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We examine the transient scattered and transmitted fields generated when an incident electromagnetic wave impinges on a dielectric scatterer or a coated conductor embedded in an infinite space. By applying a boundary-field equation method, we reformulate the problem in the Laplace domain using the electric field equation inside the scatterer and a system of boundary integral equations for the scattered electric field in free space. To analyze this nonlocal boundary problem, we replace it by an equivalent boundary value problem. Existence, uniqueness and stability of the weak solution to the equivalent BVP are established in appropriate function spaces in terms of the Laplace transformed variable. The stability bounds are translated into time-domain estimates which determine the regularity of the solution in terms of the regularity of the problem data. These estimates can be easily converted into error estimates for a numerical discretization on the convolution quadrature for time evolution.

New JWST/NIRCam wide-field slitless spectroscopy provides redshifts for four z>8 galaxies located behind the lensing cluster MACS J0416.1-2403. Two of them, "Y1" and "JD", have previously reported spectroscopic redshifts based on ALMA measurements of [OIII] 88 $\mu$m and/or [CII] 157.7 $\mu$m lines. Y1 is a merging system of three components, and the existing redshift z=8.31 is confirmed. However, JD is at z=8.34 instead of the previously claimed z=9.28. JD's close companion, "JD-N", which was a previously discovered z>8 candidate, is now identified at the same redshift as JD. JD and JD-N form an interacting pair. A new candidate at z>8, "f090d_018", is also confirmed and is at z=8.49. These four objects are likely part of an overdensity that signposts a large structure extending ~165 kpc in projected distance and ~48.7 Mpc in radial distance. They are magnified by less than one magnitude and have intrinsic $M_{UV}$ ranging from -19.57 to -20.83 mag. Their spectral energy distributions show that the galaxies are all very young with ages ~ 4-18 Myr and stellar masses about $10^{7-8}$ ${\rm M_\odot}$. These infant galaxies have very different star formation rates ranging from a few to over a hundred $\rm{M_\odot}$ yr$^{-1}$, but only two of them (JD and f090d_018) have blue rest-frame UV slopes $\beta<-2.0$ indicative of a high Lyman-continuum photon escape fraction that could contribute significantly to the cosmic hydrogen-reionizing background. Interestingly, these two galaxies are the least massive and least active ones among the four. The other two systems have much flatter UV slopes largely because of their high dust extinction ($A_{\rm V}$=0.9-1.0 mag). Their much lower indicated escape fractions show that even very young, actively star-forming galaxies can have negligible contribution to reionization when they quickly form dust throughout their bodies., Comment: 18 pages, 6 figures, after addressing the referee report

Graph Neural Networks (GNNs) excel in machine learning tasks involving graphs, such as node classification, graph classification, and link prediction. However, explaining their decision-making process is challenging due to the complex transformations GNNs perform by aggregating relational information from graph topology. Existing methods for explaining GNNs face key limitations: (1) lack of flexibility in generating explanations at varying levels, (2) difficulty in identifying unique substructures relevant to class differentiation, and (3) little support to ensure the trustworthiness of explanations. To address these challenges, we introduce GNNAnatomy, a visual analytics system designed to generate and evaluate multi-level GNN explanations for graph classification tasks. GNNAnatomy uses graphlets, primitive graph substructures, to identify the most critical substructures in a graph class by analyzing the correlation between GNN predictions and graphlet frequencies. These correlations are presented interactively for user-selected group of graphs through our visual analytics system. To further validate top-ranked graphlets, we measure the change in classification confidence after removing each graphlet from the original graph. We demonstrate the effectiveness of GNNAnatomy through case studies on synthetic and real-world graph datasets from sociology and biology domains. Additionally, we compare GNNAnatomy with state-of-the-art explainable GNN methods to showcase its utility and versatility.

Diffusion models have shown tremendous results in image generation. However, due to the iterative nature of the diffusion process and its reliance on classifier-free guidance, inference times are slow. In this paper, we propose a new distillation approach for guided diffusion models in which an external lightweight guide model is trained while the original text-to-image model remains frozen. We show that our method reduces the inference computation of classifier-free guided latent-space diffusion models by almost half, and only requires 1\% trainable parameters of the base model. Furthermore, once trained, our guide model can be applied to various fine-tuned, domain-specific versions of the base diffusion model without the need for additional training: this "plug-and-play" functionality drastically improves inference computation while maintaining the visual fidelity of generated images. Empirically, we show that our approach is able to produce visually appealing results and achieve a comparable FID score to the teacher with as few as 8 to 16 steps., Comment: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024 project page: https://5410tiffany.github.io/plug-and-play-diffusion-distillation.github.io/

