Search

We investigate the presence of hub-filament systems in a large sample of 146 active proto-clusters, using H$^{13}$CO$^{+}$ J=1-0 molecular line data obtained from the ATOMS survey. We find that filaments are ubiquitous in proto-clusters, and hub-filament systems are very common from dense core scales ($\sim$0.1 pc) to clump/cloud scales ($\sim$1-10 pc). The proportion of proto-clusters containing hub-filament systems decreases with increasing dust temperature ($T_d$) and luminosity-to-mass ratios ($L/M$) of clumps, indicating that stellar feedback from H{\sc ii} regions gradually destroys the hub-filament systems as proto-clusters evolve. Clear velocity gradients are seen along the longest filaments with a mean velocity gradient of 8.71 km s$^{-1}$pc$^{-1}$ and a median velocity gradient of 5.54 km s$^{-1}$pc$^{-1}$. We find that velocity gradients are small for filament lengths larger than $\sim$1~pc, probably hinting at the existence of inertial inflows, although we cannot determine whether the latter are driven by large-scale turbulence or large-scale gravitational contraction. In contrast, velocity gradients below $\sim$1~pc dramatically increase as filament lengths decrease, indicating that the gravity of the hubs or cores starts to dominate gas infall at small scales. We suggest that self-similar hub-filament systems and filamentary accretion at all scales may play a key role in high-mass star formation., Comment: 16 pages

Modern deep learning architecture utilize batch normalization (BN) to stabilize training and improve accuracy. It has been shown that the BN layers alone are surprisingly expressive. In the context of robustness against adversarial examples, however, BN is argued to increase vulnerability. That is, BN helps to learn fragile features. Nevertheless, BN is still used in adversarial training, which is the de-facto standard to learn robust features. In order to shed light on the role of BN in adversarial training, we investigate to what extent the expressiveness of BN can be used to robustify fragile features in comparison to random features. On CIFAR10, we find that adversarially fine-tuning just the BN layers can result in non-trivial adversarial robustness. Adversarially training only the BN layers from scratch, in contrast, is not able to convey meaningful adversarial robustness. Our results indicate that fragile features can be used to learn models with moderate adversarial robustness, while random features cannot

Coherent elastic neutrino-nucleus scattering (CE$\nu$NS) is a process in which neutrinos scatter on a nucleus which acts as a single particle. Though the total cross section is large by neutrino standards, CE$\nu$NS has long proven difficult to detect, since the deposited energy into the nucleus is $\sim$ keV. In 2017, the COHERENT collaboration announced the detection of CE$\nu$NS using a stopped-pion source with CsI detectors, followed up the detection of CE$\nu$NS using an Ar target. The detection of CE$\nu$NS has spawned a flurry of activities in high-energy physics, inspiring new constraints on beyond the Standard Model (BSM) physics, and new experimental methods. The CE$\nu$NS process has important implications for not only high-energy physics, but also astrophysics, nuclear physics, and beyond. This whitepaper discusses the scientific importance of CE$\nu$NS, highlighting how present experiments such as COHERENT are informing theory, and also how future experiments will provide a wealth of information across the aforementioned fields of physics., Comment: contribution to Snowmasss 2021. Contact authors: P. S. Barbeau, R. Strauss, L. E. Strigari

