Event time series are sequences of discrete events occurring at irregular time intervals, each associated with a domain-specific observational modality. They are common in domains such as high-energy astrophysics, computational social science, cybersecurity, finance, healthcare, neuroscience, and seismology. Their unstructured and irregular structure poses significant challenges for extracting meaningful patterns and identifying salient phenomena using conventional techniques. We propose novel two- and three-dimensional tensor representations for event time series, coupled with sparse autoencoders that learn physically meaningful latent representations. These embeddings support a variety of downstream tasks, including anomaly detection, similarity-based retrieval, semantic clustering, and unsupervised classification. We demonstrate our approach on a real-world dataset from X-ray astronomy, showing that these representations successfully capture temporal and spectral signatures and isolate diverse classes of X-ray transients. Our framework offers a flexible, scalable, and generalizable solution for analyzing complex, irregular event time series across scientific and industrial domains.

As part of the Galactic Bulge Time Domain Survey (GBTDS), the Nancy Grace Roman Galactic Exoplanet Survey (RGES) will use microlensing to discover cold outer planets and free-floating planets unbound to stars. NASA has established several science requirements for the GBTDS to ensure RGES success. A key advantage of RGES is Roman's high angular resolution, which will allow detection of flux from many host stars. One requirement specifies that Roman must measure the masses and distances of 40% of detected planet hosts with 20% precision or better. To test this, we simulated microlensing events toward the GBTDS fields and used Fisher matrix analysis to estimate light curve parameter uncertainties. Combining these with Roman imaging observables (lens flux, relative lens-source proper motion), we estimated the achievable precision of lens mass and distance measurements. Using pyLIMASS, a publicly available code for estimating lens properties, we applied this analysis to 3,000 simulated events. Assuming the Cassan et al. (2012) exoplanet mass function, we find that >40% of host stars meet the required 20% precision threshold, confirming that the GBTDS can satisfy the mission requirement. We validated our approach by comparing our inferred lens masses and distances to empirical measurements from detailed image-constrained light curve modeling of historical microlensing events with Hubble and Keck follow-up imaging. Our results agree within roughly 1 sigma, demonstrating that both approaches yield consistent and reliable mass and distance estimates, and confirming the robustness of our simulations for Roman-era microlensing science.

Few planetary systems have measured mutual inclinations, and even less are found to be non-coplanar. Observing the gravitational interactions between exoplanets is an effective tool to detect non-transiting companions to transiting planets. Evidence of these interactions can manifest in the light curve through transit timing variations (TTVs) and transit duration variations (TDVs). Through analysis of Kepler photometry and joint TTV-TDV modeling, we confirm the detection of KOI-134 b, a transiting planet with mass and size similar to Jupiter on a period of ~67 days, and find that it exhibits high TTVs (~20-hr amplitude) and significant TDVs. We explain these signals with the presence of an innermost non-transiting planet in 2:1 resonance with KOI-134 b. KOI-134 c has a mass $M = 0.220^{+0.010}_{-0.011} M_\text{Jup}$ and a moderately-high mutual inclination with KOI-134 b of $i_\text{mut} = 15.4_{-2.5}^{+2.8}{^\circ}$. Moreover, the inclination variations of KOI-134 b are so large that the planet is predicted to stop transiting in about 100 years. This system architecture cannot be easily explained by any one formation mechanism, with other dynamical effects needed to excite the planets' mutual inclination while still preserving their resonance.

We present the AGN catalog and optical spectroscopy for the second data release of the Swift BAT AGN Spectroscopic Survey (BASS DR2). With this DR2 release we provide 1425 optical spectra, of which 1181 are released for the first time, for the 858 hard X-ray selected AGN in the Swift BAT 70-month sample. The majority of the spectra (813/1425, 57%) are newly obtained from VLT/Xshooter or Palomar/Doublespec. Many of the spectra have both higher resolution (R>2500, N~450) and/or very wide wavelength coverage (3200-10000 A, N~600) that are important for a variety of AGN and host galaxy studies. We include newly revised AGN counterparts for the full sample and review important issues for population studies, with 44 AGN redshifts determined for the first time and 780 black hole mass and accretion rate estimates. This release is spectroscopically complete for all AGN (100%, 858/858) with 99.8% having redshift measurements (857/858) and 96% completion in black hole mass estimates of unbeamed AGN (outside the Galactic plane). This AGN sample represents a unique census of the brightest hard X-ray selected AGN in the sky, spanning many orders of magnitude in Eddington ratio (Ledd=10^-5-100), black hole mass (MBH=10^5-10^10 Msun), and AGN bolometric luminosity (Lbol=10^40-10^47 ergs/s).

