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Hybrid model predictive control with both continuous and discrete variables is widely applicable to robotic control tasks, especially those involving contacts with the environment. Due to combinatorial complexity, the solving speed of…

Robotics · Computer Science 2025-12-22 Xuan Lin

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements.…

High Energy Physics - Phenomenology · Physics 2025-02-28 J. M. Campbell , M. Diefenthaler , T. J. Hobbs , S. Höche , J. Isaacson , F. Kling , S. Mrenna , J. Reuter , S. Alioli , J. R. Andersen , C. Andreopoulos , A. M. Ankowski , E. C. Aschenauer , A. Ashkenazi , M. D. Baker , J. L. Barrow , M. van Beekveld , G. Bewick , S. Bhattacharya , N. Bhuiyan , C. Bierlich , E. Bothmann , P. Bredt , A. Broggio , A. Buckley , A. Butter , J. M. Butterworth , E. P. Byrne , C. M. Carloni Calame , S. Chakraborty , X. Chen , M. Chiesa , J. T. Childers , J. Cruz-Martinez , J. Currie , N. Darvishi , M. Dasgupta , A. Denner , F. A. Dreyer , S. Dytman , B. K. El-Menoufi , T. Engel , S. Ferrario Ravasio , D. Figueroa , L. Flower , J. R. Forshaw , R. Frederix , A. Friedland , S. Frixione , H. Gallagher , K. Gallmeister , S. Gardiner , R. Gauld , J. Gaunt , A. Gavardi , T. Gehrmann , A. Gehrmann-De Ridder , L. Gellersen , W. Giele , S. Gieseke , F. Giuli , E. W. N. Glover , M. Grazzini , A. Grohsjean , C. Gütschow , K. Hamilton , T. Han , R. Hatcher , G. Heinrich , I. Helenius , O. Hen , V. Hirschi , M. Höfer , J. Holguin , A. Huss , P. Ilten , S. Jadach , A. Jentsch , S. P. Jones , W. Ju , S. Kallweit , A. Karlberg , T. Katori , M. Kerner , W. Kilian , M. M. Kirchgaeßer , S. Klein , M. Knobbe , C. Krause , F. Krauss , J. Lang , J. -N. Lang , G. Lee , S. W. Li , M. A. Lim , J. M. Lindert , D. Lombardi , L. Lönnblad , M. Löschner , N. Lurkin , Y. Ma , P. Machado , V. Magerya , A. Maier , I. Majer , F. Maltoni , M. Marcoli , G. Marinelli , M. R. Masouminia , P. Mastrolia , O. Mattelaer , J. Mazzitelli , J. McFayden , R. Medves , P. Meinzinger , J. Mo , P. F. Monni , G. Montagna , T. Morgan , U. Mosel , B. Nachman , P. Nadolsky , R. Nagar , Z. Nagy , D. Napoletano , P. Nason , T. Neumann , L. J. Nevay , O. Nicrosini , J. Niehues , K. Niewczas , T. Ohl , G. Ossola , V. Pandey , A. Papadopoulou , A. Papaefstathiou , G. Paz , M. Pellen , G. Pelliccioli , T. Peraro , F. Piccinini , L. Pickering , J. Pires , W. Płaczek , S. Plätzer , T. Plehn , S. Pozzorini , S. Prestel , C. T. Preuss , A. C. Price , S. Quackenbush , E. Re , D. Reichelt , L. Reina , C. Reuschle , P. Richardson , M. Rocco , N. Rocco , M. Roda , A. Rodriguez Garcia , S. Roiser , J. Rojo , L. Rottoli , G. P. Salam , M. Schönherr , S. Schuchmann , S. Schumann , R. Schürmann , L. Scyboz , M. H. Seymour , F. Siegert , A. Signer , G. Singh Chahal , A. Siódmok , T. Sjöstrand , P. Skands , J. M. Smillie , J. T. Sobczyk , D. Soldin , D. E. Soper , A. Soto-Ontoso , G. Soyez , G. Stagnitto , J. Tena-Vidal , O. Tomalak , F. Tramontano , S. Trojanowski , Z. Tu , S. Uccirati , T. Ullrich , Y. Ulrich , M. Utheim , A. Valassi , A. Verbytskyi , R. Verheyen , M. Wagman , D. Walker , B. R. Webber , L. Weinstein , O. White , J. Whitehead , M. Wiesemann , C. Wilkinson , C. Williams , R. Winterhalder , C. Wret , K. Xie , T-Z. Yang , E. Yazgan , G. Zanderighi , S. Zanoli , K. Zapp

