Search

The $n=1$ photon ring is an important probe of black hole (BH) properties and will be resolved by the Black Hole Explorer (BHEX) for the first time. However, extraction of black hole parameters from observations of the $n=1$ subring is not trivial. Developing this capability can be achieved by building a sample of $n=1$ subring simulations, as well as by performing feature extraction on this high-volume sample to track changes in the geometry, which presents significant computational challenges. Here, we present a framework for the study of $n=1$ photon ring behavior and BH property measurement from BHEX images. We use KerrBAM to generate a grid of $\gtrsim10^6$ images of $n=1$ photon rings spanning the entire space of Kerr BH spins and inclinations. Intensity profiles are extracted from images using a novel feature extraction method developed specifically for BHEX. This novel method is highly optimized and outperforms existing EHT methods by a factor of ${\sim}3000$. Additionally, we propose a novel, minimal set of geometric measurables for characterizing the behavior of the $n=1$ subring geometry. We apply these measurables to our simulation grid and test spin recovery on simulated images using: (i) gradient boosting, a machine learning algorithm; and (ii) an extension of Deep Horizon, a deep learning framework. We find $\gtrsim90$\% correct recovery of BH properties using the machine/deep learning approaches, and characterize the space of resolution-dependent geometric degeneracies. Finally, we test both approaches on GRMHD simulations of black hole accretion flows, and report accurate recovery of spin at the expected inclination of M87*., Comment: 15 pages, 9 figures, Submitted for publication in ApJ

Industrial applications often exhibit multiple in-control patterns due to varying operating conditions, which makes a single functional linear model (FLM) inadequate to capture the complexity of the true relationship between a functional quality characteristic and covariates, which gives rise to the multimode profile monitoring problem. This issue is clearly illustrated in the resistance spot welding (RSW) process in the automotive industry, where different operating conditions lead to multiple in-control states. In these states, factors such as electrode tip wear and dressing may influence the functional quality characteristic differently, resulting in distinct FLMs across subpopulations. To address this problem, this article introduces the functional mixture regression control chart (FMRCC) to monitor functional quality characteristics with multiple in-control patterns and covariate information, modeled using a mixture of FLMs. A monitoring strategy based on the likelihood ratio test is proposed to monitor any deviation from the estimated in-control heterogeneous population. An extensive Monte Carlo simulation study is performed to compare the FMRCC with competing monitoring schemes that have already appeared in the literature, and a case study in the monitoring of an RSW process in the automotive industry, which motivated this research, illustrates its practical applicability.

Generative retrieval for search and recommendation is a promising paradigm for retrieving items, offering an alternative to traditional methods that depend on external indexes and nearest-neighbor searches. Instead, generative models directly associate inputs with item IDs. Given the breakthroughs of Large Language Models (LLMs), these generative systems can play a crucial role in centralizing a variety of Information Retrieval (IR) tasks in a single model that performs tasks such as query understanding, retrieval, recommendation, explanation, re-ranking, and response generation. Despite the growing interest in such a unified generative approach for IR systems, the advantages of using a single, multi-task model over multiple specialized models are not well established in the literature. This paper investigates whether and when such a unified approach can outperform task-specific models in the IR tasks of search and recommendation, broadly co-existing in multiple industrial online platforms, such as Spotify, YouTube, and Netflix. Previous work shows that (1) the latent representations of items learned by generative recommenders are biased towards popularity, and (2) content-based and collaborative-filtering-based information can improve an item's representations. Motivated by this, our study is guided by two hypotheses: [H1] the joint training regularizes the estimation of each item's popularity, and [H2] the joint training regularizes the item's latent representations, where search captures content-based aspects of an item and recommendation captures collaborative-filtering aspects. Our extensive experiments with both simulated and real-world data support both [H1] and [H2] as key contributors to the effectiveness improvements observed in the unified search and recommendation generative models over the single-task approaches., Comment: Accepted for publication in the 18th ACM Conference on Recommender Systems (RecSys'24)

The near-horizon region of a black hole impacts linear (LP) and circular polarization (CP) through strong lensing of photons, adding large-scale symmetries and anti-symmetries to the polarized image. To probe the signature of lensing in polarimetry, we utilise a geometric model of concentric, Gaussian rings of equal radius to investigate the transition in the Fourier plane at which the photon ring signal begins to dominate over the direct image. We find analytic, closed-form expressions for the transition radii in total intensity, LP, and CP, wherein the resultant formulae are composed of ratios of tunable image parameters, with the overall "scale" set primarily by the thickness of the direct image. Using these formulae, we compute the transition radii for time-averaged images of M87* simulations at 230 GHz, studying both Magnetically Arrested Disc (MAD) and Standard and Normal Evolution (SANE) configurations for various spin and electron heating models. We compare geometric values to radii obtained directly from the simulations through a coherent averaging scheme. We find that nearly all MAD models have a photon ring-dominated CP signal on long baselines shorter than the Earth diameter at 230 GHz. Across favored models for the M87* accretion flow identified by EHT polarimetric constraints, we quantify the sensitivity and antenna size requirements for the next-generation EHT and the Black Hole Explorer orbiter to detect these features. We find that the stringent requirements for CP favour explorations using long baselines on the ground, while LP remains promising on Earth-space baselines., Comment: Accepted by ApJ

The structure of many real-world datasets is intrinsically hierarchical, making the modeling of such hierarchies a critical objective in both unsupervised and supervised machine learning. Recently, novel approaches for hierarchical clustering with deep architectures have been proposed. In this work, we take a critical perspective on this line of research and demonstrate that many approaches exhibit major limitations when applied to realistic datasets, partly due to their high computational complexity. In particular, we show that a lightweight procedure implemented on top of pre-trained non-hierarchical clustering models outperforms models designed specifically for hierarchical clustering. Our proposed approach is computationally efficient and applicable to any pre-trained clustering model that outputs logits, without requiring any fine-tuning. To highlight the generality of our findings, we illustrate how our method can also be applied in a supervised setup, recovering meaningful hierarchies from a pre-trained ImageNet classifier.