The ALMA-IMF Large Program observed the W43-MM2-MM3 ridge, whose 1.3mm and 3mm ALMA 12m array continuum images reach a 2500au spatial resolution. We used both the best-sensitivity and the line-free ALMA-IMF images, reduced the noise with the multi-resolution segmentation technique MnGSeg, and derived the most complete and most robust core catalog possible. Using two different extraction software packages, getsf and GExt2D, we identified 200 compact sources, whose 100 common sources have on average fluxes consistent to within 30%. We filtered sources with non-negligible free-free contamination and corrected fluxes from line contamination, resulting in a W43-MM2-MM3 catalog of 205 getsf cores. With a median deconvolved FWHM size of 3400au, core masses range from 0.1Msun to 70Msun and the getsf catalog is 90% complete down to 0.8Msun. The high-mass end of the core mass function (CMF) of W43-MM2-MM3 is top-heavy compared to the canonical IMF. Fitting the cumulative CMF with a single power law of the form N(>logM)\propto M^a, we measured a=-0.95\pm0.04, compared to the canonical a=-1.35 Salpeter IMF slope. The slope of the CMF is robust with respect to map processing, extraction software package, and reasonable variations in the assumptions taken to estimate core masses. We explore several assumptions on how cores transfer their mass to stars and sub-fragment to predict the IMF resulting from the W43-MM2-MM3 CMF. In stark contrast to the commonly accepted paradigm, our result argues against the universality of the CMF shape. More robust functions of the star-formation efficiency and core sub-fragmentation are required to better predict the resulting IMF, here suggested to remain top-heavy at the end of the star-formation phase. If confirmed, the IMFs emerging from starburst events could inherit their top-heavy shape from their parental CMFs, challenging the IMF universality., Comment: 28 pages, 16 figures, 6 tables, A&A accepted on 02/08/22, revised following the language referee report

We present a comprehensive study of the gas kinematics associated with density structures at different spatial scales in the filamentary infrared dark cloud, G034.43+00.24 (G34). This study makes use of the H13CO+ (1-0) molecular line data from the ALMA Three-millimeter Observations of Massive Star-forming regions (ATOMS) survey, which has spatial and velocity resolution of 0.04 pc and 0.2 km/s, respectively. Several tens of dendrogram structures have been extracted in the position-position-velocity space of H13CO+, which include 21 small-scale leaves and 20 larger-scale branches. Overall, their gas motions are supersonic but they exhibit the interesting behavior where leaves tend to be less dynamically supersonic than the branches. For the larger-scale, branch structures, the observed velocity-size relation (i.e., velocity variation/dispersion versus size) are seen to follow the Larson scaling exponent while the smaller-scale, leaf structures show a systematic deviation and display a steeper slope. We argue that the origin of the observed kinematics of the branch structures is likely to be a combination of turbulence and gravity-driven ordered gas flows. In comparison, gravity-driven chaotic gas motion is likely at the level of small-scale leaf structures. The results presented in our previous paper and this current follow-up study suggest that the main driving mechanism for mass accretion/inflow observed in G34 varies at different spatial scales. We therefore conclude that a scale-dependent combined effect of turbulence and gravity is essential to explain the star-formation processes in G34., Comment: 11 pages, 6 figures, and 1 table. To appear in MNRAS

Many low-threshold experiments observe sharply rising event rates of yet unknown origins below a few hundred eV, and larger than expected from known backgrounds. Due to the significant impact of this excess on the dark matter or neutrino sensitivity of these experiments, a collective effort has been started to share the knowledge about the individual observations. For this, the EXCESS Workshop was initiated. In its first iteration in June 2021, ten rare event search collaborations contributed to this initiative via talks and discussions. The contributing collaborations were CONNIE, CRESST, DAMIC, EDELWEISS, MINER, NEWS-G, NUCLEUS, RICOCHET, SENSEI and SuperCDMS. They presented data about their observed energy spectra and known backgrounds together with details about the respective measurements. In this paper, we summarize the presented information and give a comprehensive overview of the similarities and differences between the distinct measurements. The provided data is furthermore publicly available on the workshop's data repository together with a plotting tool for visualization., Comment: 44 pages, 20 figures; Editors: A. Fuss, M. Kaznacheeva, F. Reindl, F. Wagner; updated copyright statements and funding information

