Source Spectrum Research Articles

Detection of pulsed X-ray emission from the isolated neutron star candidate eRASSU J131716.9–402647

The X-ray source eRASSU J131716.9–402647 was recently identified from observations with Spectrum Roentgen Gamma (SRG)/eROSITA as a promising X-ray dim isolated neutron star (XDINS) candidate on the premise of a soft energy distribution, absence of catalogued counterparts, and a high X-ray-to-optical flux ratio. Here, we report the results of a multi-wavelength observational campaign with XMM-Newton, NICER and the FORS2 instrument at the ESO-VLT. We found in both the XMM-Newton and NICER data that the X-ray emission is strongly pulsed at a period of 12.757 s (pulsed fraction pf = (29.1 ± 2.6)% in the 0.2–2 keV band). The pulse profile is double-humped, and the pulsed fraction increases with energy. The XMM-Newton and NICER epochs allow us to derive a 3σ upper limit of Ṗ ≤ 8 × 10−11 s s−1 on the spin-down rate of the neutron star. The source spectrum is well described by a purely thermal continuum, either a blackbody with kT ∼ 95 eV or a magnetised neutron star atmosphere model with kT ∼ 35 eV. Similarly to other thermally emitting isolated neutron stars, we found in either case strong deviations from the continuum, a broad absorption feature at energy ∼260 eV and a narrow one around 590 eV. The FORS2 instrument at ESO-VLT has not detected the optical counterpart (mR > 27.5 mag, 5σ detection limit), implying an X-ray-to-optical flux ratio of 104 at least. The properties of eRASSU J131716.9–402647 strongly resemble those of a highly magnetised isolated neutron star and favour an XDINS or high-B pulsar nature.

Sinusoidal transmission grating spectrometer for extreme ultraviolet measurement.

Spectral measurements play a vital role in understanding laser-plasma interactions. The ability to accurately measure the spectrum of radiation sources is crucial for unraveling the underlying physics. In this article, we introduce a novel approach that significantly enhances the efficiency of binary sinusoidal transmission grating spectrometers . The grating was tailored especially for Extreme Ultraviolet (EUV) measurements. The new design, High Contrast Sinusoidal Transmission Grating (HCSTG), not only suppresses high diffraction orders and retains the advantageous properties of previous designs but also exhibits a fourfold improvement in first-order efficiency. In addition, the HCSTG offers exceptional purity in the first order due to effectively eliminating half-order contributions from the diffraction pattern. The HCSTG spectrometer was employed to measure the emission of laser-produced Sn plasma in the 1-50nm spectral range, achieving a spectral resolution of λ/Δλ = 60. We provide a comprehensive analysis comparing the diffraction patterns of different STGs, highlighting the advantages offered by the HCSTG design. This novel, efficiency-enhanced HCSTG spectrometer opens up new possibilities for accurate and sensitive EUV spectral measurements.

CosmiXs: cosmic messenger spectra for indirect dark matter searches

The energy spectra of particles produced from dark matter (DM) annihilation or decay are one of the fundamental ingredients to calculate the predicted fluxes of cosmic rays and radiation searched for in indirect DM detection. We revisit the calculation of the source spectra for annihilating and decaying DM using the Vincia shower algorithm in Pythia to include QED and QCD final state radiation and diagrams for the EW corrections with massive bosons, not present in the default Pythia shower model. We take into account the spin information of the particles during the entire EW shower and the off-shell contributions from massive gauge bosons. Furthermore, we perform a dedicated tuning of the Vincia and Pythia parameters to LEP data on the production of pions, photons, and hyperons at the Z resonance and discuss the underlying uncertainties. To enable the use of our results in DM studies, we provide the tabulated source spectra for the most relevant cosmic messenger particles, namely antiprotons, positrons, γ rays and the three neutrino flavors, for all the fermionic and bosonic channels and DM masses between 5 GeV and 100 TeV, on github.

