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In this work, we investigate the application of an advanced nonlinear torsion- and shear-free Kirchhoff rod model, enhanced with a penalty-based barrier function (to simulate the seabed contact), intended for studying the static and dynamic behavior of mooring lines. The formulation incorporates conservative and non-conservative external loads, including those coming from the surrounding flow (added mass, tangential drag, and normal drag). To illustrate the favorable features of this model, we consider some key scenarios such as static configurations, pulsating force applications at the fairlead, and fluid-structure interaction between mooring lines and the surrounding flow. Verification against well-established solutions, including catenary configurations and OpenFAST simulations, shows excellent accuracy in predicting mooring line responses for a floating offshore wind turbine. Among the most important results, we can mention that under normal pulsating loads at the fairlead, the mooring line exhibits a transition from a drag-dominated regime at low frequencies to an added-mass-dominated regime at higher frequencies. Furthermore, tangential forcing at the fairlead reveals a strong coupling between axial and bending dynamics, contrasting with normal forcing scenarios where axial dynamics remain largely unaffected. These findings underscore the potential of the proposed approach for advanced mooring line simulations.

Recent progress has been made in detecting early stage dementia entirely through recordings of patient speech. Multimodal speech analysis methods were applied to the PROCESS challenge, which requires participants to use audio recordings of clinical interviews to predict patients as healthy control, mild cognitive impairment (MCI), or dementia and regress the patient's Mini-Mental State Exam (MMSE) scores. The approach implemented in this work combines acoustic features (eGeMAPS and Prosody) with embeddings from Whisper and RoBERTa models, achieving competitive results in both regression (RMSE: 2.7666) and classification (Macro-F1 score: 0.5774) tasks. Additionally, a novel two-tiered classification setup is utilized to better differentiate between MCI and dementia. Our approach achieved strong results on the test set, ranking seventh on regression and eleventh on classification out of thirty-seven teams, exceeding the baseline results., Comment: Submitted to IEEE ICAD 2025

We present first results from James Webb Space Telescope (JWST) Near-Infrared Spectrograph (NIRSpec), Mid-Infrared Instrument (MIRI), and Keck Cosmic Webb Imager (KCWI) integral field spectroscopy of the powerful but highly obscured host-galaxy of the jetted radio source Cygnus A. We detect 169 infrared emission lines at 1.7--27 micron and explore the kinematics and physical properties of the extended narrow-line region (NLR) in unprecedented detail. The density-stratified NLR appears to be shaped by the initial blow-out and ongoing interaction of the radio jet with the interstellar medium, creating a multi-phase bicone with a layered structure composed of molecular and ionized gas. The NLR spectrum, with strong coronal emission at kpc-scale, is well-modeled by AGN photoionization. We find evidence that the NLR is rotating around the radio axis, perhaps mediated by magnetic fields and driven by angular momentum transfer from the radio jet. The overall velocity field of the NLR is well described by 250 km/s outflow along biconical spiral flow lines, combining both rotation and outflow signatures. There is particularly bright [Fe II] 1.644 micron emission from a dense, high-velocity dispersion, photoionized clump of clouds found near the projected radio axis. Outflows of 600--2000 km/s are found in bullets and streamers of ionized gas that may be ablated by the radio jet from these clouds, driving a local outflow rate of 40 Msun/yr., Comment: Submitted to Astrophysical Journal

In the age of large-scale galaxy and lensing surveys, such as DESI, Euclid, Roman and Rubin, we stand poised to usher in a transformative new phase of data-driven cosmology. To fully harness the capabilities of these surveys, it is critical to constrain the poorly understood influence of baryon feedback physics on the matter power spectrum. We investigate the use of a powerful and novel cosmological probe - fast radio bursts (FRBs) - to capture baryonic effects on the matter power spectrum, leveraging simulations from the CAMELS projects, including IllustrisTNG, SIMBA, and Astrid. We find that FRB statistics exhibit a strong correlation, independet of the subgrid model and cosmology, with quantities known to encapsulate baryonic impacts on the matter power spectrum, such as baryon spread and the halo baryon fraction. We propose an innovative method utilizing FRB observations to quantify the effects of feedback physics and enhance weak lensing measurements of $S_{8}$. We outline the necessary steps to prepare for the imminent detection of large FRB populations in the coming years, focusing on understanding the redshift evolution of FRB observables and mitigating the effects of cosmic variance., Comment: 13 pages, 6 figures, submitted to ApJL

