19 citations · 19 across the 6 of their papers we have counts for
4 papers · 1 filter
A quantum dual logarithmic barrier method for linear optimization
Zeguan Wu, Pouya Sampourmahani, Mohammadhossein Mohammadisiahroudi +1
Quantum computing has the potential to speed up some optimization methods. One can use quantum computers to solve linear systems via Quantum Linear System Algorithms (QLSAs). QLSAs…
A preconditioned inexact infeasible quantum interior point method for linear optimization
Zeguan Wu, Xiu Yang, Tamás Terlaky
Quantum Interior Point Methods (QIPMs) have been attracting significant interests recently due to their potential of solving optimization problems substantially faster than state-o…
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…
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…