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Many machine learning algorithms try to visualize high dimensional metric data in 2D in such a way that the essential geometric and topological features of the data are highlighted. In this paper, we introduce a framework for aggregating dissimilarity functions that arise from locally adjusting a metric through density-aware normalization, as employed in the IsUMap method. We formalize these approaches as m-schemes, a class of methods closely related to t-norms and t-conorms in probabilistic metrics, as well as to composition laws in information theory. These m-schemes provide a flexible and theoretically grounded approach to refining distance-based embeddings.

Online handwriting recognition (HWR) using data from inertial measurement units (IMUs) remains challenging due to variations in writing styles and the limited availability of high-quality annotated datasets. Traditional models often struggle to recognize handwriting from unseen writers, making writer-independent (WI) recognition a crucial but difficult problem. This paper presents an HWR model with an encoder-decoder structure for IMU data, featuring a CNN-based encoder for feature extraction and a BiLSTM decoder for sequence modeling, which supports inputs of varying lengths. Our approach demonstrates strong robustness and data efficiency, outperforming existing methods on WI datasets, including the WI split of the OnHW dataset and our own dataset. Extensive evaluations show that our model maintains high accuracy across different age groups and writing conditions while effectively learning from limited data. Through comprehensive ablation studies, we analyze key design choices, achieving a balance between accuracy and efficiency. These findings contribute to the development of more adaptable and scalable HWR systems for real-world applications.

The breakthrough of generative large language models (LLMs) that can solve different tasks through chat interaction has led to a significant increase in the use of general benchmarks to assess the quality or performance of these models beyond individual applications. There is also a need for better methods to evaluate and also to compare models due to the ever increasing number of new models published. However, most of the established benchmarks revolve around the English language. This paper analyses the benefits and limitations of current evaluation datasets, focusing on multilingual European benchmarks. We analyse seven multilingual benchmarks and identify four major challenges. Furthermore, we discuss potential solutions to enhance translation quality and mitigate cultural biases, including human-in-the-loop verification and iterative translation ranking. Our analysis highlights the need for culturally aware and rigorously validated benchmarks to assess the reasoning and question-answering capabilities of multilingual LLMs accurately.

Large language models (LLMs) demonstrate unprecedented capabilities and define the state of the art for almost all natural language processing (NLP) tasks and also for essentially all Language Technology (LT) applications. LLMs can only be trained for languages for which a sufficient amount of pre-training data is available, effectively excluding many languages that are typically characterised as under-resourced. However, there is both circumstantial and empirical evidence that multilingual LLMs, which have been trained using data sets that cover multiple languages (including under-resourced ones), do exhibit strong capabilities for some of these under-resourced languages. Eventually, this approach may have the potential to be a technological off-ramp for those under-resourced languages for which "native" LLMs, and LLM-based technologies, cannot be developed due to a lack of training data. This paper, which concentrates on European languages, examines this idea, analyses the current situation in terms of technology support and summarises related work. The article concludes by focusing on the key open questions that need to be answered for the approach to be put into practice in a systematic way.

Modern AESA technology enables RF systems to not only perform various radar, communication and electronic warfare tasks on a single aperture, but even to execute multiple tasks concurrently. These capabilities increase system complexity and require intelligent or cognitive resource management. This paper introduces such a resource management framework based on quality of service based resource allocation and Monte Carlo tree search allowing for optimal system usage and profound decision-making. Furthermore, we present experimental verification in a complex application scenario., Comment: 4 pages, 6 figures, presented at Radio and Wireless Week 2025

Connected and Automated Vehicle (CAV) research has gained traction in the last decade due to significant advancements in perception, navigation, communication, and control functions. Accurate and reliable position information is needed to meet the requirements of CAV applications, especially when safety is concerned. With the advent of various perception sensors (e.g. camera, LiDAR, etc.), the vehicular positioning system has improved both in accuracy and robustness. Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) based cooperative positioning can improve the accuracy of the position estimates, but the integrity risks involved in multi-sensor fusion in a cooperative environment have not yet been fully explored. This paper reviews existing research in the field of positioning Integrity Monitoring (IM) and identifies various research gaps. Particular attention has been placed on identifying research that highlights cooperative IM methods. This analysis helps pave the way for the development of new IM frameworks for cooperative positioning solutions in the future., Comment: This work has been submitted to the IEEE for possible publication

We study magneto-transport through topological insulator nanowires shaped in the form of a constriction, as can be obtained by etching techniques. The magnetic field is coaxial, potentially turning the nanowire into a magneto-chiral junction. We show in a detailed analytical and numerical study that two main transport regimes emerge, depending on the central narrow region being short or long as compared to the magnetic length at the junction entrance and exit. In both cases the central region hosts Dirac-particle-in-a-box states due to magnetic confinement, whose conductance properties are strongly influenced by Landau levels at the ends of the constriction. Notably, in the low-energy regime only chiral states with a specific handedness can transport charge across the junction. Based on these properties and general symmetry considerations we argue that the shaped nanowire should exhibit strong magneto-chiral non-reciprocal transport beyond linear response. We employ a numerical tight-binding implementation of an effective 2D model on a non-homogeneous grid, capable of simulating samples of realistic sizes, and test its soundness against full simulations for scaled-down 3D topological insulator wires., Comment: 10 pages, 10 figures