Emotions are known to mediate the relationship between users' content consumption and their online engagement, with heightened emotional intensity leading to increased engagement. Building on this insight, we propose three regressor-guided image editing approaches aimed at diminishing the emotional impact of images. These include (i) a parameter optimization approach based on global image transformations known to influence emotions, (ii) an optimization approach targeting the style latent space of a generative adversarial network, and (iii) a diffusion-based approach employing classifier guidance and classifier-free guidance. Our findings demonstrate that approaches can effectively alter the emotional properties of images while maintaining high visual quality. Optimization-based methods primarily adjust low-level properties like color hues and brightness, whereas the diffusion-based approach introduces semantic changes, such as altering appearance or facial expressions. Notably, results from a behavioral study reveal that only the diffusion-based approach successfully elicits changes in viewers' emotional responses while preserving high perceived image quality. In future work, we will investigate the impact of these image adaptations on internet user behavior., Comment: 39 pages, 22 figures

In this work, we compare the nodal and isogeometric spatial discretization schemes for the nonlinear formulation of shear- and torsion-free rods introduced in [1]. We investigate the resulting discrete solution space, the accuracy, and the computational cost of these spatial discretization schemes. To fulfill the required C1 continuity of the rod formulation, the nodal scheme discretizes the rod in terms of its nodal positions and directors using cubic Hermite splines. Isogeometric discretizations naturally fulfill this with smoothspline basis functions and discretize the rod only in terms of the positions of the control points [2], which leads to a discrete solution in multiple copies of the Euclidean space R3. They enable the employment of basis functions of one degree lower, i.e. quadratic C1 splines, and possibly reduce the number of degrees of freedom. When using the nodal scheme, since the defined director field is in the unit sphere S2, preserving this for the nodal director variable field requires an additional constraint of unit nodal directors. This leads to a discrete solution in multiple copies of the manifold R3xS2, however, results in zero nodal axial stress values. Allowing arbitrary length for the nodal directors, i.e. a nodal director field in R3 instead of S2 as within discrete rod elements, eliminates the constrained nodal axial stresses and leads to a discrete solution in multiple copies of R3. We discuss a strong and weak approach using the Lagrange multiplier method and penalty method, respectively, to enforce the unit nodal director constraint. We compare the resulting semi-discrete formulations and the computational cost of these discretization variants. We numerically demonstrate our findings via examples of a planar roll-up, a catenary, and a mooring line.

We present the Active Galactic Nuclei (AGN) catalog from the fourth data release (HDR4) of the Hobby-Eberly Telescope Dark Energy Experiment Survey (HETDEX). HETDEX is an untargeted spectroscopic survey. HDR4 contains 345,874 Integral Field Unit (IFU) observations from January 2017 to August 2023 covering an effective area of 62.9 deg2. With no imaging pre-selection, our spectroscopic confirmed AGN sample includes low-luminosity AGN, narrow-line AGN, and/or red AGN down to g~25. This catalog has 15,940 AGN across the redshifts of z=0.1~4.6, giving a raw AGN number density of 253.4 deg-2. Among them, 10,499 (66%) have redshifts either confirmed by line pairs or matched to the Sloan Digital Sky Survey Quasar Catalog. For the remaining 5,441 AGN, 2,083 are single broad line AGN candidates, while the remaining 3,358 are single intermediate broad line (full width at half maximum, FWHM ~ 1200 km s-1) AGN candidates. A total of 4,060 (39%) of the 10,499 redshift-confirmed AGN have emission-line regions $3\sigma$ more extended than the image quality which could be strong outflows blowing into the outskirts of the host galaxies or ionized intergalactic medium., Comment: 15 pages, 7 figures, 2 tables, accepted by the Astrophysical Journal Supplement Series

We present GalSBI, a phenomenological model of the galaxy population for cosmological applications using simulation-based inference. The model is based on analytical parametrizations of galaxy luminosity functions, morphologies and spectral energy distributions. Model constraints are derived through iterative Approximate Bayesian Computation, by comparing Hyper Suprime-Cam deep field images with simulations which include a forward model of instrumental, observational and source extraction effects. We developed an emulator trained on image simulations using a normalizing flow. We use it to accelerate the inference by predicting detection probabilities, including blending effects and photometric properties of each object, while accounting for background and PSF variations. This enables robustness tests for all elements of the forward model and the inference. The model demonstrates excellent performance when comparing photometric properties from simulations with observed imaging data for key parameters such as magnitudes, colors and sizes. The redshift distribution of simulated galaxies agrees well with high-precision photometric redshifts in the COSMOS field within $1.5\sigma$ for all magnitude cuts. Additionally, we demonstrate how GalSBI's redshifts can be utilized for splitting galaxy catalogs into tomographic bins, highlighting its potential for current and upcoming surveys. GalSBI is fully open-source, with the accompanying Python package, $\texttt{galsbi}$, offering an easy interface to quickly generate realistic, survey-independent galaxy catalogs., Comment: 43 pages, 14 figures, submitted

