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Hadronic spectral densities are important quantities whose non-perturbative knowledge allows for calculating phenomenologically relevant observables, such as inclusive hadronic cross-sections and non-leptonic decay-rates. The extraction of…

High Energy Physics - Lattice · Physics 2019-06-05 Martin Hansen , Alessandro Lupo , Nazario Tantalo

Modern advances in algorithms for lattice QCD calculations have steadily driven down the resources required to generate gauge field ensembles and calculate quark propagators, such that, in cases relevant to nuclear physics, performing quark…

High Energy Physics - Lattice · Physics 2021-08-18 W. Detmold , D. J. Murphy , A. V. Pochinsky , M. J. Savage , P. E. Shanahan , M. L. Wagman

While powerful methods have been developed for high-dimensional hypothesis testing assuming orthogonal parameters, current approaches struggle to generalize to the more common non-orthogonal case. We propose Stable Distillation (SD), a…

Methodology · Statistics 2025-01-10 Ryan Christ , Ira Hall , David Steinsaltz

A multiscale method is proposed for a parabolic stochastic partial differential equation with additive noise and highly oscillatory diffusion. The framework is based on the localized orthogonal decomposition (LOD) method and computes a…

Numerical Analysis · Mathematics 2023-04-28 Annika Lang , Per Ljung , Axel Målqvist

Quantum distillation is the task of concentrating quantum correlations present in 'N' imperfect copies using free operations by involving all 'P' parties sharing the quantum correlations. We present a threshold quantum distillation task…

Quantum Physics · Physics 2026-02-16 Shashank Gupta , William John Munro , Carlos Cid

Progress in calculating the spectrum of excited baryons and mesons in lattice QCD is described. Correlation matrices of sets of spatially-extended hadron operators have been studied and their effectiveness in facilitating the extraction of…

High Energy Physics - Lattice · Physics 2010-12-01 Colin Morningstar , A. Bell , C. Y. Chen , D. Lenkner , C. H. Wong , J. Bulava , J. Foley , K. J. Juge , M. Peardon

Obtaining the free energies of condensed phase chemical reactions remains computationally prohibitive for high-level quantum mechanical methods. We introduce a hierarchical machine learning framework that bridges this gap by distilling…

Chemical Physics · Physics 2026-03-19 Chenghan Li , Garnet Kin-Lic Chan

We derive the two-point spectral correlation function of the Dirac operator with a specific external source in the $\epsilon$-regime of QCD. This correlation function has a unique and strong dependence on $F_\pi$, and thus provides an novel…

High Energy Physics - Lattice · Physics 2009-11-11 P. H. Damgaard , Urs M. Heller , K. Splittorff , B. Svetitsky

We sketch the basic ideas of the lattice regularization in Quantum Field Theory, the corresponding Monte Carlo simulations, and applications to Quantum Chromodynamics (QCD). This approach enables the numerical measurement of observables at…

High Energy Physics - Phenomenology · Physics 2016-08-24 Wolfgang Bietenholz

We study the process of assisted work distillation. This scenario arises when two parties share a bipartite quantum state $\rho_{AB}$ and their task is to locally distil the optimal amount of work when one party is restricted to thermal…

Quantum Physics · Physics 2019-04-10 Benjamin Morris , Ludovico Lami , Gerardo Adesso

A previously-proposed method of constructing spatially-extended gauge-invariant three-quark operators for use in Monte Carlo lattice QCD calculations is tested, and a methodology for using these operators to extract the energies of a large…

High Energy Physics - Lattice · Physics 2007-05-23 Adam C. Lichtl

We apply the Distillation spatial smearing program to the extraction of the unpolarized isovector valence PDF of the nucleon. The improved volume sampling and control of excited-states afforded by distillation leads to a dramatically…

We show how to compute electromagnetic polarizabilities of charged hadrons using four-point functions in lattice QCD. The low-energy behavior of Compton scattering amplitude is matched to matrix elements of current-current correlation…

High Energy Physics - Lattice · Physics 2022-01-03 Walter Wilcox , Frank X. Lee

We compute the chiral condensate in 2+1-flavor QCD through the spectrum of low-lying eigenmodes of Dirac operator. The number of eigenvalues of the Dirac operator is evaluated using a stochastic method with an eigenvalue filtering technique…

High Energy Physics - Lattice · Physics 2016-08-22 Guido Cossu , Hidenori Fukaya , Shoji Hashimoto , Takashi Kaneko , Jun-Ichi Noaki

Our ability to resolve new physics effects is, largely, limited by the precision with which we calculate. The calculation of observables in the Standard (or a new physics) Model requires knowledge of associated hadronic contributions. The…

High Energy Physics - Phenomenology · Physics 2013-09-30 C. M. Bouchard

Entanglement distillation is a fundamental building block in long-distance quantum communication. Though known to be useless on their own for distilling Gaussian entangled states, local Gaussian operations may still help to improve…

Quantum Physics · Physics 2013-05-29 ShengLi Zhang , Peter van Loock

A novel method for extracting physical parameters from experimental and simulation data is presented. The method is based on statistical concepts and it relies on Monte Carlo simulation techniques. It identifies and determines with maximal…

High Energy Physics - Phenomenology · Physics 2012-05-31 C. N. Papanicolas , E. Stiliaris

A strategy to compute inclusive hadronic processes in lattice QCD is discussed. The key idea is to view the inclusive decay or scattering rate as a smeared spectrum. The Euclidean time dependence of correlators obtained on the lattice can…

High Energy Physics - Lattice · Physics 2025-04-01 Shoji Hashimoto

Context distillation compresses contextual information into model parameters, yet existing methods often ignore how multiple distilled latent memories should be stored, retrieved, and safely activated in non-oracle settings. We formulate…

Machine Learning · Computer Science 2026-05-29 Ziyang Zheng , Zeju Li , Xiangyu Wen , Jianyuan Zhong , Junhua Huang , Lei Chen , Mingxuan Yuan , Qiang Xu

Knowledge distillation is a popular approach for enhancing the performance of ''student'' models, with lower representational capacity, by taking advantage of more powerful ''teacher'' models. Despite its apparent simplicity and widespread…

Machine Learning · Computer Science 2023-12-12 Mher Safaryan , Alexandra Peste , Dan Alistarh