For a collection of states indexed by $[n]={1,\ldots,n}$, let $F(H)$ denote the optimal unnormalized minimum discrimination error for each nonempty subfamily $H\subseteq[n]$. We call $F$ the discrimination profile and characterize exactly which profiles can arise in a general probabilistic theory (GPT). For fixed $n$, the GPT region $\mathfrak{G}_n$ is a bounded rational polytope, giving a hierarchy $\mathfrak{C}_n\subseteq\mathfrak{Q}_n\subseteq\mathfrak{G}_n$ of classical, quantum, and GPT profiles, analogous to the local--quantum--no-signalling hierarchy in Bell theory.
For $n=3$ we determine the classical and GPT polytopes explicitly. Within $\mathfrak{G}_3$, the classical region is characterized by $β:=F(123)-F(12)-F(13)-F(23)\le0$, while the GPT maximum is $1$. For qubit triples, the maximal value is attained by the trine, $β_{\mathrm{tr}}=3\sqrt3/2-2$, and we prove the dimension-independent quantum bound $β_{\mathrm Q}\le2/3$, with a slight further improvement. Hence $0=β_{\mathrm C}<3\sqrt3/2-2\leβ_{\mathrm Q}\le2/3<1=β_{\mathrm{GPT}}$. We conjecture $β_{\mathrm Q}=β_{\mathrm{tr}}$ and prove this for arbitrary pure-state triples, together with further supporting evidence.
For arbitrary $n$, every classical facet admitting a GPT violation already admits a quantum violation in dimension at most $3$. A four-state qubit example shows that quantum success profiles need not be submodular, unlike for $n=3$. Finally, we exhibit a four-dimensional quantum triple whose discrete profile is classical for all subfamilies but becomes nonclassical when unequal priors are allowed.
For a collection of states indexed by [n]=1,…,n, let F(H) denote the optimal unnormalized minimum discrimination error for each nonempty subfamily H⊆[n]. We call F the discrimination profile and characterize exactly which profiles can arise in a general probabilistic theory (GPT). For fixed n, the GPT region Gn is a bounded rational polytope, giving a hierarchy Cn⊆Qn⊆Gn of classical, quantum, and GPT profiles, analogous to the local--quantum--no-signalling hierarchy in Bell theory.
For n=3 we determine the classical and GPT polytopes explicitly. Within G3, the classical region is characterized by β:=F(123)−F(12)−F(13)−F(23)≤0, while the GPT maximum is 1. For qubit triples, the maximal value is attained by the trine, βtr=33/2−2, and we prove the dimension-independent quantum bound βQ≤2/3, with a slight further improvement. Hence 0=βC<33/2−2≤βQ≤2/3<1=βGPT. We conjecture βQ=βtr and prove this for arbitrary pure-state triples, together with further supporting evidence.
For arbitrary n, every classical facet admitting a GPT violation already admits a quantum violation in dimension at most 3. A four-state qubit example shows that quantum success profiles need not be submodular, unlike for n=3. Finally, we exhibit a four-dimensional quantum triple whose discrete profile is classical for all subfamilies but becomes nonclassical when unequal priors are allowed.
Abstract It is a key issue to characterize the model of standard quantum theory out of general models by an operational condition. The framework of general probabilistic theories (GPTs) is a new information theoretical approach to single out standard quantum theory. It is known that traditional properties, for example, Bell-CHSH inequality, are not sufficient to single out standard quantum theory among possible models in GPTs. As a more precise property, we focus on the bound of the performance for an information task called state discrimination in general models. We give an equivalent condition for outperforming the minimum discrimination error probability under the standard quantum theory given by the trace norm. Besides, by applying the equivalent condition, we characterize standard quantum theory out of general models in GPTs by the bound of the performance for state discrimination.
General probabilistic theories (GPTs) are theoretical models having states, measurements, and probabilities of obtaining measurement outcomes.For example, classical probability theory and quantum theory are GPTs with probability vectors and density matrices as states, respectively.In the study of GPTs, one often describes a finite number of GPTs A 1 , . . ., A n together, as one GPT A = A 1 • • • A n .In this case, we say that A is a whole system of subsystems A 1 , . . ., A n .If A 1 , . . ., A n are quantum systems, then A is called a locally quantum system.A quantum system is locally quantum, but there are many other locally quantum systems.In this thesis, we study three topics associated with quantum systems and locally quantum systems.The first one is capacity.For a GPT, the maximum number of simultaneously and perfectly distinguishable states is called the capacity.It is known that the capacity does not really depend on the GPT.In this thesis, we propose a statement S to determine the capacities of special locally quantum systems, and prove a weaker statement WS.Statement WS is a statement associated with tensor product spaces over C. Our proof works even if replacing the scalar field C with an arbitrary infinite field F. We also show a partial result for finite fields.The second one is differential privacy (DP).DP was born in the study to utilize private data while protecting the data (privacy-preserving data mining, PPDM).For this reason, DP has been studied by using classical probability theory, and has almost never been studied in quantum information theory.In this thesis, we define a quantum version of DP (called classical-quantum DP) and investigate its mathematical aspects.We define the set CQ n of all classical-quantum differentially private n-tuples of quantum states and the subset EC n of CQ n that is essentially classical.We prove that EC n = CQ n if n = 2 and EC n = CQ n if n ≥ 3.The third one is perfect discrimination of two states.In quantum theory, orthogonality is a necessary and sufficient condition to distinguish two states perfectly (denote this equivalence by E).However, equivalence E does not hold for a general GPT.In this thesis, we construct continuous one-parameter families of locally quantum systems in a certain natural manner, and investigate perfect discrimination of two states in the framework of those locally quantum systems.These one-parameter families contain a locally quantum system sufficiently close to a quantum system.Nevertheless, we show that they violate equivalence E.
