The Centre de Physique des Particules de Marseille is a Joint Research Unit (UMR 7346) supervised by the CNRS and Aix Marseille University.

The research conducted at CPPM is at the crossroads of two infinites - the infinitely small and the infinitely large - from the study of the elementary components of matter to the exploration of the cosmos. Most of our research is carried out in leading international collaborations, and our contributions are recognized worldwide. We participate in the training of young people in research and through research, in university teaching, and in the valorization of our results.

In the wake of recent changes in research funding methods (calls for proposals, Research Infrastructures, increased surveys and evaluations, promotion of international collaborations), the CPPM now wishes to define a long-term strategy for the development of its international relations, in order to perpetuate promising current collaborations and foster new collaborations with emerging laboratories and researchers.

All the CPPM's activities are based on ethical values, deontology and integrity, with a focus on science and society. The CPPM is committed to conducting research within the framework of open science, promoting diversity and inclusion in the workplace, and preserving the environment.

The last piece of the standard model of particle physics, the Higgs boson, was discovered by the ATLAS and CMS collaborations in 2012. The newly discovered boson provides a unique possibility to search for new unknown physics beyond the Standard Model. The ATLAS group at CPPM have a leading role in detecting and studying the Higgs boson properties in several of its production and decay modes. The group is currently concentrating on the detection of the production of two Higgs bosons or two scalar bosons, a process that was never observed before.

This internship will concentrate on the study of the production of two Higgs bosons decaying to a pair of photons and a pair or b-quarks (HH->bbyy). The detection of such process is a strong proof of the Higgs self coupling and the electroweak symmetry breaking as described by the standard model. The run 3 of the LHC, currently in operation, will provide enough data (in combination with previous data) to improve the discovery potential of such process. The analysis of the run 3 data is being prepared now by a group of several institutes around the world that collaborate at CERN. The analysis will look for the HH production as described by the Standard Model as well as with beyond the Standard Model models where the Higgs self coupling is modified or where new heavy scalar particles exist and decay to a pair of Higgs bosons.

The successful candidate will work within a team of four researchers and two PhD student at CPPM. He/She will analyze the kinematic and topological distributions of the signal in order to improve the selection of signal events and separate them from the background.

Prior knowledge of programming language especially C++/root or python is an advantage but is not mandatory.

The ATLAS (http://atlas.cern) and CMS collaborations at the LHC have celebrated this year the 10th anniversary of the Higgs boson discovery, which led to a Nobel Prize for F. Englert and P. Higgs in 2013. LHC has started this year its new Run 3 data-taking period, which will allow to collect a lot of new data, in order to better characterize the Higgs boson and to possibly find evidences of new physics beyond the Standard Model. However, in order to increase by a factor 100 the amount of useful data we already have, the LHC and its detectors will be upgraded for the High-Luminosity phase of LHC (HL-LHC, 2029-2040). The ATLAS group at CPPM, building on its previous expertise, is developing a new pixel detector and the corresponding reconstruction algorithms to this end.

This high-tech detector plays a fundamental role to measure the trajectories of charged particles and to identify jets of particles stemming from the hadronization of bottom quarks. This ability, also known as b-tagging, is instrumental to the success of the ATLAS and LHC physics program and has played a major role in the past observation of the associated production mode of a Higgs boson with top quarks and in the search for the production of a pair of Higgs bosons. Recent b-tagging algorithms based on Deep-Learning techniques have already demonstrated sizeable improvements with the current Run 3 ATLAS detector and are therefore investigated also for HL-LHC.

The student will use detailed Monte-Carlo simulations to assess the b-tagging performance associated with the most recent detector simulation and investigate potential improvements for those. The project provides an opportunity for the student to get an exposure to a broad spectrum of topics: LHC physics notably the Higgs sector; basics of silicon detectors, track-finding and pattern-recognition; b-tagging algorithms based on Deep-Learning techniques. The project requires the use of existing analysis frameworks and plotting scripts, mostly based on Python. The prior knowledge of this language is desirable but not mandatory.

The last piece of the Standard Model of particle physics, the Higgs boson, was discovered by the ATLAS and CMS collaborations in 2012. The newly discovered boson provides a unique opportunity to search for unknown physics beyond the Standard Model. The ATLAS group at CPPM had a leading role in detecting and studying the Higgs boson's properties in several of its production and decay modes. The group is currently concentrating on detecting the production of two Higgs bosons or two scalar bosons decaying into a pair of photons and b-quarks (HH/SH->bbyy), a process that has never been observed before. The CPPM group also has a strong contribution to the design, production, and installation of the ATLAS liquid argon calorimeter and its electronics.

Efficient identification of photons in the ATLAS liquid argon calorimeter is essential for detecting the HH/SH->bbyy processes. The internship will focus on developing neural networks capable of identifying photons and separating them from the background, mainly consisting of hadronic jets. The candidate will build various variables describing the electromagnetic shower shape of the photon in the calorimeter and design and train a neural network to identify photons using these shower shapes. Prior knowledge of programming languages, especially C++/ROOT or Python, and machine learning tools such as Keras, is an advantage but not mandatory.

The last piece of the standard model of particle physics, the Higgs boson, was discovered by the ATLAS and CMS collaborations in 2012. Following the Higgs boson discovery, the LHC focus has shifted to identifying new physics beyond the Standard Model. The ATLAS group at CPPM have a leading role in detecting and studying the Higgs boson properties in several of its production and decay modes. The group is currently concentrating on the detection of the production of two Higgs bosons or two scalar bosons and the search for new physics with LHC data.

The internship will concentrate on developing and optimizing a neural network capable of detecting anomalies in LHC data that correspond to new physics signatures. The neural network will be trained in a unsupervised (or weekly supervised) manner so that it is sensitive to any deviation from the Standard Model regardless of the theoretical model describing the new physics. This provides a general algorithm capable of detecting unknown new physics that might exist in nature. The successful candidate will develop a neural network with an auto-encoder architecture, train it on simulated Standard Model data, and check its performance on a wide variety of simulated signal models.

