collaborators

5 papers

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

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Ilya Tyagin, Marwa H. Farag, Kyle Sherbert +3

Quantum computing has the potential to improve our ability to solve certain optimization problems that are computationally difficult for classical computers, by offering new algori…

quant-ph2025

Parameterization and optimizability of pulse-level VQEs

Kyle M Sherbert, Hisham Amer, Sophia E Economou +2

In conventional variational quantum eigensolvers (VQEs), trial states are prepared by applying series of parameterized gates to a reference state, with the gate parameters being va…