arXiv subjects

Nicholas Milson

Publications and source records attributed to Nicholas Milson.

3 recordsLinked to original sources

arXiv2026

Tuning Topological Charge and Gauge Field Anisotropy in a Spin-1 Synthetic Monopole

Higher-dimensional Hilbert spaces in quantum simulation, as in all quantum science, expand the range of accessible phenomena. In this work, we experimentally realize a synthetic monopole using an ultracold spin-1 ensemble, where the monopole charge is quantified by the topologically invariant first Chern number and sources a synthetic magnetic field quantified by the Berry curvature. By using a three-level system with tunable spin-tensor coupling, we introduce anisotropy to the field, directly measure the Chern number, and observe a topological phase transition. We verify the robustness of the monopole's topological charge under deformation, and observe signatures of the topological phases using spin-texture and Majorana-star measurements. This work demonstrates spin-tensor coupling as a tuning parameter for engineering both geometric anisotropy and a rich topological phase space.

cond-mat.quant-gas↗

arXiv2023

High-dimensional reinforcement learning for optimization and control of ultracold quantum gases

Machine-learning techniques are emerging as a valuable tool in experimental physics, and among them, reinforcement learning offers the potential to control high-dimensional, multistage processes in the presence of fluctuating environments. In this experimental work, we apply reinforcement learning to the preparation of an ultracold quantum gas to realize a consistent and large number of atoms at microkelvin temperatures. This reinforcement learning agent determines an optimal set of thirty control parameters in a dynamically changing environment that is characterized by thirty sensed parameters. By comparing this method to that of training supervised-learning regression models, as well as to human-driven control schemes, we find that both machine learning approaches accurately predict the number of cooled atoms and both result in occasional superhuman control schemes. However, only the reinforcement learning method achieves consistent outcomes, even in the presence of a dynamic environment.

cond-mat.quant-gas↗

arXiv2020

A Python Code to Determine Orbital Parameters of Spectroscopic Binaries

We present the open source Python code BinaryStarSolver that solves for the orbital elements of a spectroscopic binary system. Given a time-series of radial velocity measurements, six orbital parameters are determined: the long-term mean, or systemic, radial velocity, the velocity amplitude, the argument of periastron, the eccentricity, the epoch of periastron, and the orbital period referred to by $\{{\gamma, K, \omega, e, T_0, P}\}$ respectively. Also returned to the user is the projected length of the semi-major axis, $a_{1}\sin(i)$, and the mass function, $f(M)$. The determination of spectroscopic orbits and masses is an example of another important area of astrophysics, once the domain of professional astronomers, to which amateurs can now make significant contributions. This code, available from GitHub, is provided in support of that work, and should be of general use to the amateur and professional astronomical community.

astro-ph.SR↗