Incorporating social objectives in evaluating sustainable fisheries harvest strategy

Fisheries management must take account of environmental sustainability, economic profitability, and social benefits generated by the public resources. The traditional approach of maximum economic yield (MEY), however, is yet to consider social objectives in deriving quantitative quotes. Current MEY evaluation framework would be appropriate if the economic rent was distributed back to the public. If public resources are privatized as corporations, the rent largely flows to the owners of large capital in the fishing industry. This is in stark contrast to the aims of benefiting the community as a whole. In this short paper, we promote a socially responsible framework in decision-making of fisheries management. This approach is beyond the fleet-based MEY approach, for it incorporates fleet profitability, chain profitability, employment, environmental concerns, and broad social benefits, in strict accordance with stock sustainability. Recognizing the needs of fishers, as well as the interests of chain sectors and the broader community, is a vital part of ensuring responsible fishery management and a viable future for Australian fisheries. The established framework will provide open view scenarios and enrich the MEY approaches in fisheries management

A 95 GHz Class I Methanol Maser Survey Toward A Sample of GLIMPSE Point Sources Associated with BGPS Clumps

We report a survey with the Purple Mountain Observatory (PMO) 13.7-m radio telescope for class I methanol masers from the 95 GHz (8_0 - 7_1 A^+) transition. The 214 target sources were selected by combining information from both the Spitzer GLIMPSE and 1.1 mm BGPS survey catalogs. The observed sources satisfy both the GLIMPSE mid-IR criteria of [3.6]-[4.5]>1.3, [3.6]-[5.8]>2.5, [3.6]-[8.0]>2.5 and 8.0 um magnitude less than 10, and also have an associated 1.1 mm BGPS source. Class I methanol maser emission was detected in 63 sources, corresponding to a detection rate of 29% for this survey. For the majority of detections (43), this is the first identification of a class I methanol maser associated with these sources. We show that the intensity of the class I methanol maser emission is not closely related to mid-IR intensity or the colors of the GLIMPSE point sources, however, it is closely correlated with properties (mass and beam-averaged column density) of the BGPS sources. Comparison of measures of star formation activity for the BGPS sources with and without class I methanol masers indicate that the sources with class I methanol masers usually have higher column density and larger flux density than those without them. Our results predict that the criteria log(S_{int})22.1, which utilizes both the integrated flux density (S_{int}) and beam-averaged column density (N_{H_{2}}^{beam}) of the BGPS sources, are very efficient for selecting sources likely to have an associated class I methanol maser. Our expectation is that searches using these criteria will detect 90% of the predicted number of class I methanol masers from the full BGPS catalog (~ 1000), and do so with a high detection efficiency (~75%).Comment: Accepted for publication in ApJ Supplement. 58 pages, 12 figures, 7 table

Gaussian Boson Sampling with Pseudo-Photon-Number Resolving Detectors and Quantum Computational Advantage

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ~ 600 years using exact methods, whereas our quantum computer, Jiuzhang 3.0, takes only 1.27 us to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier ~ 3.1*10^10 years.Comment: submitted on 10 Apri

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