33 citations · 142 across the 13 of their papers we have counts for
13 papers
An approach for calculating astrophysical opacities on quantum computers
Shivesh Pathak, Alina Kononov, Andrew D. Baczewski
We propose a quantum algorithmic protocol for calculating astrophysical opacities. Our implementation uses first- and second-quantized representations of interacting electronic and…
Quantum simulation of lattice gauge theories coupled to fermionic matter via anyonic regularization
Mason L. Rhodes, Shivesh Pathak, Riley W. Chien
The optimal regularization of infinite-dimensional gauge-field degrees of freedom is a central open problem in the simulation of lattice gauge theories on quantum computers. Here,…
Exponential improvements in the simulation of lattice gauge theories using near-optimal techniques
Mason L. Rhodes, Michael Kreshchuk, Shivesh Pathak
We report a first-of-its-kind analysis on post-Trotter simulation of U(1), SU(2) and SU(3) lattice gauge theories including fermions in arbitrary spatial dimension. We provide expl…
Non-Orientable AdS and its Holography
Shivesh Pathak, Lucas Kocia Kovalsky
Known solutions to three-dimensional gravity with negative cosmological constant so far consist of either AdS or its orbifolds (or orientifolds). We geometrically derive a nove…
Requirements for building effective Hamiltonians using quantum-enhanced density matrix downfolding
Shivesh Pathak, Antonio E. Russo, Stefan Seritan +4
Density matrix downfolding (DMD) is a technique for regressing low-energy effective Hamiltonians from quantum many-body Hamiltonians. One limiting factor in the accuracy of classic…
Registry-dependent potential energy and lattice corrugation of twisted bilayer graphene from quantum Monte Carlo
Kittithat Krongchon, Tawfiqur Rakib, Shivesh Pathak +3
An uncertainty in studying twisted bilayer graphene (TBG) is the minimum energy geometry, which strongly affects the electronic structure. The minimum energy geometry is determined…
PyQMC: an all-Python real-space quantum Monte Carlo module in PySCF
William A. Wheeler, Shivesh Pathak, Kevin Kleiner +11
We describe a new open-source Python-based package for high accuracy correlated electron calculations using quantum Monte Carlo (QMC) in real space: PyQMC. PyQMC implements modern…
Quantifying -gate-count improvements for ground-state-energy estimation with near-optimal state preparation
Shivesh Pathak, Antonio Russo, Stefan Seritan +1
We study the question of when investing additional quantum resources in preparing a ground state will improve the aggregate runtime associated with estimating its energy. We analyz…
Accurate Hellmann-Feynman forces from density functional calculations with augmented Gaussian basis sets
Shivesh Pathak, Ignacio Ema López, Alex J. Lee +4
The Hellmann-Feynman (HF) theorem provides a way to compute forces directly from the electron density, enabling efficient force calculations for large systems through machine learn…
An accurate tight binding model for twisted bilayer graphene describes topological flat bands without geometric relaxation
Shivesh Pathak, Tawfiqur Rakib, Run Hou +4
A major hurdle in understanding the phase diagram of twisted bilayer graphene (TBLG) are the roles of lattice relaxation and electronic structure on isolated band flattening near m…
Excited states in variational Monte Carlo using a penalty method
Shivesh Pathak, Brian Busemeyer, João N. B. Rodrigues +1
The authors present a technique using variational Monte Carlo to solve for excited states of electronic systems. The technique is based on enforcing orthogonality to lower energy s…
A light weight regularization for wave function parameter gradients in quantum Monte Carlo
Shivesh Pathak, Lucas K. Wagner
The parameter derivative of the expectation value of the energy, , is a key ingredient in variational quantum Monte Carlo (VMC) wave function optimization me…
Non-orthogonal determinants in multi-Slater-Jastrow trial wave functions for fixed-node diffusion Monte Carlo
Shivesh Pathak, Lucas K. Wagner
The accuracy and efficiency of ab-initio quantum Monte Carlo (QMC) algorithms benefits greatly from compact variational trial wave functions that accurately reproduce ground state…