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The current and upcoming generation of Very Large Volume Neutrino Telescopes---collecting unprecedented quantities of neutrino events---can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the…

Data Analysis, Statistics and Probability · Physics 2019-12-05 IceCube Collaboration , M. G. Aartsen , M. Ackermann , J. Adams , J. A. Aguilar , M. Ahlers , M. Ahrens , I. Al Samarai , D. Altmann , K. Andeen , T. Anderson , I. Ansseau , G. Anton , C. Argüelles , T. C. Arlen , J. Auffenberg , S. Axani , H. Bagherpour , X. Bai , A. Balagopal V. , J. P. Barron , I. Bartos , S. W. Barwick , V. Baum , R. Bay , J. J. Beatty , J. Becker Tjus , K. -H. Becker , S. BenZvi , D. Berley , E. Bernardini , D. Z. Besson , G. Binder , D. Bindig , E. Blaufuss , S. Blot , C. Bohm , M. Bohmer , M. Börner , F. Bos , S. Böser , O. Botner , E. Bourbeau , J. Bourbeau , F. Bradascio , J. Braun , M. Brenzke , H. -P. Bretz , S. Bron , J. Brostean-Kaiser , A. Burgman , R. S. Busse , T. Carver , E. Cheung , D. Chirkin , A. Christov , K. Clark , L. Classen , G. H. Collin , J. M. Conrad , P. Coppin , P. Correa , D. F. Cowen , R. Cross , P. Dave , M. Day , J. P. A. M. de André , C. De Clercq , J. J. DeLaunay , H. Dembinski , S. De Ridder , P. Desiati , K. D. de Vries , G. de Wasseige , M. de With , T. DeYoung , J. C. Díaz-Vélez , V. di Lorenzo , H. Dujmovic , J. P. Dumm , M. Dunkman , M. A. DuVernois , E. Dvorak , B. Eberhardt , T. Ehrhardt , B. Eichmann , P. Eller , R. Engel , J. J. Evans , P. A. Evenson , S. Fahey , A. R. Fazely , J. Felde , K. Filimonov , C. Finley , S. Flis , A. Franckowiak , E. Friedman , A. Fritz , T. K. Gaisser , J. Gallagher , A. Gartner , L. Gerhardt , R. Gernhaeuser , K. Ghorbani , W. Giang , T. Glauch , T. Glüsenkamp , A. Goldschmidt , J. G. Gonzalez , D. Grant , Z. Griffith , C. Haack , A. Hallgren , F. Halzen , K. Hanson , J. Haugen , A. Haungs , D. Hebecker , D. Heereman , K. Helbing , R. Hellauer , F. Henningsen , S. Hickford , J. Hignight , G. C. Hill , K. D. Hoffman , B. Hoffmann , R. Hoffmann , T. Hoinka , B. Hokanson-Fasig , K. Holzapfel , K. Hoshina , F. Huang , M. Huber , T. Huber , T. Huege , K. Hultqvist , M. Hünnefeld , R. Hussain , S. In , N. Iovine , A. Ishihara , E. Jacobi , G. S. Japaridze , M. Jeong , K. Jero , B. J. P. Jones , P. Kalaczynski , O. Kalekin , W. Kang , D. Kang , A. Kappes , D. Kappesser , T. Karg , A. Karle , T. Katori , U. Katz , M. Kauer , A. Keivani , J. L. Kelley , A. Kheirandish , J. Kim , M. Kim , T. Kintscher , J. Kiryluk , T. Kittler , S. R. Klein , R. Koirala , H. Kolanoski , L. Köpke , C. Kopper , S. Kopper , J. P. Koschinsky , D. J. Koskinen , M. Kowalski , C. B. Krauss , K. Krings , M. Kroll , G. Krückl , S. Kunwar , N. Kurahashi , T. Kuwabara , A. Kyriacou , M. Labare , J. L. Lanfranchi , M. J. Larson , F. Lauber , D. Lennarz , K. Leonard , M. Lesiak-Bzdak , A. Leszczynska , M. Leuermann , Q. R. Liu , E. Lohfink , J. LoSecco , C. J. Lozano Mariscal , L. Lu , J. Lünemann , W. Luszczak , J. Madsen , G. Maggi , K. B. M. Mahn , S. Mancina , S. Mandalia , S. Marka , Z. Marka , R. Maruyama , K. Mase , R. Maunu , K. Meagher , M. Medici , M. Meier , T. Menne , G. Merino , T. Meures , S. Miarecki , J. Micallef , G. Momenté , T. Montaruli , R. W. Moore , M. Moulai , R. Nahnhauer , P. Nakarmi , U. Naumann , G. Neer , H. Niederhausen , S. C. Nowicki , D. R. Nygren , A. Obertacke Pollmann , M. Oehler , A. Olivas , A. O'Murchadha , E. O'Sullivan , A. Palazzo , T. Palczewski , H. Pandya , D. V. Pankova , L. Papp , P. Peiffer , J. A. Pepper , C. Pérez de los Heros , T. C. Petersen , D. Pieloth , E. Pinat , J. L. Pinfold , M. Plum , P. B. Price , G. T. Przybylski , C. Raab , L. Rädel , M. Rameez , L. Rauch , K. Rawlins , I. C. Rea , R. Reimann , B. Relethford , M. Relich , M. Renschler , E. Resconi , W. Rhode , M. Richman , M. Riegel , S. Robertson , M. Rongen , C. Rott , T. Ruhe , D. Ryckbosch , D. Rysewyk , I. Safa , T. Sälzer , S. E. Sanchez Herrera , A. Sandrock , J. Sandroos , P. Sandstrom , M. Santander , S. Sarkar , S. Sarkar , K. Satalecka , H. Schieler , P. Schlunder , T. Schmidt , A. Schneider , S. Schoenen , S. Schöneberg , F. G. Schröder , L. Schumacher , S. Sclafani , D. Seckel , S. Seunarine , M. H. Shaevitz , J. Soedingrekso , D. Soldin , S. Söldner-Rembold , M. Song , G. M. Spiczak , C. Spiering , J. Stachurska , M. Stamatikos , T. Stanev , A. Stasik , R. Stein , J. Stettner , A. Steuer , T. Stezelberger , R. G. Stokstad , A. Stößl , N. L. Strotjohann , T. Stuttard , G. W. Sullivan , M. Sutherland , I. Taboada , A. Taketa , H. K. M. Tanaka , J. Tatar , F. Tenholt , S. Ter-Antonyan , A. Terliuk , S. Tilav , P. A. Toale , M. N. Tobin , C. Tönnis , S. Toscano , D. Tosi , M. Tselengidou , C. F. Tung , A. Turcati , C. F. Turley , B. Ty , E. Unger , M. Usner , J. Vandenbroucke , W. Van Driessche , D. van Eijk , N. van Eijndhoven , S. Vanheule , J. van Santen , D. Veberic , E. Vogel , M. Vraeghe , C. Walck , A. Wallace , M. Wallraff , F. D. Wandler , N. Wandkowsky , A. Waza , C. Weaver , A. Weindl , M. J. Weiss , C. Wendt , J. Werthebach , S. Westerhoff , B. J. Whelan , K. Wiebe , C. H. Wiebusch , L. Wille , D. R. Williams , L. Wills , M. Wolf , J. Wood , T. R. Wood , E. Woolsey , K. Woschnagg , G. Wrede , S. Wren , D. L. Xu , X. W. Xu , Y. Xu , J. P. Yanez , G. Yodh , S. Yoshida , T. Yuan

