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Related papers: Data Preservation in High Energy Physics

200 papers

It is becoming increasingly important that physics educators equip their students with the skills to work with data effectively. However, many educators may lack the necessary training and expertise in data science to teach these skills. To…

HEP community leads and operates cutting-edge experiments for the DOE Office of Science which have challenging sensing, data processing, and computing requirements that far surpass typical industrial applications. To make necessary progress…

Physics and Society · Physics 2022-10-05 Farah Fahim , Alex Murokh , Koji Yoshimura

Laser-plasma physics has developed rapidly over the past few decades as high-power lasers have become both increasingly powerful and more widely available. Early experimental and numerical research in this field was restricted to…

Machine Learning · Computer Science 2023-05-25 Andreas Döpp , Christoph Eberle , Sunny Howard , Faran Irshad , Jinpu Lin , Matthew Streeter

The INSPIRE platform -- the most widely-used discovery service specifically tailored to the needs of researchers in High Energy Physics (HEP) -- has become a central component of the information infrastructure for the discipline. Despite…

High Energy Physics - Phenomenology · Physics 2025-06-04 Sabine Crépé-Renaudin , Alexander Kohls , Micha Moskovic , Heath O'Connell , Kirsten Sachs , Jian Yu

I would like to thank Junk and Lyons (arXiv:2009.06864) for beginning a discussion about replication in high-energy physics (HEP). Junk and Lyons ultimately argue that HEP learned its lessons the hard way through past failures and that…

Data Analysis, Statistics and Probability · Physics 2021-05-10 Andrew Fowlie

Scientific processes rely on software as an important tool for data acquisition, analysis, and discovery. Over the years sustainable software development practices have made progress in being considered as an integral component of research.…

Software Engineering · Computer Science 2023-12-21 Akash Dhruv , Anshu Dubey

The Large Hadron Collider will provide an unprecedented quantity of collision data right from the start-up. The challenge for the LHC experiments is the quick use of these data for the final commissioning of the detectors, including…

High Energy Physics - Experiment · Physics 2007-05-23 Kati Lassila-Perini

The CMS experiment at the LHC accelerator at CERN relies on its computing infrastructure to stay at the frontier of High Energy Physics, searching for new phenomena and making discoveries. Even though computing plays a significant role in…

Data Analysis, Statistics and Probability · Physics 2016-12-21 Valentin Kuznetsov , Ting Li , Luca Giommi , Daniele Bonacorsi , Tony Wildish

This paper discusses experimental techniques and considerations associated with the transition to high repetition-rate experiments in High Energy Density Physics (HEDP). We particularly highlight approaches to experimentation that become…

Plasma Physics · Physics 2019-06-28 Scott Feister , Patrick L. Poole , Peter V. Heuer

