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Related papers: EOS -- A Software for Flavor Physics Phenomenology

200 papers

The European Open Science Cloud (EOSC) aims to create a federated environment for hosting and processing research data to support science in all disciplines without geographical boundaries, such that data, software, methods and publications…

Instrumentation and Methods for Astrophysics · Physics 2020-07-14 Eva Sciacca , Fabio Vitello , Ugo Becciani , Cristobal Bordiu , Filomena Bufano , Antonio Calanducci , Alessandro Costa , Mario Raciti , Simone Riggi

Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties. The large increase in both consumption and fraud, for example through adulteration, creates new challenges…

We develop a non-parametric method for inferring the universal neutron star (NS) equation of state (EOS) from gravitational wave (GW) observations. Many different possible realizations of the EOS are generated with a Gaussian process…

General Relativity and Quantum Cosmology · Physics 2019-05-08 Philippe Landry , Reed Essick

We introduce the Piquasso quantum programming framework, a full-stack open-source software platform for the simulation and programming of photonic quantum computers. Piquasso can be programmed via a high-level Python programming interface…

This paper lays down the research agenda for a domain-specific foundation model for operating systems (OSes). Our case for a foundation model revolves around the observations that several OS components such as CPU, memory, and network…

We present FlowMO: an open-source Python library for molecular property prediction with Gaussian Processes. Built upon GPflow and RDKit, FlowMO enables the user to make predictions with well-calibrated uncertainty estimates, an output…

Machine Learning · Computer Science 2020-10-15 Henry B. Moss , Ryan-Rhys Griffiths

The equation of state (EOS) embodies thermodynamic properties of compressible fluid materials and usually has very complicated forms in real engineering applications, subject to the physical requirements of thermodynamics. The complexity of…

Numerical Analysis · Mathematics 2021-09-01 Yue Wang , Jiequan Li

We study characteristics of the relativistic equation of state (EOS) for collapse-driven supernovae, which is derived by relativistic nuclear many body theory. Recently the relativistic EOS table has become available as a new complete set…

Nuclear Theory · Physics 2015-06-26 K. Sumiyoshi , H. Suzuki , S. Yamada , H. Toki

The advent of deep learning has yielded powerful tools to automatically compute gradients of computations. This is because training a neural network equates to iteratively updating its parameters using gradient descent to find the minimum…

Data Analysis, Statistics and Probability · Physics 2023-03-01 Nathan Simpson , Lukas Heinrich

In this paper, we make the first attempt to understand and test potential computation efficiency robustness in state-of-the-art LLMs. By analyzing the working mechanism and implementation of 20,543 public-accessible LLMs, we observe a…

Computation and Language · Computer Science 2024-05-28 Xiaoning Feng , Xiaohong Han , Simin Chen , Wei Yang

Software development in high energy physics experiments offers unique experience with rapidly changing environment and variety of different standards and frameworks that software must be adapted to. As such, regular methods of software…

High Energy Physics - Phenomenology · Physics 2010-09-21 Tomasz Przedzinski

FrOoDo is an easy-to-use and flexible framework for Out-of-Distribution detection tasks in digital pathology. It can be used with PyTorch classification and segmentation models, and its modular design allows for easy extension. The goal is…

Computer Vision and Pattern Recognition · Computer Science 2024-02-16 Jonathan Stieber , Moritz Fuchs , Anirban Mukhopadhyay

Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Since its introduction, it has been one of the most used CPU and GPU mathematical compilers -…

