A5042881549- Galaxies: Formation, Evolution, Phenomena
- Astronomy and Astrophysical Research
- Particle physics theoretical and experimental studies
- Particle Detector Development and Performance
- Quantum Chromodynamics and Particle Interactions
- Astrophysical Phenomena and Observations
- Atmospheric Ozone and Climate
- Adaptive optics and wavefront sensing
- Solar and Space Plasma Dynamics
- Blind Source Separation Techniques
- Advanced Fluorescence Microscopy Techniques
- High-Energy Particle Collisions Research
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Stellar, planetary, and galactic studies
- Ionosphere and magnetosphere dynamics
Instituto de Astrofísica de Canarias
2021
Universidad de La Laguna
2021
King's College London
2019-2020
Udaipur Solar Observatory
1961
Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range modern machine learning approaches. Unlike most methods they rely low-level input, for instance calorimeter output. While their network architectures are vastly different, performance is comparatively similar. In general, find that these new approaches extremely powerful and great fun.
We compare the performance of a convolutional neural network (CNN) trained on jet images with dense networks (DNNs) n-subjettiness variables to study distinguishing power these two separate techniques applied top quark decays. find that they perform almost identically and are highly correlated once mass information is included, which suggests accessing same underlying can be intuitively understood as being contained in 4-, 5-, 6-, 8-body kinematic phase spaces depending sample. This both...
We investigate the possibility of applying machine learning techniques to images strongly lensed galaxies detect a low mass cut-off in spectrum dark matter sub-halos within lens system. generate systems containing substructure seven different categories corresponding lower cut-offs ranging from $10^9M_\odot$ down $10^6M_\odot$. use convolutional neural networks perform multi-classification sorting these and see that algorithm is able correctly identify an order magnitude better than 93% accuracy.
Abstract We study how mock-observed stellar morphological and structural properties of massive galaxies are built up between z = 0.5 3 in the TNG50 cosmological simulation. generate mock images with CANDELS survey derive Sersic parameters optical rest-frame morphologies as usually done observations. Overall, simulation reproduces observed evolution abundances different galaxy types star-forming quiescent galaxies. The log M* − Re Σ1 relations simulated quenched also match slopes zeropoints...
Beyond the Standard Model scenarios with extensions of Higgs sector typically predict new resonances that can undergo a series cascade decays to detectable particles. On one hand, sensitivity such signatures will contribute full reconstruction extended potential if physics discovery be made. other could dominant decay channels, thus being potentially best motivated achieve in first place. In this work, we show how long short-term memory is encoded decays' phenomenology exploited...