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20232026
most citedContextual Subspace Variational Quantum Eigensolver Calculation of the Dissociation Curve of Molecular Nitrogen on a Superconducting Quantum Computer

14 citations · 23 across the 20 of their papers we have counts for

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11 papers · 1 filter

quant-ph2026

Adaptive decoding of quantum LDPC codes through decoder disagreement

Maida Wang, Peter V. Coveney

Accurate decoding of quantum low-density parity-check (qLDPC) codes often relies on expensive post-processing search, although decoding difficulty varies strongly between syndromes…

physics.flu-dyn2026

Reduced Subgrid-Scale Terms for Turbulence Simulations with the Lattice Boltzmann Method

Rik Hoekstra, Xiao Xue, Peter V. Coveney +1

Turbulent flows span a wide range of scales, making direct numerical simulation (DNS) prohibitively expensive at high Reynolds numbers. Large eddy simulation (LES) offers a pragmat…

quant-ph2026

Parallel and Distributed Fermionic Simulation via Dynamic Encoding

Michael Williams de la Bastida, Peter V. Coveney

We demonstrate a simple and efficient method to parallelize and distribute Trotterized Hamiltonian simulation of fermionic systems across multiple QPUs. Using combinatorial coverin…

physics.chem-ph2026

TNASS: Tensor Network Active Space Selection with the Entanglement Feature

Angus Mingare, Isabelle Heuzé, Peter V. Coveney

The quality of multi-scale modelling techniques in molecular electronic structure calculations, such as embedding and subspace methods, relies upon the chosen active space. The aut…

quant-ph2026

Quantum Statistical Memory Advantage Reveals Predictive Structure in Chaotic Invariant Measures

Maida Wang, Xiao Xue, Minh Chung +1

Long-horizon prediction of a chaotic system is governed by fidelity to its invariant measure, and which parts of that measure a learned predictor needs is a physical question not k…

physics.flu-dyn2026

Explainable quantum-compressed machine learning for complex fluid flows

Xiao Xue, Maida Wang, Mingyang Gao +2

Machine-learning surrogates of physical systems face a paradox: explainable models facing the challenge of expressivity to capture complex nonlinear flows, whereas expressive deep…

quant-ph2026

Quantum-Accelerated Self-Consistent Field: A Hybrid Algorithm

Alexis Ralli, Tim Weaving, Thomas M. Bickley +2

We present the Grover adaptive search self-consistent field (GAS-SCF) algorithm. GAS-SCF leverages quantum arithmetic to construct an efficient oracle that marks target states (Foc…

quant-ph2026

Irreversibility, equilibrium and measurement in quantum mechanics

Christopher J. N. Coveney, Peter V. Coveney

Quantum mechanics is widely recognised as being incomplete. It is not consistent with the second law of thermodynamics and does not provide a scientifically credible physical accou…

cs.AI2026

On the Smallness of the Large Language Models Scaling Exponents

Sauro Succi, Peter V. Coveney, Alex Hansen

We discuss reasons why the scaling exponents of current Large Language Models (LLMs) applications are indicating an unsustainable regime in terms of energy resources. We further sh…

quant-ph2026

Practical Log-Depth Quantum State Preparation and Circuit Verification via Tree Tensor Network Compilation

Angus Mingare, Peter V. Coveney

Matrix product states provide efficient classical descriptions of quantum systems that may be useful as reference states for quantum algorithms such as quantum phase estimation and…

physics.flu-dyn2026

Uni-Flow: a unified autoregressive-diffusion model for complex multiscale flows

Xiao Xue, Tianyue Yang, Mingyang Gao +7

Spatiotemporal flows govern diverse phenomena across physics, biology, and engineering, yet modelling their multiscale dynamics remains a central challenge. Despite major advances…