PhD Student at IUCAA
I am primarily interested in characterization and reduction of noise in gravitational wave detectors. Newtonian gravity gradient noise is one among them which affects the low frequency (10-30 Hz) sensitivity of Advanced LIGO like detectors. It arises mainly from surface Rayleigh waves along with contributions from body waves, anthropogenic and machinery sources which in general make the actual seismic field inhomogeneous and anisotropic. We are involved in developing realistic estimates of this fundamental noise using the measured seismic spectra obtained using optimally configured sensor arrays. We are also interested in applying machine learning and neural networks for noise detection and subsequent removal from various LIGO channels. One such technique involves using adaptive noise cancellation which combines data from various physical environment monitoring channels to perform coherent feed forward cancellation of correlated noise in various LIGO subsystems. This will help in the removal of certain broadband noise as well as non-astrophysical transient events which affect the sensitivity of GW detectors. Our work is focused on gaining expertise in real-time adaptive noise removal techniques both in hardware and software, so that it will be useful in Advanced LIGO as well as the proposed LIGO-India detector.