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Europhysics Letters (EPL)

Quantum-mechanical retrodiction through an extended mean king problem

Amir Kalev, A. Mann, M. Revzen

Published Dec 1, 2013• 7 citations
Publisher

Abstract

The mean king problem is a conditional retrodiction problem. In this problem Alice prepares a two prime-dimensional particles state and avails one of the particles to the king who measures its state in one of mutually unbiased bases of his choice. The king tells Alice his choice of basis after she completes a control measurement on his particle. Conditioned on this knowledge, she now infers the state observed by the king by utilizing the outcome of her control measurement. In the extended mean king problem, studied in this paper, the king does not tell Alice his measurement basis, but instead both the king and Alice repeat their measurements. Proper ordering of these allows Alice to deduce both the basis used by the king and the outcome of his first measurement, with the king reticent throughout, i.e., this protocol effects a (almost) complete retrodiction of the king's first measurement.

DOI
10.1209/0295-5075/104/50008

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Quantum mechanical retrodiction through an extended mean King problem

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The mean King problem is a conditional retrodiction problem. In this problem Alice prepares a two prime-dimensional particles state and avails one of the particles to the King who measures its state in one of mutually unbiased bases of his choice. The King tells Alice his choice of basis after she completes a control measurement on his particle. Conditioned on this knowledge, she now infers the state observed by the King by utilizing the outcome of her control measurement. In the extended mean King problem, studied in this paper, the King does not tell Alice his measurement basis, but instead both the King and Alice repeat their measurements. Proper ordering of these allows Alice to deduce both the basis used by the King and the outcome of his first measurement, with the King reticent throughout, i.e., this protocol effects a complete (almost) retrodiction of the King's first measurement.

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The mean king problem is a conditional retrodiction problem. In this problem Alice prepares a two prime-dimensional particles state and avails one of the particles to the king who measures its state in one of mutually unbiased bases of his choice. The king tells Alice his choice of basis after she completes a control measurement on his particle. Conditioned on this knowledge, she now infers the state observed by the king by utilizing the outcome of her control measurement. In the extended mean king problem, studied in this paper, the king does not tell Alice his measurement basis, but instead both the king and Alice repeat their measurements. Proper ordering of these allows Alice to deduce both the basis used by the king and the outcome of his first measurement, with the king reticent throughout, i.e., this protocol effects a (almost) complete retrodiction of the king's first measurement.
The mean King problem is a conditional retrodiction problem. In this problem Alice prepares a two prime-dimensional particles state and avails one of the particles to the King who measures its state in one of mutually unbiased bases of his choice. The King tells Alice his choice of basis after she completes a control measurement on his particle. Conditioned on this knowledge, she now infers the state observed by the King by utilizing the outcome of her control measurement. In the extended mean King problem, studied in this paper, the King does not tell Alice his measurement basis, but instead both the King and Alice repeat their measurements. Proper ordering of these allows Alice to deduce both the basis used by the King and the outcome of his first measurement, with the King reticent throughout, i.e., this protocol effects a complete (almost) retrodiction of the King's first measurement.
The mean king problem is a quantum mechanical retrodiction problem, in which Alice has to name the outcome of an ideal measurement made in one of several different orthonormal bases. Alice is allowed to prepare the state of the system and to do a final measurement, possibly including an entangled copy. However, Alice gains knowledge about which basis was measured only after she no longer has access to the quantum system or its copy. We give a necessary and sufficient condition on the bases, for Alice to have a strategy to solve this problem, without assuming that the bases are mutually unbiased. The condition requires the existence of an overall joint probability distribution for random variables, whose marginal pair distributions are fixed as the transition probability matrices of the given bases. In particular, in the qubit case the problem is decided by Bell's original three variable inequality. In the standard setting of mutually unbiased bases, when they do exist, Alice can always succeed. However, for randomly chosen bases her success probability rapidly goes to zero with increasing dimension.
In quantum theory, the retrodiction problem is not as clear as its classical counterpart because of the uncertainty principle of quantum mechanics. In classical physics, the measurement outcomes of the present state can be used directly for predicting the future events and inferring the past events which is known as retrodiction. However, as a probabilistic theory, quantum-mechanical retrodiction is a nontrivial problem that has been investigated for a long time, of which the Mean King Problem is one of the most extensively studied issues. Here, we present the first experimental test of a variant of the Mean King Problem, which has a more stringent regulation and is termed "Tracking the King." We demonstrate that Alice, by harnessing the shared entanglement and controlled-not gate, can successfully retrodict the choice of King's measurement without knowing any measurement outcome. Our results also provide a counterintuitive quantum communication to deliver information hidden in the choice of measurement.
In the Mean King's Problem a ship-wrecked physicist is challenged to infer the outcome of an intermediate spin measurement by a suitable preparation in conjunction with an appropriate control measurement -- the 1987 spin retrodiction puzzle of Vaidman, Aharonov, and Albert. We report the experimental realization of a quantum-optical version in which the outcome of an intermediate polarization projection is inferred by exploiting single-photon two-qubit states. The experimental success probability is consistently above the 90.2% threshold of the optimal one-qubit strategy, with an average success probability of 95.6%.
In this thesis, we study several variants of the Mean King problem from the perspective of quantum information and optimization. The Mean King problem is a quantum guessing task, where one party prepares a quantum state, another party performs a measurement chosen from a given set of bases, and the first party tries to guess the measurement outcome. We consider four variants of this problem, including both non-interactive and interactive settings. We analyze their optimal guessing performance in both the average-case and the worst-case settings. We formulate the success probabilities of these Mean King games as optimization problems over quantum states and measurement strategies. This approach gives a unified way to study the different variants. For the non-interactive games, we derive the winning operators and show that some of the optimization problems can be reduced to eigenvalue computations. For the interactive games, we formulate them as semidefinite programs. These programs include extra constraints that come from returned information and partial trace conditions. These formulations support both theoretical analysis and numerical computation. We use MATLAB and CVX to compute optimal success probabilities for several choices of measurement bases. These bases include mutually unbiased bases and rotated bases. The results show how the choice of measurement bases affects the guessing probability. The results also show the difference between average-case and worst-case performance across different Mean King variants. In particular, in one variant, the numerical results for two and three mutually unbiased bases are close to the known success probabilities of the 2 → 1 and 3 → 1 quantum random access code tasks. These numerical similarities suggest that Mean King problems and random access codes may share a deeper connection. This observation gives a possible direction for future work.