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For decades, the Free Application for Federal Student Aid (FAFSA) forms were processed electronically by the legacy Central Processing System. In 2021 the Office of Federal Student Aid (FSA) initiated a system development effort and in December 2023 deployed a new system to process forms for the 2024-2025 school year. However, student aid applicants reported that the new system had availability issues, recurring errors, and long wait times. This Government Accountability Office (GAO) testimony (1) describes the delays in delivering on the FAFSA Processing System (FPS) requirements; (2) describes the defects that were identified before and after FPS deployment; (3) assesses the extent to which disciplined systems acquisition practices were used to manage FPS requirements, conduct systems testing, and carry out independent acquisition reviews; and (4) assesses the extent to which Education and FSA IT leadership provided oversight of FPS development. This statement is a companion to GAO's related statement on the simplified FAFSA rollout (GAO-24-107407). In addressing the first two objectives, GAO summarized the preliminary results of its continuing ongoing work describing delays and defects. For the latter two objectives on requirements, testing, and independent reviews, GAO completed its audit work and is making recommendations to address weaknesses.

The MIGHTEE survey utilises the South African MeerKAT radio telescope to observe four extragalactic deep fields, with the aim of advancing our understanding of the formation and evolution of galaxies across cosmic time. MIGHTEE's frequency coverage encompasses the $\textrm{H}\scriptstyle\mathrm{I}$ line to a redshift of z $\simeq$ 0.58, and OH megamasers to z $\simeq$ 0.9. We present the MIGHTEE-$\textrm{H}\scriptstyle\mathrm{I}$ imaging products for the COSMOS field, using a total of 94.2 h on-target and a close-packed mosaic of 15 individual pointings. The spectral imaging covers two broad, relatively interference-free regions (960-1150 and 1290-1520~MHz) within MeerKAT's L-band, with up to 26 kHz spectral resolution (5.5 km s$^{-1}$ at $z$ = 0). The median noise in the highest spectral resolution data is 74 $\mu$Jy beam$^{-1}$, corresponding to a 5$\sigma$ $\textrm{H}\scriptstyle\mathrm{I}$ mass limit of 10$^{8.5}$ M$_{\odot}$ for a 300 km s$^{-1}$ line at $z$ = 0.07. The mosaics cover $>$4 deg$^{2}$, provided at multiple angular resolution / sensitivity pairings, with an angular resolution for $\textrm{H}\scriptstyle\mathrm{I}$ at $z$ = 0 of 12$''$. We describe the spectral line processing workflow that will be the basis for future MIGHTEE-$\textrm{H}\scriptstyle\mathrm{I}$ products, and validation of, and some early results from, the spectral imaging of the COSMOS field. We find no evidence for line emission at the position of the $z$ = 0.376 \HI~line reported from the CHILES survey at a $>$94 per cent confidence level, placing a 3$\sigma$ upper limit of 8.1 $\times$ 10$^{9}$ M$_{\odot}$ on $M_{\mathrm{HI}}$ for this galaxy. A public data release accompanies this article., Comment: 22 pages, 19 figures

A number of machine learning models have been proposed with the goal of achieving systematic generalization: the ability to reason about new situations by combining aspects of previous experiences. These models leverage compositional architectures which aim to learn specialized modules dedicated to structures in a task that can be composed to solve novel problems with similar structures. While the compositionality of these architectures is guaranteed by design, the modules specializing is not. Here we theoretically study the ability of network modules to specialize to useful structures in a dataset and achieve systematic generalization. To this end we introduce a minimal space of datasets motivated by practical systematic generalization benchmarks. From this space of datasets we present a mathematical definition of systematicity and study the learning dynamics of linear neural modules when solving components of the task. Our results shed light on the difficulty of module specialization, what is required for modules to successfully specialize, and the necessity of modular architectures to achieve systematicity. Finally, we confirm that the theoretical results in our tractable setting generalize to more complex datasets and non-linear architectures., Comment: The Eleventh International Conference on Learning Representations 2023

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in early 2025 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the status of the OSC experimental program and its potential to achieve the first demonstration of SSMB during the upcoming experimental run., Comment: 41st Free Electron Laser Conference (FEL2024)

Accurate patient positioning is critical for precise radiotherapy dose delivery, as positioning errors can significantly affect treatment outcomes. This study introduces a novel method for tracking loco-regional tissue deformation through Cherenkov image analysis during fractionated breast cancer radiotherapy. The primary goal was to develop and test an algorithm for Cherenkov-based regional position accuracy quantification, specifically for loco-regional deformations, which lack ideal quantification methods in radiotherapy. Blood vessel detection and segmentation were developed in Cherenkov images using a tissue phantom with incremental movements, and later applied to images from fractionated whole breast radiotherapy in human patients (n=10). A combined rigid and non-rigid registration technique was used to detect inter- and intra-fractional positioning variations. This approach quantified positioning variations in two parts: a global shift from rigid registration and a two-dimensional variation map of loco-regional deformation from non-rigid registration. The methodology was validated using an anthropomorphic chest phantom experiment, where known treatment couch translations and respiratory motion were simulated to assess inter- and intra-fractional uncertainties, yielding an average accuracy of 0.83 mm for couch translations up to 20 mm. Analysis of clinical Cherenkov data from ten breast cancer patients showed an inter-fraction setup variation of 3.7 plus minus 2.4 mm relative to the first fraction and loco-regional deformations (95th percentile) of up to 3.3 plus minus 1.9 mm. This study presents a Cherenkov-based approach to quantify global and local positioning variations, demonstrating feasibility in addressing loco-regional deformations that conventional imaging techniques fail to capture., Comment: 25 pages, 4 figures, 1 table, journal under review