The concept of persona, originally adopted in dialogue literature, has re-surged as a promising framework for tailoring large language models (LLMs) to specific context (e.g., personalized search, LLM-as-a-judge). However, the growing research on leveraging persona in LLMs is relatively disorganized and lacks a systematic taxonomy. To close the gap, we present a comprehensive survey to categorize the current state of the field. We identify two lines of research, namely (1) LLM Role-Playing, where personas are assigned to LLMs, and (2) LLM Personalization, where LLMs take care of user personas. Additionally, we introduce existing methods for LLM personality evaluation. To the best of our knowledge, we present the first survey for role-playing and personalization in LLMs under the unified view of persona. We continuously maintain a paper collection to foster future endeavors: https://github.com/MiuLab/PersonaLLM-Survey, Comment: Accepted to EMNLP 2024 Findings

Well-fitted clothing is essential for both real and virtual garments to enable self-expression and accurate representation for a large variety of body types. Common practice in the industry is to provide a pre-made selection of distinct garment sizes such as small, medium and large. While these may cater to certain groups of individuals that fall within this distribution, they often exclude large sections of the population. In contrast, individually tailored clothing offers a solution to obtain custom-fit garments that are tailored to each individual. However, manual tailoring is time-consuming and requires specialized knowledge, prohibiting the approach from being applied to produce fitted clothing at scale. To address this challenge, we propose a novel method leveraging differentiable simulation for refitting and draping 3D garments and their corresponding 2D pattern panels onto a new body shape, enabling a workflow where garments only need to be designed once, in a single size, and they can be automatically refitted to support numerous body size and shape variations. Our method enables downstream applications, where our optimized 3D drape can be directly ingested into game engines or other applications. Our 2D sewing patterns allow for accurate physics-based simulations and enables manufacturing clothing for the real world.

Paired single-cell sequencing technologies enable the simultaneous measurement of complementary modalities of molecular data at single-cell resolution. Along with the advances in these technologies, many methods based on variational autoencoders have been developed to integrate these data. However, these methods do not explicitly incorporate prior biological relationships between the data modalities, which could significantly enhance modeling and interpretation. We propose a novel probabilistic learning framework that explicitly incorporates conditional independence relationships between multi-modal data as a directed acyclic graph using a generalized hierarchical variational autoencoder. We demonstrate the versatility of our framework across various applications pertinent to single-cell multi-omics data integration. These include the isolation of common and distinct information from different modalities, modality-specific differential analysis, and integrated cell clustering. We anticipate that the proposed framework can facilitate the construction of highly flexible graphical models that can capture the complexities of biological hypotheses and unravel the connections between different biological data types, such as different modalities of paired single-cell multi-omics data. The implementation of the proposed framework can be found in the repository https://github.com/kuijjerlab/CAVACHON.

Understanding the nature of the luminous 1991T-like supernovae is of great importance to supernova cosmology as they are likely to have been more common in the early universe. In this paper we explore the observational properties of 1991T-like supernovae to study their relationship to other luminous, slow-declining Type~Ia supernovae (SNe Ia). From the spectroscopic and photometric criteria defined in Phillips et al. (1992), we identify 17 1991T-like supernovae from the literature. Combining these objects with ten 1991T-like supernovae from the Carnegie Supernova Project-II, the spectra, light curves, and colors of these events, along with their host galaxy properties, are examined in detail. We conclude that 1991T-like supernovae are closely related in essentially all of their UV, optical, and near-infrared properties -- as well as their host galaxy parameters -- to the slow-declining subset of Branch core-normal supernovae and to the intermediate 1999aa-like events, forming a continuum of luminous SNe Ia. The overriding difference between these three subgroups appears to be the extent to which $^{56}$Ni mixes into the ejecta, producing the pre-maximum spectra dominated by Fe III absorption, the broader UV light curves, and the higher luminosities that characterize the 1991T-like events. Nevertheless, the association of 1991T-like SNe with the rare Type Ia CSM supernovae would seem to run counter to this hypothesis, in which case 1991T-like events may form a separate subclass of SNe Ia, possibly arising from single-degenerate progenitor systems., Comment: Accepted for publication in ApJS

