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Lie-algebraic classical simulations for quantum computing

Matthew L. Goh ^1,2,*, Martin Larocca^1,3, Lukasz Cincio¹, M. Cerezo⁴, and Frédéric Sauvage ^1,5

¹Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
²Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, United Kingdom
³Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
⁴Information Sciences, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
⁵Quantinuum, Partnership House, Carlisle Place, London SW1P 1BX, United Kingdom

^*Contact author: matt.goh@merton.ox.ac.uk

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Articles Citing

Lie-algebraic classical simulations for quantum computing

Arbitrary Polynomial Separations in Trainable Quantum Machine Learning

On the dynamical Lie algebras of quantum approximate optimization algorithms

Quantum Convolutional Neural Networks are Effectively Classically Simulable

Efficient Quantum-Enhanced Classical Simulation for Patches of Quantum Landscapes

Direct estimation of the density of states for fermionic systems

Quantum simulation of massive Thirring and Gross-Neveu models for arbitrary number of flavors

Expressivity limits in quantum walk-based optimization

Variational decision diagrams for quantum-inspired machine-learning applications

Exact many-body quantum dynamics in one-dimensional baths via collective spins

The Lie algebra of XY-mixer topologies and warm starting QAOA for constrained optimization

Exclusive-or encoded algebraic structure for efficient quantum dynamics

Classification of dynamical Lie algebras generated by spin interactions on undirected graphs

Quantum Neural Networks for Symbol Recovery in Long-Haul Terahertz Communication Systems

Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms

Variational Quantum Computing for Quantum Simulation: Principles, Implementations, and Challenges

Analyzing the Free States of one Quantum Resource Theory as Resource States of Another

A graph-theoretic approach to chaos and complexity in quantum systems

Backpropagation scaling in parameterised quantum circuits

Analyzing the Quantum Approximate Optimization Algorithm: Ansätze, Symmetries, and Lie Algebras

Observation of Lie algebraic invariants in quantum linear optics

Vortex detection from quantum data

Efficient online quantum circuit learning with no upfront training

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