Papers by Mukharbek Organokov
arXiv (Cornell University), Nov 4, 2017
Contents 1 Time-dependent search for neutrino emission from Mrk 421 and Mrk 501 observed by the H... more Contents 1 Time-dependent search for neutrino emission from Mrk 421 and Mrk 501 observed by the HAWC gamma-ray observatory PoS(ICRC2017)946 2 Searching for High Energy Neutrinos detected by ANTARES in coincidence with Gravitational Wave signals observed during LIGO Observation Run O1 PoS(ICRC2017)947 3 Time-dependent search of neutrino emission from bright gamma-ray flaring blazars with the ANTARES telescope PoS(ICRC2017)970 4 Time-dependent search of neutrino emission from X-ray and gamma-ray binaries with the ANTARES telescope PoS(ICRC2017)971 5 Multi-messenger real-time follow-up of transient events with the ANTARES neutrino telescope PoS(ICRC2017)984 6 Multi-wavelength follow-up observations of ANTARES neutrino alerts PoS(ICRC2017)985 7 Search for muon neutrinos from GRBs with the ANTARES neutrino telescope PoS(ICRC2017)988 8 Search for neutrinos from Fast Radio Bursts with ANTARES PoS(ICRC2017)989 9 Search for a correlation between ANTARES high-energy neutrinos and ultra high-energy cosmic rays detected by the Pierre Auger Observatory and the Telescope Array PoS(ICRC2017)990
Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019), 2019
An updated analysis of a targeted search for high-energy neutrinos from Markarian 421 and Markari... more An updated analysis of a targeted search for high-energy neutrinos from Markarian 421 and Markarian 501 is reported. They are two of the closest and brightest extragalactic sources in the TeV band. In contrast to other types of active galactic nuclei, BL Lacs are characterized by rapid and large-amplitude flux variability. Such radio-loud active galactic nuclei are candidate sources of the observed high-energy cosmic rays. Because their jet is collimated to our line of sight, the hadronic interactions with the surrounding medium can produce an accompanying neutrino and gamma-ray flux. The recent detection of high-energy neutrinos from the direction of TXS 0506+056 motivates a search for high-energy neutrinos from blazars with enhanced gamma-ray activity. These two targeted blazars are subject to long-term monitoring campaigns by the HAWC TeV gamma-ray observatory located in Mexico. This contribution presents the latest results of a search and extends previously presented results to a longer period that covers ANTARES data collected between November 2014 and December 2017. The gamma-ray light curves of each source were used to search for temporally correlated neutrinos, potentially produced in hadronic processes.
arXiv: High Energy Astrophysical Phenomena, 2018
ANTARES is the largest high-energy neutrino telescope in the Northern Hemisphere. This contributi... more ANTARES is the largest high-energy neutrino telescope in the Northern Hemisphere. This contribution presents the results of a search, based on the ANTARES data collected over 17 months between November 2014 and April 2016, for high energy neutrino emission in coincidence with TeV $\gamma$-ray flares from Markarian 421 and Markarian 501, two bright BL Lac extragalactic sources highly variable in flux, detected by the HAWC observatory. The analysis is based on an unbinned likelihood-ratio maximization method. The $\gamma$-ray lightcurves (LC) for each source were used to search for temporally correlated neutrinos, that would be produced in pp or p-$\gamma$ interactions. The impact of different flare selection criteria on the discovery neutrino flux is discussed. Plausible neutrino spectra derived from the observed $\gamma$-ray spectra in addition to generic spectra $E^{-2}$ and $E^{-2.5}$ are tested.
Journal of Astronomical Telescopes, Instruments, and Systems, 2021
The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Medi... more The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Mediterranean Sea. The telescopes will detect extraterrestrial and atmospheric neutrinos by means of the incident photons induced by the passage of relativistic charged particles through the seawater as a consequence of a neutrino interaction. The telescopes are configured in a three-dimensional grid of digital optical modules, each hosting 31 photomultipliers. The photomultiplier signals produced by the incident Cherenkov photons are converted into digital information consisting of the integrated pulse duration and the time at which it surpasses a chosen threshold. The digitization is done by means of time to digital converters (TDCs) embedded in the field programmable gate array of the central logic board. Subsequently, a state machine formats the acquired data for its transmission to shore. We present the architecture and performance of the front-end firmware consisting of the TDCs and the state machine. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Journal of Astronomical Telescopes, Instruments, and Systems, 2019
The KM3NeT research infrastructure being built at the bottom of the Mediterranean Sea will host w... more The KM3NeT research infrastructure being built at the bottom of the Mediterranean Sea will host water-Cherenkov telescopes for the detection of cosmic neutrinos. The neutrino telescopes will consist of large volume three-dimensional grids of optical modules to detect the Cherenkov light from charged particles produced by neutrino-induced interactions. Each optical module houses 31 3-inch photomultiplier tubes, instrumentation for calibration of the photomultiplier signal and positioning of the optical module and all associated electronics boards. By design, the total electrical power consumption of an optical module has been capped at seven watts. This paper presents an overview of the front-end and readout electronics system inside the optical module, which has been designed for a 1 ns synchronization between the clocks of all optical modules in the grid during a life time of at least 20 years.
Computer Physics Communications, 2020
The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics s... more The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate
Journal of Instrumentation, 2020
The KM3NeT research infrastructure is currently under construction at two locations in the Medite... more The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.
Proceedings of 35th International Cosmic Ray Conference — PoS(ICRC2017), 2017
This analysis performs cloud classification and segmentation using satellite images. Shallow clou... more This analysis performs cloud classification and segmentation using satellite images. Shallow clouds play a huge role in determining the Earth's climate but poorly represented in climate models. Classification of different types of cloud organizations can improve the physical understanding of these clouds and be substantial for understanding climate change. Murky boundaries between different forms of clouds lead to obstacles in traditional rule-based algorithms cloud features separation. In this analysis, deep learning algorithms are build to identify regions in satellite images that contain certain cloud formations. The dataset used in the analysis is<br> prepared by Max Planck and released on the Kaggle platform. It contains four labels: Fish, Flower, Gravel, Sugar. The cloud segmentation and classification are done using deep learning models. These models led to Top 7% solution in the Kaggle competition. Various improvements of the algorithm are described and results are...
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Papers by Mukharbek Organokov