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Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables

This First Look report introduces new data for national and state-level public elementary and secondary revenues and expenditures for fiscal year (FY) 2022. Specifically, this report includes the following school finance data: (1) revenue and expenditure totals; (2) revenues by source; (3) expenditures by function, subfunction, and object; (4) current expenditures; (5) revenues and current expenditures per pupil; (6) expenditures from Title I funds; and (7) revenues and expenditures from COVID-19 Federal Assistance Funds. The expenditure functions include instruction, support services, food services, and enterprise operations. The support services function is further broken down into seven subfunctions: instructional staff support services, pupil support services, general administration, school administration, operations and maintenance, student transportation, other support services (such as business services). Objects reported within a function or subfunction include salaries and wages, employee benefits, purchased services, supplies, and equipment. The purpose of a First Look report is to introduce new data through the presentation of tables containing descriptive information. The selected findings chosen for this report demonstrate the range of information available when using NPEFS. They do not represent all of the data and are not meant to emphasize any particular issue. While the tables in this report include data for all NPEFS respondents, the selected findings are limited to the 50 states and the District of Columbia.

This First Look report introduces new data for national and state-level public elementary and secondary revenues and expenditures for fiscal year (FY) 2022. Specifically, this report includes the following school finance data: (1) revenue and expenditure totals; (2) revenues by source; (3) expenditures by function, subfunction, and object; (4) current expenditures; (5) revenues and current expenditures per pupil; (6) expenditures from Title I funds; and (7) revenues and expenditures from COVID-19 Federal Assistance Funds. The expenditure functions include instruction, support services, food services, and enterprise operations. The support services function is further broken down into seven subfunctions: instructional staff support services, pupil support services, general administration, school administration, operations and maintenance, student transportation, other support services (such as business services).1 Objects reported within a function or subfunction include salaries and wages, employee benefits, purchased services, supplies, and equipment. The finance data used in this report are from the National Public Education Financial Survey (NPEFS), a component of the Common Core of Data (CCD). The CCD is one of NCES's primary survey programs on public elementary and secondary education in the United States. State education agencies (SEAs) in each of the 50 states, the District of Columbia, and the five other jurisdictions of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands report these data annually to NCES. The NPEFS instructions ask SEAs to report revenues and expenditures covering prekindergarten through high school public education in regular, special, and vocational schools; charter schools; and state-run education programs (such as special education schools or education programs for incarcerated youth).

Early childhood educators play an essential role in providing child care for families and learning and development supports for young children, yet they have long faced challenges due to low wages. Recognizing this, the District of Columbia (DC) introduced the Early Childhood Pay Equity Fund in 2022. This first-of-its-kind initiative aims to bridge the pay gap between early educators and teachers at public schools, addressing historical inequities and improving recruitment and retention efforts. This report provides an in-depth exploration of early educators' experiences with the Pay Equity Fund during its initial year of implementation. Drawing on data from surveys conducted in May 2023 and follow-up focus groups, the report offers insights into the transition from direct payments to an opt-in payment structure by employers in FY 2024. It covers educators' introduction to the Fund, their application and payment experiences, financial impacts, and perceived benefits for child care programs and the broader early childhood education field.

This study comprehensively analyzes Atlas's current orbit, focusing on the secular and resonant perturbations caused by Prometheus, Pandora, and Saturn's oblateness. We performed numerical integration of the exact equations of motion for a dense ensemble of Atlas clone satellites. Through spectral analysis and interpretation of these orbits on dynamical maps, we identified the domain of the 54:53 Prometheus-Atlas and 70:67 Pandora-Atlas mean-motion resonances, showing that Atlas lies on the boundary of the separatrices of each of these resonances. We also identified the domains for the multiplets $\Psi_{1}$, $\Psi_{2}$, $\Psi_{3}$ and $\Psi_{4}$ associated with 70:67 resonance. Additionally, we explored the variation in Prometheus's eccentricity, demonstrating that as eccentricity increases (or decreases) in the 54:53 resonance domain correspondingly decreases (or increases). This combined analysis, between the above mappings, revealed qualitatively the overlap between the 54:53 and 70:67 resonances, which are responsible for the chaotic behavior of Atlas's orbit. We quantified chaotic motion in frequency space and found that the vicinity of Atlas is characterized by weak to moderate chaos, rather than strong chaos. Finally, we investigated Atlas's recent past, considering Prometheus's migration under the influence of Saturn's tidal forces. This analysis reveals several resonances crossed in the past, particularly focusing on the Atlas-Prometheus pair, which exhibited a co-orbital configuration., Comment: 29 pages, 16 figures. Published in PSS

Negative triangularity (NT) tokamak configurations have several key benefits including sufficient core confinement, improved power handling, and reduced edge pressure gradients that allow for edge-localized mode (ELM) free operation. We present the design of a compact NT device for testing sophisticated simulation and control software, with the aim of demonstrating NT controllability and informing power plant operation. The TokaMaker code is used to develop the basic electromagnetic system of the $R_0$ = 1 m, $a$ = 0.27 m, $B_t$ = 3 T, $I_p$ = 0.75 MA tokamak. The proposed design utilizes eight poloidal field coils with maximum currents of 1 MA to achieve a wide range of plasma geometries with $-0.7 < \delta < -0.3$ and $1.5 < \kappa < 1.9$. Scenarios with strong negative triangularity and high elongation are particularly susceptible to vertical instability, necessitating the inclusion of high-field side and/or low-field side passive stabilizing plates which together reduce vertical instability growth rates by $\approx$75%. Upper limits for the forces on poloidal and toroidal field coils are predicted and mechanical loads on passive structures during current quench events are assessed. The 3 T on-axis toroidal field is achieved with 16 demountable copper toroidal field coils, allowing for easy maintenance of the vacuum vessel and poloidal field coils. This pre-conceptual design study demonstrates that the key capabilities required of a dedicated NT tokamak experiment can be realized with existing copper magnet technologies.

