17 citations · 47 across the 13 of their papers we have counts for
5 papers · 1 filter
A Quantum Approximate Optimization Algorithm for Local Hamiltonian Problems
Ishaan Kannan, Robbie King, Leo Zhou
Local Hamiltonian Problems (LHPs) are important problems that are computationally QMA-complete and physically relevant for many-body quantum systems. Quantum MaxCut (QMC), which eq…
Provable quantum speedups for computing persistence in topological data analysis
Casper Gyurik, Alexander Schmidhuber, Robbie King +2
Topological data analysis (TDA) aims to extract noise-robust features from a data set by examining the number and persistence of holes in its topology. We provide an efficient quan…
Optimization by Decoded Quantum Interferometry
Stephen P. Jordan, Noah Shutty, Mary Wootters +6
Achieving superpolynomial speedups for optimization has long been a central goal for quantum algorithms. Here we introduce Decoded Quantum Interferometry (DQI), a quantum algorithm…
Shadow Hamiltonian Simulation
Rolando D. Somma, Robbie King, Robin Kothari +2
Simulating quantum dynamics is one of the most important applications of quantum computers. Traditional approaches for quantum simulation involve preparing the full evolved state o…
Triply efficient shadow tomography
Robbie King, David Gosset, Robin Kothari +1
Given copies of a quantum state , a shadow tomography protocol aims to learn all expectation values from a fixed set of observables, to within a given precision . We say that…