Fetching the paper…
Reading the bibliography…
Quantum computing has attracted significant interest in the optimization community because it potentially can solve classes of optimization problems faster than conventional supercomputers.
“Quantum algorithms for zero-sum games”
Joran van Apeldoorn and András Gilyén · 1904
Earlier work this paper cites.
“Quantum algorithm for systems of linear equations with exponentially improved dependence on precision”
Andrew. Childs, Robin Kothari and Rolando. Somma · 1950
Earlier work this paper cites.
“Adjustment of an inverse matrix corresponding to a change in one element of a given matrix”
Jack Sherman and Winifred Morrison · 1950
Earlier work this paper cites.
“Linear Programming and Extensions”
George. Dantzig · 1963
Earlier work this paper cites.
“A polynomial algorithm in linear programming”
Leonid Khachiyan · 1979
Earlier work this paper cites.
“A new polynomial-time algorithm for linear programming”
Narendra Karmarkar · 1984
Earlier work this paper cites.
“Quantum theory, the Church-Turing principle and the universal quantum computer”
David Deutsch · 1985
Earlier work this paper cites.
“Rapid solution of problems by quantum computation”
David Deutsch and Richard Jozsa · 1992
Earlier work this paper cites.
“A primal—dual infeasible-interior-point algorithm for linear programming”
Masakazu Kojima, Nimrod Megiddo and Shinji Mizuno · 1993
Earlier work this paper cites.
“An O ( n L ) O(\sqrt{n}L) -iteration homogeneous and self-dual linear programming algorithm”
Yinyu Ye, Michael. Todd and Shinji Mizuno · 1994
Earlier work this paper cites.
“Interior Point Methods of Mathematical Programming”
Tamás Terlaky · 1996
Earlier work this paper cites.
“On the power of quantum computation”
Daniel. Simon · 1997
Earlier work this paper cites.
“Primal-Dual Interior-Point Methods”
Stephen. Wright · 1997
Earlier work this paper cites.
“Inexact interior-point method”
Stefania Bellavia · 1998
Earlier work this paper cites.
“Convergence of a class of inexact interior-point algorithms for linear programs”
Roland. Freund, Florian Jarre and Shinji Mizuno · 1999
Earlier work this paper cites.
“Global and polynomial-time convergence of an infeasible-interior-point algorithm using inexact computation”
Shinji Mizuno and Florian Jarre · 1999
Earlier work this paper cites.
“Convergence analysis of inexact infeasible-interior-point algorithms for solving linear programming problems”
János Korzak · 2000
Cited alongside, same era.
“Convergence analysis of a long-step primal-dual infeasible interior-point LP algorithm based on iterative linear solvers”
Renato Monteiro and Jerome. O’Neal · 2003
Cited alongside, same era.
“Iterative Methods for Sparse Linear Systems”
Yousef Saad · 2003
Cited alongside, same era.
“The use of low-rank updates in interior-point methods”
Erling. Andersen, Cornelis Roos, Tamás Terlaky, Theodore Trafalis and Joost. Warners · 2004
Cited alongside, same era.
“Convergence analysis of an inexact infeasible interior point method for semidefinite programming”
Stefania Bellavia and Sandra Pieraccini · 2004
Cited alongside, same era.
“Polynomiality of an inexact infeasible interior point algorithm for semidefinite programming”
“Quantum speed-ups for solving semidefinite programs”
Fernando Brandao and Krysta Svore · 2017
Later among the works it cites.
“Quantum SDP solvers: Large speed-ups, optimality, and applications to quantum learning”
Fernando.S.L. Brandão, Amir Kalev, Tongyang Li, Cedric-Yu Lin, Krysta Svore and Xiaodi Wu · 2017
Later among the works it cites.
“Improvements in quantum SDP-solving with applications”
Joran van Apeldoorn and András Gilyén · 2018
Later among the works it cites.
“The power of block-encoded matrix powers: Improved regression techniques via faster Hamiltonian simulation”
Shantanav Chakraborty, András Gilyén and Stacey Jeffery · 2018
Later among the works it cites.
“Quantum linear systems algorithms: a primer”
Danial Dervovic, Mark Herbster, Peter Mountney, Simone Severini, Naïri Usher and Leonard Wossnig · 2018
Later among the works it cites.
“Quantum linear system algorithm for dense matrices”
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Guanglu Zhou and Kim-Chuan Toh · 2004
Cited alongside, same era.
“Interior Point Methods for Linear Optimization”
Cornelis Roos, Tamás Terlaky and Jean-Philippe Vial · 2005
Cited alongside, same era.
“On the convergence of an inexact primal-dual interior point method for linear programming”
Venansius Baryamureeba and Trond Steihaug · 2006
Cited alongside, same era.
“Quantum algorithm for linear systems of equations”
Aram. Harrow, Avinatan Hassidim and Seth Lloyd · 2009
Cited alongside, same era.
“Convergence analysis of the inexact infeasible interior-point method for linear optimization”
Ghussoun Al-Jeiroudi and Jacek Gondzio · 2009
Cited alongside, same era.
“Interior Point Algorithms: Theory and Analysis”
Yinyu Ye · 2011
Cited alongside, same era.
“Variable time amplitude amplification and quantum algorithms for linear algebra problems”
Andris Ambainis · 2012
Cited alongside, same era.
Leonard Wossnig, Zhikuan Zhao and Anupam Prakash · 2018
Later among the works it cites.
“Hamiltonian simulation by qubitization”
Guang Low and Isaac Chuang · 2019
Later among the works it cites.
“A quantum interior-point predictor–corrector algorithm for linear programming”
Pablo Casares and Miguel Martin-Delgado · 2020
Later among the works it cites.
“Linear programming using limited-precision oracles”
Ambros Gleixner and Daniel. Steffy · 2020
Later among the works it cites.
“A quantum interior point method for LPs and SDPs”
Iordanis Kerenidis and Anupam Prakash · 2020
Later among the works it cites.
“Quantum interior point methods for semidefinite optimization”
Brandon Augustino, Giacomo Nannicini, Tamás Terlaky and Luis Zuluaga · 2021
Later among the works it cites.
“Quantum algorithms for second-order cone programming and support vector machines”
Iordanis Kerenidis, Anupam Prakash and Dániel Szilágyi · 2021
Later among the works it cites.
“Quantum tomography using state-preparation unitaries”
Joran van Apeldoorn, Arjan Cornelissen, András Gilyén and Giacomo Nannicini · 2022
Closest in time.
“Enhancing the quantum linear systems algorithm using Richardson extrapolation”
Almudena Vazquez, Ralf Hiptmair and Stefan Woerner · 2022
Closest in time.
Mohammadhossein Mohammadisiahroudi, Ramin Fakhimi, Brandon Augustino and Tamás Terlaky · 2023
Closest in time.