1 citations · 2 across the 6 of their papers we have counts for
6 papers
Adiabatic dressing of quantum enhanced Markov chains
Wen Ting Hsieh, Alev Orfi, Dries Sels
Quantum-enhanced Markov chain Monte Carlo, a hybrid quantum-classical algorithm in which configurations are proposed by a quantum proposer and accepted or rejected by a classical a…
Adiabatic transport of neural network quantum states
Matija Medvidović, Alev Orfi, Juan Carrasquilla +1
Variational methods have offered controllable and powerful tools for capturing many-body quantum physics for decades. The recent introduction of expressive neural network quantum s…
Double descent: When do neural quantum states generalize?
M. Schuyler Moss, Alev Orfi, Christopher Roth +5
Neural quantum states (NQS) provide flexible and compact wavefunction parameterizations for numerical studies of quantum many-body physics. In particular, NQS aim to circumvent the…
Quantum enhanced Markov chains require fine-tuned quenches
Alev Orfi, Dries Sels
Quantum-enhanced Markov chain Monte Carlo, an algorithm in which configurations are proposed through a measured quantum quench and accepted or rejected by a classical algorithm, ha…
Bounding speedup of quantum-enhanced Markov chain Monte Carlo
Alev Orfi, Dries Sels
Sampling tasks are a natural class of problems for quantum computers due to the probabilistic nature of the Born rule. Sampling from useful distributions on noisy quantum hardware…
Finding the Dynamics of an Integrable Quantum Many-Body System via Machine Learning
Victor Wei, Alev Orfi, Felix Fehse +1
We study the dynamics of the Gaudin magnet ("central-spin model") using machine-learning methods. This model is of practical importance, e.g., for studying non-Markovian decoherenc…