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We propose a sequential Monte Carlo (SMC) method to efficiently and accurately compute cut-Bayesian posterior quantities of interest, variations of standard Bayesian approaches constructed primarily to account for model misspecification. We…

Computation · Statistics 2024-11-13 Joseph Mathews , Giri Gopalan , James Gattiker , Sean Smith , Devin Francom

We perform a loop-level analysis of charged-current (CC) processes involving light leptons and quarks within the Standard Model Effective Field Theory (SMEFT). This work is motivated by the high precision reached in experiment and Standard…

High Energy Physics - Phenomenology · Physics 2024-02-13 Maria Dawid , Vincenzo Cirigliano , Wouter Dekens

This report was prepared in the context of the LPCC "Electroweak Precision Measurements at the LHC WG" and summarizes the activity of a subgroup dedicated to the systematic comparison of public Monte Carlo codes, which describe the…

We introduce PineAPPL, a library that produces fast-interpolation grids of physical cross sections, computed with a general-purpose Monte Carlo generator, accurate to fixed order in the strong, electroweak, and combined strong-electroweak…

High Energy Physics - Phenomenology · Physics 2021-01-05 S. Carrazza , E. R. Nocera , C. Schwan , M. Zaro

In this article we develop a new sequential Monte Carlo (SMC) method for multilevel (ML) Monte Carlo estimation. In particular, the method can be used to estimate expectations with respect to a target probability distribution over an…

Computation · Statistics 2017-03-16 Alexandros Beskos , Ajay Jasra , Kody Law , Youssef Marzouk , Yan Zhou

This work proposes a unified Hierarchical Model Predictive Control (H-MPC) for modular manipulators across various morphologies, as the controller can adapt to different configurations to execute the given task without extensive parameter…

Robotics · Computer Science 2025-08-20 Maolin Lei , Edoardo Romiti , Arturo Laurenzi , Cheng Zhou , Wanli Xing , Liang Lu , Nikos G. Tsagarakis

We present the Monte Carlo event generator WINHAC for the charged-current Drell-Yan process, i.e. single W-boson production with leptonic decays in hadronic collisions. It features multiphoton radiationwithin the Yennie-Frautschi-Suura…

High Energy Physics - Phenomenology · Physics 2014-11-20 Wieslaw Placzek

The program package SecDec is presented, allowing the numerical evaluation of multi-loop integrals. The restriction to Euclidean kinematics of version 1.0 has been lifted: thresholds can be handled by an automated deformation of the…

High Energy Physics - Phenomenology · Physics 2012-09-28 Sophia Borowka , Gudrun Heinrich

In this article we consider a Bayesian inverse problem associated to elliptic partial differential equations (PDEs) in two and three dimensions. This class of inverse problems is important in applications such as hydrology, but the…

Computation · Statistics 2014-12-16 Alex Beskos , Ajay Jasra , Ege Muzaffer , Andrew Stuart

The next-to-leading order (NLO) evolution of the parton distribution functions (PDFs) in QCD is a common tool in the lepton-hadron and hadron-hadron collider data analysis. The standard NLO DGLAP evolution is formulated for inclusive…

High Energy Physics - Phenomenology · Physics 2010-02-02 S. Jadach , M. Skrzypek , A. Kusina , M. Slawinska

The state-of-the-art in current two-loop QCD amplitude calculations is at five-particle scattering. Computing two-loop six-particle processes requires knowledge of the corresponding one-loop amplitudes to higher orders in the dimensional…

High Energy Physics - Theory · Physics 2023-02-08 Johannes M. Henn , Antonela Matijašić , Julian Miczajka

Exponents and logarithms are fundamental components in many important applications such as logistic regression, maximum likelihood, relative entropy, and so on. Since the exponential cone can be viewed as the epigraph of perspective of the…

Optimization and Control · Mathematics 2022-03-22 Qing Ye , Weijun Xie

We introduce a recent symplectic integration scheme derived for solving physically motivated systems with non-separable Hamiltonians. We show its relevance to Riemannian manifold Hamiltonian Monte Carlo (RMHMC) and provide an alternative to…

Machine Learning · Statistics 2019-10-15 Adam D. Cobb , Atılım Güneş Baydin , Andrew Markham , Stephen J. Roberts

We propose a novel approach called Self-Learning Hybrid Monte Carlo (SLHMC) which is a general method to make use of machine learning potentials to accelerate the statistical sampling of first-principles density-functional-theory (DFT)…

Materials Science · Physics 2020-08-05 Yuki Nagai , Masahiro Okumura , Keita Kobayashi , Motoyuki Shiga

Variational inference lies at the core of many state-of-the-art algorithms. To improve the approximation of the posterior beyond parametric families, it was proposed to include MCMC steps into the variational lower bound. In this work we…

Machine Learning · Statistics 2016-09-28 Christopher Wolf , Maximilian Karl , Patrick van der Smagt

The AcerMC Monte Carlo generator is dedicated to the generation of Standard Model background processes which were recognised as critical for the searches at LHC, and generation of which was either unavailable or not straightforward so far.…

High Energy Physics - Phenomenology · Physics 2012-11-15 Borut Paul Kersevan , Elzbieta Richter-Was

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be…

High Energy Physics - Phenomenology · Physics 2011-01-17 N. Davidson , P. Golonka , T. Przedzinski , Z. Was

We present the automation of one-loop computations in the standard-model effective field theory at dimension six. Our general implementation, dubbed SMEFT@NLO, covers all types of operators: bosonic, two- and four-fermion ones. Included…

High Energy Physics - Phenomenology · Physics 2021-06-09 Céline Degrande , Gauthier Durieux , Fabio Maltoni , Ken Mimasu , Eleni Vryonidou , Cen Zhang

We present the version 2.0 of the program package GoSam, which is a public program package to compute one-loop QCD and/or electroweak corrections to multi-particle processes within and beyond the Standard Model. The extended version of the…

High Energy Physics - Phenomenology · Physics 2014-10-01 Johann Felix von Soden-Fraunhofen

The hierarchical Dirichlet process (HDP) has become an important Bayesian nonparametric model for grouped data, such as document collections. The HDP is used to construct a flexible mixed-membership model where the number of components is…

Machine Learning · Statistics 2012-01-10 Chong Wang , David M. Blei