Optimal Discrimination of Quantum States on a Two-Dimensional Hilbert

Total Page:16

File Type:pdf, Size:1020Kb

Optimal Discrimination of Quantum States on a Two-Dimensional Hilbert Optimal Discrimination of Quantum States on a Two-Dimensional Hilbert Space by Local Operations and Classical Communication Kenji Nakahira1, 3 and Tsuyoshi Sasaki Usuda2, 3 1Yokohama Research Laboratory, Hitachi, Ltd., Yokohama, Kanagawa 244-0817, Japan 2School of Information Science and Technology, Aichi Prefectural University, Nagakute, Aichi 480-1198, Japan 3Quantum Information Science Research Center, Quantum ICT Research Institute, Tamagawa University, Machida, Tokyo 194-8610, Japan (Dated: August 15, 2018) We study the discrimination of multipartite quantum states by local operations and classical communication. We derive that any optimal discrimination of quantum states spanning a two- dimensional Hilbert space in which each party’s space is finite dimensional is possible by local operations and one-way classical communication, regardless of the optimality criterion used and how entangled the states are. I. INTRODUCTION mation theory [11]. We denote a measurement on a 2D Hilbert space as a 2D measurement. Some important examples of 2D non-projective measurements are a mea- If two or more physically separated parties cannot surement maximizing the success rate for more than two communicate quantum information, their possibilities of states on a 2D Hilbert space and a measurement giving measuring quantum states are severely restricted. Intu- the result “don’t know” with non-zero probability, such itively, product states seem to be able to be optimally as an inconclusive measurement [12–14]. distinguished using only local operations and classical communication (LOCC), while entangled states seem to Let ex be a composite Hilbert space and sub be H H be indistinguishable. However, Bennett et al. found a subspace of ex. For simplicity, we say that a mea- H that orthogonal pure product states exist that cannot be surement described by the POVM Πm on sub can { } H perfectly distinguished by LOCC [1]. Later, Walgate et be realized by LOCC (or one-way LOCC) if there exists al. proved that any two pure orthogonal states in finite- an LOCC measurement (or a one-way LOCC measure- dimensional systems can be distinguished with certainty ment) described by the POVM Em on ex such that { } H using local operations and one-way classical communica- Πm = PsubEmPsub for any index m, where Psub is the or- tion (one-way LOCC) no matter how entangled they are thogonal projection operator onto sub. If any measure- H [2]. These results encourage further investigations on the ment on sub can be realized by LOCC, then any quan- H distinguishability of quantum states by LOCC, and sev- tum states on sub can be optimally distinguished using H eral important results have been reported in the case of only LOCC. Walgate et al.’s question can be rephrased as orthogonal states [3–8]. In this paper, we consider only “Can any measurement on a 2D Hilbert space be realized finite-dimensional systems. by LOCC?” The problem of LOCC discrimination for non- We emphasize that this question would be quite dif- orthogonal states is much more complicated. One of the ficult to answer. Instead of a 2D non-projective mea- main reasons is that perfect discrimination between them surement, one might consider realizing a corresponding is impossible, even without LOCC restriction. Instead, projective measurement, which is obtained by Naimark’s optimal discrimination can be sought. Walgate et al. [2] theorem [15], by LOCC. According to Naimark’s theo- posed the question: “Can any non-orthogonal states on a rem, any non-projective measurement can be realized by two-dimensional (2D) Hilbert space be optimally distin- a projective measurement on an extended Hilbert space. arXiv:1501.06222v1 [quant-ph] 26 Jan 2015 guished by LOCC?” To definitively answer this question, However, if a 2D non-projective measurement has more we must consider all optimality criteria. Various opti- than two POVM operators, then so does the correspond- mality criteria have been suggested, such as the Bayesian ing projective measurement, and such a measurement criterion, the Neyman-Pearson criterion, and the mutual often cannot be realized by LOCC [16–18]. Thus, this information criterion, but the above question is not an- approach cannot directly answer the question. Alter- swered except for very special cases, such as an opti- natively, one might try to decompose a given 2D non- mal error-free measurement for two non-orthogonal pure projective measurement into several 2D projective mea- states [9, 10]. Another reason is that optimal discrim- surements. It is known that there exist “decompos- ination for non-orthogonal states often requires a non- able” measurements, which statistically give the same projective measurement on the space spanned by the results as randomly choosing among measurements each given states, while any orthogonal states can be per- of which has fewer POVM operators than the original fectly distinguished by projective measurement. A posi- one [19]. If a 2D measurement can be decomposed into tive operator-valued measure (POVM) is the most gen- 2D projective measurements, then from [2], it can ob- eral formulation of a measurement permitted by quantum viously be realized by LOCC. However, only a few 2D mechanics and is commonly adopted in quantum infor- non-projective measurements are decomposable [19]. 