Prior knowledge of programming languages (especially python) and of Neural network tools (especially Keras) is an advantage but is not mandatory.

The top priority of particle physics community for the future is the construction of a Higgs factory: An electron-positron collider, to study the Higgs boson, discovered at CERN in 2012.

The clean collision environnement provided by such colliders enables easier and more precise analysis and measurements. One of the popular options for such a factory is the Future Circular Collider (FCC), which is being evaluated by Monte Carlo methods, including detailled simulation of detectors which would be built at FCC collision points, if this project is chosen. The FCC will have a circumference of 91 km, be located 200 m under the french-swiss boarder near Geneva and hoped to start on 2045.

One of the concept-detector being evaluated is ALLEGRO. It will be equipped by a highly granular lead/nobel liquid sampling electromagnetic calorimeter. The intership is about optimising this calorimeter by looking at the performance of different options. The options are about absorber material (lead or tungestene), noble liquid (argon or krypton), front-end electronics location (inside or outside the cryostat) and cryostat material (aluminium or carbon fibers). The performace includes naturally energy resolution, but also particle flow capability, MIP tagging and detection of photons down to 200 MeV.

The trainee will determine performance of different calorimeter options by analysing simulated calorimeter response to generated particles at different energies and locations.

The Belle II detector, located at KEK in Tsukuba, Japan, is aimed at precision measurements of the properties of beauty and charm hadrons, as well as tau leptons (https://inspirehep.net/literature/1692393). The Belle II collaboration (https://www.belle2.org/) consists of more than 1,000 scientists and has been taking data since 2019. The key feature of the Belle II detector is the nearly 4? acceptance, which allows for the full reconstruction of the visible collision products and the calculation of missing energy. This enables not only the study of B-meson decays with neutrinos in the final state, which are sensitive probes of physics beyond the Standard Model, but also to obtain inclusive datasets of charm hadrons allowing novel types of precision measurements. To achieve this, reliable particle identification is required across the entire momentum range. However, currently, the reconstruction and identification efficiency of low-momentum tracks is one of the limiting factors.

Identification of charged particles at Belle II is performed by combining several methods: Cherenkov radiation, time-of-propagation measurement, as well as the energy loss in the tracking detectors (dE/dx). At low momentum, the main sensitivity comes from the energy deposit in the silicon vertex detector (SVD).

This internship will focus on improving the performance of particle identification with the SVD, as well as its calibration. The student will learn the basics of particle physics experiments, work with real data collected by Belle II using modern data analysis tools, and understand how particle identification is applied to physics measurements.

This topic is linked to the PhD topics proposed by the CPPM Belle II group, which will rely on the concepts learned and developed in this internship.

Prior knowledge of ROOT, C++, or Python is an advantage, but not mandatory.

Processes involving Flavor Changing Neutral Currents (FCNC), where a B meson undergoes decay into a pair of oppositely charged leptons, serve as potent avenues in the exploration of physics beyond the Standard Model (SM). Notably, the decay $B^0_s \rightarrow \mu \mu$ has been observed by LHC experiments, and its measured branching fraction (BF) aligns with the SM prediction, thereby imposing rigorous constraints on theories extending beyond the SM. Investigations into the tauonic modes $B \rightarrow \tau \tau$ , where B can be either a B0 or B0s meson, become particularly compelling due to indications of lepton flavor nonuniversality hinted from several experiments in $B \rightarrow s l l$ and $B \rightarrow c l \nu$ processes. Models elucidating these anomalies propose that the BF of $B \rightarrow \tau \tau$ modes could exhibit significant enhancements compared to SM predictions, potentially by several orders of magnitude. Only few measurements have been performed on those modes so far, Belle II is expected to improve them significantly. The Belle II experiment, situated at KEK in Japan, initiated data collection in 2019 with the aim of accumulating much more data than its predecessor, Belle. The goal of the stage will be to explore new ways to reconstruct (more inclusively) the non-signal B in the events or to perform the analysis without reconstructing the non-signal B at all, using appropriate decays of the signal taus.

Activities:

Data analysis possibly using Machine Learning techniques.

Work context:

This internship will take place at CPPM, Marseille (https://www.cppm.in2p3.fr/web/en/index.html).

Additional information:

Application must include a CV, grade records and a motivation statement .

References:

https://arxiv.org/abs/1808.10567

https://arxiv.org/abs/1703.02508

https://arxiv.org/abs/hep-ex/0511015

KM3NeT/ORCA (Oscillation Research with Cosmics in the Abyss) is a deep sea

neutrino telescope currently under construction at a depth of 2500m in the

Mediterranean Sea off the coast of Toulon. ORCA is optimised for the detection of

low energy (3-100 GeV) atmospheric neutrinos and will allow precision studies

of neutrino oscillation properties. ORCA is part of the multi-site KM3NeT research infrastructure, which also incorporates a second telescope array (in Sicily) optimised for the detection of high-energy cosmic neutrinos.

The first ORCA detection strings have been operating for more than a year and are providing high quality data. During this stage the student will apply machine learning techniques to the data analysis with the aim to improve the angular and energy resolutions of the current event reconstruction algorithms. It is expected the candidate will follow this stage with a PhD on measuring the neutrino oscillation parameters.

Links:

http://antares.in2p3.fr

http://www.km3net.org

http://www.cppm.in2p3.fr/rubrique.php3?id_rubrique=259

Dark matter is one of the great enigmas of fundamental physics today. Its contribution to the total mass of the Universe is 85%, but it cannot be explained within the framework of the Standard Model of particle physics (SM). However, several candidates for dark matter exist in theories beyond the SM: this is the case of the axion, one of the best-motivated candidates as it also explains the absence of CP violation in the strong interaction.

