abstract

QCDVis: a tool for the visualisation of quantum chromodynamics (QCD) data

Authors:

Dean P. Thomas,

Robert S. Laramee,

Simon HandsAuthors Info & Claims

SCCG '17: Proceedings of the 33rd Spring Conference on Computer Graphics

Article No.: 1, Pages 1 - 14

https://doi.org/10.1145/3154353.3154355

Published: 15 May 2017 Publication History

Abstract

Quantum chromodynamics, most commonly referred to as QCD, is a relativistic quantum field theory for the strong interaction between subatomic particles called quarks and gluons. The most systematic way of calculating the strong interactions of QCD is a computational approach known as lattice gauge theory or lattice QCD. Space-time is discretised so that field variables are formulated on the sites and links of a four dimensional hypercubic lattice. This technique enables the gluon field to be represented using 3 x 3 complex matrices in four space-time dimensions. Importance sampling techniques can then be exploited to calculate physics observables as functions of the fields, averaged over a statistically-generated and suitably weighted ensemble of field configurations. In this paper we present a framework developed to visually assist scientists in the analysis of multidimensional properties and emerging phenomena within QCD ensemble simulations. Core to the framework is the use of topology-driven visualisation techniques which enable the user to segment the data into unique objects, calculate properties of individual objects present on the lattice, and validate features detected using statistical measures. The framework enables holistic analysis to validate existing hypothesis against novel visual cues with the intent of supporting and steering scientists in the analysis and decision making process. Use of the framework has lead to new studies into the effect that variation of thermodynamic control parameters has on the topological structure of lattice fields.

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Cited By

Islam MRazzak IWang XTilocca PXu G(2022)Natural language interactions enhanced by data visualization to explore insurance claims and manage riskAnnals of Operations Research10.1007/s10479-021-04465-7339:3(1569-1587)Online publication date: 14-Jan-2022
https://doi.org/10.1007/s10479-021-04465-7

Index Terms

QCDVis: a tool for the visualisation of quantum chromodynamics (QCD) data
1. Computing methodologies
  1. Computer graphics
    1. Shape modeling
      1. Mesh models
2. Human-centered computing
  1. Visualization

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Information & Contributors

Information

Published In

cover image ACM Conferences

SCCG '17: Proceedings of the 33rd Spring Conference on Computer Graphics

May 2017

163 pages

ISBN:9781450351072

DOI:10.1145/3154353

Conference Chair:
Pavel Zemcik
Brno University of Technology
,
Editor:
Stephen N. Spencer
University of Washington
,
Program Chairs:
Jiri Bittner
Czech Technical University in Prague
,
Ivan Viola
Vienna University of Technology, Austria

Copyright © 2017 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 May 2017

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Abstract

Funding Sources

Large Facilities Capital Fund of BIS and Swansea University
DEISA Consortium funded through the EU
EPSRC
STFC

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SCCG '17

Sponsor:

SIGGRAPH

SCCG '17: Spring Conference on Computer Graphics 2017

May 15 - 17, 2017

Mikulov, Czech Republic

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Overall Acceptance Rate 67 of 115 submissions, 58%

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Cited By

Islam MRazzak IWang XTilocca PXu G(2022)Natural language interactions enhanced by data visualization to explore insurance claims and manage riskAnnals of Operations Research10.1007/s10479-021-04465-7339:3(1569-1587)Online publication date: 14-Jan-2022
https://doi.org/10.1007/s10479-021-04465-7

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