Mixed Reality is increasingly used in mobile settings beyond controlled home and office spaces. This mobility introduces the need for user interface layouts that adapt to varying contexts. However, existing adaptive systems are designed only for static environments. In this paper, we introduce SituationAdapt, a system that adjusts Mixed Reality UIs to real-world surroundings by considering environmental and social cues in shared settings. Our system consists of perception, reasoning, and optimization modules for UI adaptation. Our perception module identifies objects and individuals around the user, while our reasoning module leverages a Vision-and-Language Model to assess the placement of interactive UI elements. This ensures that adapted layouts do not obstruct relevant environmental cues or interfere with social norms. Our optimization module then generates Mixed Reality interfaces that account for these considerations as well as temporal constraints. For evaluation, we first validate our reasoning module's capability of assessing UI contexts in comparison to human expert users. In an online user study, we then establish SituationAdapt's capability of producing context-aware layouts for Mixed Reality, where it outperformed previous adaptive layout methods. We conclude with a series of applications and scenarios to demonstrate SituationAdapt's versatility., Comment: 13 pages

We present IR photometry and HST imaging and spectroscopy of Sab galaxy NGC 4826. Schwarzschild dynamical modeling is used to measure its central black hole mass $M$. Photometric decomposition is used to enable a comparison of $M$ to published scaling relations between black hole masses and properties of host bulges. This decomposition implies that NGC 4826 contains classical and pseudo bulges of approximately equal mass. The classical bulge has best-fit S\'ersic index $n=3.27$. The pseudobulge is made up of three parts, an inner lens ($n=0.18$ at $r\lesssim4^{\prime\prime}$), an outer lens ($n=0.17$ at $r \lesssim 45^{\prime\prime}$), and a $n=0.58$ component required to match the surface brightness between the lens components. The total $V$-band luminosity of the galaxy is $M_{VT}=-21.07$, the ratio of classical bulge to total light is $B/T\simeq0.12$, and the ratio of pseudobulge to total light is $PB/T\simeq0.13$. The outer disk is exponential ($n=1.07$) and makes up $D/T=0.75$ of the light of the galaxy. Our best-fit Schwarzschild model has a black hole mass with $1\sigma$ uncertainties of $M=8.4^{+1.7}_{-0.6}\times10^6\ M_\odot$ and a stellar $K$-band mass-to-light ratio of $\Upsilon_K=0.46\pm0.03\ M_{\odot}\ \mathrm{L}_{\odot}^{-1}$ at the assumed distance of 7.27 Mpc. Our modeling is marginally consistent with $M=0$ at the $3\sigma$ limit. These best-fit parameters were calculated assuming the black hole is located where the velocity dispersion is largest; this is offset from the maximum surface brightness, probably because of dust absorption. The black hole mass -- one of the smallest measured by modeling stellar dynamics -- satisfies the well known correlations of $M$ with the $K$-band luminosity, stellar mass, and velocity dispersion of the classical bulge only in contrast to total (classical plus pseudo) bulge luminosity., Comment: Accepted by ApJ. 27 or so pages, 18 figures I think. Online data is available at https://doi.org/10.7302/kr8z-fj98

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 are merging a large participatory science effort with machine learning to enhance the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). Our overall goal is to remove false positives, allowing us to use lower signal-to-noise data and sources with low goodness-of-fit. With six million classifications through Dark Energy Explorers, we can confidently determine if a source is not real at over 94% confidence level when classified by at least ten individuals; this confidence level increases for higher signal-to-noise sources. To date, we have only been able to apply this direct analysis to 190,000 sources. The full sample of HETDEX will contain around 2-3M sources, including nearby galaxies ([O II] emitters), distant galaxies (Lyman-alpha emitters or LAEs), false positives, and contamination from instrument issues. We can accommodate this tenfold increase by using machine learning with visually-vetted samples from Dark Energy Explorers. We have already increased by over ten-fold in number of sources that have been visually vetted from our previous pilot study where we only had 14,000 visually vetted LAE candidates. This paper expands on the previous work increasing the visually-vetted sample from 14,000 to 190,000. In addition, using our currently visually-vetted sample, we generate a real or false positive classification for the full candidate sample of 1.2 million LAEs. We currently have approximately 17,000 volunteers from 159 countries around the world. Thus, we are applying participatory or citizen scientist analysis to our full HETDEX dataset, creating a free educational opportunity that requires no prior technical knowledge., Comment: 11 pages, 5 figures

In this article, we review a class of neuro-mimetic computational models that we place under the label of spiking predictive coding. Specifically, we review the general framework of predictive processing in the context of neurons that emit discrete action potentials, i.e., spikes. Theoretically, we structure our survey around how prediction errors are represented, which results in an organization of historical neuromorphic generalizations that is centered around three broad classes of approaches: prediction errors in explicit groups of error neurons, in membrane potentials, and implicit prediction error encoding. Furthermore, we examine some applications of spiking predictive coding that utilize more energy-efficient, edge-computing hardware platforms. Finally, we highlight important future directions and challenges in this emerging line of inquiry in brain-inspired computing. Building on the prior results of work in computational cognitive neuroscience, machine intelligence, and neuromorphic engineering, we hope that this review of neuromorphic formulations and implementations of predictive coding will encourage and guide future research and development in this emerging research area.

