Searches for new gauge bosons and dark matter with data from the LHC at CERN

Unravel the mysteries of the Universe using data from the world’s biggest and most powerful accelerator, The Large Hadron Collider, at CERN. With billions of high energy proton-proton collisions recorded by the ATLAS detector between 2015 - 2026 you can search for the evidence of new particles and phenomena to help on the understanding of today’s biggest mystery of the Universe: what constitutes Dark Matter, measured to make up 85% of all the matter in our Universe!

The Standard Model (SM) of particle physics is an extremely successful theory which several times over the past decades has predicted the existence of new particles or phenomena, which later have been discovered in experiments. The SM also explains, to unprecedented precision, many experimental observations. However, it has some clear known shortcomings, one of them being that it does not contain a viable dark matter (DM) candidate. This suggests that there must be a more complete theory beyond the SM.

Several extensions of the SM predict the existence of new fundamental forces, mediated by new heavy gauge bosons often referred to as Z’ and W’, analogous to the Z and W bosons in the SM. Theories predicting the existence of new heavy gauge bosons are often motivated by ideas like Grand Unification of the fundamental forces or restoration of parity (left-right) symmetry in weak interactions. Additionally, new gauge bosons may act as mediators between the SM particles and so-called “dark sectors” that do not interact via the SM forces. A discovery of new gauge bosons could therefore potentially shed light on the nature of DM.

The ATLAS group in the High Energy Physics (HEP) section has particular expertise in searches for new gauge bosons in the detector final-state with leptons, possibly together with additional objects like missing transverse energy (MET) or jets. In terms of analysis methodology, there are several different options (see below) which you may choose depending on your interests, but broadly you will work within one of the following scenarios:

a) Search for a Z’ in the dilepton final state. The primary aim of the analysis is searching for a bump in the distribution of invariant masses of dileptons. A key part of the analysis is modelling of the background spectrum, using MC simulations and/or data-driven methods.

b) Search for a Z’ and DM in the dilepton+MET final state.

You will search for processes where a Z’ is produced in association with DM, leading to a detector final-state with two leptons (from the Z’) and MET (from the DM particles).

c) Search for a W’ in the lepton+MET final state.

The W’ is assumed to decay to a lepton and a neutrino. Due to the neutrino the signal is less prominent than in the resonance structure expected for a Z’. The distorted resonance shape is known as a Jacobian peak and, instead of the invariant mass, you will deal with the transverse mass built from the measured lepton and MET.

d) Search for a W’ and Majorana neutrinos in the dilepton+MET+jets final state. You will search for processes where a Majorana neutrino is produced in association with the W’, leading to final-states with two leptons, two jets and MET. In this scenario, the SM background is expected to be very small as the two leptons in the final state have the same electric charge, in contrast to the Z’ models above.

The MSc topics can be related to development of new techniques to efficiently separate the relevant signals from a larger background of events from SM processes using e.g. artificial intelligence and machine learning. We also offer more theoretical topics on phenomenological aspects of the relevant signal models, trying to identify new models and scenarios, which could be searched for at the LHC, and that fits with current experimental, astronomical and cosmological constraints. Regardless of the specificity of the model or topic under study the MSc project will contain several common milestones, which might get more or less weight depending on your interests:

M1: Study relevant signal models that can be explored at the LHC and/or identify uncovered regions that could be interesting to study further.

M2: Identify which particles, of the ones we can measure in ATLAS, will be important for your study.

M3: Identify the backgrounds, i.e. known processes that will produce the same particles as your signal model.

M4: By using provided simulations of signal and background, develop novel analysis techniques/ideas to efficiently separate signal from background.

M5: Make sure the simulated background and real data recorded by ATLAS fit well in some dedicated control regions to ensure that we can trust the analysis.

M6: Apply your techniques/ideas on the real data in regions where you expect signals to be present.

M7: Do a statistical analysis of your results to compare with other methods and possibly prove or exclude the existence of new particles.

 

Courses relevant from the bachelor's degree:

STK-FYS1110 – Probability, modeling and data analysis for the physical subjects

FYS2150 – Experimental Physics

FYS3140 – Mathematical Methods in Physics

FYS3150 – Computational Physics

FYS3500 – Introduction to Nuclear and Particle Physics

FYS-STK3155 – Applied Data Analysis and Machine Learning

 

Recommended courses for theoretical curriculum in the master's programme:

(Mandatory for the project):

FYS4505 – Methods and Instrumentation for Nuclear and Particle Physics

FYS4555 – Particle Physics

FYS5555 – Research-Based Particle Physics

(Other relevant courses):

FYS4150 – Computational Physics

FYS4170 – Relativistic Quantum Field Theory

FYS4411 – Computational Physics II: Quantum Mechanical Systems (discontinued)

FYS4900

FYS5190 – Supersymmetry

FYS5429 – Advanced machine learning and data analysis for the physical sciences

If not taken during bachelor:

FYS4150 – Computational Physics

FYS-STK4155 – Applied Data Analysis and Machine Learning

Published Sep. 10, 2026 11:48 AM - Last modified Sep. 10, 2026 11:48 AM

Supervisor(s)

Scope (credits)

60