2 In this paper, we show that any 2D measurement dim B. We consider finite-dimensional systems; NA H can be realized by one-way LOCC no matter how many and NB are finite. Assume that Alice and Bob share one POVM operators it has. Our result answers the above of a known collection of L quantum states represented L question: A global measurement is not needed for a 2D by density operators ρl l=1 on and want to optimally measurement in finite-dimensional systems, regardless of discriminate between{ them} in aH certain optimality crite- the optimality criterion used. rion. Our main result is that any 2D measurement (in It is worth noting that the problem of realizing a mea- finite-dimensional systems) can be realized by one-way surement by one-way LOCC is closely related to real- LOCC (see Corollary 3), which indicates that any op- izing a quantum receiver. Realization of an optimal or timal discrimination of ρl can be realized by one-way suboptimal receiver for optical states using linear opti- LOCC. { } cal feedback (or feedforward) and photon counting has We can easily extend our result to multipartite systems been widely studied both theoretically and experimen- in a way similar to [2]. Here, let us imagine a tripar- tally [21–30]. This type of receiver performs an individ- tite system: Alice, Bob, and Charlie share two linearly ual measurement on each temporal or spatial slot. A independent quantum states ψ and φ , which can be measurement can be decomposed into such individual represented by | i | i measurements if it can be realized by one-way LOCC; ′ ′ thus, our result indicates that any 2D measurement can ψ = pn A qn BC , be decomposed into individual measurements, at least | i n | i | i X in finite-dimensional systems. It is often important to ′ ′ φ = pn A rn BC , (2) investigate whether a measurement can be realized by | i n | i | i one-way LOCC to check whether it can be implemented X using only feasible resources when the whole system is instead of (1). In (2), Bob and Charlie are first grouped spatially or temporally separated. as one party. Asuume that our main result, i.e., Corol- In Section II, we present some necessary preliminaries, lary 3, holds in a bipartite system; then, we can show that where we show that any 2D measurement can be real- any measurement on any tripartite 2D Hilbert space can ized by one-way LOCC if any measurement with finite also be realized by one-way LOCC. Indeed, Alice per- rank-one POVM operators on any 2D bipartite Hilbert forms a measurement on her system according to the space in which Alice’s subspace is two-dimensional can bipartite one-way LOCC protocol that we will propose be realized by one-way LOCC. In Section III, we recall in this paper and tells the result to Bob and Charlie. the idea of Walgate et al. [2], which provides a method Then, Bob and Charlie can again use the same protocol. for realizing a 2D projective measurement by one-way This argument can easily be extended to any multipar- LOCC. In Section IV, we consider realizing a 2D non- tite system, and thus, in the rest of paper, we consider projective measurement by one-way LOCC. We show only bipartite systems. that, by extending Walgate et al.’s idea, any measure- First, we show that our main reulst can be reduced ment with finite rank-one POVM operators on any 2D to a simpler one. For example, from [20], any quantum bipartite Hilbert space in which Alice’s subspace is two- measurement with a continuous set of outcomes (includ- dimensional can be realized by one-way LOCC (Proposi- ing the discrete outcomes) on a finite-dimensional Hilbert tions 6 and 8; also Theorem 2). We conclude the paper space is equivalent to a continuous random choice of mea- in Section V. surements with finite outcomes. Thus, it suffices to show that any 2D measurement with finite outcomes can be re- alized by one-way LOCC. We show the following lemma: II. PRELIMINARIES We first consider a bipartite system. Let ψ and φ Lemma 1 If any measurement with finite rank-one | i | i be two linearly independent quantum states shared by POVM operators on a 2D (2,N)-space (N is finite in- Alice and Bob. We can write, in general form, teger) can be realized by one-way LOCC, then any 2D measurement (in finite-dimensional systems) can be re- ψ = pn qn , A B alized by one-way LOCC.