Using the semi-analytic model Serotina, we investigate the cosmic spin evolution of supermassive black holes incorporating recent results from general relativistic magnetohydrodynamics simulations of spin-down from relativistic jets. We compare several variations of our model with compiled black hole spin measurements derived from X-ray reflection spectroscopy, correcting for a bias arising from the spin-dependent radiative efficiency of accretion flows. We show that the observed spin distribution is in agreement with a model that includes jet-driven spin-down, a key mechanism that acts to modulate spins across cosmic time at both high and very low specific accretion rates. The data also clearly prefer models with coherent accretion over models in which accretion disks rapidly switch from prograde to retrograde. We further predict spin distributions accessible via spatially resolved event horizons by the next-generation Event Horizon Telescope (ngEHT) and Black Hole Explorer (BHEX), as well as gravitational waves by the Laser Interferometer Space Antenna (LISA), each of which offer unique and distinct windows into the population of spinning black holes. Jet-driven spin-down is most strongly imprinted on the abundance of very highly spinning objects in our model. In addition, we show that the spin distribution sampled by LISA events may contain a signature of the natal spin distribution of heavy seeds, but not of light seeds, offering additional discrimination between these seeding pathways. Spin distributions from these future observed samples can be used to constrain the detailed physical properties of the accretion flow on horizon scales around supermassive black holes., Comment: 23 pages, 11 figures, 4 tables. Submitted to ApJ

The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on inter-continental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in October 2018. The longest-baseline detections approach 11$\,$G$\lambda$ corresponding to an angular resolution, or fringe spacing, of 19$\mu$as. The Allan deviation of the visibility phase at 870$\mu$m is comparable to that at 1.3$\,$mm on the relevant integration time scales between 2 and 100$\,$s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870$\mu$m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time., Comment: Corresponding author: S. Doeleman

Recent analyses of FGK stars in open clusters have helped clarify the precision with which a star's rotation rate and lithium content can be used as empirical indicators for its age. Here we apply this knowledge to stars observed by Kepler. Rotation periods are drawn from previous work; lithium is measured from new and archival Keck/HIRES spectra. We report rotation-based ages for 23,813 stars (harboring 795 known planets) for which our method is applicable. We find that our rotational ages recover the ages of stars in open clusters spanning 0.04-2.5 Gyr; they also agree with over 90% of the independent lithium ages. The resulting yield includes 63 planets younger than 1 Gyr at 2$\sigma$, and 109 with median ages below 1 Gyr. This is about half the number expected under the classic assumption of a uniform star formation history. The age distribution that we observe, rather than being uniform, shows that the youngest stars in the Kepler field are 3-5 times rarer than stars 3 Gyr old. This trend holds for both known planet hosts and for the parent stellar sample. We attribute this "demographic cliff" to a combination of kinematic heating and a declining star formation rate in the Galaxy's thin disk, and highlight its impact on the age distribution of known transiting exoplanets., Comment: AJ accepted. CSV files for Tables 1 and 2 are uploaded. Comments welcome!

Planet formation is strongly influenced by the composition and distribution of volatiles within protoplanetary disks. With JWST, it is now possible to obtain direct observational constraints on disk ices, as recently demonstrated by the detection of ice absorption features towards the edge-on HH 48 NE disk as part of the Ice Age Early Release Science program. Here, we introduce a new radiative transfer modeling framework designed to retrieve the composition and mixing status of disk ices using their band profiles, and apply it to interpret the H2O, CO2, and CO ice bands observed towards the HH 48 NE disk. We show that the ices are largely present as mixtures, with strong evidence for CO trapping in both H2O and CO2 ice. The HH 48 NE disk ice composition (pure vs. polar vs. apolar fractions) is markedly different from earlier protostellar stages, implying thermal and/or chemical reprocessing during the formation or evolution of the disk. We infer low ice-phase C/O ratios around 0.1 throughout the disk, and also demonstrate that the mixing and entrapment of disk ices can dramatically affect the radial dependence of the C/O ratio. It is therefore imperative that realistic disk ice compositions are considered when comparing planetary compositions with potential formation scenarios, which will fortunately be possible for an increasing number of disks with JWST., Comment: Accepted to ApJ. 24 pages, 15 figures

We study dipole Chern-Simons theory with and without a cosmological constant in $2+1$ dimensions. We write the theory in a second order formulation and show that this leads to a fracton gauge theory coupled to Aristotelian geometry which can also be coupled to matter. This coupling exhibits the remarkable property of generalizing dipole gauge invariance to curved spacetimes, without placing any limitations on the possible geometries. We also use the second order formulation to construct a higher dimensional generalization of the action. Finally, for the $(2+1)$-dimensional Chern-Simons theory we find solutions and interpret these as electric monopoles, analyze their charges and argue that the asymptotic symmetries are infinite-dimensional., Comment: 25 pages, no figures

We present the results of Sun-as-a-star observations by the NEID Solar Telescope at WIYN Observatory, spanning January 1, 2021 through June 30, 2024. We identify 117,060 observations which are unlikely to be significantly affected by weather, hardware or major calibration issues. We describe several high-level data products being made available to the community to aid in the interpretation and inter comparisons of NEID solar observations. Solar observations demonstrate excellent performance of NEID, including radial velocity (RV) accuracy and long-term stability of better than $\simeq 0.37$ m s$^{-1}$ over $\simeq 3.5$ years, even though NEID was not originally designed or optimized for daytime observations of the Sun. Currently, intrinsic stellar variability is the primary barrier to detecting Earth-analog planets for most nearby, Sun-like stars. We present a comparison of the effectiveness of several methods proposed to mitigate the effects of solar variability on the Sun's estimated RV. We find that the Scalpels algorithm performs particularly well and substantially reduces the RMS RV of solar spectra from over 2 m s$^{-1}$ to 0.277 m s$^{-1}$. Even when training on a subset of days with NEID solar observations and testing on a held-out sample, the RMS of cleaned RV is 0.34-0.42 m s$^{-1}$. This is significantly better than previous attempts at removing solar variability and suggests that the current generation of EPRV instruments are technically capable of detecting Earth-mass planets orbiting a solar twin if provided with sufficient observing time allocations ($\sim 10^3$ nights of observations)., Comment: 25 pages, 14 figures. Submitted to AAS Journals. Data release archived at https://zenodo.org/doi/10.5281/zenodo.13363761

