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Review of Scientific Instruments

Modified control software for imaging ultracold atomic clouds

Dwight Whitaker, Arjun Sharma, John M. Brown

Published Dec 1, 2006• 4 citations
Publisher

Abstract

A charge-coupled device (CCD) camera capable of taking high-quality images of ultracold atomic samples can often represent a significant portion of the equipment costs in atom trapping experiment. We have modified the commercial control software of a CCD camera designed for astronomical imaging to take absorption images of ultracold rubidium clouds. This camera is sensitive at 780 nm and has been modified to take three successive 16-bit images at full resolution. The control software can be integrated into a Matlab graphical user interface with fitting routines written as Matlab functions. This camera is capable of recording high-quality images at a fraction of the cost of similar cameras typically used in atom trapping experiments.

DOI
10.1063/1.2400012

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A charge-coupled device (CCD) camera capable of taking high-quality images of ultracold atomic samples can often represent a significant portion of the equipment costs in atom trapping experiment. We have modified the commercial control software of a CCD camera designed for astronomical imaging to take absorption images of ultracold rubidium clouds. This camera is sensitive at 780 nm and has been modified to take three successive 16-bit images at full resolution. The control software can be integrated into a Matlab graphical user interface with fitting routines written as Matlab functions. This camera is capable of recording high-quality images at a fraction of the cost of similar cameras typically used in atom trapping experiments.
A fluorescence detection scheme coupled to a highly sensitive nitrogen-cooled CCD camera is used to image the spatial distribution of a low-density falling rubidium atomic cloud released from an optical trap. The falling cloud passes through a thin probe laser beam tuned to resonance. The performance of the scheme is illustrated in the analysis of cold atomic clouds collimated by pinholes during their free fall under the influence of gravity. Clouds of approximately 10(4) atoms and with typically 10(6) at./cm(3) density are analyzed spatially with 24-mum resolution. This method is compared with different atomic cloud imaging techniques.
We present a novel imaging system for ultracold quantum gases in expansion. After release from a confining potential, atoms fall through a sheet of resonant excitation laser light and the emitted fluorescence photons are imaged onto an amplified CCD camera using a high numerical aperture optical system. The imaging system reaches an extraordinary dynamic range, not attainable with conventional absorption imaging. We demonstrate single-atom detection for dilute atomic clouds with high efficiency where at the same time dense Bose-Einstein condensates can be imaged without saturation or distortion. The spatial resolution can reach the sampling limit as given by the 8 μm pixel size in object space. Pulsed operation of the detector allows for slice images, a first step toward a 3D tomography of the measured object. The scheme can easily be implemented for any atomic species and all optical components are situated outside the vacuum system. As a first application we perform thermometry on rubidium Bose-Einstein condensates created on an atom chip.
The ability to detect atoms in high spatiotemporal resolution provides a powerful tool for us to investigate the quantum properties of ultracold quantum gases. Plenty of useful imaging methods, including absorption imaging, phase contrast imaging and fluorescence imaging, have been implemented in detecting atoms. Among them, absorption imaging is the most widely used method in cold atoms laboratory. However, the traditional absorption imaging method is affected by perturbations such as interference between optical elements, fluctuation of laser power, frequency, and spatial position, resulting in residual spatially structured noise and degradation of imaging quality. Especially for regions with lower density or for longer time-of-flight, a large number of repetitions are often required to obtain better signal-to-noise ratio, which would increase the time cost and induce other noise. One must reduce the time between two imaging pulses to suppress the spatial noise. A better charge coupled device (CCD) with higher frame transfer rate or other method like fast-kinetic mode will be used to improve the imaging quality. In this paper, a single-shot cold atom imaging method based on machine learning is proposed, in which only one absorption imaging of cold atoms is required, and the corresponding background image can be generated through the neural network of an autoencoder. This effectively reduces the spatial striped noise in imaging, significantly improves the imaging quality, and makes it possible for cold atoms to be imaged multiple times in a single cycle.
The quantum state of ultracold atoms is often determined through measurement of the spatial distribution of the atom cloud. Absorption imaging of the cloud is regularly used to extract this spatial information. Accurate determination of the parameters which describe the spatial distribution of the cloud is crucial to the success of many ultracold atom applications. In this work, we present modified deep learning image classification models for image regression. To overcome challenges in data collection, we train the model on simulated absorption images. We compare the performance of the deep learning models to least-squares techniques and show that the deep learning models achieve accuracy similar to least-squares, while consuming significantly less computation time. We compare the performance of models which take a single atom image against models which use an atom image plus other images that contain background information, and find that both models achieved similar accuracy. The use of single image models will enable single-exposure absorption imaging, which simplifies experiment design and eases imaging hardware requirements.
A novel home-built system for imaging cold atom samples is presented using a readily available astronomy camera which has the requisite sensitivity but no timing-control. We integrate the camera with LabVIEW achieving fast, low-jitter imaging with a convenient user-defined interface. We show that our system takes precisely timed millisecond exposures and offers significant improvements in terms of system jitter and readout time over previously reported home-built systems. Our system rivals current commercial "black box" systems in performance and user-friendliness.