%0 Journal Article %J Phys. Rev. Research %D 2022 %T Combining machine learning with physics: A framework for tracking and sorting multiple dark solitons %A Shangjie Guo %A Sophia M. Koh %A Amilson R. Fritsch %A I. B. Spielman %A Justyna P. Zwolak %X

In ultracold-atom experiments, data often comes in the form of images which suffer information loss inherent in the techniques used to prepare and measure the system. This is particularly problematic when the processes of interest are complicated, such as interactions among excitations in Bose-Einstein condensates (BECs). In this paper, we describe a framework combining machine learning (ML) models with physics-based traditional analyses to identify and track multiple solitonic excitations in images of BECs. We use an ML-based object detector to locate the solitonic excitations and develop a physics-informed classifier to sort solitonic excitations into physically motivated subcategories. Lastly, we introduce a quality metric quantifying the likelihood that a specific feature is a longitudinal soliton. Our trained implementation of this framework, SolDet, is publicly available as an open-source python package. SolDet is broadly applicable to feature identification in cold-atom images when trained on a suitable user-provided dataset.

%B Phys. Rev. Research %V 4 %P 023163 %8 06/01/2022 %G eng %U https://arxiv.org/abs/2111.04881 %R https://doi.org/10.1103/PhysRevResearch.4.023163 %0 Journal Article %D 2022 %T Dark Solitons in Bose-Einstein Condensates: A Dataset for Many-body Physics Research %A Amilson R. Fritsch %A Shangjie Guo %A Sophia M. Koh %A I. B. Spielman %A Justyna P. Zwolak %X

We establish a dataset of over 1.6×104 experimental images of Bose-Einstein condensates containing solitonic excitations to enable machine learning (ML) for many-body physics research. About 33 % of this dataset has manually assigned and carefully curated labels. The remainder is automatically labeled using SolDet -- an implementation of a physics-informed ML data analysis framework -- consisting of a convolutional-neural-network-based classifier and object detector as well as a statistically motivated physics-informed classifier and a quality metric. This technical note constitutes the definitive reference of the dataset, providing an opportunity for the data science community to develop more sophisticated analysis tools, to further understand nonlinear many-body physics, and even advance cold atom experiments.

%8 05/17/2022 %G eng %U https://arxiv.org/abs/2205.09114 %0 Journal Article %J Phys. Rev. Research %D 2021 %T Feedback-stabilized dynamical steady states in the Bose-Hubbard model %A Jeremy T. Young %A Alexey V. Gorshkov %A I. B. Spielman %X

The implementation of a combination of continuous weak measurement and classical feedback provides a powerful tool for controlling the evolution of quantum systems. In this work, we investigate the potential of this approach from three perspectives. First, we consider a double-well system in the classical large-atom-number limit, deriving the exact equations of motion in the presence of feedback. Second, we consider the same system in the limit of small atom number, revealing the effect that quantum fluctuations have on the feedback scheme. Finally, we explore the behavior of modest sized Hubbard chains using exact numerics, demonstrating the near-deterministic preparation of number states, a tradeoff between local and non-local feedback for state preparation, and evidence of a feedback-driven symmetry-breaking phase transition.

%B Phys. Rev. Research %V 3 %P 043075 %8 12/15/2021 %G eng %U https://arxiv.org/abs/2106.09744 %N 4 %R https://doi.org/10.1103/PhysRevResearch.3.043075 %0 Journal Article %J Mach. Learn.: Sci. Technol. %D 2021 %T Machine-learning enhanced dark soliton detection in Bose-Einstein condensates %A Shangjie Guo %A Amilson R. Fritsch %A Craig Greenberg %A I. B. Spielman %A Justyna P. Zwolak %X

Most data in cold-atom experiments comes from images, the analysis of which is limited by our preconceptions of the patterns that could be present in the data. We focus on the well-defined case of detecting dark solitons -- appearing as local density depletions in a BEC -- using a methodology that is extensible to the general task of pattern recognition in images of cold atoms. Studying soliton dynamics over a wide range of parameters requires the analysis of large datasets, making the existing human-inspection-based methodology a significant bottleneck. Here we describe an automated classification and positioning system for identifying localized excitations in atomic Bose-Einstein condensates (BECs) utilizing deep convolutional neural networks to eliminate the need for human image examination. Furthermore, we openly publish our labeled dataset of dark solitons, the first of its kind, for further machine learning research.

