Muons as a tool for background rejection in imaging atmospheric Cherenkov telescope arrays

The presence of muons in air-showers initiated by cosmic ray protons and nuclei is well established as a powerful tool to separate such showers from those initiated by gamma rays. However, so far this approach has been fully exploited only for ground level particle detecting arrays. We explore the feasibility of using Cherenkov light from muons as a background rejection tool for imaging atmospheric Cherenkov telescope arrays at the highest energies. We adopt an analytical model of the Cherenkov light from individual muons to allow rapid simulation of a large number of showers in a hybrid mode. This allows us to explore the very high background rejection power regime at acceptable cost in terms of computing time. We show that for very large ($$\gtrsim 20$$ ≳ 20 m mirror diameter) telescopes, efficient identification of muon light can potentially lead to background rejection levels up to 10$$^{-5}$$ - 5 whilst retaining high efficiency for gamma rays. While many challenges remain in the effective exploitation of the muon Cherenkov light in the data analysis for imaging Cherenkov telescope arrays, our study indicates that for arrays containing at least one large telescope, this is a very worthwhile endeavor.

Deep learning improves identification of Radio Frequency Interference

ABSTRACT Flagging of Radio Frequency Interference (RFI) in time–frequency visibility data is an increasingly important challenge in radio astronomy. We present R-Net, a deep convolutional ResNet architecture that significantly outperforms existing algorithms – including the default MeerKAT RFI flagger, and deep U-Net architectures – across all metrics including AUC, F1-score, and MCC. We demonstrate the robustness of this improvement on both single dish and interferometric simulations and, using transfer learning, on real data. Our R-Net model’s precision is approximately $90{{\ \rm per\ cent}}$ better than the current MeerKAT flagger at $80{{\ \rm per\ cent}}$ recall and has a 35 per cent higher F1-score with no additional performance cost. We further highlight the effectiveness of transfer learning from a model initially trained on simulated MeerKAT data and fine-tuned on real, human-flagged, KAT-7 data. Despite the wide differences in the nature of the two telescope arrays, the model achieves an AUC of 0.91, while the best model without transfer learning only reaches an AUC of 0.67. We consider the use of phase information in our models but find that without calibration the phase adds almost no extra information relative to amplitude data only. Our results strongly suggest that deep learning on simulations, boosted by transfer learning on real data, will likely play a key role in the future of RFI flagging of radio astronomy data.

Unraveling the Physics of Quasar Jets: Optical Polarimetry and Implications for the X-ray Emission Process

Since the launch of Chandra twenty years ago, one of the greatest mysteries surrounding Quasar Jets is the production mechanism for their extremely high X-ray luminosity. Two mechanisms have been proposed. In the first view, the X-ray emission is inverse-Comptonized CMB photons. This view requires a jet that is highly relativistic (bulk Lorentz factor >20–40) on scales of hundreds of kiloparsecs, and a jet that is comparably or more powerful than the black hole’s Eddington luminosity. The second possibility is synchrotron emission from a high-energy population of electrons. This requires a much less powerful jet that does not need to be relativistically beamed, but it imposes other extreme requirements, namely the need to accelerate particles to >100 TeV energies at distances of hundreds of kiloparsecs from the active nucleus. We are exploring these questions using a suite of observations from a diverse group of telescopes, including the Hubble Space Telescope (HST), Chandra X-ray Observatory (CXO), Fermi Gamma-ray Space Telescope and various radio telescope arrays. Our results strongly favor the hypothesis that the X-ray emission is synchrotron radiation from a separate, high-energy electron population. We discuss the observations, results and new questions brought up by these surprising results. We investigate the physical processes and magnetic field structure that may help to accelerate particles to such extreme energies.

Deuterated methyl mercaptan (CH3SD): Laboratory rotational spectroscopy and search toward IRAS 16293–2422 B

Methyl mercaptan (also known as methanethiol), CH3SH, has been found in the warm and dense parts of high- as well as low- mass star-forming regions. The aim of the present study is to obtain accurate spectroscopic parameters of the S-deuterated methyl mercaptan CH3SD to facilitate astronomical observations by radio telescope arrays at (sub)millimeter wavelengths. We have measured the rotational spectrum associated with the large-amplitude internal rotation of the methyl group of methyl mercaptan using an isotopically enriched sample in the 150−510 GHz frequency range using the Köln millimeter wave spectrometer. The analysis of the spectra has been performed up to the second excited torsional state. We present modeling results of these data with the RAM36 program. CH3SD was searched for, but not detected, in data from the Atacama Large Millimeter/submillimeter Array (ALMA) Protostellar Interferometric Line Survey (PILS) of the deeply embedded protostar IRAS 16293−2422. The derived upper limit corresponds to a degree of deuteration of at most ∼18%.

The Cherenkov Telescope Array Science Goals and Current Status

The Cherenkov Telescope Array (CTA) is the major ground-based gamma-ray observatory planned for the next decade and beyond. Consisting of two large atmospheric Cherenkov telescope arrays (one in the southern hemisphere and one in the northern hemisphere), CTA will have superior angular resolution, a much wider energy range, and approximately an order of magnitude improvement in sensitivity, as compared to existing instruments. The CTA science programme will be rich and diverse, covering cosmic particle acceleration, the astrophysics of extreme environments, and physics frontiers beyond the Standard Model. This paper outlines the science goals for CTA and covers the current status of the project.

Millimeter-wave spectroscopy and modeling of 1,2-butanediol

Context. The continuously enhanced sensitivity of radioastronomical observations allows the detection of increasingly complex organic molecules. These systems often exist in a large number of isomers leading to very congested spectra. Aims. We explore the conformational space of 1,2-butanediol and provide sets of spectroscopic parameters to facilitate searches for this molecule at millimeter wavelengths. Methods. We recorded the rotational spectrum of 1,2-butanediol in the 59.6–103.6 GHz frequency region (5.03–2.89 mm) using a free-jet millimeter-wave absorption spectrometer, and we analyzed the properties of 24 isomers with quantum chemical calculations. Selected measured transition lines were then searched on publicly available ALMA Band 3 data on IRAS 16293-2422 B. Results. We assigned the spectra of six conformers, namely aG′Ag, gG′Aa, g′G′Ag, aG′G′g, aG′Gg, and g′GAa, to yield the rotational constants and centrifugal distortion constants up to the fourth or sixth order. The most intense signal belong to the aG′Ag species, that is the global minimum. Search for the corresponding 30x,30 − 29x,29 transition lines toward IRAS 16293-2422 B was unsuccessful. Conclusions. Our present data will be helpful for identifying 1,2-butanediol at millimeter wavelengths with radio telescope arrays. Among all possible conformers, first searches should be focused on the aG′Ag conformers in the 400–800 GHz frequency spectral range.