A3D3 Seminar: Deep Chatterjee

Monday 20 Apr 2026, 12:00 → 13:00 US/Pacific

Title: Realtime search and characterization of binary black holes in LVK data using AI

 

Abstract: 

The number of GW events have increased from two real-time detections in the LIGO first observing run, to over two hundred in the LIGO-Virgo-KAGRA fourth observing run. In parallel, the last decade has also seen the increased use of machine learning, especially neural networks, in science. For the first time, after a decade of discovery, binary black holes (BBHs) are routinely detected by neural-networks as a part of the LVK data analysis. In the LVK fourth observing run, a total of 23 BBH events were detected in real-time by neural-network based search, Aframe, between its late-August deployment and end of observing in mid-November 2025. Sky-localization and chirp mass estimates were distributed in low latency using neural network based parameter estimation algorithm AMPLFI. I will be talking about Aframe and AMPLFI with a view toward a new paradigm of doing low latency GW science using AI.

 

This is a final year seminar from the A3D3 MMA group highlighting their achievements over the past five years.

 

The A3D3 Seminar is a monthly lecture series that hosts scholars working across applied areas of artificial intelligence, such as hardware algorithm co-development, high energy physics, multi-messenger astrophysics,  and neuroscience. Our presenters come from all four domain fields and include occasional external speakers beyond the A3D3 science areas, governmental agencies and industry. The seminar will be recorded and published in YouTube. To receive future event updates, subscribe here.