We present results from a high precision experimental study of the nuclear modification of the longitudinal ($F_L$) to transverse ($F_1$) structure function ratio for bound nucleons in the resonance region. The inclusive electron scattering cross sections were measured in Jefferson Lab Experimental Hall C on carbon and deuterium nuclei for a large range of kinematics, allowing for separations of the longitudinal and transverse structure functions to be performed at a range of four-momentum transfer values $0.5 \le Q^2 \le$ 3.75 GeV$^2$. In contrast to the significant body of measurements of the nuclear modification of the $F_2$ structure function in the deep inelastic scattering region, there is very little on $F_L$ and $R = F_L / 2xF_1$ in the region of the nucleon resonances. In this paper we present measurements of the nuclear effect on $R$ for $^{12}$C ($R_C$) relative to deuterium ($R_D$). These results indicate regions in which in $R_C>R_D$, requiring that the nuclear modifications be different in all three structure functions, $F_2$, $F_1$ and $F_L$., Comment: to be published in PRL

Hybrid clinical trials, that borrow real-world data (RWD), are gaining interest, especially for rare diseases. They assume RWD and randomized control arm be exchangeable, but violations can bias results, inflate type I error, or reduce power. A two-step hybrid design first tests exchangeability, reducing inappropriate borrowing but potentially inflating type I error (Yuan et al., 2019). We propose four methods to better control type I error. Approach 1 estimates the variance of test statistics, rejecting the null hypothesis based on large sample normal approximation. Approach 2 uses a numerical approach for exact critical value determination. Approach 3 splits type I error rates by equivalence test outcome. Approach 4 adjusts the critical value only when equivalence is established. Simulation studies using a hypothetical ALS scenario, evaluate type I error and power under various conditions, compared to the Bayesian power prior approach (Ibrahim et al., 2015). Our methods and the Bayesian power prior control type I error, whereas Yuan et al. (2019) increases it under exchangeability. If exchangeability doesn't hold, all methods fail to control type I error. Our methods show type I error inflation of 6%-8%, compared to 10% for Yuan et al. (2019) and 16% for the Bayesian power prior.

We introduce the AIDA-TNG project, a suite of cosmological magnetohydrodynamic simulations that simultaneously model galaxy formation and different variations of the underlying dark matter model. We consider the standard cold dark matter model and five variations, including three warm dark matter scenarios and two self-interacting models with constant or velocity-dependent cross-section. In each model, we simulate two cosmological boxes of 51.7 and 110.7 Mpc on a side, with the same initial conditions as TNG50 and TNG100, and combine the variations in the physics of dark matter with the fiducial IllustrisTNG galaxy formation model. The AIDA-TNG runs are thus ideal for studying the simultaneous effect of baryons and alternative dark matter models on observable properties of galaxies and large-scale structures. We resolve haloes in the range between $10^{8}$ and $4\times10^{14}\,$M$_{\odot}$ and scales down to the nominal resolution of 570 pc in the highest resolution runs. This work presents the first results on statistical quantities such as the halo mass function and the matter power spectrum; we quantify the modification in the number of haloes and the power on scales smaller than 1 Mpc, due to the combination of baryonic and dark matter physics. Despite being calibrated on cold dark matter, we find that the TNG galaxy formation model can produce a realistic galaxy population in all scenarios. The stellar and gas mass fraction, stellar mass function, black hole mass as a function of stellar mass and star formation rate density are very similar in all dark matter models, with some deviations only in the most extreme warm dark matter model. Finally, we also quantify changes in halo structure due to warm and self-interacting dark matter, which appear in the density profiles, concentration-mass relation and galaxy sizes., Comment: 20 pages, 18 figures, submitted to A&A. Comments welcome, get in touch to know more about opportunities to use the runs - https://gdespali.github.io/AIDA/

Systemic drug administration often causes off-target effects limiting the efficacy of advanced therapies. Targeted drug delivery approaches increase local drug concentrations at the diseased site while minimizing systemic drug exposure. We present a magnetically guided microrobotic drug delivery system capable of precise navigation under physiological conditions. This platform integrates a clinical electromagnetic navigation system, a custom-designed release catheter, and a dissolvable capsule for accurate therapeutic delivery. In vitro tests showed precise navigation in human vasculature models, and in vivo experiments confirmed tracking under fluoroscopy and successful navigation in large animal models. The microrobot balances magnetic material concentration, contrast agent loading, and therapeutic drug capacity, enabling effective hosting of therapeutics despite the integration complexity of its components, offering a promising solution for precise targeted drug delivery.

The prediction of solar irradiance enhances reliability in photovoltaic (PV) solar plant generation and grid integration. In Colombia, PV plants face penalties if energy production deviates beyond governmental thresholds from intraday market offers. This research employs Long Short-Term Memory (LSTM) and Bidirectional-LSTM (Bi-LSTM) models, utilizing meteorological data from a PV plant in El Paso, Cesar, Colombia, to predict solar irradiance with a 6-hour horizon and 10-minute resolution. While Bi-LSTM showed superior performance, the LSTM model achieved comparable results with significantly reduced training time (6 hours versus 18 hours), making it computationally advantageous. The LSTM predictions were averaged to create an hourly resolution model, evaluated using Mean Absolute Error, Root-Mean-Square Error, Normalized Root-Mean-Square Error, and Mean Absolute Percentage Error metrics. Comparison with the Global Forecast System (GFS) revealed similar performance, with both models effectively capturing daily solar irradiance patterns. The forecast model integrates with an Object-Oriented power production model, enabling accurate energy offers in the intraday market while minimizing penalty costs., Comment: 20 pages, 37 figures, 9 tables

We consider plumbings of symplectic disk bundles over spheres admitting concave contact boundary, with the goal of understanding the geometric properties of the boundary contact structure in terms of the data of the plumbing. We focus on the linear plumbing case in this article. We study the properties of the contact structure using two different sets of tools. First, we prove that all such contact manifolds have a global contact toric structure, and use tools from toric geometry to identify when the contact structure is tight versus overtwisted. Second, we study algebraic torsion measurements from embedded contact homology for these concavely induced contact manifolds, which has largely been unexplored. We develop a toolkit establishing existence and constraints of pseudoholomorphic curves adapted to the Morse-Bott Reeb dynamics of these plumbing examples, to provide the algebraic torsion and contact invariant calculations for the concave boundaries of linear plumbings., Comment: 66 pages, 26 figures, comments welcome!

