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New Insights on Binary Black Holes

URI researchers make extensive use of the Unity Cluster housed at MGHPCC in their work relating to the coalescence of binary black hole systems using perturbation theory and estimation of the properties of the emitted gravitational radiation.

Using advanced computer simulations, Gaurav Khanna with postdoc Tousif Islam and others studied how two orbiting black holes merge, focusing on a key aspect of Einstein's theory of relativity: the "late-time tail" behavior in the gravitational waves they produce. The pair found that as the black holes' orbits become more elongated, these late-time signals become stronger. The way these signals decay over time follows a specific pattern we expected. In the course of their work, the researchers also created a free Python tool called "gwtails" to analyze this data and have shared some of their results so others can verify our findings.

A recent paper "Phenomenology and origin of late-time tails in eccentric binary black hole mergers" by Tousif Islam and co-authors investigates the gravitational wave signals emitted during eccentric binary black hole mergers, showing that late-time tails—slowly decaying waveforms—are significantly enhanced by orbital eccentricity and originate primarily when the smaller black hole passes near apocenter, rather than from strong-field effects near the larger black hole.

Gaurav Khanna
Professor in the Department of Physics and the Director of Research Computing at URI

Research projects

A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Asteroid Data Mining
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Computation + Machine Intelligence | Wu Tsai Institute
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
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