5 papers
Breaking the chain: geometry-native state preparation with ASPIRE
Fredrik Hasselgren, Matthew L. Sims-Goh
Loading data into quantum computers is a key bottleneck that threatens end-to-end quantum advantage. Quantum-circuit compilers for structured states like matrix product states (MPS…
Structure-Aware Variance Reduction for Unbiased Randomized Hamiltonian Simulation
Joshua W. Dai, Fredrik Hasselgren, Chusei Kiumi
Randomized Hamiltonian simulation methods are often governed by a trade-off between systematic bias and sampling overhead. We study how classical variance-reduction techniques can…
A virtually connected probabilistic computer as a solver for higher-order, densely connected, or reconfigurable combinatorial optimisation problems
Amy J. Searle, Harry Youel, Fredrik Hasselgren +3
Recently, there has been growing interest in unconventional computing as an approach for solving NP-hard problems, by developing dedicated hardware to find solutions more efficient…
Quantum-inspired classical simulation through randomized time evolution
Fredrik Hasselgren, Bálint Koczor
Tensor-network simulations of quantum many-body dynamics are fundamentally limited by entanglement build-up, which leads to exponentially growing computational costs. Furthermore,…
Probabilistic Computing Optimization of Complex Spin-Glass Topologies
Fredrik Hasselgren, Max O. Al-Hasso, Amy Searle +2
Spin glass systems as lattices of disordered magnets with random interactions have important implications within the theory of magnetization and applications to a wide-range of har…