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This research explores a novel paradigm for preserving topological segmentations in existing error-bounded lossy compressors. Today's lossy compressors rarely consider preserving topologies such as Morse-Smale complexes, and the discrepancies in topology between original and decompressed datasets could potentially result in erroneous interpretations or even incorrect scientific conclusions. In this paper, we focus on preserving Morse-Smale segmentations in 2D/3D piecewise linear scalar fields, targeting the precise reconstruction of minimum/maximum labels induced by the integral line of each vertex. The key is to derive a series of edits during compression time; the edits are applied to the decompressed data, leading to an accurate reconstruction of segmentations while keeping the error within the prescribed error bound. To this end, we developed a workflow to fix extrema and integral lines alternatively until convergence within finite iterations; we accelerate each workflow component with shared-memory/GPU parallelism to make the performance practical for coupling with compressors. We demonstrate use cases with fluid dynamics, ocean, and cosmology application datasets with a significant acceleration with an NVIDIA A100 GPU. 

Existing error-bounded lossy compression techniques control the pointwise error during compression to guarantee the integrity of the decompressed data. However, they typically do not explicitly preserve the topological features in data. When performing post hoc analysis with decompressed data using topological methods, preserving topology in the compression process to obtain topologically consistent and correct scientific insights is desirable. In this paper, we introduce TopoSZ, an error-bounded lossy compression method that preserves the topological features in 2D and 3D scalar fields. Specifically, we aim to preserve the types and locations of local extrema as well as the level set relations among critical points captured by contour trees in the decompressed data. The main idea is to derive topological constraints from contour-tree-induced segmentation from the data domain, and incorporate such constraints with a customized error-controlled quantization strategy from the SZ compressor (version 1.4). Our method allows users to control the pointwise error and the loss of topological features during the compression process with a global error bound and a persistence threshold. 

Merge trees are a type of topological descriptors that record the connectivity among the sublevel sets of scalar fields. They are among the most widely used topological tools in visualization. In this paper, we are interested in sketching a set of merge trees using techniques from matrix sketching. That is, given a large set T of merge trees, we would like to find a much smaller set of basis trees S such that each tree in T can be approximately reconstructed from a linear combination of merge trees in S. A set of high-dimensional vectors can be approximated via matrix sketching techniques such as principal component analysis and column subset selection. However, until now, there has not been any work on sketching a set of merge trees. We develop a framework for sketching a set of merge trees that combines matrix sketching with tools from optimal transport. In particular, we vectorize a set of merge trees into high-dimensional vectors while preserving their structures and structural relations. We demonstrate the applications of our framework in sketching merge trees that arise from time-varying scientific simulations. Specifically, our framework obtains a set of basis trees as representatives that capture the “modes” of physical phenomena for downstream analysis and visualization. 

Existing error-bounded lossy compression techniques control the pointwise error during compression to guarantee the integrity of the decompressed data. However, they typically do not explicitly preserve the topological features in data. When performing post hoc analysis with decompressed data using topological methods, preserving topology in the compression process to obtain topologically consistent and correct scientific insights is desirable. In this paper, we introduce TopoSZ, an error-bounded lossy compression method that preserves the topological features in 2D and 3D scalar fields. Specifically, we aim to preserve the types and locations of local extrema as well as the level set relations among critical points captured by contour trees in the decompressed data. The main idea is to derive topological constraints from contour-tree-induced segmentation from the data domain, and incorporate such constraints with a customized error-controlled quantization strategy from the SZ compressor (version 1.4). Our method allows users to control the pointwise error and the loss of topological features during the compression process with a global error bound and a persistence threshold. 

We study a magnitude-limited sample of 36 broad-lined type Ic supernovae (SNe Ic-BL) from the Zwicky Transient Facility Bright Transient Survey (detected between 2018 March and 2021 August), which is the largest systematic study of SNe Ic-BL done in literature thus far. We present the light curves (LCs) for each of the SNe and analyze the shape of the LCs to derive empirical parameters, along with the explosion epochs for every event. The sample has an average absolute peak magnitude in therband of${\overline{\mathit{M}}}_{\mathrm{r},\max }=-18.51\pm 0.15$mag. Using spectra obtained around peak light, we compute expansion velocities from the Feii5169 Å line for each event with high enough signal-to-noise ratio spectra, and find an average value of$\overline{v_{\mathrm{ph}}}=16,100\pm 1100$km s⁻¹. We also compute bolometric LCs, study the blackbody temperature and radii evolution over time, and derive the explosion properties of the SNe. The explosion properties of the sample have average values of${\overline{\mathit{M}}}_{\mathrm{Ni}}={0.37}_{-0.06}^{+0.08}{\mathit{M}}_{\odot }$,${\overline{\mathit{M}}}_{\mathrm{ej}}={2.45}_{-0.41}^{+0.47}{\mathit{M}}_{\odot }$, and${\overline{\mathit{E}}}_{\mathrm{K}}=({4.02}_{-1.00}^{+1.37})\times {10}^{51}$erg. Thirteen events have radio observations from the Very Large Array, with eight detections and five non-detections. We find that the populations that have radio detections and radio non-detections are indistinct from one another with respect to their optically inferred explosion properties, and there are no statistically significant correlations present between the events’ radio luminosities and optically inferred explosion properties. This provides evidence that the explosion properties derived from optical data alone cannot give inferences about the radio properties of SNe Ic-BL and likely their relativistic jet formation mechanisms.

