TTK Seminars WS 22/23
Thu 13.10.2022, 16.30 h
Guilhem Lavaux (Institut d’Astrophysique de Paris)
Fundamental physics without cosmic variance: exploring the universe through the BORG framework and the Sibelius Dark simulation
Cosmic variance poses limits to the analyses of the physics of the nearby Universe. For example, it hinders establishing an accurate observational link between halo formation history and galaxy properties or constraining the physics of Dark Matter. The BORG framework offers a way out by generating constrained initial conditions which reproduce all the Large scale structures in a simulated environment with minimal effects due to cosmic variance. By relying on the physics of gravitational interaction and our knowledge of the Universe on large scales, it can generate an ensemble of plausible samples of the initial conditions of our Universe. That framework unlocks the possibility of studying different models of galaxy formation and their impact on different observed environments. The physical environment is notably responsible for the specific mass accretion history of small-scale structures. The Sibelius-Dark simulation is an effort in that direction. I will showcase some direct results obtained with this simulation, and also more generally by the BORG framework on e.g. gravitational lensing and upper bound on the cross-section of Dark Matter particles.
Host: J. Lesgourgues
Thu 20.10.2022, 16.30 h (via zoom)
Saša Prelovšek (University of Ljubljana)
Exotic and conventional hadrons from lattice QCD
I will review how strongly stable and strongly decaying hadrons are extracted from lattice QCD. Few recent results on exotic and conventional hadrons will be reviewed. Among others, I'll discuss the first lattice results on the doubly charm tetraquark, which was discovered in 2021 and is the longest lived exotic hadron so far.
Host: R. Harlander
Thu 27.10.2022, 16.30 h
Azadeh Moradinezhad (University of Geneva)
Fundamental Physics with galaxy clustering beyond the power spectrum
The cosmic large-scale structure (LSS) provides a rich trove of information to probe the origin of the universe, its evolution and its constituents. The upcoming wide-field galaxy surveys will provide unprecedented volume of high precision data, promising to constrain deviation from LCDM model at percent level to search for new physics. Given the nonlinear nature of the LSS, extracting the non-Gaussian information not fully captured by the galaxy power spectrum is key in fully realizing the potential of upcoming galaxy surveys. Furthermore, most types of primordial non-Gaussianity do not affect the observed galaxy power spectrum and can only be probed with clustering statistics beyond the power spectrum. In this talk, I will describe several summary statistics (including galaxy bispectrum, marked power spectrum, weighted skew spectra, and wavelet moments) that capture this non-Gaussian information. I will illusterate their cosmological information content, as well as the associated challenges in their measurments and interpretation. Finally, I will discuss prospects of applying these statistics to upcoming data to constrain LCDM model, neutrino mass, modification to gravity and primordial non-Gaussianity.
Host: J. Lesgourgues
Thu 17.11.2022, 16.30 h
Enrico Peretti (NBI Copenhagen)
Particle acceleration and multimessenger radiation from wind bubbles
Young massive stellar clusters as well as starburst galaxies and active galactic nuclei can indeed launch and sustain powerful outflows featuring very high velocity and large opening angle. Such winds often develop a bubble structure characterized by an inner wind shock and an outer forward shock. During the time the forward shock expands in the surrounding medium, the inner wind shock quickly decelerates while remaining strong, thereby creating ideal conditions for particle acceleration.
I will discuss diffusive shock acceleration as key process to energize particles in wind bubbles and I will highlight the associated multimessenger implications in terms of high energy photons, neutrinos and escaping cosmic rays.