Hate speech and abusive language are global phenomena that need socio-cultural background knowledge to be understood, identified, and moderated. However, in many regions of the Global South, there have been several documented occurrences of (1) absence of moderation and (2) censorship due to the reliance on keyword spotting out of context. Further, high-profile individuals have frequently been at the center of the moderation process, while large and targeted hate speech campaigns against minorities have been overlooked. These limitations are mainly due to the lack of high-quality data in the local languages and the failure to include local communities in the collection, annotation, and moderation processes. To address this issue, we present AfriHate: a multilingual collection of hate speech and abusive language datasets in 15 African languages. Each instance in AfriHate is annotated by native speakers familiar with the local culture. We report the challenges related to the construction of the datasets and present various classification baseline results with and without using LLMs. The datasets, individual annotations, and hate speech and offensive language lexicons are available on https://github.com/AfriHate/AfriHate

Globular clusters (GCs) are some of the oldest bound structures in the Universe, holding clues to the earliest epochs of star formation and galaxy assembly. However, accurate age measurements of ancient clusters are challenging due to the age-metallicity degeneracy. Here, we report the discovery of 42 compact stellar systems within the 'Relic', a massive, quiescent galaxy at $z=2.53$. The Relic resides in an over-density behind the Abell 2744 cluster, with a prominent tidal tail extending towards two low-mass companions. Using deep data from the UNCOVER/MegaScience JWST Surveys, we find that clusters formed in age intervals ranging from 8 Myr up to $\sim2$ Gyr, suggesting a rich formation history starting at $z\sim10$. While the cluster-based star formation history is broadly consistent with the high past star formation rates derived from the diffuse host galaxy light, one potential discrepancy is a tentative $\sim2-3\times$ higher rate in the cluster population for the past Gyr. Taken together with the spatial distribution and low inferred metallicities of these young-to-intermediate age clusters, we may be seeing direct evidence for the accretion of star clusters in addition to their early in-situ formation. The cluster masses are high, $\sim10^6-10^7~M_{\odot}$, which may explain why we are able to detect them around this likely post-merger galaxy. Overall, the Relic clusters are consistent with being precursors of the most massive present-day GCs. This unique laboratory enables the first connection between long-lived, high-redshift clusters and local stellar populations, offering insights into the early stages of GC evolution and the broader processes of galaxy assembly., Comment: 19 pages, 7 figures, submitted to Astrophysical Journal on January 9, 2025 (comments welcome!)

This paper presents \textit{TopoFormer}, a novel hybrid deep learning architecture that integrates transformer-based encoders with convolutional long short-term memory (ConvLSTM) layers for the precise prediction of topographic beach profiles referenced to elevation datums, with a particular focus on Mean Low Water Springs (MLWS) and Mean Low Water Neaps (MLWN). Accurate topographic estimation down to MLWS is critical for coastal management, navigation safety, and environmental monitoring. Leveraging a comprehensive dataset from the Wales Coastal Monitoring Centre (WCMC), consisting of over 2000 surveys across 36 coastal survey units, TopoFormer addresses key challenges in topographic prediction, including temporal variability and data gaps in survey measurements. The architecture uniquely combines multi-head attention mechanisms and ConvLSTM layers to capture both long-range dependencies and localized temporal patterns inherent in beach profiles data. TopoFormer's predictive performance was rigorously evaluated against state-of-the-art models, including DenseNet, 1D/2D CNNs, and LSTMs. While all models demonstrated strong performance, \textit{TopoFormer} achieved the lowest mean absolute error (MAE), as low as 2 cm, and provided superior accuracy in both in-distribution (ID) and out-of-distribution (OOD) evaluations., Comment: 11 pages, 5 figures, 1 table

The CIELO project introduces a novel set of chemo-dynamical zoom-in simulations designed to simultaneously resolve galaxies and their nearby environments. The initial conditions include a diverse range of cosmic structures, such as local groups, filaments, voids, and walls, allowing for a detailed exploration of galaxies within the broader context of the cosmic web. This study presents the initial conditions and characterizes the global properties of CIELO galaxies and their environments. It focuses on galaxies with stellar masses ranging from log [8,11] solar masses and examines key scaling relations, including the mass-size relation, the Tully-Fisher relation, and the mass-metallicity relation for both stars and star-forming gas. The DisPerSe algorithm was used to determine the positions of CIELO galaxies within the cosmic web, with a specific focus on the Pehuen haloes. The selection of local group volumes was guided by criteria based on the relative positions and velocities of the two primary galaxies. The Pehuen regions were chosen to map walls, filaments, and voids. Synthetic images in the SDSS i, r, and g bands were generated using the SKIRT radiative transfer code. Additionally, a dynamical decomposition was performed to classify galaxy morphologies into bulge, disc, and stellar halo components (abridged)., Comment: 13 pages, 12 figures, submitted. Comments are welcomed

We present a study of the size growth of the red sequence between $0.510$, whereas half-mass radii are derived from the F444W profiles together with the F277W-F444W color-$M_*$/L relation. We investigate the dependence of the ratio $r_{e, \mathrm{mass}}/r_{e, \mathrm{light}}$ on redshift, stellar mass, and the wavelength used to measure $r_{e, \mathrm{light}}$, also separating the sample into younger and older quiescent galaxies. Our data demonstrate that rest-frame infrared sizes accurately trace mass-weighted sizes while sizes measured at rest-frame optical wavelengths (0.5-0.7$\mu$m) are 0.1-0.2 dex larger, with only minor variations in redshift. We find that the average size of young quiescent galaxies agrees with that of old quiescent galaxies at intermediate masses, $10<$log($M_*/M_{\odot}$)$<11$, within their respective uncertainties in all observed-frame half-light, rest-frame half-light and half-mass radius measurements. At face value, our results point to a combination of progenitor bias and minor mergers driving the size growth of intermediate-mass quiescent galaxies at $0.5