Cherenkov imaging enables real-time visualization of megavoltage X-ray or electron beam delivery to the patient during Radiation Therapy (RT). Bio-morphological features, such as vasculature, seen in these images are patient-specific signatures that can be used for verification of positioning and motion management that are essential to precise RT treatment. However until now, no concerted analysis of this biological feature-based tracking was utilized because of the slow speed and accuracy of conventional image processing for feature segmentation. This study demonstrated the first deep learning framework for such an application, achieving video frame rate processing. To address the challenge of limited annotation of these features in Cherenkov images, a transfer learning strategy was applied. A fundus photography dataset including 20,529 patch retina images with ground-truth vessel annotation was used to pre-train a ResNet segmentation framework. Subsequently, a small Cherenkov dataset (1,483 images from 212 treatment fractions of 19 breast cancer patients) with known annotated vasculature masks was used to fine-tune the model for accurate segmentation prediction. This deep learning framework achieved consistent and rapid segmentation of Cherenkov-imaged bio-morphological features on another 19 patients, including subcutaneous veins, scars, and pigmented skin. Average segmentation by the model achieved Dice score of 0.85 and required less than 0.7 milliseconds processing time per instance. The model demonstrated outstanding consistency against input image variances and speed compared to conventional manual segmentation methods, laying the foundation for online segmentation in real-time monitoring in a prospective setting., Comment: 9 pages, 7 figures, 1 table, journal under review

We present a deep HI survey at L-band conducted with the Five-hundred-meter Aperture Spherical radio Telescope (FAST) over the COSMOS field. This survey is strategically designed to overlap with the MIGHTEE COSMOS field, aiming to combine the sensitivity of the FAST and high-resolution of the MeerKAT. We observed the field with FAST for approximately 11 hours covering $\sim$2 square degrees, and reduced the raw data to HI spectral cubes over the frequency range 1310-1420 MHz. The FAST-HI data reach a median 3$\sigma$ column density of $N_{\rm HI}\sim2\times10^{17}$ cm$^{-2}$ over a 5 km s$^{-1}$ channel width, allowing for studies of the distribution of HI gas in various environments, such as in galaxies, the Circum-Galactic Medium (CGM) and Intergalactic Medium (IGM). We visually searched the spectral cubes for HI sources, and found a total of 80 HI detections, of which 56 have been cross-matched with the MIGHTEE-HI catalogue. With the cross-matched sources, we compare their HI masses and find that the total HI mass fraction in the IGM and CGM surrounding the galaxy pairs is statistically higher than the HI fraction surrounding the isolated galaxies by a difference of 13$\pm$4%, indicating that the CGM and IGM associated with interacting systems are richer in neutral hydrogen compared to those around isolated galaxies in the local Universe. We also describe several FAST-MeerKAT synergy projects, highlighting the full potential of exploiting both single-dish and interferometric observations to study the distribution and evolution of the diffuse HI gas., Comment: 13 pages, 14 figures; Accepted for publication in MNRAS; Minor corrections made at proof stage

A central problem in data science is to use potentially noisy samples of an unknown function to predict function values for unseen inputs. In classical statistics, the predictive error is understood as a trade-off between the bias and the variance that balances model simplicity with its ability to fit complex functions. However, over-parameterized models exhibit counter-intuitive behaviors, such as "double descent" in which models of increasing complexity exhibit decreasing generalization error. We introduce an alternative paradigm called the generalized aliasing decomposition. We explain the asymptotically small error of complex models as a systematic "de-aliasing" that occurs in the over-parameterized regime. In the limit of large models, the contribution due to aliasing vanishes, leaving an expression for the asymptotic total error we call the invertibility failure of very large models on few training points. Because the generalized aliasing decomposition can be explicitly calculated from the relationship between model class and samples without seeing any data labels, it can answer questions related to experimental design and model selection before collecting data or performing experiments. We demonstrate this approach using several examples, including classical regression problems and a cluster expansion model used in materials science.