Recommended publications
  • FUNCTIONAL ANALYSIS 1. Banach and Hilbert Spaces in What
    FUNCTIONAL ANALYSIS PIOTR HAJLASZ 1. Banach and Hilbert spaces In what follows K will denote R of C. Definition. A normed space is a pair (X, k · k), where X is a linear space over K and k · k : X → [0, ∞) is a function, called a norm, such that (1) kx + yk ≤ kxk + kyk for all x, y ∈ X; (2) kαxk = |α|kxk for all x ∈ X and α ∈ K; (3) kxk = 0 if and only if x = 0. Since kx − yk ≤ kx − zk + kz − yk for all x, y, z ∈ X, d(x, y) = kx − yk defines a metric in a normed space. In what follows normed paces will always be regarded as metric spaces with respect to the metric d. A normed space is called a Banach space if it is complete with respect to the metric d. Definition. Let X be a linear space over K (=R or C). The inner product (scalar product) is a function h·, ·i : X × X → K such that (1) hx, xi ≥ 0; (2) hx, xi = 0 if and only if x = 0; (3) hαx, yi = αhx, yi; (4) hx1 + x2, yi = hx1, yi + hx2, yi; (5) hx, yi = hy, xi, for all x, x1, x2, y ∈ X and all α ∈ K. As an obvious corollary we obtain hx, y1 + y2i = hx, y1i + hx, y2i, hx, αyi = αhx, yi , Date: February 12, 2009. 1 2 PIOTR HAJLASZ for all x, y1, y2 ∈ X and α ∈ K. For a space with an inner product we define kxk = phx, xi . Lemma 1.1 (Schwarz inequality).
    [Show full text]
  • Using Functional Analysis and Sobolev Spaces to Solve Poisson’S Equation
    USING FUNCTIONAL ANALYSIS AND SOBOLEV SPACES TO SOLVE POISSON'S EQUATION YI WANG Abstract. We study Banach and Hilbert spaces with an eye to- wards defining weak solutions to elliptic PDE. Using Lax-Milgram we prove that weak solutions to Poisson's equation exist under certain conditions. Contents 1. Introduction 1 2. Banach spaces 2 3. Weak topology, weak star topology and reflexivity 6 4. Lower semicontinuity 11 5. Hilbert spaces 13 6. Sobolev spaces 19 References 21 1. Introduction We will discuss the following problem in this paper: let Ω be an open and connected subset in R and f be an L2 function on Ω, is there a solution to Poisson's equation (1) −∆u = f? From elementary partial differential equations class, we know if Ω = R, we can solve Poisson's equation using the fundamental solution to Laplace's equation. However, if we just take Ω to be an open and connected set, the above method is no longer useful. In addition, for arbitrary Ω and f, a C2 solution does not always exist. Therefore, instead of finding a strong solution, i.e., a C2 function which satisfies (1), we integrate (1) against a test function φ (a test function is a Date: September 28, 2016. 1 2 YI WANG smooth function compactly supported in Ω), integrate by parts, and arrive at the equation Z Z 1 (2) rurφ = fφ, 8φ 2 Cc (Ω): Ω Ω So intuitively we want to find a function which satisfies (2) for all test functions and this is the place where Hilbert spaces come into play.