Extrapolation in Large language models (LLMs) for open-ended inquiry encounters two pivotal issues: (1) hallucination and (2) expensive training costs. These issues present challenges for LLMs in specialized domains and personalized data, requiring truthful responses and low fine-tuning costs. Existing works attempt to tackle the problem by augmenting the input of a smaller language model with information from a knowledge graph (KG). However, they have two limitations: (1) failing to extract relevant information from a large one-hop neighborhood in KG and (2) applying the same augmentation strategy for KGs with different characteristics that may result in low performance. Moreover, open-ended inquiry typically yields multiple responses, further complicating extrapolation. We propose a new task, the extreme multi-label KG link prediction task, to enable a model to perform extrapolation with multiple responses using structured real-world knowledge. Our retriever identifies relevant one-hop neighbors by considering entity, relation, and textual data together. Our experiments demonstrate that (1) KGs with different characteristics require different augmenting strategies, and (2) augmenting the language model's input with textual data improves task performance significantly. By incorporating the retrieval-augmented framework with KG, our framework, with a small parameter size, is able to extrapolate based on a given KG. The code can be obtained on GitHub: https://github.com/exiled1143/Retrieval-Augmented-Language-Model-for-Multi-Label-Knowledge-Graph-Link-Prediction.git

We provide the first extensive, numerical study of the non-trivial problem of mixing between flavor-singlet composite states emerging in strongly coupled lattice field theories with matter field content consisting of fermions transforming in different representations of the gauge group. The theory of interest is the minimal candidate for a composite Higgs model that also accommodates a mechanism for top partial compositeness: the $Sp(4)$ gauge theory coupled to two (Dirac) fermions transforming as the fundamental and three as the two-index antisymmetric representation of the gauge group, respectively. We apply an admixture of APE and Wuppertal smearings, as well as the generalized eigenvalue problem approach, to two-point functions involving flavor-singlet mesons, for ensembles having time extent longer than the space extent. We demonstrate that, in the region of lattice parameter space accessible to this study, both masses and mixing angles can be measured effectively, despite the presence of (numerically noisy) contributions from disconnected diagrams., Comment: 18 pages, 3 figures, 5 tables; v2: minor changes, added appendix A, version accepted for publication in PRD

The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). The Portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. Here we also highlight Duotang, a web platform that presents genomic epidemiology and modeling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the Portal (COVID-MVP, CoVizu), are all open-source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.

Spectral densities encode non-perturbative information that enters the calculation of a plethora of physical observables in strongly coupled field theories. Phenomenological applications encompass aspects of standard-model hadronic physics, observable at current colliders, as well as correlation functions characterizing new physics proposals, testable in future experiments. By making use of numerical data produced in a Sp(4) lattice gauge theory with matter transforming in an admixture of fundamental and 2-index antisymmetric representations of the gauge group, we perform a systematic study to demonstrate the effectiveness of recent technological progress in the reconstruction of spectral densities. To this purpose, we write and test new software packages that use energy-smeared spectral densities to analyze the mass spectrum of mesons. We assess the effectiveness of different smearing kernels and optimize the smearing parameters to the characteristics of available lattice ensembles. We generate new ensembles for the theory in consideration, with lattices that have a longer extent in the time direction with respect to the spatial ones. We run our tests on these ensembles, obtaining new results about the spectrum of light mesons and their excitations. We make available our algorithm and software for the extraction of spectral densities, that can be applied to theories with other gauge groups, including the theory of strong interactions (QCD) governing hadronic physics in the standard model., Comment: Version approved for publication. 45 pages, 20 figures

We present the second and final release of optical spectroscopy of Type Ia Supernovae (SNe Ia) obtained during the first and second phases of the Carnegie Supernova Project (CSP-I and CSP-II). The newly released data consist of 148 spectra of 30 SNe Ia observed in the course of the CSP-I, and 234 spectra of 127 SNe Ia obtained during the CSP-II. We also present 216 optical spectra of 46 historical SNe Ia, including 53 spectra of 30 SNe Ia observed by the Cal\'an/Tololo Supernova Survey. We combine these observations with previously published CSP data and publicly-available spectra to compile a large sample of measurements of spectroscopic parameters at maximum light, consisting of pseudo-equivalent widths and expansion velocities of selected features, for 232 CSP and historical SNe Ia (including more than 1000 spectra). Finally, we review some of the strongest correlations between spectroscopic and photometric properties of SNe Ia. Specifically, we define two samples: one consisting of SNe Ia discovered by targeted searches (most of them CSP-I objects) and the other composed of SNe Ia discovered by untargeted searches, which includes most of the CSP-II objects. The analysed correlations are similar for both samples. We find a larger incidence of SNe Ia belonging to the Cool (CL)and Broad Line (BL) Branch subtypes among the events discovered by targeted searches, Shallow Silicon (SS) SNe Ia are present with similar frequencies in both samples, while Core Normal (CN) SNe Ia are more frequent in untargeted searches., Comment: 59 pages, 16 figures, accepted for publication in The Astrophysical Journal. May 7, 2024: LaTex file updated: corrected one missing comma and an extraneous space in Table 2