We study the effects of the inclusion of fluids In bounce scenarios driven by an exponential potential scalar field. Most solutions exhibit well known tracking behavior between the fluids and the scalar field. This tracking behavior can model transitions between different phases of cosmic evolution. We will focus on an interesting bouncing model with a dust matter fluid, where the scalar field can drive an early dark energy expanding period with a radiation-like dominated phase just after it, and then tracks the dust matter fluid with energy density compatible with the dark matter energy density. The model is dust dominated in the far past of the contracting phase, and has stiff matter behavior when approaching the singularity, allowing well known quantum bounce transitions to the expanding era. Hence, it is a quantum matter bounce scenario with an inflationary phase together with a smooth transition through a radiation era to matter domination with a possible scalar field dark matter candidate., Comment: 11 pages, 11 figures. Submitted to Physics of the Dark Universe

The James Webb Space Telescope (JWST) is unveiling the rest-frame near-IR structure of galaxies. We measure the evolution with redshift of the rest-frame optical and near-IR S\'ersic index ($n$), and examine the dependence on stellar mass and star-formation activity across the redshift range $0.5\leq z\leq2.5$. We infer rest-frame near-IR S\'ersic profiles for $\approx 15.000$ galaxies in publicly available NIRCam imaging mosaics from the COSMOS-Web and PRIMER surveys. We augment these with rest-frame optical S\'ersic indices, previously measured from HST imaging mosaics. The median S\'ersic index evolves slowly or not at all with redshift, except for very high-mass galaxies ($M_\star > 10^{11}~{\text{M}}_\odot$), which show an increase from $n\approx 2.5$ to $n\approx 4$ at $z<1$. High-mass galaxies have higher $n$ than lower-mass galaxies ($M_\star=10^{9.5}~{\text{M}}_\odot$) at all redshifts, with a stronger dependence in the rest-frame near-IR than in the rest-frame optical at $z>1$. This wavelength dependence is caused by star-forming galaxies that have lower optical than near-IR $n$ at z>1 (but not at z<1). Both at optical and near-IR wavelengths, star-forming galaxies have lower $n$ than quiescent galaxies, fortifying the connection between star-formation activity and radial stellar mass distribution. At $z>1$ the median near-IR $n$ varies strongly with star formation activity, but not with stellar mass. The scatter in near-IR $n$ is higher in the green valley (0.25 dex) than on the star-forming sequence and among quiescent galaxies (0.18 dex) -- this trend is not seen in the optical because dust and young stars contribute to the variety in optical light profiles. Our newly measured rest-frame near-IR radial light profiles motivate future comparisons with radial stellar mass profiles of simulated galaxies as a stringent constraint on processes that govern galaxy formation., Comment: Accepted for publication on A&A

Most observed exoplanets have high equilibrium temperatures. Understanding the chemistry of their atmospheres and interpreting their observations requires the use of chemical kinetic models including photochemistry. The thermal dependence of the vacuum ultraviolet (VUV) absorption cross sections of molecules used in these models is poorly known at high temperatures, leading to uncertainties in the resulting abundance profiles. The aim of our work is to study experimentally the thermal dependence of VUV absorption cross sections of molecules of interest for exoplanet atmospheres and provide accurate data for use in atmospheric models. This study focuses on acetylene (C2H2). We measured absorption cross sections of C2H2 at seven temperatures ranging from 296 to 773 K recorded in the 115-230 nm spectral domain using VUV spectroscopy and synchrotron radiation. These data were used in our 1D thermo-photochemical model, to assess their impact on the predicted composition of a generic hot Jupiter-like exoplanet atmosphere. The absolute absorption cross sections of C2H2 increase with temperature. This increase is relatively constant from 115 to 185 nm and rises sharply from 185 to 230 nm. The abundance profile of C2H2 calculated using the model shows a slight variation, with a maximum decrease of 40% near 5 x 10-5 bar, when using C2H2 absorption cross sections measured at 773 K compared to those at 296 K. This is explained by the absorption, higher in the atmosphere, of the actinic flux from 150 to 230 nm due to the increase in the C2H2 absorption in this spectral range. This change also impacts the abundance profiles of other by-products such as methane (CH4) and ethylene (C2H4). We present the first experimental measurements of the VUV absorption cross sections of C2H2 at high temperatures. Similar studies of other major species are needed to improve our understanding of exoplanet atmospheres., Comment: 12 pages, 1 table, 11 figures

Machine learning (ML) and deep learning (DL) techniques have been widely applied to analyze electroencephalography (EEG) signals for disease diagnosis and brain-computer interfaces (BCI). The integration of multimodal data has been shown to enhance the accuracy of ML and DL models. Combining EEG with other modalities can improve clinical decision-making by addressing complex tasks in clinical populations. This systematic literature review explores the use of multimodal EEG data in ML and DL models for clinical applications. A comprehensive search was conducted across PubMed, Web of Science, and Google Scholar, yielding 16 relevant studies after three rounds of filtering. These studies demonstrate the application of multimodal EEG data in addressing clinical challenges, including neuropsychiatric disorders, neurological conditions (e.g., seizure detection), neurodevelopmental disorders (e.g., autism spectrum disorder), and sleep stage classification. Data fusion occurred at three levels: signal, feature, and decision levels. The most commonly used ML models were support vector machines (SVM) and decision trees. Notably, 11 out of the 16 studies reported improvements in model accuracy with multimodal EEG data. This review highlights the potential of multimodal EEG-based ML models in enhancing clinical diagnostics and problem-solving., Comment: This paper includes 4 figures, 6 tables, and totals 18 pages

