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We consider the problem of discriminating two different quantum states in the setting of asymptotically many copies, and determine the optimal strategy that minimizes the total probability of error. This leads to the identification of the…

Quantum Physics · Physics 2007-05-23 K. M. R. Audenaert , J. Calsamiglia , Ll. Masanes , R. Munoz-Tapia , A. Acin , E. Bagan , F. Verstraete

Let $A$ be a self-adjoint operator acting over a space $X$ endowed with a partition. We give lower bounds on the energy of a mixed state $\rho$ from its distribution in the partition and the spectral density of $A$. These bounds improve…

Functional Analysis · Mathematics 2019-12-19 Michel Rumin

The purpose of the present notes is to examine the following issues related to the the Chernoff estimate: (1) For contractions on a Banach space we modify the $\sqrt{n}$-estimate and apply it in the proof of the Chernoff product formula for…

Functional Analysis · Mathematics 2022-10-26 Valentin A. Zagrebnov

We show that the Bernstein-Hoeffding method can be employed to a larger class of generalized moments. This class includes the exponential moments whose properties play a key role in the proof of a well-known inequality of Wassily Hoeffding,…

Probability · Mathematics 2015-09-02 Christos Pelekis , Jan Ramon , Yuyi Wang

The Schr{\"o}dinger inequality is known to underlie the Kennard-Robertson inequality, which is the standard expression of quantum uncertainty for the product of variances of two observables $A$ and $B$, in the sense that the latter is…

Quantum Physics · Physics 2020-08-10 Jaeha Lee , Keita Takeuchi , Kaisei Watanabe , Izumi Tsutsui

By combining the Minkowski inequality and the quantum Chernoff bound, we derive easy-to-compute upper bounds for the error probability affecting the optimal discrimination of Gaussian states. In particular, these bounds are useful when the…

Quantum Physics · Physics 2008-07-27 Stefano Pirandola , Seth Lloyd

We observe that the technique of Markov contraction can be used to establish measure concentration for a broad class of non-contracting chains. In particular, geometric ergodicity provides a simple and versatile framework. This leads to a…

Probability · Mathematics 2013-12-06 Aryeh Kontorovich , Roi Weiss

In quantum physics, the theoretical study of unbound many-body systems is typically quite complex -- owing to the combination of their large spatial extension and the so-called {\it curse of dimensionality}. Often, such systems are studied…

Quantum Physics · Physics 2021-02-03 Sølve Selstø

We consider operators with random potentials on graphs, such as the lattice version of the random Schroedinger operator. The main result is a general bound on the probabilities of simultaneous occurrence of eigenvalues in specified distinct…

Mathematical Physics · Physics 2010-10-26 Michael Aizenman , Simone Warzel

We analyze the Schwarz inequality and its generalizations, as well as inequalities resulting from the Jensen inequality. They are used in quantum theory to derive the Heisenberg-Robertson (HR) and Schroedinger-Robertson (SR) uncertainty…

Quantum Physics · Physics 2026-04-16 Krzysztof Urbanowski

We consider the problem of discriminating between two different states of a finite quantum system in the setting of large numbers of copies, and find a closed form expression for the asymptotic exponential rate at which the specified error…

Quantum Physics · Physics 2011-05-13 K. M. R. Audenaert , M. Nussbaum , A. Szkola , F. Verstraete

Macro properties of cold atomic gases are driven by few-body correlations, even if the gas has thousands of particles. Quantum systems composed of two and three particles with attractive zero\=/range pairwise interactions are considered for…

Quantum Gases · Physics 2014-11-12 F. F. Bellotti

Measurement is a fundamental notion in the usual approximate quantum mechanics of measured subsystems. Probabilities are predicted for the outcomes of measurements. State vectors evolve unitarily in between measurements and by reduction of…

General Relativity and Quantum Cosmology · Physics 2014-01-14 James B. Hartle

Work in isolated quantum systems is a random variable and its probability distribution function obeys the celebrated fluctuation theorems of Crooks and Jarzynski. In this study, we provide a simple way to describe the work probability…

Quantum Physics · Physics 2019-12-04 Eric G. Arrais , Diego A. Wisniacki , Augusto J. Roncaglia , Fabricio Toscano

Heisenberg's uncertainty principle has recently led to general measurement uncertainty relations for quantum systems: incompatible observables can be measured jointly or in sequence only with some unavoidable approximation, which can be…

Quantum Physics · Physics 2017-06-27 Alberto Barchielli , Matteo Gregoratti , Alessandro Toigo

The Chernoff bound is one of the most widely used tools in theoretical computer science. It's rare to find a randomized algorithm that doesn't employ a Chernoff bound in its analysis. The standard proofs of Chernoff bounds are beautiful but…

Data Structures and Algorithms · Computer Science 2026-02-10 William Kuszmaul

Relativistic causality, namely, the impossibility of signaling at superluminal speeds, restricts the kinds of correlations which can occur between different parts of a composite physical system. Here we establish the basic restrictions…

Quantum Physics · Physics 2007-05-23 Jose L. Cereceda

This paper develops an optimal Chernoff type bound for the probabilities of large deviations of sums $\sum_{k=1}^n f (X_k)$ where $f$ is a real-valued function and $(X_k)_{k \in \mathbb{Z}_{\ge 0}}$ is a finite state Markov chain with an…

Probability · Mathematics 2019-12-24 Vrettos Moulos , Venkat Anantharam

The Chernoff bound is a well-known tool for obtaining a high probability bound on the expectation of a Bernoulli random variable in terms of its sample average. This bound is commonly used in statistical learning theory to upper bound the…

Machine Learning · Statistics 2022-05-18 Andrew Y. K. Foong , Wessel P. Bruinsma , David R. Burt

Recent research has made significant progress on the problem of bounding log partition functions for exponential family graphical models. Such bounds have associated dual parameters that are often used as heuristic estimates of the marginal…

Machine Learning · Computer Science 2012-07-19 Pradeep Ravikumar , John Lafferty