1 citations · 1 across the 1 of their papers we have counts for
3 papers
On Speedups for Convex Optimization via Quantum Dynamics
Shouvanik Chakrabarti, Dylan Herman, Jacob Watkins +4
We explore the potential for quantum speedups in convex optimization using discrete simulations of the Quantum Hamiltonian Descent (QHD) framework, as proposed by Leng et al., and…
Fast Convex Optimization with Quantum Gradient Methods
Brandon Augustino, Dylan Herman, Enrico Fontana +4
We study quantum algorithms based on quantum (sub)gradient estimation using noisy function evaluation oracles, and demonstrate the first dimension-independent query complexities (u…
Strategies for running the QAOA at hundreds of qubits
Brandon Augustino, Madelyn Cain, Edward Farhi +5
We explore strategies aimed at reducing the amount of computation, both quantum and classical, required to run the Quantum Approximate Optimization Algorithm (QAOA). First, followi…