Symbolic Computation · Computer Science 2016-05-10 The Theano Development Team , Rami Al-Rfou , Guillaume Alain , Amjad Almahairi , Christof Angermueller , Dzmitry Bahdanau , Nicolas Ballas , Frédéric Bastien , Justin Bayer , Anatoly Belikov , Alexander Belopolsky , Yoshua Bengio , Arnaud Bergeron , James Bergstra , Valentin Bisson , Josh Bleecher Snyder , Nicolas Bouchard , Nicolas Boulanger-Lewandowski , Xavier Bouthillier , Alexandre de Brébisson , Olivier Breuleux , Pierre-Luc Carrier , Kyunghyun Cho , Jan Chorowski , Paul Christiano , Tim Cooijmans , Marc-Alexandre Côté , Myriam Côté , Aaron Courville , Yann N. Dauphin , Olivier Delalleau , Julien Demouth , Guillaume Desjardins , Sander Dieleman , Laurent Dinh , Mélanie Ducoffe , Vincent Dumoulin , Samira Ebrahimi Kahou , Dumitru Erhan , Ziye Fan , Orhan Firat , Mathieu Germain , Xavier Glorot , Ian Goodfellow , Matt Graham , Caglar Gulcehre , Philippe Hamel , Iban Harlouchet , Jean-Philippe Heng , Balázs Hidasi , Sina Honari , Arjun Jain , Sébastien Jean , Kai Jia , Mikhail Korobov , Vivek Kulkarni , Alex Lamb , Pascal Lamblin , Eric Larsen , César Laurent , Sean Lee , Simon Lefrancois , Simon Lemieux , Nicholas Léonard , Zhouhan Lin , Jesse A. Livezey , Cory Lorenz , Jeremiah Lowin , Qianli Ma , Pierre-Antoine Manzagol , Olivier Mastropietro , Robert T. McGibbon , Roland Memisevic , Bart van Merriënboer , Vincent Michalski , Mehdi Mirza , Alberto Orlandi , Christopher Pal , Razvan Pascanu , Mohammad Pezeshki , Colin Raffel , Daniel Renshaw , Matthew Rocklin , Adriana Romero , Markus Roth , Peter Sadowski , John Salvatier , François Savard , Jan Schlüter , John Schulman , Gabriel Schwartz , Iulian Vlad Serban , Dmitriy Serdyuk , Samira Shabanian , Étienne Simon , Sigurd Spieckermann , S. Ramana Subramanyam , Jakub Sygnowski , Jérémie Tanguay , Gijs van Tulder , Joseph Turian , Sebastian Urban , Pascal Vincent , Francesco Visin , Harm de Vries , David Warde-Farley , Dustin J. Webb , Matthew Willson , Kelvin Xu , Lijun Xue , Li Yao , Saizheng Zhang , Ying Zhang

Harnessing modern parallel computing resources to achieve complex multi-physics simulations is a daunting task. The Multiphysics Object Oriented Simulation Environment (MOOSE) aims to enable such development by providing simplified…

Software Engineering practitioners work using highly diverse methods and practices, and general theories in software engineering are lacking. One attempt at creating a common ground in the area of software engineering methodologies has been…

Software Engineering · Computer Science 2018-08-09 Arthur Evensen , Kai-Kristian Kemell , Xiaofeng Wang , Juhani Risku , Pekka Abrahamsson

PySEMTools is a Python-based library for post-processing simulation data produced with high-order hexahedral elements in the context of the spectral element method in computational fluid dynamics. It aims to minimize intermediate steps…

Computational Physics · Physics 2025-04-18 Adalberto Perez , Siavash Toosi , Tim Felle Olsen , Stefano Markidis , Philipp Schlatter

We present the public release of EXP, a basis function expansion C++ library and Python package for running N-body galactic simulations and dynamical discovery. EXP grew out of the need for methodology that seamlessly connects theoretical…

Astrophysics of Galaxies · Physics 2025-05-13 Michael S. Petersen , Martin D. Weinberg

The EPOS-HQ model is a framework designed for predicting heavy-flavor observables both in p-p, p-A and A-A collisions. It results from the integration of the MC$@_s$HQ and EPOS3 codes and should supersede predictions made with each of these…

High Energy Physics - Phenomenology · Physics 2019-01-15 Pol Bernard Gossiaux , Joerg Aichelin , Benjamin Guiot , Iurii Karpenko , Vitalii Ozvenchuk , Tanguy Pierog , Jan Steinheimer , Klaus Werner