On the anomalous cosmic-ray helium spectra during consecutive solar minima

The anomalous cosmic rays have been studied for about fifty years. Through theoretical and numerical models, we can learn how and where they are originating. When Voyager 1 and 2 spacecraft observed the solar wind termination shock, the main efforts were focused on try to explain the source spectrum and the acceleration mechanism. Nevertheless, there is another feature of the spectrum that need a better understanding, and it is related with the peak intensity in the energy spectrum, that occurred at different energies in consecutive solar minima. Qualitatively, it can be explained in terms of drifts and its relation with the acceleration process. In the past some works have been partially successful to explain the observations. In this paper we do another effort to explain the shift in the peak intensity of anomalous cosmic ray energy spectrum. We use a numerical model which includes diffusive shock acceleration, and the effects of the heliosheath. The present work analyzes the role played by different factors in the energy shift of the peak intensity between two successive minima, in particular the location of the region of observations with respect to the shock, the heliospheric distance, the effects of turbulence on the reduction of weak scattering drifts, as well as a possible latitudinal dependence in the ion injection on the shock.

Ages, metallicity, and α-enhancement of the globular cluster populations in NGC 3311

Aims. We aim to investigate the stellar population properties, ages, and metal content of the globular clusters (GCs) in NGC 3311, the central galaxy of the Hydra I cluster, to better constrain its evolution history. Methods. We used integral-field spectroscopic data from the Multi-Unit Spectroscopic Explorer (MUSE) to identify 680 sources in the central region of NGC 3311 and extract their 1D spectra. An analysis of these sources in terms of morphologies, radial velocities, and emission lines allowed us to narrow down our selection to 49 bona fide GC candidates. We split these candidates into two groups depending on their projected distance to the galaxy center (R), namely inner (R ≤ 20″) and outer (R > 20″) GCs. We stacked the extracted 1D spectra of the inner and outer GC populations to increase the signal-to-noise ratios (S/Ns) of the resulting spectra and hence allow full-spectrum fitting. In addition, we also created a stacked spectrum of all GCs in NGC 3311 and one of the two most central GC candidates. Using the code pPXF, we performed a stellar population analysis on the four stacked 1D spectra, obtaining mass-weighted integrated ages, metallicities, and [α/Fe] abundances. Results. All GCs are old, with ages ≥13.5 Gyr, and they have super-solar metallicities. Looking at the color distribution, we find that the inner ones tend to be redder and more metal-rich than the outer ones. This is consistent with the two-phase formation scenario. Looking at the full-spectral fitting results, at face value the outer GCs have a larger [α/Fe] ratio, which is in line with what is found for the stars that dominate the surface brightness profile at the same radii. However, the values for outer and inner GCs are consistent within the uncertainties. Interestingly, the stacked spectrum of the two most central GCs appears to have the highest metallicity and [α/Fe], although with larger uncertainties. They might be associated with the core progenitor of NGC 3311. Conclusions. The careful analysis of the MUSE-extracted 1D spectra for compact sources in the center of NGC 3311 and its halo indicate that a significant fraction (28%) do display emission lines. Once they are removed, the selected bona fide GC candidates are old (≥13.5 Gyr) and have super-solar metallicities (slightly larger in the center) and [α/Fe] (slightly larger for the outer GCs). Stellar population analyses of the extracted spectra do not support the presence of an intermediate (a few Gigayears) GC population in the central 40 arcsec (10 kpc) radius of NGC 3311.

TABDeep: A two-level action branch architecture-based deep reinforcement learning for distributed sub-tree scheduling of online multicast sessions in EON

The surge in demand for multimedia applications has brought a great pressure on network bandwidth resources. In order to improve the efficiency of bandwidth resource usage and ensure the transmission quality of multicast sessions, it is very urgent to effectively schedule online multicast sessions. To do so, in this paper, we study the distributed sub-tree scheduling problem of online multicast sessions in elastic optical network (EON). First, we model the problem as a Markov Decision Process (MDP) by defining state, action and reward. Second, a two-level action branch architecture-based deep reinforcement learning (TABDeep) algorithm is proposed to realize the destination node grouping, source node selection, route establishment and spectrum assignment of multicast sessions. Finally, to test the superiority of TABDeep, we construct a series of simulation experiments to compare TABDeep with a link-aware distributed steiner sub-tree benchmark algorithm (LA-DSST). The experimental results confirm that TABDeep performs better than LA-DSST in reducing the blocking probability of the session.

