The observation of binary neutron star merger GW170817, along with its optical counterpart, provided the first constraint on the Hubble constant H0 using gravitational wave standard sirens. When no ...counterpart is identified, a galaxy catalog can be used to provide the necessary redshift information. However, the true host might not be contained in a catalog which is not complete out to the limit of gravitational-wave detectability. These electromagnetic and gravitational-wave selection effects must be accounted for. We describe and implement a method to estimate H0 using both the counterpart and the galaxy catalog standard siren methods. We perform a series of mock data analyses using binary neutron star mergers to confirm our ability to recover an unbiased estimate of H0. Our simulations used a simplified universe with no redshift uncertainties or galaxy clustering, but with different magnitude-limited catalogs and assumed host galaxy properties, to test our treatment of both selection effects. We explore how the incompleteness of catalogs affects the final measurement of H0 , as well as the effect of weighting each galaxy's likelihood of being a host by its luminosity. In our most realistic simulation, where the simulated catalog is about three times denser than the density of galaxies in the local universe, we find that a 4.4% measurement precision can be reached using galaxy catalogs with 50% completeness and ∼ 250 binary neutron star detections with sensitivity similar to that of Advanced LIGO's second observing run.
The detection of the binary neutron star merger, GW170817, was the first success story of multi-messenger observations of compact binary mergers. The inferred merger rate, along with the increased ...sensitivity of the ground-based gravitational-wave (GW) network in the present LIGO/Virgo, and future LIGO/Virgo/KAGRA observing runs, strongly hints at detections of binaries that could potentially have an electromagnetic (EM) counterpart. A rapid assessment of properties that could lead to a counterpart is essential to aid time-sensitive follow-up operations, especially robotic telescopes. At minimum, the possibility of counterparts requires a neutron star (NS). Also, the tidal disruption physics is important to determine the remnant matter post-merger, the dynamics of which could result in the counterparts. The main challenge, however, is that the binary system parameters, such as masses and spins estimated from the real-time, GW template-based searches, are often dominated by statistical and systematic errors. Here, we present an approach that uses supervised machine learning to mitigate such selection effects to report the possibility of counterparts based on the presence of an NS component, and the presence of remnant matter post-merger in real time.
We present the Census of the Local Universe (CLU) narrowband survey to search for emission-line (H ) galaxies. CLU-H has imaged 3π of the sky (26,470 deg2) with four narrowband filters that probe a ...distance out to 200 Mpc. We have obtained spectroscopic follow-up for galaxy candidates in 14 preliminary fields (101.6 deg2) to characterize the limits and completeness of the survey. In these preliminary fields, CLU can identify emission lines down to an H flux limit of 10−14 erg s−1 cm−2 at 90% completeness, and recovers 83% (67%) of the H flux from cataloged galaxies in our search volume at the = 2.5 ( = 5) color excess levels. The contamination from galaxies with no emission lines is 61% (12%) for = 2.5 ( = 5). Also, in the regions of overlap between our preliminary fields and previous emission-line surveys, we recover the majority of the galaxies found in previous surveys and identify an additional 300 galaxies. In total, we find 90 galaxies with no previous distance information, several of which are interesting objects: 7 blue compact dwarfs, 1 green pea, and a Seyfert galaxy; we also identify a known planetary nebula. These objects show that the CLU-H survey can be a discovery machine for objects in our own Galaxy and extreme galaxies out to intermediate redshifts. However, the majority of the CLU-H galaxies identified in this work show properties consistent with normal star-forming galaxies. CLU-H galaxies with new redshifts will be added to existing galaxy catalogs to focus the search for the electromagnetic counterpart to gravitational wave events.
