150 citations · 362 across the 16 of their papers we have counts for
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Learning the Kohn-Sham map with neural operators for quasi-linear scaling density functional theory
Danish Khan, Maurice D. Hanisch, Nikolai Argatoff +3
Kohn--Sham density functional theory (DFT) underpins electronic-structure simulations, but repeated orbital diagonalizations lead to cubic scaling, restricting quantum calculations…
Size Extensive Auxiliary-Field Quantum Monte Carlo with Perturbative Coupled Cluster Trial Wavefunction
Yichi Zhang, Ankit Mahajan, Yann Damour +1
In this work, we develop a size extensive Auxiliary-Field Quantum Monte Carlo (AFQMC) approach that scales as for local energy evaluation by treating the Coupled Cluster S…
Can phaseless auxiliary-field quantum Monte Carlo with broken symmetry trials describe iron-sulfur clusters?
Eirik F. Kjønstad, Huanchen Zhai, James Shee +2
Phaseless auxiliary-field quantum Monte Carlo (AFQMC) has in several cases been found to perform well on strongly correlated systems. Here, we benchmark the method for three iron-s…
Convergence Analysis of the Stochastic Resolution of Identity: Comparing Hutchinson to Hutch++ for the Second-Order Green's Function
Leopoldo Mejía, Sandeep Sharma, Roi Baer +2
Stochastic orbital techniques offer reduced computational scaling and memory requirements to describe ground and excited states at the cost of introducing controlled statistical er…
Toward linear scaling auxiliary field quantum Monte Carlo with local natural orbitals
Jo S. Kurian, Hong-Zhou Ye, Ankit Mahajan +2
We develop a local correlation variant of auxiliary field quantum Monte Carlo (AFQMC) that is based on local natural orbitals (LNO-AFQMC). In LNO-AFQMC, independent AFQMC calculati…
Response properties in phaseless auxiliary field quantum Monte Carlo
Ankit Mahajan, Jo S. Kurian, Joonho Lee +2
We present a method for calculating first-order response properties in phaseless auxiliary field quantum Monte Carlo (AFQMC) through the application of automatic differentiation (A…