We present a JWST MIRI/MRS spectrum (5-27 $\mathrm{\mu}$m) of the Type Ia supernova (SN Ia), SN 2021aefx at $+415$ days past $B$-band maximum. The spectrum, which was obtained during the iron-dominated nebular phase, has been analyzed in combination with previous JWST observations of SN 2021aefx, to provide the first JWST time series analysis of an SN Ia. We find the temporal evolution of the [Co III] 11.888 $\mathrm{\mu}$m feature directly traces the decay of $^{56}$Co. The spectra, line profiles, and their evolution are analyzed with off-center delayed-detonation models. Best fits were obtained with White Dwarf (WD) central densities of $\rho_c=0.9-1.1\times 10^9$g cm$^{-3}$, a WD mass of M$_{\mathrm{WD}}$=1.33-1.35M$_\odot$, a WD magnetic field of $\approx10^6$G, and an off-center deflagration-to-detonation transition at $\approx$ 0.5 $M_\odot$ seen opposite to the line of sight of the observer (-30). The inner electron capture core is dominated by energy deposition from $\gamma$-rays whereas a broader region is dominated by positron deposition, placing SN 2021aefx at +415 d in the transitional phase of the evolution to the positron-dominated regime. The formerly `flat-tilted' profile at 9 $\mathrm{\mu}$m now has significant contribution from [Ni IV], [Fe II], and [Fe III] and less from [Ar III], which alters the shape of the feature as positrons excite mostly the low-velocity Ar. Overall, the strength of the stable Ni features in the spectrum is dominated by positron transport rather than the Ni mass. Based on multi-dimensional models, our analysis is consistent with a single-spot, close-to-central ignition with an indication for a pre-existing turbulent velocity field, and excludes a multiple-spot, off-center ignition., Comment: Accepted for publication in ApJ

We present JWST/NIRSpec high-resolution spectroscopy G395H/F290LP of MACS0647-JD, a gravitationally lensed galaxy merger at $z=10.167$. The new spectroscopy, which is acquired for the two lensed images (JD1 and JD2), detects and resolves emission lines in the rest-frame ultraviolet (UV) and blue optical, including the resolved [OII]3726,3729 doublet, [NeIII]3870, [HeI]3890, H$\delta$, H$\gamma$, and [OIII]4363. This is the first observation of the resolved [OII]3726,3729 doublet for a galaxy at $z>8$. We measure a line flux ratio [OII]3729/3726 $= 0.9 \pm 0.3$, which corresponds to an estimated electron density of $\log(n_{e} / \rm{cm}^{-3}) = 2.9 \pm 0.5$. This is significantly higher than the electron densities of local galaxies reported in the literature. We compile the measurements from the literature and further analyze the redshift evolution of $n_{e}$. We find that the redshift evolution follows the power-law form of $n_{e} = A\times (1+z)^{p}$ with $A=54^{+31}_{-23}$ cm$^{-3}$ and $p=1.2^{+0.4}_{-0.4}$. This power-law form may be explained by a combination of metallicity and morphological evolution of galaxies, which become, on average, more metal-poor and more compact with increasing redshift., Comment: 20 pages, 11 figures. Accepted for publication in ApJ