Despite their success, deep networks have been shown to be highly susceptible to perturbations, often causing significant drops in accuracy. In this paper, we investigate model robustness on perturbed inputs by studying the performance of internal sub-networks (subnets). Interestingly, we observe that most subnets show particularly poor robustness against perturbations. More importantly, these weak subnets are correlated with the overall lack of robustness. Tackling this phenomenon, we propose a new training procedure that identifies and enhances weak subnets (EWS) to improve robustness. Specifically, we develop a search algorithm to find particularly weak subnets and explicitly strengthen them via knowledge distillation from the full network. We show that EWS greatly improves both robustness against corrupted images as well as accuracy on clean data. Being complementary to popular data augmentation methods, EWS consistently improves robustness when combined with these approaches. To highlight the flexibility of our approach, we combine EWS also with popular adversarial training methods resulting in improved adversarial robustness., Comment: To appear in ECCV 2022

At least half of a protostar's mass is accreted in the Class 0 phase, when the central protostar is deeply embedded in a dense, infalling envelope. We present the first systematic search for outbursts from Class 0 protostars in the Orion clouds. Using photometry from Spitzer/IRAC spanning 2004 to 2017, we detect three outbursts from Class 0 protostars with $\ge 2$ mag changes at 3.6 or 4.5 $\mu$m. This is comparable to the magnitude change of a known protostellar FU Ori outburst. Two are newly detected bursts from the protostars HOPS 12 and 124. The number of detections implies that Class 0 protostars burst every 438 yr, with a 95% confidence interval of 161 to 1884 yr. Combining Spitzer and WISE/NEOWISE data spanning 2004-2019, we show that the bursts persist for more than nine years with significant variability during each burst. Finally, we use $19-100$ $\mu$m photometry from SOFIA, Spitzer and Herschel to measure the amplitudes of the bursts. Based on the burst interval, a duration of 15 yr, and the range of observed amplitudes, 3-100% of the mass accretion during the Class 0 phase occurs during bursts. In total, we show that bursts from Class 0 protostars are as frequent, or even more frequent, than those from more evolved protostars. This is consistent with bursts being driven by instabilities in disks triggered by rapid mass infall. Furthermore, we find that bursts may be a significant, if not dominant, mode of mass accretion during the Class 0 phase., Comment: Accepted to ApJL

We train a convolutional neural network, APOGEE Net, to predict $T_\mathrm{eff}$, $\log g$, and, for some stars, [Fe/H], based on the APOGEE spectra. This is the first pipeline adapted for these data that is capable of estimating these parameters in a self-consistent manner not only for low mass stars, (such as main sequence dwarfs, pre-main sequence stars, and red giants), but also high mass stars with $T_\mathrm{eff}$ in excess of 50,000 K, including hot dwarfs and blue supergiants. The catalog of ~650,000 stars presented in this paper allows for a detailed investigation of the star forming history of not just the Milky Way, but also of the Magellanic clouds, as different type of objects tracing different parts of these galaxies can be more cleanly selected through their distinct placement in $T_\mathrm{eff}$-$\log g$ parameter space than in previous APOGEE catalogs produced through different pipelines., Comment: 19 pages, 11 figures. Accepted to AJ. Data are available through https://www.sdss.org/dr17/data_access/value-added-catalogs/?vac_id=apogee-net:-a-unified-spectral-model Code is available through https://github.com/hutchresearch/ApogeeNet2

