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Forecasting is usually framed as a problem of model choice. This paper starts earlier, asking how much predictive information is available at each horizon. Under logarithmic loss, the answer is exact: the mutual information between the…

Applications · Statistics 2026-03-31 Peter Maurice Catt

We derive information-theoretic converses (i.e., lower bounds) for the minimum time required by any algorithm for distributed function computation over a network of point-to-point channels with finite capacity, where each node of the…

Information Theory · Computer Science 2017-01-04 Aolin Xu , Maxim Raginsky

Coherent information quantifies the achievable rate of the reliable quantum information transmission through a communication channel. Use of the correlated quantum states instead of the factorized ones may result in an increase in the…

Quantum Physics · Physics 2022-06-28 Sergey N. Filippov

We show that entanglement guarantees difficulty in the discrimination of orthogonal multipartite states locally. The number of pure states that can be discriminated by local operations and classical communication is bounded by the total…

Quantum Physics · Physics 2009-11-11 M. Hayashi , D. Markham , M. Murao , M. Owari , S. Virmani

Information-theoretic bounded rationality describes utility-optimizing decision-makers whose limited information-processing capabilities are formalized by information constraints. One of the consequences of bounded rationality is that…

Machine Learning · Computer Science 2020-06-30 Heinke Hihn , Sebastian Gottwald , Daniel A. Braun

The paper is focused on the tradeoff between performance and decoding complexity per iteration for LDPC codes in terms of their gap (in rate) to capacity. The study of this tradeoff is done via information-theoretic bounds which also enable…

Information Theory · Computer Science 2007-07-13 Igal Sason , Gil Wiechman

Genuine multipartite non-locality is not only of fundamental interest but also serves as an important resource for quantum information theory. We consider the $N$-partite scenario and provide an analytical upper bound on the maximal…

Quantum Physics · Physics 2024-09-16 Youwang Xiao , Zong Wang , Wen-Na Zhao , Ming Li

A connection between the state estimation problem and the separability problem is noticed and exploited to find efficient numerical algorithms to solve the first one. Based on these ideas, we also derive a systematic method to obtain upper…

Quantum Physics · Physics 2012-04-30 Miguel Navascues

Quantum data hiding stores classical information in bipartite quantum states that are, in principle, perfectly distinguishable, yet remain almost indistinguishable without access to a quantum communication channel. Here, we investigate…

Quantum Physics · Physics 2025-11-07 Aby Philip , Alexander Streltsov

Equivalence between Positive Partial Transpose (PPT) entanglement and bound entanglement is a long-standing open problem in quantum information theory. So far limited progress has been made, even on the seemingly simple case of Werner…

Quantum Physics · Physics 2024-07-02 Si-Yuan Qi , Geni Gupur , Yu-Chun Wu , Guo-Ping Guo

Resource-constrained systems are prevalent in communications. Such a system is composed of many components but only some of them can be allocated with resources such as time slots. According to the amount of information about the system,…

Information Theory · Computer Science 2014-04-02 Albert Y. S. Lam , Yanhui Geng , Victor O. K. Li

This thesis focuses on the intersection of mathematical and computational optimization and quantum information. Main contributions are open-source software code: A hybrid approach mixing "traditional" nonconvex and convex methods can make…

Quantum Physics · Physics 2025-12-19 Benjamin Desef

Deployed reinforcement learning systems lack a principled runtime reliability theory. We close this gap by introducing Bipredictability, P, a closed form information theoretic metric that quantifies how efficiently a closed loop interaction…

Artificial Intelligence · Computer Science 2026-05-18 Wael Hafez , Cameron Reid , Amit Nazeri

A new paradigm for distributed quantum systems where information is a valuable resource is developed. After finding a unique measure for information, we construct a scheme for it's manipulation in analogy with entanglement theory. In this…

The achievable information rate of finite-state input two-dimensional (2-D) channels with memory is an open problem, which is relevant, e.g., for inter-symbol-interference (ISI) channels and cellular multiple-access channels. We propose a…

Information Theory · Computer Science 2007-07-13 Ori Shental , Noam Shental , Shlomo Shamai

It is known that the high-dimensional quantum state space is notoriously complicated in contrast with the beautiful Bloch ball of the qubit. We examined the mechanism behind this fact in the frame work of general probabilistic theory (GPT),…

Quantum Physics · Physics 2022-03-17 Keiji Matsumoto , Gen Kimura

The notions of predictability and visibility are essential in the mathematical formulation of wave particle duality. The work of Jakob and Bergou [Phys. Rev. A 76, 052107] generalises these notions for higher-dimensional quantum systems,…

Quantum Physics · Physics 2024-01-03 Shailja Kapoor , Sohail , Gautam Sharma , Arun K. Pati

A single-letter characterization is provided for the capacity region of finite-state multiple-access channels, when the channel state process is an independent and identically distributed sequence, the transmitters have access to partial…

Information Theory · Computer Science 2010-12-10 Giacomo Como , Serdar Yüksel

Accumulating evidence indicates that the capacity to integrate information in the brain is a prerequisite for consciousness. Integrated Information Theory (IIT) of consciousness provides a mathematical approach to quantifying the…

Neurons and Cognition · Quantitative Biology 2016-02-22 Masafumi Oizumi , Shun-ichi Amari , Toru Yanagawa , Naotaka Fujii , Naotsugu Tsuchiya

Information theory provides tools to predict the performance of a learning algorithm on a given dataset. For instance, the accuracy of learning an unknown parameter can be upper bounded by reducing the learning task to hypothesis testing…

Quantum Physics · Physics 2026-04-21 Evan Peters
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