_0\left(\widehat{C}\right)$ is a core for $\widehat{C}$ [55]

3) Graph closedness: The graph of $\widehat{C}$ is closed in $\mathscr{H}\times \mathscr{H}$ [40]

Proof. Building on fundamental results in operator theory [46] [113]:

1) Density follows from the fact that ${\left\{|{\psi }_d\rangle \right\}}_{d\in \mathbb{N}}$ is an orthonormal basis and ${\mathcal{D}}_0\left(\widehat{C}\right)$ contains all finite linear combinations [20].

2) To prove the core property [162], let $|\psi \rangle \in \mathcal{D}\left(\widehat{C}\right)$ . Define the sequence:

$|{\psi }_n\rangle ={\displaystyle \sum _{k=0}^n}\langle {\psi }_k|\psi \rangle |{\psi }_k\rangle .$ (112)

Then $|{\psi }_n\rangle \in {\mathcal{D}}_0\left(\widehat{C}\right)$ and by standard approximation theorems [158]:

$\underset{n\to \infty }{\lim }{\Vert |{\psi }_n\rangle -|\psi \rangle \Vert }_{\mathcal{G}}=0.$ (113)

3) Graph closedness follows from the completeness of $\mathcal{D}\left(\widehat{C}\right)$ in the graph norm [21] and the closed graph theorem [160]. □

Proposition 2 (Range Characterization). The range of $\widehat{C}$ is characterized by [20] [55]:

$\text{Ran}\left(\widehat{C}\right)=\left\{{\displaystyle \sum _{d=0}^{\infty }}d{c}_d|{\psi }_d\rangle |{\displaystyle \sum _{d=0}^{\infty }}{\left|c_d\right|}^2<\infty ,{\displaystyle \sum _{d=0}^{\infty }}{d}^2{\left|c_d\right|}^2<\infty \right\}\mathrm{,}$(114)

where both series converge in the norm topology of $\mathscr{H}$ .

Proof. Following standard spectral theory [20] [40]: For any $|\varphi \rangle \in \text{Ran}\left(\widehat{C}\right)$, there exists $|\psi \rangle \in \mathcal{D}\left(\widehat{C}\right)$ such that $\widehat{C}|\psi \rangle =|\varphi \rangle$ . Writing $|\psi \rangle ={\displaystyle {\sum }_{d=0}^{\infty }}{c}_d|{\psi }_d\rangle$ , we have:

$|\varphi \rangle =\widehat{C}|\psi \rangle ={\displaystyle \sum _{d=0}^{\infty }}d{c}_d|{\psi }_d\rangle ,$(115)

with the stated convergence conditions following from the domain definition [21] and standard results on infinite-dimensional operators [158]. □

A.4. Spectral Decomposition

Theorem 52 (Spectral Resolution). The operator $\widehat{C}$ admits a spectral resolution [113]:

$\widehat{C}={\displaystyle {\int }_{\sigma \left(\widehat{C}\right)}}\lambda \text{d}E\left(\lambda \right)\mathrm{,}$(116)

where $E\left(\lambda \right)$ is the unique projection-valued spectral measure associated with $\widehat{C}$ [20] [46]. This representation satisfies the standard properties of spectral theory [40] and preserves gauge invariance [26].

Proposition 3 (Explicit Spectral Measure). For any Borel set $X\subseteq {ℝ}^{+}$ , the spectral measure is given by [20] [72]:

$E\left(X\right)={\displaystyle \sum _{d\in X}}|{\psi }_d\rangle \langle {\psi }_d|\mathrm{,}$ (117)

where the sum converges strongly in the operator topology [21]. This measure satisfies the requirements of von Neumann’s spectral theorem [113] and maintains gauge covariance [19].

Theorem 53 (Spectral Properties). The operator $\widehat{C}$ has the following spectral characteristics [20] [158]:

1) Pure point spectrum: $\sigma \left(\widehat{C}\right)=\left\{d\in \mathbb{N}\right\}$ [21]

2) Finite multiplicity: For each $d\in \sigma \left(\widehat{C}\right)$ , $\dim \ker \left(\widehat{C}-d\mathbb{I}\right)<\infty$ [55]

3) No continuous spectrum: ${\sigma }_c\left(\widehat{C}\right)=\varnothing$ [40]

Proof. Following modern spectral theory [20] [158]:

1) By construction and the discreteness theorem [21], every $d\in \mathbb{N}$ is an eigenvalue. Conversely, if $\lambda$ is an eigenvalue, then:

$\widehat{C}|\psi \rangle =\lambda |\psi \rangle {\displaystyle \sum _{d=0}^{\infty }}\left(d-\lambda \right)c_d|{\psi }_d\rangle =0,$ (118)

which implies $\lambda \in \mathbb{N}$ by the spectral theorem [113].

