Sparse identification of nonlinear dynamical systems is an important project, directly addressing the physics community’s long-standing goal of data-driven discovery. Although many effective methods ...

Abstract: Hodge theory provides a unifying view of the various line, surface, and volume integrals that appear in physics and engineering applications. Hodge theory on graphs develops discrete ...

Derived types that mimic vector and tensor fields and Differential and integral operators for writing vector and tensor expressions. Formal's types and operators implement the discrete calculus of ...

This repository contains an implementation of symmetry-adapted Gaussian Process Regression suitable to perform equivariant learning and prediction of the electron density of molecular and ...

As standard microelectronic technology approaches fundamental limitations in speed and power consumption, novel computing strategies are strongly needed. Analogue optical computing enables the ...

Proportional–integral vector control (PIVC) has been proposed as an effective control strategy for modular multi-level converter (MMC) under balanced grid conditions. However, the PIVC using ...

We present two fiberized vector magnetic-field sensors, based on nitrogen-vacancy (NV) centers in diamond. The sensors feature sub-nT/ magnetic sensitivity. We use commercially available components to ...

Quantum simulators promise to offer new insights into strongly correlated matter beyond what is accessible by means of classical computers. We propose dynamical quantum simulators (DQSs) as a method ...

Diffraction is a classic optical phenomenon accounting for the propagation of light waves. The efficient calculation of light diffraction is of significant value toward the real-time prediction of ...

U of T computer vision expert to lead new Nvidia research lab in Toronto Sanja Fidler, an expert in computer vision and applied machine learning, is the latest U of T researcher to be tapped to run a ...