JWST spectroscopy has revolutionized our understanding of galaxies in the early universe. Covering wavelengths up to $5.3\,{\rm \mu m}$, NIRSpec can detect rest-frame optical emission lines H$\alpha$ out to $z = 7$ and [O III] to $z = 9.5$. Observing these lines in more distant galaxies requires longer wavelength spectroscopy with MIRI. Here we present MIRI MRS IFU observations of the lensed galaxy merger MACS0647$-$JD at $z = 10.165$. With exposure times of 4.2 hours in each of two bands, we detect H$\alpha$ at $9\sigma$, [O III]$\,\lambda5008$ at $11\sigma$, and [O III]$\,\lambda4960$ at $3\sigma$. Combined with previously reported NIRSpec spectroscopy that yields seven emission lines including the auroral line [O III]$\,\lambda4363$, we present the first direct metallicity measurement of a $z > 10$ galaxy: $12+{\rm log(O/H)}= 7.79\pm0.09$, or $0.13^{+0.02}_{-0.03}\,Z_{\odot}$. This is similar to galaxies at $z \sim 4 - 9$ with direct metallicity measurements, though higher than expected given the high specific star formation rate ${\rm log(sSFR / yr^{-1})} = -7.4 \pm 0.3$. We further constrain the ionization parameter ${\rm log}(U)$ = $-1.9 \pm 0.1$, ionizing photon production efficiency ${\rm log}(\xi_{\rm ion})$ = $25.3\pm0.1$, and star formation rate $5.0\pm0.6\,M_{\odot}/{\rm yr}$ within the past $10\,{\rm Myr}$. These observations demonstrate the combined power of JWST NIRSpec and MIRI for studying galaxies in the first $500$ million years., Comment: 16 pages, 8 figures, accepted for publication in ApJ

Earthquake-induced liquefaction can cause substantial lateral spreading, posing threats to infrastructure. Machine learning (ML) can improve lateral spreading prediction models by capturing complex soil characteristics and site conditions. However, the "black box" nature of ML models can hinder their adoption in critical decision-making. This study addresses this limitation by using SHapley Additive exPlanations (SHAP) to interpret an eXtreme Gradient Boosting (XGB) model for lateral spreading prediction, trained on data from the 2011 Christchurch Earthquake. SHAP analysis reveals the factors driving the model's predictions, enhancing transparency and allowing for comparison with established engineering knowledge. The results demonstrate that the XGB model successfully identifies the importance of soil characteristics derived from Cone Penetration Test (CPT) data in predicting lateral spreading, validating its alignment with domain understanding. This work highlights the value of explainable machine learning for reliable and informed decision-making in geotechnical engineering and hazard assessment., Comment: to be published in "Frontiers in Built Environment"

In this paper, we present a framework for convolutional coded Poisson receivers (CCPRs) that incorporates spatially coupled methods into the architecture of coded Poisson receivers (CPRs). We use density evolution equations to track the packet decoding process with the successive interference cancellation (SIC) technique. We derive outer bounds for the stability region of CPRs when the underlying channel can be modeled by a $\phi$-ALOHA receiver. The stability region is the set of loads that every packet can be successfully received with a probability of 1. Our outer bounds extend those of the spatially-coupled Irregular Repetition Slotted ALOHA (IRSA) protocol and apply to channel models with multiple traffic classes. For CCPRs with a single class of users, the stability region is reduced to an interval. Therefore, it can be characterized by a percolation threshold. We study the potential threshold by the potential function of the base CPR used for constructing a CCPR. In addition, we prove that the CCPR is stable under a technical condition for the window size. For the multiclass scenario, we recursively evaluate the density evolution equations to determine the boundaries of the stability region. Numerical results demonstrate that the stability region of CCPRs can be enlarged compared to that of CPRs by leveraging the spatially-coupled method. Moreover, the stability region of CCPRs is close to our outer bounds when the window size is large., Comment: Part of this work was presented in 2023 IEEE International Symposium on Information Theory (ISIT) [1] and 2024 IEEE International Symposium on Information Theory (ISIT) [2]

Painterly Image Harmonization aims at seamlessly blending disparate visual elements within a single coherent image. However, previous approaches often encounter significant limitations due to training data constraints, the need for time-consuming fine-tuning, or reliance on additional prompts. To surmount these hurdles, we design a Training-and-prompt-Free General Painterly Harmonization method using image-wise attention sharing (TF-GPH), which integrates a novel "share-attention module". This module redefines the traditional self-attention mechanism by allowing for comprehensive image-wise attention, facilitating the use of a state-of-the-art pretrained latent diffusion model without the typical training data limitations. Additionally, we further introduce "similarity reweighting" mechanism enhances performance by effectively harnessing cross-image information, surpassing the capabilities of fine-tuning or prompt-based approaches. At last, we recognize the deficiencies in existing benchmarks and propose the "General Painterly Harmonization Benchmark", which employs range-based evaluation metrics to more accurately reflect real-world application. Extensive experiments demonstrate the superior efficacy of our method across various benchmarks. The code and web demo are available at https://github.com/BlueDyee/TF-GPH.

