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We study lower bounds on the worst-case error of numerical integration in tensor product spaces. As reference we use the $N$-th minimal error of linear rules that use $N$ function values. The information complexity is the minimal number $N$…

Numerical Analysis · Mathematics 2024-04-29 Erich Novak , Friedrich Pillichshammer

One of the most fundamental problems in science is to define {\it quantitatively} the complexity of organized matters, i.e., {\it organized complexity}. Although many measures have been proposed toward this aim in previous decades, there is…

Information Theory · Computer Science 2016-08-03 Tatsuaki Okamoto

We consider the problem of estimating an upper bound on the capacity of a memoryless channel with unknown channel law and continuous output alphabet. A novel data-driven algorithm is proposed that exploits the dual representation of…

Information Theory · Computer Science 2024-01-25 Christian Häger , Erik Agrell

Worst-case bounds on the expected shortfall risk given only limited information on the distribution of the random variables has been studied extensively in the literature. In this paper, we develop a new worst-case bound on the expected…

Risk Management · Quantitative Finance 2017-02-12 Anulekha Dhara , Bikramjit Das , Karthik Natarajan

The price system is often said to economize on information, but economics has lacked a formal measure of how much information it saves. This paper develops such a measure. We construct a proof-theoretic framework for decentralized…

Theoretical Economics · Economics 2026-05-25 Shuige Liu

We examine the evaluation of the minimum information loss due to an unread local measurement in mixed states of bipartite systems, for a general entropic form. Such quantity provides a measure of quantum correlations, reducing for pure…

Quantum Physics · Physics 2015-06-03 R. Rossignoli , N. Canosa , L. Ciliberti

We analyze the distinguishability norm on the states of a multi-partite system, defined by local measurements. Concretely, we show that the norm associated to a tensor product of sufficiently symmetric measurements is essentially equivalent…

Quantum Physics · Physics 2013-09-17 Cécilia Lancien , Andreas Winter

Quantum information processing is the emerging field that defines and realizes computing devices that make use of quantum mechanical principles, like the superposition principle, entanglement, and interference. In this review we study the…

Quantum Physics · Physics 2015-05-13 Harry Buhrman , Richard Cleve , Serge Massar , Ronald de Wolf

We give two strengthenings of an inequality for the quantum conditional mutual information of a tripartite quantum state recently proved by Fawzi and Renner, connecting it with the ability to reconstruct the state from its bipartite…

Quantum Physics · Physics 2016-06-03 Fernando G. S. L. Brandao , Aram W. Harrow , Jonathan Oppenheim , Sergii Strelchuk

The concept of distinguishability lies at the heart of quantum information theory. We introduce \textit{left-right relative entropy} as a quantitative measure of distinguishability within the space of boundary states in two-dimensional…

High Energy Physics - Theory · Physics 2026-05-26 Mostafa Ghasemi

Informationally complete measurements allow the estimation of expectation values of any operator on a quantum system, by changing only the data-processing of the measurement outcomes. In particular, an informationally complete measurement…

Quantum Physics · Physics 2007-05-23 G. M. D'Ariano , P. Perinotti , M. F. Sacchi

Information-theoretic techniques are based on the assumption that resources are well characterized by independent and identically distributed (iid) states. This assumption cannot be justified operationally, since, for example, correlations…

Quantum Physics · Physics 2026-03-18 Giulia Mazzola , David Sutter , Renato Renner

Bounded agents are limited by intrinsic constraints on their ability to process information that is available in their sensors and memory and choose actions and memory updates. In this dissertation, we model these constraints as…

Machine Learning · Computer Science 2017-03-31 Roy Fox

In this work the information loss in deterministic, memoryless systems is investigated by evaluating the conditional entropy of the input random variable given the output random variable. It is shown that for a large class of systems the…

Information Theory · Computer Science 2013-04-18 Bernhard C. Geiger , Gernot Kubin

This paper describes a framework in which directed information is defined on abstract spaces. The framework is employed to derive properties of directed information such as convexity, concavity, lower semicontinuity, by using the topology…

Information Theory · Computer Science 2012-05-22 Charalambos D. Charalambous , Photios A. Stavrou

Nonlocality without entanglement and its subsequent generalizations offer deep information-theoretic insights and subsequently find several useful applications. Concept of genuinely nonlocal set of product states emerges as a natural…

Quantum Physics · Physics 2023-03-31 Sumit Rout , Ananda G. Maity , Amit Mukherjee , Saronath Halder , Manik Banik

We introduce a bottleneck method for learning data representations based on information deficiency, rather than the more traditional information sufficiency. A variational upper bound allows us to implement this method efficiently. The…

Information Theory · Computer Science 2020-11-05 Pradeep Kr. Banerjee , Guido Montúfar

Inspired by Hilberg's hypothesis, which states that mutual information between blocks for natural language grows like a power law, we seek for links between power-law growth rate of algorithmic mutual information and of some estimator of…

Information Theory · Computer Science 2020-12-29 Łukasz Dębowski

We consider the communication complexity of a number of distributed optimization problems. We start with the problem of solving a linear system. Suppose there is a coordinator together with $s$ servers $P_1, \ldots, P_s$, the $i$-th of…

Data Structures and Algorithms · Computer Science 2019-11-01 Santosh S. Vempala , Ruosong Wang , David P. Woodruff

The information content of a source is defined in terms of the minimum number of bits needed to store the output of the source in a perfectly recoverable way. A similar definition can be given in the case of quantum sources, with qubits…

Quantum Physics · Physics 2023-04-03 Paolo Perinotti , Alessandro Tosini , Leonardo Vaglini
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