6 citations · 17 across the 5 of their papers we have counts for
6 papers
TheoPhysEval: Assessing AI agents at autonomous theoretical physics problem solving
A. Ramesh Chandra, Aaghaz Mahajan, Ainesh Sanyal +32
We present a suite of 50 unpublished research-level theoretical physics problems with verifiable answers. Without AI assistance, a typical problem in our collection could be solved…
Surface wakes on ultra-soft solids
Aditi Chakrabarti, Divya Jaganathan, Robert Haussman +1
We explore the dynamical response of the free surface of an ultra-soft solid driven by a localized moving pressure disturbance. Experiments reveal a steady V-shaped wake analogous…
Basset-Boussinesq history force and inertia are relevant for unsteady particle settling dynamics
Tomek Jaroslawski, Divya Jaganathan, Rama Govindarajan +1
Our experiments on a sphere falling under gravity in Stokes flow show significant history effects. We observe an algebraic, not exponential, relaxation rate to the terminal velocit…
Trapping and extreme clustering of finitely-dense inertial particles near a rotating vortex pair
Saumav Kapoor, Divya Jaganathan, Rama Govindarajan
Small heavy particles cannot get attracted into a region of closed streamlines in a non-accelerating frame (Sapsis & Haller 2010). In a rotating system, however, particles can get…
Markovian Embedding of Nonlinear Memory via Spectral Representation
Divya Jaganathan, Rahil N. Valani
Differential equations containing memory terms that depend nonlinearly on past states model a variety of non-Markovian processes. In this study, we present a Markovian embedding pr…
Explicit Runge-Kutta algorithm to solve non-local equations with memory effects: case of the Maxey-Riley-Gatignol equation
Divya Jaganathan, Rama Govindarajan, Vishal Vasan
A standard approach to solve ordinary differential equations, when they describe dynamical systems, is to adopt a Runge-Kutta or related scheme. Such schemes, however, are not appl…