The discovery of axions requires the invention of new experimental techniques. Several proposals have emerged in recent years. MADMAX is one of the few that is sensitive to the mass domain around 100 micro-eV, favored by theory. For this reason, it has attracted the attention of the scientific community since 2016, when it was first proposed. Today, MADMAX is a collaboration of 50 scientists from German and French laboratories (including CPPM since 2019) and is part of the DMLab International Research Laboratory, installed at DESY-Hamburg. Based on the innovative concept of dielectric haloscope, MADMAX will consist of a booster made of 80 1-meter-diameter disks that need to be positioned to micrometer precision at a temperature of 4 degrees Kelvin and in a magnetic field of 9 T. In order to build this detector, which will take data at DESY after 2030, the MADMAX collaboration is in an R$\&$ D phase. Several prototype tests have been carried out at CERN in 2024, some of them for the first time at liquid helium temperature.

The aim of the internship is to participate in the analysis of these data and to search for axions in a phase space that has not yet been explored. This work will be based on CPPM's experience in analyzing data from other prototype tests which have already given rise to publications. In the absence of a signal, the student will be able to interpret these results to place constraints on dark photons (another dark matter candidate).

More details about the CPPM Dark Matter team: https://www.cppm.in2p3.fr/web/en/research/particle_physics/#Dark%20Matter

On July 1, 2023, the Euclid satellite was successfully launched aboard a SpaceX Falcon 9 rocket from Cap Canaveral and is now fully operational in a halo orbit around the second Sun-Earth Lagrange point. Over the next six years, Euclid will conduct an extensive survey of one-third of the sky, gathering invaluable data to investigate the spatial distribution of both dark and luminous matter, while also sheding light on the origins of the accelerating expansion of the Universe.

During the first six months of the Euclid mission, specific fields were observed for their scientific importance and to evaluate Euclid's performance in flight. These observations, referred to as Early Release Observations (ERO), include slitless spectroscopic imaging data. This internship will focus on analyzing the slitless spectroscopic data from the ERO Perseus Cluster, with the goal of extracting spectra from targets of interest, confirming their redshifts, and determining if they are gravitationally bound to the Perseus Cluster.

The internship will require developing and implementing image processing techniques tailored to slitless spectroscopy. Specifically, the tasks will include:

1- Target Identification and Location: Curently this task is done manually, identifying source of interest bye eye. The first step intership will involve adapting algorithms to perform astrometric calibration of slitless spectroscopy image in an autonomous way. Such calibration will further allow to pinpoint objet oc interest on images based on their astrometric coordinates, fastening identifiaction of their spectrogram.

2- Automated Spectral Extraction: Once the targets are located, the next task is to adapt current script used to manually extract spectrogram into an autonomous pipeline.

3- Decontamination and Noise Removal: An important step will be to improve extraction and decontamination pipeline which currently suffer from aliasing introduced by pixel binning of the 2D spectrogram.

4- Redshift Confirmation: Using the cleaned spectra, you will then work on confirming the redshifts of the targets by identifying key spectral features such as emission or absorption lines. This step is essential for determining whether these galaxies or objects are part of the Perseus Cluster or lie outside of it. Understanding the physical conditions of these objects through their redshift will also allow for further astrophysical interpretation.

In summary, the internship will provide a comprehensive experience in astronomical data processing, focusing on autonomous spectra extraction, redshift confirmation, and advanced image analysis, all while contributing to the early scientific objectives of the Euclid mission.

Twenty years after the discovery of the accelerating expansion of the universe through supernova measurements, the supernova probe remains one of the most accurate means of measuring the cosmological parameters of this recent period in the history of our universe, dominated by the so-called dark energy.

The Rubin Observatory with the Large Survey of Space and Time (Rubin/LSST) will be commissioned in 2025 and will be fully operational by the end of 2025. It is an 8.4-m telescope equipped with a 3.2-billion-pixel camera, the most powerful ever built.

This telescope will take a picture of half the sky every three nights for ten years. This survey will make it possible to measure billions of galaxies with great precision, and to track the variation over time of all transient objects. Together with many other astrophysical studies, it will be a very powerful machine for determining cosmological parameters using many different probes and, in particular, will impose strong constraints on the nature of dark energy. The LSST project aims to discover up to half a million supernovae. This improvement of two to three statistical orders of magnitude over the current data set will enable precise testing of the parameters of dark energy, test general relativity and also impose new constraints on the isotropy of the universe.

In this Master 2 internship, we propose to analyse the first Rubin/LSST images using LSST software and our deep learning method for transient/supernova identification. The work will be prepared and conducted in parallel on existing HSC/Subaru data. Indeed, the HSC data have characteristics very close to those we expect from Rubin/LSST.

The LSST group at CPPM is already involved in precision photometry for LSST, with direct involvement in algorithm validation within DESC/LSST [1][2][3], and has proposed a new deep learning method to improve photometric supernova identification [4] and photometric redshifts [5].

[1] https://www.lsst.org/content/lsst-science-drivers-reference-design-and-anticipated-data-products

[2] https://arxiv.org/abs/1211.0310

[3] https://www.lsst.org/about/dm

[4] https://arxiv.org/abs/1901.01298

[5] https://arxiv.org/abs/1806.06607

[6] https://arxiv.org/abs/1401.4064

In the late 90s, measurements of the distance of Supernovae and the redshift of their host galaxies revealed that the expansion of the Universe was accelerating. More than 20 years after this discovery, the nature of the dark energy at the origin of this phenomenon remains unknown.

The $\Lambda$ CDM concordance model describes a homogeneous, isotropic Universe on large scales, subject to the laws of general relativity (GR). In this model, most of the Universe's energy content comes from cold dark matter and dark energy, introduced as a cosmological constant. The latter behaves like a perfect fluid with negative pressure p, equation of state p = - rho, where rho is the energy density.

Some alternative models (see [1] for a review) introduce scalar fields (quintessence) whose evolution is responsible for the accelerated expansion. These scalar fields can vary in time and space. They can therefore have a time-dependent equation of state and generate anisotropic expansion.

Other models propose to modify the law of gravitation on large scales, mimicking the role of dark energy.

Supernovae remain one of the most accurate probes of the Universe's expansion and homogeneity. In addition, part of the redshift of galaxies is due to a Doppler effect caused by their particular velocities. We can then use supernovae to reconstruct the velocity field on large scales, and measure the growth rate of cosmic structures. This will enable us to test the law of gravitation.