The Little Red Dots (LRDs) are high-redshift galaxies uncovered by JWST, characterized by small effective radii ($R_{\rm eff} \sim 80-300$ pc), number densities that are intermediate between those of typical galaxies and quasars, and a redshift distribution peaked at $z \sim 5$. We present a theoretical model in which the LRDs descend from dark matter halos in the extreme low-spin tail of the angular momentum distribution. Within this framework, we explain their three key observational signatures: (i) abundance, (ii) compactness, and (iii) redshift distribution. Our model focuses on observed, not modeled, properties; it is thus independent of whether they are powered primarily by a black hole or stars. We find that the assumption that the prototypical LRD at $z\sim5$ originates from halos in the lowest $\sim 1\%$ of the spin distribution is sufficient to reproduce both their observed number densities and physical sizes. The redshift evolution of their observability is driven by the interplay between the evolving compact disk fraction and cosmological surface brightness dimming. This effect leads to a well-defined "LRDs Era" at $48$, they are common but faint. Finally, we test the predicted redshift trend against observational data, finding excellent agreement. Additional observational support comes from their excess small-scale clustering and spectral signatures of extreme core densities, both of which are expected outcomes of galaxy formation in low-spin halos. These findings suggest that the LRDs are not a fundamentally distinct population but the natural manifestation of galaxies forming in the rarest, lowest angular momentum environments.

Imaging algorithms form powerful analysis tools for VLBI data analysis. However, these tools cannot measure certain image features (e.g., ring diameter) by their non-parametric nature. This is unfortunate since these image features are often related to astrophysically relevant quantities such as black hole mass. This paper details a new general image feature extraction technique that applies to a wide variety of VLBI image reconstructions called variational image domain analysis. Unlike previous tools, variational image domain analysis can be applied to any image reconstruction regardless of its structure. To demonstrate its flexibility, we analyze thousands of reconstructions from previous EHT synthetic datasets and recover image features such as diameter, orientation, and asymmetry. By measuring these features, VIDA can help extract astrophysically relevant quantities such as the mass and orientation of M 87.

Abridged: Very Low Luminosity Objects (VeLLOs) are deeply embedded, and extremely faint objects and are thought to be in the quiescent phase of the episodic accretion process. They fill an important gap in our understanding of star formation. The VeLLO in the isolated DC3272+18 cloud has undergone an outburst, and is thus an ideal target for investigating the chemical inventory in the gas phase of an object of its type. Observations with the Atacama Pathfinder EXperiment (APEX) in four spectral windows in the frequency range of 213.6--272.4~GHz have been carried out to identify molecules that can be directly linked to the past outburst, utilize the line fluxes, column densities, and the abundance ratios of the detected species to characterize the different physical components of the VeLLO, and probe for the presence of complex organic molecules. Nitric oxide (NO) is detected for the first time in a source of this type, and its formation could be induced by the sublimation of grain-surface species during the outburst. A pathway to form NO directly in the gas phase is from the photodissociation products created after the sublimation of H$_2$O and NH$_3$ from the ices. While the present time water snowline has likely retreated to pre-outburst small radius, the volatile NO species is still extensively present in the gas phase, as evident by its high column density relative to methanol in the observations. This suggests that NO could be potentially used to trace the water snowline in outbursting sources. In order to rule out non-thermal desorption processes that could also have led to the formation of NO, this proposition has to be verified with future observations at higher spatial resolution, and by searching for NO in additional targets.

