Entropy is a key measure in studies related to information theory and its many applications. Campbell of the first time recognized that exponential of Shannon’s entropy is just the size of the sample space when the distribution is uniform. In this paper, we introduce a quantity which is called exponential Tsallis-Havrda-Charvat entropy and discuss its some properties. Further, we gave the appli...

Near-critical quantum circuits close to equilibrium are ideal physical systems for asymptotically large-scale quantum computers, because their low energy collective excitations evolve reversibly, effectively isolated from microscopic environmental fluctuations by the renormalization group. Entropy flows in near-critical quantum circuits near equilibrium as a locally conserved quantum current, o...

Received (received date) Revised (revised date) Quantum relative entropy D(ρσ) def = Tr ρ(log ρ − log σ) plays an important role in quantum information and related fields. However, there are many quantum analogues of relative entropy. In this paper, we characterize these analogues from information geometrical viewpoint. We also consider the naturalness of quantum relative entropy among these an...

If a measurement process is regarded as an irreversible process, then by Second law of thermodynamics the entropy should increase after any measurement process. By the same spirit a quantum system undergoing repeated measurement should show strong irreversibility leading to entropy production. On the contrary we show that in quantum Zeno effect setting the entropy of a quantum system decreases ...

Estimation of Shannon and Rényi entropies of unknown discrete distributions is a fundamental problem in statistical property testing and an active research topic in both theoretical computer science and information theory. Tight bounds on the number of samples to estimate these entropies have been established in the classical setting, while little is known about their quantum counterparts. In t...

A quantum random number generator is implemented in an integrated circuit without the need for complex, bulky and expensive measurement equipment and circuitry. Quantum entropy, chaotic entropy and pseudo-entropy are defined and their combinations mathematically described. Models and design equations are provided for estimating the quantum entropy in the form of shot noise due to sub-threshold ...

We introduce ways to measure information storage in quantum systems, using a recently introduced computation-theoretic model that accounts for measurement effects. The first, the quantum excess entropy, quantifies the shared information between a quantum process’s past and its future. The second, the quantum transient information, determines the difficulty with which an observer comes to know t...

The study of mutual entropy (information) and capacity in classical system was extensively done after Shannon by several authors like Kolmogorov [16] and Gelfand [10]. In quantum systems, there have been several definitions of the mutual entropy for classical input and quantum output [5, 11, 12, 17]. In 1983, the author defined [21] the fully quantum mechanical mutual entropy by means of the re...

The random matrix ensembles (RME), especially Gaussian random matrix ensembles GRME and Ginibre random matrix ensembles, are applied to following quantum systems: nuclear systems, molecular systems, and two-dimensional electron systems (Wigner-Dyson electrostatic analogy). Measures of quantum chaos and quantum integrability with respect to eigenergies of quantum systems are defined and calculat...

The von Neumann entropy plays a vital role in quantum information theory. As the Shannon entropy does in classical information theory, the von Neumann entropy determines the capacities of quantum channels. Quantum entropies of composite quantum systems are important for future quantum network communication their characterization is related to the so called quantum marginal problem. Furthermore,...