Abstract 3D reconstruction of human brain volumes at high resolution is now possible thanks to advancements in tissue clearing methods and fluorescence microscopy techniques. Analyzing the massive ...data produced with these approaches requires automatic methods able to perform fast and accurate cell counting and localization. Recent advances in deep learning have enabled the development of various tools for cell segmentation. However, accurate quantification of neurons in the human brain presents specific challenges, such as high pixel intensity variability, autofluorescence, non-specific fluorescence and very large size of data. In this paper, we provide a thorough empirical evaluation of three techniques based on deep learning (StarDist, CellPose and BCFind-v2, an updated version of BCFind) using a recently introduced three-dimensional stereological design as a reference for large-scale insights. As a representative problem in human brain analysis, we focus on a $$4~\text {-cm}^3$$ 4 -cm 3 portion of the Broca’s area. We aim at helping users in selecting appropriate techniques depending on their research objectives. To this end, we compare methods along various dimensions of analysis, including correctness of the predicted density and localization, computational efficiency, and human annotation effort. Our results suggest that deep learning approaches are very effective, have a high throughput providing each cell 3D location, and obtain results comparable to the estimates of the adopted stereological design.
Detections of coalescing binary black holes by LIGO have opened a new window of transient astronomy. With increasing sensitivity of LIGO and participation of the Virgo detector in Cascina, Italy, we ...expect to soon detect coalescence of compact binary systems with one or more neutron stars. These are the prime targets for electromagnetic follow-up of gravitational wave triggers, which holds enormous promise of rich science. However, hunting for electromagnetic counterparts of gravitational wave events is a non-trivial task due to the sheer size of the error regions, which could span hundreds of square degrees. This may require deep observation with large field-of-view telescopes and/or use of galaxy catalogs. The Zwicky Transient facility (ZTF), scheduled to begin operation in 2017, is designed to cover such large sky-localization areas. In this work, we present the strategies of efficiently tiling the sky to facilitate the observation of the gravitational wave error regions using ZTF. To do this, we used simulations consisting of 475 binary neutron star coalescences detected using a mix of two- and three-detector networks. Our studies reveal that, using two overlapping sets of ZTF tiles and a (modified) ranked-tiling algorithm, we can cover the gravitational-wave sky-localization regions with half as many pointings as a simple contour-covering algorithm. We then incorporated the ranked-tiling strategy to study our ability to observe the counterparts. This requires optimization of observation depth and localization area coverage. Our results show that observation in r-band with ∼600 seconds of integration time per pointing seems to be optimum for typical assumed brightnesses of electromagnetic counterparts, if we plan to spend equal amount of time per pointing. However, our results also reveal that we can gain by as much as 50% in detection efficiency if we linearly scale our integration time per pointing based on the tile probability.
A large body of work has focused on understanding stimulus-driven behavior, sex differences in these processes, and the neural circuits underlying them. Many preclinical mouse models present ...rewarding or aversive stimuli in isolation, ignoring that ethologically, reward seeking requires the consideration of potential aversive outcomes. In addition, the context (or reinforcement schedule under) in which stimuli are encountered can engender different behavioral responses to the same stimulus. Thus, delineating neural control of behavior requires a dissociation between stimulus valence and stimulus-driven behavior. We developed the Multidimensional Cue Outcome Action Task (MCOAT) to dissociate motivated action from cue learning and valence in mice. First, mice acquire positive and negative reinforcement in the presence of discrete discriminative stimuli. Next, discriminative stimuli are presented concurrently allowing for parsing innate behavioral strategies based on reward seeking and avoidance. Lastly, responding in the face of punishment is assessed, thus examining how positive and negative outcomes are relatively valued. First, we identified sex-specific behavioral strategies, showing that females prioritize avoidance of negative outcomes over seeking positive, while males have the opposite strategy. Next, we show that chemogenetically inhibiting D1 medium spiny neurons (MSNs) in the nucleus accumbens-a population that has been linked to reward-driven behavior-reduces positive and increases negative reinforcement learning rates. Thus, D1 MSNs modulate stimulus processing, rather than motivated responses or the reinforcement process itself. Together, the MCOAT has broad utility for understanding complex behaviors as well as the definition of the discrete information encoded within cellular populations.
