Algorithmic boundedness-from-below conditions for generic scalar potentials

Checking that a scalar potential is bounded from below (BFB) is an ubiquitous and notoriously difficult task in many models with extended scalar sectors. Exact analytic BFB conditions are known only in simple cases. In this work, we present a novel approach to algorithmically establish the BFB conditions for any polynomial scalar potential. The method relies on elements of multivariate algebra, in particular, on resultants and on the spectral theory of tensors, which is being developed by the mathematical community. We give first a pedagogical introduction to this approach, illustrate it with elementary examples, and then present the working Mathematica implementation publicly available at GitHub. Due to the rapidly increasing complexity of the problem, we have not yet produced ready-to-use analytical BFB conditions for new multi-scalar cases. But we are confident that the present implementation can be dramatically improved and may eventually lead to such results

Algorithmic Boundedness-From-Below Conditions for Generic Scalar Potentials

Checking that a scalar potential is bounded from below (BFB) is an ubiquitous and notoriously difficult task in many models with extended scalar sectors. Exact analytic BFB conditions are known only in simple cases. In this work, we present a novel approach to algorithmically establish the BFB conditions for any polynomial scalar potential. The method relies on elements of multivariate algebra, in particular, on resultants and on the spectral theory of tensors, which is being developed by the mathematical community. We give first a pedagogical introduction to this approach, illustrate it with elementary examples, and then present the working Mathematica implementation publicly available at GitHub. Due to the rapidly increasing complexity of the problem, we have not yet produced ready-to-use analytical BFB conditions for new multi-scalar cases. But we are confident that the present implementation can be dramatically improved and may eventually lead to such results.Comment: 27 pages, 2 figures; v2: added reference

SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors

The increasing attention paid to urban air quality modeling places higher requirements on urban air quality datasets. This article introduces a new urban air quality dataset—the SmartAQnet2020 dataset—which has a large span and high resolution in both time and space dimensions. The dataset contains 248,572,003 observations recorded by over 180 individual measurement devices, including ceilometers, Radio Acoustic Sounding System (RASS), mid- and low-cost stationary measuring equipment equipped with meteorological sensors and particle counters, and low-weight portable measuring equipment mounted on different platforms such as trolley, bike, and UAV

SmartAQnet – neuer smarter Weg zur räumlichen Erfassung von Feinstaub

Mit dem Forschungsprojekt SmartAQnet wird ein smarter Weg zur räumlichen Bestimmung von Feinstaub untersucht und am Modellstandort Augsburg erprobt. Forschungsansatz ist die Erfassung und Zusammenführung unterschiedlicher Qualitäten von Feinstaubmesswerten mit Fernerkundungsdaten. Feinstaubmesswerte können hierbei von Jedermann (z. B. mit Ultra-Low-Cost-Sensoren) bis hin zu offiziellen Messnetzen (mit hochpräziser Messtechnik) in die Datenarchitektur eingespeist werden. Eine neuartige Internet-of-Things-Analyseplattform soll Daten zur Anwendung sowohl für Planer als auch für den Bürger bieten, welche der nachhaltigen Gesundheitsvorsorge dienen können (z. B. App für eine luftqualitätsbezogene Navigation)

IceCube Search for Neutrinos Coincident with Compact Binary Mergers from LIGO-Virgo's First Gravitational-Wave Transient Catalog

Using the IceCube Neutrino Observatory, we search for high-energy neutrino emission coincident with compact binary mergers observed by the LIGO and Virgo gravitational wave (GW) detectors during their first and second observing runs. We present results from two searches targeting emission coincident with the sky localization of each gravitational wave event within a 1000 second time window centered around the reported merger time. One search uses a model-independent unbinned maximum likelihood analysis, which uses neutrino data from IceCube to search for point-like neutrino sources consistent with the sky localization of GW events. The other uses the Low-Latency Algorithm for Multi-messenger Astrophysics, which incorporates astrophysical priors through a Bayesian framework and includes LIGO-Virgo detector characteristics to determine the association between the GW source and the neutrinos. No significant neutrino coincidence is seen by either search during the first two observing runs of the LIGO-Virgo detectors. We set upper limits on the time-integrated neutrino emission within the 1000 second window for each of the 11 GW events. These limits range from 0.02-0.7 $\mathrm{GeV~cm^{-2}}$. We also set limits on the total isotropic equivalent energy, $E_{\mathrm{iso}}$, emitted in high-energy neutrinos by each GW event. These limits range from 1.7 $\times$ 10$^{51}$ - 1.8 $\times$ 10$^{55}$ erg. We conclude with an outlook for LIGO-Virgo observing run O3, during which both analyses are running in real time