We present an efficient solver for massively-parallel direct numerical simulations of incompressible turbulent flows.

Fluid Dynamics

Quantum computing's transition from theory to reality has spurred the need for novel software tools to manage the increasing complexity, sophistication, toil, and fallibility of quantum algorithm development.

Quantum Physics Programming Languages

In this proceedings, we present two new quantum circuit simulation protocols recently added as optional backends to Qibo, an open-source framework for quantum simulation, hardware control and calibration.

Quantum Physics Computational Physics

Density functional theory (DFT) has been a cornerstone in computational chemistry, physics, and materials science for decades, benefiting from advancements in computational power and theoretical methods.

Chemical Physics

Machine learning is rapidly becoming an integral part of experimental physical discovery via automated and high-throughput synthesis, and active experiments in scattering and electron/probe microscopy.

Materials Science Data Analysis, Statistics and Probability

Moreover, we have included models for non-constant relaxation time in electronic transport calculations, doubling the real space dimensions of the Hamiltonian as well as the construction of Hamiltonians directly from analytical models.

Materials Science

A complete treatment of the intersections of two geodesics on the surface of an ellipsoid of revolution is given.

Geophysics

We describe how to apply adjoint sensitivity methods to backward Monte-Carlo schemes arising from simulations of particles passing through matter.

Computational Physics Data Analysis, Statistics and Probability

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering.

Computational Physics

The marriage of density functional theory (DFT) and deep learning methods has the potential to revolutionize modern computational materials science.

Materials Science Disordered Systems and Neural Networks Mesoscale and Nanoscale Physics Computational Physics Quantum Physics