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

Operation with ultra-low momentum-compaction factor (alpha) is a desirable capability for many storage rings and synchrotron radiation sources. For example, low-alpha lattices are commonly used to produce picosecond bunches for the generation of coherent THz radiation and are the basis of a number of conceptual designs for EUV generation via steady-state microbunching (SSMB). Achieving ultra-low alpha requires not only a high-level of stability in the linear optics but also flexible control of higher-order compaction terms. Operation with lower momentum-compaction lattices has recently been investigated at the IOTA storage ring at Fermilab. A procedure for lowering the ring compaction using the linear optics along with compensations from the higher-order magnets was developed with the aid of a model, and an experimental technique for measuring the momentum compaction was developed. The lowest momentum compaction achieved during the available run-time was $3.4\times10^{-4}$, around 15 times lower than previously operated. These feasibility studies ensure an improved experimental understanding of the IOTA optics and potentially will enable new research programs at the facility., Comment: 15th International Particle Accelerator Conference (IPAC'24)

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})<11.51$. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at $\log(M_\mathrm{host}/M_\odot) < 11.84$. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs., Comment: 16 pages, 15 figures

The search for the electromagnetic counterparts to gravitational wave (GW) events has been rapidly gathering pace in recent years thanks to the increasing number and capabilities of both gravitational wave detectors and wide field survey telescopes. Difficulties remain, however, in detecting these counterparts due to their inherent scarcity, faintness and rapidly evolving nature. To find these counterparts, it is important that one optimises the observing strategy for their recovery. This can be difficult due to the large number of potential variables at play. Such follow-up campaigns are also capable of detecting hundreds or potentially thousands of unrelated transients, particularly for GW events with poor localisation. Even if the observations are capable of detecting a counterpart, finding it among the numerous contaminants can prove challenging. Here we present the Gravitational wave Electromagnetic RecovRY code (GERry) to perform detailed analysis and survey-agnostic quantification of observing campaigns attempting to recover electromagnetic counterparts. GERry considers the campaign's spatial, temporal and wavelength coverage, in addition to Galactic extinction and the expected counterpart light curve evolution from the GW 3D localisation volume. It returns quantified statistics that can be used to: determine the probability of having detected the counterpart, identify the most promising sources, and assess and refine strategy. Here we demonstrate the code to look at the performance and parameter space probed by current and upcoming wide-field surveys such as GOTO & VRO., Comment: 19 pages, 11 figures, submitted to SPIE Astronomical Telescopes + Instrumentation 2024

The Gravitational-wave Optical Transient Observer (GOTO) is a project dedicated to identifying optical counter-parts to gravitational-wave detections using a network of dedicated, wide-field telescopes. After almost a decade of design, construction, and commissioning work, the GOTO network is now fully operational with two antipodal sites: La Palma in the Canary Islands and Siding Spring in Australia. Both sites host two independent robotic mounts, each with a field-of-view of 44 square degrees formed by an array of eight 40 cm telescopes, resulting in an instantaneous 88 square degree field-of-view per site. All four telescopes operate as a single integrated network, with the ultimate aim of surveying the entire sky every 2-3 days and allowing near-24-hour response to transient events within a minute of their detection. In the modern era of transient astronomy, automated telescopes like GOTO form a vital link between multi-messenger discovery facilities and in-depth follow-up by larger telescopes. GOTO is already producing a wide range of scientific results, assisted by an efficient discovery pipeline and a successful citizen science project: Kilonova Seekers., Comment: 8 pages, 5 figures, submitted to SPIE Astronomical Telescopes + Instrumentation 2024

The spin-exotic hybrid meson $\pi_{1}(1600)$ is predicted to have a large decay rate to the $\omega\pi\pi$ final state. Using 76.6~pb$^{-1}$ of data collected with the GlueX detector, we measure the cross sections for the reactions $\gamma p \to \omega \pi^+ \pi^- p$, $\gamma p \to \omega \pi^0 \pi^0 p$, and $\gamma p\to\omega\pi^-\pi^0\Delta^{++}$ in the range $E_\gamma =$ 8-10 GeV. Using isospin conservation, we set the first upper limits on the photoproduction cross sections of the $\pi^{0}_{1}(1600)$ and $\pi^{-}_{1}(1600)$. We combine these limits with lattice calculations of decay widths and find that photoproduction of $\eta'\pi$ is the most sensitive two-body system to search for the $\pi_1(1600)$., Comment: 6 pages, 3 figures plus supplemental materials