In this work, we propose time-integrated spike-timing-dependent plasticity (TI-STDP), a mathematical model of synaptic plasticity that allows spiking neural networks to continuously adapt to sensory input streams in an unsupervised fashion. Notably, we theoretically establish and formally prove key properties related to the synaptic adjustment mechanics that underwrite TI-STDP. Empirically, we demonstrate the efficacy of TI-STDP in simulations of jointly learning deeper spiking neural networks that process input digit pixel patterns, at both full image and patch-levels, comparing to two powerful historical instantations of STDP; trace-based STDP (TR-STDP) and event-based post-synaptic STDP (EV-STDP). Usefully, we demonstrate that not only are all forms of STDP capable of meaningfully adapting the synaptic efficacies of a multi-layer biophysical architecture, but that TI-STDP is notably able to do so without requiring the tracking of a large window of pre- and post-synaptic spike timings, the maintenance of additional parameterized traces, or the restriction of synaptic plasticity changes to occur within very narrow windows of time. This means that our findings show that TI-STDP can efficiently embody the benefits of models such as canonical STDP, TR-STDP, and EV-STDP without their costs or drawbacks. Usefully, our results further demonstrate the promise of using a spike-correlation scheme such as TI-STDP in conducting credit assignment in discrete pulse-based neuromorphic models, particularly those than acquire a lower-level distributed representation jointly with an upper-level, more abstract representation that self-organizes to cluster based on inherent cross-pattern similarities. We further demonstrate TI-STDP's effectiveness in adapting a simple neuronal circuit that learns a simple bi-level, part-whole hierarchy from sensory input patterns.

The three-dimensional galaxy power spectrum is a powerful probe of primordial non-Gaussianity and additional general relativistic (GR) effects on large scales, which can be constrained by the current and upcoming large-scale structure surveys. In this work, we calculate the linear-order relativistic power spectrum in the spherical Fourier-Bessel (SFB) basis, a coordinate system that preserves the geometry of the curved sky and fully accounts for the wide-angle effect. In particular, we model the GR effects present in the discrete SFB power spectrum, which is a more efficient and stable decomposition of the galaxy density field compared to the continuous SFB basis in the presence of radial windows. To validate our GR calculations, we introduce a mapping between the angular power spectrum and the SFB power spectrum, and we compare our calculations with outputs from CLASS. We discuss the rich pattern of GR effects in the SFB basis and compare the GR effects to the local primordial non-Gaussianity (PNG) effect. The Doppler and lensing effects have different angular and Fourier dependence compared to the PNG in the SFB basis, while the gravitational potential term is more degenerate with the PNG and comparable to a signal of $f_{\rm NL}\sim 1$. We also discuss the potential opportunities of extracting the lensing effect through SFB modes in upcoming LSS surveys., Comment: 31 pages, 13 figures. Revised to match version accepted by PRD

We present a stellar dynamical mass measurement of the supermassive black hole in the elliptical (E1) galaxy NGC 3258. Our findings are based on integral field unit spectroscopy from the Multi Unit Spectroscopic Explorer (MUSE) observations in narrow-field mode with adaptive optics and the MUSE wide-field mode, from which we extract kinematic information by fitting the Ca II and Mg $b$ triplets, respectively. Using axisymmetric, three-integral Schwarzschild orbit library models, we fit the observed line-of-sight velocity distributions to infer the supermassive black hole mass, the $H$-band mass-to-light ratio, the asymptotic circular velocity, and the dark matter halo scale radius of the galaxy. We report a black hole mass of $(2.2 \pm 0.2)\times10^9 \ \rm M_{\scriptscriptstyle\odot}$ at an assumed distance of $31.9 \ \rm Mpc$. This value is in close agreement with a previous measurement from Atacama Large Millimeter/submillimeter Array CO observations. The consistency between these two measurements provides strong support for both the gas dynamical and stellar dynamical methods., Comment: 18 pages, 12 figures, 1 table

Acquiring complex behaviors is essential for artificially intelligent agents, yet learning these behaviors in high-dimensional settings poses a significant challenge due to the vast search space. Traditional reinforcement learning (RL) requires extensive manual effort for reward function engineering. Inverse reinforcement learning (IRL) uncovers reward functions from expert demonstrations but relies on an iterative process that is often computationally expensive. Imitation learning (IL) provides a more efficient alternative by directly comparing an agent's actions to expert demonstrations; however, in high-dimensional environments, such direct comparisons offer insufficient feedback for effective learning. We introduce RILe (Reinforced Imitation Learning), a framework that combines the strengths of imitation learning and inverse reinforcement learning to learn a dense reward function efficiently and achieve strong performance in high-dimensional tasks. RILe employs a novel trainer-student framework: the trainer learns an adaptive reward function, and the student uses this reward signal to imitate expert behaviors. By dynamically adjusting its guidance as the student evolves, the trainer provides nuanced feedback across different phases of learning. Our framework produces high-performing policies in high-dimensional tasks where direct imitation fails to replicate complex behaviors. We validate RILe in challenging robotic locomotion tasks, demonstrating that it significantly outperforms existing methods and achieves near-expert performance across multiple settings.