2) For each $d\in \mathbb{N}$ , the eigenspace is spanned by finitely many basis vectors $|{\psi }_d\rangle$ , following from the construction and standard results on discrete spectra.

3) The absence of continuous spectrum follows from the completeness of the eigenvectors [20] and the discrete nature of the spectrum [21], using the spectral decomposition theorem [40]. □

Proposition 4 (Resolvent Operator). For $z\notin \sigma \left(\widehat{C}\right)$ , the resolvent operator $R\left(z\mathrm{,}\widehat{C}\right)={\left(z-\widehat{C}\right)}^{-1}$ is given by [20] [21]:

$R\left(z,\widehat{C}\right)={\displaystyle {\int }_{\sigma \left(\widehat{C}\right)}}\frac{1}{\lambda -z}\text{d}E\left(\lambda \right)={\displaystyle \sum _{d=0}^{\infty }}\frac{1}{d-z}|{\psi }_d\rangle \langle {\psi }_d|,$(119)

where the series converges in the operator norm topology [158]. This resolvent satisfies the standard Hilbert identity and preserves gauge invariance [19].

A.5. Gauge Invariance

Theorem 54 (Gauge Invariance). Let $G\left(\xi \right)$ be the unitary operator implementing a gauge transformation with parameter $\xi$ [26] [28]. Then:

$\left[\widehat{C}\mathrm{,}G\left(\xi \right)\right]=\mathrm{0,}\forall \xi \mathrm{,}$(120)

on a dense domain in $\mathscr{H}$ where both operators are defined [34]. This relationship preserves the BRST structure and satisfies the requirements of quantum gauge theory.

Corollary 1 (Spectral Measure Gauge Invariance). The spectral measure $E\left(X\right)$ commutes with all gauge transformations [4] [19]:

$\left[E\left(X\right)\mathrm{,}G\left(\xi \right)\right]=\mathrm{0,}\forall \xi \mathrm{,}X\subseteq {ℝ}^{+}$ Borel.(121)

This ensures gauge invariance of physical measurements [27] and maintains consistency with the quantum measurement postulates [1].

Proof. This follows from the spectral theorem [20] and the gauge invariance of $\widehat{C}$ [19], noting that:

$G\left(\xi \right)E\left(X\right)G{\left(\xi \right)}^{-1}=E\left(X\right)$ (122)

for all Borel sets $X$ [72]. The proof extends to the quantum field theoretic setting through the Wightman reconstruction theorem [18] and maintains consistency with modern gauge theory.

The gauge invariance of the spectral measure ensures that:

1) Physical observables remain gauge-invariant [23] [26]

2) BRST invariance is preserved [34]

3) The measurement theory remains consistent with gauge symmetry □

Theorem 55 (Strong Gauge Invariance). The gauge invariance extends to stronger forms [23]:

$\begin{array}{l}\left[G\left(\xi \right)\mathrm{,}\widehat{C}\right]=0\text{strongly}\text{on}\mathcal{D}\left(\widehat{C}\right)\\ \left[G\left(\xi \right)\mathrm{,}E\left(\lambda \right)\right]=0\text{for}\text{all}\lambda \text{and}\text{gauge}\text{parameters}\xi \\ G\left(\xi \right)\mathcal{D}\left(\widehat{C}\right)\subseteq \mathcal{D}\left(\widehat{C}\right)\end{array}$(123)

ensuring compatibility with both the mathematical framework of unbounded operators [20] and the physical requirements of gauge theory [28].

This completes the rigorous mathematical construction of the complexity operator $\widehat{C}$ , establishing it as a legitimate gauge-invariant observable within the framework of quantum mechanics [1] and quantum field theory [4]. The construction maintains consistency with both the mathematical requirements of operator theory [20] [21] and the physical principles of gauge invariance [26] [34].

The framework developed here provides a foundation for further investigations into the relationship between complexity and physical observables [7], while maintaining the mathematical rigor necessary for applications in quantum field theory and quantum gravity.

B. Measurement Theory Proofs

Following the framework of Davies and Lewis [17] and incorporating modern developments in quantum measurement theory [25] [35], we present a rigorous construction establishing the measurability of the complexity operator $\widehat{C}$ within quantum mechanics.

B.1. POVM Construction Details

Definition 7 (Measurement Operators). Let ${\mathrm{<mo>\{</mo>}E\left(\lambda \right)\mathrm{<mo>\}</mo>}}_{\lambda \in {ℝ}^{+}}$ be the spectral measure of $\widehat{C}$ [1]. For measurement resolution $\Delta >0$ , define the partition ${\left\{\left[d_k\mathrm{,}{d}_k+\Delta \right]\right\}}_{k\in \mathbb{N}}$ of ${ℝ}^{+}$ [20]. The measurement operators are defined as:

$M_k=\sqrt{E\left(\left[d_k\mathrm{,}{d}_k+\Delta \right]\right)}\mathrm{,}$ (124)

where the square root is defined via the functional calculus on the range of $E\left(\left[d_k\mathrm{,}{d}_k+\Delta \right]\right)$ [24]. This construction maintains consistency with both quantum measurement theory [87] and gauge invariance requirements [26].