    [Show full text]
  • Hilbert Space Methods for Partial Differential Equations
    Hilbert Space Methods for Partial Differential Equations R. E. Showalter Electronic Journal of Differential Equations Monograph 01, 1994. i Preface This book is an outgrowth of a course which we have given almost pe- riodically over the last eight years. It is addressed to beginning graduate students of mathematics, engineering, and the physical sciences. Thus, we have attempted to present it while presupposing a minimal background: the reader is assumed to have some prior acquaintance with the concepts of “lin- ear” and “continuous” and also to believe L2 is complete. An undergraduate mathematics training through Lebesgue integration is an ideal background but we dare not assume it without turning away many of our best students. The formal prerequisite consists of a good advanced calculus course and a motivation to study partial differential equations. A problem is called well-posed if for each set of data there exists exactly one solution and this dependence of the solution on the data is continuous. To make this precise we must indicate the space from which the solution is obtained, the space from which the data may come, and the correspond- ing notion of continuity. Our goal in this book is to show that various types of problems are well-posed. These include boundary value problems for (stationary) elliptic partial differential equations and initial-boundary value problems for (time-dependent) equations of parabolic, hyperbolic, and pseudo-parabolic types. Also, we consider some nonlinear elliptic boundary value problems, variational or uni-lateral problems, and some methods of numerical approximation of solutions. We briefly describe the contents of the various chapters.
    [Show full text]
  • 3. Hilbert Spaces
    3. Hilbert spaces In this section we examine a special type of Banach spaces. We start with some algebraic preliminaries. Definition. Let K be either R or C, and let Let X and Y be vector spaces over K. A map φ : X × Y → K is said to be K-sesquilinear, if • for every x ∈ X, then map φx : Y 3 y 7−→ φ(x, y) ∈ K is linear; • for every y ∈ Y, then map φy : X 3 y 7−→ φ(x, y) ∈ K is conjugate linear, i.e. the map X 3 x 7−→ φy(x) ∈ K is linear. In the case K = R the above properties are equivalent to the fact that φ is bilinear. Remark 3.1. Let X be a vector space over C, and let φ : X × X → C be a C-sesquilinear map. Then φ is completely determined by the map Qφ : X 3 x 7−→ φ(x, x) ∈ C. This can be see by computing, for k ∈ {0, 1, 2, 3} the quantity k k k k k k k Qφ(x + i y) = φ(x + i y, x + i y) = φ(x, x) + φ(x, i y) + φ(i y, x) + φ(i y, i y) = = φ(x, x) + ikφ(x, y) + i−kφ(y, x) + φ(y, y), which then gives 3 1 X (1) φ(x, y) = i−kQ (x + iky), ∀ x, y ∈ X. 4 φ k=0 The map Qφ : X → C is called the quadratic form determined by φ. The identity (1) is referred to as the Polarization Identity.
    [Show full text]
  • Notes for Functional Analysis
    Notes for Functional Analysis Wang Zuoqin (typed by Xiyu Zhai) November 13, 2015 1 Lecture 18 1.1 Characterizations of reflexive spaces Recall that a Banach space X is reflexive if the inclusion X ⊂ X∗∗ is a Banach space isomorphism. The following theorem of Kakatani give us a very useful creteria of reflexive spaces: Theorem 1.1. A Banach space X is reflexive iff the closed unit ball B = fx 2 X : kxk ≤ 1g is weakly compact. Proof. First assume X is reflexive. Then B is the closed unit ball in X∗∗. By the Banach- Alaoglu theorem, B is compact with respect to the weak-∗ topology of X∗∗. But by definition, in this case the weak-∗ topology on X∗∗ coincides with the weak topology on X (since both are the weakest topology on X = X∗∗ making elements in X∗ continuous). So B is compact with respect to the weak topology on X. Conversly suppose B is weakly compact. Let ι : X,! X∗∗ be the canonical inclusion map that sends x to evx. Then we've seen that ι preserves the norm, and thus is continuous (with respect to the norm topologies). By PSet 8-1 Problem 3, ∗∗ ι : X(weak) ,! X(weak) is continuous. Since the weak-∗ topology on X∗∗ is weaker than the weak topology on X∗∗ (since X∗∗∗ = (X∗)∗∗ ⊃ X∗. OH MY GOD!) we thus conclude that ∗∗ ι : X(weak) ,! X(weak-∗) is continuous. But by assumption B ⊂ X(weak) is compact, so the image ι(B) is compact in ∗∗ X(weak-∗). In particular, ι(B) is weak-∗ closed.
