Molecular Hydrogen Formation on Ice Under Interstellar Conditions

The results of experiments on the formation of molecular hydrogen on low density and high density amorphous ice surfaces are analyzed using a rate equation model. The activation energy barriers for the relevant diffusion and desorption processes are obtained. The more porous morphology of the low density ice gives rise to a broader spectrum of energy barriers compared to the high density ice. Inserting these parameters into the rate equation model under steady state conditions we evaluate the production rate of molecular hydrogen on ice-coated interstellar dust grains.Comment: 20 pages, 3 tables and 10 figures. Accepted to ApJ. Minor changes made and adittional references adde

Investigations of the Formation of Molecular Hydrogen on Dust Grain Analogues

In the last four years we have been working to investigate the formation of molecular hydrogen on surfaces of materials of astrophysical interest, such as silicates, carbonaceous particles and ices, and in conditions approximating the ones present in a variety of astrophysical environments. Our experimental studies - the first of their kind and complemented with computer simulations and theoretical analyses - have given not only hydrogen recombination rates under different ISM conditions, but they have also offered new insights into this fundamental astrophysical problem. Here we summarize our experimental methods and most significant results

Sensitivity of the Cherenkov Telescope Array to a dark matter signal from the Galactic centre

High-energy gamma rays are promising tools to constrain or reveal the nature of dark matter, in particular Weakly Interacting Massive Particles. Being well into its pre-construction phase, the Cherenkov Telescope Array (CTA) will soon probe the sky in the 20 GeV - 300 TeV energy range. Thanks to its improved energy and angular resolutions as well as significantly larger effective area when compared to the current generation of Cherenkov telescopes, CTA is expected to probe heavier dark matter, with unprecedented sensitivity, reaching the thermal annihilation cross-section at 1 TeV. This talk will summarise the planned dark matter search strategies with CTA, focusing on the signal from the Galactic centre. As observed with the Fermi LAT at lower energies, this region is rather complex and CTA will be the first ground-based observatory sensitive to the large scale diffuse astrophysical emission from that region. We report on the collaboration effort to study the impact of such extended astrophysical backgrounds on the dark matter search, based on Fermi-LAT data in order to guide our observational strategies, taking into account various sources of systematic uncertainty

Performance of a proposed event-type based analysis for the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) will be the next-generation observatory in the field of very-high-energy (20 GeV to 300 TeV) gamma-ray astroparticle physics. Classically, data analysis in the field maximizes sensitivity by applying quality cuts on the data acquired. These cuts, optimized using Monte Carlo simulations, select higher quality events from the initial dataset. Subsequent steps of the analysis typically use the surviving events to calculate one set of instrument response functions (IRFs). An alternative approach is the use of event types, as implemented in experiments such as the Fermi-LAT. In this approach, events are divided into sub-samples based on their reconstruction quality, and a set of IRFs is calculated for each sub-sample. The sub-samples are then combined in a joint analysis, treating them as independent observations. This leads to an improvement in performance parameters such as sensitivity, angular and energy resolution. Data loss is reduced since lower quality events are included in the analysis as well, rather than discarded. In this study, machine learning methods will be used to classify events according to their expected angular reconstruction quality. We will report the impact on CTA high-level performance when applying such an event-type classification, compared to the classical procedure

Active Galactic Nuclei population studies with the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) observatory is the next generation of ground-based imaging atmospheric Cherenkov telescopes (IACTs). Building on the strengths of current IACTs, CTA is designed to achieve an order of magnitude improvement in sensitivity, with unprecedented angular and energy resolution. CTA will also increase the energy reach of IACTs, observing photons in the energy range from 20 GeV to beyond 100 TeV. These advances in performance will see CTA heralding in a new era for high-energy astrophysics, with the emphasis shifting from source discovery, to population studies and precision measurements. In this talk we discuss CTA’s ability to conduct source population studies of γ-ray bright active galactic nuclei and how this ability will enhance our understanding on the redshift evolution of this dominant γ-ray source class