Our aim in this article is to compute the mixed volume of a matroid. We give two computations. The first one is based on the integration formula for complete fans given by Brion. The second computation is a step-by-step method using deletion of elements in the matroid as in Braden-Huh-Matherne-Proudfoot-Wang., Comment: 29 pages, 1 figure

We present recent JWST NIRCam imaging observations of SPT0615-JD (also known as the Cosmic Gems Arc), lensed by the galaxy cluster SPT-CL J0615-5746. The 5-arcsec-long arc is the most highly magnified $z>10$ galaxy known, straddling the lensing critical curve and revealing five star clusters with radii $\sim 1$ pc or less. We measure the full arc to have F200W 24.5 AB mag, consisting of two mirror images, each 25.3 AB mag with a magnification $\mu \sim 60$ (delensed 29.7 AB mag, $M_{UV} = -17.8$). The galaxy has an extremely strong Lyman break F115W$-$F200W $>3.2$ mag ($2\sigma$ lower limit), is undetected in all bluer filters ($< 2\sigma$), and has a very blue continuum slope redward of the break ($\beta = -2.7 \pm 0.1$), resulting in a photometric redshift $z_{phot} = 10.2 \pm 0.2$ (95% confidence) with no significant likelihood below $z < 9.8$. Based on SED fitting to the total photometry, we estimate an intrinsic stellar mass of $M_{*} \sim 2.4 - 5.6 \times 10^{7} M_{\odot}$, young mass-weighted age of $\sim 21 - 79$ Myr, low dust content ($A_V < 0.15$), and a low metallicity of $\lesssim 1\%~Z_{\odot}$. We identify a fainter third counterimage candidate within 2.2 arcsec of the predicted position, lensed to AB mag 28.4 and magnified by $\mu \sim 2$, suggesting the fold arc may only show $\sim60$% of the galaxy. SPT0615-JD is a unique laboratory to study star clusters observed within a galaxy just 460 Myr after the Big Bang., Comment: 22 pages, 8 figures, 4 tables, submitted to ApJ

We present a statistical study of the properties of diffuse HI in ten nearby galaxies, comparing the HI detected by the single-dish telescope FAST (FEASTS program) and the interferometer VLA (THINGS program), respectively. The THINGS' observation missed HI with a median of 23% due to the short-spacing problem of interferometry and limited sensitivity. We extract the diffuse HI by subtracting the dense HI, which is obtained from the THINGS data with a uniform flux-density threshold, from the total HI detected by FAST. Among the sample, the median diffuse-HI fraction is 34%, and more diffuse HI is found in galaxies exhibiting more prominent tidal-interaction signatures. The diffuse HI we detected seems to be distributed in disk-like layers within a typical thickness of $1\,\text{kpc}$, different from the more halo-like diffuse HI detected around NGC 4631 in a previous study. Most of the diffuse HI is cospatial with the dense HI and has a typical column density of $10^{17.7}$-$10^{20.1}\,\text{cm}^{-2}$. The diffuse and dense HI exhibits a similar rotational motion, but the former lags by a median of 25% in at least the inner disks, and its velocity dispersions are typically twice as high. Based on a simplified estimation of circum-galactic medium properties and assuming pressure equilibrium, the volume density of diffuse HI appears to be constant within each individual galaxy, implying its role as a cooling interface. Comparing with existing models, these results are consistent with a possible link between tidal interactions, the formation of diffuse HI, and gas accretion., Comment: 45 pages, 23 figures. In press at ApJ. Data will be released at the FEASTS site upon publication

The extension of photonic technologies such as lidar and free-space optical communications from the traditional visible and near-infrared wavelengths to longer wavelengths can improve performance in adverse environments such as haze, fog, smoke, or strong solar background. Non-mechanical beam steerers will be a critical component of the low size, weight, and power modules needed for the portable or unmanned systems deployed in these environments. In this work, we demonstrate the first 2D optical phased array for non-mechanical beam steering in the mid-infrared spectral region. We combine a total internal-reflection mirror emitter with a non-redundant array of 30 elements to carry out 2D beam steering at a single wavelength of 4.6 $\mu$m. The experiment yielded 600 resolvable far-field points, with 2400 points over a $28^\circ \times 28^\circ$ field of view calculated theoretically. Moreover, the device was fabricated in a passive InGaAs/InP platform, contributing another advance in the ongoing development of quantum cascade laser-based photonic integration., Comment: Main document: 16 pages, 11 figures; Supplement: 3 pages, 2 figures

