collaborators

7 papers

quant-ph2026

An efficient algorithm for approximate shadow Hamiltonian simulation

Abhijit Chakraborty, Bharath Sambasivam, Karunya Shirali +4

The paper introduces an algorithm that approximates real-time quantum dynamics by pruning the operator algebra of a shadow Hamiltonian, reducing the required qubit resources for si…

quant-ph2026

Q3SAT-GPT: A Generative Model for Discovering Quantum Circuits for the 3-SAT Problem

Pratim Ugale, Ilya Tyagin, Karunya Shirali +2

This work introduces Q3SAT-GPT, a generative model for discovering quantum circuits for the Max-E3-SAT problem. Our method learns from high-performing QAOA-style ansätze to direct…

quant-ph2026

TIMES-ADAPT: A Quantum algorithm for real-time evolution in low-energy subspaces using fixed-depth circuits

Bharath Sambasivam, Kyle Sherbert, Karunya Shirali +3

We propose a new variational quantum algorithm, which we refer to as TIMES-ADAPT, that prepares time-evolved states in a low-energy or symmetric subspace of a time-independent Hami…

quant-ph2025

TEPID-ADAPT: Adaptive variational method for simultaneous preparation of low-temperature Gibbs and low-lying eigenstates

Bharath Sambasivam, Kyle Sherbert, Karunya Shirali +4

Preparing Gibbs states, which describe systems in equilibrium at finite temperature, is of great importance, particularly at low temperatures. In this work, we propose a new method…

quant-ph2025

To break, or not to break: Symmetries in adaptive quantum simulations, a case study on the Schwinger model

Karunya Shailesh Shirali, Kyle Sherbert, Yanzhu Chen +4

We investigate the role of symmetries in constructing resource-efficient operator pools for adaptive variational quantum eigensolvers. In particular, we focus on the lattice Schwin…

quant-ph2025

Floquet-ADAPT-VQE: A Quantum Algorithm to Simulate Non-Equilibrium Physics in Periodically Driven Systems

Abhishek Kumar, Karunya Shirali, Nicholas J. Mayhall +2

Periodically driven quantum systems exhibit many fascinating phenomena absent in equilibrium systems, but their simulation is more challenging than that of static systems. Conseque…