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20202026
most citedChallenges and Opportunities in Quantum Optimization

181 citations · 237 across the 18 of their papers we have counts for

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Showing 2026 · quant-phShow all

6 papers · 2 filters

quant-ph2026

Quantum Simulation on Riemannian Manifolds

Dylan Herman, Jacob Watkins, Guneykan Ozgul +4

We investigate algorithms for the quantum simulation of the Schrödinger equation on a Riemannian manifold, where the kinetic operator is defined by the Laplace--Beltrami operator c…

quant-ph2026

An analysis of iterative refinement for quantum linear system solvers

Adrian Harkness, Mohammadhossein Mohammadisiahroudi, Brandon Augustino +2

We present and analyze an iterative refinement (IR) framework for improving the precision dependence of algorithms that combine a quantum linear system algorithm (QLSA) with quantu…

quant-ph2026

Near-Optimal Quantum Lower Bounds for Convex Optimization via Fourier Rank

Brandon Augustino, Shouvanik Chakrabarti, Enrico Fontana +4

We establish a linear quantum query lower bound for high-accuracy convex optimization over an explicit family of -dimensional ellipsoids. We focus on linear optimization with an…

quant-ph2026

Faster Algorithms for Multimarginal Optimal Transport

Brandon Augustino, Yue Sun, Atithi Acharya +4

We study constructive discrete multimarginal optimal transport (MOT) among distributions on points, where the cost tensor has entries. For additive accuracy $\v…

quant-ph2026

Regularized Warm-Started Quantum Approximate Optimization and Conditions for Surpassing Classical Solvers on the Max-Cut Problem

Zichang He, Anuj Apte, Brandon Augustino +4

Demonstrating quantum heuristics that outperform strong classical solvers on large-scale optimization remains an open challenge. Here we introduce Regularized Warm-Started QAOA (RW…

quant-ph2026

Quantum Speedups for Group Relaxations of Integer Linear Programs

Brandon Augustino, Dylan Herman, Guneykan Ozgul +5

Integer Linear Programs (ILPs) are a flexible and ubiquitous model for discrete optimization problems. Solving ILPs is \textsf{NP-Hard} yet of great practical importance. Super-qua…