168 research outputs found
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Searches for exotic particles at the Fermilab Tevatron
Searches for new particles have been conducted at the Tevatron using data from the 1992{ 1996 data sets. Brief descriptions of searches for vector leptoquarks, Dirac monopoles and technicolor particles are presented here
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Status of the HEPVis class library
Since 1994 a group of High Energy Physicists and Computer Scientists have been collaborating on HEPVis, a library of 2-D and 3-D shapes for detector visualization and HEP analysis. Based on the Open Inventor (1) toolkit, HEPVis has grown into an international collaboration since its inception in 1994. This paper describes the library, its history, and its future. Images from HEP applications that use the library are also included
Machine Learning in Nuclear Physics
Advances in machine learning methods provide tools that have broad
applicability in scientific research. These techniques are being applied across
the diversity of nuclear physics research topics, leading to advances that will
facilitate scientific discoveries and societal applications.
This Review gives a snapshot of nuclear physics research which has been
transformed by machine learning techniques.Comment: Comments are welcom
Status Report of the DPHEP Study Group: Towards a Global Effort for Sustainable Data Preservation in High Energy Physics
Data from high-energy physics (HEP) experiments are collected with
significant financial and human effort and are mostly unique. An
inter-experimental study group on HEP data preservation and long-term analysis
was convened as a panel of the International Committee for Future Accelerators
(ICFA). The group was formed by large collider-based experiments and
investigated the technical and organisational aspects of HEP data preservation.
An intermediate report was released in November 2009 addressing the general
issues of data preservation in HEP. This paper includes and extends the
intermediate report. It provides an analysis of the research case for data
preservation and a detailed description of the various projects at experiment,
laboratory and international levels. In addition, the paper provides a concrete
proposal for an international organisation in charge of the data management and
policies in high-energy physics
Combined Forward-Backward Asymmetry Measurements in Top-Antitop Quark Production at the Tevatron
The CDF and D0 experiments at the Fermilab Tevatron have measured the asymmetry between yields of forward- and backward-produced top and antitop quarks based on their rapidity difference and the asymmetry between their decay leptons. These measurements use the full data sets collected in proton-antiproton collisions at a center-of-mass energy of TeV. We report the results of combinations of the inclusive asymmetries and their differential dependencies on relevant kinematic quantities. The combined inclusive asymmetry is . The combined inclusive and differential asymmetries are consistent with recent standard model predictions
JANA2 Framework for Event Based and Triggerless Data Processing
Development of the second generation JANA2 multi-threaded event processing framework is ongoing through an LDRD initiative grant at Jefferson Lab. The framework is designed to take full advantage of all cores on modern many-core compute nodes. JANA2 efficiently handles both traditional hardware triggered event data and streaming data in online triggerless environments. Development is being done in conjunction with the Electron Ion Collider development. Anticipated to be the next large scale Nuclear Physics facility constructed. The core framework is written in modern C++ but includes an integrated Python interface. The status of development and summary of the more interesting features are presented
JANA2 Framework for Event Based and Triggerless Data Processing
Development of the second generation JANA2 multi-threaded event processing framework is ongoing through an LDRD initiative grant at Jefferson Lab. The framework is designed to take full advantage of all cores on modern many-core compute nodes. JANA2 efficiently handles both traditional hardware triggered event data and streaming data in online triggerless environments. Development is being done in conjunction with the Electron Ion Collider development. Anticipated to be the next large scale Nuclear Physics facility constructed. The core framework is written in modern C++ but includes an integrated Python interface. The status of development and summary of the more interesting features are presented
A.I. for nuclear physics
This report is an outcome of the workshop AI for Nuclear Physics held at Thomas Jefferson National Accelerator Facility on March 4–6, 202
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