Search

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: 52 pages, 12 figures

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

Reinforcement Learning has achieved significant success in generating complex behavior but often requires extensive reward function engineering. Adversarial variants of Imitation Learning and Inverse Reinforcement Learning offer an alternative by learning policies from expert demonstrations via a discriminator. Employing discriminators increases their data- and computational efficiency over the standard approaches; however, results in sensitivity to imperfections in expert data. We propose RILe, a teacher-student system that achieves both robustness to imperfect data and efficiency. In RILe, the student learns an action policy while the teacher dynamically adjusts a reward function based on the student's performance and its alignment with expert demonstrations. By tailoring the reward function to both performance of the student and expert similarity, our system reduces dependence on the discriminator and, hence, increases robustness against data imperfections. Experiments show that RILe outperforms existing methods by 2x in settings with limited or noisy expert data.

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: 7 pages, 3 figures

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. This paper first presents 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 rejected suggestions, as well as analysis of user sentiments. The analysis 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 in evaluating code assistants for domain-specific languages. We propose an improved version of user acceptance rate and we are the first code completion tool to present N-Day user retention figures. With our findings we provide insights into the effectiveness of small, dedicated models in a domain-specific context. We hope this work serves as a reference for software engineering and machine learning researchers exploring code completion services for domain-specific languages in particular and programming languages in general.

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

In this paper, we present a discrete formulation of nonlinear shear- and torsion-free rods introduced by Gebhardt and Romero in [20] that uses isogeometric discretization and robust time integration. Omitting the director as an independent variable field, we reduce the number of degrees of freedom and obtain discrete solutions in multiple copies of the Euclidean space (R^3), which is larger than the corresponding multiple copies of the manifold (R^3 x S^2) obtained with standard Hermite finite elements. For implicit time integration, we choose the same integration scheme as Gebhardt and Romero in [20] that is a hybrid form of the midpoint and the trapezoidal rules. In addition, we apply a recently introduced approach for outlier removal by Hiemstra et al. [26] that reduces high-frequency content in the response without affecting the accuracy, ensuring robustness of our nonlinear discrete formulation. We illustrate the efficiency of our nonlinear discrete formulation for static and transient rods under different loading conditions, demonstrating good accuracy in space, time and the frequency domain. Our numerical example coincides with a relevant application case, the simulation of mooring lines.

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

We describe the ensemble properties of the $1.9 < z < 3.5$ Lyman Alpha Emitters (LAEs) found in the HETDEX survey's first public data release, HETDEX Public Source Catalog 1 (Mentuch Cooper et al. 2023). Stacking the low-resolution ($R \sim$ 800) spectra greatly increases the signal-to-noise ratio, revealing spectral features otherwise hidden by noise, and we show that the stacked spectrum is representative of an average member of the set. The flux limited, Ly$\alpha$ signal-to-noise ratio restricted stack of 50K HETDEX LAEs shows the ensemble biweight ``average" $z \sim 2.6$ LAE to be a blue (UV continuum slope $\sim -2.4$ and E(B-V) $< 0.1$), moderately bright (M$_{\text{UV}} \sim -19.7$) star forming galaxy with strong Ly$\alpha$ emission (log $L_{Ly\alpha}$ $\sim$ 42.8 and $W_{\lambda}$(Ly$\alpha$) $\sim$ 114\AA), and potentially significant leakage of ionizing radiation. The restframe UV light is dominated by a young, metal poor stellar population with an average age 5-15 Myr and metallicity of 0.2-0.3 Z$_{\odot}$., Comment: 17 pages, 11 figures, 2 data files (ApJ Accepted)

The LIGO HET Response (LIGHETR) project is an enterprise to follow up optical transients (OT) discovered as gravitational wave merger sources by the LIGO/Virgo collaboration (LVC). Early spectroscopy has the potential to constrain crucial parameters such as the aspect angle. The LIGHETR collaboration also includes the capacity to model the spectroscopic evolution of mergers to facilitate a real-time direct comparison of models with our data. The principal facility is the Hobby-Eberly Telescope. LIGHETR uses the massively-replicated VIRUS array of spectrographs to search for associated OTs and obtain early blue spectra and in a complementary role, the low-resolution LRS-2 spectrograph is used to obtain spectra of viable candidates as well as a densely-sampled series of spectra of true counterparts. Once an OT is identified, the anticipated cadence of spectra would match or considerably exceed anything achieved for GW170817 = AT2017gfo for which there were no spectra in the first 12 hours and thereafter only roughly once daily. We describe special HET-specific software written to facilitate the program and attempts to determine the flux limits to undetected sources. We also describe our campaign to follow up OT candidates during the third observational campaign of the LIGO and Virgo Scientific Collaborations. We obtained VIRUS spectroscopy of candidate galaxy hosts for 5 LVC gravitational wave events and LRS-2 spectra of one candidate for the OT associated with S190901ap. We identified that candidate, ZTF19abvionh = AT2019pip, as a possible Wolf-Rayet star in an otherwise unrecognized nearby dwarf galaxy., Comment: 26 pages, 15 figures