Measurements of AmBe and PuC spectra using EJ309 and stilbene scintillators

Two organic scintillators (EJ309 and stilbene) with their different detection chains and elaborate software were used to measure neutron spectra of AmBe and PuC sources. Method of shadow cone ensures minimization of scattered neutron influence. To separate neutrons and γ, a modern method of pulse shape discrimination was employed using fast digitizers. Calibration was performed by γ sources and three different methods for the identification of the Compton edge. Spectrometric systems also used different light output functions and unfolding methods. The same spectra were calculated using the MCNP6 code and the JENDL-5 library. The measured and calculated results were mutually compared, and also with the published results available in the literature. Generally, the results agree on the main peaks of neutron spectra but differ in their abundance. The lower limit for the ability to distinguish between neutrons and γ in spectrometry with organic scintillators was found at about 1.5 MeV.

Cs and Br tuning to achieve ultralow-hysteresis and high-performance indoor triple cation perovskite solar cell with low-cost carbon-based electrode

With high efficacy for electron-photon conversion under low light, perovskite materials show great potential for indoor solar cell applications to power small electronics for internet of things (IoTs). To match the spectrum of an indoor LED light source, triple cation perovskite composition was varied to adjust band gap values via Cs and Br tuning. However, increased band gaps lead to morphology, phase instability, and defect issues. 10% Cs and 30% Br strike the right balance, leading to low-cost carbon-based devices with the highest power conversion efficiency (PCE) of 31.94% and good stability under low light cycles. With further improvement in device stack and size, functional solar cells with the ultralow hysteresis index (HI) of 0.1 and the highest PCE of 30.09% with an active area of 1cm2 can be achieved. A module from connecting two such cells in series can simultaneously power humidity and temperature sensors under 1000 lux.

A simple and efficient approach to unsupervised instance matching and its application to linked data of power plants

Knowledge graphs store and link semantically annotated data about real-world entities from a variety of domains and on a large scale. The World Avatar is based on a dynamic decentralised knowledge graph and on semantic technologies to realise complex cross-domain scenarios. Accurate computational results for such scenarios require the availability of complete, high-quality data. This work focuses on instance matching — one of the subtasks of automatically populating the knowledge graph with data from a wide spectrum of external sources. Instance matching compares two data sets and seeks to identify instances (data, records) referring to the same real-world entity. We introduce AutoCal, a new instance matcher which does not require labelled data and runs out of the box for a wide range of domains without tuning method-specific parameters. AutoCal achieves results competitive to recently proposed unsupervised matchers from the field of Machine Learning. We also select an unsupervised state-of-the-art matcher from the field of Deep Learning for a thorough comparison. Our results show that neither AutoCal nor the state-of-the-art matcher is superior regarding matching quality while AutoCal has only moderate hardware requirements and runs 2.7 to 60 times faster. In summary, AutoCal is specifically well-suited to be used in an automated environment. We present its prototypical integration into the World Avatar and apply AutoCal to the domain of power plants which is relevant for practical environmental scenarios of the World Avatar.

Powerful Radio Sources in the Southern Sky. III. First Results of the Optical Spectroscopic Campaign

We recently built the G4Jy-3CRE catalog of extragalactic radio sources. This catalog lists 264 powerful radio sources selected with similar criteria to those of the revised Third Cambridge Catalog, but visible from the Southern Hemisphere. A literature search revealed that 119 sources in the G4Jy-3CRE catalog (i.e., 45%) lack a firm spectroscopic redshift measurement. Here, we present a campaign aimed at acquiring optical spectra of G4Jy-3CRE sources and measuring their redshifts. We used single-slit observations obtained with the Víctor Blanco Telescope, the New Technology Telescope, the Southern Astrophysical Research Telescope, and the 2.1 m telescope of the Observatorio Astronómico Nacional at San Pedro Mártir, Mexico. In addition, we analyzed Very Large Telescope/MUSE archival observations. From these observations, we report the spectra and redshifts of 93 sources, 42 of which are the first optical spectra and redshift determinations for the respective sources. With our new data, approximately 71% of the sources in the G4Jy-3CRE catalog now have firm spectroscopic redshift measurements. This data set will be the basis of our future analysis of the optical properties of the G4Jy-3CRE catalog.