Let $V$ be a finite-dimensional vector space over the field with $p$ elements, where $p$ is a prime number. Given arbitrary $\alpha,\beta\in \mathrm{GL}(V)$, we consider the semidirect products $V\rtimes\langle \alpha\rangle$ and $V\rtimes\langle \beta\rangle$, and show that if $V\rtimes\langle \alpha\rangle$ and $V\rtimes\langle \beta\rangle$ are isomorphic, then $\alpha$ must be similar to a power of $\beta$ that generates the same subgroup as $\beta$; that is, if $H$ and $K$ are cyclic subgroups of $\mathrm{GL}(V)$ such that $V\rtimes H\cong V\rtimes K$, then $H$ and $K$ must be conjugate subgroups of $\mathrm{GL}(V)$. If we remove the cyclic condition, there exist examples of non-isomorphic, let alone non-conjugate, subgroups $H$ and $K$ of $\mathrm{GL}(V)$ such that $V\rtimes H\cong V\rtimes K$. Even if we require that non-cyclic subgroups $H$ and $K$ of $\mathrm{GL}(V)$ be abelian, we may still have $V\rtimes H\cong V\rtimes K$ with $H$ and $K$ non-conjugate in $\mathrm{GL}(V)$, but in this case, $H$ and $K$ must at least be isomorphic. If we replace $V$ by a free module $U$ over ${\mathbf Z}/p^m{\mathbf Z}$ of finite rank, with $m>1$, it may happen that $U\rtimes H\cong U\rtimes K$ for non-conjugate cyclic subgroups of $\mathrm{GL}(U)$. If we completely abandon our requirements on $V$, a sufficient criterion is given for a finite group $G$ to admit non-conjugate cyclic subgroups $H$ and $K$ of $\mathrm{Aut}(G)$ such that $G\rtimes H\cong G\rtimes K$. This criterion is satisfied by many groups.

The three-dimensional galaxy power spectrum is a powerful probe of primordial non-Gaussianity and additional general relativistic effects, which become important on large scales. At the same time, wide-angle (WA) effects due to differing lines-of-sight (LOS) on the curved sky also become important with large angular separation. In this work, we accurately model WA and Doppler effects using the spherical Fourier-Bessel (SFB) formalism, before transforming the result into the commonly used power spectrum multipoles (PSM). This mapping from the SFB power spectrum to PSM represents a new way to non-perturbatively model WA and GR effects present in the PSM, which we validate with log-normal mocks. Moreover, for the first time, we can compute the analytical PSM Gaussian covariance on large scales, exactly including WA-induced mode-couplings, without resorting to any plane-parallel approximations., Comment: 9 pages, 3 figures. Added derivation of PSM covariance

As galaxy redshift surveys expand to larger areas on the sky, effects coming from the curved nature of the sky become important, introducing wide-angle (WA) corrections to the power spectrum multipoles at large galaxy-pair separations. These corrections particularly impact the measurement of physical effects that are predominantly detected on large scales, such the local primordial non-Gaussianities. In this paper, we examine the validity of the perturbative approach to modeling WA effects in the power spectrum multipoles for upcoming surveys by comparing to measurements on simulated galaxy catalogs using the Yamamoto estimator. We show that on the scales $k \lesssim 2\pi/\chi$, where $\chi$ is the comoving distance to the galaxies, the estimated power spectrum monopole differs by up to $5\%$ from the second-order perturbative result, with similar absolute deviations for higher multipoles. To enable precision comparison, we pioneer an improved treatment of the $\mu$-leakage effects in the Yamamoto estimator. Additionally, we devise a solution to include $f_{\rm NL}$ in the perturbative WA calculations, avoiding divergences in the original framework through the integral constraint. This allows us to conclude that WA effects can mimic a $f_{\rm NL}\sim5$ signal in the lowest SPHEREx redshift bin. We recommend using non-perturbative methods to model large scale power spectrum multipoles for $f_{\rm NL}$ measurements. A companion paper, Wen et al. 2024, addresses this by introducing a new non-perturbative method going through the spherical Fourier-Bessel basis., Comment: 23 pages, 13 figures

The integrated device of a perovskite solar cell with a Li-ion battery is an innovative solution for decentralized energy storage in smart electronic devices. In this study, we examine the stability of Li ions intercalated in a CsPbI$_3$ perovskite and their effect on the electronic structure of Li$_x$CsPbI$_3$ compounds using first-principles density functional theory. Our simulations demonstrate that the insertion of Li at concentrations up to $x$ = 1 into CsPbI$_3$ is energetically possible. Moreover, we identify that the distortion of the Pb-I octahedra has the strongest impact on the change in the electronic band gap. Specifically, an increase in the amount of intercalated Li causes larger structural distortions, which in turn lead to an increasing band gap as function of the Li content.

