Large Cloud Research Articles

A stochastic gravitational wave background in LISA from unresolved white dwarf binaries in the Large Magellanic Cloud

ABSTRACT The Laser Interferometer Space Antenna (LISA) is expected to detect a wide variety of gravitational wave sources in the mHz band. Some of these signals will elude individual detection, instead contributing as confusion noise to one of several stochastic gravitational-wave backgrounds (SGWBs) – notably including the ‘Galactic foreground’, a loud signal resulting from the superposition of millions of unresolved double white dwarf binaries (DWDs) in the Milky Way. It is possible that similar, weaker SGWBs will be detectable from other DWD populations in the local Universe, including the Large Magellanic Cloud (LMC). We use the Bayesian LISA Inference Package (blip) to investigate the possibility of an anisotropic SGWB generated by unresolved DWDs in the LMC. To do so, we compute the LMC SGWB from a realistic DWD population generated via binary population synthesis, simulate 4 years of time-domain data with blip comprised of stochastic contributions from the LMC SGWB and the LISA detector noise, and analyse this data with blip’s spherical harmonic anisotropic SGWB search. We also consider the case of spectral separation from the Galactic foreground. We present the results of these analyses and show, for the first time, that the unresolved DWDs in the LMC will comprise a significant SGWB for LISA.

Ground-based cloud microphysical observations at Mount Lu in the East Asian monsoon region from 2015 to 2020

Ground-based cloud microphysical observations were continuously conducted at Mount (Mt.) Lu site from 2015 to 2020, which is located in the East Asian monsoon areas of eastern China. The statistical characteristics of cloud microphysics under different meteorological conditions were analyzed by using visibility, cloud droplet and raindrop size distribution data, and meteorological variables. The mean cloud droplet number concentration (Nc), liquid water content (LWC) and effective diameter (De) are 151 cm−3, 0.08 g m−3 and 11.4 μm, respectively. Nc and LWC observed at Mount Lu are lower than the observation results of cloud from other mountain stations all over the world. Broader cloud droplet spectra are correlated with higher temperatures and lower wind speeds. The clouds are classified into nonprecipitating, lightly-raining and raining clouds. Statistics show that lightly-raining and raining clouds account for 66% of all clouds. Nc and LWC of lightly-raining (drizzling) clouds are highest, while spectral width of raining clouds is largest. Spectral dispersion of raining clouds converges to the narrow range of 0.4–0.7. Notably, medium sized cloud droplets (11–40 μm) promote the formation of large cloud droplets (40–50 μm, pre-drizzle size) and drizzle drops which initiate the auto-conversion from condensation to collision-coalescence growth. This study relying on in-situ continuous cloud observation from mountain station are helpful to understand cloud microphysical structures in East Asian monsoon region, and fitting parameters also provide observational evidence for numerical models.

NGC 1856: Using Machine Learning Techniques to Uncover Detailed Stellar Abundances from MUSE Data

We present the first application of the novel approach based on data-driven machine learning methods applied to Multi-Unit Spectroscopic Explorer (MUSE) field data to derive stellar abundances of star clusters. MUSE has been used to target more than 10,000 fields, and it is unique in its ability to study dense stellar fields such as stellar clusters providing spectra for each individual star. We use MUSE data of the extragalactic young stellar cluster NGC 1856, located in the Large Magellanic Cloud (LMC). We present the individual stellar [Fe/H] abundance of 327 cluster members in addition to [Mg/Fe], [Si/Fe], [Ti/Fe], [C/Fe], [Ni/Fe], and [Cr/Fe] abundances of subsample sets. Our results match the LMC abundances obtained in the literature for [Mg/Fe], [Ti/Fe], [Ni/Fe], and [Cr/Fe]. This study is the first to derive [Si/Fe] and [C/Fe] abundances for this cluster. The revolutionary combination of integral-field spectroscopy and data-driven modeling will allow us to understand the chemical enrichment of star clusters and their host galaxies in greater detail expanding our understanding of galaxy evolution.

