43 citations · 179 across the 19 of their papers we have counts for
6 papers · 1 filter
QAOAKit: A Toolkit for Reproducible Study, Application, and Verification of the QAOA
Ruslan Shaydulin, Kunal Marwaha, Jonathan Wurtz +1
Understanding the best known parameters, performance, and systematic behavior of the Quantum Approximate Optimization Algorithm (QAOA) remain open research questions, even as the a…
The Quantum Approximate Optimization Algorithm at High Depth for MaxCut on Large-Girth Regular Graphs and the Sherrington-Kirkpatrick Model
Joao Basso, Edward Farhi, Kunal Marwaha +2
The Quantum Approximate Optimization Algorithm (QAOA) finds approximate solutions to combinatorial optimization problems. Its performance monotonically improves with its depth .…
Bounds on approximating Max XOR with quantum and classical local algorithms
Kunal Marwaha, Stuart Hadfield
We consider the power of local algorithms for approximately solving Max XOR, a generalization of two constraint satisfaction problems previously studied with classical and quant…
An explicit vector algorithm for high-girth MaxCut
Jessica K. Thompson, Ojas Parekh, Kunal Marwaha
We give an approximation algorithm for MaxCut and provide guarantees on the average fraction of edges cut on -regular graphs of girth . For every and $k \geq…
Classical algorithms and quantum limitations for maximum cut on high-girth graphs
Boaz Barak, Kunal Marwaha
We study the performance of local quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) for the maximum cut problem, and their relationship to that of cl…
Local classical MAX-CUT algorithm outperforms QAOA on high-girth regular graphs
Kunal Marwaha
The -stage Quantum Approximate Optimization Algorithm (QAOA) is a promising approach for combinatorial optimization on noisy intermediate-scale quantum (NISQ) devices, but i…