A Continuous Time Quantum Monte Carlo as an Impurity Solver for Strongly Correlated System

Authors

  • R.K. Rai Patan Multiple Campus, Tribhuvan University, Patandhoka, Lalipur, Nepal
  • R.B. Ray Amrit Campus, Tribhuvan University, Lainchaur, Kathmandu, Nepal
  • G.C. Kaphle Central Department of Physics, Tribhuvan University, Kirtipur, Kathmandu, Nepal
  • O.P. Niraula Central Department of Physics, Tribhuvan University, Kirtipur, Kathmandu, Nepal

DOI:

https://doi.org/10.3126/jnphyssoc.v7i3.42185

Keywords:

CT-QMC, DFT, DMFT, MIT, Neuromorphic Computing

Abstract

We assess the continuous-time quantum Monte Carlo (CT-QMC) technique with hybridization expansion for solving
the electronic structure of the strongly correlated system LaxSr1−xVO3 . The impurity solver method implemented here shows the fair agreement with the other available Monte Carlo techniques. From the study, it is found that the CT-QMC technique clearly distinguishes metallic phase, quasiparticle phase and insulating phases of the system depending upon the strength of the correlation. In case of La0.33Sr0.67VO3 system the metal-insulator transition is found to be at U = 4.5 eV for β = 6(eV)−1.  The value of U depends with the value of β, and also the value of Hund’s coupling (J) and bandwidth (W). This technique allows the particle to exchange with the reservoir of the particles and the impurity sites, which is accounted numerically to treat the temporal fluctuation of the fermionic systems termed as dynamical mean field theory (DMFT). This theory is used to explain the phenomena of MottHubbard metal insulator transition of the materials which are applicable for designing the Mottronics, Neuromorphic computing, Quantum computing and resistive memory devices.

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Published

2021-12-31

How to Cite

Rai, R., Ray, R., Kaphle, G., & Niraula, O. (2021). A Continuous Time Quantum Monte Carlo as an Impurity Solver for Strongly Correlated System. Journal of Nepal Physical Society, 7(3), 14–26. https://doi.org/10.3126/jnphyssoc.v7i3.42185

Issue

Vol. 7 No. 3 (2021): Special Issue: ANPA Conference 2021

Section

Articles

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