Effective Field Theory Models for Thermal QCD

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Nov 2017Embargo end date: 01 Apr 2017 English Publisher:Elsevier BVJournal:Nuclear Physics A, volume 967, pages 716-719 (issn: 0375-9474,

Copyright policy )Funded by:FCT | D4

Authors: Gupta, Sourendu; Sharma, Rishi;

doi: 10.1016/j.nuclphysa.2017.04.036 , 10.48550/arxiv.1704.04495

arXiv: 1704.04495

Effective Field Theory Models for Thermal QCD

- Summary
- Subjects
- Metrics

Abstract

We present an effective field theory model for QCD at finite temperature with quarks. We discuss the mean field theory, the fixing of parameters, and a prediction for the curvature of the critical line. We proceed to write down a pionic theory of fluctuations around the mean field, and discuss how the parameters of this pionic effective theory descend from the model with quarks.

Proceedings of Quark Matter 2017

Related Organizations

Tata Institute of Fundamental Research
India

Keywords

High Energy Physics - Theory, Nuclear Theory (nucl-th), High Energy Physics - Phenomenology, High Energy Physics - Lattice, High Energy Physics - Phenomenology (hep-ph), Nuclear Theory, High Energy Physics - Theory (hep-th), High Energy Physics - Lattice (hep-lat), FOS: Physical sciences

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average