The NOEMA formIng Cluster survEy (NICE) is a large program targeting 69 massive galaxy group candidates at $z>2$ in six deep fields. We report spectroscopic confirmation of eight groups at $1.65\leq z\leq3.61$ in COSMOS. Homogeneously selected as significant overdensities of red IRAC sources with red Herschel colors, four groups are confirmed by CO and [CI] with NOEMA 3mm observations, three are confirmed with ALMA, and one is confirmed by H$\alpha$ from Subaru/FMOS. We constructed the integrated FIR SEDs for the eight groups, obtaining total IR SFR $=260-1300~{\rm M_\odot}$~yr$^{-1}$. We adopted six methods to estimate the dark matter masses, including stellar mass to halo mass relations, overdensity with galaxy bias, and NFW profile fitting to radial stellar mass density. We found the radial stellar mass density are consistent with a NFW profile, supporting that they are collapsed structures hosted by a single dark matter halo. The best halo mass estimates are $\log(M_{\rm h}/{\rm M_\odot})=12.8-13.7$ with uncertainty of 0.3 dex. From halo mass estimates, we derive baryonic accretion rate ${\rm BAR}=(1-8)\times10^{3}\,{\rm M_{\odot}/yr}$ for this sample. We find a quasi-linear correlation between the integrated SFR/BAR and the theoretical halo mass limit for cold streams, $M_{\rm stream}/M_{\rm h}$, with ${\rm SFR/BAR}=10^{-0.46\pm0.22}\left({M_{\rm stream}/M_{\rm h}}\right)^{0.71\pm0.16}$ with a scatter of $0.40\,{\rm dex}$. Further, we compare halo masses and stellar masses with simulations, and find all structures are consistent with being progenitors of $M_{\rm h}(z=0)>10^{14}\,{\rm M_{\odot}}$ galaxy clusters, and the most massive central galaxies have stellar masses consistent with brightest cluster galaxies (BCGs) progenitors in the TNG300 simulation. The results strongly suggest these structures are forming massive galaxy clusters via baryonic and dark matter accretion., Comment: 44 pages (27pp appendix), 32 figures, 18 tables, accepted for publication in A&A

We study the ring of invariant functions over the $N$-fold Cartesian product of copies of the compact Lie group $G=SU(2)$, modulo the action of conjugation by the diagonal subgroup, generalizing the group character ring. For $N=1$, an orthonormal basis for the space of invariant functions is given by the irreducible characters, and the structure constants under pointwise multiplication are the coefficients of the Clebsch-Gordan series for the reduction of angular momentum tensor products ($3j$ coefficients). For $N \ge 2$, the structure constants under pointwise multiplication of the corresponding invariants, which we term irreducible quasicharacters, are Racah $3(2N\!-\!1)j$ recoupling coefficients, which can be decomposed as products of $9j$ coefficients (for $N=2$, they are squares thereof). We identify the irreducible quasicharacters for $\times^N\! SU(2)$ with traces of representations of group elements, over totally coupled angular momentum states labelled by binary coupling trees $T$ with $N$ leaves, $N\!-\!1$ internal vertices and associated intermediate edge labels. Using concrete spin chain realizations and projection techniques, we give explicit constructions for some low degree $N=2, 3$ and $4$ quasicharacters. In the case $N=2$, related methods are used to work out the expansions of products of generic, with elementary spin-$\textstyle{\frac 12}$, quasicharacters (equivalent to an \emph{ab initio} evaluation of certain basic $9j$ coefficients). We provide an appendix which summarizes formal properties of the quasicharacter calculus known from our previous work for both $SU(2)$ and for compact $G$ (J Math Phys 59 (8) 083505 (2018) and 62(3) 033514 (2021). In particular, we provide an explicit derivation for the $N=2$ angular momentum quasicharacter product rule., Comment: 35 pages, 6 tables, LaTeX, uses youngtab.tex. arXiv admin note: text overlap with arXiv:1803.11077

The three-point correlation function (3PCF) of a weak lensing shear field contains information that is complementary to that in the two-point correlation function (2PCF), which can help improve the cosmological parameters and calibrate astrophysical and observational systematics parameters. However, the application of the 3PCF to observed data has been limited due to the computational challenges of calculating theoretical predictions of the 3PCF from a bispectrum model. In this paper, we present a new method to compute the shear 3PCF efficiently and accurately. We employ the multipole expansion of the bispectrum to compute the shear 3PCF, and show that the method is substantially more efficient than direct numerical integration. We found that the multipole-based method can compute the shear 3PCF with 5% accuracy in 10 (40) seconds for the single (four) source redshift bin setup. The multipole-based method can be also used to compute the third-order aperture mass statistics quickly and accurately, accounting for the bin-averaging effect on the shear 3PCF. Our method provides a fast and robust tool for probing the underlying cosmological model with third-order statistics of weak lensing shear., Comment: 20 pages, 9 figures, 2 tables, code available at https://github.com/git-sunao/fastnc

The presence of defects in transition metal dichalcogenides (TMDs) can lead to dramatic local changes in their properties which are of interest for a range of technologies including quantum security devices, hydrogen production, and energy storage. It is therefore essential to be able to study these materials in their native environments, including ambient conditions. Here we report single atom resolution imaging of atomic defects in MoS2, WSe2 and WS2 monolayers carried out in ambient conditions using conductive atomic force microscopy (C-AFM). By comparing measurements from a range of TMDs we use C-AFM to chemically identify the most likely atomic species for the defects observed and quantify their prevalence on each material, identifying oxygen chalcogen substitutions and transition metal substitutions as the most likely, and most common, defect types. Moreover, we demonstrate that C-AFM operated in ambient environments can resolve subtle changes in electronic structure with atomic resolution, which we apply to WSe2 monolayers doped using a nitrogen plasma, demonstrating the capability of C-AFM to resolve electronic, and chemical-specific, details at the atomic scale.

