scholarly journals Color screening potential at finite density in two-flavor lattice QCD with Wilson fermions

2013 ◽  
Vol 88 (11) ◽  
Author(s):  
Junichi Takahashi ◽  
Keitaro Nagata ◽  
Takuya Saito ◽  
Atsushi Nakamura ◽  
Takahiro Sasaki ◽  
...  
2004 ◽  
Vol 129-130 ◽  
pp. 539-541 ◽  
Author(s):  
Yuji Sasai ◽  
Atsushi Nakamura ◽  
Tetsuya Takaishi

2022 ◽  
Vol 258 ◽  
pp. 02003
Author(s):  
Giuseppe Burgio ◽  
Hannes Vogt

We show that, when investigating Wilson-fermions correlation functions on the lattice, one is bound to encounter major difficulties in defining their dispersion relation, even at tree level. The problem is indeed quite general and, although we stumbled upon it while studying Coulomb-gauge applications, it also affects gauge fixed studies in covariant gauges, including their most popular version, Landau gauge. In this paper we will discuss a solution to this problems based on a redefinition of the kinematic momentum of the fermion.


2015 ◽  
Author(s):  
Rajiv V. Gavai ◽  
Sayantan Sharma

2007 ◽  
Vol 22 (07n10) ◽  
pp. 473-489
Author(s):  
Atsushi NAKAMURA

This is a short overview of the lattice QCD simulations of finite density systems. We first describe a brief introduction of the lattice QCD at finite density, including the minimum necessary formulation, where we show why an annoying complex fermion determinant appears, and why in some cases it does not appear. Then we review several approaches of present and past days. We conclude possible directions of lattice QCD simulations at finite density in near future.


2002 ◽  
Vol 16 (14n15) ◽  
pp. 2017-2032 ◽  
Author(s):  
KEH-FEI LIU

I will review the finite density algorithm for lattice QCD based on finite chemical potential and summarize the associated difficulties. I will propose a canonical ensemble approach which projects out the finite baryon number sector from the fermion determinant. For this algorithm to work, it requires an efficient method for calculating the fermion determinant and a Monte Carlo algorithm which accommodates unbiased estimate of the probability. I shall report on the progress made along this direction with the Padé–Z2 estimator of the determinant and its implementation in the newly developed Noisy Monte Carlo algorithm.


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