The nuclear equation of state (EOS) is at the center of numerous theoretical and experimental efforts in nuclear physics. With advances in microscopic theories for nuclear interactions, the availability of experiments probing nuclear matter…

Nuclear Theory · Physics 2024-01-29 Agnieszka Sorensen , Kshitij Agarwal , Kyle W. Brown , Zbigniew Chajęcki , Paweł Danielewicz , Christian Drischler , Stefano Gandolfi , Jeremy W. Holt , Matthias Kaminski , Che-Ming Ko , Rohit Kumar , Bao-An Li , William G. Lynch , Alan B. McIntosh , William G. Newton , Scott Pratt , Oleh Savchuk , Maria Stefaniak , Ingo Tews , ManYee Betty Tsang , Ramona Vogt , Hermann Wolter , Hanna Zbroszczyk , Navid Abbasi , Jörg Aichelin , Anton Andronic , Steffen A. Bass , Francesco Becattini , David Blaschke , Marcus Bleicher , Christoph Blume , Elena Bratkovskaya , B. Alex Brown , David A. Brown , Alberto Camaiani , Giovanni Casini , Katerina Chatziioannou , Abdelouahad Chbihi , Maria Colonna , Mircea Dan Cozma , Veronica Dexheimer , Xin Dong , Travis Dore , Lipei Du , José A. Dueñas , Hannah Elfner , Wojciech Florkowski , Yuki Fujimoto , Richard J. Furnstahl , Alexandra Gade , Tetyana Galatyuk , Charles Gale , Frank Geurts , Fabiana Gramegna , Sašo Grozdanov , Kris Hagel , Steven P. Harris , Wick Haxton , Ulrich Heinz , Michal P. Heller , Or Hen , Heiko Hergert , Norbert Herrmann , Huan Zhong Huang , Xu-Guang Huang , Natsumi Ikeno , Gabriele Inghirami , Jakub Jankowski , Jiangyong Jia , José C. Jiménez , Joseph Kapusta , Behruz Kardan , Iurii Karpenko , Declan Keane , Dmitri Kharzeev , Andrej Kugler , Arnaud Le Fèvre , Dean Lee , Hong Liu , Michael A. Lisa , William J. Llope , Ivano Lombardo , Manuel Lorenz , Tommaso Marchi , Larry McLerran , Ulrich Mosel , Anton Motornenko , Berndt Müller , Paolo Napolitani , Joseph B. Natowitz , Witold Nazarewicz , Jorge Noronha , Jacquelyn Noronha-Hostler , Grażyna Odyniec , Panagiota Papakonstantinou , Zuzana Paulínyová , Jorge Piekarewicz , Robert D. Pisarski , Christopher Plumberg , Madappa Prakash , Jørgen Randrup , Claudia Ratti , Peter Rau , Sanjay Reddy , Hans-Rudolf Schmidt , Paolo Russotto , Radoslaw Ryblewski , Andreas Schäfer , Björn Schenke , Srimoyee Sen , Peter Senger , Richard Seto , Chun Shen , Bradley Sherrill , Mayank Singh , Vladimir Skokov , Michał Spaliński , Jan Steinheimer , Mikhail Stephanov , Joachim Stroth , Christian Sturm , Kai-Jia Sun , Aihong Tang , Giorgio Torrieri , Wolfgang Trautmann , Giuseppe Verde , Volodymyr Vovchenko , Ryoichi Wada , Fuqiang Wang , Gang Wang , Klaus Werner , Nu Xu , Zhangbu Xu , Ho-Ung Yee , Sherry Yennello , Yi Yin

In many real-world applications, we are interested in approximating black-box, costly functions as accurately as possible with the smallest number of function evaluations. A complex computer code is an example of such a function. In this…

Computation · Statistics 2022-03-22 Hossein Mohammadi , Peter Challenor , Daniel Williamson , Marc Goodfellow