Properties of the Magellanic Corona

We characterize the Magellanic Corona, the warm gaseous halo around the Large Magellanic Cloud (LMC). The Corona is a key ingredient in the formation of the Magellanic Stream and has recently been observed in high-ion absorption around the LMC. In this work, we present a suite of high-resolution hydrodynamical simulations to constrain its total mass and temperature prior to the infall of the Magellanic Clouds to our Galaxy. We find that the LMC is able to host a stable Corona before and during its approach to the MW through to the present day. With a Magellanic Corona of >2 × 109 M ⊙ at 3 × 105 K, our simulations can reproduce the observed total mass of the neutral and ionized components of the Trailing Stream, the size of the LMC disk, the ionization fractions along the Stream, the morphology of the neutral gas, and the on-sky extent of the ionized gas. The Corona plays an integral role in the survival, morphology, and composition of the Magellanic Clouds and the Trailing Stream.

Deep Hubble Space Telescope Photometry of Large Magellanic Cloud and Milky Way Ultrafaint Dwarfs: A Careful Look into the Magnitude–Size Relation

We present deep Hubble Space Telescope photometry of 10 targets from Treasury Program GO-14734, including six confirmed ultrafaint dwarf (UFD) galaxies, three UFD candidates, and one likely globular cluster. Six of these targets are satellites of, or have interacted with, the Large Magellanic Cloud (LMC). We determine their structural parameters using a maximum-likelihood technique. Using our newly derived half-light radius (r h ) and V-band magnitude (M V ) values in addition to literature values for other UFDs, we find that UFDs associated with the LMC do not show any systematic differences from Milky Way UFDs in the magnitude–size plane. Additionally, we convert simulated UFD properties from the literature into the M V –r h observational space to examine the abilities of current dark matter (DM) and baryonic simulations to reproduce observed UFDs. Some of these simulations adopt alternative DM models, thus allowing us to also explore whether the M V –r h plane could be used to constrain the nature of DM. We find no differences in the magnitude–size plane between UFDs simulated with cold, warm, and self-interacting DM, but note that the sample of UFDs simulated with alternative DM models is quite limited at present. As more deep, wide-field survey data become available, we will have further opportunities to discover and characterize these ultrafaint stellar systems and the greater low surface-brightness universe.

Stellar Variability and Distance Indicators in the Near-infrared in Nearby Galaxies. I. RR Lyrae and Anomalous Cepheids in Draco Dwarf Spheroidal

The Draco Dwarf spheroidal (dSph) galaxy is one of the nearest and the most dark-matter-dominated satellites of the Milky Way. We obtained multiepoch near-infrared (NIR, JHK s ) observations of the central region of Draco dSph covering a sky area of ∼21′ × 21′ using the WIRCam instrument at the 3.6 m Canada–France–Hawaii Telescope. Homogeneous JHK s time-series photometry for 212 RR Lyrae (173 fundamental-mode, 24 first-overtone, and 15 mixed-mode variables) and five Anomalous Cepheids in Draco dSph are presented and used to derive their period–luminosity relations at NIR wavelengths for the first-time. The small scatter of ∼0.05 mag in these empirical relations for RR Lyrae stars is consistent with those in globular clusters and suggests a very small metallicity spread, up to ∼0.2 dex, among these centrally located variables. Based on empirically calibrated NIR period–luminosity–metallicity relations for RR Lyrae in globular clusters, we determined a distance modulus to Draco dSph of μ RRL = 19.557 ± 0.026 mag. The calibrated K s -band period–luminosity relations for Anomalous Cepheids in the Draco dSph and the Large Magellanic Cloud exhibit statistically consistent slopes but systematically different zero points, hinting at possible metallicity dependence of ∼ − 0.3 mag dex−1. Finally, the apparent magnitudes of the tip of the red-giant branch in I and J bands also agree well with their absolute calibrations with the adopted RR Lyrae distance to Draco. Our recommended ∼1.5% precise RR Lyrae distance, D Draco = 81.55 ± 0.98(statistical) ± 1.17(systematic) kpc, is the most accurate and precise distance to Draco dSph galaxy.