The HERA electron--proton collider has collected 100 pb$^{-1}$ of data since its start-up in 1992, and recently moved into a high-luminosity operation mode, with upgraded detectors, aiming to increase the total integrated luminosity per…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. Alekhin , G. Altarelli , N. Amapane , J. Andersen , V. Andreev , M. Arneodo , V. Avati , J. Baines , R. D. Ball , A. Banfi , S. P. Baranov , J. Bartels , O. Behnke , R. Bellan , J. Blumlein , H. Bottcher , S. Bolognesi , M. Boonekamp , D. Bourilkov , J. Bracinik , A. Bruni , G. Bruni , A. Buckley , A. Bunyatyan , C. M. Buttar , J. M. Butterworth , S. Butterworth , M. Cacciari , T. Carli , G. Cerminara , S. Chekanov , M. Ciafaloni , D. Colferai , J. Collins , A. Cooper-Sarkar , G. Corcella , M. Corradi , B. E. Cox , R. Croft , Z. Czyczula , A. Dainese , M. Dasgupta , G. Davatz , L. Del Debbio , Y. Delenda , A. De Roeck , M. Diehl , S. Diglio , G. Dissertori , M. Dittmar , J. Ellis , K. J. Eskola , T. O. Eynck , J. Feltesse , F. Ferro , R. D. Field , J. Forshaw , S. Forte , A. Geiser , S. Gieseke , A. Glazov , T. Gleisberg , P. Golonka , E. Gotsman , G. Grindhammer , M. Grothe , C. Group , M. Groys , A. Guffanti , G. Gustafson , C. Gwenlan , S. Hoche , C. Hogg , J. Huston , G. Iacobucci , G. Ingelman , S. Jadach , H. Jung , J. Kalliopuska , M. Kapishin , B. Kersevan , V. Khoze , M. Klasen , M. Klein , B. A. Kniehl , V. J. Kolhinen , H. Kowalski , G. Kramer , F. Krauss , S. Kretzer , K. Kutak , J. W. Lamsa , L. Lonnblad , T. Lastovicka , G. Lastovicka-Medin , E. Laenen , Th. Lagouri , J. I. Latorre , N. Lavesson , V. Lendermann , E. Levin , A. Levy , A. V. Lipatov , M. Lublinsky , L. Lytkin , T. Maki , L. Magnea , F. Maltoni , M. Mangano , U. Maor , C. Mariotti , N. Marola , A. D. Martin , A. Meyer , S. Moch , J. Monk , A. Moraes , A. Morsch , L. Motyka , E. Naftali , P. Newman , A. Nikitenko , F. Oljemark , R. Orava , M. Ottela , K. Osterberg , K. Peters , F. Petrucci , A. Piccione , A. Pilkington , K. Piotrzkowski , O. I. Piskounova , A. Proskuryakov , A. Prygarin , J. Pumplin , K. Rabbertz , R. Ranieri , V. Ravindran , B. Reisert , E. Richter-Was , L. Rinaldi , P. Robbe , E. Rodrigues , J. Rojo , H. Ruiz , M. Ruspa , M. G. Ryskin , A. Sabio Vera , G. P. Salam , A. Schalicke , S. Schatzel , T. Schorner-Sadenius , I. Schienbein , F-P. Schilling , S. Schumann , M. H. Seymour , F. Siegert , T. Sjostrand , M. Skrzypek , J. Smith , M. Smizanska , H. Spiesberger , F. Schrempp , A. Stasto , H. Stenzel , W. J. Stirling , P. Szczypka , S. Tapprogge , C. Targett-Adams , M. Tasevsky , T. Teubner , R. S. Thorne , A. Tonazzo , A. Tricoli , N. Tuning , J. Turnau , U. Uwer , P. Van Mechelen , R. Venugopalan , M. Verducci , J. A. M. Vermaseren , A. Vogt , R. Vogt , B. F. L. Ward , Z. Was , G. Watt , B. M. Waugh , C. Weiser , M. R. Whalley , M. Wing , J. Winter , S. A. Yost , G. Zanderighi , N. P. Zotov

We describe the plans and objectives of the CEDAR project (Combined e-Science Data Analysis Resource for High Energy Physics) newly funded by the PPARC e-Science programme in the UK. CEDAR will combine the strengths of the well established…

High Energy Physics - Phenomenology · Physics 2007-05-23 J. M. Butterworth , S. Butterworth , B. M. Waugh , W. J. Stirling , M. R. Whalley

The field of high energy physics (HEP) has seen a marked increase in the use of machine learning (ML) techniques in recent years. The proliferation of applications has revolutionised many aspects of the data processing pipeline at collider…

This proposal concerns the participation of the Brazilian High-Energy Physics community in the next-generation collider experiments. As the LHC at CERN is getting ready for its third data-taking period, Run 3, with increased centre-of-mass…

The ability to read, use and develop code efficiently and successfully is a key ingredient in modern particle physics. We report the experience of a training program, identified as "Advanced Programming Concepts", that introduces software…

Physics Education · Physics 2016-01-20 Stefan Kluth , Maria Grazia Pia , Thomas Schoerner-Sadenius , Peter Steinbach

In this new era of large data, it is important to make sure we do not miss any signs of new physics. Using the publicly-available open data collected by the arXiv.org experiment in the \texttt{hep-ph} channel, corresponding to a raw total…

High Energy Physics - Phenomenology · Physics 2025-04-01 Rikab Gambhir

Beginning from a basic neural-network architecture, we test the potential benefits offered by a range of advanced techniques for machine learning, in particular deep learning, in the context of a typical classification problem encountered…

Data Analysis, Statistics and Probability · Physics 2020-06-03 Giles Chatham Strong

The HERA electron--proton collider has collected 100 pb$^{-1}$ of data since its start-up in 1992, and recently moved into a high-luminosity operation mode, with upgraded detectors, aiming to increase the total integrated luminosity per…

