Skip to content
aiqbench takeQuantum Computing

aiqbench analysis

This research introduces a locality-based truncation framework that significantly reduces query costs for estimating time-accumulated observables in quantum simulations of lattice Hamiltonians. By leveraging Lieb-Robinson bounds to manage errors from spatial truncation, the method achieves unbounded efficiency gains as system size increases across free, interacting, and open quantum systems. The approach represents a critical algorithmic advancement for scaling classical information extraction from complex quantum dynamics without relying on full-Hamiltonian norms.
Source coveringarXiv
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Accelerating Quantum Dense-Output Simulation through Locality

arXiv2 min read

arXiv:2609.40094v1 Announce Type: new Abstract: Estimating time-accumulated observables, or dense outputs, is central to extracting classical information from quantum simulations. Whereas most quantum-simulation algorithms aim to reproduce a final state or a single-time expectation value, many applications require the integrated signal $J_H(O)=\int_0^T \langle \psi(t)|O(t)|\psi(t)\rangle\,dt$. Previous Hamiltonian-simulation-based dense-output algorithms have query costs that depend on the norm of the full Hamiltonian, which can grow with system size. However, one can naturally optimize the simulation algorithm when the system structure is known. Consequently, we develop a locality-based truncation framework for the dense-output problem on lattice Hamiltonians. By truncating the Hamiltonian and tightening the resulting error with Lieb-Robinson bounds, we show that a local simulation can recover the dense output. We bound the quantum simulation error from spatial truncation and translate it into local-simulation query bounds. Our analysis includes free and interacting systems for both fermions and bosons, as well as open quantum systems governed by Lindbladians. The improvement from our truncation algorithm varies from constant to unbounded as the system size grows. We also give example applications and conduct relevant numerical experiments to support our findings.

Abstract:Estimating time-accumulated observables, or dense outputs, is central to extracting classical information from quantum simulations. Whereas most quantum-simulation algorithms aim to reproduce a final state or a single-time expectation value, many applications require the integrated signal $J_H(O)=\int_0^T \langle \psi(t)|O(t)|\psi(t)\rangle\,dt$. Previous Hamiltonian-simulation-based dense-output algorithms have query costs that depend on the norm of the full Hamiltonian, which can grow with system size. However, one can naturally optimize the simulation algorithm when the system structure is known. Consequently, we develop a locality-based truncation framework for the dense-output problem on lattice Hamiltonians. By truncating the Hamiltonian and tightening the resulting error with Lieb-Robinson bounds, we show that a local simulation can recover the dense output. We bound the quantum simulation error from spatial truncation and translate it into local-simulation query bounds. Our analysis includes free and interacting systems for both fermions and bosons, as well as open quantum systems governed by Lindbladians. The improvement from our truncation algorithm varies from constant to unbounded as the system size grows. We also give example applications and conduct relevant numerical experiments to support our findings.

arXiv:2609.40094 [quant-ph]

(or arXiv:2609.40094v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.40094 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 270 words

Related coverage