In this paper, we compare the chemistry and the emission spectra of nitrogen-dominated cool, warm, and hot ultra-short-period (USP) super-Earth atmospheres in and out of chemical equilibrium at various surface pressure scenarios ranging from 0.1 to 10 bar. We link the one-dimensional VULCAN chemical kinetic code, in which thermochemical kinetic and vertical transport and photochemistry are taken into account, to the one-dimensional radiative transfer model, PETITRADTRANS, to predict the emission spectra of these planets. The radiative-convective temperature-pressure profiles were computed with the HELIOS code. Then, using PANDEXO noise simulator, we explore the observability of the differences produced by disequilibrium processes with the JWST. Our grids show how different surface pressures can significantly affect the temperature profiles, the atmospheric abundances, and consequently the emission spectra of these planets. We find that the divergences due to disequilibrium processes would be possible to observe in cooler planets by targeting HCN, C2H4, and CO, and in warmer planets by targeting CH4 with HCN, using the NIRSpec and MIRI LRS JWST instruments. These species are also found to be sensitive indicators of the existence of surfaces on nitrogen-dominated USP super-Earths, providing information regarding the thickness of these atmospheres.

Cassini's observations of Titan's atmosphere are exemplary benchmarks for exoplanet atmospheric studies owing to (1) their precision and (2) our independent knowledge of Titan. Leveraging these observations, we perform retrievals (i.e., analyses) of Titan's transmission spectrum to investigate the strengths/limitations of exoplanet atmospheric retrievals with a particular focus on the underlying assumptions regarding the molecular species included in the retrieval. We find that multiple hydrocarbons can be ``retrieved'' depending on the selection made ahead of a retrieval. More importantly, we find that the estimates of other parameters such as the abundance of key absorbers like methane can be biased by $\sim$0.5 dex (by a factor of $\sim$3) due to such choices. This shows that beyond the possible misidentification of a molecular feature (e.g., current debate surrounding dimethyl sulfide, DMS, in K2-18 b), the implicit molecular detections made pre-retrieval to avoid retrieving for hundreds of molecules at a time can bias a large range of parameters. We thus recommend sensitivity analysis to assess the dependencies of atmospheric inferences on such selections in tandem with complementary information (e.g., chemistry models) to support any pre-retrieval selection. Finally, we introduce an independent path to constrain the dominant atmospheric constituent, even when lacking observable absorption feature (e.g., H$_2$ and N$_2$) through the scale height.

The BAT AGN Spectroscopic Survey (BASS) is designed to provide a highly complete census of the key physical parameters of supermassive black holes (SMBHs) that power local active galactic nuclei (AGN) (z<0.3), including their bolometric luminosity, black hole mass, accretion rates, and line-of-sight gas obscuration, and the distinctive properties of their host galaxies (e.g., star formation rates, masses, and gas fractions). We present an overview of the BASS data release 2 (DR2), an unprecedented spectroscopic survey in spectral range, resolution, and sensitivity, including 1449 optical (3200-10000 A) and 233 NIR (1-2.5 um) spectra for the brightest 858 ultra-hard X-ray (14-195 keV) selected AGN across the entire sky and essentially all levels of obscuration. This release provides a highly complete set of key measurements (emission line measurements and central velocity dispersions), with 99.9% measured redshifts and 98% black hole masses estimated (for unbeamed AGN outside the Galactic plane). The BASS DR2 AGN sample represents a unique census of nearby powerful AGN, spanning over 5 orders of magnitude in AGN bolometric luminosity, black hole mass, Eddington ratio, and obscuration. The public BASS DR2 sample and measurements can thus be used to answer fundamental questions about SMBH growth and its links to host galaxy evolution and feedback in the local universe, as well as open questions concerning SMBH physics. Here we provide a brief overview of the survey strategy, the key BASS DR2 measurements, data sets and catalogs, and scientific highlights from a series of DR2-based works.

We take a snapshot of current resources available for teaching and learning AI with a focus on the Galleries, Libraries, Archives and Museums (GLAM) community. The review was carried out in 2021 and 2022. The review provides an overview of material we identified as being relevant, offers a description of this material and makes recommendations for future work in this area.