The Size–Linewidth Relation and Signatures of Feedback from Quiescent to Active Star Forming Regions in the LMC

To investigate the effects of stellar feedback on the gravitational state of giant molecular clouds (GMCs), we study 12CO and 13CO Atacama Large Millimeter/submillimeter Array maps of nine GMCs distributed throughout the Large Magellanic Cloud (LMC), the nearest star-forming galaxy to our own. We perform noise and resolution matching on the sample, working at a common resolution of 3.″5 (0.85 pc at the LMC distance of 50 kpc), and we use the Spectral Clustering for Molecular Emission Segmentation clustering algorithm to identify discrete substructure, or “clumps.” We supplement these data with three tracers of recent star formation: 8 μm surface brightness, continuum-subtracted Hα flux, and interstellar radiation field energy density inferred from dust emission. The 12CO clumps identified cover a range of 3.6 dex in luminosity-based mass and 2.4 dex in average 8 μm surface brightness, representative of the wide range of conditions of the interstellar medium in the LMC. Our observations suggest evidence for increased turbulence in these clouds. While the turbulent linewidths are correlated with clump surface density, in agreement with previous observations, we find even better correlation with the three star formation activity tracers considered, suggesting stellar energy injection plays a significant role in the dynamical state of the clumps. The excess linewidths we measure do not appear to result from opacity broadening. 12CO clumps are found to be typically less gravitationally bound than 13CO clumps, with some evidence of the kinetic-to-gravitational potential energy ratio increasing with star formation tracers. Further multiline analysis may better constrain the assumptions made in these calculations.

Exploring Molecular Gas toward the Magellanic Bridge

The Magellanic Bridge (MB) is a diffuse gas structure that connects the Large Magellanic Cloud with the Small Magellanic Cloud. The MB is the closest tidal interaction system between two galaxies to the Milky Way. Taking into account that young stellar objects are embedded in such gaseous structure, it is a unique laboratory to investigate gas dynamics and star formation processes in a very low metallicity environment. In this work we present a preview of the results obtained from observations made with the Atacama Pathfinder Experiment telescope toward some regions of the MB. Through the emission of the 12CO J = 2–1 line we characterize the molecular gas of these regions.

Secure and fine-grained access control of electronic health record using SAPCP-ABE technique in cloud

This study explores how Electronic Health Records (EHR) might be transformed in the context of the rapid improvements in cloud computing and IoT technology. But worries about sensitive data security and access management when it moves to large cloud provider networks surface. Even if they are secure, traditional encryption techniques sometimes lack the granularity needed for effective data protection. We suggest the Secure Access Policy – Ciphertext Policy – Attribute-based Encryption (SAPCP-ABE) algorithm as a solution to this problem. This method ensures that only authorized users may access the necessary data while facilitating fine-grained encrypted data exchange. The three main phases of SAPCP-ABE are retrieval and decoding, where the system verifies users’ access restrictions, secure outsourcing that prioritizes critical attributes, and an authenticity phase for early authentication. Performance tests show that SAPCP-ABE is a better scheme than earlier ones, with faster encryption and decryption speeds of 5 and 5.1 seconds for 512-bit keys, respectively. Security studies, numerical comparisons, and implementation outcomes demonstrate our suggested approach’s efficacy, efficiency, and scalability.

Music Curriculum Research Using a Large Language Model, Cloud Computing and Data Mining Technologies

This paper presents a method to enhance the scientific nature of the music curriculum model by integrating a large language model, cloud computing and data mining technology for the analysis of the music teaching curriculum model. To maintain the integrity of the mixing matrix while employing the frequency hopping frequency, the paper suggests dividing the mixing matrix into a series of sub-matrices along the vertical time axis. This approach transforms wideband music signal processing into a narrowband processing problem. Additionally, two hybrid matrix estimation algorithms are proposed in this paper using underdetermined conditions. Furthermore, utilizing the estimated mixing matrix and the detected time-frequency support domain, the paper employs the subspace projection algorithm for underdetermined blind separation of music signals in the time-frequency domain. This procedure, along with the integration of the estimated direction of arrival (DoA), enables the completion of frequency-hopping network station music signal sorting. Extensive simulation teaching demonstrates that the music curriculum model proposed in this paper, based on a large language model, cloud computing and data mining technologies, significantly enhances the quality of modern music teaching.