In a recent study [Rev. Bras. Ens. F\'is. vol. 45, 2023], the absence of the Cognitive Theory of Multimedia Learning (CTML) in the curricula of Physics teacher education programs at Brazilian public universities was highlighted. Considering this gap, the present study investigates whether, even without any formal prior knowledge of CTML principles (Coherence, Signaling, Spatial Contiguity, Segmentation, Multimedia, and Personalization), Physics teacher trainees and educators tend to choose, among two formats of multimedia materials - one aligned with a given CTML principle and the other not - the materials aligned with these principles. The findings of this case study revealed that, although most participants generally selected materials aligned with the mentioned principles, a significant portion did not. These results underscore the importance of Brazilian universities considering the inclusion of CTML in Physics teacher education curricula., Comment: 24 pages, 7 figures

Machine learning models offer powerful predictive capabilities but often lack transparency. Local Interpretable Model-agnostic Explanations (LIME) addresses this by perturbing features and measuring their impact on a model's output. In text-based tasks, LIME typically removes present words (bits set to 1) to identify high-impact tokens. We propose \textbf{Q-LIME $\pi$} (Quantum LIME $\pi$), a quantum-inspired extension of LIME that encodes a binary feature vector in a quantum state, leveraging superposition and interference to explore local neighborhoods more efficiently. Our method focuses on flipping bits from $1 \rightarrow 0$ to emulate LIME's ``removal'' strategy, and can be extended to $0 \rightarrow 1$ where adding features is relevant. Experiments on subsets of the IMDb dataset demonstrate that Q-LIME $\pi$ often achieves near-identical top-feature rankings compared to classical LIME while exhibiting lower runtime in small- to moderate-dimensional feature spaces. This quantum-classical hybrid approach thus provides a new pathway for interpretable AI, suggesting that, with further improvements in quantum hardware and methods, quantum parallelism may facilitate more efficient local explanations for high-dimensional data.

The Mekong Delta Region of Vietnam faces increasing dengue risks driven by urbanization, globalization, and climate change. This study introduces a probabilistic forecasting model for predicting dengue incidence and outbreaks with one to three month lead times, integrating meteorological, sociodemographic, preventive, and epidemiological data. Seventy-two models were evaluated, and an ensemble combining top-performing spatiotemporal, supervised PCA, and semi-mechanistic hhh4 frameworks was developed. Using data from 2004-2022 for training, validation, and evaluation, the ensemble model demonstrated 69% accuracy at a 3-month horizon, outperforming a baseline model. While effective, its performance declined in years with atypical seasonality, such as 2019 and 2022. The model provides critical lead time for targeted dengue prevention and control measures, addressing a growing public health need in the region., Comment: 34 pages, 6 figures

From a spectroscopic survey of candidate H II regions in the Andromeda galaxy (M31) with MMT/Hectospec, we have identified 294 H II regions using emission line ratios and calculated elemental abundances from strong-line diagnostics (values ranging from sub-solar to super-solar) producing both Oxygen and Nitrogen radial abundance gradients. The Oxygen gradient is relatively flat, while the Nitrogen gradient is significantly steeper, indicating a higher N/O ratio in M31's inner regions, consistent with recent simulations of galaxy chemical evolution. No strong evidence was found of systematic galaxy-scale trends beyond the radial gradient. After subtracting the radial gradient from abundance values, we find an apparently stochastic and statistically significant scatter of standard deviation 0.06 dex, which exceeds measurement uncertainties. One explanation includes a possible collision with M32 200 - 800 Myrs ago. Using the two-point correlation function of the Oxygen abundance, we find that, similar to other spiral galaxies, M31 is well-mixed on sub-kpc scales but less so on larger (kpc) scales, which could be a result of an exponential decrease in mixing speed with spatial scale, and the aforementioned recent merger. Finally, the MMT spectroscopy is complemented by a dust continuum and CO survey of individual Giant Molecular Clouds, conducted with the Submillimeter Array. By combining the MMT and SMA observations, we obtain a unique direct test of the Oxygen abundance dependence of the $\alpha^{\prime}(^{12}\mathrm{CO})$ factor which is crucial to convert CO emission to dust mass. Our results suggest that within our sample there is no trend of the $\alpha^{\prime}(^{12}\mathrm{CO})$ with Oxygen abundance., Comment: MNRAS, in press

In pharmacoepidemiology, safety and effectiveness are frequently evaluated using readily available administrative and electronic health records data. In these settings, detailed confounder data are often not available in all data sources and therefore missing on a subset of individuals. Multiple imputation (MI) and inverse-probability weighting (IPW) are go-to analytical methods to handle missing data and are dominant in the biomedical literature. Doubly-robust methods, which are consistent under fewer assumptions, can be more efficient with respect to mean-squared error. We discuss two practical-to-implement doubly-robust estimators, generalized raking and inverse probability-weighted targeted maximum likelihood estimation (TMLE), which are both currently under-utilized in biomedical studies. We compare their performance to IPW and MI in a detailed numerical study for a variety of synthetic data-generating and missingness scenarios, including scenarios with rare outcomes and a high missingness proportion. Further, we consider plasmode simulation studies that emulate the complex data structure of a large electronic health records cohort in order to compare anti-depressant therapies in a rare-outcome setting where a key confounder is prone to more than 50\% missingness. We provide guidance on selecting a missing data analysis approach, based on which methods excelled with respect to the bias-variance trade-off across the different scenarios studied., Comment: 142 pages (27 main, 115 supplemental); 6 figures, 2 tables

