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  1. Abstract

    While basaltic volcanism is dominant during rifting and continental breakup, felsic magmatism may be a significant component of some rift margins. During International Ocean Discovery Program (IODP) Expedition 396 on the continental margin of Norway, a graphite‐garnet‐cordierite bearing dacitic unit (the Mimir dacite) was recovered in two holes within early Eocene sediments on Mimir High (Site U1570), a marginal high on the Vøring Transform Margin. Here, we present a comprehensive textural, petrological, and geochemical study of the Mimir dacite in order to assess its origin and discuss the geodynamic implications. The major mineral phases (garnet, cordierite, quartz, plagioclase, alkali feldspar) are hosted in a fresh rhyolitic, vesicular, glassy matrix that is locally mingled with sediments. The major element chemistry of garnet and cordierite, the presence of zircon inclusions with inherited cores, and thermobarometric calculations all support an upper crustal metapelitic origin. While most magma‐rich margin models favor crustal anatexis in the lower crust, thermobarometric calculations performed here show that the Mimir dacite was produced at upper‐crustal depths (<5 kbar, 18 km depth) and high temperature (750–800°C) with up to 3 wt% water content. In situ U‐Pb analyses on zircon inclusions give a magmatic crystallization age of 54.6 ± 1.1 Ma, consistent with emplacement that post‐dates the Paleocene‐Eocene Thermal Maximum. Our results suggest that the opening of the Northeast Atlantic was associated with a phase of low‐pressure, high‐temperature crustal anatexis preceding the main phase of magmatism.

     
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    Free, publicly-accessible full text available July 1, 2025
  2. Free, publicly-accessible full text available March 7, 2025
  3. ABSTRACT

    Stringent observational constraints on the subgalactic matter power spectrum would allow one to distinguish between the concordance ΛCDM and the various alternative dark-matter models that predict significantly different properties of mass structure in galactic haloes. Galaxy–galaxy strong gravitational lensing provides a unique opportunity to probe the subgalactic mass structure in lens galaxies beyond the Local Group. Here, we demonstrate the first application of a novel methodology to observationally constrain the subgalactic matter power spectrum in the inner regions of massive elliptical lens galaxies on 1–10 kpc scales from the power spectrum of surface-brightness anomalies in highly magnified galaxy-scale Einstein rings and gravitational arcs. The pilot application of our approach to Hubble Space Telescope (HST/WFC3/F390W) observations of the SLACS lens system SDSS J0252+0039 allows us to place the following observational constraints (at the 99 per cent confidence level) on the dimensionless convergence power spectrum $\Delta ^{2}_{\delta \kappa }$ and the standard deviation in the aperture mass σAM: $\Delta ^{2}_{\delta \kappa }\lt 1$ (σAM < 0.8 × 108 M⊙) on 0.5-kpc scale, $\Delta ^{2}_{\delta \kappa }\lt 0.1$ (σAM < 1 × 108 M⊙) on 1-kpc scale and $\Delta ^{2}_{\delta \kappa }\lt 0.01$ (σAM < 3 × 108 M⊙) on 3-kpc scale. These first upper-limit constraints still considerably exceed the estimated effect of CDM subhaloes. However, future analysis of a larger sample of galaxy–galaxy strong lens systems can substantially narrow down these limits and possibly rule out dark-matter models that predict a significantly higher level of density fluctuations on the critical subgalactic scales.

     
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  4. Abstract

    The repeating fast radio bursts (FRBs) 180916.J0158 and 121102 are visible during periodically occurring windows in time. We consider the constraints on internal magnetic fields and geometries if the cyclical behavior observed for FRB 180916.J0158 and FRB 121102 is due to the precession of magnetars. In order to frustrate vortex line pinning we argue that internal magnetic fields must be stronger than about 1016G, which is large enough to prevent superconductivity in the core and destroy the crustal lattice structure. We conjecture that the magnetic field inside precessing magnetars has three components: (1) a dipole component with characteristic strength ∼ 1014G; (2) a toroidal component with characteristic strength ∼ 1015–1016G that only occupies a modest fraction of the stellar volume; and (3) a disordered field with characteristic strength ∼ 1016G. The disordered field is primarily responsible for permitting precession, which stops once this field component decays away, which we conjecture happens after ∼1000 yr. Conceivably, as the disordered component damps bursting activity diminishes and eventually ceases. We model the quadrupolar magnetic distortion of the star, which is due to its ordered components primarily, as triaxial and very likely prolate. We address the question of whether the spin frequency ought to be detectable for precessing, bursting magnetars by constructing a specific model in which bursts happen randomly in time with random directions distributed in or between cones relative to a single symmetry axis. Within the context of these specific models, we find that there are precession geometries for which detecting the spin frequency is very unlikely.