Halide perovskites are highly promising light-harvesting materials with strong ionic character, enabling in principle the combination of a solar cell and a Li-ion battery in one integrated photo-battery device. Here, we investigate Li ions inside crystals of CsPbI$_3$, as a prototype compound, by means of density-functional-theory calculations. Our findings demonstrate that the interstitial location and migration of Li ions depend strongly on the dynamic nature of the crystal structure of the perovskite compound. We consider two limiting cases for Li in CsPbI$_{3}$,(i) the cubic-symmetry structure as a model for the limit of fast ion motion and (ii) a distorted cubic structure as a model for the limit of slow ion motion. For both limiting cases we obtain moderate energy barriers for migrating Li ions, which highlight the potential of halide perovskites like CsPbI$_3$ for applications in photo-battery devices.

The availability of Large Language Models (LLMs) which can generate code, has made it possible to create tools that improve developer productivity. Integrated development environments or IDEs which developers use to write software are often used as an interface to interact with LLMs. Although many such tools have been released, almost all of them focus on general-purpose programming languages. Domain-specific languages, such as those crucial for Information Technology (IT) automation, have not received much attention. Ansible is one such YAML-based IT automation-specific language. Ansible Lightspeed is an LLM-based service designed explicitly to generate Ansible YAML, given natural language prompt. In this paper, we present the design and implementation of the Ansible Lightspeed service. We then evaluate its utility to developers using diverse indicators, including extended utilization, analysis of user edited suggestions, as well as user sentiments analysis. The evaluation is based on data collected for 10,696 real users including 3,910 returning users. The code for Ansible Lightspeed service and the analysis framework is made available for others to use. To our knowledge, our study is the first to involve thousands of users of code assistants for domain-specific languages. We are also the first code completion tool to present N-Day user retention figures, which is 13.66% on Day 30. We propose an improved version of user acceptance rate, called Strong Acceptance rate, where a suggestion is considered accepted only if less than 50% of it is edited and these edits do not change critical parts of the suggestion. By focusing on Ansible, Lightspeed is able to achieve a strong acceptance rate of 49.08% for multi-line Ansible task suggestions. With our findings we provide insights into the effectiveness of small, dedicated models in a domain-specific context., Comment: This paper has been published at the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE 2024), Industry Showcase under the title "Ansible Lightspeed: A Code Generation Service for IT Automation"

Biological movement patterns can sometimes be quasi linear with abrupt changes in direction and speed, as in plastids in root cells investigated here. For the analysis of such changes we propose a new stochastic model for movement along linear structures. Maximum likelihood estimators are provided, and due to serial dependencies of increments, the classical MOSUM statistic is replaced by a moving kernel estimator. Convergence of the resulting difference process and strong consistency of the variance estimator are shown. We estimate the change points and propose a graphical technique to distinguish between change points in movement direction and speed.

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is designed to detect and measure the redshifts of more than one million Ly$\alpha$ emitting galaxies (LAEs) between $1.88 < z < 3.52$. In addition to its cosmological measurements, these data enable studies of Ly$\alpha$ spectral profiles and the underlying radiative transfer. Using the roughly half a million LAEs in the HETDEX Data Release 3, we stack various subsets to obtain the typical Ly$\alpha$ profile for the $z \sim 2-3$ epoch and to understand their physical properties. We find clear absorption wings around Ly$\alpha$ emission, which extend $\sim 2000$ km $\mathrm{s}^{-1}$ both redward and blueward of the central line. Using far-UV spectra of nearby ($0.002 < z < 0.182$) LAEs in the CLASSY treasury and optical/near-IR spectra of $2.8 < z < 6.7$ LAEs in the MUSE-Wide survey, we observe absorption profiles in both redshift regimes. Dividing the sample by volume density shows that the troughs increase in higher density regions. This trend suggests that the depth of the absorption is dependent on the local density of objects near the LAE, a geometry that is similar to damped Lyman-$\alpha$ systems. Simple simulations of Ly$\alpha$ radiative transfer can produce similar troughs due to absorption of light from background sources by HI gas surrounding the LAEs., Comment: 15 pages, 10 figures, accepted for publication in The Astrophysical Journal

