Multiscale Monte Carlo equilibration: Two-color QCD with two fermion flavors
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Center for Theoretical Physics
In this study, we demonstrate the applicability of a recently proposed multiscale thermalization algorithm to two-color quantum chromodynamics (QCD) with two mass-degenerate fermion flavors. The algorithm involves refining an ensemble of gauge configurations that had been generated using a renormalization group (RG) matched coarse action, thereby producing a fine ensemble that is close to the thermalized distribution of a target fine action; the refined ensemble is subsequently rethermalized using conventional algorithms. Although the generalization of this algorithm from pure Yang-Mills theory to QCD with dynamical fermions is straightforward, we find that in the latter case, the method is susceptible to numerical instabilities during the initial stages of rethermalization when using the hybrid Monte Carlo algorithm. We find that these instabilities arise from large fermion forces in the evolution, which are attributed to an accumulation of spurious near-zero modes of the Dirac operator. We propose a simple strategy for curing this problem, and demonstrate that rapid thermalization--as probed by a variety of gluonic and fermionic operators--is possible with the use of this solution. Also, we study the sensitivity of rethermalization rates to the RG matching of the coarse and fine actions, and identify effective matching conditions based on a variety of measured scales.
- Research Organization:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- Grant/Contract Number:
- SC0010495; SC0011090
- OSTI ID:
- 1424917
- Alternate ID(s):
- OSTI ID: 1334216
- Journal Information:
- Physical Review D, Vol. 94, Issue 11; ISSN 2470-0010
- Publisher:
- American Physical Society (APS)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Flow-based generative models for Markov chain Monte Carlo in lattice field theory
|
journal | August 2019 |
| Flow-based generative models for Markov chain Monte Carlo in lattice field theory | text | January 2019 |
Similar Records
Nonperturbative QCD simulations with 2+1 flavors of improved staggered quarks
Machine learning action parameters in lattice quantum chromodynamics