Strong gravitational magnification by massive galaxy clusters enable us to detect faint background sources, resolve their detailed internal structures, and in the most extreme cases identify and study individual stars in distant galaxies. Highly magnified individual stars allow for a wide range of applications, including studies of stellar populations in distant galaxies and constraining small-scale dark matter structures. However, these applications have been hampered by the small number of events observed, as typically one or a few stars are identified from each distant galaxy. Here, we report the discovery of 46 significant microlensed stars in a single strongly-lensed high-redshift galaxy behind the Abell 370 cluster at redshift of 0.725 when the Universe was half of its current age (dubbed the ``Dragon arc''), based on two observations separated by one year with the James Webb Space Telescope ({\it JWST}). These events are mostly found near the expected lensing critical curves, suggesting that these are magnified individual stars that appear as transients from intracluster stellar microlenses. Through multi-wavelength photometry and colors, we constrain stellar types and find that many of them are consistent with red giants/supergiants magnified by factors of thousands. This finding reveals an unprecedented high occurrence of microlensing events in the Dragon arc, and proves that {\it JWST}'s time-domain observations open up the possibility of conducting statistical studies of high-redshift stars and subgalactic scale perturbations in the lensing dark matter field., Comment: 15 pages, 4 figures, 1 table submitted to Nature Astronomy

We present a method of extrapolating the spectroscopic behavior of Type Ia supernovae (SNe Ia) in the near-infrared (NIR) wavelength regime up to 2.30 $\mu$m using optical spectroscopy. Such a process is useful for accurately estimating K-corrections and other photometric quantities of SNe Ia in the NIR. Principal component analysis is performed on data consisting of Carnegie Supernova Project I & II optical and near-infrared FIRE spectra to produce models capable of making these extrapolations. This method differs from previous spectral template methods by not parameterizing models strictly by photometric light-curve properties of SNe Ia, allowing for more flexibility of the resulting extrapolated NIR flux. A difference of around -3.1% to -2.7% in the total integrated NIR flux between these extrapolations and the observations is seen here for most test cases including Branch core-normal and shallow-silicon subtypes. However, larger deviations from the observation are found for other tests, likely due to the limited high-velocity and broad-line SNe Ia in the training sample. Maximum-light principal components are shown to allow for spectroscopic predictions of the color-stretch light-curve parameter, $s_{BV}$, within approximately $\pm$0.1 units of the value measured with photometry. We also show these results compare well with NIR templates, although in most cases the templates are marginally more fitting to observations, illustrating a need for more concurrent optical+NIR spectroscopic observations to truly understand the diversity of SNe Ia in the NIR., Comment: 25 pages, 16 figures, ApJ, in press

We present the first report on fabrication of Hafnium aluminum nitride chiral sculptured thin films (CSTFs) using reactive magnetron sputtering in a glancing angle deposition configuration, and the analysis of its optical polarization properties. The resulting CSTFs were designed to give interference extrema or so-called circular Bragg (CB) resonances at desired wavelengths in the region from 370 to 690 nm. This was achieved by tailoring the growth of the chiral thin films to obtain a dielectric pitch between 87 and 260.9 nm. The spectral positions of the obtained CB resonances were compared to values from analytical expressions. Contrary to the common case where the dielectric pitch is half of the growth-related rotational pitch due to a 180{\deg} symmetry, this pitch was shown to be the same as the rotational pitch. It is concluded that this is due to the c-axis of the CSTF being tilted about 45{\deg} from the substrate normal. The morphology and crystallographic characterizations were done using scanning electron microscopy and X-ray diffraction, respectively, while the tilt of the crystal lattice was corroborated using X-ray diffraction pole figures. The optical response from the CSTFs was analyzed using Mueller matrix spectroscopic ellipsometry from which the degree of circular polarization at the CB resonances was obtained. In addition, a strong non-reciprocal reflection was observed which could be attributed to the helicoidal morphology and the intrinsic crystal tilt. An optical layered model of the chiral structure including azimuthal twist and using the Cauchy dispersion relations was used to simulate the Mueller matrix elements and compare with the ellipsometry measurements. The correlation between the simulated and experimental data gave information of the morphological parameters of the CSTF and its optical properties.