Thermal X-ray emission in the western half of the LMC superbubble 30 Dor C

ABSTRACT While 30 Dor C is a unique superbubble in the Large Magellanic Cloud for its luminous non-thermal X-ray emission, the thermal X-ray emission it emanates has not yet been thoroughly investigated and well constrained. Based on the separate ∼1 Ms deep XMM–Newton and Chandra observations, we report the discovery of the thermally emitting plasma in some portions of the western half of 30 Dor C. The thermal emission can be reproduced by a collisional-ionization-equilibrium plasma model with an average electron temperature of ∼0.4 keV. We find a significant overabundance of the intermediate-mass elements such as O, Ne, Mg, and Si, which may be indicative of a recent supernova explosion in 30 Dor C. Dynamical properties in combination with the information of the OB association LH 90 suggest that the internal post-main-sequence stars dominate the power of the superbubble and blow it out in the past ∼1 Myr.

Automatic offline-capable smartphone paper-based microfluidic device for efficient biomarker detection of Alzheimer's disease

BackgroundAlzheimer's disease (AD) is a prevalent neurodegenerative disease with no effective treatment. Efficient and rapid detection plays a crucial role in mitigating and managing AD progression. Deep learning-assisted smartphone-based microfluidic paper analysis devices (μPADs) offer the advantages of low cost, good sensitivity, and rapid detection, providing a strategic pathway to address large-scale disease screening in resource-limited areas. However, existing smartphone-based detection platforms usually rely on large devices or cloud servers for data transfer and processing. Additionally, the implementation of automated colorimetric enzyme-linked immunoassay (c-ELISA) on μPADs can further facilitate the realization of smartphone μPADs platforms for efficient disease detection. ResultsThis paper introduces a new deep learning-assisted offline smartphone platform for early AD screening, offering rapid disease detection in low-resource areas. The proposed platform features a simple mechanical rotating structure controlled by a smartphone, enabling fully automated c-ELISA on μPADs. Our platform successfully applied sandwich c-ELISA for detecting the β-amyloid peptide 1–42 (Aβ 1–42, a crucial AD biomarker) and demonstrated its efficacy in 38 artificial plasma samples (healthy: 19, unhealthy: 19, N = 6). Moreover, we employed the YOLOv5 deep learning model and achieved an impressive 97 % accuracy on a dataset of 1824 images, which is 10.16 % higher than the traditional method of curve-fitting results. The trained YOLOv5 model was seamlessly integrated into the smartphone using the NCNN (Tencent's Neural Network Inference Framework), enabling deep learning-assisted offline detection. A user-friendly smartphone application was developed to control the entire process, realizing a streamlined “samples in, answers out” approach. SignificanceThis deep learning-assisted, low-cost, user-friendly, highly stable, and rapid-response automated offline smartphone-based detection platform represents a good advancement in point-of-care testing (POCT). Moreover, our platform provides a feasible approach for efficient AD detection by examining the level of Aβ 1–42, particularly in areas with low resources and limited communication infrastructure.

Evolved Massive Stars at Low Metallicity. VII. The Lower Mass Limit of the Red Supergiant Population in the Large Magellanic Cloud

The precise definition of the lower mass limit of red supergiant stars (RSGs) is an open question in astrophysics and does not attract much attention. Here, we assemble a spectroscopic evolved cool star sample with 6602 targets, including RSGs, asymptotic giant branch stars, and red giant branch stars, in the Large Magellanic Cloud based on Gaia DR3 and Sloan Digital Sky Survey IV/APOGEE-2. The reference spectrum of each stellar population is built according to the quantile range of relative intensity (1% ∼ 99%). Five different methods, e.g., χ 2, cosine similarity, machine learning (ML), equivalent width, and line ratio, are used in order to separate different stellar populations. ML and χ 2 provide the best and relatively consistent prediction of a certain population. The derived lower limit of the RSG population is able to reach the K s -band tip of the red giant branch (K s ≈12.0 mag), indicating a luminosity as low as about 103.5 L ⊙, which corresponds to a stellar radius of only about 100 R ⊙. Given the mass–luminosity relation of L/L⊙=f(M/M⊙)3 with f ≈ 15.5 ± 3 and taking into account the mass loss of faint RSGs up to now, the minimal initial mass of the RSG population would be about 6.1 ± 0.4 M ⊙, which is much lower than the traditional threshold of 8 M ⊙ for the massive stars. This is the first spectroscopic evidence, indicating that the lower mass limit of the RSG population is around 6 M ⊙. However, the destinies of such faint RSGs are still elusive and may have a large impact on stellar evolutionary and supernova models.

Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks.

Graph convolutional networks (GCNs) are widely used in a variety of applications and can be seen as an unstructured version of standard convolutional neural networks (CNNs). As in CNNs, the computational cost of GCNs for large input graphs (such as large point clouds or meshes) can be high and inhibit the use of these networks, especially in environments with low computational resources. To ease these costs, quantization can be applied to GCNs. However, aggressive quantization of the feature maps can lead to a significant degradation in performance. On a different note, the Haar wavelet transforms are known to be one of the most effective and efficient approaches to compress signals. Therefore, instead of applying aggressive quantization to feature maps, we propose to use Haar wavelet compression and light quantization to reduce the computations involved with the network. We demonstrate that this approach surpasses aggressive feature quantization by a significant margin, for a variety of problems ranging from node classification to point cloud classification and both part and semantic segmentation.

Phenomenon of self-oscillation in bubble dynamics: Bouncing acoustic bubbles

Self-oscillations underlie many natural phenomena, such as heartbeat, ocean waves, and the pulsation of variable stars. From pendulum clocks to the behavior of animal groups, self-oscillation is one of the keys to the understanding of synchronization phenomena and hence to the collective behavior of interacting systems. In this study, we consider two closely spaced bubbles pulsating in the kHz range in response to ultrasonic excitation. A translational bouncing motion emerges from their interaction with a much lower frequency than the bubble pulsation frequency. Our analysis reveals that the observed bubble bouncing exhibits the main features of self-oscillation, such as negative damping and the emergence of a limit cycle. These results highlight unexpected nonlinear effects in the field of microbubbles and give insights into the understanding of synchronization in large bubble clouds.

A Bias-corrected Luminosity Function for Red Supergiant Supernova Progenitor Stars

The apparent tension between the luminosity functions of red supergiant (RSG) stars and of RSG progenitors of Type II supernovae (SNe) is often referred to as the RSG problem and it motivated some to suggest that many RSGs end their life without an SN explosion. However, the luminosity functions of RSG SN progenitors presented so far were biased to high luminosities, because the sensitivity of the search was not considered. Here, we use limiting magnitudes to calculate a bias-corrected RSG progenitor luminosity function. We find that only (36 ± 11)% of all RSG progenitors are brighter than a bolometric magnitude of −7 mag, a significantly smaller fraction than (56 ± 5)% quoted by Davies & Beasor. The larger uncertainty is due to the relatively small progenitor sample, while uncertainties on measured quantities such as magnitudes, bolometric corrections, extinction, or SN distances, only have a minor impact, as long as they fluctuate randomly for different objects in the sample. The bias-corrected luminosity functions of RSG SN progenitors and Type M supergiants in the Large Magellanic Cloud are consistent with each other, as also found by Davies & Beasor for the uncorrected luminosity function. The RSG progenitor luminosity function, hence, does not imply the existence of failed SNe. The presented statistical method is not limited to progenitor searches, but applies to any situation in which a measurement is done for a sample of detected objects, but the probed quantity or property can only be determined for part of the sample.

The abundance of core-collapsed subhaloes in SIDM: insights from structure formation in ΛCDM