Brownian particles interacting sequentially with distinct temperatures and driving forces at each stroke have been tackled as a reliable alternative for the construction of engine setups. However they can behave very inefficiently depending…

Statistical Mechanics · Physics 2022-12-28 Iago N. Mamede , Angel L. L. Stable , C. E. Fiore

The optimized random phase approximation (ORPA) for classical liquids is re-examined in the framework of the generating functional approach to the integral equations. We show that the two main variants of the approximation correspond to the…

Chemical Physics · Physics 2009-10-30 G. Pastore , O. Akinlade , F. Matthews , Z. Badirkhan

Metal hydrides are promising candidates for hydrogen storage applications. From a materials discovery perspective, an accurate, efficient computational workflow is urgently required that can rapidly analyze/predict thermodynamic properties…

Materials Science · Physics 2023-08-08 Swati Rana , Dayadeep S. Monder , Abhijit Chatterjee

We develop a physics-based model for classical computation based on autonomous quantum thermal machines. These machines consist of few interacting quantum bits (qubits) connected to several environments at different temperatures. Heat flows…

Quantum Physics · Physics 2025-03-06 Patryk Lipka-Bartosik , Martí Perarnau-Llobet , Nicolas Brunner

We introduce the `nhppp' package for simulating events from one-dimensional non-homogeneous Poisson point processes (NHPPPs) in R fast and with a small memory footprint. We developed it to facilitate the sampling of event times in discrete…

Computation · Statistics 2024-05-30 Thomas A. Trikalinos , Yuliia Sereda

The PYTHIA program can be used to generate high-energy-physics `events', i.e. sets of outgoing particles produced in the interactions between two incoming particles. The objective is to provide as accurate as possible a representation of…

High Energy Physics - Phenomenology · Physics 2009-11-11 Torbjorn Sjostrand , Stephen Mrenna , Peter Skands

Our recently developed 2+1 (boost-invariant) hydrodynamic model has been presented and used to i) describe the soft hadronic data collected in the central region of the relativistic heavy-ion collisions at RHIC and ii) to make predictions…

Nuclear Theory · Physics 2011-02-02 Mikolaj Chojnacki

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

Quantum turbulence can be generated in superfluid helium either thermally (by applying a heat flux, as in thermal counterflow) or mechanically (by stirring the liquid). By modelling the superfluid vortex lines as reconnecting space curves…

Other Condensed Matter · Physics 2015-06-04 A. W. Baggaley , L. K. Sherwin , C. F. Barenghi , Y. A. Sergeev

We discuss the phenomenon of energization of relativistic charged particles in three-dimensional (3D) incompressible MHD turbulence and the diffusive properties of the motion of the same particles. We show that the random electric field…

High Energy Astrophysical Phenomena · Physics 2022-04-05 Oreste Pezzi , Pasquale Blasi , William H. Matthaeus

We review the Random Batch Methods (RBM) for interacting particle systems consisting of $N$-particles, with $N$ being large. The computational cost of such systems is of $O(N^2)$, which is prohibitively expensive. The RBM methods use small…

Numerical Analysis · Mathematics 2021-04-12 Shi Jin , Lei Li

Machine learning techniques are powerful tools for construction of emulators for complex systems. We explore different machine learning methods and conceptual methodologies, ranging from functional approximations to dynamical…

Dynamical Systems · Mathematics 2021-01-01 Hannah Lu , Dinara Ermakova , Haruko Murakami Wainwright , Liange Zheng , Daniel M. Tartakovsky

