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We present our latest results for the the complex valued static heavy-quark potential at finite temperature from lattice QCD. The real and imaginary part of the potential are obtained from the position and width of the lowest lying peak in…

High Energy Physics - Lattice · Physics 2014-10-28 Yannis Burnier , Olaf Kaczmarek , Alexander Rothkopf

We present a new method to obtain spectral properties of a non-Abelian gauge theory in the region where occupation numbers are high. The method to measure the (single-particle) spectral function is based on linear response theory and…

High Energy Physics - Phenomenology · Physics 2018-12-18 Kirill Boguslavski , Aleksi Kurkela , Tuomas Lappi , Jarkko Peuron

We propose a new probabilistic method for unsupervised recovery of corrupted data. Given a large ensemble of degraded samples, our method recovers accurate posteriors of clean values, allowing the exploration of the manifold of possible…

Machine Learning · Computer Science 2020-07-01 Francesco Tonolini , Pablo G. Moreno , Andreas Damianou , Roderick Murray-Smith

The paper discusses the reconstruction of potentials for quantum systems at finite temperatures from observational data. A nonparametric approach is developed, based on the framework of Bayesian statistics, to solve such inverse problems.…

Quantum Physics · Physics 2009-11-06 J. C. Lemm , J. Uhlig , A. Weiguny

We investigate the possibility to assist the numerically ill-posed calculation of spectral properties of interacting quantum systems in thermal equilibrium by extending the imaginary-time simulation to a finite Schwinger-Keldysh contour.…

Strongly Correlated Electrons · Physics 2013-02-25 Andreas Dirks , Martin Eckstein , Thomas Pruschke , Philipp Werner

We introduce a novel extrapolation algorithm inspired by quantum mechanics and evaluate its performance against linear prediction. Our method involves mapping function values onto a quantum state and estimating future function values by…

Quantum Physics · Physics 2023-10-13 Lambert Lin , Steven R White

This paper proposes a new approach for Bayesian and maximum likelihood parameter estimation for stationary Gaussian processes observed on a large lattice with missing values. We propose an MCMC approach for Bayesian inference, and a Monte…

Computation · Statistics 2014-02-19 Jonathan R. Stroud , Michael L. Stein , Shaun Lysen

We propose a novel approach for estimating conditional or parametric expectations in the setting where obtaining samples or evaluating integrands is costly. Through the framework of probabilistic numerical methods (such as Bayesian…

Machine Learning · Statistics 2024-06-25 Zonghao Chen , Masha Naslidnyk , Arthur Gretton , François-Xavier Briol

The Generalized Eigenvalue Problem (GEVP) has been used extensively in the past in order to reliably extract energy levels from time-dependent Euclidean correlators calculated in Lattice QCD. We propose a formulation of the GEVP in…

High Energy Physics - Lattice · Physics 2016-11-09 Tim Harris , Harvey B. Meyer , Daniel Robaina

In this paper, we develop a new and effective approach to nonparametric quantile regression that accommodates ultrahigh-dimensional data arising from spatio-temporal processes. This approach proves advantageous in staving off computational…

Methodology · Statistics 2024-05-27 Soudeep Deb , Claudia Neves , Subhrajyoty Roy

We study the charmonium spectral functions at finite momentum and the dispersion relation of $\eta_c$ at finite temperature. For the analysis of the spectral function, we use an extended maximum entropy method (MEM). We perform the MEM…

High Energy Physics - Lattice · Physics 2014-12-02 A. Ikeda , M. Asakawa , M. Kitazawa

We present an improved Bayesian framework for performing inference of affine transformations of constrained functions. We focus on quadrature with nonnegative functions, a common task in Bayesian inference. We consider constraints on the…

Machine Learning · Computer Science 2019-02-28 Henry Chai , Roman Garnett

We expand the treatment of the problem of the extraction of smeared spectral densities from Euclidean correlators introduced in [Phys. Rev. D 99, 094508], providing an alternative which does not rely on the Backus-Gilbert regularization.…

High Energy Physics - Lattice · Physics 2026-05-15 Alessandro Lupo , Nazario Tantalo

In this work, a new Bayesian framework for OFDM channel estimation is proposed. Using Jaynes' maximum entropy principle to derive prior information, we successively tackle the situations when only the channel delay spread is a priori known,…

Information Theory · Computer Science 2008-11-06 Romain Couillet , Merouane Debbah

We present the generalization to non positive definite spectral functions of a recently proposed Bayesian deconvolution approach (BR method). The novel prior used here retains many of the beneficial analytic properties of the original…

High Energy Physics - Phenomenology · Physics 2017-03-30 Alexander Rothkopf

Deep directed generative models have attracted much attention recently due to their expressive representation power and the ability of ancestral sampling. One major difficulty of learning directed models with many latent variables is the…

Machine Learning · Computer Science 2015-06-16 Siqi Nie , Qiang Ji

QCD spectral functions of hadrons in the pseudo-scalar and vector channels are extracted from lattice Monte Carlo data of the imaginary time Green's functions. The maximum entropy method works well for this purpose, and the resonance and…

High Energy Physics - Lattice · Physics 2009-12-30 Y. Nakahara , M. Asakawa , T. Hatsuda

The main obstacle in describing inclusive decay spectra in QCD - which, in particular, limits the precision in extrapolating the measured \bar{B} \to X(s) gamma rate to the full phase space as well as in extracting |V_{ub}| from inclusive…

High Energy Physics - Phenomenology · Physics 2007-05-23 Einan Gardi , Jeppe R. Andersen

Maximum entropy method for analytic continuation is extended by introducing quantum relative entropy. This new method is formulated in terms of matrix-valued functions and therefore invariant under arbitrary unitary transformation of input…

Strongly Correlated Electrons · Physics 2018-11-05 Jae-Hoon Sim , Myung Joon Han

Bayesian techniques are widely used to obtain spectral functions from correlators. We suggest a technique to rid the results of nuisance parameters, ie, parameters which are needed for the regularization but cannot be determined from data.…

High Energy Physics - Lattice · Physics 2016-11-29 Sourendu Gupta , Anirban Lahiri