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Soma Mukherjee

Researcher at University of Texas at Austin

Publications -  280
Citations -  72580

Soma Mukherjee is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: LIGO & Gravitational wave. The author has an hindex of 95, co-authored 266 publications receiving 59549 citations. Previous affiliations of Soma Mukherjee include The University of Texas Rio Grande Valley & Saha Institute of Nuclear Physics.

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Preliminary results from the hierarchical glitch pipeline

TL;DR: In this paper, the hierarchical glitch classification pipeline on LIGO data has been tested and is now complete and end-to-end tested, and the results obtained with one days analysis on the gravitational wave and several auxiliary and environmental channels from all three LIGA detectors are discussed.
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Erratum: Beating the spin-down limit on gravitational wave emission from the crab pulsar (Astrophysical Journal (2008) 683 (L45))

B. P. Abbott, +453 more
TL;DR: A processing error in the signal template used in this search led to upper limits about 30% lower than we now know is warranted by the early S5 data as discussed by the authors, and the multitemplate search was not affected by the error.
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Model-based Cross-correlation Search for Gravitational Waves from the Low-mass X-Ray Binary Scorpius X-1 in LIGO O3 Data

The Ligo Scientific Collaboration, +1677 more
TL;DR: In this paper , the authors present the results of a model-based search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO detector data from the third observing run of Advanced LIGA and Advanced Virgo.
Posted Content

Enhancing the Sensitivity of Searches for Gravitational Waves from Core-Collapse Supernovae with a Bayesian classification of candidate events

TL;DR: In this article, a morphological veto involving Bayesian statistics was used to improve the receiver-operating characteristic (ROC) curves of the current search for core-collapse supernovae (CCSNe) as implemented by the coherent Waveburst (cWB) algorithm.
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Multidimensional classification of kleineWelle triggers from LIGO science run

TL;DR: In this article, multidimensional classification analysis is performed on burst triggers generated by event trigger generating algorithms such as the kleineWelle algorithm in LIGO's fifth science run data.