571 citations · 9.2k across the 125 of their papers we have counts for
124 papers
Digital quantum state preparation by nucleation
Jean Paul Sadia, Morten Hjorth-Jensen, Dean Lee +1
Quantum state preparation is crucial for quantum algorithms, and improved state preparation methods can reduce resource requirements by orders of magnitude. In this work, we introd…
Neural-network quantum states for ultra-cold Fermi gases
Jane Kim, Gabriel Pescia, Bryce Fore +5
Ultra-cold Fermi gases display diverse quantum mechanical properties, including the transition from a fermionic superfluid BCS state to a bosonic superfluid BEC state, which can be…
Quantum Information Science and Technology for Nuclear Physics. Input into U.S. Long-Range Planning, 2023
Douglas Beck, Joseph Carlson, Zohreh Davoudi +98
In preparation for the 2023 NSAC Long Range Plan (LRP), members of the Nuclear Science community gathered to discuss the current state of, and plans for further leveraging opportun…
Dilute neutron star matter from neural-network quantum states
Bryce Fore, Jane M. Kim, Giuseppe Carleo +2
Low-density neutron matter is characterized by fascinating emergent quantum phenomena, such as the formation of Cooper pairs and the onset of superfluidity. We model this density r…
Solving the nuclear pairing model with neural network quantum states
Mauro Rigo, Benjamin Hall, Morten Hjorth-Jensen +2
We present a variational Monte Carlo method that solves the nuclear many-body problem in the occupation number formalism exploiting an artificial neural network representation of t…
Efficient Solutions of Fermionic Systems using Artificial Neural Networks
Even M. Nordhagen, Jane M. Kim, Bryce Fore +2
We discuss differences and similarities between variational Monte Carlo approaches that use conventional and artificial neural network parameterizations of the ground-state wave fu…