19 citations · 72 across the 6 of their papers we have counts for
6 papers
Prolate spheroidal wave functions enable fast and exponent-aware long-range machine learning interatomic potentials
Jiuyang Liang, Libin Lu, Yajie Ji +1
Long-range interactions such as electrostatics and dispersion remain a central bottleneck for machine learning interatomic potentials (MLIPs), especially in ionic, polar and interf…
pmwd: A Differentiable Cosmological Particle-Mesh -body Library
Yin Li, Libin Lu, Chirag Modi +7
The formation of the large-scale structure, the evolution and distribution of galaxies, quasars, and dark matter on cosmological scales, requires numerical simulations. Differentia…
Differentiable Cosmological Simulation with Adjoint Method
Yin Li, Chirag Modi, Drew Jamieson +5
Rapid advances in deep learning have brought not only myriad powerful neural networks, but also breakthroughs that benefit established scientific research. In particular, automatic…
Scalable Simulation of Realistic Volume Fraction Red Blood Cell Flows through Vascular Networks
Libin Lu, Matthew J. Morse, Abtin Rahimian +2
High-resolution blood flow simulations have potential for developing better understanding biophysical phenomena at the microscale, such as vasodilation, vasoconstriction and overal…
Parallel contact-aware simulations of deformable particles in 3D Stokes flow
Libin Lu, Abtin Rahimian, Denis Zorin
We present a parallel-scalable method for simulating non-dilute suspensions of deformable particles immersed in Stokesian fluid in three dimensions. A critical component in these s…
Contact-aware simulations of particulate Stokesian suspensions
Libin Lu, Abtin Rahimian, Denis Zorin
We present an efficient, accurate, and robust method for simulation of dense suspensions of deformable and rigid particles immersed in Stokesian fluid in two dimensions. We use a w…