The Vera C. Rubin Observatory is slated to observe nearly 20 billion galaxies during its decade-long Legacy Survey of Space and Time. The rich imaging data it collects will be an invaluable resource for probing galaxy evolution across cosmic time, characterizing the host galaxies of transient phenomena, and identifying novel populations of anomalous systems. While machine learning models have shown promise for extracting galaxy features from multi-band astronomical imaging, the large dimensionality of the learned latent space presents a challenge for mechanistic interpretability studies. In this work, we present Minuet, a low-dimensional diffusion autoencoder for multi-band galaxy imaging. Minuet is trained to reconstruct 72x72-pixel $grz$ image cutouts of 6M galaxies within z&lt;1 from the Dark Energy Camera Legacy Survey using only five latent dimensions. By using a diffusion model conditioned on the transformer-based autoencoder's output for image reconstruction, we achieve semantically-meaningful latent representations of galaxy images while still allowing for high-fidelity, probabilistic reconstructions. We train a series of binary classifiers on Minuet's latent features to quantify their connection to morphological labels from Galaxy Zoo, and a conditional flow to produce posterior distributions of SED-derived redshifts, stellar masses, and star-formation rates. We further show the value of Minuet for nearest neighbor searches in the learned latent space. Minuet provides strong evidence for the low intrinsic dimensionality of galaxy imaging, and introduces a class of astrophysical models that produce highly compact representations for diverse science goals.

We look for simulated star-forming linear wakes such as the one recently discovered by van Dokkum et al. (2023) in the cosmological hydrodynamical simulation ASTRID. Amongst the runaway black holes in ASTRID, none are able to produce clear star-forming wakes. Meanwhile, fly-by encounters, typically involving a compact galaxy (with a central black hole) and a star-forming galaxy (with a duo of black holes) reproduce remarkably well many of the key properties (its length and linearity; recent star formation, etc.) of the observed star-forming linear feature. We predict the feature to persist for approximately 100 Myr in such a system and hence constitute a rare event. The feature contains a partly stripped galaxy (with $M_{\rm gal}=10^9 \sim 10^{10}M_\odot$) and a dual BH system ($M_{\rm BH}=10^5 \sim 10^7\,M_\odot$) in its brightest knot. X-ray emission from AGN in the knot should be detectable in such systems. After $100\sim 200\,{\rm Myrs}$ from the first fly-by, the galaxies merge leaving behind a triple black hole system in a (still) actively star-forming early-type remnant of mass $\sim 5\times 10^{10}\,M_\odot$. Follow-up JWST observations may be key for revealing the nature of these linear features by potentially detecting the older stellar populations constituting the bright knot. Confirmation of such detections may therefore help discriminate a fly-by encounter from a massive BH wake to reveal the origin of such features.

Observations of density variations in stellar streams are a promising probe of low-mass dark matter substructure in the Milky Way. However, survey systematics such as variations in seeing and sky brightness can also induce artificial fluctuations in the observed densities of known stellar streams. These variations arise because survey conditions affect both object detection and star-galaxy misclassification rates. To mitigate these effects, we use Balrog synthetic source injections in the Dark Energy Survey (DES) Y3 data to calculate detection rate variations and classification rates as functions of survey properties. We show that these rates are nearly separable with respect to survey properties and can be estimated with sufficient statistics from the synthetic catalogs. Applying these corrections reduces the standard deviation of relative detection rates across the DES footprint by a factor of five, and our corrections significantly change the inferred linear density of the Phoenix stream when including faint objects. Additionally, for artificial streams with DES like survey properties we are able to recover density power spectra with reduced bias. We also find that uncorrected power-spectrum results for LSST-like data can be around five times more biased, highlighting the need for such corrections in future ground based surveys.

I review and augment my work of the last few years on the physical origins and limitations of canonical quantum measurement behavior. Central to this work is a detailed analysis of the microstructure of real measurement devices. Particular attention is paid to the Mott problem, which addresses a simpler version of canonical quantum measurement behavior: It asks why an alpha particle emitted in a nuclear decay produces one and only one track in a cloud chamber. My analysis - entirely consistent with unitarity - leads to an emergent, approximate Born rule supported by experiment, with possible breakdown at very small probability density. I argue that a similar picture applies to other measurement scenarios, including Geiger counters, the Stern-Gerlach experiment and superconducting qubits.