An anisotropy of expansion on large scales, a modification of GR, or an evolution of the equation of state for Dark Energy, would all be revolutionary observations that would challenge our current model.

Until now, supernova surveys have gathered data from multiple telescopes, complicating their statistical analysis. Surveys by the Zwicky Tansient Facility (ZTF: https://www.ztf.caltech.edu/) and the Vera Rubin/LSST Observatory (https://www.lsst.org/) will change all that. They cover the entire sky and accurately measure the distance to tens (hundreds) of thousands of nearby (distant) supernovae.

The CPPM has been working on ZTF data since 2021 and will publish a first cosmological analysis in 2025 with ~3000 SN1a. We have also been involved in the construction and implementation of LSST for years, preparing for the arrival of the first data this summer.

Within the group, we are working on the photometric calibration of the ZTF survey, essential for the measurement precision we need (see ubercalibration [2,3]). A recent PhD student has developed a pipeline to simulate ZTF and measure the growth rate of structures ([4]), and a current PhD student is adapting this exercise to LSST. In addition, a post-doc has just joined the group to work on ZTF, and a Chair of Excellence (DARKUNI) is extending this work by combining these data with spectroscopic data from DESI.

The aim of the internship is to develop and perfect this analysis pipeline for measuring the growth rate of structures with the totality of 30000 SN1a of ZTF. We will then use machine learning algorithms to classify the SN1a using photometric data [5].

This is an observational cosmology internship, for a candidate interested in cosmology and data analysis.

[1] https://arxiv.org/abs/1601.06133

[2] https://arxiv.org/abs/astro-ph/0703454v2

[3] https://arxiv.org/abs/1201.2208v2

[4] https://arxiv.org/abs/2303.01198 https://snsim.readthedocs.io/

[5] https://arxiv.org/abs/2401.02945

The context: More than twenty years after the discovery of the accelerated nature of the Universe's expansion, there is still no definitive explanation for its physical origin. Several types of dark energy or even alternatives/extensions to general relativity have been proposed in the literature attempting to explain the acceleration of the expansion. By accurately measuring of both the expansion rate of the Universe as well as the growth rate of structures as a function of cosmic time, we can learn more about this cosmological mystery. Particularly at low redshift when the expansion is accelerated and dark energy dominates the expansion, we are interested in obtaining the best constraints on the growth rate of structures. These measurements can be achieved by combining galaxy positions and their velocities. The statistical properties of the density and velocity field are tightly connected to the underlying cosmological model.

Experiments: Measurements of the expansion and growth rates of the Universe are the main scientific goal of current and future experiments such as the Dark Energy Spectroscopic Instrument (DESI), the Zwicky Transient Facility (ZTF), Euclid and the Vera Rubin Observatory Legacy Survey of Space and Time (Rubin-LSST).

DESI is currently measuring the 40 million galaxy positions (with their redshift) and their lower redshift sample will be the most complete to date.

The ZTF survey will discover more than 5 000 type-Ia supernovae, from which we can derive galaxy velocities. Rubin-LSST will increase this number to the hundreds of thousands.

Goal of thesis: The selected candidate will work towards the joint analysis of DESI and ZTF datasets, which contain millions of galaxies and thousands of type-Ia supernovae. The candidate will get familiarised with the physics and the statistics of galaxy clustering, will code their own analysis pipeline, test it on state-of-the-art simulations, and apply it on real data. The measurement of the growth rate of structures using DESI galaxies and peculiar velocities from ZTF supernovae will enable tests of general relativity on cosmic scales. This study is a key project in the roadmap of DESI and ZTF collaborations.

Profile required: The candidate has to have large interest by cosmology, statistics, data analysis and programming (we use mostly python). English proficiency and team work skills are also required.

The imXgam research team conducts interdisciplinary research activities for imaging applications of ionizing radiation in the health and energy fields. It participates in the PGTI (Prompt Gamma Time Imaging) project, whose objective is to reduce the uncertainties related to the path of protons during proton therapy treatments through the development of a detector for time-of-flight imaging of prompt gamma rays (PGs) created during irradiation. This project is based on the development of the TIARA (Time-of-flight Imaging Array) detector.

The accuracy of proton therapy is currently limited by the uncertainties related to the proton path, which result from the composition of the patient's tissues, physiological movements or transient changes in the anatomy and which lead to the use of large safety margins (up to 1 cm) to avoid irradiating healthy tissues. The purpose of PG imaging is to allow real-time control of tumor treatment [1]. To fully exploit its potential, an innovative real-time treatment control detector based on time-of-flight imaging of PGs with a temporal resolution of 100 ps is proposed [2]. This detector consists of a set of lead fluoride Cherenkov converters of about 1 cm³ each surrounding the irradiated volume and read in coincidence with a beam monitor. The principle consists in measuring precisely (better than 100 ps) the time difference between the time of passage of the protons in the beam monitor based on a diamond detector and the time of arrival of the PGs in the Cherenkov converters, which corresponds to the time-of-flight of the proton between its passage in the beam monitor until its interaction in the tissues followed by the time-of-flight of the PG emitted during this interaction until its detection by TIARA. This time difference, knowing the position of the TIARA detectors, constrains the coordinates of the point of emission of the PGs, which allows a 3D reconstruction of the proton path in real time with a millimeter precision [3].

A 3D reconstruction algorithm of the proton path in real time specific to the TIARA detector and its physics has been developed and validated on analytical and Monte Carlo data. The objective of this internship is to develop and study the performance of machine and/or deep learning methods for this problem. The first part will involve building a substantial database by exploiting the modelling of the PGTI/TIARA experiment on the GEANT4 Monte Carlo simulation platform, which has already been carried out. This data should correspond to a realistic benchmark. In a second part, this database will be used to train neural networks capable of estimating the energy deposited in the patient on the basis of time of flight. The robustness and accuracy of these neural networks will be assessed and compared with an analytical algorithm that has already been developed.

These developments will mainly use Python and GATE/Geant4 languages.

Candidates are invited to contact the person in charge of the thesis subject by attaching a CV with a letter of motivation and the last transcript (the one of the previous year and the one of the current semester, if available).