Robust inference for stochastic dynamical systems is often hampered by sparse sampling and the absence of closed-form likelihoods. We introduce a Monte Carlo path-inference framework that leverages full-path statistics and bridge processes…

Statistical Mechanics · Physics 2025-10-07 Javier Aguilar , Miguel A. Muñoz , Sandro Azaele

Estimating sample size and statistical power is an essential part of a good study design. This R package allows users to conduct power analysis based on Monte Carlo simulations in settings in which consideration of the correlations between…

Methodology · Statistics 2024-04-16 Phuc H. Nguyen , Stephanie M. Engel , Amy H. Herring

Fairness in machine learning remains challenging due to its ethical complexity, the absence of a universal definition, and the need for context-specific bias metrics. Existing methods still struggle with intersectionality, multiclass…

Machine Learning · Computer Science 2026-05-01 Jeanne Monnier , Thomas George , Frédéric Guyard , Christèle Tarnec , Marios Kountouris

We use Monte Carlo techniques to simulate an organized prediction competition between a group of a scientific experts acting under the influence of a ``self-governing'' prediction reward algorithm. Our aim is to illustrate the advantages of…

Social and Information Networks · Computer Science 2023-05-09 J. O. Gonzalez-Hernandez , Jonathan Marino , Ted Rogers , Brandon Velasco

This review summarizes recent developments in the study of fermionic quantum criticality, focusing on new progress in numerical methodologies, especially quantum Monte Carlo methods, and insights that emerged from recently large-scale…

Strongly Correlated Electrons · Physics 2019-09-10 Xiao Yan Xu , Zi Hong Liu , Gaopei Pan , Yang Qi , Kai Sun , Zi Yang Meng

A new release of the Monte Carlo event generator Herwig (version 7.1) is now available. This version introduces a number of improvements, notably: multi-jet merging with the dipole shower at LO and NLO QCD; a new model for soft interactions…

We present a new quantum Monte Carlo algorithm suitable for generically complex problems, such as systems coupled to external magnetic fields or anyons in two spatial dimensions. We find that the choice of gauge plays a nontrivial role, and…

Condensed Matter · Physics 2009-10-22 Lizeng Zhang , Geoff Canright , Ted Barnes

A careful study of the classical/quantum connection with the aid of coherent states offers new insights into various technical problems. This analysis includes both canonical as well as closely related affine quantization procedures. The…

High Energy Physics - Theory · Physics 2015-06-12 John R. Klauder

A new release of the Monte Carlo program Herwig++ (version 2.1) is now available. This version includes a number of significant improvements including: an eikonal multiple parton-parton scattering model of the underlying event; the…

High Energy Physics - Phenomenology · Physics 2007-11-21 M. Bahr , S. Gieseke , M. Gigg , D. Grellscheid , K. Hamilton , O. Latunde-Dada , S. Platzer , P. Richardson , M. H. Seymour , A. Sherstnev , B. R. Webber

A new release of the Monte Carlo program Herwig++ (version 2.5) is now available. This version comes with a number of improvements including: new next-to-leading order matrix elements, including weak boson pair production; a colour…

High Energy Physics - Phenomenology · Physics 2011-02-09 S. Gieseke , D. Grellscheid , K. Hamilton , A. Papaefstathiou , S. Plätzer , P. Richardson , C. A. Röhr , P. Ruzicka , A. Siódmok , L. Suter , D. Winn

We describe the implementation of the MSSM in the diagram generator FeynArts and the calculational tool FormCalc. This extension allows to perform loop calculations of MSSM processes almost fully automatically. The actual implementation has…

High Energy Physics - Phenomenology · Physics 2009-11-07 T. Hahn , C. Schappacher

Computer programs are not executed in isolation, but rather interact with the execution environment which drives the program behaviors. Software validation methods thus need to capture the effect of possibly complex environmental…

Software Engineering · Computer Science 2024-09-04 Ruijie Meng , Gregory J. Duck , Abhik Roychoudhury

We present a Monte Carlo method to compute efficiently susceptibilites or covariances of two physical variables. The method relies on a generalization of the exchange cluster algorithm to any model of interacting particles with any $2$-body…

Computational Physics · Physics 2025-02-11 Assaraf Roland , Chevreau Hilaire

We present a NNLO QCD accurate event generator for direct photon pair production at hadron colliders, based on the MiNNLOPS formalism, within the POWHEG BOX RES framework. Despite the presence of the photons requires the use of isolation…

High Energy Physics - Phenomenology · Physics 2022-09-28 Alessandro Gavardi , Carlo Oleari , Emanuele Re

Fractal TRIDYN (F-TRIDYN) is a modified version of the widely used Monte Carlo, Binary Collision Approximation code TRIDYN that includes an explicit model of surface roughness and additional output modes for coupling to plasma edge and…

Computational Physics · Physics 2018-03-14 Jon Drobny , Davide Curreli , Alyssa Hayes , David N. Ruzic

FEniCS Mechanics is a Python package to facilitate computational mechanics simulations. The Python library dolfin, from the FEniCS Project, is used to formulate and numerically solve the problem in variational form. The general balance laws…

Computational Engineering, Finance, and Science · Computer Science 2019-01-30 Miguel A. Rodriguez , Christoph M. Augustin , Shawn C. Shadden

The integration of different learning paradigms has long been a focus of machine learning research, aimed at overcoming the inherent limitations of individual methods. Fuzzy rule-based models excel in interpretability and have seen…

Machine Learning · Computer Science 2025-11-12 Jinbo Li , Peng Liu , Long Chen , Witold Pedrycz , Weiping Ding

Much of today's machine learning research involves interpreting, modifying or visualizing models after they are trained. I present Penzai, a neural network library designed to simplify model manipulation by representing models as simple…

Machine Learning · Computer Science 2024-08-02 Daniel D. Johnson

We develop a Monte Carlo event generator for Higgs Boson pair production merged to exact one-jet matrix elements. The matrix elements are generated with OpenLoops and event generation is performed with the HERWIG++ general-purpose event…

High Energy Physics - Phenomenology · Physics 2015-06-18 Philipp Maierhöfer , Andreas Papaefstathiou