4 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…
Multivariate quantum state preparation with optimized tensor networks
Matthew L. Sims-Goh, Lukasz Cincio, Annina Z. Lieberherr +2
Quantics tensor trains are attracting intense interest for quantum-inspired computing and quantum state preparation. These methods, which approximate continuum functions by represe…
Quantum-Inspired Computational Fluid Dynamics for Transient Turbulent Compressible Flows
Shang Xian Matthew Lee, Melissa Kozul, Muhammad Usman +3
Quantum-inspired algorithms are an emerging class of algorithms for computational fluid dynamics (CFD) with potentially favourable scaling for large problems compared to classical…
Enabling Lie-Algebraic Classical Simulation beyond Free Fermions
Adelina Bärligea, Matthew L. Sims-Goh, Jakob S. Kottmann
Efficient classical simulation has matured to a critical component of the quantum computing stack, driving hardware validation, algorithm design, benchmarking, and the study of str…