1 citations · 2 across the 11 of their papers we have counts for
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Quantum-Inspired Hamiltonian Descent for Radiation Therapy Treatment Planning
Mohammadhossein Mohammadisiahroydi, Yuxiang Peng, Jiaqi Leng +5
Direct incorporation of dose-volume constraints into inverse radiotherapy planning leads to large mixed-integer optimization problems that accurately represent clinical requirement…
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…
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…
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…