204 citations · 2.4k across the 80 of their papers we have counts for
82 papers
Classifying metal-poor stars with machine learning using nucleosynthesis calculations
Nicole Vassh, Yilin Wang, Richard M. Woloshyn +4
We apply the capabilities of machine learning (ML) to discern patterns in order to classify metal-poor stars. To do so, we train an ML model on a bank of nucleosynthesis calculatio…
Bose-Hubbard model with a single qubit
R. M. Woloshyn
The use of a single-qubit parametrized circuit as an Ansatz for the variational wave function in the calculation of the ground state energy of a quantum many-body system is demonst…
Demonstrating quantum computing with the quark model
R. M. Woloshyn
The use of quantum computing to solve a problem in quantum mechanics is illustrated, step by step, by calculating energies and transition amplitudes in a nonrelativistic quark mode…
Quantum computing fidelity susceptibility using automatic differentiation
Olivia Di Matteo, R. M. Woloshyn
Automatic differentiation is an invaluable feature of machine learning and quantum machine learning software libraries. In this work it is shown how quantum automatic differentiati…
Exploring phases of the Su-Schrieffer-Heeger model with tSNE
R. M. Woloshyn
T-distributed stochastic neighborhood embedding (tSNE) is used as a tool to reveal the phase diagram of the Su-Schrieffer-Heeger model and some of its extended and non-Hermitian va…
Improving Hamiltonian encodings with the Gray code
Olivia Di Matteo, Anna McCoy, Peter Gysbers +3
Due to the limitations of present-day quantum hardware, it is especially critical to design algorithms that make the best possible use of available resources. When simulating quant…