 

Atmospheric rivers (ARs) are long, narrow regions of water vapor in the Earth's atmosphere that transport heat and moisture from the tropics to the mid‐latitudes. ARs are often associated with extreme weather events in North America and contribute significantly to water supply and flood risk. However, characterizing ARs has been a major challenge due to the lack of a universal definition and their structural variations. Existing AR detection tools (ARDTs) produce distinct AR boundaries for the same event, making the risk assessment of ARs a difficult task. Understanding these uncertainties is crucial to improving the predictability of AR impacts, including their landfall areas and associated precipitation, which could cause catastrophic flooding and landslides over the coastal regions. In this work, we develop an uncertainty visualization framework that captures boundary and interior uncertainties, i.e., structural variations, of an ensemble of ARs that arise from a set of ARDTs. We first provide a statistical overview of the AR boundaries using the contour boxplots of Whitaker et al. that highlight the structural variations of AR boundaries based on their nesting relationships. We then introduce the topological skeletons of ARs based on Morse complexes that characterize the interior variation of an ensemble of ARs. We propose an uncertainty visualization of these topological skeletons, inspired by MetroSets of Jacobson et al. that emphasizes the agreements and disagreements across the ensemble members. Through case studies and expert feedback, we demonstrate that the two approaches complement each other, and together they could facilitate an effective comparative analysis process and provide a more confident outlook on an AR's shape, area, and onshore impact.

 

Eruptive mass loss of massive stars prior to supernova (SN) explosion is key to understanding their evolution and end fate. An observational signature of pre-SN mass loss is the detection of an early, short-lived peak prior to the radioactive-powered peak in the lightcurve of the SN. This is usually attributed to the SN shock passing through an extended envelope or circumstellar medium. Such an early peak is common for double-peaked Type IIb SNe with an extended hydrogen envelope but uncommon for normal Type Ibc SNe with very compact progenitors. In this paper, we systematically study a sample of 14 double-peaked Type Ibc SNe out of 475 Type Ibc SNe detected by the Zwicky Transient Facility. The rate of these events is ∼3%–9% of Type Ibc SNe. A strong correlation is seen between the peak brightness of the first and the second peak. We perform a holistic analysis of this sample’s photometric and spectroscopic properties. We find that six SNe have ejecta mass less than 1.5M_⊙. Based on the nebular spectra and lightcurve properties, we estimate that the progenitor masses for these are less than ∼12M_⊙. The rest have an ejecta mass >2.4M_⊙and a higher progenitor mass. This sample suggests that the SNe with low progenitor masses undergo late-time binary mass transfer. Meanwhile, the SNe with higher progenitor masses are consistent with wave-driven mass loss or pulsation-pair instability-driven mass-loss simulations.

 

The origin of cosmic high-energy neutrinos remains largely unexplained. For high-energy neutrino alerts from IceCube, a coincidence with time-variable emission has been seen for three different types of accreting black holes: (1) a gamma-ray flare from a blazar (TXS 0506+056), (2) an optical transient following a stellar tidal disruption event (TDE; AT2019dsg), and (3) an optical outburst from an active galactic nucleus (AGN; AT2019fdr). For the latter two sources, infrared follow-up observations revealed a powerful reverberation signal due to dust heated by the flare. This discovery motivates a systematic study of neutrino emission from all supermassive black hole with similar dust echoes. Because dust reprocessing is agnostic to the origin of the outburst, our work unifies TDEs and high-amplitude flares from AGN into a population that we dub accretion flares. Besides the two known events, we uncover a third flare that is coincident with a PeV-scale neutrino (AT2019aalc). Based solely on the optical and infrared properties, we estimate a significance of 3.6σ for this association of high-energy neutrinos with three accretion flares. Our results imply that at least ∼10 per cent of the IceCube high-energy neutrino alerts could be due to accretion flares. This is surprising because the sum of the fluence of these flares is at least three orders of magnitude lower compared to the total fluence of normal AGN. It thus appears that the efficiency of high-energy neutrino production in accretion flares is increased compared to non-flaring AGN. We speculate that this can be explained by the high Eddington ratio of the flares.

 

Multipeaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility. Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (−17.4 mag) and long (∼100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew’s spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak’s photospheric phase, before Hαresurfaces again during the nebular phase. The nebular lines ([Oi], [Caii], Mgi], Hα) exhibit a double-peaked structure that hints toward a clumpy or nonspherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than that of normal SESNe as well as requiring a very high⁵⁶Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak and also powers the second peak of the light curve through interaction of the SN with the circumstellar medium.

 

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 of${1.37}_{-0.30}^{+0.26}\times {10}^{-6}$Mpc⁻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.