Future wireless communication systems are envisioned to support ultra-reliable and low-latency communication (URLLC), which will enable new applications such as compute offloading, wireless real-time control, and reliable monitoring. Distributed multiple-input multiple-output (D-MIMO) is one of the most promising technologies for delivering URLLC. This paper classifies obstruction and derives a channel model from a D-MIMO measurement campaign carried out at a carrier frequency of 3.75 GHz with a bandwidth of 35 MHz using twelve distributed fully coherent dipole antennas in an industrial environment. Channel characteristics are investigated, including statistical measures such as small-scale fading, large-scale fading, delay spread, and transition rates between line-of-sight and obstructed line-of-sight conditions for the different antenna elements, laying the foundations for an accurate channel model for D-MIMO systems in industrial environments. Furthermore, correlations of large-scale fading between antennas, spatial correlation, and tail distributions are included to enable proper evaluations of reliability and rare events. Based on the results, a channel model for D-MIMO in industrial environments is presented together with a recipe for its implementation., Comment: 10 double column pages, 14 figures, Submitted to Transactions on Wireless Communications

Cross-assignment of directional wave spectra is a critical task in wave data assimilation. Traditionally, most methods rely on two-parameter spectral distances or energy ranking approaches, which often fail to account for the complexities of the wave field, leading to inaccuracies. To address these limitations, we propose the Controlled Four-Parameter Method (C4PM), which independently considers four integrated wave parameters. This method enhances the accuracy and robustness of cross-assignment by offering flexibility in assigning weights and controls to each wave parameter. We compare C4PM with a two-parameter spectral distance method using data from two buoys moored 13 km apart in deep water. Although both methods produce negligible bias and high correlation, C4PM demonstrates superior performance by preventing the occurrence of outliers and achieving a lower root mean square error across all parameters. The negligible computational cost and customization make C4PM a valuable tool for wave data assimilation, improving the reliability of forecasts and model validations.

We extend the theory of topological recursion by considering Airy structures whose partition functions are highest weight vectors of particular $\mathcal{W}$-algebra representations. Such highest weight vectors arise as partition functions of Airy structures only under certain conditions on the representations. In the spectral curve formulation of topological recursion, we show that this generalization amounts to adding specific terms to the correlators $ \omega_{g,1}$, which leads to a ``shifted topological recursion'' formula. We then prove that the wave-functions constructed from this shifted version of topological recursion are WKB solutions of families of quantizations of the spectral curve with $ \hbar$-dependent terms. In the reverse direction, starting from an $\hbar$-connection, we find that it is of topological type if the exact same conditions that we found for the Airy structures are satisfied. When this happens, the resulting shifted loop equations can be solved by the shifted topological recursion obtained earlier., Comment: 49 pages, 1 figure

The prevalence of unhealthy eating habits has become an increasingly concerning issue in the United States. However, major food recommendation platforms (e.g., Yelp) continue to prioritize users' dietary preferences over the healthiness of their choices. Although efforts have been made to develop health-aware food recommendation systems, the personalization of such systems based on users' specific health conditions remains under-explored. In addition, few research focus on the interpretability of these systems, which hinders users from assessing the reliability of recommendations and impedes the practical deployment of these systems. In response to this gap, we first establish two large-scale personalized health-aware food recommendation benchmarks at the first attempt. We then develop a novel framework, Multi-Objective Personalized Interpretable Health-aware Food Recommendation System (MOPI-HFRS), which provides food recommendations by jointly optimizing the three objectives: user preference, personalized healthiness and nutritional diversity, along with an large language model (LLM)-enhanced reasoning module to promote healthy dietary knowledge through the interpretation of recommended results. Specifically, this holistic graph learning framework first utilizes two structure learning and a structure pooling modules to leverage both descriptive features and health data. Then it employs Pareto optimization to achieve designed multi-facet objectives. Finally, to further promote the healthy dietary knowledge and awareness, we exploit an LLM by utilizing knowledge-infusion, prompting the LLMs with knowledge obtained from the recommendation model for interpretation.

Modern power grids are evolving to become more interconnected, include more electric vehicles (EVs), and utilize more renewable energy sources (RES). Increased interconnectivity provides an opportunity to manage EVs and RES by using price signaling to shift EV loads towards periods of high RES output. This work uses ERCOT's 2035 RES installation plans and projections for Texas's EV fleet to examine and compare how both open-loop control and model predictive control (MPC) schemes can leverage time varying rates for EV charging to utilize excess RES supply that may otherwise be underutilized in a highly weather-dependent grid. The results show that while open-loop control increases RES usage, MPC increases RES usage even further by responding to RES outputs that differ from forecasts due to the inherent uncertainty of weather predictions. If MPC is used with time steps that are too frequent, however, difficulties arise; EV owners may find it too onerous to keep up with changing price structures, and frequent over-corrections to charging profiles can lead to a ``rebound peak" phenomenon. Therefore, control schemes should balance maximizing RES usage with ensuring customer participation.

As extreme weather events become more common and threaten power grids, the continuing adoption of electric vehicles (EVs) introduces a growing opportunity for their use as a distributed energy storage resource. This energy storage can be used as backup generation through the use of vehicle-to-grid (V2G) technology, where electricity is sent back from EV batteries to the grid. With enough participation from EV owners, V2G can mitigate outages during grid emergencies. In order to investigate a practical application of V2G, this study leverages a vast array of real-world data, such as survey results on V2G participation willingness, historical outage data within ERCOT, current EV registrations, and demographic data. This data informs realistic emergency grid scenarios with V2G support using a synthetic transmission grid for Travis County. The results find that as EV ownership rises in the coming years, the simultaneous facilitation of bidirectional charging availability would allow for V2G to play a substantial role in preventing involuntary load shed as a result of emergencies like winter storms.

