47 citations · 137 across the 18 of their papers we have counts for
22 papers
An SU(2)-symmetric Semidefinite Programming Hierarchy for Quantum Max Cut
Jun Takahashi, Chaithanya Rayudu, Cunlu Zhou +3
Understanding and approximating extremal energy states of local Hamiltonians is a central problem in quantum physics and complexity theory. Recent work has focused on developing ap…
HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware
Nicolas PD Sawaya, Daniel Marti-Dafcik, Yang Ho +13
In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum co…
Synergies Between Operations Research and Quantum Information Science
Ojas Parekh
This article highlights synergies between quantum information science (QIS) and operations research for QIS-curious operations researchers (and vice-versa).
Improved Approximations for Extremal Eigenvalues of Sparse Hamiltonians
Daniel Hothem, Ojas Parekh, Kevin Thompson
We give a classical -approximation for the maximum eigenvalue of a -sparse fermionic Hamiltonian with strictly -local terms, as well as a -approximation w…
Stochastic Neuromorphic Circuits for Solving MAXCUT
Bradley H. Theilman, Yipu Wang, Ojas D. Parekh +3
Finding the maximum cut of a graph (MAXCUT) is a classic optimization problem that has motivated parallel algorithm development. While approximate algorithms to MAXCUT offer attrac…
An Optimal Product-State Approximation for 2-Local Quantum Hamiltonians with Positive Terms
Ojas Parekh, Kevin Thompson
We resolve the approximability of the maximum energy of the Quantum Max Cut (QMC) problem using product states. A classical 0.498-approximation, using a basic semidefinite programm…