Projects

Choose among these 8 projects

Determining galaxy properties with PAUS using machine learning

Martin Børstad Eriksen, Malgorzata Siudek, Observational Cosmology group

PAUS is state-of-the-art ongoing galaxy survey, using a custom instrument with 40 narrow bands. This allows for high precision distance determination. These data are also expected to give novel insight into galaxy properties, e.g. type, as a function of cosmic time. The student will work on machine learning (ML) approaches, either unsupervised or supervised, to explore these data. The student will have the chance to learn about machine learning techniques and data handling. A solid background in programming is beneficial.


Number of students: 1

Place: IFAE




Gravitational Waves detection with the Virgo Interferometer

Mario Martinez, Lluïsa-Maria Mir, Gravitational Wave group

IFAE is a member of the VIRGO collaboration. This opens a new long-term research line in IFAE related to Gravitational Waves detection using terrestrial interferometry. A group of researches from IFAE has taken significant responsibilities in the VIRGO experiment related to the control of the stray light inside the experiment, which is considered a limiting factor for its sensitivity. In the physics analysis front, the IFAE team is developing a complete research program using LIGO/Virgo data for which a Deep Learning (DL) approach is being taken.

Project 1 Supervisor: Mario Martinez The candidate will have the opportunity to participate in the analysis of the data using a state-of-the-art DL approach together with the rest of the IFAE team.

Project 2 Supervisor: Lluisa Mir The candidate will be offered the opportunity to participate in the IFAE activities related to the construction of new detectors for Virgo, involving high-tech photosensors and sophisticated simulations of the propagation of light inside the interferometer.


Number of students: 2

Place: IFAE




Backend software for superconducting quantum computers

Pol Forn-Díaz, Quantum Computing group

Quantum algorithms consists of a set of instructions in the form of unitary operations that need to be applied to the qubits in a quantum computer. At the higher-level of a quantum programmer, these instructions are independent on the physical implementation of the quantum computer. Deep down in the hardware implementation level, the instructions become translated into physical processes taking place in the actual physical qubits. Such translation unavoidably depends on the physical system that implements a quantum computer. In our group, we operate superconducting quantum circuits. Superconducting qubits are electrical circuits behaving as artifical atoms which resonate at the microwave frequency domain. Qubit operations correspond to microwave engineered pulses which rotate the qubit state at will. In this project, the candidate will develop a software interface, also known as backend, to transform the instructions from quantum algorithms, developed by the quantum software team, into microwave pulses to control an actual experiment in our laboratory.


Number of students: 1

Place: IFAE




Particle Physics Simulations

Pere Masjuan, Theory group

The students will develop computer simulations of high energy phenomena using Python programming. Concepts such as decay amplitudes and branching ratios will be learnt and explored systematically in the context of Quantum Field Theory to yield a consistent programmable picture.

Within this approach, there are a number of different projects that can be developed depending on the student’s interests.


Number of students: 2

Place: IFAE




High Energy Astrophysics with the MAGIC Telescopes

Abelardo Moralejo, Gamma Ray group

The MAGIC telescopes explore the most violent phenomena of the Universe through the study of Very High Energy gamma rays, the most energetic known form of electromagnetic radiation. They are produced in the most violent, non-thermal cosmic environments and their study helps us address fundamental questions such as the nature of dark matter, the intensity and evolution of the extragalactic background light, the quantum nature of Gravity or the origin of Galactic cosmic rays.

The IFAE Astroparticles group is very active in the in the physics exploitation of the MAGIC data. The students selected will be able to participate in the analysis of MAGIC observational data.


Number of students: 2

Place: IFAE




Particle Physics with the ATLAS Experiment @ the LHC

Martine Bosman, ATLAS group

The student will work in the IFAE ATLAS group in topics such as:

  1. Search for vector-like quarks decaying to top quarks and Higgs or Z bosons with the full Run-2 dataset. The student will investigate potential improvements to the search that can be obtained through the use of track jets for the purpose of identifying jets originating from b-quarks.
  2. Development of deep neural network for the search of Dark Matter at the LHC.


Number of students: 1

Place: IFAE




Characterization of Pixel Detectors

Sebastián Grinstein, ATLAS Pixels group

Highly segmented silicon sensors are widely used in High Energy Physics as precision tracking devices. Upgrades of the CERN experiments to high luminosities set unprecedented requirements with respect to radiation hardness and require the development of new generations of silicon detectors. The student will work at the IFAE Pixel Lab to help gain a deep understanding of the charge collection and the underlying signal formation in the silicon sensors.


Number of students: 1

Place: IFAE Pixel Lab




Feasibility study of using Big Data platform to analyze MAGIC telescope gamma-ray data

Prof. Manuel Delfino, Port d'Informació Científica (PIC)

MAGIC has been observing the gamma-ray sky for 15 years, and will continue for at least the next five, while the new generation Cherenkov Telescope Array (CTA) is built. When MAGIC was designed, terms like Big Data or Cloud Computing didn't exist. But they do now, and provide powerful tools such as the Cosmohub platform at the Port d'Informació Científica (PIC), a joint undertaking by IFAE and CIEMAT located on the UAB campus. Students in the summer fellowship program will have the opportunity to learn how a MAGIC science analysis is done using the standard MARS analysis tools, learn how Big Data tools have been used to build Cosmohub, and then contribute to a feasibility study on whether Cosmohub can be adapted to execute MAGIC analysis in a more powerful manner.


Number of students: 1

Place: PIC