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  1. Multi-Agent Path Finding (MA-PF) computes a set of collision-free paths for multiple agents from their respective starting locations to destinations. This paper considers a generalization of MA-PF called Multi-Agent Teamwise Cooperative Path Finding (MA-TC-PF), where agents are grouped as multiple teams and each team has its own objective to be minimized. For example, an objective can be the sum or max of individual arrival times of the agents. In general, there is more than one team, and MA-TC-PF is thus a multi-objective planning problem with the goal of finding the entire Paretooptimal front that represents all possible trade-offs among the objectives of the teams. To solve MA-TC-PF, we propose two algorithms TC-CBS and TC-M*, which leverage the existing CBS and M* for conventional MA-PF. We discuss the conditions under which the proposed algorithms are complete and are guaranteed to find the Pareto-optimal front. We present numerical results for several types of MA-TC-PF problems. 
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    Free, publicly-accessible full text available May 29, 2024
  2. Careful placement of a distributed computational application within a target device cluster is critical for achieving low application completion time. The problem is challenging due to its NP-hardness and combinatorial nature. In recent years, learning-based approaches have been proposed to learn a placement policy that can be applied to unseen applications, motivated by the problem of placing a neural network across cloud servers. These approaches, however, generally assume the device cluster is fixed, which is not the case in mobile or edge computing settings, where heterogeneous devices move in and out of range for a particular application. To address the challenge of scaling to different-sized device clusters and adapting to the addition of new devices, we propose a new learning approach called GiPH, which learns policies that generalize to dynamic device clusters via 1) a novel graph representation gpNet that efficiently encodes the information needed for choosing a good placement, and 2) a scalable graph neural network (GNN) that learns a summary of the gpNet information. GiPH turns the placement problem into that of finding a sequence of placement improvements, learning a policy for selecting this sequence that scales to problems of arbitrary size. We evaluate GiPH with a wide range of task graphs and device clusters and show that our learned policy rapidly finds good placements for new problem instances. GiPH finds placements that achieve up to 30.5% better makespan, searching up to 3× faster than other search-based placement policies. 
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  3. Abstract

    SN 1987A was an unusual hydrogen-rich core-collapse supernova originating from a blue supergiant star. Similar blue supergiant explosions remain a small family of events, and are broadly characterized by their long rises to peak. The Zwicky Transient Facility Census of the Local Universe (CLU) experiment aims to construct a spectroscopically complete sample of transients occurring in galaxies from the CLU galaxy catalog. We identify 13 long-rising (>40 days) Type II supernovae from the volume-limited CLU experiment during a 3.5 yr period from 2018 June to 2021 December, approximately doubling the previously known number of these events. We present photometric and spectroscopic data of these 13 events, finding peakr-band absolute magnitudes ranging from −15.6 to −17.5 mag and the tentative detection of Baiilines in nine events. Using our CLU sample of events, we derive a long-rising Type II supernova rate of1.370.30+0.26×106Mpc−3yr−1, ≈1.4% of the total core-collapse supernova rate. This is the first volumetric rate of these events estimated from a large, systematic, volume-limited experiment.

     
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  4. Abstract

    One of the open questions following the discovery of GW170817 is whether neutron star (NS) mergers are the only astrophysical sites capable of producingr-process elements. Simulations have shown that 0.01–0.1Mofr-process material could be generated in the outflows originating from the accretion disk surrounding the rapidly rotating black hole that forms as a remnant to both NS mergers and collapsing massive stars associated with long-duration gamma-ray bursts (collapsars). The hallmark signature ofr-process nucleosynthesis in the binary NS merger GW170817 was its long-lasting near-infrared (NIR) emission, thus motivating a systematic photometric study of the light curves of broad-lined stripped-envelope (Ic-BL) supernovae (SNe) associated with collapsars. We present the first systematic study of 25 SNe Ic-BL—including 18 observed with the Zwicky Transient Facility and 7 from the literature—in the optical/NIR bands to determine what quantity ofr-process material, if any, is synthesized in these explosions. Using semi-analytic models designed to account forr-process production in SNe Ic-BL, we perform light curve fitting to derive constraints on ther-process mass for these SNe. We also perform independent light curve fits to models without ther-process. We find that ther-process-free models are a better fit to the light curves of the objects in our sample. Thus, we find no compelling evidence ofr-process enrichment in any of our objects. Further high-cadence infrared photometric studies and nebular spectroscopic analysis would be sensitive to smaller quantities ofr-process ejecta mass or indicate whether all collapsars are completely devoid ofr-process nucleosynthesis.

     
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  5. Abstract

    Luminous red novae (LRNe) are transients characterized by low luminosities and expansion velocities, and they are associated with mergers or common-envelope ejections in stellar binaries. Intermediate-luminosity red transients (ILRTs) are an observationally similar class with unknown origins, but they are generally believed to be either electron-capture supernovae in super-asymptotic giant branch stars or outbursts in dusty luminous blue variables (LBVs). In this paper, we present a systematic sample of eight LRNe and eight ILRTs detected as part of the Census of the Local Universe (CLU) experiment on the Zwicky Transient Facility (ZTF). The CLU experiment spectroscopically classifies ZTF transients associated with nearby (<150 Mpc) galaxies, achieving 80% completeness formr< 20 mag. Using the ZTF-CLU sample, we derive the first systematic LRNe volumetric rate of7.83.7+6.5×105Mpc−3yr−1in the luminosity range −16 ≤Mr≤ −11 mag. We find that, in this luminosity range, the LRN rate scales asdN/dLL2.5±0.3—significantly steeper than the previously derived scaling ofL−1.4±0.3for lower-luminosity LRNe (MV≥ −10 mag). The steeper power law for LRNe at high luminosities is consistent with the massive merger rates predicted by binary population synthesis models. We find that the rates of the brightest LRNe (Mr≤ −13 mag) are consistent with a significant fraction of them being progenitors of double compact objects that merge within a Hubble time. For ILRTs, we derive a volumetric rate of2.61.4+1.8×106Mpc−3yr−1forMr≤ −13.5 mag, which scales asdN/dLL2.5±0.5. This rate is ∼1%–5% of the local core-collapse supernova rate and is consistent with theoretical ECSN rate estimates.

     
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  6. Abstract

    The Zwicky Transient Facility (ZTF), a public–private enterprise, is a new time-domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope with a 47 deg2field of view and an 8 second readout time. It is well positioned in the development of time-domain astronomy, offering operations at 10% of the scale and style of the Large Synoptic Survey Telescope (LSST) with a single 1-m class survey telescope. The public surveys will cover the observable northern sky every three nights ingandrfilters and the visible Galactic plane every night ingandr. Alerts generated by these surveys are sent in real time to brokers. A consortium of universities that provided funding (“partnership”) are undertaking several boutique surveys. The combination of these surveys producing one million alerts per night allows for exploration of transient and variable astrophysical phenomena brighter thanr ∼ 20.5 on timescales of minutes to years. We describe the primary science objectives driving ZTF, including the physics of supernovae and relativistic explosions, multi-messenger astrophysics, supernova cosmology, active galactic nuclei, and tidal disruption events, stellar variability, and solar system objects.

     
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