Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Synthese von Steuerprogrammen durch Klassifizierungslernen am Beispiel der Stabilisierungssteuerung von Nachrichtensatelliten

Verfahren des Maschinellen Lernens haben heute eine Reife erreicht, die zu ersten erfolgreichen industriellen Anwendungen geführt hat. In der Prozessdiagnose und -steuerung ermöglichen Lernverfahren die Klassifikation und Bewertung von Betriebszuständen, d.h. eine Grobmodellierung eines Prozesses, wenn dieser nicht oder nur teilweise mathematisch beschreibbar ist. Ausserdem gestatten Lernverfahren die automatische Generierung von Klassifizierungsprozeduren, die deterministisch abgearbeitet werden und daher für die Belange der Echtzeitdiagnose und -steuerung u.U. zeiteffektiver als Inferenzmechanismen auf logischer bzw. Produktionsregelbasis sind, da letztere immer mit zeitaufwendigen Suchprozessen verbunden sind

Synthese von Steuerprogrammen durch Klassifizierungslernen am Beispiel der Stabilisierungssteuerung von Nachrichtensatelliten

Verfahren des Maschinellen Lernens haben heute eine Reife erreicht, die zu ersten erfolgreichen industriellen Anwendungen geführt hat. In der Prozessdiagnose und -steuerung ermöglichen Lernverfahren die Klassifikation und Bewertung von Betriebszuständen, d.h. eine Grobmodellierung eines Prozesses, wenn dieser nicht oder nur teilweise mathematisch beschreibbar ist. Ausserdem gestatten Lernverfahren die automatische Generierung von Klassifizierungsprozeduren, die deterministisch abgearbeitet werden und daher für die Belange der Echtzeitdiagnose und -steuerung u.U. zeiteffektiver als Inferenzmechanismen auf logischer bzw. Produktionsregelbasis sind, da letztere immer mit zeitaufwendigen Suchprozessen verbunden sind

Radiopurity treatment of the intelligent PMTs for OSIRIS

The Jiangmen Underground Neutrino Observatory (JUNO), currently under construction in Southern China, is expected to yield new insights regarding the mass hierarchy of neutrinos. In order to reach the design sensitivity for detecting reactor and solar neutrinos, a radiopure liquid scintillator is required.The Online Scintillator Internal Radioactivity Investigation System (OSIRIS) allows an on-line quality evaluation of the scintillator during filling of the JUNO detector. It features a 20 ton liquid scintillator target monitored by 76 intelligent photomultiplier tubes (iPMTs).Because contamination with radioactive isotopes might prevent OSIRIS to reach its target sensitivity, the detector has to be cleaned prior to installation. For removing potential production residues from the iPMTs, a cleaning procedure has been developed. In this talk, the construction of the facility using ultra pure water at RWTH Aachen University will be presented

Potential for a precision measurement of solar pppp neutrinos in the Serappis Experiment

The Serappis (SEarch for RAre PP-neutrinos In Scintillator) project aims at a precision measurement of the flux of solar $pp$ neutrinos on the few-percent level. Such a measurement will be a relevant contribution to the study of solar neutrino oscillation parameters and a sensitive test of the solar luminosity constraint. The concept of Serappis relies on a small organic liquid scintillator detector ($\sim$20 m$^3$) with excellent energy resolution ($\sim$2.5 % at 1 MeV), low internal background and sufficient shielding from surrounding radioactivity. This can be achieved by a minor upgrade of the OSIRIS facility at the site of the JUNO neutrino experiment in southern China. To go substantially beyond current accuracy levels for the $pp$ flux, an organic scintillator with ultra-low $^{14}$C levels (below $10^{-18}$) is required. The existing OSIRIS detector and JUNO infrastructure will be instrumental in identifying suitable scintillator materials, offering a unique chance for a low-budget high-precision measurement of a fundamental property of our Sun that will be otherwise hard to access

Potential for a precision measurement of solar pp neutrinos in the Serappis experiment

The Serappis (SEarch for RAre PP-neutrinos In Scintillator) project aims at a precision measurement of the flux of solar pp neutrinos on the few-percent level. Such a measurement will be a relevant contribution to the study of solar neutrino oscillation parameters and a sensitive test of the equilibrium between solar energy output in neutrinos and electromagnetic radiation (solar luminosity constraint). The concept of Serappis relies on a small organic liquid scintillator detector (∼20 m$^3$) with excellent energy resolution (∼2.5% at 1 MeV), low internal background and sufficient shielding from surrounding radioactivity. This can be achieved by a minor upgrade of the OSIRIS facility at the site of the JUNO neutrino experiment in southern China. To go substantially beyond current accuracy levels for the pp flux, an organic scintillator with ultra-low $^{14}$C levels (below 10$^{−18}$) is required. The existing OSIRIS detector andJUNO infrastructure will be instrumental in identifying suitable scintillator materials, offering a unique chance for a low-budget high-precision measurement of a fundamental property of our Sun that will be otherwise hard to access

Potential for a precision measurement of solar pppp neutrinos in the Serappis Experiment

The Serappis (SEarch for RAre PP-neutrinos In Scintillator) project aims at a precision measurement of the flux of solar $pp$ neutrinos on the few-percent level. Such a measurement will be a relevant contribution to the study of solar neutrino oscillation parameters and a sensitive test of the solar luminosity constraint. The concept of Serappis relies on a small organic liquid scintillator detector ($\sim$20 m$^3$) with excellent energy resolution ($\sim$2.5 % at 1 MeV), low internal background and sufficient shielding from surrounding radioactivity. This can be achieved by a minor upgrade of the OSIRIS facility at the site of the JUNO neutrino experiment in southern China. To go substantially beyond current accuracy levels for the $pp$ flux, an organic scintillator with ultra-low $^{14}$C levels (below $10^{-18}$) is required. The existing OSIRIS detector and JUNO infrastructure will be instrumental in identifying suitable scintillator materials, offering a unique chance for a low-budget high-precision measurement of a fundamental property of our Sun that will be otherwise hard to access

Damping signatures at JUNO, a medium-baseline reactor neutrino oscillation experiment

International audienceWe study damping signatures at the Jiangmen Underground Neutrino Observatory (JUNO), a medium-baseline reactor neutrino oscillation experiment. These damping signatures are motivated by various new physics models, including quantum decoherence, ν$_{3}$ decay, neutrino absorption, and wave packet decoherence. The phenomenological effects of these models can be characterized by exponential damping factors at the probability level. We assess how well JUNO can constrain these damping parameters and how to disentangle these different damping signatures at JUNO. Compared to current experimental limits, JUNO can significantly improve the limits on τ$_{3}$/m$_{3}$ in the ν$_{3}$ decay model, the width of the neutrino wave packet σ$_{x}$, and the intrinsic relative dispersion of neutrino momentum σ$_{rel}$.[graphic not available: see fulltext