Stochastic method for analytic continuation of quantum Monte Carlo data

1998 ◽  
Vol 57 (17) ◽  
pp. 10287-10290 ◽  
Author(s):  
Anders W. Sandvik
Keyword(s):  
Monte Carlo ◽  
Analytic Continuation ◽  
Quantum Monte Carlo ◽  
Stochastic Method ◽  
Monte Carlo Data

scholarly journals Identification of non-Fermi liquid fermionic self-energy from quantum Monte Carlo data

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Xiao Yan Xu ◽  
Avraham Klein ◽  
Kai Sun ◽  
Andrey V. Chubukov ◽  
Zi Yang Meng
Keyword(s):  
Monte Carlo ◽  
Finite Temperature ◽  
Quantum Monte Carlo ◽  
Fermi Liquid ◽  
Quantum Critical Point ◽  
Critical Metals ◽  
Monte Carlo Data ◽  
Low Frequencies ◽  
Self Energy ◽  
Quantum Critical

Abstract Quantum Monte Carlo (QMC) simulations of correlated electron systems provide unbiased information about system behavior at a quantum critical point (QCP) and can verify or disprove the existing theories of non-Fermi liquid (NFL) behavior at a QCP. However, simulations are carried out at a finite temperature, where quantum critical features are masked by finite-temperature effects. Here, we present a theoretical framework within which it is possible to separate thermal and quantum effects and extract the information about NFL physics at T = 0. We demonstrate our method for a specific example of 2D fermions near an Ising ferromagnetic QCP. We show that one can extract from QMC data the zero-temperature form of fermionic self-energy Σ(ω) even though the leading contribution to the self-energy comes from thermal effects. We find that the frequency dependence of Σ(ω) agrees well with the analytic form obtained within the Eliashberg theory of dynamical quantum criticality, and obeys ω2/3 scaling at low frequencies. Our results open up an avenue for QMC studies of quantum critical metals.

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