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Related papers: On the entropy of a noisy function

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There are several inequalities in physics which limit how well we can process physical systems to achieve some intended goal, including the second law of thermodynamics, entropy bounds in quantum information theory, and the uncertainty…

Quantum Physics · Physics 2016-07-19 Francesco Buscemi , Siddhartha Das , Mark M. Wilde

Suppose $\XX{N}$ is a uniformly distributed $N$-dimensional binary vector and $\YY{N}$ is obtained by passing $\XX{N}$ through a binary symmetric channel with crossover probability $\alpha$. Recently, Courtade and Kumar postulates that…

Information Theory · Computer Science 2017-10-20 Mustafa Kesal

We prove that, to compute a Boolean function $f$ on $N$ variables with error probability $\epsilon$, any quantum black-box algorithm has to query at least $\frac{1 - 2\sqrt{\epsilon}}{2} \rho_f N = \frac{1 - 2\sqrt{\epsilon}}{2} \bar{S}_f$…

Quantum Physics · Physics 2007-05-23 Yaoyun Shi

The estimation of signal frequency count in the presence of background noise has had much discussion in the recent physics literature, and Mandelkern [1] brings the central issues to the statistical community, leading in turn to extensive…

Data Analysis, Statistics and Probability · Physics 2009-11-10 D. A. S. Fraser , N. Reid , A. C. M. Wong

We consider the models Y_{i,n}=\int_0^{i/n} \sigma(s)dW_s+\tau(i/n)\epsilon_{i,n}, and \tilde Y_{i,n}=\sigma(i/n)W_{i/n}+\tau(i/n)\epsilon_{i,n}, i=1,...,n, where W_t denotes a standard Brownian motion and \epsilon_{i,n} are centered i.i.d.…

Methodology · Statistics 2010-04-07 Axel Munk , Johannes Schmidt-Hieber

Whether noisy quantum devices without error correction can provide quantum advantage over classical computers is a critical issue of current quantum computation. In this work, the random quantum circuits, which are used as the paradigm…

Quantum Physics · Physics 2022-12-07 Meng Zhang , Chao Wang , Shaojun Dong , Hao Zhang , Yongjian Han , Lixin He

Computer simulations of the Ising model exhibit white noise if thermal fluctuations are governed by Boltzmann's factor alone; whereas we find that the same model exhibits 1/f noise if Boltzmann's factor is extended to include local…

Mesoscale and Nanoscale Physics · Physics 2015-06-22 Ralph V. Chamberlin , Derek M. Nasir

We study the convergence properties of the conditional (Kullback-Leibler) entropy in stochastic systems. We have proved very general results showing that asymptotic stability is a necessary and sufficient condition for the monotone…

Statistical Mechanics · Physics 2008-04-15 Michael C. Mackey , Marta Tyran-Kaminska

We study noise sensitivity of properties of the largest components $({\cal C}_j)_{j\geq 1}$ of the random graph ${\cal G}(n,p)$ in its critical window $p=(1+\lambda n^{-1/3})/n$. For instance, is the property "$|{\cal C}_1|$ exceeds its…

Probability · Mathematics 2020-09-04 Eyal Lubetzky , Yuval Peled

We study functions on the infinite-dimensional Hamming cube $\{-1,1\}^\infty$, in particular Boolean functions into $\{-1,1\}$, generalising results on analysis of Boolean functions on $\{-1,1\}^n$ for $n\in\mathbb{N}$. The notion of noise…

Probability · Mathematics 2019-06-11 Vilhelm Agdur

Nowadays many tools, e.g. fluctuation relations, are available to characterize the statistical properties of non-equilibrium systems. However, most of these tools rely on the assumption that the driving noise is normally distributed. Here…

Statistical Mechanics · Physics 2023-11-29 Dario Lucente , Andrea Puglisi , Massimiliano Viale , Angelo Vulpiani

We review with a tutorial scope the information theory foundations of quantum statistical physics. Only a small proportion of the variables that characterize a system at the microscopic scale can be controlled, for both practical and…

Statistical Mechanics · Physics 2007-05-23 R. Balian

We adopt an information-theoretic framework to analyze the generalization behavior of the class of iterative, noisy learning algorithms. This class is particularly suitable for study under information-theoretic metrics as the algorithms are…

Machine Learning · Computer Science 2023-07-20 Ibrahim Issa , Amedeo Roberto Esposito , Michael Gastpar

To understand the sample-to-sample fluctuations in disorder-generated multifractal patterns we investigate analytically as well as numerically the statistics of high values of the simplest model - the ideal periodic $1/f$ Gaussian noise. By…

Statistical Mechanics · Physics 2015-06-05 Yan V. Fyodorov , Pierre Le Doussal , Alberto Rosso

We extend the notion of estimation entropy of autonomous dynamical systems proposed by Liberzon and Mitra [1] to nonlinear dynamical systems with uncertain inputs with bounded variation. We call this new notion the {$\epsilon$}-estimation…

Systems and Control · Electrical Eng. & Systems 2023-11-14 Hussein Sibai , Sayan Mitra

The purpose of this note is to show how the method of maximum entropy in the mean (MEM) may be used to improve parametric estimation when the measurements are corrupted by large level of noise. The method is developed in the context on a…

Machine Learning · Computer Science 2021-08-23 Henryk Gzyl , Enrique ter Horst

We study the relationship between two measures of Boolean functions; \emph{algebraic thickness} and \emph{normality}. For a function $f$, the algebraic thickness is a variant of the \emph{sparsity}, the number of nonzero coefficients in the…

Computational Complexity · Computer Science 2015-09-22 Joan Boyar , Magnus Gausdal Find

Consider estimating a structured signal $\mathbf{x}_0$ from linear, underdetermined and noisy measurements $\mathbf{y}=\mathbf{A}\mathbf{x}_0+\mathbf{z}$, via solving a variant of the lasso algorithm: $\hat{\mathbf{x}}=\arg\min_\mathbf{x}\{…

Optimization and Control · Mathematics 2014-01-28 Christos Thrampoulidis , Samet Oymak , Babak Hassibi

We prove two new results about the randomized query complexity of composed functions. First, we show that the randomized composition conjecture is false: there are families of partial Boolean functions $f$ and $g$ such that $R(f\circ g)\ll…

Computational Complexity · Computer Science 2020-12-08 Shalev Ben-David , Eric Blais

The main objective of this study is fractionally integrated fractional Brownian noise, I(t/a,H) where a>0 is the 'multiplicity' of integration, and H is the Hurst parameter . The subject of the analysis is the persistence exponent e(a,H)…

Probability · Mathematics 2026-05-21 G. Molchan