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19962026
most citedExciton Binding Energy and Nonhydrogenic Rydberg Series in Monolayer WS2

2.6k citations · 17.9k across the 190 of their papers we have counts for

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physics.chem-ph2025

Excited states in auxiliary field quantum Monte Carlo

Ankit Mahajan, Sandeep Sharma, Shiwei Zhang +1

We systematically investigate the calculation of excited states in quantum chemistry using auxiliary field quantum Monte Carlo (AFQMC). Symmetry allows targeting of the lowest trip…

physics.chem-ph2025★ 3 cited

Mixed Quantum-Classical Methods for Polaron Spectral Functions

Haimi Nguyen, Arkajit Mandal, Ankit Mahajan +1

In this work, using two distinct semiclassical approaches, namely the mean-field Ehrenfest (MFE) method and the mapping approach to surface hopping (MASH), we investigate the spect…

physics.chem-ph2024★ 1 cited

Beyond CCSD(T) accuracy at lower scaling with auxiliary field quantum Monte Carlo

Ankit Mahajan, James H. Thorpe, Jo S. Kurian +3

We introduce a black-box auxiliary field quantum Monte Carlo (AFQMC) approach to perform highly accurate electronic structure calculations using configuration interaction singles a…

physics.chem-ph2024★ 11 cited

Correlation Functions From Tensor Network Influence Functionals: The Case of the Spin-Boson Model

Haimi Nguyen, Nathan Ng, Lachlan P. Lindoy +4

We investigate the application of matrix product state (MPS) representations of the influence functionals (IF) for the calculation of real-time equilibrium correlation functions in…

physics.chem-ph2024★ 10 cited

Scalable Ab Initio Electronic Structure Methods with Near Chemical Accuracy for Main Group Chemistry

Yujing Wei, Sibali Debnath, John L. Weber +3

This study evaluates the precision of widely recognized quantum chemical methodologies, CCSD(T), DLPNO-CCSD(T) and localized ph-AFQMC, for determining the thermochemistry of main g…

physics.chem-ph2023★ 1 cited

Hierarchical Framework for Predicting Entropies in Bottom-Up Coarse-Grained Models

Jaehyeok Jin, David R. Reichman

The thermodynamic entropy of coarse-grained (CG) models stands as one of the most important properties for quantifying the missing information during the CG process and for establi…