In the era of Large Language Models (LLMs), given their remarkable text understanding and generation abilities, there is an unprecedented opportunity to develop new, LLM-based methods for trustworthy medical knowledge synthesis, extraction and summarization. This paper focuses on the problem of Pharmacovigilance (PhV), where the significance and challenges lie in identifying Adverse Drug Events (ADEs) from diverse text sources, such as medical literature, clinical notes, and drug labels. Unfortunately, this task is hindered by factors including variations in the terminologies of drugs and outcomes, and ADE descriptions often being buried in large amounts of narrative text. We present MALADE, the first effective collaborative multi-agent system powered by LLM with Retrieval Augmented Generation for ADE extraction from drug label data. This technique involves augmenting a query to an LLM with relevant information extracted from text resources, and instructing the LLM to compose a response consistent with the augmented data. MALADE is a general LLM-agnostic architecture, and its unique capabilities are: (1) leveraging a variety of external sources, such as medical literature, drug labels, and FDA tools (e.g., OpenFDA drug information API), (2) extracting drug-outcome association in a structured format along with the strength of the association, and (3) providing explanations for established associations. Instantiated with GPT-4 Turbo or GPT-4o, and FDA drug label data, MALADE demonstrates its efficacy with an Area Under ROC Curve of 0.90 against the OMOP Ground Truth table of ADEs. Our implementation leverages the Langroid multi-agent LLM framework and can be found at https://github.com/jihyechoi77/malade., Comment: Paper published at Machine Learning for Healthcare 2024 (MLHC'24)

Mechanistic interpretability aims to reverse engineer the computation performed by a neural network in terms of its internal components. Although there is a growing body of research on mechanistic interpretation of neural networks, the notion of a mechanistic interpretation itself is often ad-hoc. Inspired by the notion of abstract interpretation from the program analysis literature that aims to develop approximate semantics for programs, we give a set of axioms that formally characterize a mechanistic interpretation as a description that approximately captures the semantics of the neural network under analysis in a compositional manner. We use these axioms to guide the mechanistic interpretability analysis of a Transformer-based model trained to solve the well-known 2-SAT problem. We are able to reverse engineer the algorithm learned by the model -- the model first parses the input formulas and then evaluates their satisfiability via enumeration of different possible valuations of the Boolean input variables. We also present evidence to support that the mechanistic interpretation of the analyzed model indeed satisfies the stated axioms.

Multiflavor gauge theories of matter systems on a three-dimensional lattice have recently been widely investigated especially in connection with a possible symmetry enlargement at a continuous phase transition. Abelian models were studied both with compact gauge fields and in a mixed formulation in which the coupling with matter fields is in compact form while the gauge fields Lagrangian is written in terms of noncompact gauge fields, getting quite different results. Such a mixed formulation is not permissible for non-Abelian theories, for which however there exists an entirely noncompact formulation (in which exact gauge invariance is enforced by help of auxiliary fields), which for SU(2) was shown to yield in the scaling window a larger physical volume than Wilson's one. The corresponding U(1) noncompact regularization is derived in the present work. In both Abelian and SU(2) cases there is only one auxiliary field that for a large mass has a linear coupling with the other fields and it can be integrated out yielding a negative definite correction. The coupling with the auxiliary field might make the inversion of the fermion matrix easier., Comment: 11 pages; a new section (sec. V) added; match the published version

The polarized images of the supermassive black hole Messier 87* (M87*) produced by the Event Horizon Telescope (EHT) provide a direct view of the near-horizon emission from a black hole accretion and jet system. The EHT theoretical analysis of the polarized M87* images compared thousands of snapshots from numerical models with a variety of spins, magnetization states, viewing inclinations, and electron energy distributions, and found a small subset consistent with the observed image. In this article, we examine two models favored by EHT analyses: a magnetically arrested disk with moderate retrograde spin and a magnetically arrested disk with high prograde spin. Both have electron distribution functions which lead to strong depolarization by cold electrons. We ray trace five snapshots from each model at 22, 43, 86, 230, 345, and 690 GHz to forecast future VLBI observations and examine limitations in numerical models. We find that even at low frequencies where optical and Faraday rotation depths are large, approximately rotationally symmetric polarization persists, suggesting that shallow depths dominate the polarization signal. However, morphology and spectra suggest that the assumed thermal electron distribution is not adequate to describe emission from the jet. We find 86 GHz images show a ring-like shape determined by a combination of plasma and spacetime imprints, smaller in diameter than recent results from the Global mm-VLBI array. We find that the photon ring becomes more apparent with increasing frequency, and is more apparent in the retrograde model, leading to large differences between models in asymmetry and polarization structure., Comment: 8 pages, 4 figures, accepted to ApJ

The Event Horizon Telescope (EHT) has imaged two supermassive black holes, Messier 87* (M87*) and Sagittarius A* (Sgr A*), using very-long-baseline interferometry (VLBI). The theoretical analyses of each source suggest magnetically arrested disk (MAD) accretion viewed at modest inclination. These MADs exhibit rotationally symmetric polarization of synchrotron emission caused by symmetries of their ordered magnetic fields. We leverage these symmetries to study the detectability of the black hole photon ring, which imposes known antisymmetries in polarization. In this letter, we propose a novel observational strategy based on coherent baseline-averaging of polarization ratios in a rotating basis to detect the photon ring with 345 GHz VLBI from the Earth's surface. Using synthetic observations from a likely future EHT, we find a reversal in polarimetric phases on long baselines that reveals the presence of the Sgr\,A* photon ring in a MAD system at 345 GHz, a critical frequency for lengthening baselines and overcoming interstellar scattering. We use our synthetic data and analysis pipeline to estimate requirements for the EHT using a new metric: ${\rm SNR}_{\rm PR}$, the signal-to-noise ratio of this polarimetric reversal signal. We identify long, coherent integrations using frequency phase transfer as a critical enabling technique for the detection of the photon ring, and predict a ${\rm SNR}_{\rm PR} \sim 2-3$ detection using proposed ngEHT parameters and currently-favored models for the Sgr A* accretion flow. We find that higher sensitivity, rather than denser Fourier sampling, is the most critical requirement for polarimetric detection of the photon ring., Comment: 9 pages, 5 figures, accepted to ApJL