We study the rest-frame optical and ultraviolet morphology of galaxies in the first billion years of the Universe. Using JWST data from the UNCOVER and MegaScience surveys targeting the lensing cluster Abell 2744 we present multi-band morphological measurements for a sample of 995 galaxies selected using 20-band NIRCam photometry and 35 using NIRSpec Prism spectroscopy over the redshift range of $4

Low carrier densities in topological semimetals (TSMs) enable the exploration of novel magnetotransport in the quantum limit (QL). Reports consistent with 3D quasi-quantum Hall effect (QQHE) have repositioned TSMs as promising platforms for exploring 3D quantum Hall transport, but the lack of tunability in the Fermi has thus far limited the ability to control the QQHE signal. Here, we tune the defect concentrations in the Dirac semimetal Cd${}_3$As${}_2$ to achieve ultra-low carrier concentrations at 2 K around $2.9\times10^{16}$cm${}^{-3}$, giving way to QQHE signal at modest fields under 10 T. At low carrier densities, where QQHE is most accessible, we find that a zero resistivity state is obscured by a carrier density dependent background originating from Coulomb disorder from charged point defects. Our results highlight the interplay between QQHE and Coulomb disorder scattering, demonstrating that clear observation of QQHE in TSMs intricately depends on Fermi level. Predicted in TSMs a decade ago, we find that Coulomb disorder is an essential ingredient for understanding the magnetoresistivity for a spectrum of Fermi levels, experimentally anchoring the important roles of defects and charged disorder in TSM applications. We discuss future constraints and opportunities in exploring 3D QHE in TSMs.

We report on a search for millicharged particles (mCPs) produced in cosmic ray proton atmospheric interactions using data collected during the first science run of the LUX-ZEPLIN experiment. The mCPs produced by two processes -- meson decay and proton bremsstrahlung -- are considered in this study. This search utilized a novel signature unique to liquid xenon (LXe) time projection chambers (TPCs), allowing sensitivity to mCPs with masses ranging from 10 to 1000 MeV/c$^2$ and fractional charges between 0.001 and 0.02 of the electron charge e. With an exposure of 60 live days and a 5.5 tonne fiducial mass, we observed no significant excess over background. This represents the first experimental search for atmospheric mCPs and the first search for mCPs using an underground LXe experiment.

We present a detailed exploration of the most optically-luminous Little Red Dot ($L_{H\alpha}=10^{44}$erg/s, $L_V=10^{45}$erg/s, F444W=22AB) found to date. Located in the Abell 2744 field, source A744-45924 was observed by NIRSpec/PRISM with ultradeep spectroscopy reaching SNR$\sim$100pix$^{-1}$, high-resolution 3-4 micron NIRCam/Grism spectroscopy, and NIRCam Medium Band imaging. The NIRCam spectra reveal high rest-frame EW $W_{H\alpha,0,broad}>800$\r{A}, broad H$\alpha$ emission (FWHM$\sim$4500 km/s), on top of narrow, complex absorption. NIRSpec data show exceptionally strong rest-frame UV to NIR Fe II emission ($W_{FeII-UV,0}\sim$340\r{A}), N IV]$\lambda\lambda$1483,1486 and N III]$\lambda$1750, and broad NIR O I $\lambda$8446 emission. The spectra unambiguously demonstrate a broad-line region associated with an inferred $M_{BH}\sim10^9M_\odot$ supermassive black hole embedded in dense gas, which might explain a non-detection in ultradeep Chandra X-ray data (>$10\times$ underluminous relative to broad $L_{H\alpha}$). Strong UV Nitrogen lines suggest supersolar N/O ratios due to rapid star formation or intense radiation near the AGN. The continuum shows a clear Balmer break at rest-frame 3650\r{A}, which cannot be accounted for by an AGN power-law alone. A stellar population model produces an excellent fit with a reddened Balmer break and implying a massive ($M_*\sim8\times10^{10}M_\odot$), old $\sim$500 Myr, compact stellar core, among the densest stellar systems known ($\rho\sim3\times10^6M_\odot$/pc$^2$ for $R_{e,opt}=70\pm10$ pc), and AGN emission with extreme intrinsic EW $W_{H\alpha,0}\gg$1000\r{A}. However, although high $M_*$ and $M_{BH}$ are supported by evidence of an overdensity containing 40 galaxies at $z=4.41-4.51$, deep high-resolution spectroscopy is required to confirm stellar absorption and rule out that dense gas around the AGN causes the Balmer break instead., Comment: 28 pages,10 figures, submitted to ApJ

votess is a library for computing parallel 3D Voronoi tessellations on heterogeneous platforms, from CPUs and GPUs, to future accelerator architectures. To do so, it leverages the SYCL abstraction layer to achieve portability and performance across these architectures. The core library is an implementation of a Voronoi cell-by-cell computation algorithm, producing the geometry of the cells and their neighbor connectivity information, rather than a full combinatorial mesh data structure. This simplifies the Voronoi tessellation and makes it more suitable to data parallel architectures than alternatives such as sequential insertion or the Bowyer-Watson algorithm. The library demonstrates significant performance improvements over established single-threaded programs and serves as a foundational tool for performance-critical applications, such as on-the-fly computations in hydrodynamical codes., Comment: submitted to Journal of Open Source Software; open-source development at https://github.com/samridh-dev/votess.git; Comment: fixed author typo

Swirl-shaped flow structures have been observed throughout the solar atmosphere, in both emission and absorption, at different altitudes and locations, and are believed to be associated with magnetic structures. However, the distribution patterns of such swirls, especially their spatial positions, remain unclear. Using the Automated Swirl Detection Algorithm (ASDA), we identified swirls from the high-resolution photospheric observations, centered on Fe I 630.25 nm, of a quiet region near the Sun's central meridian by the Swedish 1-m Solar Telescope. Through a detailed study of the locations of the detected small-scale swirls with an average radius of $\sim$300 km, we found that most of them are located in lanes between mesogranules (which have an average diameter of $\sim$5.4 Mm) instead of the commonly believed intergranular lanes. The squared rotation, expansion/contraction, vector speeds, and proxy kinetic energy are all found to follow Gaussian distributions. Their rotation speed, expansion/contraction speed, and circulation are positively correlated with their radius. These results suggest that photospheric swirls at different scales and locations across the observational 56.5" $\times$ 57.5" field-of-view (FOV) could share the same triggering mechanism at preferred spatial and energy scales. A comparison with previous work suggests that the number of photospheric swirls is positively correlated with the number of local magnetic concentrations, stressing the close relation between swirls and local magnetic concentrations:the number of swirls should positively correlate with the number and strength of local magnetic concentrations., Comment: Accepted for publication in the Astrophysical Journal. 13 pages, 10 figures, 1 table