    [Show full text]
  • The Riesz Representation Theorem
    The Riesz Representation Theorem MA 466 Kurt Bryan Let H be a Hilbert space over lR or Cl, and T a bounded linear functional on H (a bounded operator from H to the field, lR or Cl, over which H is defined). The following is called the Riesz Representation Theorem: Theorem 1 If T is a bounded linear functional on a Hilbert space H then there exists some g 2 H such that for every f 2 H we have T (f) =< f; g > : Moreover, kT k = kgk (here kT k denotes the operator norm of T , while kgk is the Hilbert space norm of g. Proof: Let's assume that H is separable for now. It's not really much harder to prove for any Hilbert space, but the separable case makes nice use of the ideas we developed regarding Fourier analysis. Also, let's just work over lR. Since H is separable we can choose an orthonormal basis ϕj, j ≥ 1, for 2 H. Let T be a bounded linear functionalP and set aj = T (ϕj). Choose f H, n let cj =< f; ϕj >, and define fn = j=1 cjϕj. Since the ϕj form a basis we know that kf − fnk ! 0 as n ! 1. Since T is linear we have Xn T (fn) = ajcj: (1) j=1 Since T is bounded, say with norm kT k < 1, we have jT (f) − T (fn)j ≤ kT kkf − fnk: (2) Because kf − fnk ! 0 as n ! 1 we conclude from equations (1) and (2) that X1 T (f) = lim T (fn) = ajcj: (3) n!1 j=1 In fact, the sequence aj must itself be square-summable.
    [Show full text]
  • Optimal Quantum Observables 3
    OPTIMAL QUANTUM OBSERVABLES ERKKA THEODOR HAAPASALO AND JUHA-PEKKA PELLONPA¨A¨ Abstract. Various forms of optimality for quantum observables described as normalized pos- itive operator valued measures (POVMs) are studied in this paper. We give characterizations for observables that determine the values of the measured quantity with probabilistic certainty or a state of the system before or after the measurement. We investigate observables which are free from noise caused by classical post-processing, mixing, or pre-processing of quantum nature. Especially, a complete characterization of pre-processing and post-processing clean observables is given, and necessary and sufficient conditions are imposed on informationally complete POVMs within the set of pure states. We also discuss joint and sequential measure- ments of optimal quantum observables. PACS numbers: 03.65.Ta, 03.67.–a 1. Introduction A normalized positive operator valued measure (POVM) describes the statistics of the out- comes of a quantum measurement and thus we call them as observables of a quantum system. However, some observables can be considered better than the others according to different cri- teria: The observable may be powerful enough to differentiate between any given initial states of the system or it may be decisive enough to completely determine the state after the mea- surement no matter how we measure this observable. The observable may also be free from different types of noise either of classical or quantum nature or its measurement cannot be reduced to a measurement of a more informational observable from the measurement of which it can be obtained by modifying either the initial state or the outcome statistics.
    [Show full text]
  • Optimization in Infinite-Dimensional Hilbert Spaces
    Optimization in infinite-dimensional Hilbert spaces Alen Alexanderian* Abstract We consider the minimization of convex functionals on a real Hilbert space. The req- uisite theory is reviewed, and concise proofs of the relevant results are given. 1 Introduction We are concerned here with the classical results on optimization of convex function- als in infinite-dimensional real Hilbert spaces. When working with infinite-dimensional spaces, a basic difficulty is that, unlike the case in finite-dimension, being closed and bounded does not imply that a set is compact. In reflexive Banach spaces, this prob- lem is mitigated by working in weak topologies and using the result that the closed unit ball is weakly compact. This in turn enables mimicking some of the same ideas in finite-dimensional spaces when working on unconstrained optimization problems. It is the goal of these note to provide a concise coverage of the problem of minimiza- tion of a convex function on a Hilbert space. The focus is on real Hilbert spaces, where there is further structure that makes some of the arguments simpler. Namely, proving that a closed and convex set is also weakly sequentially closed can be done with an ele- mentary argument, whereas to get the same result in a general Banach space we need to invoke Mazur’s Theorem. The ideas discussed in this brief note are of great utility in theory of PDEs, where weak solutions of problems are sought in appropriate Sobolev spaces. After a brief review of the requisite preliminaries in Sections 2– 4, we develop the main results we are concerned with in Section 5.
