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Register a new userAnalysing causal structures using Tsallis entropies
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Understanding cause-effect relationships is a crucial part of the scientific process. As Bells theorem shows, within a given causal structure, classical and quantum physics impose different constraints on the correlations that are realisable, a fundamental feature that has technological applications. However, in general it is difficult to distinguish the set of classical and quantum correlations within a causal structure. Here we investigate a method to do this based on using entropy vectors for Tsallis entropies. We derive constraints on the Tsallis entropies that are implied by (conditional) independence between classical random variables and apply these to causal structures. We find that the number of independent constraints needed to characterise the causal structure is prohibitively high such that the computations required for the standard entropy vector method cannot be employed even for small causal structures. Instead, without solving the whole problem, we find new Tsallis entropic constraints for the triangle causal structure by generalising known Shannon constraints. Our results reveal new mathematical properties of classical and quantum Tsallis entropies and highlight difficulties of using Tsallis entropies for analysing causal structures.
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We initiate the study of relative operator entropies and Tsallis relative operator entropies in the setting of JB-algebras. We establish their basic properties and extend the operator inequalities on relative operator entropies and Tsallis relative operator entropies to this setting. In addition, we improve the lower and upper bounds of the relative operator $(alpha, beta)$-entropy in the setting of JB-algebras that were established in Hilbert space operators setting by Nikoufar [18, 20]. Though we employ the same notation as in the classical setting of Hilbert space operators, the inequalities in the setting of JB-algebras have different connotations and their proofs requires techniques in JB-algebras.
The Tsallis and Renyi entropies are important quantities in the information theory, statistics and related fields because the Tsallis entropy is an one parameter generalization of the Shannon entropy and the Renyi entropy includes several useful entropy measures such as the Shannon entropy, Min-entropy and so on, as special choices of its parameter. On the other hand, the discrete-time quantum walk plays important roles in various applications, for example, quantum speed-up algorithm and universal computation. In this paper, we show limiting behaviors of the Tsallis and Renyi entropies for discrete-time quantum walks on the line which are starting from the origin and defined by arbitrary coin and initial state. The results show that the Tsallis entropy behaves in polynomial order of time with the parameter dependent exponent while the Renyi entropy tends to infinity in logarithmic order of time independent of the choice of the parameter. Moreover, we show the difference between the Renyi entropy and the logarithmic function characterizes by the Renyi entropy of the limit distribution of the quantum walk. In addition, we show an example of asymptotic behavior of the conditional Renyi entropies of the quantum walk.
The Renyi and Tsallis entropies are discussed as possible alternatives to the Bekenstein-Hawking area-law entropy. It is pointed out how replacing the entropy notion, but not the Hawking temperature and the thermodynamical energy may render the whole black hole thermodynamics inconsistent. The possibility to relate the Renyi and Tsallis entropies with the quantum gravity corrected Bekenstein-Hawking entropy is discussed.
The constraints arising for a general set of causal relations, both classically and quantumly, are still poorly understood. As a step in exploring this question, we consider a coherently controlled superposition of direct-cause and common-cause relationships between two events. We propose an implementation involving the spatial superposition of a mass and general relativistic time dilation. Finally, we develop a computationally efficient method to distinguish such genuinely quantum causal structures from classical (incoherent) mixtures of causal structures and show how to design experimental verifications of the nonclassicality of a causal structure.
Quantum operations are the most widely used tool in the theory of quantum information processing, representing elementary transformations of quantum states that are composed to form complex quantum circuits. The class of quantum transformations can be extended by including transformations on quantum operations, and transformations thereof, and so on up to the construction of a potentially infinite hierarchy of transformations. In the last decade, a sub-hierarchy, known as quantum combs, was exhaustively studied, and characterised as the most general class of transformations that can be achieved by quantum circuits with open slots hosting variable input elements, to form a complete output quantum circuit. The theory of quantum combs proved to be successful for the optimisation of information processing tasks otherwise untreatable. In more recent years the study of maps from combs to combs has increased, thanks to interesting examples showing how this next order of maps requires entanglement of the causal order of operations with the state of a control quantum system, or, even more radically, superpositions of alternate causal orderings. Some of these non-circuital transformations are known to be achievable and have even been achieved experimentally, and were proved to provide some computational advantage in various information-processing tasks with respect to quantum combs. Here we provide a formal language to form all possible types of transformations, and use it to prove general structure theorems for transformations in the hierarchy. We then provide a mathematical characterisation of the set of maps from combs to combs, hinting at a route for the complete characterisation of maps in the hierarchy. The classification is strictly related to the way in which the maps manipulate the causal structure of input circuits.
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