Ice-coated dust grains provide the main reservoir of volatiles that play an important role in planet formation processes and may become incorporated into planetary atmospheres. However, due to observational challenges, the ice abundance distribution in protoplanetary disks is not well constrained. We present JWST/MIRI observations of the edge-on disk HH 48 NE carried out as part of the IRS program Ice Age. We detect CO$_2$, NH$_3$, H$_2$O and tentatively CH$_4$ and NH$_4^+$. Radiative transfer models suggest that ice absorption features are produced predominantly in the 50-100 au region of the disk. The CO$_2$ feature at 15 micron probes a region closer to the midplane (z/r = 0.1-0.15) than the corresponding feature at 4.3 micron (z/r = 0.2-0.6), but all observations trace regions significantly above the midplane reservoirs where we expect the bulk of the ice mass to be located. Ices must reach a high scale height (z/r ~ 0.6; corresponding to modeled dust extinction Av ~ 0.1), in order to be consistent with the observed vertical distribution of the peak ice optical depths. The weakness of the CO$_2$ feature at 15 micron relative to the 4.3 micron feature and the red emission wing of the 4.3 micron CO$_2$ feature are both consistent with ices being located at high elevation in the disk. The retrieved NH$_3$ abundance and the upper limit on the CH$_3$OH abundance relative to H$_2$O are significantly lower than those in the interstellar medium (ISM), but consistent with cometary observations. Full wavelength coverage is required to properly study the abundance distribution of ices in disks. To explain the presence of ices at high disk altitudes, we propose two possible scenarios: a disk wind that entrains sufficient amounts of dust, thus blocking part of the stellar UV radiation, or vertical mixing that cycles enough ices into the upper disk layers to balance ice photodesorption., Comment: 16 pages, 11 figures, accepted in A&A

The Event Horizon Telescope has produced resolved images of the supermassive black holes Sgr A* and M87*, which present the largest shadows on the sky. In the next decade, technological improvements and extensions to the array will enable access to a greater number of sources, unlocking studies of a larger population of supermassive black holes through direct imaging. In this paper, we identify 12 of the most promising sources beyond Sgr A* and M87* based on their angular size and millimeter flux density. For each of these sources, we make theoretical predictions for their observable properties by ray tracing general relativistic magnetohydrodynamic models appropriately scaled to each target's mass, distance, and flux density. We predict that these sources would have somewhat higher Eddington ratios than M87*, which may result in larger optical and Faraday depths than previous EHT targets. Despite this, we find that visibility amplitude size constraints can plausibly recover masses within a factor of 2, although the unknown jet contribution remains a significant uncertainty. We find that the linearly polarized structure evolves substantially with Eddington ratio, with greater evolution at larger inclinations, complicating potential spin inferences for inclined sources. We discuss the importance of 345 GHz observations, milli-Jansky baseline sensitivity, and independent inclination constraints for future observations with upgrades to the Event Horizon Telescope (EHT) through ground updates with the next-generation EHT (ngEHT) program and extensions to space through the Black Hole Explorer (BHEX)., Comment: 21 pages, 9 figures, 1 table, submitted to ApJ

It has long been established that certain higher-dimensional topological phases of matter support extended objects like quasi-strings and quasi-membranes in their bulk states. In this study, we investigate the physics of these topological systems using a phase-space approach in the semiclassical regime, incorporating tensorial coordinates related to the extended objects. Specifically, we explore the semiclassical currents associated to open quasi-strings in topological phases in three spatial dimensions, considering the presence of both coordinate-space Kalb-Ramond fields and momentum-space tensor Berry connections. Our results show that the currents associated to the endpoints of open quasi-strings on the system's boundary exhibit a quantized Hall response. This formalism accurately reproduces the boundary response as predicted by an Abelian BF theory proving a novel way to study extended objects in topological matter., Comment: 5 pages

The phase separation that occurs in two-temperature mixtures, which are driven out of equilibrium at the local scale, has been thoroughly characterized, but much less is known about the depletion interactions that drive it. Using numerical simulations in dimension 2, we show that the depletion interactions extend beyond two particle diameters in dilute systems, as expected at equilibrium, and decay algebraically with an exponent $-4$. Solving for the $N$-particle distribution function in the stationary state, perturbatively in the interaction potential, we show that algebraic correlations with an exponent $-2d$ arise from triplets of particles at different temperatures in spatial dimension $d$. Finally, simulations allow us to extend our results beyond the perturbative limit.

We present the Black Hole Explorer (BHEX), a mission that will produce the sharpest images in the history of astronomy by extending submillimeter Very-Long-Baseline Interferometry (VLBI) to space. BHEX will discover and measure the bright and narrow "photon ring" that is predicted to exist in images of black holes, produced from light that has orbited the black hole before escaping. This discovery will expose universal features of a black hole's spacetime that are distinct from the complex astrophysics of the emitting plasma, allowing the first direct measurements of a supermassive black hole's spin. In addition to studying the properties of the nearby supermassive black holes M87* and Sgr A*, BHEX will measure the properties of dozens of additional supermassive black holes, providing crucial insights into the processes that drive their creation and growth. BHEX will also connect these supermassive black holes to their relativistic jets, elucidating the power source for the brightest and most efficient engines in the universe. BHEX will address fundamental open questions in the physics and astrophysics of black holes that cannot be answered without submillimeter space VLBI. The mission is enabled by recent technological breakthroughs, including the development of ultra-high-speed downlink using laser communications, and it leverages billions of dollars of existing ground infrastructure. We present the motivation for BHEX, its science goals and associated requirements, and the pathway to launch within the next decade., Comment: Proceedings for SPIE Astronomical Telescopes and Instrumentation

