14 citations · 23 across the 20 of their papers we have counts for
24 papers
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Optimised Fermion-Qubit Encodings for Quantum Simulation with Reduced Transpiled Circuit Depth
Michael Williams de la Bastida, Thomas M. Bickley, Peter V. Coveney
Simulation of fermionic Hamiltonians with gate-based quantum computers requires the selection of an encoding from fermionic operators to quantum gates, the most widely used being t…
Fast-Forward Lattice Boltzmann: Learning Kinetic Behaviour with Physics-Informed Neural Operators
Xiao Xue, Marco F. P. ten Eikelder, Mingyang Gao +7
The lattice Boltzmann equation (LBE), rooted in kinetic theory, provides a powerful framework for capturing complex flow behaviour by describing the evolution of single-particle di…
Equivariant U-Shaped Neural Operators for the Cahn-Hilliard Phase-Field Model
Xiao Xue, Marco F. P. ten Eikelder, Tianyue Yang +4
Phase separation in binary mixtures, governed by the Cahn-Hilliard equation, plays a central role in interfacial dynamics across materials science and soft matter. While numerical…
Towards Compact Wavefunctions from Quantum-Selected Configuration Interaction
Tim Weaving, Angus Mingare, Alexis Ralli +1
A recent direction in quantum computing for molecular electronic structure sees the use of quantum devices as configuration sampling machines integrated within high-performance com…
An Uncertainty Visualization Framework for Large-Scale Cardiovascular Flow Simulations: A Case Study on Aortic Stenosis
Xiao Xue, Tushar M. Athawale, Jon W. S. McCullough +5
We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated…
The wall confronting large language models
Peter V. Coveney, Sauro Succi
We show that the scaling laws which determine the performance of large language models (LLMs) severely limit their ability to improve the uncertainty of their predictions. As a res…
Quantum-Informed Machine Learning for Predicting Spatiotemporal Chaos with Practical Quantum Advantage
Maida Wang, Xiao Xue, Mingyang Gao +1
We introduce a quantum-informed machine learning (QIML) framework for modelling the long-term behaviour of high-dimensional chaotic systems. QIML combines a one-time, offline-train…
Simulating the Antiferromagnetic Heisenberg Model on a Spin-Frustrated Kagome Lattice with the Contextual Subspace Variational Quantum Eigensolver
Tim Weaving, Alexis Ralli, Vinul Wimalaweera +2
In this work we investigate the ground state properties of a candidate quantum spin liquid using a superconducting Noisy Intermediate-Scale Quantum (NISQ) device. Specifically, we…
Bridging Quantum Chemistry and MaxCut: Classical Performance Guarantees and Quantum Algorithms for the Hartree-Fock Method
Alexis Ralli, Tim Weaving, Peter V. Coveney +1
In quantum chemistry, self-consistent field (SCF) algorithms define a nonlinear optimization problem, with both continuous and discrete components. In this work, we derive Hartree-…
A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor
Maida Wang, Jinyang Jiang, Peter V. Coveney
Quantum machine learning has gained attention for its potential to address computational challenges. However, whether those algorithms can effectively solve practical problems and…
A Multi-Component, Multi-Physics Computational Model for Solving Coupled Cardiac Electromechanics and Vascular Haemodynamics
Sharp C. Y. Lo, Alberto Zingaro, Jon W. S. McCullough +5
The circulatory system, comprising the heart and blood vessels, is vital for nutrient transport, waste removal, and homeostasis. Traditional computational models often treat cardia…
Accurately Simulating the Time Evolution of an Ising Model with Echo Verified Clifford Data Regression on a Superconducting Quantum Computer
Tim Weaving, Alexis Ralli, Peter J. Love +2
We present an error mitigation strategy composed of Echo Verification (EV) and Clifford Data Regression (CDR), the combination of which allows one to learn the effect of the quantu…
Contextual Subspace Variational Quantum Eigensolver Calculation of the Dissociation Curve of Molecular Nitrogen on a Superconducting Quantum Computer
Tim Weaving, Alexis Ralli, Peter J. Love +2
In this work we present an experimental demonstration of the Contextual Subspace Variational Quantum Eigensolver on superconducting quantum hardware. In particular, we compute the…