Summary form only given. We show how to discriminate between overcomplete sets of quantum states with minimum error probabilities. It is not possible to distinguish reliably between non-orthogonal states, but given a specific set of N states (N>2 for a two-state system) one can ask how well can they be distinguished. The answer is different depending on whether you want the minimum error, or the maximum information.
Summary form only given. We show how to discriminate between overcomplete sets of quantum states with minimum error probabilities. It is not possible to distinguish reliably between non-orthogonal states, but given a specific set of N states (N>2 for a two-state system) one can ask how well can they be distinguished. The answer is different depending on whether you want the minimum error, or the maximum information.
Distinguishing different quantum states is a fundamental task having practical applications in information processing. Despite the effort devoted so far, however, strategies for optimal discrimination are known only for specific examples. In this paper we consider the problem of minimum-error quantum state discrimination where one attempts to minimize the average error. We show the general structure of minimum-error state discrimination as well as useful properties to derive analytic solutions. Based on the general structure, we present a geometric formulation of the problem, which can be applied to cases where quantum state geometry is clear. We also introduce equivalent classes of sets of quantum states in terms of minimum-error discrimination: sets of quantum states in an equivalent class that share the same guessing probability. In particular, for qubit states where the state geometry is found with the Bloch sphere, we illustrate that for an arbitrary set of qubit states, the minimum-error state discrimination with equal prior probabilities can be analytically solved, that is, optimal measurement and the guessing probability are explicitly obtained.
We consider two different optimized measurement strategies for the discrimination of nonorthogonal quantum states. The first is ambiguous discrimination with a minimum probability of inferring an erroneous result, and the second is unambiguous, i.e., error-free, discrimination with a minimum probability of getting an inconclusive outcome, where the measurement fails to give a definite answer. For distinguishing between two mixed quantum states, we investigate the relation between the minimum-error probability achievable in ambiguous discrimination, and the minimum failure probability that can be reached in unambiguous discrimination of the same two states. The latter turns out to be at least twice as large as the former for any two given states. As an example, we treat the case where the state of the quantum system is known to be, with arbitrary prior probability, either a given pure state, or a uniform statistical mixture of any number of mutually orthogonal states. For this case we derive an analytical result for the minimum probability of error and perform a quantitative comparison with the minimum failure probability.
Unambiguous discrimination among non-orthogonal but linearly independent quantum states is possible with a certain probability of success. Here we consider a variant of that problem; rather than discriminating among all of the different states, we shall discriminate between two subsets of them. In particular, for the case of 3 states, we find the optimal strategy to distinguish one from the other two. This procedure has a higher probability of success than distinguishing all 3 states. We show how to construct generalized interferometers that provide an implementation of the optimal strategy.
The problem of discriminating between non-orthogonal states is one that has generated a lot of interest. This basic formalism is useful in many areas of quantum information. It serves as a fundamental basis for many quantum key distribution schemes, it functions as an integral part of other quantum algorithms, and it is useful in experimental settings where orthogonal states are not always possible to generate. Additionally, the discrimination problem reveals important fundamental properties, and is intrinsically related to entanglement. In this thesis, the focus is on exploring the problem of sequentially discriminating between non-orthogonal states. In the simplest version these schemes, Alice sends one of two known pure states to Bob who performs a non-optimal discrimination procedure such that the post measurement states resulting from his measurement can then be discriminated by a third participant, Charlie. In these schemes, the goal is to optimize the joint probability of both Bob and Charlie succeeding. In devising such a scheme, there are several different criteria that can be prioritized. The most basic scheme, referred to as Minimum Error (ME) discrimination, prioritizes Bob's and Charlie's abilities to successfully determine which state was sent by Alice. In this scheme, Bob and Charlie each set up two detectors and based on the result from the detector they make a guess as to which state was sent. For instance, if Bob registers a click in his first detector, he concludes that Alice sent the first state. As each detector has some probability to produce a result for either incoming result, Bob and Charlie optimize their joint probability of success by optimizing the probability that each detector will fire when the correlated state is sent by Alice. Another possible scheme, referred to as Unambiguous Discrimination (UD), prioritizes Bob's and Charlie's ability to correctly determine the state sent by Alice. In this scheme, Bob and Charlie each set up three detectors, where if a result is obtained from the first two detectors Bob or Charlie can determine with certainty which state was sent by Alice. One final setup, referred to as Discrimination with a Fixed Rate of Inconclusive Outcome, is a combination of the previous two schemes, where Bob and Charlie maximize their probability of successfully determining the state sent by Alice where they allow some fixed probability that they will not be able to determine which state Alice sent. This fixed inconclusive probability allows Bob and Charlie to control how much they prioritize correctly determining the state that was sent, as in the Unambiguous Discrimination, versus prioritizing successfully determining the state sent by Alice, as in Minimum Error discrimination. One final topic that will be discussed by this thesis is Quantum Retrodiction. Quantum Retrodiction applies an alternate perspective on the communication protocol between Alice and Bob. In the predictive model, Alice calculates the probability that Bob gets a specific measurement result given that she prepares her system in a specific state. In the retrodictive model, Bob calculates the probability that Alice prepared her system in a specific state given the result of his measurement. This alternate perspective on the communication procedure gives new a new understanding and new tools for approaching the problem of state discrimination, as exemplified by applying the retrodictive formalism to unambiguous discrimination.
We present the solution to the problem of optimally discriminating among quantum states, i.e., identifying the states with maximum probability of success when a certain fixed rate of inconclusive answers is allowed. By varying the inconclusive rate, the scheme optimally interpolates between unambiguous and minimum error discrimination, the two standard approaches to quantum state discrimination. We introduce a very general method that enables us to obtain the solution in a wide range of cases and give a complete characterization of the minimum discrimination error as a function of the rate of inconclusive answers. A critical value of this rate is identified that coincides with the minimum failure probability in the cases where unambiguous discrimination is possible and provides a natural generalization of it when states cannot be unambiguously discriminated. The method is illustrated on two explicit examples: discrimination of two pure states with arbitrary prior probabilities and discrimination of trine states.
We show a geometric formulation for minimum-error discrimination of qubit states that can be applied to arbitrary sets of qubit states given with arbitrary a priori probabilities. In particular, when qubit states are given with equal a priori probabilities, we provide a systematic way of finding optimal discrimination and the complete solution in a closed form. This generally gives a bound to cases when prior probabilities are unequal. Then it is shown that the guessing probability does not depend on detailed relations among the given states, such as the angles between them, but on a property that can be assigned by the set of given states itself. This also shows how a set of quantum states can be modified such that the guessing probability remains the same. Optimal measurements are also characterized accordingly, and a general method of finding them is provided.