[1] J Krimmer et al., Prompt-gamma monitoring in hadrontherapy: A review, Nucl. Instrum. Methods A 878 (2018) 58-73

[2] S. Marcatili et al., Ultra-fast prompt gamma detection in single proton counting regime for range monitoring in particle therapy, Phys. Med. Biol. 65 (2020) 45033

[3] M. Jacquet et al., A time-of-flight-based reconstruction for real-time prompt-gamma imaging in protontherapy, Phys. Med. Biol. 66 (2021) 135003

The imXgam research team conducts interdisciplinary research activities for imaging applications of ionizing radiation in the health and energy fields. It participates in the ClearMind project whose objective is to develop an optimized detector for highly time-resolved applications, in particular for time-of-flight positron emission tomography (PET).

The measurement of the time of flight of a pair of annihilation photons, i.e. the time between the detection of the two 511 keV photons, allows to constrain the tomographic inversion within a back-projection range determined by the accuracy of the time-of-flight measurement, which is given by the coincidence time resolution (CTR). Knowing that the speed of light in vacuum is 30 cm/ns, a CTR of 10 ps FWHM would allow to localize the electron-positron annihilation with an accuracy of 1.5 mm FWHM, which would be sufficient to obtain an image of the distribution of annihilation points virtually without reconstruction and thus limit the dose required to obtain an image quality equivalent to that of the clinical PET cameras. Currently, state-of-the-art cameras achieve a CTR of 215 ps FWHM. The objective of the ClearMind project is to improve the temporal resolution of the detectors by using a scintillating lead tungstate (PWO) crystal as the input window of a microchannel plate photomultiplier tube (MCP-PMT) and to deposit a photocathode directly on the inner face of the PWO crystal in order to avoid total reflections of scintillation and Cherenkov photons on the PWO/photocathode interface to improve the collection of Cherenkov photons whose emission is practically instantaneous when a photoelectric electron is emitted at a speed higher than the speed of light in the PWO [1].

It is necessary to deposit a passivation layer on the PWO crystal to protect the photocathode. The deposition of a thin layer affects the transmittance of the interface, enabling frustrated transmission of optical photons at incidences above the limit angle [2]. The aim of the internship will be to study the theoretical transmittance of a multilayer passivation between the crystal and its photocathode.

Candidates are invited to contact the person in charge of the thesis subject by attaching a CV with a letter of motivation and the last transcript (the one of the previous year and the one of the current semester, if available).

[1] D. Yvon et al., Design study of a scintronic crystal targeting tens of picoseconds time resolution for gamma ray imaging: the ClearMind detector, J. Instrum. 15 (2020) P07029

[2] L. Cappellugola et al., Modelisation of light transmission through surfaces with thin film optical coating in Geant4, in Conf. Rec. IEEE NSS/MIC 2021, 16-23 Oct, Yokohama (virtual), Japan, IEEE Press

L'expérience MadMax cherche à démontrer l'existence d'axions, bosons scalaires initialement introduits pour expliquer naturellement l'absence de violation de la symétrie CP en Chromodynamique quantique. Le domaine de masse investigué par MadMax est entre 40 et 400 microeV. Le principe de recherche est l'induction d'un champ électromagnétique (EM) par le champ d'axions dans un champ magnétique (environ 9T). Le champ EM induit dépend de la permittivité diélectrique du milieu. La discontinuité existante aux interfaces entre des milieux différents donne lieu à la production d'une onde EM, qui pourrait être détectée. La fréquence est de l'ordre de 10-100 GHz, la puissance est de l'ordre de 10^{-24} W. La faiblesse du signal requiert un dispositif capable d'amplifier naturellement le signal: l'exploitation de plusieurs disques dielectriques dans MadMax permet d'additionner constructivement les signaux, et/ou de créer des cavités résonantes, afin d'atteindre une puissance détectable par une antenne (requérant néammoins une température de quelques Kelvins seulement, et une amplification très bas bruit). L'ensemble des calculs analytiques est détaillé référence [1]. Il s'agira ici de s'intéresser plus généralement, de façon analytique et numérique, à la génération d'une onde EM à une interface, dans un régime permanent tel que dans le cas du champ EM induit par le champ d'axion, et aussi dans un régime transitoire (émission impulsionnelle), et d'étudier la propagation/ réflexion/ transmission/ amplification dans le cas de plusieurs interfaces.

[1]:Dielectric Haloscopes to search for Axion Dark Matter: Theoretical Foundations, JCAP01(2017)061, DOI 10.1088/1475-7516/2017/01/061, Millar AJ, Raffelt GG, Redondo J, Steffen FD.

On July 1, 2023, the Euclid satellite was successfully launched aboard a SpaceX Falcon 9 rocket from Cap Canaveral and is now fully operational in a halo orbit around the second Sun-Earth Lagrange point. Over the next six years, Euclid will conduct an extensive survey of one-third of the sky, gathering invaluable data to investigate the spatial distribution of both dark and luminous matter, while also sheding light on the origins of the accelerating expansion of the Universe.

During the first six months of the Euclid mission, specific fields were observed for their scientific importance and to evaluate Euclid's performance in flight. These observations, referred to as Early Release Observations (ERO), include slitless spectroscopic imaging data. This internship will focus on analyzing the slitless spectroscopic data from the ERO Perseus Cluster, with the goal of extracting spectra from targets of interest, confirming their redshifts, and determining if they are gravitationally bound to the Perseus Cluster.

The internship will require developing and implementing image processing techniques tailored to slitless spectroscopy. Specifically, the tasks will include:

1- Target Identification and Location: Curently this task is done manually, identifying source of interest bye eye. The first step intership will involve adapting algorithms to perform astrometric calibration of slitless spectroscopy image in an autonomous way. Such calibration will further allow to pinpoint objet oc interest on images based on their astrometric coordinates, fastening identifiaction of their spectrogram.

2- Automated Spectral Extraction: Once the targets are located, the next task is to adapt current script used to manually extract spectrogram into an autonomous pipeline.

