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Natural language is one of the most fundamental features that distinguish people from other living things and enable people to communicate each other. Language is a tool that enables people to express their feelings and thoughts and to…

Computation and Language · Computer Science 2019-05-15 Baris Baburoglu , Adem Tekerek , Mehmet Tekerek

We review the status of, and prospects for, real-time data processing for collider experiments in experimental High Energy Physics. We discuss the historical evolution of data rates and volumes in the field and place them in the context of…

High Energy Physics - Experiment · Physics 2023-11-20 V. V. Gligorov , V. Reković

These lectures were presented at the 2019 CERN Latin-American School of High Energy Physics. They were centered on the experimental methods used in hadron colliders to advance our understanding in the field of high energy particle physics.…

High Energy Physics - Experiment · Physics 2021-06-07 Cecilia E. Gerber

Ab initio wavefunction methods provide accurate molecular simulations but their computational scaling restricts applications to small systems. We develop a workflow combining quantum embedding to decompose a molecule into fragments with a…

We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross-detector fine-tuning study, where we initially pretrain the…

High Energy Physics - Experiment · Physics 2025-06-26 Farouk Mokhtar , Joosep Pata , Dolores Garcia , Eric Wulff , Mengke Zhang , Michael Kagan , Javier Duarte

The European Workshop on Photocathodes for (particle) Accelerator Applications (EWPAA) brings together experts in the field of photocathode based electron sources for use in particle accelerators, with the aim of sharing their knowledge and…

Accelerator Physics · Physics 2023-04-21 L. Monaco , D. Sertore , M. Baylac , L. B. Jones , T. C. Q. Noakes , J. Kühn , R. Xiang

We present a new Deep Dictionary Learning and Coding Network (DDLCN) for image recognition tasks with limited data. The proposed DDLCN has most of the standard deep learning layers (e.g., input/output, pooling, fully connected, etc.), but…

Computer Vision and Pattern Recognition · Computer Science 2020-05-25 Hao Tang , Hong Liu , Wei Xiao , Nicu Sebe

The ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management,…

High Energy Physics - Experiment · Physics 2025-07-17 ATLAS Collaboration

Computation is becoming an increasingly important part of physics education. However, there are currently few theories of learning that can be used to help explain and predict the unique challenges and affordances associated with…

Physics Education · Physics 2020-01-01 Tor Ole B. Odden , Elise Lockwood , Marcos D. Caballero

In recent years, Large Language Models (LLMs) have made significant strides towards Artificial General Intelligence. However, training these models from scratch requires substantial computational resources and vast amounts of text data. In…

Computation and Language · Computer Science 2024-10-03 Wenzhen Zheng , Wenbo Pan , Xu Xu , Libo Qin , Li Yue , Ming Zhou

This EPTCS volume contains the proceedings of the 16th Workshop on Quantitative Aspects of Programming Languages and Systems (QAPL 2019) held in Prague, Czech Republic, on Sunday 7 April 2019. QAPL 2019 was a satellite event of the European…

Programming Languages · Computer Science 2020-01-20 Alessandro Aldini , Herbert Wiklicky

Measurements from the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) can be used to study the properties of quark-gluon plasma. Systematic constraints on these properties must combine measurements from different…

At high energy physics experiments, processing billions of records of structured numerical data from collider events to a few statistical summaries is a common task. The data processing is typically more complex than standard query…

Data Analysis, Statistics and Probability · Physics 2019-10-22 Joosep Pata , Maria Spiropulu

This volume contains a selection of papers presented at Linearity&TLLA 2020, namely the Second Joint International Workshop on Linearity & Trends in Linear Logic and Applications, held on June 29-30, 2020 online. (The workshop was supposed…

Logic in Computer Science · Computer Science 2021-12-30 Ugo Dal Lago , Valeria de Paiva

The IPPOG and U.S. Particle Physics Masterclasses took place worldwide in March 2011. For the first time, all masterclasses used real LHC data. Students in the U.S. Masterclasses (that included participants in several countries outside the…

Physics Education · Physics 2011-09-13 Kenneth Cecire

The ATLAS experiment is designed to study the proton-proton collisions produced at the Large Hadron Collider (LHC) at CERN. Liquid argon sampling calorimeters are used for all electromagnetic calorimetry as well as hadronic calorimetry in…

Instrumentation and Detectors · Physics 2013-07-05 Nikiforos Nikiforou

ATLAS, a general-purpose experiment at the Large Hadron Collider (LHC), makes use of a large internationally-distributed computing infrastructure, including over $10^6$ TB of managed data on disk and tape and almost one million…

High Energy Physics - Experiment · Physics 2026-04-16 ATLAS Collaboration

The ATLAS experiment at the Large Hadron Collider employs a two-level trigger system to record data at an average rate of 1 kHz from physics collisions, starting from an initial bunch crossing rate of 40 MHz. During the LHC Run 2…

Instrumentation and Detectors · Physics 2020-10-09 ATLAS Collaboration

Computational physics is a key part of what it means to do physics in the twenty-first century. However, upper division computational physics remains a largely understudied area. We set out to understand the experiences of students in an…

Physics Education · Physics 2026-03-13 Luke Nearhood , Patti Hamerski

Quantum chemical simulations can be greatly accelerated by constructing machine learning potentials, which is often done using active learning (AL). The usefulness of the constructed potentials is often limited by the high effort required…

Chemical Physics · Physics 2024-09-19 Yi-Fan Hou , Lina Zhang , Quanhao Zhang , Fuchun Ge , Pavlo O. Dral