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Event shape and charged particle inclusive distributions determined from 750 000 hadronic Z events measured with the DELPHI detector at LEP are presented. The statistical and systematic precision of this data allows for a decisive…

High Energy Physics - Experiment · Physics 2016-08-31 K. Hamacher , M. Weierstall

As deep learning models nowadays are widely adopted by both cloud services and edge devices, reducing the latency of deep learning model inferences becomes crucial to provide efficient model serving. However, it is challenging to develop…

Machine Learning · Computer Science 2023-02-16 Yaoyao Ding , Cody Hao Yu , Bojian Zheng , Yizhi Liu , Yida Wang , Gennady Pekhimenko

The DZERO experiment, located at the Fermi National Accelerator Laboratory, has recently started the Run 2 physics program. The detector upgrade included a new Data Acquisition/Level 3 Trigger system. Part of the design for the DAQ/Trigger…

Recent developments in QCD phenomenology have spurred on several improved approaches to Monte Carlo event generation, relative to the post--LEP state of the art. In this brief review, the emphasis is placed on approaches for 1) consistently…

High Energy Physics - Phenomenology · Physics 2009-11-11 Peter Z. Skands

MeetEval is an open-source toolkit to evaluate all kinds of meeting transcription systems. It provides a unified interface for the computation of commonly used Word Error Rates (WERs), specifically cpWER, ORC-WER and MIMO-WER along other…

Computation and Language · Computer Science 2024-01-29 Thilo von Neumann , Christoph Boeddeker , Marc Delcroix , Reinhold Haeb-Umbach

Recent jet and jet substructure measurements at the LHC, and of machine-learning-based tagging techniques are presented using proton-proton collision data collected by the ATLAS and CMS experiments at CERN's Large Hadron Collider. These…

High Energy Physics - Experiment · Physics 2022-02-10 Meena Meena

The CMS Integration Grid Testbed (IGT) comprises USCMS Tier-1 and Tier-2 hardware at the following sites: the California Institute of Technology, Fermi National Accelerator Laboratory, the University of California at San Diego, and the…

Large-scale machine learning models deliver strong performance across a wide range of tasks but come with significant computational and resource constraints. To mitigate these challenges, local smaller models are often deployed alongside…

Integrated development environments (IDEs) are prevalent code-writing and debugging tools. However, they have yet to be widely adopted for launching machine learning (ML) experiments. This work aims to fill this gap by introducing JetTrain,…

Software Engineering · Computer Science 2024-02-19 Artem Trofimov , Mikhail Kostyukov , Sergei Ugdyzhekov , Natalia Ponomareva , Igor Naumov , Maksim Melekhovets

After the successful conclusion of the CLEO III phase, the CLEO experiment at the Cornell Electron Positron Storage Ring CESR is preparing for its transition to CLEO-c. This new program contains a wide array of Physics studies at e+ e-…

High Energy Physics - Experiment · Physics 2008-11-26 N. Adam , S. Lee , H. Schwarthoff , T. Wilksen

The authors' "metatools" are a collection of tools for generic programming. This includes generating Java sources from mathematically well-founded specifications, as well as the creation of strictly typed document object models for XML…

Software Engineering · Computer Science 2011-11-22 Markus Lepper , Baltasar Trancón y Widemann

We introduce a new algorithm, called CDER, for supervised machine learning that merges the multi-scale geometric properties of Cover Trees with the information-theoretic properties of entropy. CDER applies to a training set of labeled…

Machine Learning · Computer Science 2018-01-23 Abraham Smith , Paul Bendich , John Harer , Alex Pieloch , Jay Hineman

Run II at the Fermilab Tevatron Collider started in March 2001, and it will continue probing the high energy frontier in particle physics until the start of the LHC at CERN. The CDF collaboration at Fermilab has already stored 260 TB of…

Computational Physics · Physics 2008-11-26 P. Jacques , F. Ratnikov , I. Terekhov , T. Watts

The progress of event extraction research has been hindered by the absence of wide-coverage, large-scale datasets. To make event extraction systems more accessible, we build a general-purpose event detection dataset GLEN, which covers 205K…

Computation and Language · Computer Science 2023-11-01 Qiusi Zhan , Sha Li , Kathryn Conger , Martha Palmer , Heng Ji , Jiawei Han

Lidar data can be used to generate point clouds for the navigation of autonomous vehicles or mobile robotics platforms. Scan matching, the process of estimating the rigid transformation that best aligns two point clouds, is the basis for…

Robotics · Computer Science 2022-08-01 Matthew McDermott , Jason Rife

Software systems evolve throughout their life cycles. Many revisions are produced over time. Model checking each revision of the software is impractical. Regression verification suggests reusing intermediate results from the previous…

Software Engineering · Computer Science 2018-06-14 Fei He , Qianshan Yu , Liming Cai

A series of far-detector programs have been proposed for operation at various interaction points of the Large Hadron Collider during the upcoming runs. Investigating the potential and complementarity of these experiments for new-physics…

High Energy Physics - Phenomenology · Physics 2024-07-04 Florian Domingo , Julian Günther , Jong Soo Kim , Zeren Simon Wang

After an introduction to event generators we give an overview of developments in the field of joining matrix elements with parton showers. Starting with matrix element corrections, we also discuss implementations that match LO and NLO…

High Energy Physics - Phenomenology · Physics 2007-05-23 Stefan Gieseke

Scientific metadata often suffer from incompleteness, inconsistency, and formatting errors, which hinder effective discovery and reuse of the associated datasets. We present a method that combines GPT-4 with structured metadata templates…

Information Retrieval · Computer Science 2025-06-10 Sowmya S Sundaram , Rafael S. Gonçalves , Mark A Musen

This article presents an innovative study in exploring, evaluating, and implementing deep learning architectures for the calibration of multi-modal sensor systems. The focus behind this is to leverage the use of sensor fusion to achieve…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Venkat Karramreddy , Liam Mitchell
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