Machine learning applications for the study of AGN physical properties using photometric observations

We investigate the physical nature of Active Galactic Nuclei using machine learning tools. We show that the redshift $z$, the bolometric luminosity $L_{\rm Bol}$, the central mass of the supermassive black hole $M_{\rm BH}$, the Eddington ratio $\lambda_{\rm Edd}$ as well as the AGN class (obscured or unobscured) can be reconstructed through multi-wavelength photometric observations only. A Support Vector Regression (SVR) ML-model is trained on 7616 of spectroscopically observed AGN from the SPIDERS-AGN survey, previously cross-matched with soft X-ray observations (from ROSAT or XMM), WISE mid-infrared photometry, and optical photometry from SDSS $ugriz$ filters. We build a catalogue of 21364 AGN to be reconstructed with the trained SVR: for 9944 sources, we found archival redshift measurements. All AGN are classified as either Type 1/2 using a Random Forest (RF) algorithm on a subset of known sources. All known photometric measurement uncertainties are incorporated using a simulation-based approach. We present the reconstructed catalogue of 21364 AGN with redshifts ranging from $0 < z < 2.5$. $z$ estimations are made for 11420 new sources, with an outlier rate within 10%. Type 1/2 AGN can be identified with respective efficiencies of 88% and 93%: the estimated classification of all sources is given in the dataset. $L_{\rm Bol}$, $M_{\rm BH}$, and $\lambda_{\rm Edd}$ values are given for 16907 new sources with their estimated error. These results have been made publicly available. The release of this catalogue will advance AGN studies by presenting key parameters of the accretion history of 6 dex in luminosity over a wide range of $z$. Similar applications of ML techniques using photometric data only will be essential in the future, with large datasets from eROSITA, JSWT and the VRO poised to be released in the next decade.Comment: 20 pages, 24 figures, submitted to A&

Measurement of low-energy cosmic-ray electron and positron spectra at 1 AU with the AESOP-Lite spectrometer

We report on a new measurement of the cosmic ray (CR) electron and positron spectra in the energy range of 20 MeV -- 1 GeV. The data were taken during the first flight of the balloon-borne spectrometer AESOP-Lite (Anti Electron Sub Orbital Payload), which was flown from Esrange, Sweden, to Ellesmere Island, Canada, in May 2018. The instrument accumulated over 130 hours of exposure at an average altitude of 3 g.cm$^{-2}$ of residual atmosphere. The experiment uses a gas Cherenkov detector and a magnetic spectrometer, consisting of a permanent dipole magnet and silicon strip detectors (SSDs), to identify particle type and measure the rigidity. Electrons and positrons were detected against a background of protons and atmospheric secondary particles. The primary cosmic ray spectra of electrons and positrons, as well as the re-entrant albedo fluxes, were extracted between 20 MeV -- 1 GeV during a positive solar magnetic polarity epoch. The positron fraction below 100 MeV appears flat, suggesting diffusion dominated solar modulation at low rigidity. The all-electron spectrum is presented and compared with models from a heliospheric numerical transport code.Comment: 21 pages, 13 figure

Fabrication of low-cost, large-area prototype Si(Li) detectors for the GAPS experiment

A Si(Li) detector fabrication procedure has been developed with the aim of satisfying the unique requirements of the GAPS (General Antiparticle Spectrometer) experiment. Si(Li) detectors are particularly well-suited to the GAPS detection scheme, in which several planes of detectors act as the target to slow and capture an incoming antiparticle into an exotic atom, as well as the spectrometer and tracker to measure the resulting decay X-rays and annihilation products. These detectors must provide the absorption depth, energy resolution, tracking efficiency, and active area necessary for this technique, all within the significant temperature, power, and cost constraints of an Antarctic long-duration balloon flight. We report here on the fabrication and performance of prototype 2"-diameter, 1-1.25 mm-thick, single-strip Si(Li) detectors that provide the necessary X-ray energy resolution of $\sim$4 keV for a cost per unit area that is far below that of previously-acquired commercial detectors. This fabrication procedure is currently being optimized for the 4"-diameter, 2.5 mm-thick, multi-strip geometry that will be used for the GAPS flight detectors.Comment: Accepted for publication at Nuclear Instrumentation and Methods A, 12 pages, 11 figure

Non-standard neutrino interactions in IceCube

Non-standard neutrino interactions (NSI) may arise in various types of new physics. Their existence would change the potential that atmospheric neutrinos encounter when traversing Earth matter and hence alter their oscillation behavior. This imprint on coherent neutrino forward scattering can be probed using high-statistics neutrino experiments such as IceCube and its low-energy extension, DeepCore. Both provide extensive data samples that include all neutrino flavors, with oscillation baselines between tens of kilometers and the diameter of the Earth. DeepCore event energies reach from a few GeV up to the order of 100 GeV - which marks the lower threshold for higher energy IceCube atmospheric samples, ranging up to 10 TeV. In DeepCore data, the large sample size and energy range allow us to consider not only flavor-violating and flavor-nonuniversal NSI in the μ−τ sector, but also those involving electron flavor. The effective parameterization used in our analyses is independent of the underlying model and the new physics mass scale. In this way, competitive limits on several NSI parameters have been set in the past. The 8 years of data available now result in significantly improved sensitivities. This improvement stems not only from the increase in statistics but also from substantial improvement in the treatment of systematic uncertainties, background rejection and event reconstruction

In-situ estimation of ice crystal properties at the South Pole using LED calibration data from the IceCube Neutrino Observatory