Induced seismic activity and source parameter characteristics in the Datong coal mine, China

To clarify the activity patterns and source characteristics of coal mining–induced microseismicity, this study analyzed the spatial distribution characteristics of microseismic events in the Datong coal mining area based on records from the regional digital seismic network. We conducted a detailed characterization of the depth distribution characteristics of microseismic events using the double-difference localization method. Additionally, the source parameters, including corner frequency ( fc), source rupture radius ( r), seismic moment ( M0), source radiated energy ( Es), and stress drop (Δσ), were calculated for 136 mine-induced earthquakes with magnitudes ranging from ML1.3 to ML3.2. The results show that ML ≥ 2.0 mining-induced seismic events occur mainly within numerous microfractures in the Datong mining area. The depth of the seismic sources in the mining area is concentrated at 200∼500 m, with significant north–south differences and a close correlation with the mining depth. The displacement spectra of microseismic sources show agreement with the Brune source model [Formula: see text] attenuation pattern. As M0 gradually increases, r, Δσ, and Es show an increasing trend, while fc gradually decreases, exhibiting characteristics similar to those of tectonic earthquakes. Compared to tectonic earthquakes, coal mining-induced earthquakes have lower corner frequencies and stress drop levels mainly because mining activities alter the originally stable geological structure and stress state, leading to weakened rock strength, decreased elastic modulus, and shallower source depths. These factors contribute to the reduction in corner frequencies. As mining operations continue, microfracturing occurs in the coal and surrounding rock mass, intensifying the dynamic instability of the rock mass that was already under high stress conditions. This situation triggers larger-magnitude, mining-induced seismic events under lower stress conditions.

Securing Tomorrow: The Intersection of AI, Data, and Analytics in Fraud Prevention

Aim: This research investigates the interconnections among Data Analytics, Artificial Intelligence, and other cutting-edge technologies to enhance comprehension of fraud prevention. The advantages of integrating machine learning and data analytics into artificial intelligence systems for industry-wide fraud detection and prevention are examined in this study. Study Design: My approach involved conducting an extensive examination of existing literature and analysing numerous case studies to gather information on the role of artificial intelligence, data, and analytics in fraud prevention. Place and Duration of the Study: A broad spectrum of academic, corporate, and governmental sources is utilised to supply the research study with its international scope. This study examines publications and developments from 2019 to 2023. Methodology: The research procedure incorporated an exhaustive literature review. This assessment was composed of academic journals, conference proceedings, and official publications. A qualitative analysis was conducted to assess the data, identify commonalities, and evaluate the strengths and weaknesses of AI fraud protection solutions. A more comprehensive examination of practical implementations was facilitated by case studies, which enhanced comprehension of fraud prevention strategies propelled by AI. Results: The research revealed important findings concerning the various ways in which analytics, data, and artificial intelligence can be implemented to prevent fraudulent activities. An examination of comparisons between generative AI for social engineering, credit card analytics, and cyber-physical security for Internet of Things (IoT) networks illuminated the merits and demerits of different Artificial Intelligence (AI) approaches. Conclusion: According to the findings of the study, AI, data, and analytics may alter system defences against fraud. The above-mentioned results underscore the significance of flexible fraud prevention strategies. Constant collaboration, innovative technology, and ongoing investigation are required to remain ahead of evolving fraud techniques. The paper concludes by emphasising the significance of future challenges and orientations.

