181 citations · 237 across the 18 of their papers we have counts for
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Quantum Computing Inspired Iterative Refinement for Semidefinite Optimization
Mohammadhossein Mohammadisiahroudi, Brandon Augustino, Pouya Sampourmahani +1
Iterative Refinement (IR) is a classical computing technique for obtaining highly precise solutions to linear systems of equations, as well as linear optimization problems. In this…
Challenges and Opportunities in Quantum Optimization
Amira Abbas, Andris Ambainis, Brandon Augustino +43
Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum a…
A quantum central path algorithm for linear optimization
Brandon Augustino, Jiaqi Leng, Giacomo Nannicini +2
We propose a novel quantum algorithm for solving linear optimization problems by quantum-mechanical simulation of the central path. While interior point methods follow the central…
Improvements to Quantum Interior Point Method for Linear Optimization
Mohammadhossein Mohammadisiahroudi, Zeguan Wu, Brandon Augustino +2
Quantum linear system algorithms (QLSA) have the potential to speed up Interior Point Methods (IPM). However, a major challenge is that QLSAs are inexact and sensitive to the condi…
Generating Linear, Semidefinite, and Second-order Cone Optimization Problems for Numerical Experiments
Mohammadhossein Mohammadisiahroudi, Ramin Fakhimi, Brandon Augustino +1
The numerical performance of algorithms can be studied using test sets or procedures that generate such problems. This paper proposes various methods for generating linear, semidef…
An Inexact Feasible Quantum Interior Point Method for Linearly Constrained Quadratic Optimization
Zeguan Wu, Mohammadhossein Mohammadisiahroudi, Brandon Augustino +2
Quantum linear system algorithms (QLSAs) have the potential to speed up algorithms that rely on solving linear systems. Interior Point Methods (IPMs) yield a fundamental family of…
Solving the semidefinite relaxation of QUBOs in matrix multiplication time, and faster with a quantum computer
Brandon Augustino, Giacomo Nannicini, Tamás Terlaky +1
Recent works on quantum algorithms for solving semidefinite optimization (SDO) problems have leveraged a quantum-mechanical interpretation of positive semidefinite matrices to deve…