We measure the spin-density matrix elements (SDMEs) of the $\Delta^{++}(1232)$ in the photoproduction reaction $\gamma p \to \pi^-\Delta^{++}(1232)$ with the GlueX experiment in Hall D at Jefferson Lab. The measurement uses a linearly--polarized photon beam with energies from $8.2$ to $8.8$~GeV and the statistical precision of the SDMEs exceeds the previous measurement by three orders of magnitude for the momentum transfer squared region below $1.4$ GeV$^2$. The data are sensitive to the previously undetermined relative sign between couplings in existing Regge-exchange models. Linear combinations of the extracted SDMEs allow for a decomposition into natural and unnatural--exchange amplitudes. We find that the unnatural exchange plays an important role in the low momentum transfer region.

We present the joint tomographic analysis of galaxy-galaxy lensing and galaxy clustering in harmonic space, using galaxy catalogues from the first three years of observations by the Dark Energy Survey (DES Y3). We utilise the redMaGiC and MagLim catalogues as lens galaxies and the METACALIBRATION catalogue as source galaxies. The measurements of angular power spectra are performed using the pseudo-$C_\ell$ method, and our theoretical modelling follows the fiducial analyses performed by DES Y3 in configuration space, accounting for galaxy bias, intrinsic alignments, magnification bias, shear magnification bias and photometric redshift uncertainties. We explore different approaches for scale cuts based on non-linear galaxy bias and baryonic effects contamination. Our fiducial covariance matrix is computed analytically, accounting for mask geometry in the Gaussian term, and including non-Gaussian contributions and super-sample covariance terms. To validate our harmonic space pipelines and covariance matrix, we used a suite of 1800 log-normal simulations. We also perform a series of stress tests to gauge the robustness of our harmonic space analysis. In the $\Lambda$CDM model, the clustering amplitude $S_8 =\sigma_8(\Omega_m/0.3)^{0.5}$ is constrained to $S_8 = 0.704\pm 0.029$ and $S_8 = 0.753\pm 0.024$ ($68\%$ C.L.) for the redMaGiC and MagLim catalogues, respectively. For the $w$CDM, the dark energy equation of state is constrained to $w = -1.28 \pm 0.29$ and $w = -1.26^{+0.34}_{-0.27}$, for redMaGiC and MagLim catalogues, respectively. These results are compatible with the corresponding DES Y3 results in configuration space and pave the way for harmonic space analyses using the DES Y6 data., Comment: To be submitted to MNRAS

Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratised, distributed approaches to training sets for machine learning classifiers are crucial to make the most of this torrent of discovery -- with citizen science approaches proving effective at meeting these requirements. In this paper, we describe the creation of and the initial results from the $\textit{Kilonova Seekers}$ citizen science project, built to find transient phenomena from the GOTO telescopes in near real-time. $\textit{Kilonova Seekers}$ launched in July 2023 and received over 600,000 classifications from approximately 2,000 volunteers over the course of the LIGO-Virgo-KAGRA O4a observing run. During this time, the project has yielded 20 discoveries, generated a `gold-standard' training set of 17,682 detections for augmenting deep-learned classifiers, and measured the performance and biases of Zooniverse volunteers on real-bogus classification. This project will continue throughout the lifetime of GOTO, pushing candidates at ever-greater cadence, and directly facilitate the next-generation classification algorithms currently in development., Comment: 20 pages, 15 figures. Accepted in MNRAS

Single-dish far-infrared (far-IR) and sub-millimetre (sub-mm) point source catalogues and their connections with catalogues at other wavelengths are of paramount importance. However, due to the large mismatch in spatial resolution, cross-matching galaxies at different wavelengths is challenging. This work aims to develop the next-generation deblended far-IR and sub-mm catalogues and present the first application in the COSMOS field. Our progressive deblending used the Bayesian probabilistic framework known as XID+. The deblending started from the Spitzer/MIPS 24 micron data, using an initial prior list composed of sources selected from the COSMOS2020 catalogue and radio catalogues from the VLA and the MeerKAT surveys, based on spectral energy distribution modelling which predicts fluxes of the known sources at the deblending wavelength. To speed up flux prediction, we made use of a neural network-based emulator. After deblending the 24 micron data, we proceeded to the Herschel PACS (100 & 160 micron) and SPIRE wavebands (250, 350 & 500 micron). Each time we constructed a tailor-made prior list based on the predicted fluxes of the known sources. Using simulated far-IR and sub-mm sky, we detailed the performance of our deblending pipeline. After validation with simulations, we then deblended the real observations from 24 to 500 micron and compared with blindly extracted catalogues and previous versions of deblended catalogues. As an additional test, we deblended the SCUBA-2 850 micron map and compared our deblended fluxes with ALMA measurements, which demonstrates a higher level of flux accuracy compared to previous results.We publicly release our XID+ deblended point source catalogues. These deblended long-wavelength data are crucial for studies such as deriving the fraction of dust-obscured star formation and better separation of quiescent galaxies from dusty star-forming galaxies., Comment: 23 pages, 30 figures, accepted for publication in A&A. Catalogues can be downloaded from https://hedam.lam.fr/HELP/dataproducts/dmu26/dmu26_XID+COSMOS2024/

