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20242026
most citedPushing the Boundary of Quantum Advantage in Hard Combinatorial Optimization with Probabilistic Computers

9 citations · 12 across the 10 of their papers we have counts for

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cond-mat.mtrl-sci2025

A fluctuation-free pathway for a topological magnetic phase transition

Riccardo Battistelli, Lukas Körber, Kai Litzius +27

Topological magnetic textures are particle-like spin configurations stabilized by competing interactions. Their formation is commonly attributed to fluctuation-driven, first-order…

cond-mat.mes-hall2025

Picosecond localization dynamics following ultrafast nanoscale magnetic switching

Daniel Metternich, Michael Schneider, Giuseppe Mercurio +28

Ultrashort laser pulses provide the fastest known way to switch magnetic order. Such excitation commonly creates nanometer-scale domains, even after homogeneous illumination when t…

quant-ph2025

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…

cond-mat.mtrl-sci2025

Multi-value Probabilistic Computing with current-controlled Skyrmion Diffusion

Thomas B. Winkler, Yuean Zhou, Grischa Beneke +6

Magnetic systems are highly promising for implementing probabilistic computing paradigms because of the fitting energy scales and conspicuous non-linearities. While conventional bi…

cond-mat.mtrl-sci2025★ 1 cited

Revealing domain wall stability during ultrafast demagnetization

Hung-Tzu Chang, Sergey Zayko, Timo Schmidt +5

The ultrafast control of nanoscale spin textures such as magnetic domain walls or skyrmions is essential for advancing high-speed, high-density spintronics. However, imaging their…

quant-ph2025

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★ 9 cited

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…