3- Decontamination and Noise Removal: An important step will be to improve extraction and decontamination pipeline which currently suffer from aliasing introduced by pixel binning of the 2D spectrogram.

4- Redshift Confirmation: Using the cleaned spectra, you will then work on confirming the redshifts of the targets by identifying key spectral features such as emission or absorption lines. This step is essential for determining whether these galaxies or objects are part of the Perseus Cluster or lie outside of it. Understanding the physical conditions of these objects through their redshift will also allow for further astrophysical interpretation.

In summary, the internship will provide a comprehensive experience in astronomical data processing, focusing on autonomous spectra extraction, redshift confirmation, and advanced image analysis, all while contributing to the early scientific objectives of the Euclid mission.

This master project focuses on the study of the large and under-dense regions in the distribution of galaxies in our Universe: cosmic voids. We will study these voids through the use of state-of-the-art simulations, together with Alice Pisani. Based on common interest and on student-supervisor initial discussions, the project will focus on either analyzing the size distribution of voids, as well as other common properties like their shape, or on analyzing the distribution of matter and galaxies around voids via their density profile. These statistics can be studied with respect to the impact of alternative physical models on these regions, their general and universal properties or their dependence on cosmological parameters

Le CPPM travaille sur l'expérience ATLAS basée au CERN à Genève, collaboration internationale comprenant 3 000 scientifiques issus de 174 instituts et de 38 pays. Le projet consiste à œuvrer pour l'horizon 2029 à une mise à niveau de l'électronique de lecture du calorimètre à argon liquide en réalisant un tout nouveau système d'acquisition de données et de trigger appelé le processeur LASP ( Liquid Argon Signal Processor~). Il s'agit de développer une carte au format ATCA à base de deux FPGA INTEL AGILEX, d'un contrôleur MAX10 et d'une vingtaine de modules optiques pour calculer en temps réels les énergies déposées dans le calorimètre suite aux collisions dans le LHC.

L'un des défis technologiques est de traiter une énorme quantité de données (250 Gb/s par FPGA), tout en calculant l'énergie en moins de 125 ns. L'arrivée de la carte est prévue pour mi-2024.

Activités principales

Il s'agit de développer une solution de configuration de FPGA AGILEX de INTEL à distance par protocole Ethernet. Cette solution est appelée RSU pour «~Remote System Update~». Elle comprend le développement d'un firmware VHDL spécifique, le dévéloppement de scripts de gestion capables de gérer des protocoles de communication sécurisés et de lancer le processus de configuration à distance des FPGA et de leurs mémoires FLASH associées. Ces dernières pourront stocker plusieurs configurations possibles. D'autres développements en VHDL sont également à prévoir pour ce FPGA AGILEX en fonction du temps disponible. Ce FPGA AGILEX est en interaction permanente avec un contrôleur FPGA MAX10 via des protocoles I2C et SPI pour le monitoring des températures internes ou des valeurs de configuration de modules de communication optiques. Des firmwares seront développés pour la validation de certaines fonctionnalités de la carte.

Les développements et les activités proposés concerneront~:

- Firmware de reconfiguration RSU du FPGA, utilisant l'IP «~Secure Device Manager~»

- Software de contrôle et de configuration de la mémoire Flash externe au FPGA

- Software de transfert des firmwares des FPGA via le protocole Ethernet

- Firmware utilisant les protocoles I²C et SPI pour transmettre les données de monitoring au contrôleur de type MAX 10

- Rédaction de documentation et participation aux réunions du CERN.

Connaissances requises

- Développement de firmwares FPGA en VHDL avec Quartus

- Très bonne pratique du langage Python

- Bonnes bases en électronique numérique

- Anglais pour les présentations, la documentation technique et la rédaction de rapports

Le stage de 6 mois sera conventionné et rémunéré.

Candidature par email avec référence du stage, CV et lettre de motivation

à Frédéric Hachon, hachon@cppm.in2p3.fr.

Situé à Marseille, sur le campus de Luminy au sein du Parc National des Calanques, le CPPM est un laboratoire de recherche affilié au CNRS et à Aix-Marseille Université. Il rassemble 180?Chercheurs, Ingénieurs et Doctorants qui travaillent sur des thématiques variées comme la physique des particules, l'astroparticule et la cosmologie. Fort de son expertise technologique en électronique, mécanique et informatique, le CPPM développe des systèmes de détection avancés, utilisés dans des environnements extrêmes tels que les fonds marins, l'espace ou sous terre. Les recherches s'inscrivent dans des collaborations internationales de haut niveau. L'équipe d'Ingénieurs en électronique et micro-électronique, spécialisée dans la conception et le test de systèmes électroniques de pointe, contribue à des projets phares, comme LHCb au CERN https://home.cern/fr/science/experiments/lhcb. L'expérience étudie notamment la dissymétrie matière/antimatière observée après le Big Bang.

Pour toute information complémentaire, consultez les sites cnrs.fr et du CPPM~: cppm.in2p3.fr.

Activités principales

Les détecteurs sont installés sur le grand collisionneur de hadrons (LHC) du CERN à Genève. Après avoir optimisé la granularité physique des canaux de détection, ils requièrent désormais un synchronisme avec une précision ultime en O (10) ps pic à pic afin d'assurer un alignement des données acquises en temps réel. Les techniques utilisées sont de distribuer une horloge superposée aux données de contrôle sur des liens sériels émis par des FPGA via des fibres optiques. Il s'agit donc de mettre en œuvre, d'éprouver et de caractériser des gateware sur les FPGA les plus puissants de la gamme Agilex Intel/Altera. Ces gateware devront assurer une phase constante entre les reset et les redémarrages du système à l'échelle de 1 à 48 canaux sur un seul FPGA, puis sur plusieurs cartes FPGA en parallèle en tenant compte des aléas dus aux variations de température de l'environnement.