We present a baseline science operations plan for the Black Hole Explorer (BHEX), a space mission concept aiming to confirm the existence of the predicted sharp ``photon ring" resulting from strongly lensed photon trajectories around black holes, as predicted by general relativity, and to measure its size and shape to determine the black hole's spin. BHEX will co-observe with a ground-based very long baseline interferometric (VLBI) array at high-frequency radio wavelengths, providing unprecedented high resolution with the extension to space that will enable photon ring detection and studies of active galactic nuclei. Science operations require a simultaneous coordination between BHEX and a ground array of large and small radio apertures to provide opportunities for surveys and imaging of radio sources, while coordination with a growing network of optical downlink terminals provides the data rates necessary to build sensitivity on long baselines to space. Here we outline the concept of operations for the hybrid observatory, the available observing modes, the observation planning process, and data delivery to achieve the mission goals and meet mission requirements., Comment: 12 pages, 10 figures, submitted to SPIE Astronomical Telescopes + Instrumentation (AS24)

The Black Hole Explorer (BHEX) is a mission concept that can dramatically improve state-of-the-art astronomical very long baseline interferometry (VLBI) imaging resolution by extending baseline distances to space. To support these scientific goals, a high data rate downlink is required from space to ground. Laser communications is a promising option for realizing these high data rate, long-distance space-to-ground downlinks with smaller space/ground apertures. Here, we present a scalable laser communications downlink design and current lasercom mission results., Comment: Submitted to SPIE Astronomical Telescopes + Instrumentation, 2024

General relativity predicts that black hole images ought to display a bright, thin (and as-of-yet-unresolved) ring. This "photon ring" is produced by photons that explore the strong gravity of the black hole, flowing along trajectories that experience extreme light bending within a few Schwarzschild radii of the horizon before escaping. The shape of the photon ring is largely insensitive to the precise details of the emission from the astronomical source surrounding the black hole and therefore provides a direct probe of the Kerr geometry and its parameters. The Black Hole Explorer (BHEX) is a proposed space-based experiment targeting the supermassive black holes M87* and Sgr A* with radio-interferometric observations at frequencies of 100 GHz through 300 GHz and from an orbital distance of ~30,000 km. This design will enable measurements of the photon rings around both M87* and Sgr A*, confirming the Kerr nature of these sources and delivering sharp estimates of their masses and spins., Comment: Submitted to SPIE Space Telescopes & Instrumentation

The challenges involved in executing neural networks (NNs) at the edge include providing diversity, flexibility, and sustainability. That implies, for instance, supporting evolving applications and algorithms energy-efficiently. Using hardware or software accelerators can deliver fast and efficient computation of the NNs, while flexibility can be exploited to support long-term adaptivity. Nonetheless, handcrafting an NN for a specific device, despite the possibility of leading to an optimal solution, takes time and experience, and that's why frameworks for hardware accelerators are being developed. This work, starting from a preliminary semi-integrated ONNX-to-hardware toolchain [21], focuses on enabling approximate computing leveraging the distinctive ability of the original toolchain to favor adaptivity. The goal is to allow lightweight adaptable NN inference on FPGAs at the edge., Comment: Proceedings of the XXIV International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS), June 29 - July 4, 2024. arXiv admin note: text overlap with arXiv:2309.13321

We present a complete census of candidate nuggets, i.e., dense galaxies likely formed by compaction with intense gas influx, within the volume-limited $z \sim 0$ REsolved Spectroscopy Of a Local VolumE (RESOLVE) survey. These nuggets span all evolutionary stages and 3 orders of magnitude in stellar mass ($M_{*} \sim 10^{8} M_\odot$ to $10^{11} M_\odot$) from the dwarf to the giant regime. We develop selection criteria for our $z\sim0$ nugget candidates based on structure and introduce the use of environmental criteria to eliminate nugget-like objects with suspected non-compaction origins. The resulting $z\sim0$ nuggets follow expectations with respect to structure (i.e., density, size), population frequency, and likely origins. We show that the properties of our nugget census are consistent with permanent quenching above the gas-richness threshold scale (halo mass $M_{halo} \sim 10^{11.4} M_\odot$), cyclic temporary quenching below the threshold scale, and feedback from active galactic nuclei (AGN) assisting in permanent quenching. As predicted in simulations, most nuggets quench within the halo mass range $M_{halo} \sim 10^{11.45} M_\odot$ to $10^{11.9} M_\odot$. We find $\sim 0.29$ dex scatter around the star-forming main sequence for candidate blue nuggets below the threshold scale, which is consistent with temporary quenching as seen in simulations. A transitional population of green nuggets appears above the threshold scale. AGN also become more common in nuggets above this scale, and we see a likely AGN excess in nuggets vs. comparably selected non-nuggets. Our results provide the first observational confirmation of the mass-dependent, AGN-mediated shift from cyclic quenching to halo quenching in nuggets., Comment: 18 pages, 14 figures

