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In this paper, for a given family of constraints and the classical Cantor distribution we determine the constrained optimal sets of $n$-points, $n$th constrained quantization errors for all positive integers $n$. We also calculate the…

Dynamical Systems · Mathematics 2024-03-05 Megha Pandey , Mrinal Kanti Roychowdhury

This paper considers lossy source coding of $n$-dimensional memoryless sources and shows an explicit approximation to the minimum source coding rate required to sustain the probability of exceeding distortion $d$ no greater than $\epsilon$,…

Information Theory · Computer Science 2017-02-28 Victoria Kostina

Phase-space versions of quantum mechanics -- from Wigner's original distribution to modern discrete-qudit constructions -- represent some states with negative quasi-probabilities. Conventional Shannon and R\'enyi entropies become…

Quantum Physics · Physics 2025-12-23 Adam Brandenburger , Pierfrancesco La Mura

We show that the method of distributed noise-shaping beta-quantization offers superior performance for the problem of spectral super-resolution with quantization whenever there is redundancy in the number of measurements. More precisely, if…

Information Theory · Computer Science 2019-05-06 C. Sinan Güntürk , Weilin Li

The relative entropy between quantum states quantifies their distinguishability. The estimation of certain relative entropies has been investigated in the literature, e.g., the von Neumann relative entropy and sandwiched R\'enyi relative…

Quantum Physics · Physics 2026-02-24 Jinge Bao , Minbo Gao , Qisheng Wang

We consider the problem of approximating the empirical Shannon entropy of a high-frequency data stream under the relaxed strict-turnstile model, when space limitations make exact computation infeasible. An equivalent measure of entropy is…

Computation · Statistics 2013-04-18 Peter Clifford , Ioana Ada Cosma

For variable-length coding with an almost-sure distortion constraint, Zhang et al. show that for discrete sources the redundancy is upper bounded by $\log n/n$ and lower bounded (in most cases) by $\log n/(2n)$, ignoring lower order terms.…

Information Theory · Computer Science 2026-01-21 Sharang M. Sriramu , Aaron B. Wagner

Many modern distributed real-time signal sensing/monitoring systems require quantization for efficient signal representation. These distributed sensors often have inherent computational and energy limitations. Motivated by this concern, we…

Signal Processing · Electrical Eng. & Systems 2019-02-19 Vijay Anavangot , Animesh Kumar

We investigate the computational hardness of estimating the quantum $\alpha$-R\'enyi entropy ${\rm S}^{\tt R}_{\alpha}(\rho) = \frac{\ln {\rm Tr}(\rho^\alpha)}{1-\alpha}$ and the quantum $q$-Tsallis entropy ${\rm S}^{\tt T}_q(\rho) =…

Quantum Physics · Physics 2026-04-08 Yupan Liu

We prove a tight uniform continuity bound for Arimoto's version of the conditional $\alpha$-R\'enyi entropy, for the range $\alpha \in [0, 1)$. This definition of the conditional R\'enyi entropy is the most natural one among the multiple…

Information Theory · Computer Science 2022-03-29 Michael G. Jabbour , Nilanjana Datta

We investigate the large-time asymptotics of nonlinear diffusion equations $u_t = \Delta u^p$ in dimension $n \ge 1$, in the exponent interval $p > n/(n+2)$, when the initial datum $u_0$ is of bounded second moment. Precise rates of…

Analysis of PDEs · Mathematics 2015-06-19 J. A. Carrillo , G. Toscani

We introduce a novel measure for the quantum property of nonstabilizerness - commonly known as "magic" - by considering the R\'enyi entropy of the probability distribution associated to a pure quantum state given by the square of the…

Quantum Physics · Physics 2022-03-15 Lorenzo Leone , Salvatore F. E. Oliviero , Alioscia Hamma

In this paper, we analyze the asymptotics of the normalized remaining uncertainty of a source when a compressed or hashed version of it and correlated side-information is observed. For this system, commonly known as Slepian-Wolf source…

Information Theory · Computer Science 2016-06-01 Vincent Y. F. Tan , Masahito Hayashi

We study the R\'enyi entropies in the spin-$1/2$ anisotropic Heisenberg chain after a quantum quench starting from the N\'eel state. The quench action method allows us to obtain the stationary R\'enyi entropies for arbitrary values of the…

Statistical Mechanics · Physics 2018-11-13 Vincenzo Alba , Pasquale Calabrese

The rate-distortion-perception (RDP) framework has attracted significant recent attention due to its application in neural compression. It is important to understand the underlying mechanism connecting procedures with common randomness and…

Information Theory · Computer Science 2024-06-28 Ruida Zhou , Chao Tian

This paper studies the complexity of estimating Renyi divergences of discrete distributions: $p$ observed from samples and the baseline distribution $q$ known \emph{a priori}. Extending the results of Acharya et al. (SODA'15) on estimating…

Information Theory · Computer Science 2017-02-09 Maciej Skorski

We report multipronged progress on the stochastic averaging approach to numerical analytic continuation of quantum Monte Carlo data. With the sampled spectrum parametrized with delta-functions in continuous frequency space, a calculation of…

Strongly Correlated Electrons · Physics 2023-01-11 Hui Shao , Anders W. Sandvik

This paper investigates three closely related topics -- R\'enyi resolvability, noise stability, and anti-contractivity. The R\'enyi resolvability problem refers to approximating a target output distribution of a given channel in the R\'enyi…

Information Theory · Computer Science 2025-06-10 Lei Yu

Entanglement concentration from many copies of unknown pure states is discussed, and we propose the protocol which not only achieves entropy rate, but also produces the perfect maximally entangled state. Our protocol is induced naturally…

Quantum Physics · Physics 2007-05-23 Masahito Hayashi , Keiji Matsumoto

The Matrix-based Renyi's entropy enables us to directly measure information quantities from given data without the costly probability density estimation of underlying distributions, thus has been widely adopted in numerous statistical…

Machine Learning · Statistics 2022-05-17 Yuxin Dong , Tieliang Gong , Shujian Yu , Chen Li