NuMeriQS Projects

Investigating energy-device systems with computational methods requires large timescales and an accurate treatment of all the atomic interactions present, thus this project aims to develop methods that can efficiently yield accurate results for this purpose.

This project aims to achieve large-scale implementations of many-body electronic structure theories using automatic code generation. The developments aims at addressing a number of pressing issues in the Development of quantum chemical ab initio methods including legacy code, code of uncertain correctness, code of overwhelming complexity, and hardware adaptability.

This project aims to develop fast methods to quantify the uncertainty in properties of liquids predicted by computational chemistry methods like Molecular Dynamics (MD) simulations, Ab Initio MD (AIMD) simulations, and Quantum Cluster Equilibrium (QCE) calculations.

Quantum many-body systems as well as multiple other areas of physics heavily rely on discrete time evolution using so-called Trotterization techniques. This project aims to derive maximally precise Trotterizations at minimal computational cost.

The project aims to improve Ab initio molecular dynamics (AIMD) simulations and the analysis of their results for liquid systems in theoretical chemistry. The approach involves running multiple AIMD simulations simultaneously and using novel graph algorithms to exchange and analyze trajectory data.

Periodically driven quantum many-body systems are relevant for describing recent experiments in ultracold atom experiments and can be characterized by the structure of the eigenstates of the unitary generator of their dynamics.

The project aims to describe emergent phenomena in low-dimensional systems, such as graphene, nanoribbons, and nanotubes, which require strong-interaction techniques due to their highly non-linear electronic behavior. These systems exhibit exotic phenomena tied to their underlying topology, resulting in topological insulators and superconductors, with potential applications in topological quantum computing.

This project aims to develop an open-source software framework for efficient and scalable numerical simulations in Lattice Field Theory (LFT). It will address increasing complexity in LFT problems and adapt to evolving heterogeneous hardware platforms.

The project aims to investigate high-dimensional integration and quadrature methods for lattice field theories. Predicting the average value of an observable in a high-dimensional space is a challenging problem, typically addressed using Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) methods.

The project aims to improve theoretical predictions for hadron collider experiments like the LHC. Current computational complexities and lack of analytic solutions for the appearing integrals are among the main obstacles to achieving the precision required by the experiments.