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1) second and third moments; 2) wavelet phase harmonics; 3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven $\nu w$CDM cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the Figure of Merit $\textrm{FoM}(S_8, \Omega_{\textrm{m}})$ is improved by 70 percent ($\Lambda$CDM) and 90 percent ($w$CDM). When all the summary statistics are combined, we achieve a 2 percent constraint on the amplitude of fluctuations parameter $S_8 \equiv \sigma_8 (\Omega_{\textrm{m}}/0.3)^{0.5}$, obtaining $S_8 = 0.794 \pm 0.017$ ($\Lambda$CDM) and $S_8 = 0.817 \pm 0.021$ ($w$CDM). The constraints from different statistics are shown to be internally consistent (with a $p$-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the DES Y3 data, finding good consistency; we also compare with results from external datasets, such as \planck{} constraints from the Cosmic Microwave Background, finding statistical agreement, with discrepancies no greater than $<2.2\sigma$., Comment: 24 pages, 13 figures, to be submitted to PRD. Comments welcome!

Runaway electron incidence on plasma facing components triggers explosive events that are accompanied by the expulsion of fast solid debris. Subsequent dust-wall high speed impacts constitute a mechanism of wall damage and dust destruction. Empirical damage laws that can be employed for erosion estimates are based on room-temperature impact experiments. We use light-gas gun shooting systems to accelerate solid tungsten dust to near-supersonic speeds towards bulk tungsten targets that are maintained at different temperatures. This concerns targets cooled down to $-100^{\circ}$C with liquid nitrogen and targets resistively heated up to $400^{\circ}$C. Post-mortem surface analysis reveals that the three erosion regimes (plastic deformation, bonding, partial disintegration) weakly depend on the target temperature within the investigated range. It is concluded that empirical damage laws based on room-temperature measurements can be safely employed for predictions., Comment: 6 pages, 5 figures, 1 table

The tight relationship between infrared luminosity (L$_\mathrm{TIR}$) and 1.4 GHz radio continuum luminosity (L$_\mathrm{1.4GHz}$) has proven useful for understanding star formation free from dust obscuration. Infrared emission in star-forming galaxies typically arises from recently formed, dust-enshrouded stars, whereas radio synchrotron emission is expected from subsequent supernovae. By leveraging the wealth of ancillary far-ultraviolet - far-infrared photometry from the Deep Extragalactic VIsible Legacy Survey (DEVILS) and Galaxy and Mass Assembly (GAMA) surveys, combined with 1.4 GHz observations from the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) survey and Deep Investigation of Neutral Gas Origins (DINGO) projects, we investigate the impact of timescale differences between far-ultraviolet - far-infrared and radio-derived star formation rate (SFR) tracers. We examine how the SED-derived star formation histories (SFH) of galaxies can be used to explain discrepancies in these SFR tracers, which are sensitive to different timescales. Galaxies exhibiting an increasing SFH have systematically higher L$_\mathrm{TIR}$ and SED-derived SFRs than predicted from their 1.4 GHz radio luminosity. This indicates that insufficient time has passed for subsequent supernovae-driven radio emission to accumulate. We show that backtracking the SFR(t) of galaxies along their SED-derived SFHs to a time several hundred megayears prior to their observed epoch will both linearise the SFR-L$_\mathrm{1.4GHz}$ relation and reduce the overall scatter. The minimum scatter in the SFR(t)-L$_\mathrm{1.4GHz}$ is reached at 200 - 300 Myr prior, consistent with theoretical predictions for the timescales required to disperse the cosmic ray electrons responsible for the synchrotron emission., Comment: 23 pages, 13 figures, 2 tables. Accepted for publication in MNRAS

Major European Union-funded research infrastructure and open science projects have traditionally included dissemination work, for mostly one-way communication of the research activities. Here we present and review our radical re-envisioning of this work, by directly engaging citizen science volunteers into the research. We summarise the citizen science in the Horizon-funded projects ASTERICS (Astronomy ESFRI and Research Infrastructure Clusters) and ESCAPE (European Science Cluster of Astronomy and Particle Physics ESFRI Research Infrastructures), engaging hundreds of thousands of volunteers in providing millions of data mining classifications. Not only does this have enormously more scientific and societal impact than conventional dissemination, but it facilitates the direct research involvement of what is often arguably the most neglected stakeholder group in Horizon projects, the science-inclined public. We conclude with recommendations and opportunities for deploying crowdsourced data mining in the physical sciences, noting that the primary goal is always the fundamental research question; if public engagement is the primary goal to optimise, then other, more targeted approaches may be more effective., Comment: Accepted by European Physical Journal Plus. Invited review. 26 pages, 1 figure