Modeling the Multiwavelength Spectral Energy Distributions of the Fermi-4LAC Bright Flat-spectrum Radio Quasars

In this paper, we present a long-term multiwavelength investigation focusing on 12 distinct samples of Fermi-4LAC bright flat-spectrum radio quasars (FSRQs). Detailed variability and spectral analyses of γ-ray, X-ray, and ultraviolet/optical data obtained by the Fermi Large Area Telescope, the Swift X-ray Telescope, and the Swift Ultraviolet and Optical Telescope were performed over a period of about 14 yr, spanning from 2008 October to 2022 October. These analyses provide insights into characterizing the variations within different activity states. To efficiently reproduce the multiwavelength simultaneous/quasi-simultaneous spectral energy distributions (SEDs) of the samples, we propose a novel approach for constraining the model parameters. By analyzing the parameters of the energy spectral curvature (β), the peak frequency (ν pk), the peak luminosity (L pk), the Compton dominance parameter (A C), and the variability timescale (t var) in different activity states, we can estimate the values of the jet radiation region parameters for the samples. Subsequently, we utilize the synchrotron-self-Compton and external Compton processes, employing a logarithmic-parabolic spectral shape to approximate the observed spectra of the sample sources, while considering the induced regime for the physical parameters. The model results show that: (1) by effectively reproducing SEDs in various active states of bright FSRQs, the parameters within the emission region were reasonably constrained; (2) compared to other active states, the emission region of the jet exhibits a reduced radius during the high state, while the magnetic field strength increases during the low state; and (3) for bright FSRQs in a high-activity state, there is an enhancement of the Doppler factor, often exhibiting a tendency toward energy equipartition.

Soft X-Ray Energy Spectra in the Wide-field Galactic Disk Area Revealed with HaloSat

We analyzed data from HaloSat observations for five fields in the Galactic disk located far away from the Galactic center (135° < l < 254°) to understand the nature of soft X-ray energy emission in the Galactic disk. The fields have 14° diameter and were selected to contain no significant high-flux X-ray sources. All five HaloSat soft X-ray energy spectra (0.4–7 keV with energy resolution of < 100 eV below 1 keV) show a possibility of the presence of unresolved high-temperature plasma in the Galactic disk (UHTPGD) with a temperature of 0.8–1.0 keV and an emission measure of (8–11) × 10−4 cm−6 pc in addition to the soft X-ray diffuse background components mainly studied at higher Galactic latitudes (solar wind charge exchange emission, Local Hot Bubble, Milky Way halo emission, and the cosmic X-ray background). This suggests that the UHTPGD is present across the whole Galactic disk. We also observed UHTPGD emission in a region with no bright sources in an XMM-Newton field contained within one of the HaloSat fields. The temperature and emission measure are consistent with those measured with HaloSat. Moreover, the stacked spectra of the X-ray pointlike sources and near-infrared-identified point sources such as stars in the XMM-Newton field also show a spectral feature similar to the UHTPGD emission. This suggests that the UHTPGD may partly originate from pointlike sources such as stars.

EROSITA studies of the Carina nebula

Context. During the first four all-sky surveys eRASS:4, which was carried out from December 2019 to 2021, the extended Roentgen Survey with an Imaging Telescope Array (eROSITA) on board the Spektrum-Roentgen-Gamma (Spektr-RG, SRG) observed the Galactic H II region, the Carina nebula. Aims. We analysed the eRASS:4 data to study the distribution and spectral properties of the hot interstellar plasma and the bright stellar sources in the Carina nebula. Methods. The spectral extraction regions of the diffuse emission were defined based on the X-ray spectral morphology and multi-wavelength data. The spectra were fit with a combination of thermal and non-thermal emission models. The X-ray bright point sources in the Carina nebula are the colliding wind binary η Car, several O stars, and Wolf–Rayet (WR) stars. We extracted the spectra of the brightest stellar sources, which can be well fit with a multi-component thermal plasma model. Results. The spectra of the diffuse emission in the brighter parts of the Carina nebula are well reproduced by two thermal models, a lower-temperature component (~0.2 keV) and a higher-temperature component (0.6–0.8 keV). An additional non-thermal component dominates the emission above ~1 keV in the Central region around η Car and the other massive stars. Significant orbital variation in the X-ray flux was measured for η Car, WR 22, and WR 25. η Car requires an additional time-variable thermal component in the spectral model, which is associated with the wind-wind collision zone. Conclusions. Properties such as temperature, pressure, and luminosity of the X-ray emitting plasma in the Carina nebula derived from the eROSITA data are consistent with theoretical calculations of emission from superbubbles. This confirms that the X-ray emission is caused by the hot plasma inside the Carina nebula that has been shocked-heated by the stellar winds of the massive stars, in particular, of η Car.