Query recommendation systems are ubiquitous in modern search engines, assisting users in producing effective queries to meet their information needs. However, these systems require a large amount of data to produce good recommendations, such as a large collection of documents to index and query logs. In particular, query logs and user data are not available in cold start scenarios. Query logs are expensive to collect and maintain and require complex and time-consuming cascading pipelines for creating, combining, and ranking recommendations. To address these issues, we frame the query recommendation problem as a generative task, proposing a novel approach called Generative Query Recommendation (GQR). GQR uses an LLM as its foundation and does not require to be trained or fine-tuned to tackle the query recommendation problem. We design a prompt that enables the LLM to understand the specific recommendation task, even using a single example. We then improved our system by proposing a version that exploits query logs called Retriever-Augmented GQR (RA-GQR). RA-GQr dynamically composes its prompt by retrieving similar queries from query logs. GQR approaches reuses a pre-existing neural architecture resulting in a simpler and more ready-to-market approach, even in a cold start scenario. Our proposed GQR obtains state-of-the-art performance in terms of NDCG@10 and clarity score against two commercial search engines and the previous state-of-the-art approach on the Robust04 and ClueWeb09B collections, improving on average the NDCG@10 performance up to ~4% on Robust04 and ClueWeb09B w.r.t the previous best competitor. RA-GQR further improve the NDCG@10 obtaining an increase of ~11%, ~6\% on Robust04 and ClueWeb09B w.r.t the best competitor. Furthermore, our system obtained ~59% of user preferences in a blind user study, proving that our method produces the most engaging queries., Comment: Generating Query Recommendations via LLMs

We present an updated version of GRASS (the GRanulation And Spectrum Simulator, Palumbo et al. 2022) which now uses an expanded library of 22 solar lines to empirically model time-resolved spectral variations arising from solar granulation. We show that our synthesis model accurately reproduces disk-integrated solar line profiles and bisectors, and we quantify the intrinsic granulation-driven radial-velocity (RV) variability for each of the 22 lines studied. We show that summary statistics of bisector shape (e.g., bisector inverse slope) are strongly correlated with the measured anomalous, variability-driven RV at high pixel signal-to-noise ratio (SNR) and spectral resolution. Further, the strength of the correlations vary both line by line and with the summary statistic used. These correlations disappear for individual lines at the typical spectral resolutions and SNRs achieved by current EPRV spectrographs; so we use simulations from GRASS to demonstrate that they can, in principle, be recovered by selectively binning lines that are similarly affected by granulation. In the best-case scenario (high SNR and large number of binned lines), we find that a $\lesssim$30$\%$ reduction in the granulation-induced root mean square (RMS) RV can be achieved, but that the achievable reduction in variability is most strongly limited by the spectral resolution of the observing instrument. Based on our simulations, we predict that existing ultra-high-resolution spectrographs, namely ESPRESSO and PEPSI, should be able to resolve convective variability in other, bright stars., Comment: 20 + 16 pages, 6 + 11 figures, 4 tables; in revision for AJ

We propose a simple, analytic dual-cone accretion model for horizon scale images of the cores of Low-Luminosity Active Galactic Nuclei (LLAGN), including those observed by the Event Horizon Telescope (EHT). Our underlying model is of synchrotron emission from an axisymmetric, magnetized plasma, which is constrained to flow within two oppositely oriented cones that are aligned with the black hole's spin axis. We show that this model can accurately reproduce images for a variety of time-averaged general relativistic magnetohydrodynamic (GRMHD) simulations, that it accurately recovers both the black hole and emission parameters from these simulations, and that it is sufficiently efficient to be used to measure these parameters in a Bayesian inference framework with radio interferometric data. We show that non-trivial topologies in the source image can result in non-trivial multi-modal solutions when applied to observations from a sparse array, such as the EHT 2017 observations of M87${}^*$. The presence of these degeneracies underscores the importance of employing Bayesian techniques that adequately sample the posterior space for the interpretation of EHT measurements. We fit our model to the EHT observations of M87${}^*$ and find a 95% Highest Posterior Density Interval (HPDI) for the mass-to-distance ratio of $\theta_g\in(2.84,3.75)\,\mu{\rm as}$, and give an inclination of $\theta_{\rm o}\in(11^\circ,24^\circ)$. These new measurements are consistent with mass measurements from the EHT and stellar dynamical estimates (e.g., Gebhardt et al. 2011; EHTC et al. 2019a,b; Liepold et al. 2023), and with the spin axis inclination inferred from properties of the M87${}^*$ jet (e.g., Walker et al. 2018).

We report the discovery of several classes of novel topological insulators (TIs) with hybrid-order boundary states generated from the first-order TIs with additional crystalline symmetries. Unlike the current studies on hybrid-order TIs where different-order topology arises from merging different-order TIs in various energy, these novel TIs exhibit a remarkable coexsitence of first-order gapless modes and higher-order Fermi-arc states, behaving as a hybrid between the first-order TIs and higher-order topological semimetals within a single bulk gap. Our findings establish a profound connection between these novel $d$-dimensional ($d$D) TIs and ($d-1$)D higher-order TIs (HOTIs), which can be understood as a result of stacking $(d-1)$D HOTIs to $d$D with $d=3,4$, revealing unconventional topological phase transitions by closing the gap in certain first-order boundaries rather than the bulk. The bulk-boundary correspondence between these higher-order Fermi-arcs and bulk topological invariants acossiated with additional crystallline symmetries is also demonstrated. We then discuss the conventional topological phase transitions from these novel TIs to nodal-line/nodal-surface semimetal phases, where the gapless phases host new kinds of topological responses. Meawhile, we present the corresponding topological semimetal phases by stacking these unique TIs. Finally, we discuss potential ways to realize these novel phases in synthetic and real materials, with a particular focus on the feasible implementation in optical lattices using ultracold atoms., Comment: More relevant references and the supplemental materials are added in this new version

Stellar photospheric inhomogeneities are a significant source of noise which currently precludes the discovery of Earth-mass planets orbiting Sun-like stars with the radial-velocity (RV) method. To complement several previous studies which have used ground- and spaced-based facilities to characterize the RV of the Sun, we here characterize the center-to-limb variability (CLV) of solar RVs arising from various solar-surface inhomogeneities observed by SDO/HMI and SDO/AIA. By using various SDO observables to classify pixels and calculate line-of-sight velocities as a function of pixel classification and limb angle, we show that each identified feature type, including the umbrae and penumbrae of sunspots, quiet-Sun magnetoconvective cells, magnetic network, and plage, exhibit distinct and complex CLV signatures, including a notable limb-angle dependence in the observed suppression of convective blueshift for magnetically active regions. We discuss the observed distributions of velocities by identified region type and limb angle, offer interpretations of the physical phenomena that shape these distributions, and emphasize the need to understand the RV signatures of these regions as astrophysical signals, rather than simple (un)correlated noise processes., Comment: 21 pages, 10 figures, 2 tables, accepted for publication in ApJ