Reasoning language models (RLMs), also known as Large Reasoning Models (LRMs), such as OpenAI's o1 and o3, DeepSeek-V3, and Alibaba's QwQ, have redefined AI's problem-solving capabilities by extending LLMs with advanced reasoning mechanisms. Yet, their high costs, proprietary nature, and complex architectures - uniquely combining Reinforcement Learning (RL), search heuristics, and LLMs - present accessibility and scalability challenges. To address these, we propose a comprehensive blueprint that organizes RLM components into a modular framework, based on a survey and analysis of all RLM works. This blueprint incorporates diverse reasoning structures (chains, trees, graphs, and nested forms), reasoning strategies (e.g., Monte Carlo Tree Search, Beam Search), RL concepts (policy, value models and others), supervision schemes (Outcome-Based and Process-Based Supervision), and other related concepts (e.g., Test-Time Compute, Retrieval-Augmented Generation, agent tools). We also provide detailed mathematical formulations and algorithmic specifications to simplify RLM implementation. By showing how schemes like LLaMA-Berry, QwQ, Journey Learning, and Graph of Thoughts fit as special cases, we demonstrate the blueprint's versatility and unifying potential. To illustrate its utility, we introduce x1, a modular implementation for rapid RLM prototyping and experimentation. Using x1 and a literature review, we provide key insights, such as multi-phase training for policy and value models, and the importance of familiar training distributions. Finally, we discuss scalable RLM cloud deployments and we outline how RLMs can integrate with a broader LLM ecosystem. Our work demystifies RLM construction, democratizes advanced reasoning capabilities, and fosters innovation, aiming to mitigate the gap between "rich AI" and "poor AI" by lowering barriers to RLM design and experimentation.

Future multifunction RF systems will be able to not only perform various different radar, communication and electronic warfare functionalities but also to perform them simultaneously on the same aperture. This ability of concurrent operations requires new, cognitive approaches of resource management compared to classical methods. This paper presents such a new approach using a combination of quality of service based resource management and Monte Carlo tree search., Comment: 6 pages, 9 figures, presented at 2024 International Radar Conference (RADAR2024)

Inferring sky surface brightness distributions from noisy interferometric data in a principled statistical framework has been a key challenge in radio astronomy. In this work, we introduce Imaging for Radio Interferometry with Score-based models (IRIS). We use score-based models trained on optical images of galaxies as an expressive prior in combination with a Gaussian likelihood in the uv-space to infer images of protoplanetary disks from visibility data of the DSHARP survey conducted by ALMA. We demonstrate the advantages of this framework compared with traditional radio interferometry imaging algorithms, showing that it produces plausible posterior samples despite the use of a misspecified galaxy prior. Through coverage testing on simulations, we empirically evaluate the accuracy of this approach to generate calibrated posterior samples., Comment: 17 pages, 8 figures, submitted to the Astrophysical Journal

A new and detailed measurement of the cross section for hard exclusive neutral-pion muoproduction on the proton was performed in a wide kinematic region, with the photon virtuality $Q^2$ ranging from 1 to 8 (GeV/$c$)$^{\rm\, 2}$ and the Bjorken variable $x_{\rm Bj}$ ranging from 0.02 to 0.45. The data were collected at COMPASS at CERN using 160 GeV/$c$ longitudinally polarised $\mu^+$ and $\mu^-$ beams scattering off a 2.5 m long liquid hydrogen target. From the average of the measured $\mu^+$ and $\mu^-$ cross sections, the virtual-photon--proton cross section is determined as a function of the squared four-momentum transfer between the initial and final state proton in the range 0.08 (GeV/$c$)$^{\rm\, 2}$ $< |t| <$ 0.64 (GeV/$c$)$^{\rm\, 2}$. From its angular distribution, the combined contribution of transversely and longitudinally polarised photons are determined, as well as transverse--transverse and longitudinal--transverse interference contributions. They are studied as functions of four-momentum transfer $|t|$, photon virtuality $Q^2$ and virtual-photon energy $\nu$. The longitudinal--transverse interference contribution is found to be compatible with zero. The significant transverse--transverse interference contribution reveals the existence of a dominant contribution by transversely polarized photons. This provides clear experimental evidence for the chiral-odd GPD $\overline{E}_T$. In addition, the existence of a non-negligible contribution of longitudinally polarized photons is suggested by the $|t|$-dependence of the cross section at $x_{\rm Bj} < $ 0.1 . Altogether, these results provide valuable input for future modelling of GPDs and thus of cross sections for exclusive pseudo-scalar meson production. Furthermore, they can be expected to facilitate the study of next-to-leading order corrections and higher-twist contributions.

