Master Theses 2021/2022

Master Theses offered by CIEMAT-CFP Members for the academic year 2021/2022

1. Search for Beyond Standard Model Physics with the SBND experiment at Fermilab

The neutrino masses and their large different value from the rest of the elementary particles constitute the strongest hint of the existence of physics beyond the Standard Model. The SBND experiment, a liquid argon time projection chamber located just 110 m downstream from the origin of the Booster Neutrino Beam (BNB) at Fermilab (Illinois, USA), has as one of its goals the search for New Physics. In this Master Thesis, the sensitivity of SBND to different extensions of the Standard Model will be studied.

Supervisor: Dr. José I. Crespo-Anadón (CIEMAT) (

2. Optimization of the scintillation light detection in the DUNE neutrino oscillation experiment

The DUNE neutrino experiment in Fermilab (USA), whose main goal is to measure the CPsymmetry violation in the leptonic sector, is composed of liquid argon TPC detectors exposed to
neutrino beams. The CIEMAT neutrino group participates in the design and characterization of the scintillation light detection system of this detector, consisting in light collector modules called XARAPUCAs. Functionally, these modules are light traps that convert VUV photons (127 nm) to longer wavelengths and guide them towards silicon photosensors, where they are detected and converted into an electric signal. The tasks proposed in this Master project include the measurement of the X-ARAPUCA photon-detection efficiency at the CIEMAT lab, as well as the simulation of their response to study their expected performance in the detector.

Supervisors: Dr. Inés Gil (CIEMAT) (, Dr. Clara Cuesta (CIEMAT) (

3. LiquidO: A Novel Neutrino Technology

The unknowns in neutrino physics demand huge detectors (>kton), with high energy resolution and accurate particle identification. A simple and not costly detector fulfilling these requirements would be a game-changer in neutrino physics. LiquidO is an R+D project for the development of a new neutrino detection technology which uses opaque liquid scintillator, like milk or paraffin. This new technology represents a breakthrough with respect to the traditional neutrino detection with liquid scintillator, essential for future neutrino physics experiments. The tasks proposed in this End-of-Master project cover the development of simulations and the data analysis of a prototype that is currently taking data. LiquidO is an international collaboration that includes research institutes and universities from France, Italy and Japan.

Supervisor: Dr. Carmen Palomares (CIEMAT) (

4. Study of the associated production of a W vector boson and two jets originated from a c quark in proton-proton collisions at sqrt(s)=13TeV with data from the CMS experiment at the CERN LHC.

This is a high precision measurement in the context of the standard model of particle physics. The characterization of these processes is also critical to understand one of the most relevant backgrounds to the study of the Higgs boson properties in its decay channels into a pair of heavy flavour quarks (H --> bb, H --> cc). There remains a possible extension to the associated production of a W vector boson and two b jets.

Supervisors: Dr. Juan Pablo Fernández (CIEMAT) ( ), Dr. Isabel Josa (CIEMAT) ( )

5. Search for new physics in Higgs studies at future e+e- colliders

Is the Higgs an elementary or a composite particle? What is behind the symmetry breaking mechanism predicted by the standard model (SM)? The highest priority objective of High Energy Physics at present is the detailed study of this scalar sector of the SM, and in particular the search for deviations indicating the path towards new interactions and particles completing it. In this work we will develop analyses based on event simulations at future electron-positron colliders, still in a conceptual/development phase. These analyses will enable us to estimate and optimize the sensitivity to various effects beyond the SM.

Supervisor: Dr. Juan Alcaraz (CIEMAT) (

6. Search for QED deviations in future e+e- colliders

Quantum electrodynamics (QED) is one of the presently best studied theories at the level of precision, although a good fraction of these studies are dominated by uncertainties due to quantum chromodynamics (QCD). A future electron-positron collider at energies of the order of teraelectron volts (TeV) will allow the search for deviations in processes minimally sensitive to QCD, as simple as e+e--> gamma gamma, sensitive to interactions and particles that may exist at the scale of tens of TeV. In this work will develop analyses based on event simulations at future electron-positron colliders, still in a conceptual/development phase. These analyses will provide estimates for the potential detection of new physics effects, as well as limits in the absence of those effects.

Supervisor: Dr. Juan Alcaraz (CIEMAT) (

7. High-level data analysis with the MAGIC and LST1 telescopes.

Very high energy photons have become an essential tool for astrophysics and fundamental physics, studying the non-thermal universe. Over the last two decades, Cherenkov telescopes such as MAGIC have proven capable of producing high-impact scientific results. In fact, the new generation of these telescopes is on its way: the Cherenkov Telescope Array (CTA) will be made up of two observatories, one in each hemisphere, one being located next to MAGIC at the Roque de los Muchachos Observatory. The LST1 prototype is currently being validated as CTA's first telescope. In this project we propose the student to become familiar with high-level analysis of both MAGIC and LST data, and to use these data to compare the capabilities of both instruments and verify that the results are consistent with each other.

Supervisor: Dr. Tarek Hassan Collado (CIEMAT) ( )

8. Robust neural networks against data poisoning applied to the problem of discrimination of neck events in DEAP-3600.

Adversary attacks cause neural networks to lose performance. Injecting a little noise into the image or hiding parts of the image leads to a great degradation of the prediction quality generated by the neural network, even though the evaluation by humans remains unchanged. The alteration of the input data can be done with a great variety of modifications and be due to multiple causes. Globally, these altered data are termed poisoned data.

Building robust models against poisoned data injection can help in DEAP-3600 experiment and other particle physics projects. As long as the observations are subject to systematic uncertainty, neural networks must create defense mechanisms against the variability of the values taken by the independent variables.

Thus, it is proposed to study the defense and attack mechanisms proposed in the scientific literature, and apply them to the problem of separation of background and signal in DEAP-3600.

Supervisors: Dr. Miguel Cárdenas (CIEMAT), Dr. Vicente Pesudo (CIEMAT) - (