ABSTRACT Dark matter haloes enter a phase of gravothermal core-collapse in the presence of self-interactions. This phase is expected to be subdominant given the long time-scales involved. However, it has been shown that collapse is accelerated in subhaloes in strong tidal environments. Cosmological simulations in ΛCDM give complete distributions of subhalo orbits and their profiles. We use these to estimate the fraction of the subhaloes in different host halo environments that are in the core-collapse phase. Our hosts range from the Large Magellanic cloud (LMC)-like hosts to clusters. We use fluid simulations of self-interacting dark matter (SIDM) to evolve subhaloes in their hosts, including the effect of tidal truncation at the time of pericentre crossing. We find, for parameters that allow the interaction cross-section to be high at dwarf scales, at least $10\%$ of all subhaloes are expected to have intrinsically collapsed within Hubble time up to the group mass host scales. This fraction increases significantly, becoming at least 20% when tidal interactions are considered. To identify these objects in observations, we find that we need to measure their densities at very small radial scales, where the subhaloes show a bimodal distribution of densities or we need to measure the slopes of their inner density profiles near the scale radius, which are much steeper than NFW slopes. Current measurements of central slopes of classical dwarfs do not show preference for being completely collapsed, however they are consistent with being cored or in a phase of transition between expansion and collapse.

Abstract 2541: The landscape of circular extrachromosomal amplification in pediatric cancers

Abstract Circular extrachromosomal DNA (ecDNA, also known as double minutes, dm) has emerged as a driver of oncogenic copy number amplification, intratumoral heterogeneity, tumor evolution and therapy resistance. We recently screened the whole genomes of 481 medulloblatomas for ecDNA and concluded that medulloblastoma tumors harboring ecDNA are more than twice as likely to progress within 5 years of diagnosis. To evaluate the frequency and clincical impact of ecDNA across the spectrum of childhood cancers, we performed a retrospective analysis of 1671 tumors from 1482 patients across 47 pediatric tumor types from two large cloud pediatric cancer genomics resources, the Children’s Brain Tumor Network and St. Jude Cloud. ecDNA was detected in 15 pediatric tumor types, including ETMR (100%, n=4), osteosarcoma (47%, n=57), rhabdomyosarcoma (40%, n=35), neuroblastoma (30%, n=106), high-grade glioma (20%, n=157), and retinoblastoma (19%, n=32). Patients with tumors containing ecDNA had significantly poorer 5-year overall survival. In sequential samples from the same tumor at diagnosis and relapse, we observe evidence of ecDNA evolution including sequence instability and generation of new high-copy ecDNA amplification not detected at initial diagnosis. These results comprise the most detailed survey to date of the landscape of extrachromosomal amplifications across childhood cancers. Citation Format: Sunita Sridhar, Owen S. Chapman, Shanqing Wang, Aditi Dutta, Jill P. Mesirov, Lukas Chavez. The landscape of circular extrachromosomal amplification in pediatric cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2541.

Enrichment by extragalactic first stars in the Large Magellanic Cloud

Enrichment by extragalactic first stars in the Large Magellanic Cloud

Cloud properties across spatial scales in simulations of the interstellar medium

Molecular clouds (MCs) are structures of dense gas in the interstellar medium (ISM) that extend from ten to a few hundred parsecs and form the main gas reservoir available for star formation. Hydrodynamical simulations of a varying complexity are a promising way to investigate MCs evolution and their properties. However, each simulation typically has a limited range in resolution and different cloud extraction algorithms are used, which complicates the comparison between simulations. In this work, we aim to extract clouds from different simulations covering a wide range of spatial scales. We compare their properties, such as size, shape, mass, internal velocity dispersion, and virial state. We applied the Hop cloud detection algorithm on (M)HD numerical simulations of stratified ISM boxes and isolated galactic disk simulations that were produced using Flash Ramses and Arepo We find that the extracted clouds are complex in shape, ranging from round objects to complex filamentary networks in all setups. Despite the wide range of scales, resolution, and sub-grid physics, we observe surprisingly robust trends in the investigated metrics. The mass spectrum matches in the overlap between simulations without rescaling and with a high-mass power-law index of -1 for logarithmic bins of mass, in accordance with theoretical predictions. The internal velocity dispersion scales with the size of the cloud as $ $ for large clouds ($R pc $). For small clouds we find larger sigma compared to the power-law scaling, as seen in observations, which is due to supernova-driven turbulence. Almost all clouds are gravitationally unbound with the virial parameter scaling as $ vir $, which is slightly flatter compared to observed scaling but in agreement given the large scatter. We note that the cloud distribution towards the low-mass end is only complete if the more dilute gas is also refined, rather than only the collapsing regions.