We investigate the impact of CO$_2$ on TRAPPIST-1 e, f and g during the magma ocean stage. These potentially habitable rocky planets are currently the most accessible for astronomical observations. A constraint on the volatile budget during the magma ocean stage is a link to planet formation and also needed to judge their habitability. We perform simulations with 1-100 terrestrial oceans (TO) of H$_2$O with and without CO$_2$ and for albedos 0 and 0.75. The CO$_2$ mass is scaled with initial H$_2$O by a constant factor between 0.1 and 1. The magma ocean state of rocky planets begins with a CO$_2$-dominated atmosphere but can evolve into a H$_2$O dominated state, depending on initial conditions. For less than 10 TO initial H$_2$O, the atmosphere tends to desiccate and the evolution may end with a CO$_2$ dominated atmosphere. Otherwise, the final state is a thick (>1000 bar) H$_2$O-CO$_2$ atmosphere. Complete atmosphere desiccation with less than 10 TO initial H$_2$O can be significantly delayed for TRAPPIST-1e and f, when H$_2$O has to diffuse through a CO$_2$ atmosphere to reach the upper atmosphere, where XUV photolysis occurs. As a consequence of CO$_2$ diffusion-limited water loss, the time of mantle solidification for TRAPPIST-1 e, f, and g can be significantly extended compared to a pure H$_2$O evolution by up to 40 Myrs for albedo 0.75 and by up to 200 Mrys for albedo 0. The addition of CO$_2$ further results in a higher water content in the melt during the magma ocean stage. Our compositional model adjusted for the measured metallicity of TRAPPIST-1 yields for the dry inner planets (b, c, d) an iron fraction of 27 wt-%. For TRAPPIST-1 e, this iron fraction would be compatible with a (partly) desiccated evolution scenario and a CO$_2$ atmosphere with surface pressures of a few 100 bar. A comparative study between TRAPPIST-1 e and the inner planets may yield the most insights about formation and evolution scenarios., Comment: 36 pages, 28 figues, accepted by A&A 9/12/2024

Zero-shot named entity recognition (NER) is the task of detecting named entities of specific types (such as 'Person' or 'Medicine') without any training examples. Current research increasingly relies on large synthetic datasets, automatically generated to cover tens of thousands of distinct entity types, to train zero-shot NER models. However, in this paper, we find that these synthetic datasets often contain entity types that are semantically highly similar to (or even the same as) those in standard evaluation benchmarks. Because of this overlap, we argue that reported F1 scores for zero-shot NER overestimate the true capabilities of these approaches. Further, we argue that current evaluation setups provide an incomplete picture of zero-shot abilities since they do not quantify the label shift (i.e., the similarity of labels) between training and evaluation datasets. To address these issues, we propose Familiarity, a novel metric that captures both the semantic similarity between entity types in training and evaluation, as well as their frequency in the training data, to provide an estimate of label shift. It allows researchers to contextualize reported zero-shot NER scores when using custom synthetic training datasets. Further, it enables researchers to generate evaluation setups of various transfer difficulties for fine-grained analysis of zero-shot NER., Comment: 9 pages, 4 figures, 5 tables

We present a novel class of Convolutional Neural Networks called Pre-defined Filter Convolutional Neural Networks (PFCNNs), where all nxn convolution kernels with n>1 are pre-defined and constant during training. It involves a special form of depthwise convolution operation called a Pre-defined Filter Module (PFM). In the channel-wise convolution part, the 1xnxn kernels are drawn from a fixed pool of only a few (16) different pre-defined kernels. In the 1x1 convolution part linear combinations of the pre-defined filter outputs are learned. Despite this harsh restriction, complex and discriminative features are learned. These findings provide a novel perspective on the way how information is processed within deep CNNs. We discuss various properties of PFCNNs and prove their effectiveness using the popular datasets Caltech101, CIFAR10, CUB-200-2011, FGVC-Aircraft, Flowers102, and Stanford Cars. Our implementation of PFCNNs is provided on Github https://github.com/Criscraft/PredefinedFilterNetworks

The James Webb Space Telescope has uncovered a puzzling population of UV-faint broad-line active galactic nuclei (AGN), nicknamed ``Little Red Dots'' (LRD) owing to their compact morphology and red rest-frame optical colours. Interpreted as dust attenuated AGN, their inferred intrinsic luminosities and supermassive black hole (SMBH) masses rival those of UV-luminous quasars, although they are $>100$ times more abundant. If LRDs and quasars are members of the same underlying population, they should inhabit comparable mass dark matter halos, traced by similar overdensities of galaxies. Otherwise, they represent distinct populations with different physical properties and formation histories. Characterizing LRD environments thus provides a critical test of their nature. Here, we report the discovery of a LRD at $z=7.3$, attenuated by moderate amounts of dust, $A_V = {3.26}\,\rm{mag}$, with an intrinsic bolometric luminosity of $10^{46.7}\,\rm{erg}\,\rm{s}^{-1}$ and a SMBH mass of $7\times10^8\,\rm{M}_\odot$. Most notably, this object is embedded in an overdensity of eight nearby galaxies, allowing us to calculate the first spectroscopic estimate of the clustering of galaxies around LRDs. We find a LRD-galaxy cross-correlation length of $r_0\!=\!9\pm2\,\rm{h}^{-1}\,\rm{cMpc}$, comparable to that of $z\!\sim\!6$ UV-luminous quasars. The resulting estimate of their minimum dark matter halo mass of $\log_{10}(M_{\rm{halo, min}}/\rm{M}_{\odot})= 12.3_{-0.8}^{+0.7}$ indicates that nearly all halos above this mass must host actively accreting SMBHs at $z\approx7$, in strong contrast with the far smaller duty cycle of luminous quasars ($<1\%$). Our results, taken at face value, motivate a picture in which LRDs are the obscured counterparts of UV-luminous quasars, which provides a natural explanation for the short UV-luminous lifetimes inferred from both quasar clustering and quasar proximity zones., Comment: Submitted. Comments welcome!