Most stars form in clusters and groups rather than in isolation. We present $\lesssim 5^{\prime\prime}$ angular resolution ($\sim 2000$ au, or 0.01 pc) Very Large Array NH$_3$ (1,1), (2,2), and (3,3) and 1.3 cm continuum emission observations of the dense gas within the Serpens South protocluster and extended filaments to the north and south. We identify 94 dense cores using a dendrogram analysis of the NH$_3$ (1,1) integrated intensity. Gas temperatures $T_K$ and non-thermal linewidths $\sigma_\mathrm{NT}$ both increase towards the centre of the young stellar cluster, in the dense gas generally and in the cores specifically. We find that most cores (54\%) are super-virial, with gravitationally bound cores located primarily in the filaments. Cores in the protocluster have higher virial parameters by a factor $\sim 1.7$, driven primarily by the increased core $\sigma_\mathrm{NT}$ values. These cores cannot collapse to form stars unless they accrete additional mass or their core internal motions are reduced. The southern filament shows a significant velocity gradient previously interpreted as mass flow toward the cluster. We find more complex kinematics in the northern filament. We find a strong correlation between $\sigma_\mathrm{NT}$ and $T_K$, and argue that the enhanced temperatures and non-thermal motions are due to mechanical heating and interaction between the protocluster-driven outflows and the dense gas. Filament-led accretion may also contribute to the increased $\sigma_\mathrm{NT}$ values. Assuming a constant fraction of core mass ends up in the young stars, future star formation in the Serpens South protocluster will shift to higher masses by a factor $\sim 2$., Comment: 27 pages, 12 figures, accepted to ApJ

Extracting precise cosmology from weak lensing surveys requires modelling the non-linear matter power spectrum, which is suppressed at small scales due to baryonic feedback processes. However, hydrodynamical galaxy formation simulations make widely varying predictions for the amplitude and extent of this effect. We use measurements of Dark Energy Survey Year 3 weak lensing (WL) and Atacama Cosmology Telescope DR5 kinematic Sunyaev-Zel'dovich (kSZ) to jointly constrain cosmological and astrophysical baryonic feedback parameters using a flexible analytical model, `baryonification'. First, using WL only, we compare the $S_8$ constraints using baryonification to a simulation-calibrated halo model, a simulation-based emulator model and the approach of discarding WL measurements on small angular scales. We find that model flexibility can shift the value of $S_8$ and degrade the uncertainty. The kSZ provides additional constraints on the astrophysical parameters and shifts $S_8$ to $S_8=0.823^{+0.019}_{-0.020}$, a higher value than attained using the WL-only analysis. We measure the suppression of the non-linear matter power spectrum using WL + kSZ and constrain a mean feedback scenario that is more extreme than the predictions from most hydrodynamical simulations. We constrain the baryon fractions and the gas mass fractions and find them to be generally lower than inferred from X-ray observations and simulation predictions. We conclude that the WL + kSZ measurements provide a new and complementary benchmark for building a coherent picture of the impact of gas around galaxies across observations.

While Reinforcement Learning from Human Feedback (RLHF) effectively aligns pretrained Large Language and Vision-Language Models (LLMs, and VLMs) with human preferences, its computational cost and complexity hamper its wider adoption. To alleviate some of the computational burden of fine-tuning, parameter efficient methods, like LoRA were introduced. In this work, we empirically evaluate the setup of Parameter Efficient Reinforcement Learning from Human Feedback (PE-RLHF) that leverages LoRA fine-tuning for Reward Modeling, and Reinforcement Learning. We benchmark the PE-RLHF setup on six diverse datasets spanning summarization, harmless/helpful response generation, UI automation, and visual question answering in terms of effectiveness of the trained models, and the training resources required. Our findings show, for the first time, that PE-RLHF achieves comparable performance to RLHF, while significantly reducing training time (up to 90% faster for reward models, and 30% faster for RL), and memory footprint (up to 50% reduction for reward models, and 27% for RL). We provide comprehensive ablations across LoRA ranks, and model sizes for both reward modeling and reinforcement learning. By mitigating the computational burden associated with RLHF, we push for a broader adoption of PE-RLHF as an alignment technique for LLMs and VLMs.

This paper studies the gradient flow dynamics that arise when training deep homogeneous neural networks, starting with small initializations. The present work considers neural networks that are assumed to have locally Lipschitz gradients and an order of homogeneity strictly greater than two. This paper demonstrates that for sufficiently small initializations, during the early stages of training, the weights of the neural network remain small in norm and approximately converge in direction along the Karush-Kuhn-Tucker (KKT) points of the neural correlation function introduced in [1]. Additionally, for square loss and under a separability assumption on the weights of neural networks, a similar directional convergence of gradient flow dynamics is shown near certain saddle points of the loss function.

