Abstracts of Interest
Selected by:
Kirsty and Sabrina
Abstract: 1907.12121
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Title:On the TeV Halo Fraction in gamma-ray bright Pulsar Wind Nebulae
(Submitted on 28 Jul 2019)
Abstract: The discovery of extended TeV emission around the Geminga and PSR B0656+14 pulsars, with properties consistent with free particle propagation in the interstellar medium (ISM), has sparked considerable discussion on the possible presence of such halos in other systems. Here we make an assessment of the current TeV source population associated with energetic pulsars, in terms of size and estimated energy density. Based on two alternative estimators we conclude that a large majority of the known TeV sources have emission originating in the zone energetically and dynamically dominated by the pulsar (i.e. the pulsar wind nebula), rather than from a halo of particles diffusing in to the ISM. Furthermore, whilst the number of established halos will surely increase in the future, we find that it is unlikely that such halos contribute significantly to the total TeV $\gamma$-ray luminosity from electrons accelerated in PWN.
Abstract: 1907.10197
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Title:Exploring the nature of 2HWC J2006+341 with HAWC and Fermi-LAT
(Submitted on 24 Jul 2019)
Abstract: The High Altitude Water Cherenkov (HAWC) gamma-ray observatory is carrying out a detailed survey of the northern sky at TeV energies. 2HWC J2006+341 is a newly discovered source reported by the point source search in the 2HWC HAWC Observatory Gamma Ray Catalog. Using $\sim$1038 days of HAWC data we carried out a detailed analysis of the region revealing extended emission. No emission has been detected by other TeV instruments at the location of 2HWC J2006+341. We also analyzed publicly available data from the \textit{Fermi}-LAT that show for the first time the existence of an extended GeV source with a hard spectrum in the region of 2HWC J2006+341. Combined modeling of the data from HAWC and the \textit{Fermi}-LAT allowed us to explore different scenarios for the origin of 2HWC J2006+341.
Abstract: 1907.09357
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Title:The calibration of the first Large-Sized Telescope of the Cherenkov Telescope Array
(Submitted on 22 Jul 2019)
Abstract: The Cherenkov Telescope Array (CTA) represents the next generation of very high-energy gamma-ray observatory, which will provide broad coverage of gamma rays from 20 GeV to 300 TeV with unprecedented sensitivity. CTA will employ three different sizes of telescopes, and the Large-Sized Telescopes (LSTs) of 23-m diameter dish will provide the sensitivity in the lowest energies down to 20 GeV. The first LST prototype has been inaugurated in October 2018 at La Palma (Canary Islands, Spain) and has entered the commissioning phase. The camera of the LST consists of 265 PMT modules. Each module is equipped with seven high-quantum-efficiency Photomultiplier Tubes (PMTs), a slow control board, and a readout board. Ensuring high uniformity and precise characterization of the camera is the key aspects leading to the best performance and low systematic uncertainty of the LST cameras. Therefore, prior to the installation on site, we performed a quality check of all PMT modules. Moreover, the absolute calibration of light throughput is essential to reconstruct the amount of light received by the telescope. The amount of light is affected by the atmosphere, by the telescope optical system and camera, and can be calibrated using the ring-shaped images produced by cosmic-ray muons. In this contribution, we will show the results of off-site quality control of PMT modules and on-site calibration using muon rings. We will also highlight the status of the development of Silicon Photomultiplier modules that could be considered as a replacement of PMT modules for further improvement of the camera.
Abstract: 1907.09816
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Title:Through the Looking-Glass with ALICE into the Quark-Gluon Plasma: A New Test for Hadronic Interaction Models Used in Air Shower Simulations
(Submitted on 23 Jul 2019)
Abstract: Recently, the ALICE Collaboration reported an enhancement of the yield ratio of strange and multi-strange hadrons to charged pions as a function of multiplicity at mid-rapidity in proton-proton, proton-lead, lead-lead, and xenon-xenon scattering. ALICE observations provide a strong indication that a quark-gluon plasma is partly formed in high multiplicity events of both small and large colliding systems. Motivated by ALICE's results, we propose a new test for hadronic interaction models used for analyzing ultra-high-energy-cosmic-ray (UHECR) collisions with air nuclei. The test is grounded in the almost equal column-energy density in UHECR-air collisions and lead-lead collisions at the LHC. We applied the test to post-LHC event generators describing hadronic phenomena of UHECR scattering and show that these QCD Monte Carlo-based codes must be retuned to accommodate the strangeness enhancement relative to pions observed in LHC data.