The origin of the tight scaling relation between the mass of supermassive black holes (SMBHs; $M_{\rm BH}$) and their host-galaxy properties remains unclear. Active galactic nuclei (AGNs) probe phases of ongoing SMBH growth and offer the only opportunity to measure $M_{\rm BH}$ beyond the local Universe. However, determining AGN host galaxy stellar velocity dispersion $\sigma_\star$, and their galaxy dynamical masses $M_{\rm dyn}$, is complicated by AGN contamination, aperture effects and different host galaxy morphologies. We select a sample of AGNs for which $M_{\rm BH}$ has been independently determined to high accuracy by state-of-the-art techniques: dynamical modeling of the reverberation signal and spatially resolving the broad-line region with VLTI/GRAVITY. Using IFU observations, we spatially map the host galaxy stellar kinematics across the galaxy and bulge effective radii. We find that that the dynamically hot component of galaxy disks correlates with $M_{\rm BH}$; however, the correlations are tightest for aperture-integrated $\sigma_\star$ measured across the bulge. Accounting for the different $M_{\rm BH}$ distributions, we demonstrate - for the first time - that AGNs follow the same $M_{\rm BH}$-$\sigma_\star$ and $M_{\rm BH}$-$M_{\rm bulge, dyn}$ relations as quiescent galaxies. We confirm that the classical approach of determining the virial factor as sample-average, yielding ${\rm log }f= 0.65 \pm 0.18$, is consistent with the average $f$ from individual measurements. The similarity between the underlying scaling relations of AGNs and quiescent galaxies implies that the current AGN phase is too short to have altered BH masses on a population level. These results strengthen the local calibration of $f$ for measuring single-epoch $M_{\rm BH}$ in the distant Universe., Comment: Submitted to ApJ. 40 pages, 19 figures, 6 tables. Reuploaded after acceptance for publication

We explore electrical transport through a point contact in strained HgTe, a three-dimensional topological insulator. In the absence of a magnetic field $B$, there is no quantization. However, under higher magnetic fields, we observe distinct non-integer conductance steps. Based on numerical tight-binding calculations and a phenomenological Landauer-B\"uttiker approach, we attribute these atypical, non-integer quantized plateaus to significant scattering effects at the point contact., Comment: Submitted to PRR on 10/21/2024, re-submitted with minor changes to PRR on 01/14/2025, 9 pages, 7 figures

Activation maximization (AM) strives to generate optimal input stimuli, revealing features that trigger high responses in trained deep neural networks. AM is an important method of explainable AI. We demonstrate that AM fails to produce optimal input stimuli for simple functions containing ReLUs or Leaky ReLUs, casting doubt on the practical usefulness of AM and the visual interpretation of the generated images. This paper proposes a solution based on using Leaky ReLUs with a high negative slope in the backward pass while keeping the original, usually zero, slope in the forward pass. The approach significantly increases the maxima found by AM. The resulting ProxyGrad algorithm implements a novel optimization technique for neural networks that employs a secondary network as a proxy for gradient computation. This proxy network is designed to have a simpler loss landscape with fewer local maxima than the original network. Our chosen proxy network is an identical copy of the original network, including its weights, with distinct negative slopes in the Leaky ReLUs. Moreover, we show that ProxyGrad can be used to train the weights of Convolutional Neural Networks for classification such that, on some of the tested benchmarks, they outperform traditional networks.

The multiplicities of positive and negative pions, kaons and unidentified hadrons produced in deep-inelastic scattering are measured in bins of the Bjorken scaling variable $x$, the relative virtual-photon energy $y$ and the fraction of the virtual-photon energy transferred to the final-state hadron $z$. Data were obtained by the COMPASS Collaboration using a 160 GeV muon beam of both electric charges and a liquid hydrogen target. These measurements cover the kinematic domain with photon virtuality $Q^2 > 1$ (GeV/$c)^2$, $0.004 < x < 0.4$, $0.1 < y < 0.7$ and $0.2 < z < 0.85$, in accordance with the kinematic domain used in earlier published COMPASS multiplicity measurements with an isoscalar target. The calculation of radiative corrections was improved by using the Monte Carlo generator DJANGOH, which results in up to 12\% larger corrections in the low-$x$ region., Comment: 19 pages, 29 figures

The rise of Large Language Models (LLMs) has revolutionized natural language processing across numerous languages and tasks. However, evaluating LLM performance in a consistent and meaningful way across multiple European languages remains challenging, especially due to the scarcity of language-parallel multilingual benchmarks. We introduce a multilingual evaluation approach tailored for European languages. We employ translated versions of five widely-used benchmarks to assess the capabilities of 40 LLMs across 21 European languages. Our contributions include examining the effectiveness of translated benchmarks, assessing the impact of different translation services, and offering a multilingual evaluation framework for LLMs that includes newly created datasets: EU20-MMLU, EU20-HellaSwag, EU20-ARC, EU20-TruthfulQA, and EU20-GSM8K. The benchmarks and results are made publicly available to encourage further research in multilingual LLM evaluation.

