Related papers: A novel energy reconstruction method for the MAGIC…

The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the Hyper-Kamiokande experiment. It is found…

Large fraction of studies of active galactic nuclei objects is based on performing follow-up observations using high-sensitivity instruments of high flux states observed by monitoring instruments (the so-called Target of Opportunity, ToO).…

Cherenkov gamma telescope observes high energy gamma rays, taking advantage of the radiation emitted by charged particles produced inside the electromagnetic showers initiated by the gammas, and developing in the atmosphere. The detector…

The last 20 years have seen the development of new techniques in Astroparticle Physics providing access to the highest end of the electromagnetic spectrum. It has been shown that some sources emit photons up to energies close to 100 TeV.…

The MAGIC telescopes discovered very high energy (VHE, E>100 GeV) gamma-ray emission coming from the distant Flat Spectrum Radio Quasar (FSRQ) PKS 1222+21 (4C +21.35, z=0.432). It is the second most distant VHE gamma-ray source, with well…

We study the problem of reconstruction of high-energy cosmic rays mass composition from the experimental data of extensive air showers. We develop several machine learning methods for the reconstruction of energy spectra of separate primary…

We develop an efficient, non-parametric Bayesian method for reconstructing the time evolution of the dark energy equation of state w(z) from observational data. Of particular importance is the choice of prior, which must be chosen carefully…

MAGIC is a stereoscopic system of two Imaging Air Cherenkov Telescopes (IACTs) located at La Palma (Canary Islands, Spain) and working in the field of very high energy gamma-ray astronomy. It makes use of a traditional digital trigger with…

Ground based gamma-ray observations with Imaging Atmospheric Cherenkov Telescopes (IACTs) play a significant role in the discovery of very high energy (E > 100 GeV) gamma-ray emitters. The analysis of IACT data demands a highly efficient…

This review summarizes recent attempts to reconstruct the expansion history of the Universe and to probe the nature of dark energy. Reconstruction methods can be broadly classified into parametric and non-parametric approaches. It is…

The observational progress in the $\gamma$-ray astronomy in the last few years has led to the discovery of more than a thousand sources at GeV energies and more than a hundred sources at TeV energies. A few different classes of compact…

The construction of the H.E.S.S. (High Energy Stereoscopic System), a superior system of four 12 m imaging atmospheric Cherenkov telescopes, has been completed recently in the Namib desert close to Windhoek, at 1800 m above sea level. This…

In this work we expand upon the Tomographic Absorption Reconstruction and Density Inference Scheme (TARDIS) in order to include multiple tracers while reconstructing matter density fields at Cosmic Noon (z ~ 2-3). In particular, we jointly…

In this work, we present a new, high performance algorithm for background rejection in imaging atmospheric Cherenkov telescopes. We build on the already popular machine-learning techniques used in gamma-ray astronomy by the application of…

Instruments for gamma-ray astronomy at Very High Energies ($E>100\,{\rm GeV}$) have traditionally derived their scientific results through proprietary data and software. Data standardisation has become a prominent issue in this field both…

For reliable event reconstruction of Imaging Atmospheric Cherenkov Telescopes (IACTs), calibration of the optical throughput efficiency is required. Within current facilities, this is achieved through the use of ring shaped images generated…

We perform a cosmological parameter analysis of the 75 square degree CTIO lensing survey in conjunction with CMB and Type Ia supernovae data. For Lambda CDM cosmologies, we find that the amplitude of the power spectrum at low redshift is…

We present a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems. This method treats the source as a pixelated image and utilizes the Recurrent Inference Machine (RIM) to…

We use the latest data to investigate observational constraints on the new generalized Chaplygin gas (NGCG) model. Using the Markov Chain Monte Carlo (MCMC) method, we constrain the NGCG model with the type Ia supernovae (SNe Ia) from…

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure…