Rama SharmaSwinburne University of Technology · Centre for Quantum and Optical Sciences
Rama Sharma
Research scholar
About
7
Publications
99
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9
Citations
Introduction
Quantum turbulence— characterise as the chaotic motion of quantised vortices (swirls) in superfluids. Exploring such highly non-equilibrium physics of systems governed by quantum mechanics will find applications ranging from problems in elementary physics to implement of future quantum technologies.
Our research is focused on understanding the microscopic behaviour underlying quantum turbulence, with a particular focus on superfluid BECs in which vortices are restricted to move in 2D space.
Additional affiliations
August 2011 - January 2017
Berhampore Girls' College
Position
- Lecturer
Education
July 2017 - June 2019
Publications
Publications (7)
The second law of thermodynamics posits that in closed macroscopic systems the rate of entropy production must be positive. However, small systems can exhibit negative entropy production over short timescales, seemingly in contradiction with this law. The fluctuation theorem quantitatively connects these two limits, predicting that entropy-producin...
The second law of thermodynamics posits that in closed macroscopic systems the rate of entropy production must be positive. However, small systems can exhibit negative entropy production over short timescales, seemingly in contradiction with this law. The fluctuation theorem quantitatively connects these two limits, predicting that entropy producin...
According to second law of thermodynamics the entropy production rate is always positive for large systems over long time scales. However, the fluctuation theorem (FT) allows observable violations of the second law in finite size systems. We have computationally studied the FT predictions as a function of the system temperature, in the context of a...
We
consider computer generated configurations of quantised vortices in planar
superfluid Bose Einstein condensates We show that unsupervised machine
learning technology can successfully be used for classifying such vortex
configurations to identify prominent vortex phases of matter 1 The machine
learning approach could thus be applied for automatic...
We consider computer-generated configurations of quantized vortices in planar superfluid Bose-Einstein condensates. We show that unsupervised machine-learning technology can successfully be used for classifying such vortex configurations to identify prominent vortex phases of matter. The machine-learning approach could thus be applied for automatic...
A facility for performing serial crystallography measurements has been developed at the Australian synchrotron. This facility incorporates a purpose built high viscous injector, Lipidico, as part of the macromolecular crystallography (MX2) beamline to measure large numbers of small crystals at room temperature. The goal of this technique is to enab...