- Etude des techniques de transmission de données à phase déterministe sur FPGA

- Développement de gateware intégrant des transceivers de données sériels

- Développement de logiciels nécessaires aux tests et mesures

- Tests, mesures, caractérisation et métrologie

Profil recherché et connaissances appréciées

Les compétences suivantes seront appréciées et une formation en interne sur les outils utilisés sera assurée~:

- Utilisation d'appareils de mesure : serial data analyser, analyseur de spectres~

- Électronique, transmission de signaux rapides~; intégrité de signal

- Conception de firmware FPGA en langage VHDL en utilisant Quartus~

- Conception logicielle, langage Python (Polars, Pytest), C++

Le stage de 6 mois sera conventionné et rémunéré.

Candidature par email avec référence du stage, CV et lettre de motivation

à Frédéric Hachon, hachon@cppm.in2p3.fr.

Situé au coeur du Parc National des Calanques, sur le campus de Luminy, le CPPM est un laboratoire de recherche commun au CNRS et à Aix-Marseille Université, qui compte environ 180 chercheurs, ingénieurs et doctorants. Le laboratoire étudie des sujets allant de la physique des particules à la physique des astroparticules et à la cosmologie, avec une forte expertise technologique en électronique, mécanique, instrumentation et informatique, permettant la conception et la construction de systèmes de détection de pointe, souvent appelés à fonctionner dans des conditions extrêmes : dans les profondeurs de la mer, dans l'espace ou sous terre. La plupart de nos recherches sont menées dans le cadre de collaborations scientifiques internationales de premier plan et nos contributions sont reconnues dans le monde entier.

Activité principale

Le stagiaire travaillera au sein du service électronique du laboratoire, composé d'une vingtaine de personnes. Il aura comme objectif principal de concevoir une nouvelle infrastructure informatique en tenant compte des différents projets, des groupes de travail, des types de machines, des ressources et des besoins spécifiques pour le déploiement, l'accès et le support des outils de Conception Assistée par Ordinateur (CAO).

En intégrant le CPPM, vous contribuerez à la réalisation de projets de recherche ambitieux en physique des particules. Vous aurez l'opportunité d'évoluer dans un environnement stimulant et de participer au développement d'outils informatiques essentiels pour la recherche de pointe, tout en renforçant vos compétences dans les infrastructures informatiques modernes.

Le stagiaire devra notamment

- Analyser l'infrastructure informatique existante ;

- Proposer et concevoir une solution moderne prenant en compte les contraintes des projets de recherche ;

- Explorer des solutions d'infrastructure basées sur le Cloud, des conteneurs ou des machines virtuelles (VM), tout en garantissant l'efficacité et la flexibilité des outils utilisés par le laboratoire.

Connaissances requises

- Maîtrise de l'environnement Linux

- Compétence en script shell

- Bonne compréhension de l'architecture des systèmes informatiques et réseaux

- Connaissance des technologies de virtualisation, de conteneurisation, Cloud

Encadrement et environnement de travail :

Le stagiaire sera encadré par un ingénieur spécialisé et travaillera en collaboration étroite avec les différents service et groupes de recherche du laboratoire. Il bénéficiera d'un ordinateur de test et d'un accès aux ressources Cloud nécessaires pour mener à bien sa mission.

Le stage de 6 mois sera conventionné et rémunéré.

Candidature par email avec référence du stage, CV et lettre de motivation

à Frédéric Hachon, hachon@cppm.in2p3.fr.

Le stage se déroule au Centre de Physique des Particules de Marseille (CPPM). C'est est une unité mixte de recherche (UMR 7346) qui relève de l'IN2P3, institut regroupant les activités de physique des particules et de physique nucléaire au sein du CNRS et d'Aix-Marseille Université.

Dans le cadre du grand collisionneur à hadrons (LHC) du CERN à Genève, le CPPM participe depuis plusieurs années à l'expérience ATLAS et en particulier au développement et à la construction du détecteur interne à pixels, sous-détecteur le plus proche du point d'interaction, où les faisceaux de protons entrent en collision.

Sans les progrès de la technologie des circuits intégrés, certains projets importants du CERN n'auraient pas été réalisables ou auraient montré de faibles performances et des coûts très élevés.

L'avenir ne devrait pas être différent puisque les futurs détecteurs à pixels nécessitent l'adoption de technologies de circuits intégrés encore plus performantes et plus complexes. Le process CMOS 28~nm reste la base pour les développements futurs des pixels de type hybride pour les mises à niveau du LHC ou pour les prochaines générations de collisionneurs.

Au sein de collaborations R\&D du CERN, le CPPM contribue à la réalisation de pixels hybrides basés sur le process 28 nm visant à réduire la taille du pixel et surtout inclure de nouvelles fonctionnalités permettant d'améliorer la résolution temporelle, caractéristique essentielle qui ouvrira la voie à de nouvelles améliorations de la reconstruction des traces.

Activités principales

Le but du stage est de proposer, étudier et intégrer un circuit TDC (time to digital converter) 10 bits pour la mesure du temps d'arrivée de la charge dans le pixel. L'architecture et la conception doivent permettre de maintenir une surface réduite compatible avec la taille du pixel et montrer une consommation en accord avec les spécifications.

Le stage de 6 mois sera organisé en plusieurs étapes :

- Etude du prototype de matrice de pixels développé au CPPM en CMOS 28 nm

- Test et caractérisation de la matrice de pixels avec un TDC du commerce pour montrer la possibilité de mesure de temps d'arrivée de la charge avec la résolution temporelle inférieure à 50 ps

- Etude, conception et optimisation du circuit TDC avec le process CMOS 28 nm

- Simulation et optimisation du circuit sous Cadence Virtuoso

- Dessin des masques sous Cadence

Connaissances requises et appréciées

- Bonnes connaissances en conception de circuits analogiques CMOS

- Le développement de bancs de test basés sur des composants programmables de type FPGA est considéré comme un avantage

Possibilité de poursuite en Thèse de Doctorat

Le stage de 6 mois sera conventionné et rémunéré.

Candidature par email avec référence du stage, CV et lettre de motivation

à Frédéric Hachon, hachon@cppm.in2p3.fr.