Determining the Origin of Very-high-energy Gamma Rays from Galactic Sources by Future Neutrino Observations

Recently, the Large High Altitude Air Shower Observatory (LHAASO) identified 12 gamma-ray sources emitting gamma rays with energies above 100 TeV, making them potential PeV cosmic-ray accelerators (PeVatrons). Neutrino observations are crucial in determining whether the gamma-ray radiation process is of hadronic or leptonic origin. In this paper, we study three detected sources, LHAASO J1908+0621, LHAASO J2018+3651, and LHAASO J2032+4102, which are also the most promising Galactic high-energy neutrino candidate sources with the lowest pretrial p-value based on the stacking searches testing for excess neutrino emission by the IceCube Neutrino Observatory. We study the lepto-hadronic scenario for the observed multiband spectra of these LHAASO sources considering the possible counterpart source of the LHAASO sources. The very-high-energy gamma rays are entirely attributed to the hadronic contribution; therefore, the most optimistic neutrino flux can be derived. Then, we evaluate the statistical significance (p-value) as a function of the observation time of IceCube and the next-generation IceCube-Gen2 neutrino observatory, respectively. Our results tend to disfavor that all gamma rays above 100 GeV from LHAASO J1908+0621 are of purely hadronic origin based on current IceCube observations, but the purely hadronic origin of gamma rays above 100 TeV is still possible. By IceCube-Gen2, the origin of gamma rays above 100 TeV from LHAASO J1908+0621 can be further determined at a 5σ significance level within a running time of ∼3 yr. For LHAASO J2018+3651 and LHAASO J2032+4102, the required running time of IceCube-Gen2 is ∼10 yr (3σ) and ∼10 yr (5σ), respectively. Future observations by the next-generation neutrino telescope will be crucial to understanding the particle acceleration and radiation processes inside the sources.

Between the Cosmic-Ray “Knee” and the “Ankle”: Contribution from Star Clusters

We show that massive, young star clusters may be possible candidates that can accelerate Galactic cosmic rays (CRs) in the range of 107–109 GeV (between the “knee” and “ankle”). Various plausible scenarios, such as acceleration at the wind termination shock and supernova shocks inside these young star clusters, have been proposed, since it is difficult to accelerate particles up to the 107–109 GeV range in the standard paradigm of CR acceleration in supernova remnants. We consider a model for the production of different nuclei in CRs from massive stellar winds using the observed distribution of young star clusters in the Galactic plane. We present a detailed calculation of CR transport in the Galaxy, taking into account the effect of diffusion, interaction losses during propagation, and particle reacceleration by old supernova remnants to determine the all-particle CR spectrum. Using the maximum energy estimate from the Hillas criterion, we argue that a young, massive star cluster can accelerate protons up to a few tens of PeV. Upon comparison with the observed data, our model requires a CR source spectrum with an exponential cutoff of 5 × 107 Z GeV (50 Z PeV) from these clusters, together with a CR injection fraction of ∼5% of the wind kinetic energy. We discuss the possibility of achieving these requirements in star clusters, as well as the associated uncertainties, in the context of considering star clusters as the natural accelerator of the “second component” of Galactic CRs.