The local (z=0.0315) AGN Mrk 817, was monitored over more than 500 days with space-borne and ground-based instruments as part of a large international campaign AGN STORM 2. Here, we present a comprehensive analysis of the broad-band continuum variations using detailed modeling of the broad line region (BLR), several types of disk winds classified by their optical depth, and new numerical simulations. We find that diffuse continuum (DC) emission, with additional contributions from strong and broad emission lines, can explain the continuum lags observed in this source during high and low luminosity phases. Disk illumination by the variable X-ray corona contributes only a small fraction of the observed continuum lags. Our BLR models assume radiation pressure-confined clouds distributed over a distance of 2-122 light days. We present calculated mean-emissivity radii of many emission lines, and DC emission, and suggest a simple, transfer-function-dependent method that ties them to cross-correlation lag determinations. We do not find clear indications for large optical depth winds but identify the signature of lower column density winds. In particular, we associate the shortest observed continuum lags with a combination of tau(1 Ryd) approx. 2 wind and a partly shielded BLR. Even smaller optical depth winds may be associated with X-ray absorption features and with noticeable variations in the width and lags of several high ionization lines like HeII and CIV. Finally, we demonstrate the effect of torus dust emission on the observed lags in the i and z bands., Comment: 23 pages, 18 figures. Corrected typographical error in the title of the paper as it appeared in the Metadata

The mental health landscape in higher education has reached a critical juncture, with an increasing number of students experiencing severe psychological issues. Recent studies have found that over 60% of college students meet the criteria for at least one mental health problem, with significant portions reporting symptoms of depression, anxiety, and suicidal ideation (Flannery, 2023; Alonso, 2023). Encouragingly, more students are seeking mental health counseling, yet a substantial gap remains, with over 60% not receiving the care they need (Alonso, 2023; Sutton, 2023). The COVID-19 pandemic has further complicated these trends, significantly impacting student enrollment patterns and increasing the need for quality online education and telemental health services. The study aims to address the mental health crisis by focusing specifically on the needs of online students and support strategies that can more effectively support this population. Through a comprehensive, global survey of 338 respondents from diverse roles in higher education, the researchers sought to understand the changing demand and utilization of mental health services among online students, the steps institutions are taking to customize these services, the unique mental health needs online students face, and the barriers preventing them from seeking help. This research reveals that online student demand and utilization of mental health services have significantly increased over the past year, with key challenges including isolation, diverse schedules, and less visible mental health issues. Also, educators identify barriers like lack of awareness, limited service availability, and time constraints in seeking support as especially significant for online students. [This study was collaborated with Uwill.]

The evolution of artificial intelligence (AI) presents an unprecedented opportunity for Historically Black Colleges and Universities (HBCUs) to lead in an era characterized by rapid technological advancement and societal transformation. This report explores the integral role HBCUs--with their history of academic excellence and commitment to inclusivity--can play in steering the AI revolution, ensuring that the Black community remains at the forefront of educational, economic, and social progress. Institutional leaders, faculty and instructors, and instructional support staff can benefit from the findings of this report, which is presented in the following sections: (1) Why AI Matters and the Unique Role of HBCUs in the AI Revolution; (2) An AI Policy and Practice Framework for Institutional Development; (3) AI and Curricular Innovation; (4) The Importance of Industry Partnerships and Student Development; and (5) AI at HBCUs: A Path to the Future. [This report was created in collaboration with the Thurgood Marshall College Fund.]

We present two multilingual LLMs designed to embrace Europe's linguistic diversity by supporting all 24 official languages of the European Union. Trained on a dataset comprising around 60% non-English data and utilizing a custom multilingual tokenizer, our models address the limitations of existing LLMs that predominantly focus on English or a few high-resource languages. We detail the models' development principles, i.e., data composition, tokenizer optimization, and training methodologies. The models demonstrate competitive performance across multilingual benchmarks, as evidenced by their performance on European versions of ARC, HellaSwag, MMLU, and TruthfulQA.

James Webb Space Telescope opens a new window to directly probe luminous quasars powered by billion solar mass black holes in the epoch of reionization and their co-evolution with massive galaxies with unprecedented details. In this paper, we report the first results from the deep NIRSpec integral field spectroscopy study of a quasar at $z = 7.5$. We obtain a bolometric luminosity of $\sim$$1.8\times10^{47}$ erg s$^{-1}$ and a black hole mass of $\sim$0.7--2.5$\times10^{9}$ M$_{\odot}$ based on H$\beta$ emission line from the quasar spectrum. We discover $\sim$2 kpc scale, highly blueshifted ($\sim$$-$870 km/s) and broad ($\sim$1400 km/s) [O III] line emission after the quasar PSF has been subtracted. Such line emission most likely originates from a fast, quasar-driven outflow, the earliest one on galactic-scale known so far. The dynamical properties of this outflow fall within the typical ranges of quasar-driven outflows at lower redshift, and the outflow may be fast enough to reach the circumgalactic medium. Combining both the extended and nuclear outflow together, the mass outflow rate, $\sim$300 M$_{\odot}$yr, is $\sim$60%--380% of the star formation rate of the quasar host galaxy, suggesting that the outflow may expel a significant amount of gas from the inner region of the galaxy. The kinetic energy outflow rate, $\sim$3.6$\times10^{44}$ erg s$^{-1}$, is $\sim$0.2% of the quasar bolometric luminosity, which is comparable to the minimum value required for negative feedback based on simulation predictions. The dynamical timescale of the extended outflow is $\sim$1.7 Myr, consistent with the typical quasar lifetime in this era.

