Linear Anyon Model with Rydberg Atoms
Aditya Banerjee
Abstract
Master’s thesis by Aditya Banerjee, Master in Quantum Science and Technology, Facultat de Física, Universitat de Barcelona, academic year 2025–2026. Supervisor: Prof. Alessio Celi. First published in the university repository in September 2026. Abstract We propose a scheme for quantum-simulating the one-dimensional anyon-Hubbard model with Rydberg atoms. Starting from the generalized Jordan–Wigner transformation, which trades anyonic exchange statistics for a density-dependent Peierls phase, we encode the truncated local occupations {|0⟩, |1⟩, |2⟩} in the internal levels of Rydberg atoms driven by Raman lasers with site-dependent phases. Adiabatically eliminating the far-detuned intermediate states in the dispersive regime yields an effective bond Hamiltonian whose four tunnelling amplitudes we obtain in second-order perturbation theory. First, we show that the Raman scheme allows one to simulate pseudo-fermions with bosons, but not generic anyons: Floquet driving is necessary to engineer a generic statistical phase. In fact, we find that single-tone Floquet driving leads to density-dependent amplitudes, but it is not sufficient to achieve the desired density-dependent tunnelling. This calculation suggests that to achieve the phases one needs a drive with several tones, each resonant with one occupation-resolved process and each carrying its own phase, a mechanism similar to the one employed in the recent few-particle realization of the anyon-Hubbard model with ultracold neutral atoms in optical lattices. Files and provenance Masters_Thesis_Banerjee_Aditya.pdf is the thesis PDF downloaded from the University of Barcelona repository. Permanent institutional identifier: https://hdl.handle.net/2445/231684. linear-anyon-rydberg-thesis-code-and-data-2295996.zip archives the code and saved data from the accompanying GitHub repository, commit 22959963191fcbc4d283ec4b272b506ad6dd979b, archived on 18 October 2026. It includes the README, 10 Python scripts, two saved NumPy datasets and the source manifest, with their original file contents unchanged. An ARCHIVE_CONTENTS.txt file describes the package. Reference figures remain available in the linked GitHub repository at the identified commit. Consult the repository README for figure mappings, dependencies and limitations. Rights The CC BY-NC-ND 4.0 licence listed for this record applies to the thesis PDF, matching the institutional record. The accompanying GitHub snapshot is supplied with its original rights retained; the source repository contained no separate software licence, and this deposit does not grant an additional software licence.