The GlueX Central Drift Chamber (CDC) in Hall D at Jefferson Lab, used for detecting and tracking charged particles, is calibrated and controlled during data taking using a Gaussian process. The system dynamically adjusts the high voltage applied to the anode wires inside the chamber in response to changing environmental and experimental conditions such that the gain is stabilized. Control policies have been established to manage the CDC's behavior. These policies are activated when the model's uncertainty exceeds a configurable threshold or during human-initiated tests during normal production running. We demonstrate the system reduces the time detector experts dedicate to calibration of the data offline, leading to a marked decrease in computing resource usage without compromising detector performance., Comment: AI4EIC2023, 9 pages

We present simulation-based cosmological $w$CDM inference using Dark Energy Survey Year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky PKDGRAV dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock DES lensing data sets. For $w$CDM inference, for which we allow $-1

We present the first measurement of HI mass of star-forming galaxies in different large scale structure environments from a blind survey at $z\sim 0.37$. In particular, we carry out a spectral line stacking analysis considering $2875$ spectra of colour-selected star-forming galaxies undetected in HI at $0.23 < z < 0.49$ in the COSMOS field, extracted from the MIGHTEE-HI Early Science datacubes, acquired with the MeerKAT radio telescope. We stack galaxies belonging to different subsamples depending on three different definitions of large scale structure environment: local galaxy overdensity, position inside the host dark matter halo (central, satellite, or isolated), and cosmic web type (field, filament, or knot). We first stack the full star-forming galaxy sample and find a robust HI detection yielding an average galaxy HI mass of $M_{\rm HI}=(8.12\pm 0.75)\times 10^9\, {\rm M}_\odot$ at $\sim 11.8\sigma$. Next, we investigate the different subsamples finding a negligible difference in $M_{\rm HI}$ as a function of the galaxy overdensity. We report an HI excess compared to the full sample in satellite galaxies ($M_{\rm HI}=(11.31\pm1.22)\times 10^9$, at $\sim 10.2 \sigma$) and in filaments ($M_{\rm HI}=(11.62\pm 0.90)\times 10^9$. Conversely, we report non-detections for the central and knot galaxies subsamples, which appear to be HI-deficient. We find the same qualitative results also when stacking in units of HI fraction ($f_{\rm HI}$). We conclude that the HI amount in star-forming galaxies at the studied redshifts correlates with the large scale structure environment., Comment: Accepted for publication in MNRAS. 15 figures, 3 tables

This paper examines gradient flow dynamics of two-homogeneous neural networks for small initializations, where all weights are initialized near the origin. For both square and logistic losses, it is shown that for sufficiently small initializations, the gradient flow dynamics spend sufficient time in the neighborhood of the origin to allow the weights of the neural network to approximately converge in direction to the Karush-Kuhn-Tucker (KKT) points of a neural correlation function that quantifies the correlation between the output of the neural network and corresponding labels in the training data set. For square loss, it has been observed that neural networks undergo saddle-to-saddle dynamics when initialized close to the origin. Motivated by this, this paper also shows a similar directional convergence among weights of small magnitude in the neighborhood of certain saddle points., Comment: tmlr-final-version

Final report for the AI Assisted Experiment Control and Calibration project. This project integrated AI/ML into the controls and calibration of a production detector system in the GlueX spectrometer, a large scale Nuclear Physics detector in experimental Hall-D at Jefferson Lab. The AI/ML model predicted calibration constants for a Central Drift Chamber using environmental information available prior to taking the data. The device controls were then automatically adjusted so that the calibration values needed for post-processing of the data were much more stable and quicker to determine. Integration into a production system required guardrails and policy choices to ensure safety of the equipment and the data quality. The project sought to apply similar technology to other detectors. Those efforts are also described here. This documents many of the details of the project., Comment: 68 pages

We use data from the JWST Public Release IMaging for Extragalactic Research (PRIMER) survey to measure the size scaling relations of 1668 rest-frame UV-bright Lyman-break galaxies (LBGs) at $z=3-5$ with stellar masses $\mathrm{log}_{10}(M_{\star}/M_{\odot}) > 9$. The sample was selected from seeing-dominated ground-based data, presenting an unbiased sampling of the morphology and size distributions of luminous sources. We fit S\'ersic profiles to eight NIRCam bands and also measure a non-parametric half-light radius. We find that the size distributions with both measurements are well-fit by a log-normal distribution at all redshifts, consistent with disk formation models where size is governed by host dark-matter halo angular momentum. We find a size-redshift evolution of $R_{e} = 3.51(1+z)^{-0.60\pm0.22}$ kpc, in agreement with JWST studies. When considering the typical (modal) size over $z=3-5$, we find little evolution with bright LBGs remaining compact at $R_{e}\simeq0.7-0.9$ kpc. Simultaneously, we find evidence for a build-up of large ($R_{e} > 2$ kpc) galaxies by $z=3$. We find some evidence for a negatively sloped size-mass relation at $z=5$ when S\'ersic profiles are used to fit the data in F200W. The intrinsic scatter in our size-mass relations increases at higher redshifts. Additionally, measurements probing the rest-UV (F200W) show larger intrinsic scatter than those probing the rest-optical (F356W). Finally, we leverage rest-UV and rest-optical photometry to show that disky galaxies are well established by $z=5$, but are beginning to undergo dissipative processes, such as mergers, by $z=3$. The agreement of our size-mass and size-luminosity relations with simulations provides tentative evidence for centrally concentrated star formation at high-redshift., Comment: 15 pages, 9 figures, 3 tables. Accepted to MNRAS. 2 figures added in appendix