    [Show full text]
  • Hilbert Spaces
    Hilbert Spaces Definition. A complex inner product space (or pre-Hilbert space) is a complex vector space X together with an inner product: a function from X × X into C (denoted by hy, xi) satisfying: (1) (∀ x ∈ X) hx, xi ≥ 0 and hx, xi =0 iff x = 0. (2) (∀ α, β ∈ C) (∀ x, y, z ∈ X), hz,αx + βyi = αhz, xi + βhz,yi. (3) (∀ x, y ∈ X) hy, xi = hx, yi Remarks. (2) says the inner product is linear in the second variable; (3) says the inner product is sesquilinear; (2) and (3) imply hαx + βy,zi =α ¯hx, zi + β¯hy, zi, so the inner product is conjugate linear in the first variable. Definition. For x ∈ X, let kxk = hx, xi. p Cauchy-Schwarz Inequality. (∀ x, y ∈ X) |hy, xi| ≤ kxk·kyk, with equality iff x and y are linearly dependent. Proof. The result is obvious if hy, xi = 0. Suppose γ ≡ hy, xi= 6 0. Then x =6 0, y =6 0. Let z = γ|γ|−1y. Then hz, xi =γ ¯|γ|−1hy, xi = |γ| > 0. Let v = xkxk−1, w = zkzk−1. Then kvk = kwk = 1 and hw, vi > 0. Since 0 ≤kv − wk2 = hv, vi − 2Rehw, vi + hw,wi, it follows that hw, vi ≤ 1 (with equality iff v = w, which happens iff x and y are linearly dependent). So |hy, xi| = hz, xi = kxk·kzkhw, vi≤kxk·kzk = kxk·kyk. Facts. (1′) (∀ x ∈ X)kxk ≥ 0; kxk =0 iff x = 0. (2′) (∀ α ∈ C)(∀ x ∈ X) kαxk = |α|·kxk. (3′) (∀ x, y ∈ X) kx + yk≤kxk + kyk.
    [Show full text]
  • Mathematical Introduction to Quantum Information Processing
    Mathematical Introduction to Quantum Information Processing (growing lecture notes, SS2019) Michael M. Wolf June 22, 2019 Contents 1 Mathematical framework 5 1.1 Hilbert spaces . .5 1.2 Bounded Operators . .8 Ideals of operators . 10 Convergence of operators . 11 Functional calculus . 12 1.3 Probabilistic structure of Quantum Theory . 14 Preparation . 15 Measurements . 17 Probabilities . 18 Observables and expectation values . 20 1.4 Convexity . 22 Convex sets and extreme points . 22 Mixtures of states . 23 Majorization . 24 Convex functionals . 26 Entropy . 28 1.5 Composite systems and tensor products . 29 Direct sums . 29 Tensor products . 29 Partial trace . 34 Composite and reduced systems . 35 Entropic quantities . 37 1.6 Quantum channels and operations . 38 Schrödinger & Heisenberg picture . 38 Kraus representation and environment . 42 Choi-matrices . 45 Instruments . 47 Commuting dilations . 48 1.7 Unbounded operators and spectral measures . 51 2 Basic trade-offs 53 2.1 Uncertainty relations . 53 Variance-based preparation uncertainty relations . 54 Joint measurability . 55 2 CONTENTS 3 2.2 Information-disturbance . 56 No information without disturbance . 56 2.3 Time-energy . 58 Mandelstam-Tamm inequalities . 58 Evolution to orthogonal states . 59 These are (incomplete but hopefully growing) lecture notes of a course taught in summer 2019 at the department of mathematics at the Technical University of Munich. 4 CONTENTS Chapter 1 Mathematical framework 1.1 Hilbert spaces This section will briefly summarize relevant concepts and properties of Hilbert spaces. A complex Hilbert space is a vector space over the complex numbers, equipped with an inner product h·; ·i : H × H ! C and an induced norm k k := h ; i1=2 w.r.t.