The Orion molecular cloud complex harbours the nearest GMCs and site of high-mass star formation. Its YSO populations are thoroughly characterized. The region is therefore a prime target for the study of star formation. Here, we verify the performance of the SuperCAM 64 pixel heterodyne array on APEX. We give a descriptive overview of a set of wide-field CO(3-2) spectral cubes obtained towards the Orion GMC complex, aimed at characterizing the dynamics and structure of the extended molecular gas in diverse regions of the clouds, ranging from very active sites of clustered star formation in Orion B to comparatively quiet regions in southern Orion A. We present a 2.7 square degree (130pc$^2$) mapping survey in the CO(3-2) transition, obtained using SuperCAM on APEX at an angular resolution of 19'' (7600AU or 0.037pc at a distance of 400pc), covering L1622, NGC2071, NGC2068, OriB9, NGC2024, and NGC2023 in Orion B, and the southern part of the L1641 cloud in Orion A. We describe CO integrated emission and line moment maps and position-velocity diagrams and discuss a few sub-regions in some detail. Evidence for expanding bubbles is seen with lines splitting into double components, most prominently in NGC2024, where we argue that the bulk of the molecular gas is in the foreground of the HII region. High CO(3-2)/CO(1-0) line ratios reveal warm CO along the western edge of Orion B in the NGC2023/NGC2024 region facing the IC434 HII region. Multiple, well separated radial velocity components seen in L1641-S suggest that it consists of a sequence of clouds at increasingly larger distances. We find a small, spherical cloud - the 'Cow Nebula' globule - north of NGC2071. We trace high velocity line wings for the NGC2071-IR outflow and the NGC2024 CO jet. The protostellar dust core FIR4 (rather than FIR5) is the true driving source of the NGC2024 monopolar outflow., Comment: Accepted for publication in Astronomy and Astrophysics

We present the first data release of the ALMA-IMF Large Program, which covers the 12m-array continuum calibration and imaging. The ALMA-IMF Large Program is a survey of fifteen dense molecular cloud regions spanning a range of evolutionary stages that aims to measure the core mass function (CMF). We describe the data acquisition and calibration done by the Atacama Large Millimeter/submillimeter Array (ALMA) observatory and the subsequent calibration and imaging we performed. The image products are combinations of multiple 12m array configurations created from a selection of the observed bandwidth using multi-term, multi-frequency synthesis imaging and deconvolution. The data products are self-calibrated and exhibit substantial noise improvements over the images produced from the delivered data. We compare different choices of continuum selection, calibration parameters, and image weighting parameters, demonstrating the utility and necessity of our additional processing work. Two variants of continuum selection are used and will be distributed: the "best-sensitivity" data, which include the full bandwidth, including bright emission lines that contaminate the continuum, and "cleanest", which select portions of the spectrum that are unaffected by line emission. We present a preliminary analysis of the spectral indices of the continuum data, showing that the ALMA products are able to clearly distinguish free-free emission from dust emission, and that in some cases we are able to identify optically thick emission sources. The data products are made public with this release., Comment: Data released on Zenodo at https://zenodo.org/record/5702966. Accepted for publication in A&A

The ALMA-IMF Large Program imaged a total noncontiguous area of 53pc2, covering 15 extreme, nearby protoclusters of the Milky Way. They were selected to span relevant early protocluster evolutionary stages. Our 1.3mm and 3mm observations provide continuum images that are homogeneously sensitive to point-like cores with masses of 0.2 and 0.6Msun, respectively, with a matched spatial resolution of 2000au. We also detect lines that probe the protocluster structure, kinematics, chemistry, and feedback over scales from clouds to filaments to cores. We classify ALMA-IMF protoclusters as Young, Intermediate, or Evolved based on the amount of dense gas in the cloud that has potentially been impacted by HII regions. The ALMA-IMF catalog contains 700 cores that span a mass range of 0.15-250Msun at a typical size of 2100au. We show that this core sample has no significant distance bias and can be used to build core mass functions at similar physical scales. Significant gas motions, which we highlight here in the G353.41 region, are traced down to core scales and can be used to look for inflowing gas streamers and to quantify the impact of the possible associated core mass growth on the shape of the CMF with time. Our first analysis does not reveal any significant evolution of the matter concentration from clouds to cores or from the youngest to more evolved protoclusters, indicating that cloud dynamical evolution and stellar feedback have for the moment only had a slight effect on the structure of high-density gas in our sample. Furthermore, the first-look analysis of the line richness toward bright cores indicates that the survey encompasses several tens of hot cores, of which we highlight the most massive in the G351.77 cloud. Their homogeneous characterization can be used to constrain the emerging molecular complexity in protostars of high to intermediate masses., Comment: 27 pages, 9 figures, accepted for publication by A&A