Abstract: 1907.10146
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Title:Status of the Large Size Telescopes of the Cherenkov Telescope Array
(Submitted on 19 Jul 2019)
Abstract: The Cherenkov Telescope Array (CTA) will consist of two arrays of Imaging Atmospheric Cherenkov Telescopes (IACTs) at the northern and southern hemispheres. CTA will feature IACTs with mirrors of three different sizes optimized to cover different energy ranges. The proposed sub-arrays of four Large Size Telescopes (LST) at CTA-North and CTA-South target the lowest energy range between around 20 GeV and 100 GeV. Thanks to their low weight of around 110 tons the LSTs can move by 180 deg in azimuth in 20 seconds for Gamma Ray Burst (GRB) follow-up. An LST has a tessellated parabolic mirror of 23 m diameter equipped with a system of actuators to correct for gravity-induced deformations during data taking. Its low-weight 2 ton camera at the prime focus has a 4.5 deg diameter, 1855 high QE PMTs and an embedded readout with 1 GSps sampling speed designed for data acquisition rates exceeding 10 kHz. A fully equipped LST has been installed at the CTA-North site in 2018 and is expected to be finished commissioning during 2019. The remaining three LSTs in the north will be installed by 2022. We will review the status of the LSTs, describe the installation of the first LST and report on the first results of the commissioning tests.
Abstract: 1907.10480
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Title:Deep Learning for Energy Estimation and Particle Identification in Gamma-ray Astronomy
(Submitted on 23 Jul 2019)
Abstract: Deep learning techniques, namely convolutional neural networks (CNN), have previously been adapted to select gamma-ray events in the TAIGA experiment, having achieved a good quality of selection as compared with the conventional Hillas approach. Another important task for the TAIGA data analysis was also solved with CNN: gamma-ray energy estimation showed some improvement in comparison with the conventional method based on the Hillas analysis. Furthermore, our software was completely redeveloped for the graphics processing unit (GPU), which led to significantly faster calculations in both of these tasks. All the results have been obtained with the simulated data of TAIGA Monte Carlo software; their experimental confirmation is envisaged for the near future.
Abstract: 1907.11222
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Title:Decaying dark matter at IceCube and its signature on High Energy gamma experiments
(Submitted on 25 Jul 2019)
Abstract: The origin of neutrino flux observed in IceCube is still mainly unknown. Typically two flux components are assumed, namely: atmospheric neutrinos and an unknown astrophysical term. In principle the latter could also contain a top-down contribution coming for example from decaying dark matter. In this case one should also expect prompt and secondary gammas as well. This leads to the possibility of a multimessenger analysis based on the simultaneous comparison of the Dark Matter hypothesis both with neutrino and high energy gamma rays data. In this paper, we analyze, for different decaying Dark Matter channels, the 7.5 years IceCube HESE data, and compare the results with previous exclusion limits coming from Fermi data. Finally, we test whether the Dark Matter hypothesis could be further scrutinised by using forthcoming high energy gamma rays experiments.
Abstract: 1907.11720
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Title:OH maser emission in the THOR survey of the northern Milky Way
(Submitted on 26 Jul 2019)
Abstract: Context: OH masers trace diverse physical processes, from the expanding envelopes around evolved stars to star-forming regions or supernovae remnants. Aims: We identify the ground-state OH masers at 18cm wavelength in the area covered by ``The HI/OH/Recombination line survey of the Milky Way (THOR)''. We present a catalogue of all OH maser features and their possible associated environments. Methods: The THOR survey covers longitude and latitude ranges of 14.3<l<66.8 and b<1.25 deg. All OH ground state lines at 1612, 1665, 1667 and 1720MHz have been observed, employing the Very Large Array. The spatial resolution of the data varies between 12.5'' and 19'', the spectral resolution is 1.5km/s, and the rms sensitivity of the data is ~10mJy/beam per channel. Results: We identify 1585 individual maser spots distributed over 807 maser sites. Based on different criteria from spectral profiles to literature comparison, we try to associate the maser sites with astrophysical source types. Approximately 51\% of the sites exhibit the double-horned 1612MHz spectra typically emitted from the expanding shells of evolved stars. The separations of the two main velocity features of the expanding shells typically vary between 22 and 38km/s. In addition to this, at least 20% of the maser sites are associated with star-forming regions. While the largest fraction of 1720MHz maser spots (21 out of 53) is associated with supernova remnants, a significant fraction of the 1720MHz maser spots (17) are also associated with star-forming regions. We present comparisons to the thermal 13CO(1-0) emission as well as to other surveys of class II CH3OH and H3O maser emission. The catalogue attempts to present associations to astrophysical sources where available, and the full catalogue is available in electronic form.
