Author

Matthew L. Sims-Goh

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Preprint Oct 2026

Breaking the chain: geometry-native state preparation with ASPIRE

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) are a critical enabler to manage this in quantum chemistry, finance, and many-body quantum simulation. Approximate preparation of MPS typi...

Fredrik Hasselgren, Matthew L. Sims-Goh · 0 citations

Preprint Aug 2026

Quantum-Inspired Computational Fluid Dynamics for Transient Turbulent Compressible Flows

This work introduces the first true end-to-end quantum-inspired computational fluid dynamics (QICFD) solver for direct numerical simulation of the compressible Navier-Stokes equations, and demonstrates the correctness of the new TT division and square-root algorithms, and that QICFD is capable of compressible flow simu...

S. Lee, M. Kozul, Muhammad Usman et al. · 2 citations

Preprint Sep 2026

Multivariate quantum state preparation with optimized tensor networks

SCENT (Spectral Clustering for Entanglement miNimizing Trees) is a protocol that utilizes efficiently-computable pairwise entanglement metrics to determine a suitable tree tensor network (TTN) structure, which is efficiently approximated using tensor cross-interpolation (TCI) and substantially outperforms MPS methods a...

Matthew L. Sims-Goh, L. Cincio, Annina Z. Lieberherr et al. · 2 citations