most citedVeloxQ: A Fast and Efficient QUBO Solver

2 citations · 2 across the 2 of their papers we have counts for

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quant-ph2026

Toward quantum scaling advantage in approximate optimization

J. Pawłowski, P. Tarasiuk, J. Tuziemski +2

In a recent Letter [H. Munoz-Bauza and D. Lidar, Phys. Rev. Lett. 134, 160601 (2025)], quantum annealing was reported to exhibit a scaling advantage in approximately solving quadra…

quant-ph20262 cited

VeloxQ: A Fast and Efficient QUBO Solver

J. Pawłowski, J. Tuziemski, P. Tarasiuk +5

We introduce VeloxQ, a fast solver for Quadratic Unconstrained Binary Optimization (QUBO) problems, which are central to many real-world optimization tasks. Unlike approaches that…

quant-ph2026

Simulated Bifurcation Quantum Annealing

Jakub Pawłowski, Paweł Tarasiuk, Jan Tuziemski +2

We introduce Simulated Bifurcation Quantum Annealing (SBQA), a quantum-inspired optimization algorithm that extends simulated bifurcation by incorporating inter-replica interaction…

quant-ph2026

Recent quantum runtime (dis)advantages

J. Tuziemski, J. Pawłowski, P. Tarasiuk +2

A robust definition of quantum runtime is essential for assessing the performance of quantum algorithms and claims of quantum advantage. While for most classical hardware the total…

quant-ph20261 cited

Quantum-inspired dynamical models on quantum and classical annealers

Philipp Hanussek, Jakub Pawłowski, Zakaria Mzaouali +1

We propose a practical, physics-inspired benchmarking suite to challenge both quantum and classical computers by mapping real-time quantum dynamics to a common optimization format.…