We propose a two-stage memory retrieval dynamics for modern Hopfield models, termed $\mathtt{U\text{-}Hop}$, with enhanced memory capacity. Our key contribution is a learnable feature map $\Phi$ which transforms the Hopfield energy function into kernel space. This transformation ensures convergence between the local minima of energy and the fixed points of retrieval dynamics within the kernel space. Consequently, the kernel norm induced by $\Phi$ serves as a novel similarity measure. It utilizes the stored memory patterns as learning data to enhance memory capacity across all modern Hopfield models. Specifically, we accomplish this by constructing a separation loss $\mathcal{L}_\Phi$ that separates the local minima of kernelized energy by separating stored memory patterns in kernel space. Methodologically, $\mathtt{U\text{-}Hop}$ memory retrieval process consists of: (Stage I) minimizing separation loss for a more uniform memory (local minimum) distribution, followed by (Stage II) standard Hopfield energy minimization for memory retrieval. This results in a significant reduction of possible metastable states in the Hopfield energy function, thus enhancing memory capacity by preventing memory confusion. Empirically, with real-world datasets, we demonstrate that $\mathtt{U\text{-}Hop}$ outperforms all existing modern Hopfield models and state-of-the-art similarity measures, achieving substantial improvements in both associative memory retrieval and deep learning tasks. Code is available at https://github.com/MAGICS-LAB/UHop ; future updates are on arXiv:2404.03827, Comment: Accepted at ICML 2024; v3 added a note on follow-up UHop+ (arXiv:2410.23126); v2 updated to camera-ready version; Code available at https://github.com/MAGICS-LAB/UHop

One of the surprising early findings with JWST has been the discovery of a strong "roll-over" or a softening of the absorption edge of Ly$\alpha$ in a large number of galaxies at ($z\gtrsim 6$), in addition to systematic offsets from photometric redshift estimates and fundamental galaxy scaling relations. This has been interpreted as damped Ly$\alpha$ absorption (DLA) wings from high column densities of neutral atomic hydrogen (HI), signifying major gas accretion events in the formation of these galaxies. To explore this new phenomenon systematically, we assemble the JWST/NIRSpec PRImordial gas Mass AssembLy (PRIMAL) legacy survey of 494 galaxies at $z=5.5-13.4$. We characterize this benchmark sample in full and spectroscopically derive the galaxy redshifts, metallicities, star-formation rates, and ultraviolet slopes. We define a new diagnostic, the Ly$\alpha$ damping parameter $D_{\rm Ly\alpha}$ to measure and quantify the Ly$\alpha$ emission strength, HI fraction in the IGM, or local HI column density for each source. The JWST-PRIMAL survey is based on the spectroscopic DAWN JWST Archive (DJA-Spec). All the software, reduced spectra, and spectroscopically derived quantities and catalogs are made publicly available in dedicated repositories. The fraction of strong galaxy DLAs are found to be in the range $65-95\%$ at $z>5.5$. The fraction of strong Ly$\alpha$ emitters (LAEs) is found to increase with decreasing redshift, in qualitative agreement with previous observational results, and are predominantly associated with low-metallicity and UV faint galaxies. By contrast, strong DLAs are observed in galaxies with a variety of intrinsic physical properties. Our results indicate that strong DLAs likely reflect a particular early assembly phase of reionization-era galaxies, at which point they are largely dominated by pristine HI gas accretion. [abridged], Comment: 20 pages, 18 figures, 3 tables. Submitted to A&A. Comments welcome! All data and catalogs are available through the DAWN JWST Archive (DJA): https://dawn-cph.github.io/dja/ and https://github.com/keheintz/jwst-primal

The Canadian Hydrogen Intensity Mapping Experiment (CHIME) is a drift-scan interferometer designed to map the entire northern sky every 24 hours. The all-sky coverage and sensitivity to neutral hydrogen flux at intermediate redshifts makes the instrument a resource for other exciting science in addition to cosmology for which it was originally designed. Characterizing the contents of CHIME's beam-smoothed maps will aid in planning novel use-cases for the instrument, particularly those pertaining to galaxy evolution studies. Here, we demonstrate its utility for the study of the HI content of stacked galaxy populations across environments. Focusing first on galaxy clusters, we use simulated data from the IllustrisTNG project to understand the relative contribution of objects that fall into CHIME's synthesized beam to the observed HI flux using stacking analyses at a couple of representative redshifts. We find that there is an appreciable difference in the estimated stacked flux when galaxy clusters or cluster member galaxies are used as tracers compared to stacking on a general galaxy catalog. Stacking on galaxy clusters, we report that it is possible to recover an average $M_\mathrm{HI}$ for clusters as a function of redshift and selection criteria., Comment: 10+2 pages, version accepted to MNRAS