     
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  5. ABSTRACT

    With unparalleled rotational stability, millisecond pulsars (MSPs) serve as ideal laboratories for numerous astrophysical studies, many of which require precise knowledge of the distance and/or velocity of the MSP. Here, we present the astrometric results for 18 MSPs of the ‘MSPSR$\pi$’ project focusing exclusively on astrometry of MSPs, which includes the re-analysis of three previously published sources. On top of a standardized data reduction protocol, more complex strategies (i.e. normal and inverse-referenced 1D interpolation) were employed where possible to further improve astrometric precision. We derived astrometric parameters using sterne, a new Bayesian astrometry inference package that allows the incorporation of prior information based on pulsar timing where applicable. We measured significant (${>}3\, \sigma$) parallax-based distances for 15 MSPs, including 0.81 ± 0.02 kpc for PSR J1518+4904 – the most significant model-independent distance ever measured for a double neutron star system. For each MSP with a well-constrained distance, we estimated its transverse space velocity and radial acceleration. Among the estimated radial accelerations, the updated ones of PSR J1012+5307 and PSR J1738+0333 impose new constraints on dipole gravitational radiation and the time derivative of Newton’s gravitational constant. Additionally, significant angular broadening was detected for PSR J1643−1224, which offers an independent check of the postulated association between the HII region Sh 2-27 and the main scattering screen of PSR J1643−1224. Finally, the upper limit of the death line of γ-ray-emitting pulsars is refined with the new radial acceleration of the hitherto least energetic γ-ray pulsar PSR J1730−2304.

     
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  6. Abstract

    The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online data quality monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. A real-time autoencoder-based anomaly detection system using semi-supervised machine learning is presented enabling the detection of anomalies in the CMS electromagnetic calorimeter data. A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. The autoencoder-based system is able to efficiently detect anomalies, while maintaining a very low false discovery rate. The performance of the system is validated with anomalies found in 2018 and 2022 LHC collision data. In addition, the first results from deploying the autoencoder-based system in the CMS online data quality monitoring workflow during the beginning of Run 3 of the LHC are presented, showing its ability to detect issues missed by the existing system.

     
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    Free, publicly-accessible full text available June 24, 2025
  7. null (Ed.)
    Annotated IMU sensor data from smart devices and wearables are essential for developing supervised models for fine-grained human activity recognition, albeit generating sufficient annotated data for diverse human activities under different environments is challenging. Existing approaches primarily use human-in-the-loop based techniques, including active learning; however, they are tedious, costly, and time-consuming. Leveraging the availability of acoustic data from embedded microphones over the data collection devices, in this paper, we propose LASO, a multimodal approach for automated data annotation from acoustic and locomotive information. LASO works over the edge device itself, ensuring that only the annotated IMU data is collected, discarding the acoustic data from the device itself, hence preserving the audio-privacy of the user. In the absence of any pre-existing labeling information, such an auto-annotation is challenging as the IMU data needs to be sessionized for different time-scaled activities in a completely unsupervised manner. We use a change-point detection technique while synchronizing the locomotive information from the IMU data with the acoustic data, and then use pre-trained audio-based activity recognition models for labeling the IMU data while handling the acoustic noises. LASO efficiently annotates IMU data, without any explicit human intervention, with a mean accuracy of 0.93 ($\pm 0.04$) and 0.78 ($\pm 0.05$) for two different real-life datasets from workshop and kitchen environments, respectively. 
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