Photonic simulation of localization phenomena using boson sampling

Quantum simulation in its current state faces experimental overhead in terms of physical space and cooling. We propose boson sampling as an alternative compact synthetic platform performing at room temperature. Identifying the capability of estimating matrix permanents, we explore the applicability of boson sampling for tackling the dynamics of quantum systems without having access to information about the full state vector. By mapping the time-evolution unitary of a Hamiltonian onto an interferometer via continuous-variable gate decompositions, we present proof-of-principle results of localization characteristics of a single particle. We study the dynamics of one-dimensional tight-binding systems in the clean and quasiperiodic-disordered limits to observe Bloch oscillations and dynamical localization, and the delocalization-to-localization phase transition in the Aubry-Andr\'e-Harper model, respectively. Our computational results obtained using boson sampling are in complete agreement with the dynamical and static results of noninteracting tight-binding systems obtained using conventional numerical calculations. Additionally, our study highlights the role of the number of sampling measurements or ``shots'' for simulation accuracy.

Authors

Institutions

Publication Details

Journal
Physical review. A/Physical review, A
Published
2025-03-31
DOI
https://doi.org/10.1103/physreva.111.032622
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Photonic simulation of localization phenomena using boson sampling

Auditya Sharma, Ankur Raina, Vatsana Tiwari, Anuprita V. Kulkarni
Physical review. A/Physical review, A
Neural Networks and Reservoir Computing
article

Photonic simulation of localization phenomena using boson sampling

Auditya Sharma, Ankur Raina, Vatsana Tiwari, Anuprita V. Kulkarni
article en

Abstract

Quantum simulation in its current state faces experimental overhead in terms of physical space and cooling. We propose boson sampling as an alternative compact synthetic platform performing at room temperature. Identifying the capability of estimating matrix permanents, we explore the applicability of boson sampling for tackling the dynamics of quantum systems without having access to information about the full state vector. By mapping the time-evolution unitary of a Hamiltonian onto an interferometer via continuous-variable gate decompositions, we present proof-of-principle results of localization characteristics of a single particle. We study the dynamics of one-dimensional tight-binding systems in the clean and quasiperiodic-disordered limits to observe Bloch oscillations and dynamical localization, and the delocalization-to-localization phase transition in the Aubry-Andr\'e-Harper model, respectively. Our computational results obtained using boson sampling are in complete agreement with the dynamical and static results of noninteracting tight-binding systems obtained using conventional numerical calculations. Additionally, our study highlights the role of the number of sampling measurements or ``shots'' for simulation accuracy.

Physical review. A/Physical review, AVol. 111(3)
Indian Institute of Science Education and Research, Bhopal (IN)
Department of Science and Technology, Ministry of Science and Technology, India, Indian Institute of Science Education and Research Bhopal
Openalex Percentile: Top 97%
Neural Networks and Reservoir Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.