5 citations · 5 across the 1 of their papers we have counts for
6 papers
Machine-learning Iterative Calculation of Entropy for Physical Systems
Amit Nir, Eran Sela, Roy Beck +1
Characterizing the entropy of a system is a crucial, and often computationally costly, step in understanding its thermodynamics. It plays a key role in the study of phase transitio…
Thermal conductance of one dimensional disordered harmonic chains
Biswarup Ash, Ariel Amir, Yohai Bar-Sinai +2
We study heat conduction mediated by longitudinal phonons in one dimensional disordered harmonic chains. Using scaling properties of the phonon density of states and localization i…
Spatiotemporal dynamics of frictional systems: The interplay of interfacial friction and bulk elasticity
Yohai Bar-Sinai, Michael Aldam, Robert Spatschek +2
Frictional interfaces are abundant in natural and engineering systems, and predicting their behavior still poses challenges of prime scientific and technological importance. At the…
Learning data driven discretizations for partial differential equations
Yohai Bar-Sinai, Stephan Hoyer, Jason Hickey +1
The numerical solution of partial differential equations (PDEs) is challenging because of the need to resolve spatiotemporal features over wide length and timescales. Often, it is…
Machine Learning in a data-limited regime: Augmenting experiments with synthetic data uncovers order in crumpled sheets
Jordan Hoffmann, Yohai Bar-Sinai, Lisa Lee +4
Machine learning has gained widespread attention as a powerful tool to identify structure in complex, high-dimensional data. However, these techniques are ostensibly inapplicable f…
On the spatial distribution of thermal energy in equilibrium
Yohai Bar-Sinai, Eran Bouchbinder
The equipartition theorem states that in equilibrium thermal energy is equally distributed among uncoupled degrees of freedom which appear quadratically in the system's Hamiltonian…