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quant-ph2026
Probabilistic Computers for Neural Quantum States
Shuvro Chowdhury, Jasper Pieterse, Navid Anjum Aadit +3
Neural quantum states efficiently represent many-body wavefunctions with neural networks, but the cost of Monte Carlo sampling limits their scaling to large system sizes. Here we a…
quant-ph2026
Predicting sampling advantage of stochastic Ising Machines for Quantum Simulations
Rutger J. L. F. Berns, Davi R. Rodrigues, Giovanni Finocchio +1
Stochastic Ising machines, sIMs, are highly promising accelerators for optimization and sampling of computational problems that can be formulated as an Ising model. Here we investi…
quant-ph2025
Pushing the Boundary of Quantum Advantage in Hard Combinatorial Optimization with Probabilistic Computers
Shuvro Chowdhury, Navid Anjum Aadit, Andrea Grimaldi +12
Recent demonstrations on specialized benchmarks have reignited excitement for quantum computers, yet whether they can deliver an advantage for practical real-world problems remains…