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Algorithms which sort lists of real numbers into ascending order have been studied for decades. They are typically based on a series of pairwise comparisons and run entirely on chip. However people routinely sort lists which depend on…

Artificial Intelligence · Computer Science 2016-12-28 Samuel L Smith

We derive a new method for initial-state collinear showering in Monte-Carlo event generators which is based on the use of unintegrated parton correlation functions. Combined with a previously derived method for final-state showering, the…

High Energy Physics - Phenomenology · Physics 2008-11-26 John C. Collins , Xiaomin Zu

The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source/channel models. The focus of the paper is on binary-input channels with constraints on the allowed input configurations. The…

Information Theory · Computer Science 2012-12-27 Mehdi Molkaraie , Hans-Andrea Loeliger

We present a Monte-Carlo approach to prompt-photon production, where photons and QCD partons are treated democratically. The photon fragmentation function is modelled by an interleaved QCD+QED parton shower. This known technique is improved…

High Energy Physics - Phenomenology · Physics 2014-11-20 Stefan Hoeche , Steffen Schumann , Frank Siegert

We propose a new class of infrared-collinear (IRC) and Sudakov safe observables with an associated jet grooming technique that removes dynamically soft and large angle branches. It is based on identifying the hardest branch in the…

High Energy Physics - Phenomenology · Physics 2020-02-12 Yacine Mehtar-Tani , Alba Soto-Ontoso , Konrad Tywoniuk

A new Monte Carlo model is proposed for radiative corrections to Bhabha scattering by extending QEDPS developed for multi-photon emission in muon pair production in $e^+e^-$ annihilation. This is the QED version of the model known as parton…

High Energy Physics - Phenomenology · Physics 2017-02-01 J. Fujimoto , Y. Shimizu , T. Munehisa

A body of recent work has focused on constructing a variational family of filtered distributions using Sequential Monte Carlo (SMC). Inspired by this work, we introduce Particle Smoothing Variational Objectives (SVO), a novel backward…

Machine Learning · Statistics 2019-09-24 Antonio Khalil Moretti , Zizhao Wang , Luhuan Wu , Iddo Drori , Itsik Pe'er

We extend the Helac-Dipoles package with the implementation of a new subtraction formalism, first introduced by Nagy and Soper in the formulation of an improved parton shower. We discuss a systematic, semi-numerical approach for the…

High Energy Physics - Phenomenology · Physics 2013-11-04 G. Bevilacqua , M. Czakon , M. Kubocz , M. Worek

Software defect prediction is an essential task during the software development Lifecycle as it can help managers to identify the most defect-proneness modules. Thus, it can reduce the test cost and assign testing resources efficiently.…

Software Engineering · Computer Science 2022-09-30 Haneen Abu Alhija , Mohammad Azzeh , Fadi Almasalha

Monte Carlo event generators are essential components of almost all experimental analyses and are also widely used by theorists and experiments to make predictions and preparations for future experiments. They are all too often used as…

High Energy Physics - Phenomenology · Physics 2013-04-25 Michael H. Seymour , Marilyn Marx

A novel algorithm for computing the action of a matrix exponential over a vector is proposed. The algorithm is based on a multilevel Monte Carlo method, and the vector solution is computed probabilistically generating suitable random paths…

Numerical Analysis · Mathematics 2019-07-05 Juan A. Acebron , Jose R. Herrero , Jose Monteiro

Recently a cluster Monte Carlo algorithm has been used very successfully in the two-dimensional Edwards-Anderson (EA) model. We show that this algorithm and a variant thereof can also be used successfully in models with a non-zero spin…

Disordered Systems and Neural Networks · Physics 2015-06-24 Thomas Jorg

Random batch algorithms are constructed for quantum Monte Carlo simulations. The main objective is to alleviate the computational cost associated with the calculations of two-body interactions, including the pairwise interactions in the…

Computational Physics · Physics 2020-09-01 Shi Jin , Xiantao Li

We discuss the GENEVA Monte Carlo framework, which combines higher-order resummation (NNLL) of large Sudakov logarithms with multiple next-to-leading-order (NLO) matrix-element corrections and parton showering (using PYTHIA8) to give a…

We propose a novel class of Sequential Monte Carlo (SMC) algorithms, appropriate for inference in probabilistic graphical models. This class of algorithms adopts a divide-and-conquer approach based upon an auxiliary tree-structured…

Construction of a QCD cascade at the NLO level requires recalculation of the splitting functions in a different manner [1]. We describe the calculation of some of the virtual contributions to the non-singlet splitting function. In order to…

High Energy Physics - Phenomenology · Physics 2015-06-17 O. Gituliar , S. Jadach , A. Kusina , M. Skrzypek

A major challenge facing existing sequential Monte-Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results…

Quantum Physics · Physics 2017-09-13 Christopher Granade , Nathan Wiebe

The task of Monte Carlo simulation of the evolution of the parton distributions in QCD and of constructing new parton shower Monte Carlo algorithms requires new way of organizing solutions of the QCD evolution equations, in which…

High Energy Physics - Phenomenology · Physics 2010-03-25 S. Jadach , M. Skrzypek , Z. Was

In electroweak-boson production processes with a jet veto, higher-order corrections are enhanced by logarithms of the veto scale over the invariant mass of the boson system. In this paper, we resum these Sudakov logarithms at…

High Energy Physics - Phenomenology · Physics 2015-06-23 Thomas Becher , Rikkert Frederix , Matthias Neubert , Lorena Rothen

Multivariate data analysis techniques have the potential to improve physics analyses in many ways. The common classification problem of signal/background discrimination is one example. The Support Vector Machine learning algorithm is a…

High Energy Physics - Experiment · Physics 2009-11-07 A. Vaiciulis