X-ray reverberation mapping is a powerful technique for probing the innermost accretion disk, whereas continuum reverberation mapping in the UV, optical, and infrared (UVOIR) reveals reprocessing by the rest of the accretion disk and broad-line region (BLR). We present the time lags of Mrk 817 as a function of temporal frequency measured from 14 months of high-cadence monitoring from Swift and ground-based telescopes, in addition to an XMM-Newton observation, as part of the AGN STORM 2 campaign. The XMM-Newton lags reveal the first detection of a soft lag in this source, consistent with reverberation from the innermost accretion flow. These results mark the first simultaneous measurement of X-ray reverberation and UVOIR disk reprocessing lags$\unicode{x2013}$effectively allowing us to map the entire accretion disk surrounding the black hole. Similar to previous continuum reverberation mapping campaigns, the UVOIR time lags arising at low temporal frequencies are longer than those expected from standard disk reprocessing by a factor of 2-3. The lags agree with the anticipated disk reverberation lags when isolating short-timescale variability, namely timescales shorter than the H$\beta$ lag. Modeling the lags requires additional reprocessing constrained at a radius consistent with the BLR size scale inferred from contemporaneous H$\beta$-lag measurements. When we divide the campaign light curves, the UVOIR lags show substantial variations, with longer lags measured when obscuration from an ionized outflow is greatest. We suggest that, when the obscurer is strongest, reprocessing by the BLR elongates the lags most significantly. As the wind weakens, the lags are dominated by shorter accretion disk lags., Comment: 28 pages, 11 figures, 3 tables. Accepted for publication in the Astrophysical Journal

We present 0$.\!\!^{\prime\prime}{22}$-resolution CO(2$-$1) observations of the circumnuclear gas disk in the local compact galaxy NGC 384 with the Atacama Large Millimeter/submillimeter Array (ALMA). While the majority of the disk displays regular rotation with projected velocities rising to $370$ km s$^{-1}$, the inner $\sim$0\farcs{5} exhibits a kinematic twist. We develop warped disk gas-dynamical models to account for this twist, fit those models to the ALMA data cube, and find a stellar mass-to-light ratio in the $H$-band of \mlabstract\ and a supermassive black hole (BH) mass ($M_{\mathrm{BH}}$) of $M_{\mathrm{BH}}$ $= (7.26^{+0.43}_{-0.48}$ [$1\sigma$ statistical] $^{+0.55}_{-1.00}$ [systematic])$\times 10^8$ $M_\odot$. In contrast to most previous dynamical $M_{\mathrm{BH}}$ measurements in local compact galaxies, which typically found over-massive BHs compared to the local BH mass$-$bulge luminosity and BH mass$-$bulge mass relations, NGC 384 lies within the scatter of those scaling relations. NGC 384 and other local compact galaxies are likely relics of $z\sim2$ red nuggets, and over-massive BHs in these relics indicate BH growth may conclude before the host galaxy stars have finished assembly. Our NGC 384 results may challenge this evolutionary picture, suggesting there may be increased scatter in the scaling relations than previously thought. However, this scatter could be inflated by systematic differences between stellar- and gas-dynamical measurement methods, motivating direct comparisons between the methods for NGC 384 and the other compact galaxies in the sample., Comment: 19 pages, 8 figures, accepted for publication in ApJ

We study how the rigidity transition in a triangular lattice changes as a function of anisotropy by preferentially filling bonds on the lattice in one direction. We discover that the onset of rigidity in anisotropic spring networks arises in at least two steps, reminiscent of the two-step melting transition in two dimensional crystals. In particular, our simulations demonstrate that the percolation of stress-supporting bonds happens at different critical volume fractions along different directions. By examining each independent component of the elasticity tensor, we determine universal exponents and develop universal scaling functions to analyze isotropic rigidity percolation as a multicritical point. We expect that these results will be important for elucidating the underlying mechanical phase transitions governing the properties of biological materials ranging from the cytoskeletons of cells to the extracellular networks of tissues such as tendon where the networks are often preferentially aligned., Comment: 13 pages, 17 figures

This work considers stochastic Galerkin approximations of linear elliptic partial differential equations (PDEs) with stochastic forcing terms and stochastic diffusion coefficients, that cannot be bounded uniformly away from zero and infinity. A traditional numerical method for solving the resulting high-dimensional coupled system of PDEs is replaced by deep learning techniques. In order to achieve this, physics-informed neural networks (PINNs), which typically operate on the strong residual of the PDE and can therefore be applied in a wide range of settings, are considered. As a second approach, the Deep Ritz method, which is a neural network that minimizes the Ritz energy functional to find the weak solution, is employed. While the second approach only works in special cases, it overcomes the necessity of testing in variational problems while maintaining mathematical rigor and ensuring the existence of a unique solution. Furthermore, the residual is of a lower differentiation order, reducing the training cost considerably. The efficiency of the method is demonstrated on several model problems.