Incompressibility plays a key role in the geometric description of fractional quantum Hall fluids. It is naturally related to quantum area-preserving diffeomorphisms and the underlying Girvin-MacDonald-Plazman algebra, which gives rise to an emergent non-relativistic massive spin-2 mode propagating in the bulk. The corresponding metric tensor can be identified with a nematic order parameter for the bulk states. In the linearised regime with a flat background, it has been shown that this mode can be described by a spin-2 Schroedinger action. However, quantum area-preserving diffeomorphisms also suggest the existence of higher-spin modes that cannot be described through nematic fractional quantum Hall states. Here, we consider p-atic Hall phases, in which the corresponding p-atic order parameters are related to higher-rank symmetric tensors. We then show that in this framework, non-relativistic massive chiral higher-spin fields naturally emerge and that their dynamics is described by higher-spin Schroedinger actions. We finally show that these effective actions can be derived from relativistic massive higher-spin theories in 2+1 dimensions after taking a non-relativistic limit., Comment: 5+6 pages

Despite the well-acknowledged benefits of physical activity for type 2 diabetes (T2D) prevention, the literature surprisingly lacks validated models able to predict the long-term benefits of exercise on T2D progression and support personalized risk prediction and prevention. To bridge this gap, we developed a novel mathematical model that formalizes the link between exercise and short- and long-term glucose-insulin dynamics to predict the benefits of regular exercise on T2D progression. The model quantitatively captured the dose-response relationship (larger benefits with increasing intensity and/or duration of exercise), it consistently reproduced the benefits of clinical guidelines for diabetes prevention, and it accurately predicted persistent benefits following interruption of physical activity, in line with real-world evidence from the literature. These results are encouraging and can be the basis for future development of decision support tools able to assist patients and clinicians in tailoring preventive lifestyle interventions.

One of the main problems in astrochemistry is determining the amount of sulfur in volatiles and refractories in the interstellar medium. The detection of the main sulfur reservoirs (icy H$_2$S and atomic gas) has been challenging, and estimates are based on the reliability of models to account for the abundances of species containing less than 1% of the total sulfur. The high sensitivity of the James Webb Space Telescope provides an unprecedented opportunity to estimate the sulfur abundance through the observation of the [S I] 25.249 $\mu$m line. We used the [S III] 18.7 $\mu$m, [S IV] 10.5 $\mu$m, and [S l] 25.249 $\mu$m lines to estimate the amount of sulfur in the ionized and molecular gas along the Orion Bar. For the theoretical part, we used an upgraded version of the Meudon photodissociation region (PDR) code to model the observations. New inelastic collision rates of neutral atomic sulfur with ortho- and para- molecular hydrogen were calculated to predict the line intensities. The [S III] 18.7 $\mu$m and [S IV] 10.5 $\mu$m lines are detected over the imaged region with a shallow increase (by a factor of 4) toward the HII region. We estimate a moderate sulfur depletion, by a factor of $\sim$2, in the ionized gas. The corrugated interface between the molecular and atomic phases gives rise to several edge-on dissociation fronts we refer to as DF1, DF2, and DF3. The [S l] 25.249 $\mu$m line is only detected toward DF2 and DF3, the dissociation fronts located farthest from the HII region. The detailed modeling of DF3 using the Meudon PDR code shows that the emission of the [S l] 25.249 $\mu$m line is coming from warm ($>$ 40 K) molecular gas located at A$_{\rm V}$ $\sim$ 1$-$5 mag from the ionization front. Moreover, the intensity of the [S l] 25.249 $\mu$m line is only accounted for if we assume the presence of undepleted sulfur., Comment: 16 pages, 6 figures. Accepted for publication in Astronomy and Astrophysics

We present the first results of the JWST program PROJECT-J (PROtostellar JEts Cradle Tested with JWST ), designed to study the Class I source HH46 IRS and its outflow through NIRSpec and MIRI spectroscopy (1.66 to 28 micron). The data provide line-images (~ 6.6" in length with NIRSpec, and up to 20" with MIRI) revealing unprecedented details within the jet, the molecular outflow and the cavity. We detect, for the first time, the red-shifted jet within ~ 90 au from the source. Dozens of shock-excited forbidden lines are observed, including highly ionized species such as [Ne III] 15.5 micron, suggesting that the gas is excited by high velocity (> 80 km/s) shocks in a relatively high density medium. Images of H2 lines at different excitations outline a complex molecular flow, where a bright cavity, molecular shells, and a jet-driven bow-shock interact with and are shaped by the ambient conditions. Additional NIRCam 2 micron images resolve the HH46 IRS ~ 110 au binary system and suggest that the large asymmetries observed between the jet and the H2 wide angle emission could be due to two separate outflows being driven by the two sources. The spectra of the unresolved binary show deep ice bands and plenty of gaseous lines in absorption, likely originating in a cold envelope or disk. In conclusion, JWST has unraveled for the first time the origin of the HH46 IRS complex outflow demonstrating its capability to investigate embedded regions around young stars, which remain elusive even at near-IR wavelengths., Comment: 28 pages, 15 figures, Accepted for publication on The Astrophysical Journal (9 April 2024)