Abstract: 1907.09500
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Title:deepCR: Cosmic Ray Rejection with Deep Learning
(Submitted on 22 Jul 2019)
Abstract: Cosmic ray (CR) identification and removal are critical components of imaging and spectroscopic reduction pipelines involving solid-state detectors. We present deepCR, a deep learning based framework for cosmic ray (CR) identification and subsequent image inpainting based on the predicted CR mask. To demonstrate the effectiveness of our framework, we have trained and evaluated models on Hubble Space Telescope ACS/WFC images of sparse extragalactic fields, globular clusters, and resolved galaxies. We demonstrate that at a reasonable false positive rate of 0.5%, deepCR achieves close to 100% detection rates in both extragalactic and globular cluster fields, and 91% in resolved galaxy fields, which is a significant improvement over current state-of-the-art method, LACosmic. Compared to a well-threaded CPU implementation of LACosmic, deepCR mask predictions runs up to 6.5 times faster on CPU and 90 times faster on GPU. For image inpainting, mean squared error of deepDR predictions are 20 times lower in globular cluster fields, 5 times lower in resolved galaxy fields, and 2.5 times lower in extragalactic fields, compared to the best performing non-neural technique. We present our framework and trained models as an open-source Python project, with a simple-to-use API.
Abstract: 1907.09226
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Title:Steepening of Cosmic Ray Spectra in Shocks with Varying Magnetic Field Direction
(Submitted on 22 Jul 2019)
Abstract: Cosmic ray (CR) spectra, both measured upon their arrival at the Earth's atmosphere and inferred from the emission in supernova remnants (SNRs), appear to be significantly steeper than the ``standard'' diffusive shock acceleration (DSA) theory predicts. Although the reconstruction of the primary spectra introduces an additional steepening due to propagation effects, there is a growing consensus in the CR community that these corrections fall short to explain the newest high-precision data. Using 2D hybrid simulations, we investigate a new mechanism that may steepen the spectrum during the acceleration in SNR shocks.
Most of the DSA treatments are limited to homogeneous shock environments. To investigate whether inhomogeneity effects can produce the necessary extra steepening, we assume that the magnetic field changes its angle along the shock front. The rationale behind this approach is the strong dependence of the DSA efficiency upon the field angle, $\theta_\mathrm{Bn}$. Our results show that the variation of shock obliquity along its face results in a noticeable steepening of the DSA spectrum. Compared to simulations of quasi-parallel shocks, we observe an increase of the spectral index by $\Delta q=0.1-0.15$. Possible extrapolation of the limited simulation results to more realistic SNR conditions are briefly considered.
Abstract: 1903.09162
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Title:The ALMA Spectroscopic Survey in the Hubble Ultra Deep Field: Evolution of the molecular gas in CO-selected galaxies
(Submitted on 21 Mar 2019 (v1), last revised 22 Jul 2019 (this version, v2))
Abstract: We analyze the interstellar medium properties of a sample of sixteen bright CO line emitting galaxies identified in the ALMA Spectroscopic Survey in the Hubble Ultra Deep Field (ASPECS) Large Program. This CO$-$selected galaxy sample is complemented by a couple of additional CO line emitters in the UDF that are identified based on their MUSE optical spectroscopic redshifts. The ASPECS CO$-$selected galaxies cover a larger range of star-formation rates and stellar masses compared to literature CO emitting galaxies at $z>1$ for which scaling relations have been established previously. Most of ASPECS CO-selected galaxies follow these established relations in terms of gas depletion timescales and gas fractions as a function of redshift, as well as the star-formation rate-stellar mass relation (`galaxy main sequence'). However, we find that $\sim30\%$ of the galaxies (5 out of 16) are offset from the galaxy main sequence at their respective redshift, with $\sim12\%$ (2 out of 16) falling below this relationship. Some CO-rich galaxies exhibit low star-formation rates, and yet show substantial molecular gas reservoirs, yielding long gas depletion timescales. Capitalizing on the well-defined cosmic volume probed by our observations, we measure the contribution of galaxies above, below, and on the galaxy main sequence to the total cosmic molecular gas density at different lookback times. We conclude that main sequence galaxies are the largest contributor to the molecular gas density at any redshift probed by our observations (z$\sim$1$-$3). The respective contribution by starburst galaxies above the main sequence decreases from z$\sim$2.5 to z$\sim$1, whereas we find tentative evidence for an increased contribution to the cosmic molecular gas density from the passive galaxies below the main sequence.