Monte Carlo simulations of systems of particles such as hard spheres or soft spheres with singular kernels can display around a phase transition prohibitively long convergence times when using traditional Hasting-Metropolis reversible…

Statistical Mechanics · Physics 2023-10-10 Athina Monemvassitis , Arnaud Guillin , Manon Michel

Thermodynamics is traditionally concerned with systems comprised of a large number of particles. Here we present a framework for extending thermodynamics to individual quantum systems, including explicitly a thermal bath and work-storage…

Quantum Physics · Physics 2014-09-29 Paul Skrzypczyk , Anthony J. Short , Sandu Popescu

This paper introduces a random-batch molecular dynamics (RBMD) package for fast simulations of particle systems at the nano/micro scale. Different from existing packages, the RBMD uses random batch methods for nonbonded interactions of…

Computational Physics · Physics 2025-11-11 Weihang Gao , Teng Zhao , Yongfa Guo , Jiuyang Liang , Huan Liu , Maoying Luo , Zedong Luo , Wei Qin , Yichao Wang , Qi Zhou , Shi Jin , Zhenli Xu

The hadron production in heavy ion collision is treated in the framework of thermodynamic vision. Thermodynamic system formed during central collision of Pb-Pb at high energies is considered, through which binary collision is assumed among…

High Energy Physics - Phenomenology · Physics 2017-08-23 Wedad AL-Harbi , Tarek Hussein

The HL-LHC phase is designed to increase by an order of magnitude the amount of data to be collected by the LHC experiments. To achieve this goal in a reasonable time scale the instantaneous luminosity would also increase by an order of…

Instrumentation and Detectors · Physics 2016-09-21 F. Lagarde , M. Gouzevitch , I. Laktineh , V. Buridon , X. Chen , C. Combaret , A. Eynard , L. Germani , G. Grenier , H. Mathez , L. Mirabito , A. Petrukhin , A. Steen , W. Tromeuraa , Y. Wang , A. Gongab , N. Moreau , C. de la Taille , F. Dulucqac , A. Cimmino , S. Crucy , A. Fagot , M. Gul , A. A. O. Rios , M. Tytgat , N. Zaganidisb , S. Aly , Y. Assran , A. Radi , A. Sayedc , G. Singhd , M. Abbrescia , G. Iaselli , M. Maggi , G. Pugliese , P. Verwilligene , W. Van Doninck , S. Colafranceschi , A. Sharmag , L. Benussi , S. Bianco , D. Piccolo , F. Primaverah , V. Bhatnagar , R. Kumari , A. Mehta , J. Singhi , A. Ahmad , W. Ahmed , H. M. I. Asghar , I. M. Awan , R. Hoorani , S. Muhammad , H. Shahzad , M. A. Shah , S. W. Cho , S. Y. Choi , B. Hong , M. H. Kang , K. S. Lee , J. H. Lim , S. K. Parkk , M. S. Kiml , S. Carpinteyro Bernardino , I. Pedraza , C. Uribe Estradam , S. Carrillo Moreno , F. Vazquez Valencian , L. M. Panto , S. Buontempo , N. Cavallo , M. Esposito , F. Fabozzi , G. Lanza , I. Orso , L. Lista , S. Meola , M. Merola , P. Paolucci , F. Thyssen , A. Braghieri , A. Magnani , P. Montagna , C. Riccardi , P. Salvini , I. Vai , P. Vituloq , Y. Ban , S. J. Qianr , M. Choi , Y. Choi , J. Goh , D. Kimt , A. Aleksandrov , R. Hadjiiska , P. Iaydjiev , M. Rodozov , S. Stoykova , G. Sultanov , M. Vutovau , A. Dimitrov , L. Litov , B. Pavlov , P. Petkovv , I. Bagaturia , D. Lomidzew , C. Avila , A. Cabrera , J. C. Sanabria , I. Crottyy , J. Vaitkusz

We introduce a novel method for obtaining a wide variety of moments of any random variable with a well-defined moment-generating function (MGF). We derive new expressions for fractional moments and fractional absolute moments, both central…

Econometrics · Economics 2025-10-21 Peter Reinhard Hansen , Chen Tong