Scientists developed a new technology by studying extremely cold or absolute zero temperatures
Scientists have developed a new image-enhancement technique that enables better images when studying atoms at ultracold or absolute zero temperatures. This technique can get rid of up to 50 percent of unwanted interference limitations in images that are important for better understanding the properties controlled by the complex quantum mechanics of atoms at cold temperatures. At low temperatures near absolute zero, the basic properties of atoms based on classical mechanics change and are then governed by the laws of quantum mechanics. In this condition they have the potential to study atomic properties at such low temperatures and provide the possibility of understanding them better.
A commonly used technique for studying ultracold atoms is to use magneto-optical traps combined with high-power laser cooling techniques. Generally cold atoms of elements like sodium, potassium, rubidium are studied. For this, detection techniques, namely fluorescence, absorption or phase-contrast imaging techniques are used. Among these, imaging through fluorescence or absorption techniques is also widely used.
However, images obtained using these techniques are often spoiled by unwanted interference fringes, which form unwanted dark-bright patterns on the actual images and reduce the quality of the results obtained. She goes. The presence of unwanted interference boundaries has the potential to derail accurate calculations of important parameters – atomic number, temperature, dynamics in small time scales, etc. To address this interference problem, a research group at the Raman Research Institute (RRI), an autonomous institute of the Department of Science and Technology, has developed an image-correction solution.
The newly developed algorithm is based on existing eigen-face recognition as well as smart masking techniques, which aims to obtain images with minimal interference fringes. This eigen-face recognition is similar to finding the correct image of a person or object from a set of images based on the features of the objects. Our cell phones use this as the base technology, although modern smartphones have modified it with additional machine-learning based technology to improve this feature, but the fundamental concept remains the same.
Gaurav Pal, a PhD student in the QMIX Lab at the Raman Research Institute (RRI), said, “When working with soft atoms it is essential to calculate the optical density (OD), which takes into account any temperature, size, density and other factors.” Can determine useful parameters.
