BB.20.007 – Discovering new phenomena by bridging the gap between simulation and reality

Route: Building blocks of matter and fundaments of space and time

Cluster question: 128 Have we identified all the elementary particles of matter?

Have we identified all elementary particles? What is Dark Matter? How can we use big data to generate insights? These NWA questions are addressed in this proposal.
The goal of our project is to systematically improve the ability to identify and close gaps between simulations and reality. To this end, we are forming a consortium of physicists and experts from the fields of data science, high performance computing and industry.

The Standard Model (SM) is currently our best theory to describe the building blocks of physical reality. Despite its overwhelming successes, the SM cannot e.g. describe gravity at the quantum level, account for Dark Matter, or describe the absence of antimatter in our Universe. Despite extensive efforts, no unambiguous signals for new phenomena beyond the SM have been identified. Perhaps the problem lies in our search strategy?

While the SM is based on beautiful mathematics, producing predictions for physical phenomena is in practice extremely challenging.
Our best modelling tools are sophisticated computer simulations, and the ongoing quest for new phenomena can be understood as a systematic search for ‘gaps’ between reality and simulations. Such gaps can manifest themselves in outliers and anomalies, such as colliders producing unexpected particles that are not present in the simulation. Due to limitations of the simulations and the complexity of the data, a systematic search for anomalies can often not be carried out.
To overcome these limitations, we combine physics (from effective field theories to generalized modelling of Dark Matter), with data science (generative models) and scientific computing (HPC, differentiable programming). Urgent applications within the Dutch industry are found e.g. in fraud detection, VR, customer behaviour informatics, and performance modelling for (payment) infrastructures. We aim to join forces by building an open consortium to identify and bridge the gap between simulations and reality.


Astroparticle physics, Data Science, Particle Physics, Simulations

Other organisations

Hogeschool NHL Stenden, Netherlands escience center, NeuroReality, NIKHEF, other (e.g. Industry) partners welcome, Radboud Universiteit Nijmegen (RU), surfsara, UvA


Organisation Radboud University Nijmegen (RU)
Name Dr. S. (Sasha) Caron
Website (not yet)