76 citations · 240 across the 7 of their papers we have counts for
7 papers
Efficient ground-state energy estimation and certification on early fault-tolerant quantum computers
Guoming Wang, Daniel Stilck França, Gumaro Rendon +1
A major thrust in quantum algorithm development over the past decade has been the search for the quantum algorithms that will deliver practical quantum advantage first. Today's qua…
Quantum algorithm for ground state energy estimation using circuit depth with exponentially improved dependence on precision
Guoming Wang, Daniel Stilck França, Ruizhe Zhang +2
A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods. The current understanding…
State Preparation Boosters for Early Fault-Tolerant Quantum Computation
Guoming Wang, Sukin Sim, Peter D. Johnson
Quantum computing is believed to be particularly useful for the simulation of chemistry and materials, among the various applications. In recent years, there have been significant…
Computing Ground State Properties with Early Fault-Tolerant Quantum Computers
Ruizhe Zhang, Guoming Wang, Peter Johnson
Significant effort in applied quantum computing has been devoted to the problem of ground state energy estimation for molecules and materials. Yet, for many applications of practic…
Quantum algorithm for credit valuation adjustments
Javier Alcazar, Andrea Cadarso, Amara Katabarwa +4
Quantum mechanics is well known to accelerate statistical sampling processes over classical techniques. In quantitative finance, statistical samplings arise broadly in many use cas…
Minimizing estimation runtime on noisy quantum computers
Guoming Wang, Dax Enshan Koh, Peter D. Johnson +1
The number of measurements demanded by hybrid quantum-classical algorithms such as the variational quantum eigensolver (VQE) is prohibitively high for many problems of practical va…
Foundations for Bayesian inference with engineered likelihood functions for robust amplitude estimation
Dax Enshan Koh, Guoming Wang, Peter D. Johnson +1
We present mathematical and conceptual foundations for the task of robust amplitude estimation using engineered likelihood functions (ELFs), a framework introduced in Wang et al. […