Conveners
Morning Talks
- Mihoko Nojiri (IPNS, KEK)
Morning Talks
- Tianji Cai (SLAC)
Morning Talks
- Vinicius Mikuni (NERSC, Berkeley Lab)
Recent advances in machine learning (ML), particularly neural density estimation like normalizing flows, diffusion models, and flow matching, have opened new doors for high-precision, model-independent density estimation. These techniques are highly valuable for galactic dynamics studies, as they allow us to estimate the distribution of stars in phase space (position and velocity) without...
Gravitational Wave (GW) Physics has entered a new Multi-Messenger Astronomy (MMA) era, marked by increasing detections from GW observatories led by LIGO, Virgo, and KAGRA collaborations. This presentation will introduce the KAGRA experiment and explore the transformative role of machine learning (ML) in GW data analysis — some successful ML key applications, among which glitch identification,...
In physics, while analytical calculations remain appealing, there are situations where the use of computers becomes indispensable. A straightforward example is the three-body problem, where even the interactions of just three bodies are challenging to solve analytically. This necessity is similarly evident in studies of the early universe. Understanding the dynamics of the inflaton requires...