The bispectrum, the three-point correlation in Fourier space, is a crucial statistic for studying many effects targeted by the next-generation galaxy surveys, such as primordial non-Gaussianity (PNG) and general relativistic (GR) effects on large scales. In this work we develop a formalism for the bispectrum in the Spherical Fourier-Bessel (SFB) basis - a natural basis for computing correlation functions on the curved sky, as it diagonalizes the Laplacian operator in spherical coordinates. Working in the SFB basis allows for line-of-sight effects such as redshift space distortions (RSD) and GR to be accounted for exactly, i.e without having to resort to perturbative expansions to go beyond the plane-parallel approximation. Only analytic results for the SFB bispectrum exist in the literature given the intensive computations needed. We numerically calculate the SFB bispectrum for the first time, enabled by a few techniques: We implement a template decomposition of the redshift-space kernel $Z_2$ into Legendre polynomials, and separately treat the PNG and velocity-divergence terms. We derive an identity to integrate a product of three spherical harmonics connected by a Dirac delta function as a simple sum, and use it to investigate the limit of a homogeneous and isotropic Universe. Moreover, we present a formalism for convolving the signal with separable window functions, and use a toy spherically symmetric window to demonstrate the computation and give insights into the properties of the observed bispectrum signal. While our implementation remains computationally challenging, it is a step toward a feasible full extraction of information on large scales via a SFB bispectrum analysis., Comment: 32 pages, 6 figures

Supernova (SN) 2023ixf was discovered on May 19th, 2023. The host galaxy, M101, was observed by the Hobby Eberly Telescope Dark Energy Experiment (HETDEX) collaboration over the period April 30, 2020 -- July 10, 2020, using the Visible Integral-field Replicable Unit Spectrograph (VIRUS; $3470\lesssim\lambda\lesssim5540$ \r{A}) on the 10-m Hobby-Eberly Telescope (HET). The fiber filling factor within $\pm$ 30 arcsec of SN 2023ixf is 80% with a spatial resolution of 1 arcsec. The r<5.5 arcsec surroundings are 100% covered. This allows us to analyze the spatially resolved pre-explosion local environments of SN 2023ixf with nebular emission lines. The 2-dimensional (2D) maps of the extinction and the star-formation rate (SFR) surface density ($\Sigma_{\rm SFR}$) show weak increasing trends in the radial distributions within the r<5.5 arcsec regions, suggesting lower values of extinction and SFR in the vicinity of the progenitor of SN 2023ixf. The median extinction and that of the surface density of SFR within r<3 arcsec are $E(B-V)=0.06\pm0.14$, and $\Sigma_{\rm SFR}=10^{-5.44\pm0.66}~\rm M_{\odot}\cdot yr^{-1}\cdot arcsec^{-2}$. There is no significant change in extinction before and after the explosion. The gas metallicity does not change significantly with the separation from SN 2023ixf. The metal-rich branch of the $R_{23}$ calculations indicates that the gas metallicity around SN 2023ixf is similar to the solar metallicity ($\sim Z_{\odot}$). The archival deep images from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) show a clear detection of the progenitor of SN 2023ixf in the $z$-band at $22.778\pm0.063$ mag, but non-detections in the remaining four bands of CFHTLS ($u,g,r,i$). The results suggest a massive progenitor of $\approx$ 22 $M_\odot$., Comment: 11 pages, 5 figures, Accepted by ApJL

In this work we consider the hybrid Data-Driven Computational Mechanics (DDCM) approach, in which a smooth constitutive manifold is reconstructed to obtain a well-behaved nonlinear optimization problem (NLP) rather than the much harder discrete-continous NLP (DCNLP) of the direct DDCM approach. The key focus is on the addition of geometric inequality constraints to the hybrid DDCM formulation. Therein, the required constraint force leads to a contact problem in the form of a mathematical program with complementarity constraints (MPCC), a problem class that is still less complex than the DCNLP. For this MPCC we propose a heuristic quick-shot solution approach, which can produce verifiable solutions by solving up to four NLPs. We perform various numerical experiments on three different contact problems of increasing difficulty to demonstrate the potential and limitations of this approach., Comment: 23 pages