Classification and parameterization of a large Gaia sample of white dwarfs using XP spectra

Context. The latest Gaia data release in July 2022, DR3, in addition to the refinement of the astrometric and photometric parameters from DR2, added a number of important data products to those available in earlier releases, including radial velocity data, information on stellar multiplicity, and XP spectra of a selected sample of stars. Gaia has proved to be an important search tool for white dwarf stars, which are readily identifiable from their absolute G magnitudes as low luminosity objects in the Hertzsprung–Russell (H–R) diagram. Each data release has yielded large catalogs of white dwarfs, containing several hundred thousand objects, far in excess of the numbers known from all previous surveys (∼40 000). While the normal Gaia photometry (G, GBP, and GRP bands) and astrometry can be used to identify white dwarfs with high confidence, it is much more difficult to parameterize the stars and determine the white dwarf spectral type from this information alone. Observing all stars in these catalogs with follow-up spectroscopy and photometry is also a huge logistical challenge with current facilities. Aims. The availability of the XP spectra and synthetic photometry presents an opportunity for a more detailed spectral classification and measurement of the effective temperature and surface gravity of Gaia white dwarfs. Methods. A magnitude limit of G &lt; 17.6 was applied to the routine production of XP spectra for Gaia sources, which would have excluded most white dwarfs. Therefore, we created a catalog of 100 000 high-quality white dwarf identifications for which XP spectra were processed, with a magnitude limit of G &lt; 20.5. Synthetic photometry was computed for all these stars, from the XP spectra, in Johnson, SDSS, and J-PAS, published as the Gaia Synthetic Photometry Catalog – White Dwarfs (GSPC-WD). We took this catalog and applied machine learning techniques to provide a classification of all the stars from the XP spectra. We have then applied an automated spectral fitting program, with χ-squared minimization, to measure their physical parameters (effective temperature and log g) from which we could estimate the white dwarf masses and radii. Results. We present the results of this work, demonstrating the power of being able to classify and parameterize such a large sample of ≈100 000 stars. We describe what we can learn about the white dwarf population from this dataset. We also explored the uncertainties in the process and the limitations of the dataset.

Ground-Based Mobile Measurements to Track Urban Methane Emissions from Natural Gas in 12 Cities across Eight Countries.

To mitigate methane emission from urban natural gas distribution systems, it is crucial to understand local leak rates and occurrence rates. To explore urban methane emissions in cities outside the U.S., where significant emissions were found previously, mobile measurements were performed in 12 cities across eight countries. The surveyed cities range from medium size, like Groningen, NL, to large size, like Toronto, CA, and London, UK. Furthermore, this survey spanned across European regions from Barcelona, ES, to Bucharest, RO. The joint analysis of all data allows us to focus on general emission behavior for cities with different infrastructure and environmental conditions. We find that all cities have a spectrum of small, medium, and large methane sources in their domain. The emission rates found follow a heavy-tailed distribution, and the top 10% of emitters account for 60-80% of total emissions, which implies that strategic repair planning could help reduce emissions quickly. Furthermore, we compare our findings with inventory estimates for urban natural gas-related methane emissions from this sector in Europe. While cities with larger reported emissions were found to generally also have larger observed emissions, we find clear discrepancies between observation-based and inventory-based emission estimates for our 12 cities.

Source parameters and scaling relationships of stress drop for shallow crustal seismic events in Western Europe

For an ω2-source model, moment-based estimates of the stress drop are obtained by combining corner frequency and seismic moment source parameters. Therefore, the moment-based estimates of the stress drop are informative about the amount of energy radiated at high frequencies by dynamic rupture processes. This study aims to systematically estimate such stress drop from the harmonized dataset at the European scale and to characterize the distributions of the stress drop for application in future stochastic simulations. We analyze the seismological records associated with shallow crustal seismic events that occurred in Western Europe between January 1990 and May 2020. We processed 220,000 high-quality records and isolated the contributions of the source, site, and path contributions using the Generalized Inversion Technique. The source parameters, including the corner frequency, moment magnitude, and stress drop, of 6135 seismic events are calculated. The events processed are mainly tectonic events (e.g., earthquakes of the central Italy 2009–2016 sequence), although non-tectonic events associated with the Groningen gas field and mining activities in Western Europe are also included in the analysis. The impact of different attenuation models and reference site choices are evaluated. Most of the obtained source spectra follow the standard ω2-model except for a few events where the data sampling considered does not allow an effective spectral decomposition. The resulting stress drop shows a positive correlation with moment magnitude between 3 and 4, and a self-similarity for magnitudes greater than 4 with a mean stress drop of 13.8 MPa.