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys., Comment: 40 pages, 8 figures, 6 tables. In press at ApJSS (arxiv v2 corrects some minor typos and updates references)

Multitype branching processes are ideal for studying the population dynamics of stem cell populations undergoing mutation accumulation over the years following transplant. In such stochastic models, several quantities are of clinical interest as insertional mutagenesis carries the potential threat of leukemogenesis following gene therapy with autologous stem cell transplantation. In this paper, we develop a three-type branching process model describing accumulations of mutations in a population of stem cells distinguished by their ability for long-term self-renewal. Our outcome of interest is the appearance of a double-mutant cell, which carries a high potential for leukemic transformation. In our model, a single-hit mutation carries a slight proliferative advantage over a wild-type stem cells. We compute marginalized transition probabilities that allow us to capture important quantitative aspects of our model, including the probability of observing a double-hit mutant and relevant moments of a single-hit mutation population over time. We thoroughly explore the model behavior numerically, varying birth rates across the initial sizes and populations of wild type stem cells and single-hit mutants, and compare the probability of observing a double-hit mutant under these conditions. We find that increasing the number of single-mutants over wild-type particles initially present has a large effect on the occurrence of a double-mutant, and that it is relatively safe for single-mutants to be quite proliferative, provided the lentiviral gene addition avoids creating single mutants in the original insertion process. Our approach is broadly applicable to an important set of questions in cancer modeling and other population processes involving multiple stages, compartments, or types., Comment: 19 pages, 5 figures

We present an overview of recent progress towards the Ricochet coherent elastic neutrino nucleus scattering CE$\nu$NS experiment. The ILL research reactor in Grenoble, France has been selected as the experiment site, after in situ studies of vibration and particle backgrounds. We present background rate estimates specific to that site, along with descriptions of the planned CryoCube and Q-Array detector payloads., Comment: Proceedings for the 19th International Workshop on Low Temperature Detectors (LTD19)

We characterize protostellar multiplicity in the Orion molecular clouds using ALMA 0.87~mm and VLA 9~mm continuum surveys toward 328 protostars. These observations are sensitive to projected spatial separations as small as $\sim$20~au, and we consider source separations up to 10$^4$~au as potential companions. The overall multiplicity fraction (MF) and companion fraction (CF) for the Orion protostars are 0.30$\pm$0.03 and 0.44$\pm$0.03, respectively, considering separations from 20 to 10$^4$~au. The MFs and CFs are corrected for potential contamination by unassociated young stars using a probabilistic scheme based on the surface density of young stars around each protostar. The companion separation distribution as a whole is double peaked and inconsistent with the separation distribution of solar-type field stars, while the separation distribution of Flat Spectrum protostars is consistent solar-type field stars. The multiplicity statistics and companion separation distributions of the Perseus star-forming region are consistent with those of Orion. Based on the observed peaks in the Class 0 separations at $\sim$100~au and $\sim$10$^3$~au, we argue that multiples with separations $<$500~au are likely produced by both disk fragmentation and turbulent fragmentation with migration, and those at $\ga$10$^3$~au result primarily from turbulent fragmentation. We also find that MFs/CFs may rise from Class 0 to Flat Spectrum protostars between 100 and 10$^3$~au in regions of high YSO density. This finding may be evidence for migration of companions from $>$10$^3$~au to $<$10$^3$~au, and that some companions between 10$^3$ and 10$^4$~au must be (or become) unbound., Comment: 76 pages, 20 Figures, 10 Tables, accepted by the Astrophysical Journal

