60 citations · 116 across the 21 of their papers we have counts for
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QuantumMatterExplorer: An Autonomous Agent for the Discovery of Quantum Many-Body Phases of Matter
Jannes Nys, Andrew Jreissaty, Juan Carrasquilla
Mapping the phase diagram of a new quantum Hamiltonian demands expert judgement at every step: which observables to measure, where in parameter space to compute, or how to separate…
Projected Inverse Iteration: An Eigenvalue Approach to Ground-State Computation with Neural Quantum States
Hang Zhang, Victor Armegioiu, Juan Carrasquilla +4
Deep learning offers a powerful approach to quantum many-body problems via neural network wavefunctions, but their optimization remains a severe bottleneck. Existing optimization m…
Neural network quantum states in the grand canonical ensemble
Anton Hul, Matija Medvidović, Juan Carrasquilla
Variational Monte Carlo calculations have recently reached state-of-the-art accuracy in the approximation of ground state properties of quantum many-body systems. Making use of fle…
Distributions of Noisy Expectation Values over Sets of Measurement Operators
Matthew Duschenes, Roger G. Melko, Juan Carrasquilla +1
Expectation values of measurement operators, interpreted as measurement probabilities, arise frequently throughout quantum algorithms. When quantum states are randomly distributed,…
Fermionic neural Gibbs states
Jannes Nys, Juan Carrasquilla
We introduce fermionic neural Gibbs states (fNGS), a variational framework for modeling finite-temperature properties of strongly interacting fermions. fNGS starts from a reference…
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…
Entanglement and optimization within autoregressive neural quantum states
Andrew Jreissaty, Hang Zhang, Jairo C. Quijano +2
Neural quantum states (NQSs) are powerful variational ansätze capable of representing highly entangled quantum many-body wavefunctions. While the average entanglement properties of…
Discovery of energy landscapes towards optimized quantum transport: Environmental effects and long-range tunneling
Maggie Lawrence, Matthew Pocrnic, Erin Fung +3
Carrier transport in quantum networks is governed by a variety of factors, including network dimensionality and connectivity, on-site energies, couplings between sites and whether…
Biorthogonal Neural Network Approach to Two-Dimensional Non-Hermitian Systems
Massimo Solinas, Brandon Barton, Yuxuan Zhang +2
Non-Hermitian quantum many-body systems exhibit a rich array of physical phenomena, including non-Hermitian skin effects and exceptional points, that remain largely inaccessible to…
Circuit compression for 2D quantum dynamics
Matteo D'Anna, Yuxuan Zhang, Roeland Wiersema +2
The study of out-of-equilibrium quantum many-body dynamics remains one of the most exciting research frontiers of physics, standing at the crossroads of our understanding of comple…
Comment on: "Dynamics of disordered quantum systems with two- and three-dimensional tensor networks" arXiv:2503.05693
Andrew D. King, Alberto Nocera, Marek M. Rams +8
In a recent preprint [1] (arXiv:2503.05693), Tindall et al. presented impressive classical simulations of quantum dynamics using tensor networks. Their methods represent a signific…
A Framework for Demonstrating Practical Quantum Advantage: Racing Quantum against Classical Generative Models
Mohamed Hibat-Allah, Marta Mauri, Juan Carrasquilla +1
Generative modeling has seen a rising interest in both classical and quantum machine learning, and it represents a promising candidate to obtain a practical quantum advantage in th…