We propose a dynamical protocol to probe the rigidity and phase coherence of dipolar supersolids by merging initially separated fragments in quasi-one-dimensional (1D) double-well potentials. Simulations based on the extended Gross-Pitaevskii equation reveal distinct dynamical signatures across phases. Supersolids exhibit damped crystal oscillations following barrier removal, with the damping rate reflecting superfluid connectivity. A phase-imprinted jump additionally triggers metastable dark solitons, which excites second sound, as revealed by an out-of-phase drift between the droplet lattice and the superfluid background. Our results show a realizable path to dynamically detect the second sound and rigidity of supersolids, as well as to realize and probe soliton formation.

Here, we report the discovery of a kilonova associated with the nearby (350 Mpc) minute-duration GRB 211211A. In tandem with deep optical limits that rule out the presence of an accompanying supernova to $M_I > -13$ mag at 17.7 days post-burst, the identification of a kilonova confirms that this burst's progenitor was a compact object merger. While the spectrally softer tail in GRB 211211A's gamma-ray light curve is reminiscent of previous extended emission short GRBs (EE-SGRBs), its prompt, bright spikes last $\gtrsim 12$ s, separating it from past EE-SGRBs. GRB 211211A's kilonova has a similar luminosity, duration and color to AT2017gfo, the kilonova found in association with the gravitational wave (GW)-detected binary neutron star (BNS) merger GW170817. We find that the merger ejected $\approx 0.04 M_{\odot}$ of r-process-rich material, and is consistent with the merger of two neutron stars (NSs) with masses close to the canonical $1.4 M_{\odot}$. This discovery implies that GRBs with long, complex light curves can be spawned from compact object merger events and that a population of kilonovae following GRBs with durations $\gg 2$ s should be accounted for in calculations of the NS merger r-process contribution and rate. At 350 Mpc, the current network of GW interferometers at design sensitivity would have detected the merger precipitating GRB 211211A, had it been operating at the time of the event. Further searches for GW signals coincident with long GRBs are therefore a promising route for future multi-messenger astronomy.

Using a quantum-mechanical close-coupling method, we calculate cross sections for fine structure excitation and relaxation of Si and S atoms in collisions with atomic hydrogen. Rate coefficients are calculated over a range of temperatures for astrophysical applications. We determine the temperature-dependent critical densities for the relaxation of Si and S in collisions with H and compare these to the critical densities for collisions with electrons. The present calculation should be useful in modeling environments exhibiting the [S i] 25 {\mu}m and [S i] 57 {\mu}m far-infrared emission lines or where cooling of S and Si by collisions with H are of interest.

We present SCUBA-2/POL-2 850 $\mu$m polarimetric observations of the circumstellar envelope (CSE) of the carbon-rich asymptotic giant branch (AGB) star IRC+10216. Both FIR and optical polarization data indicate grains aligned with their long axis in the radial direction relative to the central star. The 850 $\mu$m polarization does not show this simple structure. The 850 $\mu$m data are indicative, albeit not conclusive, of a magnetic dipole geometry. Assuming such a simple dipole geometry, the resulting 850 $\mu$m polarization geometry is consistent with both Zeeman observations and small-scale structure in the CSE. While there is significant spectral line polarization contained within the SCUBA-2 850 $\mu$m pass-band for the source, it is unlikely that our broadband polarization results are dominated by line polarization. To explain the required grain alignment, grain mineralogy effects, due to either fossil silicate grains from the earlier oxygen-rich AGB phase of the star, or due to the incorporation of ferromagnetic inclusions in the largest grains, may play a role. We argue that the most likely explanation is due to a new alignment mechanism \citep{arXiv:2009.11304} wherein a charged grain, moving relative to the magnetic field, precesses around the induced electric field and therefore aligns with the magnetic field. This mechanism is particularly attractive as the optical, FIR, and sub-mm wave polarization of the carbon dust can then be explained in a consistent way, differing simply due to the charge state of the grains.