The stellar dynamic-based black hole mass measurements of M87 are twice that determined via ionized gas kinematics; the former is closer to the estimation from the diameter of the gravitationally-lensed ring around the black hole. Using deeper and more comprehensive ionized gas kinematic data, we aim to better constrain the morphology and kinematics of the nuclear ionized gas, thus gaining insights into the reasons behind the disagreement of the measurements. We use both Narrow and Wide Field Mode integral field spectroscopic data from the Multi Unit Spectroscopic Explorer instrument, to model the morphology and kinematics of multiple ionized gas emission lines in the nucleus of M87. The new deep dataset reveals complexities in the nuclear ionized gas kinematics. Several ionized gas filaments can be traced down into the projected sphere of influence. We also found evidence of a partially-filled biconical outflow. The velocity isophotes of the ionized gas disk are twisted and the position angle of the innermost gas disk tends toward a value perpendicular to the radio jet axis. The complexity of the nuclear morphology and kinematics precludes the measurement of an accurate black hole mass. The results support a 6.0 $\times 10^{9}\rm M_{\odot}$ black hole in a 25\deg disk, rather than a 3.5 $\times 10^{9}\rm M_{\odot}$ black hole in a 42\deg disk. The specific RIAF model earlier proposed to reconcile the mass measurement discrepancy was also tested. In general, Keplerian disk models perform better than the RIAF model when fitting the sub-arcsec ionized gas disk. A disk inclination close to 25\deg for the nuclear gas disk, and the warp in the sub-arcsec ionized gas disk, help to reconcile the contradictory nature of the mass discrepancy between stellar and ionized gas black hole masses, and the mis-orientation between the axes of the ionized gas disk and the jet., Comment: 21 pages, 22 figures (5 of them in the appendix). Accepted in Astronomy & Astrophysics

We present analysis using a citizen science campaign to improve the cosmological measures from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the Hubble expansion rate, $H(z)$, and angular diameter distance, $D_A(z)$, at $z =$ 2.4, each to percent-level accuracy. This accuracy is determined primarily from the total number of detected Lyman-$\alpha$ emitters (LAEs), the false positive rate due to noise, and the contamination due to [O II] emitting galaxies. This paper presents the citizen science project, Dark Energy Explorers, with the goal of increasing the number of LAEs, decreasing the number of false positives due to noise and the [O II] galaxies. Initial analysis shows that citizen science is an efficient and effective tool for classification most accurately done by the human eye, especially in combination with unsupervised machine learning. Three aspects from the citizen science campaign that have the most impact are 1) identifying individual problems with detections, 2) providing a clean sample with 100% visual identification above a signal-to-noise cut, and 3) providing labels for machine learning efforts. Since the end of 2022, Dark Energy Explorers has collected over three and a half million classifications by 11,000 volunteers in over 85 different countries around the world. By incorporating the results of the Dark Energy Explorers we expect to improve the accuracy on the $D_A(z)$ and $H(z)$ parameters at $z =$ 2.4 by 10 - 30%. While the primary goal is to improve on HETDEX, Dark Energy Explorers has already proven to be a uniquely powerful tool for science advancement and increasing accessibility to science worldwide., Comment: 14 pages, 6 figures, accepted for publication in The Astrophysical Journal

We present the Texas Euclid Survey for Lyman-Alpha (TESLA), a spectroscopic survey in the 10 square degree of the Euclid North Ecliptic Pole (NEP) field. Using TESLA, we study how the physical properties of Lyman-alpha emitters (LAEs) correlate with Lyman-alpha emission to understand the escape of Lyman alpha from galaxies at redshifts 2 -- 3.5. We present an analysis of 43 LAEs performed in the NEP field using early data from the TESLA survey. We use Subaru Hyper Suprime-Cam imaging in the grizy-bands, Spitzer/IRAC channels 1 and 2 from the Hawaii 20 square degree (H20) survey and spectra acquired by the Visible Integral-Field Replicable Unit Spectrograph (VIRUS) on the Hobby-Eberly Telescope. We perform spectral energy distribution (SED) fitting to compute the galaxy properties of 43 LAEs, and study correlations between stellar mass, star formation rate (SFR), and dust, to the Lyman-alpha rest-frame equivalent widths (EW). We uncover marginal (1 sigma significance) correlations between stellar mass and Lyman-alpha EW, and star formation rate (SFR) and Lyman-alpha EW, with a Spearman correlation coefficient of -0.$34_{-.14}^{+.17}$ and -0.$37_{-.14}^{+.16}$ respectively. We show that the Lyman-alpha distribution of the 43 LAEs is consistent with being drawn from an exponential distribution with an e-folding scale of 150 Angstrom. Once complete the TESLA survey will enable the study of ~ thousands of LAEs to explore correlations between galaxy properties and Lyman-alpha EW. The large sample size will allow the construction of a predictive model for the Lyman-alpha EW as a function of SED-derived galaxy properties, which could be used to improve Lyman-alpha based constraints on reionization.

We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algorithms designed for cosmological studies. CAMELS-ASTRID employs the galaxy formation model following the ASTRID simulation and contains 2,124 hydrodynamic simulation runs that vary 3 cosmological parameters ($\Omega_m$, $\sigma_8$, $\Omega_b$) and 4 parameters controlling stellar and AGN feedback. Compared to the existing TNG and SIMBA simulation suites in CAMELS, the fiducial model of ASTRID features the mildest AGN feedback and predicts the least baryonic effect on the matter power spectrum. The training set of ASTRID covers a broader variation in the galaxy populations and the baryonic impact on the matter power spectrum compared to its TNG and SIMBA counterparts, which can make machine-learning models trained on the ASTRID suite exhibit better extrapolation performance when tested on other hydrodynamic simulation sets. We also introduce extension simulation sets in CAMELS that widely explore 28 parameters in the TNG and SIMBA models, demonstrating the enormity of the overall galaxy formation model parameter space and the complex non-linear interplay between cosmology and astrophysical processes. With the new simulation suites, we show that building robust machine-learning models favors training and testing on the largest possible diversity of galaxy formation models. We also demonstrate that it is possible to train accurate neural networks to infer cosmological parameters using the high-dimensional TNG-SB28 simulation set.