Abstract: 1907.09934
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Title:Interpolation of turbulent magnetic fields and its consequences on diffusive cosmic ray propagation
(Submitted on 23 Jul 2019)
Abstract: Numerical simulations of the propagation of charged particles through magnetic fields solving the equation of motion often leads to the usage of an interpolation in case of discretely defined magnetic fields, typically given on a homogeneous grid structure. However, the interpolation method influences the magnetic field properties on the scales of the grid spacing and the choice of interpolation routine can therefore change the result. At the same time, it provides an impact, i.e.\ error, on the spatial particle distribution.
We compare three different interpolation routines -- trilinear, tricubic and nearest neighbor interpolation -- in the case of turbulent magnetic fields and show that there is no benefit in using trilinear interpolation. We show that in comparison, the nearest neighbor interpolation provides the best performance, i.e.\ requires least CPU time and results in the smallest error. In addition, we optimize the performance of an algorithm that generates a continuous grid-less turbulent magnetic field by more than an order of magnitude. This continuous method becomes practicable for the simulation of large particle numbers and its accuracy is only limited by the used number of wave-modes. We show that by using more than 100 wave-modes the diffusive behavior of the spatial particle distribution in form of the diffusion coefficient is determined with an error less than a few percentage.
Abstract: 1907.10088
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Title:New Insights into Uncertainties in the Relic Neutrino Background and Effects from the Nuclear Equation of State
(Submitted on 19 Jul 2019)
Abstract: We review the computation of and associated uncertainties in the current understanding of the relic neutrino background due to core-collapse supernovae, black hole formation and neutron-star merger events. We consider the current status of uncertainties due to the nuclear equation of state (EoS), the progenitor masses, the source supernova neutrino spectrum, the cosmological star formation rate, the stellar initial mass function, neutrino oscillations, and neutrino self-interactions. We summarize the current viability of future neutrino detectors to distinguish the nuclear EoS and the temperature of supernova neutrinos via the detected relic supernova neutrino spectrum.
Abstract: 1907.10893
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Title:Carpet results on astrophysical gamma rays above 100 TeV
(Submitted on 25 Jul 2019)
Abstract: Carpet is an air-shower array at Baksan, Russia, equipped with a large-area muon detector, which makes it possible to separate primary photons from hadrons. We report first results of the search for primary photons with energies E>100 TeV. The experiment's ongoing upgrade and future sensitivity are also discussed.
Abstract: 1907.11109
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Title:Classifying Exoplanet Candidates with Convolutional Neural Networks: Application to the Next Generation Transit Survey
(Submitted on 25 Jul 2019)
Abstract: Vetting of exoplanet candidates in transit surveys is a manual process, which suffers from a large number of false positives and a lack of consistency. Previous work has shown that Convolutional Neural Networks (CNN) provide an efficient solution to these problems. Here, we apply a CNN to classify planet candidates from the Next Generation Transit Survey (NGTS). For training datasets we compare both real data with injected planetary transits and fully-simulated data, as well as how their different compositions affect network performance. We show that fewer hand labelled lightcurves can be utilised, while still achieving competitive results. With our best model, we achieve an AUC (area under the curve) score of $(95.6\pm{0.2})\%$ and an accuracy of $(88.5\pm{0.3})\%$ on our unseen test data, as well as $(76.5\pm{0.4})\%$ and $(74.6\pm{1.1})\%$ in comparison to our existing manual classifications. The neural network recovers 13 out of 14 confirmed planets observed by NGTS, with high probability. We use simulated data to show that the overall network performance is resilient to mislabelling of the training dataset, a problem that might arise due to unidentified, low signal-to-noise transits. Using a CNN, the time required for vetting can be reduced by half, while still recovering the vast majority of manually flagged candidates. In addition, we identify many new candidates with high probabilities which were not flagged by human vetters.