XENONnT: Dark matter

Of all matter in our Universe, only about 5% consists of ‘ordinary matter’ as we commonly know it, built up from atoms. This is what all stars, planets and other visible materials are made up from. However, no less than 95% consists of dark energy (68%) and dark matter (27%).

Particle Physics

In particle physics, very large detectors are used to study elementary particles. Particles such as protons are accelerated in a particle accelerator, and made to collide with each other. The detectors record these collisions, which release a lot of energy to create new particles. Nikhef is active in ALICE, ATLAS and LHCb at CERN and eEDM in Groningen.

Astroparticle physics

Astroparticle physics combines physics and astronomy. In the cosmos, very strong magnetic fields create what can be considered a ‘natural’ particle accelerator. To perform astrophysics research, scientists ‘just’ need to build the right detectors. Nikhef is active in KM3NeT, Auger, XENON1T/nT and Virgo.

Mechanical technology

The Mechanical Technology (MT) department is made up of approximately 30 MBO-, HBO- and University schooled technical engineers. The main task of the department is to develop, design and realise mechanical solutions for the mostly international projects that Nikhef participates in.

Nikhef rules regarding visitors

At the moment Nikhef is open only to a limited extent due to precautionary measures taken to minimise the spread of the coronavirus. External visitors can only access the building by invitation and accompanied by a Nikhef employee.

Detector R&D

Theory

Nikhef’s Theoretical Physics group performs theoretical research on a wide range of fundamental topics in high-energy physics, ranging from particle and astroparticle physics to cosmology, gravitational waves and string theory.

Physics Data Processing

Advanced computing for physics and other sciences. Nikhef researchers are mainly developing increasingly better grid software, and transferring their grid knowledge, so that  scientists who are struggling with an ‘impossible’ data problem can profit from the grid.