Mid-infrared emission features probe the properties of ionized gas, and hot or warm molecular gas. The Orion Bar is a frequently studied photodissociation region (PDR) containing large amounts of gas under these conditions, and was observed with the MIRI IFU aboard JWST as part of the "PDRs4All" program. The resulting IR spectroscopic images of high angular resolution (0.2") reveal a rich observational inventory of mid-IR emission lines, and spatially resolve the substructure of the PDR, with a mosaic cutting perpendicularly across the ionization front and three dissociation fronts. We extracted five spectra that represent the ionized, atomic, and molecular gas layers, and measured the most prominent gas emission lines. An initial analysis summarizes the physical conditions of the gas and the potential of these data. We identified around 100 lines, report an additional 18 lines that remain unidentified, and measured the line intensities and central wavelengths. The H I recombination lines originating from the ionized gas layer bordering the PDR, have intensity ratios that are well matched by emissivity coefficients from H recombination theory, but deviate up to 10% due contamination by He I lines. We report the observed emission lines of various ionization stages of Ne, P, S, Cl, Ar, Fe, and Ni, and show how certain line ratios vary between the five regions. We observe the pure-rotational H$_2$ lines in the vibrational ground state from 0-0 S(1) to 0-0 S(8), and in the first vibrationally excited state from 1-1 S(5) to 1-1 S(9). We derive H$_2$ excitation diagrams, and approximate the excitation with one thermal (~700 K) component representative of an average gas temperature, and one non-thermal component (~2700 K) probing the effect of UV pumping. We compare these results to an existing model for the Orion Bar PDR and highlight the differences with the observations., Comment: 26 pages, 12 figures, 3 tables. Submitted to A&A, under review (1st revision)

Very long baseline interferometry (VLBI) provides the highest-resolution images in astronomy. The sharpest resolution is nominally achieved at the highest frequencies, but as the observing frequency increases so too does the atmospheric contribution to the system noise, degrading the sensitivity of the array and hampering detection. In this paper, we explore the limits of high-frequency VLBI observations using ngehtsim, a new tool for generating realistic synthetic data. ngehtsim uses detailed historical atmospheric models to simulate observing conditions, and it employs heuristic visibility detection criteria that emulate single- and multi-frequency VLBI calibration strategies. We demonstrate the fidelity of ngehtsim's predictions using a comparison with existing 230 GHz data taken by the Event Horizon Telescope (EHT), and we simulate the expected performance of EHT observations at 345 GHz. Though the EHT achieves a nearly 100% detection rate at 230 GHz, our simulations indicate that it should expect substantially poorer performance at 345 GHz; in particular, observations of M87 at 345 GHz are predicted to achieve detection rates of $\lesssim$20% that may preclude imaging. Increasing the array sensitivity through wider bandwidths and/or longer integration times -- as enabled through, e.g., the simultaneous multi-frequency upgrades envisioned for the next-generation EHT -- can improve the 345 GHz prospects and yield detection levels that are comparable to those at 230 GHz. M87 and Sgr A* observations carried out in the atmospheric window around 460 GHz could expect to regularly achieve multiple detections on long baselines, but analogous observations at 690 and 875 GHz consistently obtain almost no detections at all., Comment: 29 pages, 12 figures, accepted for publication in ApJ

Earth-based Very Long Baseline Interferometry (VLBI) has made rapid advances in imaging black holes. However, due to the limitations imposed on terrestrial VLBI by the Earth's finite size and turbulent atmosphere, it is imperative to have a space-based component in future VLBI missions. Herein, this paper investigates the effect of Earth's oblateness, also known as the $J_{2}$ effect, on orbiters in Earth-Space and Space-Space VLBI. The paper provides an extensive discussion on how the $J_{2}$ effect can directly impact orbit selection for black hole observations and how through informed choices of orbital parameters, the effect can be used to the mission's advantage, a fact that has not been addressed in existing space-VLBI investigations. We provide a comprehensive study of how the orbital parameters of several current space VLBI proposals will vary specifically due to the $J_{2}$ effect. For black hole accretion flow targets of interest, we have demonstrated how the $J_{2}$ effect leads to modest increase in shorter baseline coverage, filling gaps in the $(u,v)$ plane. Subsequently, we construct a simple analytical formalism that allows isolation of the impact of the $J_{2}$ effect on the $(u,v)$ plane without requiring computationally intensive orbit propagation simulations. By directly constructing $(u,v)$ coverage using the $J_{2}$ affected and invariant equations of motion, we obtain distinct coverage patterns for M87* and SgrA* that show extremely dense coverage on short baselines as well as long term orbital stability on longer baselines., Comment: Accepted in ApJ

In the realm of personalization, integrating diverse information sources such as consumption signals and content-based representations is becoming increasingly critical to build state-of-the-art solutions. In this regard, two of the biggest trends in research around this subject are Graph Neural Networks (GNNs) and Foundation Models (FMs). While GNNs emerged as a popular solution in industry for powering personalization at scale, FMs have only recently caught attention for their promising performance in personalization tasks like ranking and retrieval. In this paper, we present a graph-based foundation modeling approach tailored to personalization. Central to this approach is a Heterogeneous GNN (HGNN) designed to capture multi-hop content and consumption relationships across a range of recommendable item types. To ensure the generality required from a Foundation Model, we employ a Large Language Model (LLM) text-based featurization of nodes that accommodates all item types, and construct the graph using co-interaction signals, which inherently transcend content specificity. To facilitate practical generalization, we further couple the HGNN with an adaptation mechanism based on a two-tower (2T) architecture, which also operates agnostically to content type. This multi-stage approach ensures high scalability; while the HGNN produces general purpose embeddings, the 2T component models in a continuous space the sheer size of user-item interaction data. Our comprehensive approach has been rigorously tested and proven effective in delivering recommendations across a diverse array of products within a real-world, industrial audio streaming platform.

In many modern industrial scenarios, the measurements of the quality characteristics of interest are often required to be represented as functional data or profiles. This motivates the growing interest in extending traditional univariate statistical process monitoring (SPM) schemes to the functional data setting. This article proposes a new SPM scheme, which is referred to as adaptive multivariate functional EWMA (AMFEWMA), to extend the well-known exponentially weighted moving average (EWMA) control chart from the univariate scalar to the multivariate functional setting. The favorable performance of the AMFEWMA control chart over existing methods is assessed via an extensive Monte Carlo simulation. Its practical applicability is demonstrated through a case study in the monitoring of the quality of a resistance spot welding process in the automotive industry through the online observations of dynamic resistance curves, which are associated with multiple spot welds on the same car body and recognized as the full technological signature of the process.