An up-to-date catalog of nearby galaxies considered to be hosts of binary compact objects is provided, with complete information about sky position, distance, extinction-corrected blue luminosity, ...and error estimates. With our current understanding of binary evolution, rates of formation and coalescence for binary compact objects scale with massive-star formation, and hence the (extinction-corrected) blue luminosity of host galaxies. Coalescence events in binary compact objects are among the most promising gravitational-wave sources for ground-based gravitational-wave detectors such as LIGO. Our catalog and associated error estimates are important for the interpretation of analyses carried out for LIGO, in constraining the rates of compact binary coalescence, given an astrophysical population model for the sources considered. We discuss how the notion of effective distance, created to account for the antenna pattern of a gravitational-wave detector, must be used in conjunction with our catalog. We also note that the catalog provided can be used in other astronomical analysis of populations that scale with galaxy blue luminosity.
The past couple of decades have seen an emergence of transient detection facilities in various avenues of time-domain astronomy that have provided us with a rich data set of transients. The rates of ...these transients have implications in star formation, progenitor models, evolution channels, and cosmology measurements. The crucial component of any rate calculation is the detectability and spacetime volume sensitivity of a survey to a particular transient type as a function of many intrinsic and extrinsic parameters. Fully sampling that multidimensional parameter space is challenging. Instead, we present a scheme to assess the detectability of transients using supervised machine learning. The data product is a classifier that determines the detection likelihood of sources resulting from an image subtraction pipeline associated with time-domain survey telescopes, taking into consideration the intrinsic properties of the transients and the observing conditions. We apply our method to assess the spacetime volume sensitivity of type Ia supernovae (SNe Ia) in the intermediate Palomar Transient Factory (iPTF) and obtain the result, . With rate estimates in the literature, this volume sensitivity gives a count of 680-1160 SNe Ia detectable by iPTF, which is consistent with the archival data. With a view toward wider applicability of this technique we do a preliminary computation for long-duration type IIp supernovae (SNe IIp) and find . This classifier can be used for computationally fast spacetime volume sensitivity calculation of any generic transient type using their light-curve properties. Hence, it can be used as a tool to facilitate calculation of transient rates in a range of time-domain surveys, given suitable training sets.
Previous clinical and animal studies suggest that selective activators of M(1) and/or M(4) muscarinic acetylcholine receptors (mAChRs) have potential as novel therapeutic agents for treatment of ...schizophrenia and Alzheimer's disease. However, highly selective centrally penetrant activators of either M(1) or M(4) have not been available, making it impossible to determine the in vivo effects of selective activation of these receptors. We previously identified VU10010 3-amino-N-(4-chlorobenzyl)-4, 6-dimethylthieno2,3-bpyridine-2-carboxamide as a potent and selective allosteric potentiator of M(4) mAChRs. However, unfavorable physiochemical properties prevented use of this compound for in vivo studies. We now report that chemical optimization of VU10010 has afforded two centrally penetrant analogs, VU0152099 3-amino-N-(benzod1,3dioxol-5-ylmethyl)-4,6-dimethylthieno2,3-bpyridine carboxamide and VU0152100 3-amino-N-(4-methoxybenzyl)-4,6-dimethylthieno2,3-bpyridine carboxamide, that are potent and selective positive allosteric modulators of M(4). VU0152099 and VU0152100 had no agonist activity but potentiated responses of M(4) to acetylcholine. Both compounds were devoid of activity at other mAChR subtypes or at a panel of other GPCRs. The improved physiochemical properties of VU0152099 and VU0152100 allowed in vivo dosing and evaluation of behavioral effects in rats. Interestingly, these selective allosteric potentiators of M(4) reverse amphetamine-induced hyperlocomotion in rats, a model that is sensitive to known antipsychotic agents and to nonselective mAChR agonists. This is consistent with the hypothesis that M(4) plays an important role in regulating midbrain dopaminergic activity and raises the possibility that positive allosteric modulation of M(4) may mimic some of the antipsychotic-like effects of less selective mAChR agonists.
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