Experimental Demonstration of 7-Dimensional N-Vector Model with Dimensional Inflation and Annealing
Abstract
We report the first experimental realization of a physical system described by a high-dimensional Hamiltonian comprising up to seven dimensions. Our setup is based on a holographic optical computer, which realizes a dimensional inflation by spatial and temporal multiplexing of lower dimensional systems. We demonstrate an N-vector model, with applications in field theory and computing. The approach is scalable and enables table-top implementation of high-dimensional theoretical models, and novel methods for combinatorial optimization. We experimentally demonstrate dimensional annealing: by dynamically reducing the number of dimensions, the ground state of an Ising model is found in complex graphs by an adiabatic evolution from high-dimensional spaces.
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BibTeX
@misc{veraldi2026experimental,
title = {{Experimental Demonstration of 7-Dimensional N-Vector Model with Dimensional Inflation and Annealing}},
author = {Daniele Veraldi and Marcello Calvanese Strinati and Paolo Charlesworth and Matteo Spaziani and Silvia Gentilini and Davide Pierangeli and Claudio Conti},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.18153},
eprint = {2610.18153},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.18153},
}
RIS
TY - UNPB
TI - Experimental Demonstration of 7-Dimensional N-Vector Model with Dimensional Inflation and Annealing
AU - Daniele Veraldi
AU - Marcello Calvanese Strinati
AU - Paolo Charlesworth
AU - Matteo Spaziani
AU - Silvia Gentilini
AU - Davide Pierangeli
AU - Claudio Conti
PY - 2026
DA - 2026/10/13
PB - arXiv
DO - 10.48550/arxiv.2610.18153
UR - https://arxiv.org/abs/2610.18153
AB - We report the first experimental realization of a physical system described by a high-dimensional Hamiltonian comprising up to seven dimensions. Our setup is based on a holographic optical computer, which realizes a dimensional inflation by spatial and temporal multiplexing of lower dimensional systems. We demonstrate an N-vector model, with applications in field theory and computing. The approach is scalable and enables table-top implementation of high-dimensional theoretical models, and novel methods for combinatorial optimization. We experimentally demonstrate dimensional annealing: by dynamically reducing the number of dimensions, the ground state of an Ising model is found in complex graphs by an adiabatic evolution from high-dimensional spaces.
ER -