SuperBIT was a 0.5-meter near-ultraviolet to near-infrared wide-field telescope that launched on a NASA superpressure balloon into the stratosphere from New Zealand for a 45-night flight. SuperBIT acquired multi-band images of galaxy clusters to study the properties of dark matter using weak gravitational lensing. We provide an overview of the instrument and its various subsystems. We then present the instrument performance from the flight, including the telescope and image stabilization system, the optical system, the power system, and the thermal system. SuperBIT successfully met the instrument's technical requirements, achieving a telescope pointing stability of 0.34 +/- 0.10 arcseconds, a focal plane image stability of 0.055 +/- 0.027 arcseconds, and a PSF FWHM of ~ 0.35 arcseconds over 5-minute exposures throughout the 45-night flight. The telescope achieved a near-diffraction limited point-spread function in all three science bands (u, b, and g). SuperBIT served as a pathfinder to the GigaBIT observatory, which will be a 1.34-meter near-ultraviolet to near-infrared balloon-borne telescope., Comment: 17 pages, 25 pages, published in the Astronomical Journal

The study of cycloaddition mechanisms is central to the fabrication of extended sp2 carbon nanostructures. Reaction modeling in this context has focused mostly on putative, energetically preferred, exothermic products with limited consideration for symmetry allowed or forbidden mechanistic effects. Here, we introduce a scheme for classifying symmetry-forbidden reaction coordinates in Woodward-Hoffmann correlation diagrams. Topological classifiers grant access to the study of reaction pathways and correlation diagrams in the same footing, for the purpose of elucidating mechanisms and products of polycyclic aromatic azomethine ylide (PAMY) cycloadditions with pentacene-yielding polycyclic aromatic hydrocarbons with an isoindole core in the solid-state and on surfaces as characterized by mass spectrometry and scanning tunneling microscopy, respectively. By means of a tight-binding reaction model and density functional theory (DFT) we find topologically-allowed pathways if a product is endothermic, and topologically-forbidden if a product is exothermic. Our work unveils topological classification as a crucial element for reaction modeling for nanographene engineering, and highlights its fundamental role in the design of cycloadditions in on-surface and solid-state chemical reactions, while underscoring that exothermic pathways can be topologically-forbidden.

This work introduces IsUMap, a novel manifold learning technique that enhances data representation by integrating aspects of UMAP and Isomap with Vietoris-Rips filtrations. We present a systematic and detailed construction of a metric representation for locally distorted metric spaces that captures complex data structures more accurately than the previous schemes. Our approach addresses limitations in existing methods by accommodating non-uniform data distributions and intricate local geometries. We validate its performance through extensive experiments on examples of various geometric objects and benchmark real-world datasets, demonstrating significant improvements in representation quality.

Low-luminosity AGNs with low-mass black holes (BHs) in the early universe are fundamental to understanding the BH growth and their co-evolution with the host galaxies. Utilizing JWST NIRCam Wide Field Slitless Spectroscopy (WFSS), we perform a systematic search for broad-line ${\rm H\alpha}$ emitters (BHAEs) at $z\approx 4-5$ in 25 fields of the ASPIRE (A SPectroscopic survey of biased halos In the Reionization Era) project, covering a total area of 275 arcmin$^2$. We identify 16 BHAEs with FWHM of the broad components spanning from $\sim$ 1000 km s$^{-1}$ to 3000 km s$^{-1}$. Assuming the broad linewidths arise due to Doppler broadening around BHs, the implied BH masses range from $10^7$ to $10^{8}~M_\odot$, with broad ${\rm H\alpha}$-converted bolometric luminosity of $10^{44.5}-10^{45.5}$ erg s$^{-1}$ and Eddington ratios of $0.07-0.47$. The spatially extended structure of the F200W stacked image may trace the stellar light from the host galaxies. The ${\rm H\alpha}$ luminosity function indicates an increasing AGN fraction towards the higher ${\rm H\alpha}$ luminosities. We find possible evidence for clustering of BHAEs: two sources are at the same redshift with a projected separation of 519 kpc; one BHAE appears as a composite system residing in an overdense region with three close companion ${\rm H\alpha}$ emitters. Three BHAEs exhibit blueshifted absorption troughs indicative of the presence of high-column-density gas. We find the broad-line and photometrically selected BHAE samples exhibit different distributions in the optical continuum slopes, which can be attributed to their different selection methods. The ASPIRE broad-line ${\rm H\alpha}$ sample provides a good database for future studies of faint AGN populations at high redshift., Comment: 19 pages, 13 figures, 4 tables. Accepted by the ApJ

Quantitative mass spectrometry has revolutionized proteomics by enabling simultaneous quantification of thousands of proteins. Pooling patient-derived data from multiple institutions enhances statistical power but raises significant privacy concerns. Here we introduce FedProt, the first privacy-preserving tool for collaborative differential protein abundance analysis of distributed data, which utilizes federated learning and additive secret sharing. In the absence of a multicenter patient-derived dataset for evaluation, we created two, one at five centers from LFQ E.coli experiments and one at three centers from TMT human serum. Evaluations using these datasets confirm that FedProt achieves accuracy equivalent to DEqMS applied to pooled data, with completely negligible absolute differences no greater than $\text{$4 \times 10^{-12}$}$. In contrast, -log10(p-values) computed by the most accurate meta-analysis methods diverged from the centralized analysis results by up to 25-27. FedProt is available as a web tool with detailed documentation as a FeatureCloud App., Comment: 52 pages, 16 figures, 12 tables. Last two authors listed are joint last authors