The IceCube Neutrino Observatory instruments about 1 km3 of deep, glacial ice at the geographic South Pole using 5160 photomultipliers to detect Cherenkov light emitted by charged relativistic particles. A unexpected light propagation effect observed by the experiment is an anisotropic attenuation, which is aligned with the local flow direction of the ice. Birefringent light propagation has been examined as a possible explanation for this effect. The predictions of a first-principles birefringence model developed for this purpose, in particular curved light trajectories resulting from asymmetric diffusion, provide a qualitatively good match to the main features of the data. This in turn allows us to deduce ice crystal properties. Since the wavelength of the detected light is short compared to the crystal size, these crystal properties do not only include the crystal orientation fabric, but also the average crystal size and shape, as a function of depth. By adding small empirical corrections to this first-principles model, a quantitatively accurate description of the optical properties of the IceCube glacial ice is obtained. In this paper, we present the experimental signature of ice optical anisotropy observed in IceCube LED calibration data, the theory and parametrization of the birefringence effect, the fitting procedures of these parameterizations to experimental data as well as the inferred crystal properties.</p

Mechanical design of the optical modules intended for IceCube-Gen2

IceCube-Gen2 is an expansion of the IceCube neutrino observatory at the South Pole that aims to increase the sensitivity to high-energy neutrinos by an order of magnitude. To this end, about 10,000 new optical modules will be installed, instrumenting a fiducial volume of about 8 km3. Two newly developed optical module types increase IceCube’s current sensitivity per module by a factor of three by integrating 16 and 18 newly developed four-inch PMTs in specially designed 12.5-inch diameter pressure vessels. Both designs use conical silicone gel pads to optically couple the PMTs to the pressure vessel to increase photon collection efficiency. The outside portion of gel pads are pre-cast onto each PMT prior to integration, while the interiors are filled and cast after the PMT assemblies are installed in the pressure vessel via a pushing mechanism. This paper presents both the mechanical design, as well as the performance of prototype modules at high pressure (70 MPa) and low temperature (−40∘C), characteristic of the environment inside the South Pole ice

The next generation neutrino telescope: IceCube-Gen2

The IceCube Neutrino Observatory, a cubic-kilometer-scale neutrino detector at the geographic South Pole, has reached a number of milestones in the field of neutrino astrophysics: the discovery of a high-energy astrophysical neutrino flux, the temporal and directional correlation of neutrinos with a flaring blazar, and a steady emission of neutrinos from the direction of an active galaxy of a Seyfert II type and the Milky Way. The next generation neutrino telescope, IceCube-Gen2, currently under development, will consist of three essential components: an array of about 10,000 optical sensors, embedded within approximately 8 cubic kilometers of ice, for detecting neutrinos with energies of TeV and above, with a sensitivity five times greater than that of IceCube; a surface array with scintillation panels and radio antennas targeting air showers; and buried radio antennas distributed over an area of more than 400 square kilometers to significantly enhance the sensitivity of detecting neutrino sources beyond EeV. This contribution describes the design and status of IceCube-Gen2 and discusses the expected sensitivity from the simulations of the optical, surface, and radio components

Sensitivity of IceCube-Gen2 to measure flavor composition of Astrophysical neutrinos

The observation of an astrophysical neutrino flux in IceCube and its detection capability to separate between the different neutrino flavors has led IceCube to constraint the flavor content of this flux. IceCube-Gen2 is the planned extension of the current IceCube detector, which will be about 8 times larger than the current instrumented volume. In this work, we study the sensitivity of IceCube-Gen2 to the astrophysical neutrino flavor composition and investigate its tau neutrino identification capabilities. We apply the IceCube analysis on a simulated IceCube-Gen2 dataset that mimics the High Energy Starting Event (HESE) classification. Reconstructions are performed using sensors that have 3 times higher quantum efficiency and isotropic angular acceptance compared to the current IceCube optical modules. We present the projected sensitivity for 10 years of data on constraining the flavor ratio of the astrophysical neutrino flux at Earth by IceCube-Gen2

Direction reconstruction performance for IceCube-Gen2 Radio

The IceCube-Gen2 facility will extend the energy range of IceCube to ultra-high energies. The key component to detect neutrinos with energies above 10 PeV is a large array of in-ice radio detectors. In previous work, direction reconstruction algorithms using the forward-folding technique have been developed for both shallow (≲20 m) and deep in-ice detectors, and have also been successfully used to reconstruct cosmic rays with ARIANNA. Here, we focus on the reconstruction algorithm for the deep in-ice detector, which was recently introduced in the context of the Radio Neutrino Observatory in Greenland (RNO-G)

Deep Learning Based Event Reconstruction for the IceCube-Gen2 Radio Detector

The planned in-ice radio array of IceCube-Gen2 at the South Pole will provide unprecedented sensitivity to ultra-high-energy (UHE) neutrinos in the EeV range. The ability of the detector to measure the neutrino’s energy and direction is of crucial importance. This contribution presents an end-to-end reconstruction of both of these quantities for both detector components of the hybrid radio array (\u27shallow\u27 and \u27deep\u27) using deep neural networks (DNNs). We are able to predict the neutrino\u27s direction and energy precisely for all event topologies, including the electron neutrino charged-current (νe-CC) interactions, which are more complex due to the LPM effect. This highlights the advantages of DNNs for modeling the complex correlations in radio detector data, thereby enabling a measurement of the neutrino energy and direction. We discuss how we can use normalizing flows to predict the PDF for each individual event which allows modeling the complex non-Gaussian uncertainty contours of the reconstructed neutrino direction. Finally, we discuss how this work can be used to further optimize the detector layout to improve its reconstruction performance