    [Show full text]
  • Hilbert Space Quantum Mechanics
    qitd114 Hilbert Space Quantum Mechanics Robert B. Griffiths Version of 16 January 2014 Contents 1 Introduction 1 1.1 Hilbertspace .................................... ......... 1 1.2 Qubit ........................................... ...... 2 1.3 Intuitivepicture ................................ ........... 2 1.4 General d ............................................... 3 1.5 Ketsasphysicalproperties . ............. 4 2 Operators 5 2.1 Definition ....................................... ........ 5 2.2 Dyadsandcompleteness . ........... 5 2.3 Matrices........................................ ........ 6 2.4 Daggeroradjoint................................. .......... 7 2.5 Normaloperators................................. .......... 7 2.6 Hermitianoperators .............................. ........... 8 2.7 Projectors...................................... ......... 8 2.8 Positiveoperators............................... ............ 9 2.9 Unitaryoperators................................ ........... 9 3 Bloch sphere 10 4 Composite systems and tensor products 11 4.1 Definition ....................................... ........ 11 4.2 Productandentangledstates . ............. 11 4.3 Operatorsontensorproducts . ............. 12 4.4 Exampleoftwoqubits .............................. .......... 12 4.5 Multiplesystems. Identicalparticles . .................. 13 References: CQT = Consistent Quantum Theory by Griffiths (Cambridge, 2002), Ch. 2; Ch. 3; Ch. 4 except for Sec. 4.3; Ch. 6. QCQI = Quantum Computation and Quantum Information by Nielsen and Chuang (Cambridge,
    [Show full text]
  • THE C∗-ALGEBRAIC FORMALISM of QUANTUM MECHANICS Contents 1. Introduction 1 2. a Brief Look at Classical Mechanics 2 3. What'
    THE C∗-ALGEBRAIC FORMALISM OF QUANTUM MECHANICS JONATHAN JAMES GLEASON Abstract. In this paper, by examining the more tangible, more physically intuitive classical mechanics, we aim to motivate more natural axioms of quan- tum mechanics than those usually given in terms of Hilbert spaces. Specifically, we plan to replace the assumptions that observable are self-adjoint operators on a separable Hilbert space and states are normalized vectors in that Hilbert space with more natural assumptions about the observables and states in terms of C∗-algebras. Then, with these assumptions in place, we plan to derive the aforementioned assumptions about observables and states in terms of Hilbert spaces from our new assumptions about observables and states in terms of C∗-algebras. Contents 1. Introduction 1 2. A Brief Look at Classical Mechanics 2 3. What’s Wrong with Classical Mechanics 4 4. The Theory of C∗-Algebras 7 5. The Theory of Hilbert Spaces 7 6. Quantum Mechanics from the Ground Up 8 7. Closing Comments 17 8. Appendix: Definitions 18 Acknowledgments 20 References 20 1. Introduction If you are familiar with the usual mathematical formulation of quantum mechan- ics (i.e., the states are elements of a separable Hilbert space and the observables self-adjoint linear operators on that space), then you have certainly realized that this mathematical formulation is starkly different from the mathematical formula- tion used in Classical Mechanics. In classical mechanics, at a very early stage one is usually introduced to the Newtonian formalism of classical mechanics, and as the student progresses through his or her study of physics, in particular mechanics, they are eventually introduced to the Hamiltonian formalism of classical mechanics and they are shown that this formalism is in fact equivalent to the Newtonian formalism.
    [Show full text]