HAWC J2227+610: a potential PeVatron candidate for the CTA in the northern hemisphere

Recent observations of the gamma-ray source HAWC J2227+610 by Tibet AS+MD and LHAASO confirm the special interest of this source as a galactic PeVatron candidate in the northern hemisphere. HAWC J2227+610 emits Very High Energy (VHE) gamma-rays up to 500 TeV, from a region coincident with molecular clouds and significantly displaced from the nearby pulsar J2229+6114. Even if this morphology favours an hadronic origin, both leptonic or hadronic models can describe the current VHE gamma-ray emission. The morphology of the source is not well constrained by the present measurements and a better characterisation would greatly help the understanding of the underlying particle acceleration mechanisms. The Cherenkov Telescope Array (CTA) will be the future most sensitive Imaging Atmospheric Cherenkov Telescope and, thanks to its unprecedented angular resolution, could contribute to better constrain the nature of this source. The present work investigates the potentiality of CTA to study the morphology and the spectrum of HAWC J2227+610. For this aim, the source is simulated assuming the hadronic model proposed by the Tibet AS+MD collaboration, recently fitted on multi-wavelength data, and two spatial templates associated to the source nearby molecular clouds. Different CTA layouts and observation times are considered. A 3D map based analysis shows that CTA is able to significantly detect the extension of the source and to attribute higher detection significance to the simulated molecular cloud template compared to the alternative one. CTA data does not allow to disentangle the hadronic and the leptonic emission models. However, it permits to correctly reproduce the simulated parent proton spectrum characterized by a ∼ 500 TeV cutoff

Southern African Large Telescope Spectroscopy of BL Lacs for the CTA project

In the last two decades, very-high-energy gamma-ray astronomy has reached maturity: over 200 sources have been detected, both Galactic and extragalactic, by ground-based experiments. At present, Active Galactic Nuclei (AGN) make up about 40% of the more than 200 sources detected at very high energies with ground-based telescopes, the majority of which are blazars, i.e. their jets are closely aligned with the line of sight to Earth and three quarters of which are classified as high-frequency peaked BL Lac objects. One challenge to studies of the cosmological evolution of BL Lacs is the difficulty of obtaining redshifts from their nearly featureless, continuum-dominated spectra. It is expected that a significant fraction of the AGN to be detected with the future Cherenkov Telescope Array (CTA) observatory will have no spectroscopic redshifts, compromising the reliability of BL Lac population studies, particularly of their cosmic evolution. We started an effort in 2019 to measure the redshifts of a large fraction of the AGN that are likely to be detected with CTA, using the Southern African Large Telescope (SALT). In this contribution, we present two results from an on-going SALT program focused on the determination of BL Lac object redshifts that will be relevant for the CTA observatory

Reconstruction of stereoscopic CTA events using deep learning with CTLearn

The Cherenkov Telescope Array (CTA), conceived as an array of tens of imaging atmospheric Cherenkov telescopes (IACTs), is an international project for a next-generation ground-based gamma-ray observatory, aiming to improve on the sensitivity of current-generation instruments a factor of five to ten and provide energy coverage from 20 GeV to more than 300 TeV. Arrays of IACTs probe the very-high-energy gamma-ray sky. Their working principle consists of the simultaneous observation of air showers initiated by the interaction of very-high-energy gamma rays and cosmic rays with the atmosphere. Cherenkov photons induced by a given shower are focused onto the camera plane of the telescopes in the array, producing a multi-stereoscopic record of the event. This image contains the longitudinal development of the air shower, together with its spatial, temporal, and calorimetric information. The properties of the originating very-high-energy particle (type, energy, and incoming direction) can be inferred from those images by reconstructing the full event using machine learning techniques. In this contribution, we present a purely deep-learning driven, full-event reconstruction of simulated, stereoscopic IACT events using CTLearn. CTLearn is a package that includes modules for loading and manipulating IACT data and for running deep learning models, using pixel-wise camera data as input