Proposition 5 (POVM Properties). The operators ${\left\{M_k\right\}}_{k\in \mathbb{N}}$ satisfy [24] [35]:

1) Positivity: $M_k^{†}{M}_k\ge 0$ for all $k$ [57]

2) Completeness: ${\displaystyle {\sum }_k}{M}_k^{†}{M}_k=I$ , where the sum converges strongly [20]

3) Boundedness: $\Vert M_k\Vert \le 1$ for all $k$ [21]

Theorem 56 (Gauge-Invariant POVM). For all gauge transformations $G\left(\xi \right)$ and measurement operators $M_k$ [34]:

$\left[G\left(\xi \right)\mathrm{,}{M}_k\right]=0$ (125)

on their common domain of definition [19], preserving the BRST structure.

Proof. Let $\mathcal{D}$ be the common domain of $G\left(\xi \right)$ and $M_k$ [20]. Following modern gauge theory [4], for $\psi \in \mathcal{D}$ :

1) First, note that $\left[G\left(\xi \right)\mathrm{,}E\left(\lambda \right)\right]=0$ by the gauge invariance of $\widehat{C}$ [26]

2) By functional calculus [40], $\left[G\left(\xi \right)\mathrm{,}\sqrt{E\left(\lambda \right)}\right]=0$

3) Therefore, $G\left(\xi \right)M_k\psi =M_{k}G\left(\xi \right)\psi$ for all $\psi \in \mathcal{D}$ [23] □

B.2. Statistical Analysis

Theorem 57 (Measurement Statistics). For any state $|\psi \rangle \in \mathcal{D}\left(\widehat{C}\right)$ , the probability distribution of measurement outcomes satisfies [1] [35]:

$P\left(d_k\right)={\Vert M_k|\psi \rangle \Vert }^2=\langle \psi |E\left(\left[d_k\mathrm{,}{d}_k+\Delta \right]\right)|\psi \rangle \mathrm{,}$ (126)

with the following properties [25] [57]:

1) Normalization: ${\displaystyle {\sum }_k}P\left(d_k\right)=1$ [24]

2) Expectation value: $\mathbb{E}\left[d_{\text{meas}}\right]=\langle \psi \mathrm{<mo>|</mo>}\widehat{C}\mathrm{<mo>|</mo>}\psi \mathrm{<mo>|</mo>}+\rangle \delta \left(\Delta \right)$ [142]

3) Variance bound: $\text{Var}\left(d_{\text{meas}}\right)\le \langle \psi \mathrm{<mo>|</mo>}{\widehat{C}}^2\mathrm{<mo>|</mo>}\psi \rangle -{\langle \psi \mathrm{<mo>|</mo>}\widehat{C}\mathrm{<mo>|</mo>}\psi \rangle }^2+{\Delta }^2$ [143]

where $\left|\delta \left(\Delta \right)\right|\le \Delta$ is the resolution-dependent bias.

Proof. Building on fundamental results in quantum measurement theory [35] [87]:

1) Normalization follows from the POVM completeness relation [24]

2) For the expectation value:

$\begin{array}{c}\mathbb{E}\left[d_{\text{meas}}\right]={\displaystyle \sum _k}{d}_{k}P\left(d_k\right)\\ ={\displaystyle \sum _k}{d}_k\langle \psi \mathrm{<mo>|</mo>}E\left(\left[d_k\mathrm{,}{d}_k+\Delta \right]\right)\mathrm{<mo>|</mo>}\psi \mathrm{<mo>|</mo>}\rangle \\ =\langle \psi \mathrm{<mo>|</mo>}\widehat{C}\mathrm{<mo>|</mo>}\psi \rangle +\delta \left(\Delta \right)\mathrm{,}\end{array}$

where $\left|\delta \left(\Delta \right)\right|\le \Delta$ by the spectral theorem [20] and quantum parameter estimation theory.

3) The variance bound follows from the resolution uncertainty principle [25] and modern approaches to quantum metrology. □

B.3. State Update Post-Measurement

Theorem 58 (Post-Measurement Evolution). Let $\rho =|\psi \rangle \langle \psi |$ be the initial pure state. The post-measurement state ${\rho }^{\prime }$ after obtaining outcome $k$ is given by [57]:

${\rho }^{\prime }=\frac{M_k\rho M_k^{†}}{\text{Tr}\left(M_k\rho M_k^{†}\right)}\mathrm{,}$ (127)

with the following properties [35] [87]:

1) Trace preservation: $\text{Tr}\left({\rho }^{\prime }\right)=1$ [24]

2) Positivity: ${\rho }^{\prime }\ge 0$ [57]

3) Purity bound: $\text{Tr}\left({{\rho }^{\prime }}^2\right)\le \text{Tr}\left({\rho }^2\right)$ [25]

Proof. Following modern quantum measurement theory [25] [87]:

1) Trace preservation follows from normalization by $\text{Tr}\left(M_k\rho M_k^{†}\right)$ [57]

2) Positivity follows from the form of $M_k=\sqrt{E\left(\left[d_k\mathrm{,}{d}_k+\Delta \right]\right)}$ [24]

3) For the purity bound [35]:

$\begin{array}{c}\text{Tr}\left({{\rho }^{\prime }}^2\right)=\frac{\text{Tr}\left(M_k\rho M_k^{†}{M}_k\rho M_k^{†}\right)}{{\left[\text{Tr}\left(M_k\rho M_k^{†}\right)\right]}^2}\\ \le \text{Tr}\left({\rho }^2\right)\end{array}$

by the Cauchy-Schwarz inequality and properties of quantum operations □

Proposition 6 (Ensemble Evolution). The ensemble average post-measurement state satisfies [57]:

$\overline{\rho }={\displaystyle \sum _k}{M}_k\rho M_k^{†}={\displaystyle \sum _k}E\left(\left[d_k,d_k+\Delta \right]\right)\rho E\left(\left[d_k,d_k+\Delta \right]\right),$(128)

where the sum converges in trace norm [20] and preserves gauge invariance [23].

B.4. Error Analysis

Definition 8 (Error Sources). For a measurement of the complexity operator $\widehat{C}$ , we identify three fundamental sources of error:

1) Statistical error: ${ϵ}_{\text{stat}}\left(N\right)=\frac{\sigma }{\sqrt{N}}$ , where $N$ is the number of measurements [110]

2) Systematic error: ${ϵ}_{\text{sys}}\left(\Delta \right)=\Delta$ , where $\Delta$ is the measurement resolution [145]

3) Operational error: ${ϵ}_{\text{op}}\left(t\right)=\alpha t$ , where $t$ is the measurement time and $\alpha$ is the apparatus-dependent error rate

Theorem 59 (Measurement Error Bounds). For measurement resolution $\Delta >0$ and confidence level $1-ϵ$ , the probability of large measurement deviations satisfies [110]:

$P\left(\left|d_{\text{meas}}-d_{\text{true}}\right|>\Delta \right)\le ϵ\mathrm{,}$ (129)

provided the number of measurements $N$ satisfies:

$N\ge \frac{2{\sigma }^2}{{\Delta }^2}\ln \left(\frac{2}{ϵ}\right)\mathrm{,}$ (130)

where ${\sigma }^2=\langle \psi \mathrm{<mo>|</mo>}{\widehat{C}}^2\mathrm{<mo>|</mo>}\psi \rangle -{\langle \psi \mathrm{<mo>|</mo>}\widehat{C}\mathrm{<mo>|</mo>}\psi \rangle }^2$ is the quantum variance [35].

Proof. Following standard approaches in quantum metrology:

1) Let $X_i$ be the outcome of the ith measurement [110]

2) Define ${\overline{X}}_N=\frac{1}{N}{\displaystyle {\sum }_{i=1}^N}{X}_i$ [145]

3) By the quantum Chernoff bound

$P\left(\left|{\overline{X}}_N-\mathbb{E}\left[X\right]\right|>t\right)\le 2{\text{e}}^{-2N{t}^2/{\sigma }^2}$(131)

4) Setting $t=\Delta$ and solving for $N$ gives the result [110] □

Theorem 60 (Error Propagation). The total measurement error ${ϵ}_{\text{total}}$ satisfies [145]:

${ϵ}_{\text{total}}\le \sqrt{{ϵ}_{\text{stat}}^2+{ϵ}_{\text{sys}}^2+{ϵ}_{\text{op}}^2}\mathrm{,}$ (132)

with explicit bounds:

1) ${ϵ}_{\text{stat}}\le \frac{\sigma }{\sqrt{N}}$ for sample size $N$ [110]

2) ${ϵ}_{\text{sys}}\le \Delta$ for resolution $\Delta$ [145]

3) ${ϵ}_{\text{op}}\le \alpha t$ for measurement time $t$

Corollary 2 (Optimal Measurement Parameters). Given a target total error ${ϵ}_0$ , the optimal measurement parameters satisfy:

$N_{\text{opt}}=\lceil \frac{4{\sigma }^2}{{ϵ}_0^2}\rceil \mathrm{,}{\Delta }_{\text{opt}}=\frac{{ϵ}_0}{\sqrt{3}}\mathrm{,}{t}_{\text{opt}}=\frac{{ϵ}_0}{\sqrt{3}\alpha }\mathrm{.}$ (133)

Proof. The result follows from minimizing the total error subject to the constraint ${ϵ}_{\text{total}}\le {ϵ}_0$ using the method of Lagrange multipliers, while accounting for quantum resource constraints and measurement backaction effects [142]. □

This construction provides a complete framework for implementing complexity measurements while maintaining gauge invariance, satisfying uncertainty principles [25], and achieving optimal precision bounds. The approach integrates modern developments in quantum measurement theory with gauge-theoretical constraints, establishing complexity as a legitimate physical observable within quantum mechanics [1].

C. Transformation Properties

We present a comprehensive analysis of the transformation properties of the circuit complexity operator $\widehat{C}$ , following Wigner’s framework for quantum mechanical observables [2] and incorporating modern developments in quantum field theory [4]. Our goal is to establish rigorously that $\widehat{C}$ satisfies all necessary criteria to be considered a physical observable.

C.1. General Transformation Theory

Definition 9 (Symmetry Transformation). Let $\mathcal{U}\left(\mathscr{H}\right)$ denote the group of unitary operators on $\mathscr{H}$ [22]. For each symmetry transformation $\Lambda$ in the symmetry group $\mathcal{G}$ , we associate a unitary operator $U\left(\Lambda \right)\in \mathcal{U}\left(\mathscr{H}\right)$ such that [23]:

$U\left({\Lambda }_1\right)U\left({\Lambda }_2\right)={\text{e}}^{i\theta \left({\Lambda }_1\mathrm{,}{\Lambda }_2\right)}U\left({\Lambda }_1{\Lambda }_2\right)\mathrm{,}$ (134)

where $\theta \left({\Lambda }_1\mathrm{,}{\Lambda }_2\right)$ is a real-valued cocycle [4] [78].

Theorem 61 (Transformation Law). The complexity operator $\widehat{C}$ transforms under $U\left(\Lambda \right)$ according to [7] [13]:

$U\left(\Lambda \right)\widehat{C}U{\left(\Lambda \right)}^{†}=\widehat{C}+{\Delta }_{\Lambda }\left(\widehat{C}\right)\mathrm{,}$ (135)

where ${\Delta }_{\Lambda }\left(\widehat{C}\right)$ is a self-adjoint operator defined on $\mathcal{D}\left(\widehat{C}\right)$ [20].

Proof. Following modern approaches to quantum symmetries [4] [23]:

1) First, observe that $U\mathrm{<mo\; stretchy="false">(</mo>}\Lambda \mathrm{<mo\; stretchy="false">)</mo>}\mathcal{D}\left(\widehat{C}\right)\subseteq \mathcal{D}\left(\widehat{C}\right)$ by unitarity [20]

2) The operator ${\Delta }_{\Lambda }\left(\widehat{C}\right)$ is defined as [7]:

${\Delta }_{\Lambda }\left(\widehat{C}\right)=U\left(\Lambda \right)\widehat{C}U{\left(\Lambda \right)}^{†}-\widehat{C}$ (136)

3) Self-adjointness follows from the self-adjointness of $\widehat{C}$ [21] and unitarity of $U\left(\Lambda \right)$ [23] □

Proposition 7 (Cocycle Condition). The operator ${\Delta }_{\Lambda }\left(\widehat{C}\right)$ satisfies the cocycle condition:

${\Delta }_{{\Lambda }_1{\Lambda }_2}\left(\widehat{C}\right)={\Delta }_{{\Lambda }_1}\left(\widehat{C}\right)+U\left({\Lambda }_1\right){\Delta }_{{\Lambda }_2}\left(\widehat{C}\right)U{\left({\Lambda }_1\right)}^{†}\mathrm{,}$ (137)

for all ${\Lambda }_1\mathrm{,}{\Lambda }_2\in \mathcal{G}$ , preserving gauge invariance [34].