In this paper we compute predictions for the number of stellar collisions derived from analytic models based on the mean free path (MFP) approximation and compare them to the results of $N$-body simulations. Our goal is to identify the cluster conditions under which the MFP approximation remains valid. Adopting a range of particle numbers ($100\leq N\leq5000$) and different combinations of particle masses and radii, we explore three different channels leading to stellar collisions, all of which are expected to occur in realistic stellar environments. At high densities, binaries form from isolated three-body interactions of single stars. Hence, we consider collisions between single stars and collisions involving binary stars, after they form in our simulations. For the latter, we consider two channels for mergers, namely direct stellar collisions during chaotic single-binary interactions and perturbation-driven mergers of binaries due to random walks in eccentricity approaching unity. In the densest systems considered here, a very massive object is formed at the cluster centre, causing local stellar orbits to become increasingly Keplerian and the assumptions going into our analytic model to break down. Before reaching this limit, we obtain excellent agreement between our theoretical predictions and the simulations: the analytic rates are typically accurate to within one standard deviation for the entire parameter space considered here, but the agreement is best for short integration times. Our results have direct implications for blue straggler formation in dense star clusters, and stellar mergers in galactic nuclei hosting massive black holes., Comment: 13 pages, 7 figures. Accepted by MNRAS

We present new 3-mm continuum and molecular lines observations from the ATOMS survey towards the massive protostellar clump, MM1, located in the filamentary infrared dark cloud (IRDC), G034.43+00.24 (G34). The lines observed are the tracers of either dense gas (e.g. HCO+/H13CO+ J = 1-0) or outflows (e.g. CS J = 2-1). The most complete picture to date of seven cores in MM1 is revealed by dust continuum emission. These cores are found to be gravitationally bound, with virial parameter, $\alpha_{vir}<2$. At least four outflows are identified in MM1 with a total outflowing mass of $\sim 45 M_\odot$, and a total energy of $\sim 1\times 10^{47}$ erg, typical of outflows from a B0-type star. Evidence of hierarchical fragmentation, where turbulence dominates over thermal pressure, is observed at both the cloud and the clump scales. This could be linked to the scale-dependent, dynamical mass inflow/accretion on clump and core scales. We therefore suggest that the G34 cloud could be undergoing a dynamical mass inflow/accretion process linked to the multiscale fragmentation, which leads to the sequential formation of fragments of the initial cloud, clumps, and ultimately dense cores, the sites of star formation., Comment: 14 pages with 6 figures, and in press

Different extensions of the standard model of particle physics, such as braneworld or mirror matter models, predict the existence of a neutron sterile state, possibly as a dark matter candidate. This Letter reports a new experimental constraint on the probability $p$ for neutron conversion into a hidden neutron, set by the STEREO experiment at the high flux reactor of the Institut Laue-Langevin. The limit is $p<3.1\times 10^{-11}$ at $95 \%$ C.L. improving the previous limit by a factor 13. This result demonstrates that short-baseline neutrino experiments can be used as competitive passing-through-walls neutron experiments to search for hidden neutrons., Comment: 5 pages, 3 figures

Modern deep learning based classifiers show very high accuracy on test data but this does not provide sufficient guarantees for safe deployment, especially in high-stake AI applications such as medical diagnosis. Usually, predictions are obtained without a reliable uncertainty estimate or a formal guarantee. Conformal prediction (CP) addresses these issues by using the classifier's predictions, e.g., its probability estimates, to predict confidence sets containing the true class with a user-specified probability. However, using CP as a separate processing step after training prevents the underlying model from adapting to the prediction of confidence sets. Thus, this paper explores strategies to differentiate through CP during training with the goal of training model with the conformal wrapper end-to-end. In our approach, conformal training (ConfTr), we specifically "simulate" conformalization on mini-batches during training. Compared to standard training, ConfTr reduces the average confidence set size (inefficiency) of state-of-the-art CP methods applied after training. Moreover, it allows to "shape" the confidence sets predicted at test time, which is difficult for standard CP. On experiments with several datasets, we show ConfTr can influence how inefficiency is distributed across classes, or guide the composition of confidence sets in terms of the included classes, while retaining the guarantees offered by CP., Comment: ICLR 2022