Preclinical research and organ-dedicated applications require high-resolution positron emission tomography (PET) detectors to visualize small structures and understand biological processes at a finer level of detail. Current commercial systems often employ finely pixelated or monolithic scintillators, each with its limitations. We present a semi-monolithic detector, tailored for high-resolution PET applications, and merging concepts of monolithic and pixelated crystals. The detector features slabs measuring (24 x 10 x 1) sq. mm, coupled to a 12 x 12 readout channel photosensor with 4 mm pitch. The slabs are grouped in two arrays of 44 slabs each to achieve a higher optical photon density. We employ a fan beam collimator for fast calibration to train machine-learning-based positioning models for all three dimensions, including slab identification and depth-of-interaction (DOI), utilizing gradient tree boosting (GTB). Energy calculation was based on a position-dependent energy calibration. Using an analytical timing calibration, time skews were corrected for coincidence timing resolution (CTR) estimation. Leveraging machine-learning-based calibration in all three dimensions, we achieved high detector spatial resolution: down to 1.18 mm full width at half maximum (FWHM) detector spatial resolution and 0.75 mm mean absolute error (MAE) in the planar-monolithic direction along the slabs, and 2.14 mm FWHM and 1.03 mm MAE for depth-of-interaction (DOI) at an energy window of (435-585) keV. Correct slab interaction identification exceeded 80%, alongside an energy resolution of 13.8% and a CTR of 450 ps FWHM. Therewith, the introduced finely segmented, high-resolution slab detector demonstrates an appealing performance suitable for high-resolution PET applications. The current benchtop-based detector calibration routine allows these detectors to be used in PET systems., Comment: 14 pages, 11 figures, IEEE NSS MIC RTSD 2023

Tuning into the bass notes of the large-scale structure requires careful attention to geometrical effects arising from wide angles. The spherical Fourier-Bessel (SFB) basis provides a harmonic-space coordinate system that fully accounts for all wide-angle effects. To demonstrate the feasibility of the SFB power spectrum, in this paper we validate our SFB pipeline by applying it to lognormal, and both complete and realistic EZmock simulations that were generated for eBOSS DR16 LRG sample. We include redshift space distortions and the local average effect (aka integral constraint). The covariance matrix is obtained from 1000 EZmock simulations, and inverted using eigenvalue decomposition., Comment: 20 pages, 16 figures

We present 0$.\!\!^{\prime\prime}22$-resolution Atacama Large Millimeter/submillimeter Array (ALMA) observations of CO(2$-$1) emission from the circumnuclear gas disk in the red nugget relic galaxy PGC 11179. The disk shows regular rotation, with projected velocities near the center of 400 km s$^{-1}$. We assume the CO emission originates from a dynamically cold, thin disk and fit gas-dynamical models directly to the ALMA data. In addition, we explore systematic uncertainties by testing the impacts of various model assumptions on our results. The supermassive black hole (BH) mass ($M_\mathrm{BH}$) is measured to be $M_\mathrm{BH} = (1.91\pm0.04$ [$1\sigma$ statistical] $^{+0.11}_{-0.51}$ [systematic])$\times 10^9$ $M_\odot$, and the $H$-band stellar mass-to-light ratio $M/L_H=1.620\pm0.004$ [$1\sigma$ statistical] $^{+0.211}_{-0.107}$ [systematic] $M_\odot/L_\odot$. This $M_\mathrm{BH}$ is consistent with the BH mass$-$stellar velocity dispersion relation but over-massive compared to the BH mass$-$bulge luminosity relation by a factor of 3.7. PGC 11179 is part of a sample of local compact early-type galaxies that are plausible relics of $z\sim2$ red nuggets, and its behavior relative to the scaling relations echoes that of three relic galaxy BHs previously measured with stellar dynamics. These over-massive BHs could suggest BHs gain most of their mass before their host galaxies do. However, our results could also be explained by greater intrinsic scatter at the high-mass end of the scaling relations, or by systematic differences in gas- and stellar-dynamical methods. Additional $M_\mathrm{BH}$ measurements in the sample, including independent cross-checks between molecular gas- and stellar-dynamical methods, will advance our understanding of the co-evolution of BHs and their host galaxies., Comment: 18 pages, 8 figures, 2 tables. Accepted in ApJ

We quantify the cosmological spread of baryons relative to their initial neighboring dark matter distribution using thousands of state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. We show that dark matter particles spread relative to their initial neighboring distribution owing to chaotic gravitational dynamics on spatial scales comparable to their host dark matter halo. In contrast, gas in hydrodynamic simulations spreads much further from the initial neighboring dark matter owing to feedback from supernovae (SNe) and Active Galactic Nuclei (AGN). We show that large-scale baryon spread is very sensitive to model implementation details, with the fiducial \textsc{SIMBA} model spreading $\sim$40\% of baryons $>$1\,Mpc away compared to $\sim$10\% for the IllustrisTNG and \textsc{ASTRID} models. Increasing the efficiency of AGN-driven outflows greatly increases baryon spread while increasing the strength of SNe-driven winds can decrease spreading due to non-linear coupling of stellar and AGN feedback. We compare total matter power spectra between hydrodynamic and paired $N$-body simulations and demonstrate that the baryonic spread metric broadly captures the global impact of feedback on matter clustering over variations of cosmological and astrophysical parameters, initial conditions, and galaxy formation models. Using symbolic regression, we find a function that reproduces the suppression of power by feedback as a function of wave number ($k$) and baryonic spread up to $k \sim 10\,h$\,Mpc$^{-1}$ while highlighting the challenge of developing models robust to variations in galaxy formation physics implementation., Comment: 17 pages, 15 figures