This work investigates which sets of quantum states give rise to the highest achievable success probability in minimum-error state discrimination if multiple copies of the unknown state are given. Specifically, we consider uniformly distributed ensembles of the form {N1,ρi⊗k}i=1N, where N states in dimension d are provided in k identical copies, and derive universal limits in this scenario. For pure state ensembles, we prove that whenever N is large enough to support a state k-design, these designs will exactly give rise to the maximally discriminable sets. We further show that when N exceeds the size required for a k-design, mixed states can outperform all pure state ensembles. We then recognise that the problem of most discriminable classical states in the multi-copy regime is in one-to-one correspondence to the concept of the multiplicative Bayes capacity of independent uses of classical channels, a concept that emerges naturally in the context of classical information leakage. This connection allows us to completely solve the classical analogue of our problem when N≥(kd+k−1), and to prove that quantum systems offer a quadratic advantage (in number of copies k) over classical ones. Then, we prove that this quantum over classical advantage is strongly reduced when one is restricted to real quantum states, more precisely, when N≥k+1, pure real qubits only offer a constant advantage over classical bits. Finally, we introduce computational techniques to find sets of most discriminable ensembles and to obtain rigorous universal upper bounds on the maximal success probability for multi-copy state discrimination in cases that are analytically intractable.
Quantum state discrimination is a fundamental task in the field of quantum communication and quantum information theory. Unless the states to be discriminated are mutually orthogonal, there will be some error in any attempt to determine which state was sent. Several strategies to optimally discriminate between quantum states exist, each maximising some figure of merit. In this thesis we mainly investigate the minimum-error strategy, in which the probability of correctly guessing the signal state is maximised. We introduce a method for constructing the optimal Positive-Operator Valued Measure (POVM) for this figure of merit, which is applicable for arbitrary states and arbitrary prior probabilities. We then use this method to solve minimum-error state discrimination for the so-called trine states with arbitrary prior probabilities - the first such general solution for a set of quantum states since the two-state case was solved when the problem of state discrimination was first introduced. We also investigate the difference between local and global measurements for a bipartite ensemble of states, and find that in certain circumstances the local measurement is superior. We conclude by finding a bipartite analogue to the Helstrom conditions, which indicate when a POVM satisfies the minimum-error criteria.
Many experiments in the field of quantum foundations seek to adjudicate between quantum theory and speculative alternatives to it.This requires one to analyze the experimental data in a manner that does not presume the correctness of the quantum formalism.The mathematical framework of generalized probabilistic theories (GPTs) provides a means of doing so.We present a scheme for determining which GPTs are consistent with a given set of experimental data.It proceeds by performing tomography on the preparations and measurements in a self-consistent manner, i.e., without presuming a prior characterization of either.We illustrate the scheme by analyzing experimental data for a large set of preparations and measurements on the polarization degree of freedom of a single photon.We first test various hypotheses for the dimension of the GPT vector space for this degree of freedom.Our analysis identifies the most plausible hypothesis to be dimension 4, which is the value predicted by quantum theory.Under this hypothesis, we can draw the following additional conclusions from our scheme: (i) that the smallest and largest GPT state spaces that could describe photon polarization are a pair of polytopes, each approximating the shape of the Bloch sphere and having a volume ratio of 0.977 ± 0.001, which provides a quantitative bound on the scope for deviations from the state and effect spaces predicted by quantum theory, and (ii) that the maximal violation of the Clauser, Horne, Shimony, and Holt inequality can be at most 1.3% ± 0.1 greater than the maximum violation allowed by quantum theory, and the maximal violation of a particular inequality for universal noncontextuality can not differ from the quantum prediction by more than this factor on either side.The only possibility for a greater deviation from the quantum state and effect spaces or for greater degrees of supraquantum nonlocality or contextuality, according to our analysis, is if a future experiment (perhaps following the scheme developed here) discovers that additional dimensions of GPT vector space are required to describe photon polarization, in excess of the four dimensions predicted by quantum theory to be adequate to the task.
Abstract Associative memories are devices storing information that can be fully retrieved given partial disclosure of it. We examine a toy model of associative memory and the ultimate limitations to which it is subjected within the framework of general probabilistic theories (GPTs), which represent the most general class of physical theories satisfying some basic operational axioms. We ask ourselves how large the dimension of a GPT should be so that it can accommodate 2 m states with the property that any N of them are perfectly distinguishable. Call d ( N , m ) the minimal such dimension. Invoking an old result by Danzer and Grünbaum, we prove that d ( 2 , m ) = m + 1 , to be compared with O ( 2 m ) when the GPT is required to be either classical or quantum. This yields an example of a task where GPTs outperform both classical and quantum theory exponentially. More generally, we resolve the case of fixed N and asymptotically large m, proving that d ( N , m ) ⩽ m 1 + o N ( 1 ) (as m → ∞ ) for every N ⩾ 2 , which yields again an exponential improvement over classical and quantum theories. Finally, we develop a numerical approach to the general problem of finding the largest N-wise mutually distinguishable set for a given GPT, which can be seen as an instance of the maximum clique problem on N-regular hypergraphs.