The Super-pressure Balloon-borne Imaging Telescope (SuperBIT) is a near-diffraction-limited 0.5m telescope that launched via NASA's super-pressure balloon technology on April 16, 2023. SuperBIT achieved precise pointing control through the use of three nested frames in conjunction with an optical Fine Guidance System (FGS), resulting in an average image stability of 0.055" over 300-second exposures. The SuperBIT FGS includes a tip-tilt fast-steering mirror that corrects for jitter on a pair of focal plane star cameras. In this paper, we leverage the empirical data from SuperBIT's successful 45-night stratospheric mission to inform the FGS design for the next-generation balloon-borne telescope. The Gigapixel Balloon-borne Imaging Telescope (GigaBIT) is designed to be a 1.35m wide-field, high resolution imaging telescope, with specifications to extend the scale and capabilities beyond those of its predecessor SuperBIT. A description and analysis of the SuperBIT FGS will be presented along with methodologies for extrapolating this data to enhance GigaBIT's FGS design and fine pointing control algorithm. We employ a systems engineering approach to outline and formalize the design constraints and specifications for GigaBIT's FGS. GigaBIT, building on the SuperBIT legacy, is set to enhance high-resolution astronomical imaging, marking a significant advancement in the field of balloon-borne telescopes., Comment: 13 pages, 7 figures, SPIE Astronomical Telescopes + Instrumentation 2024

Dusty circumnuclear disks (CNDs) in luminous early-type galaxies (ETGs) show regular, dynamically cold molecular gas kinematics. For a growing number of ETGs, Atacama Large Millimeter/sub-millimeter Array (ALMA) CO imaging and detailed gas-dynamical modeling facilitate moderate-to-high precision black hole (BH) mass ($M_{BH}$) determinations. From the ALMA archive, we identified a subset of 26 ETGs with estimated $M_{BH}/M_{\odot} \gtrsim 10^8$ to a few $\times$10$^9$ and clean CO kinematics but that previously did not have sufficiently high angular resolution near-IR observations to mitigate dust obscuration when constructing stellar luminosity models. We present new optical and near-IR Hubble Space Telescope (HST) images of this sample to supplement the archival HST data, detailing the sample properties and data analysis techniques. After masking the most apparent dust features, we measure stellar surface brightness profiles and model the luminosities using the multi-Gaussian expansion (MGE) formalism. Some of these MGEs have already been used in CO dynamical modeling efforts to secure quality \mbh\ determinations, and the remaining ETG targets here are expected to significantly improve the high-mass end of the current BH census, facilitating new scrutiny of local BH mass-host galaxy scaling relationships. We also explore stellar isophotal behavior and general dust properties, finding these CNDs generally become optically thick in the near-IR ($A_H \gtrsim 1$ mag). These CNDs are typically well-aligned with the larger-scale stellar photometric axes with a few notable exceptions. Uncertain dust impact on the MGE often dominates the BH mass error budget, so extensions of this work will focus on constraining CND dust attenuation., Comment: 47 pages, 37 Figures, Accepted for publication in ApJ

Relativistic jets are thought to play a crucial role in the formation and evolution of massive galaxies and supermassive black holes. Blazars, which are quasars with jets aligned along our line of sight, provide insights into the jetted population and have been observed up to redshifts of z=6.1. Here, we report the discovery and multi-wavelength characterization of the blazar VLASS J041009.05-013919.88 at z=7 (Universe's age ~750 Myr), powered by a ~7x10^8 Msun black hole. The presence of this high-redshift blazar implies a large population of similar but unaligned jetted sources in the early Universe. Our findings suggest two possible scenarios: in one, the jet in J0410-0139 is intrinsically low-power but appears highly luminous due to relativistic beaming, suggesting that most UV-bright quasars at this redshift host jets. Alternatively, if J0410-0139 represents an intrinsically powerful radio source, there should be hundreds to thousands of radio-quiet quasars at z~7 with properties similar to J0410-0139, a prediction in tension with observed quasar densities based on their UV luminosity function. These results support the hypothesis that rapid black hole growth in the early Universe may be driven by jet-enhanced or obscured super-Eddington accretion, potentially playing a key role in forming massive black holes during the epoch of reionization., Comment: Updated to match accepted/final version in Nature Astronomy

We observed the Seyfert 1 galaxy Mrk817 during an intensive multi-wavelength reverberation mapping campaign for 16 months. Here, we examine the behavior of narrow UV absorption lines seen in HST/COS spectra, both during the campaign and in other epochs extending over 14 years. We conclude that while the narrow absorption outflow system (at -3750 km/s with FWHM=177 km/s) responds to the variations of the UV continuum as modified by the X-ray obscurer, its total column density (logNH =19.5 cm-2) did not change across all epochs. The adjusted ionization parameter (scaled with respect to the variations in the Hydrogen ionizing continuum flux) is log UH =-1.0. The outflow is located at a distance smaller than 38 parsecs from the central source, which implies a hydrogen density of nH > 3000 cm-3. The absorption outflow system only covers the continuum emission source and not the broad emission line region, which suggests that its transverse size is small (< 1e16 cm), with potential cloud geometries ranging from spherical to elongated along the line of sight., Comment: 18 pages, 12 Figures, Accepted for publication in ApJ