An application of continuous-variable gate synthesis to quantum simulation of classical dynamics
Sam Cochran, James Stokes, Paramsothy Jayakumar, Shravan Veerapaneni

TL;DR
This paper explores using continuous-variable quantum computing to simulate classical nonlinear dynamics, addressing limitations of qubit-based methods by proposing a CVQC approach with explicit gate synthesis for anharmonic vibrational systems.
Contribution
It introduces a CVQC algorithm for classical dynamics simulation, overcoming projection issues in qubit-based methods, with explicit gate synthesis for anharmonic vibrational Hamiltonians.
Findings
CVQC naturally avoids projection artifacts
Proposed explicit gate synthesis for anharmonic systems
Enhanced simulation of classical nonlinear dynamics
Abstract
Although quantum computing holds promise to accelerate a wide range of computational tasks, the quantum simulation of quantum dynamics as originally envisaged by Feynman remains the most promising candidate for achieving quantum advantage. A less explored possibility with comparably far-reaching technological applicability is the quantum simulation of classical nonlinear dynamics. Attempts to develop digital quantum algorithms based on the Koopman von Neumann formalism have met with challenges because of the necessary projection step from an infinite-dimensional Hilbert space to the finite-dimensional subspace described by a collection of qubits. This finitization produces numerical artifacts that limit solutions to very short time horizons. In this paper we review continuous-variable quantum computing (CVQC), which naturally avoids such obstacles, and a CVQC algorithm for KvN…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Neural Networks and Reservoir Computing · Quantum Information and Cryptography