ITER (International Thermonuclear Experimental Reactor) est un projet international de réacteur à fusion nucléaire, situé en France, dont l'objectif est de démontrer la faisabilité scientifique et technique de la fusion nucléaire comme source d'énergie. Basé sur la fusion du deutérium et du tritium, ITER cherche à reproduire sur Terre les réactions qui se déroulent au cœur des étoiles. Il s'agit du plus grand projet de fusion jamais construit, rassemblant des partenaires du monde entier (UE, Russie, Japon, Chine, Inde, Corée du Sud et États-Unis).

Le système de diagnostiques XRCS (X-Ray Crystal Spectroscopy) d'ITER est un outil essentiel pour surveiller le plasma à très haute température. Il utilise la spectroscopie de rayons X pour mesurer la température et la vitesse de rotation du plasma.

Le laboratoire CPPM est engagé à réaliser un détecteur à rayons X répondant au cahier des charges du système de diagnostiques XRCS. La brique élémentaire du détecteur est un circuit intégré spécifique (ASIC) matriciel de plusieurs millions de transistors. Ce circuit opère comme un appareil photo à pixels, qui doit prendre une image de la détection des rayons X. Plusieurs contraintes de conception sont imposées sur l'électronique, comme la surface, la rapidité, la consommation et la précision.

Activité principale

Le ou la stagiaire va rejoindre l'équipe de développement du CPPM qui doit réaliser un premier prototype pour la fin 2025. Le circuit sera réalisé en technologie 65nm et contiendra des fonctions analogiques et digitales (comme un préamplificateur, un ADC, des DACs de control, un bandgap ou encore des fonctions numériques de contrôle, ou de lecture des données)

Dans un premier temps, le/la stagiaire doit mener une recherche bibliographique détaillée sur les détecteurs à pixels monolithiques et sur les fonctions générales. Ensuite, il lui sera proposé d'étudier et concevoir une des fonctions qui soit le mieux adaptée à l'application selon le cahier des charges fourni.

En fonction de l'avancement du projet, le/la stagiaire aidera l'équipe de conception à finaliser le circuit prototype.

- Etude bibliographique sur les architectures de la fonction.

- Conception, simulation sous Cadence

- Dessin des masques (Layout)

- Simulation post-layout

Connaissances requises

Bonnes connaissances en conception de circuits intégrés en technologie CMOS

Le stage de 6 mois sera conventionné et rémunéré.

Candidature par email avec référence du stage, CV et lettre de motivation

à Frédéric Hachon, hachon@cppm.in2p3.fr.

Activité principale

Les détecteurs infrarouges d'Euclid ont été développés expressément pour la mission Euclid. À la pointe de la technologie, chacun est constitué d'une matrice de 2048 x 2048 pixels. Mise en évidence lors de la calibration des détecteurs au CPPM, la persistance s'avère déjà un vrai défi pour l'extraction des données en vol. Une meilleure compréhension de cet effet complexe est indispensable. Aussi l'ingénieur/l'ingénieure-stagiaire cherchera à caractériser la persistance et à comprendre les possibles dépendances de la persistance à des paramètres comme l'amplitude du signal ou la température.

Pour ce faire, l'ingénieur ou l'ingénieure-stagiaire pourra s'appuyer sur des outils précédemment développer et qui permettent de manipuler les données disponibles. Il cherchera :

Appliquer les modèles connus de la persistance (e.g. exponentielle décroissante)

Extraire des grandeurs les constantes de temps et amplitudes à partir des données de calibration existantes

Mettre en évidence les dépendances

Connaissances requises

Base solide en programmation en langage python

Bonnes connaissances en traitement du signal

Bonnes connaissances en physique du semi-conducteur

Le stage de 4 à 6 mois sera conventionné et rémunéré.

Dans le cadre d'une infrastructure sous-marine complexe destinée à s'agrandir, nous souhaitons optimiser les futurs Noeuds, de grosses structures en titane distribuant l'énergie et les fibres optiques vers des lignes de détection à neutrinos de 200m de haut.

Ces Noeuds, immergés à 2500m de fond, auront pour base les deux structures précédemment immergées. Il s'agira de les optimiser : châssis, systèmes de connexion des interlinks opérables par sous-marin, prise en compte des évolutions imposées. L'étude doit concerner également l'aspect réalisation (contraintes, coûts, moyens, etc) et s'assurer de la conformité aux impératifs des opérations en mer.

Je me permets de vous adresser un/deux sujet de stage , il y aura certainement 2 parties/sujets

a) Faisabilité technique d'un outillage de démultiplication d'effort pour une connectique Haute tension 5000 volt AC ( Alternative Current) à 2500 m de profondeur

b) Définition détaillé d'un chassis en titane , calculs en statique sur certaine partie du chassis .

stage pour année 2025

Dans le cadre de l extension de l infrastructure KM3-Net , un manifold est en cours de conception. les efforts de connexion / deconnexion étant important un outillage est a étudier. Connaissance et pratique du logiciel CATIA fortement apprécié.

The Euclid mission (http://www.euclid-ec.org) is a major project by ESA that launched a space telescope dedicated to understanding the Universe in July 2023. Through a survey of the entire sky, it will provide a 3D-mapping of galaxies with unprecedented precision. These measurements of the distant Universe large structures will test the cosmological model, particularly questioning the nature of dark energy. The mapping will be achieved using the NISP spectrophotometer and its 16 infrared detectors, which were calibrated on ground by CPPM, a fundamental step to validate the instrument's performance.

Main Activity

NISP's infrared detectors were specifically developed for the Euclid mission. At the cutting edge of technology, each one consists of a matrix of 2048 x 2048 pixels. Their fine calibration was carried out at CPPM, resulting in the recording of 500 Terabytes of data to be analyzed. These data clearly show the presence of persistence that contaminates the data during several hours of acquisition. In order to gain a better understanding of this phenomenon, the intern will work on characterizing the persistence and understanding the influence of environmental parameters on it.

Thus, the intern will need to apply classical or more sophisticated analysis methods in the following steps:

Implement the methods in Python.

Extract parameters such as time constants and amplitudes from the existing calibration data.

Analyze correlations between persistence and environmental data.

Conduct a similar study on a detector of a different technology and compare the results.

Required Knowledge