High Energy Physics - Phenomenology · Physics 2007-05-23 S. Alekhin , G. Altarelli , N. Amapane , J. Andersen , V. Andreev , M. Arneodo , V. Avati , J. Baines , R. D. Ball , A. Banfi , S. P. Baranov , J. Bartels , O. Behnke , R. Bellan , J. Blumlein , H. Bottcher , S. Bolognesi , M. Boonekamp , D. Bourilkov , J. Bracinik , A. Bruni , G. Bruni , A. Buckley , A. Bunyatyan , C. M. Buttar , J. M. Butterworth , S. Butterworth , M. Cacciari , T. Carli , G. Cerminara , S. Chekanov , M. Ciafaloni , D. Colferai , J. Collins , A. Cooper-Sarkar , G. Corcella , M. Corradi , B. E. Cox , R. Croft , Z. Czyczula , A. Dainese , M. Dasgupta , G. Davatz , L. Del Debbio , Y. Delenda , A. De Roeck , M. Diehl , S. Diglio , G. Dissertori , M. Dittmar , J. Ellis , K. J. Eskola , T. O. Eynck , J. Feltesse , F. Ferro , R. D. Field , J. Forshaw , S. Forte , A. Geiser , S. Gieseke , A. Glazov , T. Gleisberg , P. Golonka , E. Gotsman , G. Grindhammer , M. Grothe , C. Group , M. Groys , A. Guffanti , G. Gustafson , C. Gwenlan , S. Hoche , C. Hogg , J. Huston , G. Iacobucci , G. Ingelman , S. Jadach , H. Jung , J. Kalliopuska , M. Kapishin , B. Kersevan , V. Khoze , M. Klasen , M. Klein , B. A. Kniehl , V. J. Kolhinen , H. Kowalski , G. Kramer , F. Krauss , S. Kretzer , K. Kutak , J. W. Lamsa , L. Lonnblad , T. Lastovicka , G. Lastovicka-Medin , E. Laenen , Th. Lagouri , J. I. Latorre , N. Lavesson , V. Lendermann , E. Levin , A. Levy , A. V. Lipatov , M. Lublinsky , L. Lytkin , T. Maki , L. Magnea , F. Maltoni , M. Mangano , U. Maor , C. Mariotti , N. Marola , A. D. Martin , A. Meyer , S. Moch , J. Monk , A. Moraes , A. Morsch , L. Motyka , E. Naftali , P. Newman , A. Nikitenko , F. Oljemark , R. Orava , M. Ottela , K. Osterberg , K. Peters , F. Petrucci , A. Piccione , A. Pilkington , K. Piotrzkowski , O. I. Piskounova , A. Proskuryakov , A. Prygarin , J. Pumplin , K. Rabbertz , R. Ranieri , V. Ravindran , B. Reisert , E. Richter-Was , L. Rinaldi , P. Robbe , E. Rodrigues , J. Rojo , H. Ruiz , M. Ruspa , M. G. Ryskin , A. Sabio Vera , G. P. Salam , A. Schalicke , S. Schatzel , T. Schorner-Sadenius , I. Schienbein , F-P. Schilling , S. Schumann , M. H. Seymour , F. Siegert , T. Sjostrand , M. Skrzypek , J. Smith , M. Smizanska , H. Spiesberger , F. Schrempp , A. Stasto , H. Stenzel , W. J. Stirling , P. Szczypka , S. Tapprogge , C. Targett-Adams , M. Tasevsky , T. Teubner , R. S. Thorne , A. Tonazzo , A. Tricoli , N. Tuning , J. Turnau , U. Uwer , P. Van Mechelen , R. Venugopalan , M. Verducci , J. A. M. Vermaseren , A. Vogt , R. Vogt , B. F. L. Ward , Z. Was , G. Watt , B. M. Waugh , C. Weiser , M. R. Whalley , M. Wing , J. Winter , S. A. Yost , G. Zanderighi , N. P. Zotov

The lectures address some of the issues of triggering and data acquisition in large high-energy physics experiments. Emphasis is placed on hadron-collider experiments that present a particularly challenging environment for event selection…

Instrumentation and Detectors · Physics 2010-10-15 N. Ellis

ROOT is high energy physics' software for storing and mining data in a statistically sound way, to publish results with scientific graphics. It is evolving since 25 years, now providing the storage format for more than one exabyte of data;…