%B Mach. Learn.: Sci. Technol. %V 2 %P 035020 %8 6/17/2021 %G eng %U https://arxiv.org/abs/2101.05404 %R https://doi.org/10.1088/2632-2153/abed1e %0 Journal Article %D 2020 %T Feedback Induced Magnetic Phases in Binary Bose-Einstein Condensates %A Hilary M. Hurst %A Shangjie Guo %A I. B. Spielman %X

Weak measurement in tandem with real-time feedback control is a new route toward engineering novel non-equilibrium quantum matter. Here we develop a theoretical toolbox for quantum feedback control of multicomponent Bose-Einstein condensates (BECs) using backaction-limited weak measurements in conjunction with spatially resolved feedback. Feedback in the form of a single-particle potential can introduce effective interactions that enter into the stochastic equation governing system dynamics. The effective interactions are tunable and can be made analogous to Feshbach resonances -- spin-independent and spin-dependent -- but without changing atomic scattering parameters. Feedback cooling prevents runaway heating due to measurement backaction and we present an analytical model to explain its effectiveness. We showcase our toolbox by studying a two-component BEC using a stochastic mean-field theory, where feedback induces a phase transition between easy-axis ferromagnet and spin-disordered paramagnet phases. We present the steady-state phase diagram as a function of intrinsic and effective spin-dependent interaction strengths. Our result demonstrates that closed-loop quantum control of Bose-Einstein condensates is a powerful new tool for quantum engineering in cold-atom systems.

%8 7/14/2020 %G eng %U https://arxiv.org/abs/2007.07266 %0 Journal Article %J Phys. Rev. Lett %D 2019 %T Scale-Invariant Continuous Entanglement Renormalization of a Chern Insulator %A Su-Kuan Chu %A Guanyu Zhu %A James R. Garrison %A Zachary Eldredge %A Ana Valdés Curiel %A Przemyslaw Bienias %A I. B. Spielman %A Alexey V. Gorshkov %X

The multi-scale entanglement renormalization ansatz (MERA) postulates the existence of quantum circuits that renormalize entanglement in real space at different length scales. Chern insulators, however, cannot have scale-invariant discrete MERA circuits with finite bond dimension. In this Letter, we show that the continuous MERA (cMERA), a modified version of MERA adapted for field theories, possesses a fixed point wavefunction with nonzero Chern number. Additionally, it is well known that reversed MERA circuits can be used to prepare quantum states efficiently in time that scales logarithmically with the size of the system. However, state preparation via MERA typically requires the advent of a full-fledged universal quantum computer. In this Letter, we demonstrate that our cMERA circuit can potentially be realized in existing analog quantum computers, i.e., an ultracold atomic Fermi gas in an optical lattice with light-induced spin-orbit coupling. 

%B Phys. Rev. Lett %V 122 %8 03/27/2019 %G eng %U https://arxiv.org/abs/1807.11486 %N 120502 %R https://doi.org/10.1103/PhysRevLett.122.120502 %0 Journal Article %J Physical Review A %D 2011 %T Chern numbers hiding in time-of-flight images %A Erhai Zhao %A Noah Bray-Ali %A Carl J. Williams %A I. B. Spielman %A Indubala I. Satija %X We present a technique for detecting topological invariants -- Chern numbers -- from time-of-flight images of ultra-cold atoms. We show that the Chern numbers of integer quantum Hall states of lattice fermions leave their fingerprints in the atoms' momentum distribution. We analytically demonstrate that the number of local maxima in the momentum distribution is equal to the Chern number in two limiting cases, for large hopping anisotropy and in the continuum limit. In addition, our numerical simulations beyond these two limits show that these local maxima persist for a range of parameters. Thus, an everyday observable in cold atom experiments can serve as a useful tool to characterize and visualize quantum states with non-trivial topology. %B Physical Review A %V 84 %8 2011/12/21 %G eng %U http://arxiv.org/abs/1105.3100v3 %N 6 %! Phys. Rev. A %R 10.1103/PhysRevA.84.063629