Host: P. Mertsch
Thu 24.11.2022, 16.30 h
Giada Peron (MPI für Kernphysik Heidelberg)
Probing Cosmic ray density with giant molecular clouds
The accumulation and effective mixture of relativistic particles during their propagation through the interstellar magnetic fields results in the formation of the so-called "sea" of galactic Cosmic Rays (CRs). The level and the energy distribution of the CR sea is determined by the operation of all galactic accelerators over the confinement time of CRs in the Galactic Disk. The homogeneity of CRs, however, can be violated on smaller scales, in the form of excess fluxes over the CR sea, caused by the injection of fresh relativistic particles by young accelerators into the interstellar medium (ISM). CRs interacting with Giant Molecular Clouds with masses larger than 105 Solar masses produce “enhanced” gamma-ray emission which can be used to probe the level of the CR sea throughout the Galactic Disk. I present the results that we obtained from Fermi-LAT analysis of molecular clouds located at different distances from the Galactic Center. I will also discuss their connection with lower energy tracers of CRs and the prospect for detection of clouds and diffuse emission at high and very high energies.
Host: P. Mertsch
Thu 15.12.2022, 16.30 h
Diego Blas (IFAE and Universitat Autonoma de Barcelona)
Over the rainbow… of gravitational waves
Gravitational waves from different frequencies bring information about different phenomena of the Universe. CMB studies, Ligo-Virgo-Kagra, PTA and LISA-like missions are able to provide relevant information in several bands, but leave some gaps where new signals may be hiding. In this talk, I’ll first give an overview of the different phenomena probed and main detection strategies at different frequencies After that, I‘ll focus on two gaps poorly studied by these searches (the microHz band and gravitational waves above kHz) and describe why they are important and some ideas to reach interesting sensitivities.
Host: J. Lesgourgues
Thu 19.01.2023, 16.30 h
Claudius Krause (Uni Heidelberg)
Searching the Unknown: Anomaly Detection at the LHC and with Gaia
Physics has entered the era of Big Data. On the one hand, the LHC has recorded an unprecedented number of high-energy proton collisions, with a factor 20 more to come in the high-luminosity phase in the next decade. On the other hand, large surveys like the Gaia satellite mission provide information of billions of stars in our Galaxy. Yet, Dark Matter (DM) is still elusive and has not been seen in particle experiments. Recent advances in Machine Learning, together with the large amounts of available data, open up new possibilities to look for new physics and other unknown effects. I will be introducing machine-learning assisted methods to improve searches for new physics in bump hunts. In particular, I will focus on the CATHODE (Classifying anomalies through outer density estimation) algorithm. After showing its performance on the LHC Olympics 2020 dataset, I will demonstrate how it can be used to find candidates of cold stellar streams in the Gaia dataset of 1.5 billion stars in our Milky Way. Detailed studies of these streams will shed light on the Milky Way's merger history, its gravitational potential, and also the distribution of DM within the Galaxy.
Host: T. Finke
Thu 26.01.2023, 16.30 h
Daniel Figueroa (University of Valencia)
The Numerical early Universe
We will introduce CosmoLattice, a modern code for simulating the non-linear dynamics of interactive fields in an expanding background. As a demonstration of its power we will solve different problems of early Universe cosmology: i) the non-linear dynamics of axion-inflation, ii) the use of gravitational waves as a probe of particle couplings, and upon demand: iii) the dynamics of non-minimally coupled scalar fields in the Jordan frame, or iii) the dynamics and gravitational wave emission of a single cosmic string loop.
Host: J. Lesgourgues
Thu 02.02.2023, 16.30 h
Thea Aarrestad (ETH Zürich)
Ultrafast Machine Learning Inference at the Large Hadron Collider
At the CERN Large Hadron Collider, protons are brought to collide hundreds of millions of times per second. The collision debris allows us to study the fundamental building blocks of the universe and look for hints of new forces and particles. The vast majority of the collision data are immediately discarded by a real-time event filtering system due to storage and computational limitations. While most of these data are uninterresting, signals of new physics might be inadvertendly thrown away in the process. The first stage of this event filtering system consists of hundreds of field programmable gate arrays (FPGAs), tasked with rejecting over 98% of the proton collisions within a few microseconds. With the start of High Luminosity LHC in 2029, a more granular detector and more particles per collision will increase the event complexity significantly, and ultimately require the FPGA farm to process an amount of data comparable to 5% of the total internet traffic.
In this talk, I will discuss how real-time Machine Learning (ML) is used to process and filter this enormous amount of data in order to improve physics acceptance, and how ML can be used to select data in ways never before performed at colliders.