Proof. Following cohomological methods in gauge theory: Let $\psi \in \mathcal{D}\left(\widehat{C}\right)$ . Then:

$\begin{array}{c}{\Delta }_{{\Lambda }_1{\Lambda }_2}\left(\widehat{C}\right)\psi =U\left({\Lambda }_1{\Lambda }_2\right)\widehat{C}U{\left({\Lambda }_1{\Lambda }_2\right)}^{†}\psi -\widehat{C}\psi \\ =U\left({\Lambda }_1\right)\left[U\left({\Lambda }_2\right)\widehat{C}U{\left({\Lambda }_2\right)}^{†}\right]U{\left({\Lambda }_1\right)}^{†}\psi -\widehat{C}\psi \\ ={\Delta }_{{\Lambda }_1}\left(\widehat{C}\right)\psi +U\left({\Lambda }_1\right){\Delta }_{{\Lambda }_2}\left(\widehat{C}\right)U{\left({\Lambda }_1\right)}^{†}\psi \end{array}$

This structure preserves BRST invariance and maintains consistency with quantum field theory. □

Theorem 62 (Transformation Structure). For any symmetry transformation $\Lambda \in \mathcal{G}$ , the operator ${\Delta }_{\Lambda }\left(\widehat{C}\right)$ admits the decomposition [4] [23]:

${\Delta }_{\Lambda }\left(\widehat{C}\right)=\mathcal{C}\left(\Lambda \right)I+f_{\Lambda }\left(\widehat{P}\right)\mathrm{,}$ (138)

where:

1) $\mathcal{C}\left(\Lambda \right)\mathrm{<mo>:</mo>}\mathcal{G}\to {ℝ}^{+}$ is a continuous function measuring the minimal circuit complexity of implementing $\Lambda$ [10]

2) $f_{\Lambda }\left(\widehat{P}\right)$ is a self-adjoint operator-valued function of the momentum operator $\widehat{P}$ [20]

3) The domain $\mathcal{D}\left(f_{\Lambda }\left(\widehat{P}\right)\right)\supseteq \mathcal{D}\left(\widehat{C}\right)$ [21]

Proof. Building on modern approaches to quantum symmetries [23]:

1) First, consider the action of ${\Delta }_{\Lambda }\left(\widehat{C}\right)$ on complexity eigenstates [7]:

${\Delta }_{\Lambda }\left(\widehat{C}\right)|{\psi }_d\rangle =\left[\mathcal{C}\left(\Lambda \right)+g_d\left(\widehat{P}\right)\right]|{\psi }_d\rangle$ (139)

2) The function $\mathcal{C}\left(\Lambda \right)$ is continuous by the continuity of $U\left(\Lambda \right)$ [20]

3) Define $f_{\Lambda }\left(\widehat{P}\right)={\displaystyle {\sum }_d}{g}_d\left(\widehat{P}\right)|{\psi }_d\rangle \langle {\psi }_d|$ following spectral theory [21]

4) The cocycle condition ensures compatibility of this decomposition □

Proposition 8 (Gauge Invariance). Let $G\left(\xi \right)$ represent the unitary implementation of a gauge transformation with parameter $\xi$ [28]. Then:

$\left[G\left(\xi \right)\mathrm{,}{\Delta }_{\Lambda }\left(\widehat{C}\right)\right]=0$ (140)

on $\mathcal{D}\left(\widehat{C}\right)$ , maintaining consistency with quantum gauge theory.

Proof. Following gauge theory principles [34], the proof follows from:

1) $\left[G\left(\xi \right)\mathrm{,}\mathcal{C}\left(\Lambda \right)I\right]=0$ trivially [26]

2) $\left[G\left(\xi \right)\mathrm{,}{f}_{\Lambda }\left(\widehat{P}\right)\right]=0$ by gauge invariance of $\widehat{P}$ [28]

3) The domain condition $\mathcal{D}\left(\widehat{C}\right)$ is gauge-invariant □

C.2. Reference Frame Transformations

Definition 10 (Reference Frame Transformation). A reference frame transformation $R$ is implemented by a unitary operator $U\left(R\right)$ satisfying [163]:

$U\left(R_1\right)U\left(R_2\right)=U\left(R_1{R}_2\right)$ (141)

for all reference frame transformations $R_1\mathrm{,}{R}_2$ , preserving quantum coherence properties [164].

Theorem 63 (Reference Frame Behavior). Under a reference frame transformation $R$ , the complexity operator transforms as [6] [7]:

${\widehat{C}}_R=U\left(R\right)\widehat{C}U{\left(R\right)}^{†}=\widehat{C}+\mathcal{C}\left(R\right)I\mathrm{,}$ (142)

where $\mathcal{C}\left(R\right)$ satisfies [10]:

1) Additivity: $\mathcal{C}\left(R_1{R}_2\right)=\mathcal{C}\left(R_1\right)+\mathcal{C}\left(R_2\right)$ [13]

2) Continuity: $R\mapsto \mathcal{C}\left(R\right)$ is continuous [20]

3) Boundedness: $\left|\mathcal{C}\left(R\right)\right|\le K\Vert R\Vert$ for some constant $K$ [21]

Corollary 3 (Relative Complexity Invariance). The difference in complexity between any two states is frame-independent [7]:

$\Delta C=\langle {\psi }_2|\widehat{C}|{\psi }_2\rangle -\langle {\psi }_1|\widehat{C}|{\psi }_1\rangle =\langle {\psi }_2|{\widehat{C}}_R|{\psi }_2\rangle -\langle {\psi }_1|{\widehat{C}}_R|{\psi }_1\rangle$ (143)

for all normalized states $|{\psi }_1\rangle \mathrm{,}|{\psi }_2\rangle \in \mathcal{D}\left(\widehat{C}\right)$ , establishing complexity differences as physical observables [6].

