Title:	Real-time local density probe for cold atoms utilizing Raman driven spin noise spectroscopy
Authors:	Majumder, Sayari Bidwai, Bhagyashri Varsha, Bernadette Chaudhuri, Saptarishi
Keywords:	Fluorescence Absorption imaging Spin noise spectroscopy Integral transforms Photon scattering Magneto-optical trap Spectrum analyzers Lasers Stochastic processes
Issue Date:	31-Jul-2025
Publisher:	AIP Publishing
Citation:	Applied Physics Letters, 2025, Vol.127, p044004
Abstract:	We demonstrate a minimally perturbative detection method—Raman driven spin noise spectroscopy (RDSNS)—to directly probe the local density of a cloud of cold atoms in real time. The technique relies on detecting the polarization fluctuations of a far-off resonant focused probe light passing through the atoms, driven by two coherent Raman lasers connecting adjacent Zeeman spin states. This is an easily implementable scheme with a wide-ranging applicability in detecting cold atoms. Unlike traditional fluorescence and absorption imaging techniques, this approach does not require stochastic photon scattering from trapped atoms, thereby leaving the cold cloud unperturbed. The data can be collected in MHz refresh rate, allowing for near real-time detection. We validated this technique by monitoring the strength of the RDSNS signal by varying the key parameters of the three-dimensional magneto-optical trap (MOT) and the cold atom source (two-dimensional MOT). We performed experiments to probe local densities across the cold atom cloud using our technique and compared it with the inverse Abel-transformed density profiles extracted from the fluorescence of a spherically symmetric atomic cloud and found excellent agreement. This detection protocol is particularly advantageous for probing systems that lack inherent symmetry, where the Abel transformation is inapplicable. Moreover, RDSNS imaging is suitable for extracting the dynamical properties of systems in real time.
Description:	Open Access
URI:	http://hdl.handle.net/2289/8423
Alternative Location:	https://doi.org/10.1063/5.0277027
Copyright:	2025 AIP Publishing
Appears in Collections:	Research Papers (LAMP)

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