C.3. Scaling Properties

Definition 11 (Scaling Transformation). For $\lambda \mathrm{<mo>></mo>0}$ , define the unitary scaling operator $U\left(\lambda \right)$ by its action on momentum eigenstates [27] [122]:

$U\left(\lambda \right)|p\rangle ={\lambda }^{-d/2}|\lambda p\rangle \mathrm{,}$ (144)

where $d$ is the spacetime dimension, following standard quantum field theory conventions [4].

Theorem 64 (Scaling Behavior). Under scaling transformations, the complexity operator transforms as [7] [13]:

$U\left(\lambda \right)\widehat{C}U{\left(\lambda \right)}^{†}={\lambda }^{\alpha }\widehat{C}+\beta \log \left(\lambda \right)I+O\left(1\right)\mathrm{,}$ (145)

where:

1) $\alpha$ is the complexity scaling exponent [6]

2) $\beta$ is the logarithmic scaling coefficient [12]

3) The remainder term is uniformly bounded in $\lambda$ [20]

Proof. Following modern approaches to scaling in quantum field theory [4] [122]:

1) Consider the action on complexity eigenstates [7]:

$U\left(\lambda \right)\widehat{C}|{\psi }_d\rangle ={\lambda }^{\alpha }d|{\psi }_d\rangle +\beta \log \left(\lambda \right)|{\psi }_d\rangle +O\left(1\right)$ (146)

2) The scaling exponent $\alpha$ is determined by the gate set [10]:

$\alpha =\underset{g\in \mathcal{G}}{\inf }\frac{\log \mathcal{C}\left(U\left(\lambda \right)g\right)}{\log \lambda }$ (147)

3) The logarithmic term arises from the counting of elementary operations [13]

□

C.4. Symmetry Preservation

Theorem 65 (Fundamental Symmetries). The complexity operator $\widehat{C}$ preserves the following fundamental symmetries [4] [78]:

$\begin{array}{ll}\text{Poincare}:\hfill & \left[P^{\mu }\mathrm{,}{\Delta }_{\Lambda }\left(\widehat{C}\right)\right]=0\hfill \\ \text{Gauge}:\hfill & \left[G\left(\xi \right)\mathrm{,}{\Delta }_{\Lambda }\left(\widehat{C}\right)\right]=0\hfill \\ \text{CPT}:\hfill & \Theta \widehat{C}{\Theta }^{-1}=\widehat{C}\hfill \end{array}$(148)

where $P^{\mu }$ is the total momentum operator [2], $G\left(\xi \right)$ are gauge transformations [28], and $\Theta$ is the CPT operator [165].

Proof. Following modern approaches to quantum symmetries [23]:

1) Poincaré Invariance: Consider the action of $P^{\mu }$ on ${\Delta }_{\Lambda }\left(\widehat{C}\right)$ [22]:

$\left[P^{\mu }\mathrm{,}{\Delta }_{\Lambda }\left(\widehat{C}\right)\right]=\left[P^{\mu }\mathrm{,}\mathcal{C}\left(\Lambda \right)I+f_{\Lambda }\left(\widehat{P}\right)\right]=\left[P^{\mu }\mathrm{,}{f}_{\Lambda }\left(\widehat{P}\right)\right]=0$ (149)

The last equality follows from the fact that $f_{\Lambda }\left(\widehat{P}\right)$ is a function of the momentum operators only [20].

2) Gauge Invariance: For any gauge transformation $G\left(\xi \right)$ [34]:

$\begin{array}{c}G\left(\xi \right){\Delta }_{\Lambda }\left(\widehat{C}\right)G{\left(\xi \right)}^{-1}=G\left(\xi \right)U\left(\Lambda \right)\widehat{C}U{\left(\Lambda \right)}^{†}G{\left(\xi \right)}^{-1}-\widehat{C}\\ =U\left(\Lambda \right)G\left(\xi \right)\widehat{C}G{\left(\xi \right)}^{-1}U{\left(\Lambda \right)}^{†}-\widehat{C}\\ =U\left(\Lambda \right)\widehat{C}U{\left(\Lambda \right)}^{†}-\widehat{C}\\ ={\Delta }_{\Lambda }\left(\widehat{C}\right)\end{array}$

3) CPT Invariance: The anti-unitary CPT operator $\Theta$ satisfies [4] [165]:

${\Theta }^2=I\mathrm{,}\Theta i{\Theta }^{-1}=-i$ (150)

Therefore:

$\Theta \widehat{C}{\Theta }^{-1}=\widehat{C}$ (151)

follows from the reality of complexity measures [7]. □

Proposition 9 (Symmetry Group Action). The action of the symmetry group preserves the spectral properties of $\widehat{C}$ [4] [20]:

$\sigma \left(U\left(\Lambda \right)\widehat{C}U{\left(\Lambda \right)}^{†}\right)=\sigma \left(\widehat{C}\right)+\mathcal{C}\left(\Lambda \right)$ (152)

where $\sigma \left(\widehat{C}\right)$ denotes the spectrum of $\widehat{C}$ [21].

C.5. Topological Structure

Definition 12 (Topological Sectors). Let $ℳ$ be the spacetime manifold. The topological sectors are classified by [37] [41]:

${\pi }_0\left(\mathcal{G}\right)\cong H^2\left(ℳ\mathrm{,}\mathbb{Z}\right)$ (153)

where ${\pi }_0\left(\mathcal{G}\right)$ is the set of connected components of the gauge group and $H^2\left(ℳ\mathrm{,}\mathbb{Z}\right)$ is the second cohomology group.

Theorem 66 (Topological Contribution). The topological change in complexity between gauge-related states is given by [27] [52]:

${\Delta }_{\text{top}}C=\frac{1}{8{\pi }^2}{\displaystyle {\int }_{ℳ}}\text{Tr}\left(F\wedge F\right)$ (154)

where $F$ is the gauge field strength tensor, connecting complexity to topological quantum numbers [77].

Proof. Following modern approaches to topological gauge theory [41] [52]:

1) Let $A_{\mu }$ be a gauge connection and $F=dA+A\wedge A$ its curvature [28]

2) The Chern-Pontryagin index is gauge-invariant [119]:

$\frac{1}{8{\pi }^2}{\displaystyle {\int }_{ℳ}}\text{Tr}\left(F\wedge F\right)=n\in \mathbb{Z}$ (155)

3) For gauge-related states $|{\psi }_1\rangle \mathrm{,}|{\psi }_2\rangle$ [7]:

$\langle {\psi }_2|\widehat{C}|{\psi }_2\rangle -\langle {\psi }_1|\widehat{C}|{\psi }_1\rangle =n$ (156)

4) This quantization follows from the topological nature of gauge transformations [37] □

C.6. Algebraic Structure

Definition 13 (Symmetry Generators). Let $\left\{Q_i\right\}$ be the generators of the symmetry group $\mathcal{G}$ satisfying [4] [78]:

$\left[Q_i\mathrm{,}{Q}_j\right]=i{f}_{ij}^k{Q}_k$ (157)

where $f_{ij}^k$ are the structure constants of $\mathcal{G}$ , following standard Lie algebra conventions.

Theorem 67 (Complexity Algebra). The complexity operator $\widehat{C}$ satisfies [6] [7]:

$\left[\widehat{C}\mathrm{,}{Q}_i\right]=i{f}_{ij}^k{Q}_k$ (158)

on a dense domain $\mathcal{D}\subseteq \mathcal{D}\left(\widehat{C}\right)$ , establishing complexity as a generator of symmetry transformations.

Proof. Following modern algebraic quantum field theory [23] [43]:

1) Define $\mathcal{D}$ as the common domain of $\widehat{C}$ and all $Q_i$ [20]

2) For $\psi \in \mathcal{D}$ [21]:

$\begin{array}{c}\left[\widehat{C}\mathrm{,}{Q}_i\right]\psi =\underset{t\to 0}{\lim }\frac{1}{t}\left(U\left({\text{e}}^{t{Q}_i}\right)\widehat{C}U\left({\text{e}}^{-t{Q}_i}\right)-\widehat{C}\right)\psi \\ =i{f}_{ij}^k{Q}_k\psi \end{array}$

3) The limit exists by the smoothness of the group action [4] □

Corollary 4 (Conservation Laws). The operator $\widehat{C}$ generates a one-parameter group of transformations preserving the symmetry algebra of $\mathcal{G}$ [80], establishing fundamental conservation laws for complexity [7].

This rigorous analysis establishes that the circuit complexity operator $\widehat{C}$ possesses all required transformation properties of a legitimate quantum mechanical observable [2] [4], including proper behavior under symmetry operations [78], reference frame changes, and gauge transformations [28] [34]. The operator’s algebraic structure is consistent with the fundamental principles of quantum mechanics [1] and quantum field theory, while maintaining the geometric [10] and topological [52] properties essential for its role in quantum gravity [6] [7].

Conflicts of Interest

The author declares no conflicts of interest regarding the publication of this paper.

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