Geometry and topology play a fundamental role in determining pattern formation on 2D surfaces in condensed matter physics. For example, local positive Gaussian curvature of a 2D surface attracts positive topological defects in a liquid crystal phase confined to the curved surface while repelling negative topological defects. Although the cone geometry is flat on the flanks, the concentrated Gaussian curvature at the cone apex geometrically frustrates liquid crystal orientational fields arbitrarily far away. The apex acts as an unquantized pseudo-defect interacting with the topological defects on the flank. By exploiting the conformal mapping methods of F. Vafa et al., we explore a simple theoretical framework to understand the ground states of liquid crystals with $p$-fold rotational symmetry on cones, and uncover important finite size effects for the ground states with boundary conditions that confine both plus and minus defects to the cone flanks. By combining the theory and simulations, we present new results for liquid crystal ground states on cones with anti-twist boundary conditions at the cone base, which enforce a total topological charge of $-1$. We find that additional quantized negative defects are created on the flank as the cone apex becomes sharper via a defect unbinding process, such that an equivalent number of quantized positive defects become trapped at the apex, thus partially screening the apex charge, whose magnitude is a continuous function of cone angle.

Model finding, as embodied by SAT solvers and similar tools, is used widely, both in embedding settings and as a tool in its own right. For instance, tools like Alloy target SAT to enable users to incrementally define, explore, verify, and diagnose sophisticated specifications for a large number of complex systems. These tools critically include a visualizer that lets users graphically explore these generated models. As we show, however, default visualizers, which know nothing about the domain, are unhelpful and even actively violate presentational and cognitive principles. At the other extreme, full-blown visualizations require significant effort as well as knowledge a specifier might not possess; they can also exhibit bad failure modes (including silent failure). Instead, we need a language to capture essential domain information for lightweight diagramming. We ground our language design in both the cognitive science literature on diagrams and on a large number of example custom visualizations. This identifies the key elements of lightweight diagrams. We distill these into a small set of orthogonal primitives. We extend an Alloy-like tool to support these primitives. We evaluate the effectiveness of the produced diagrams, finding them good for reasoning. We then compare this against many other drawing languages and tools to show that this work defines a new niche that is lightweight, effective, and driven by sound principles.

Interfaces between twisted 2D materials host a wealth of physical phenomena originating from the long-scale periodicity associated with the resulting moire structure. Besides twisting, an alternative route to create structures with comparably long or even longer periodicities is inducing a differential strain between adjacent layers in a van der Waals (vdW) material. Despite recent theoretical efforts analyzing its benefits, this route has not yet been implemented experimentally. Here we report evidence for the simultaneous presence of ferromagnetic and antiferromagnetic regions in CrBr3 _a hallmark of moire magnetism_ from the observation of an unexpected magnetoconductance in CrBr3 tunnel barriers with ferromagnetic Fe3GeTe2 and graphene electrodes. The observed magnetoconductance evolves with temperature and magnetic field as the magnetoconductance measured in small angle CrBr3 twisted junctions, in which moire magnetism occurs. Consistent with Raman measurements and theoretical modeling, we attribute the phenomenon to the presence of a differential strain in the CrBr3 multilayer, which locally modifies the stacking and the interlayer exchange between adjacent CrBr3 layers, resulting in spatially modulated spin textures. Our conclusions indicate that inducing differential strain in vdW multilayers is a viable strategy to create moire-like superlattices, which in the future may offer in-situ continuous tunability even at low temperatures.

We consider the problem of finding a minimum cut of a weighted graph presented as a single-pass stream. While graph sparsification in streams has been intensively studied, the specific application of finding minimum cuts in streams is less well-studied. To this end, we show upper and lower bounds on minimum cut problems in insertion-only streams for a variety of settings, including for both randomized and deterministic algorithms, for both arbitrary and random order streams, and for both approximate and exact algorithms. One of our main results is an $\widetilde{O}(n/\varepsilon)$ space algorithm with fast update time for approximating a spectral cut query with high probability on a stream given in an arbitrary order. Our result breaks the $\Omega(n/\varepsilon^2)$ space lower bound required of a sparsifier that approximates all cuts simultaneously. Using this result, we provide streaming algorithms with near optimal space of $\widetilde{O}(n/\varepsilon)$ for minimum cut and approximate all-pairs effective resistances, with matching space lower-bounds. The amortized update time of our algorithms is $\widetilde{O}(1)$, provided that the number of edges in the input graph is at least $(n/\varepsilon^2)^{1+o(1)}$. We also give a generic way of incorporating sketching into a recursive contraction algorithm to improve the post-processing time of our algorithms. In addition to these results, we give a random-order streaming algorithm that computes the {\it exact} minimum cut on a simple, unweighted graph using $\widetilde{O}(n)$ space. Finally, we give an $\Omega(n/\varepsilon^2)$ space lower bound for deterministic minimum cut algorithms which matches the best-known upper bound up to polylogarithmic factors., Comment: 25+3 pages, 2 figures. Accepted to ITCS 2025. v2: minor updates to author information

In condensed matter systems, interactions between collective modes offer avenues for nonlinear coherent manipulation of coupled excitations and quantum phases. Antiferromagnets, with their inherently coupled magnon modes, provide a promising platform for nonlinear control of microscopic spin waves and macroscopic magnetization. However, nonlinear magnon-magnon interactions have been only partially elaborated, leaving key gaps in the prospects for potential ultrahigh-bandwidth magnonic signal processing. Here, we use a pair of intense terahertz pulses to sequentially excite two distinct coherent magnon modes in an antiferromagnet and find that the magnon mode with a lower frequency undergoes amplification when the higher-frequency mode is driven. We unveil the nonlinear excitation pathways of this stimulated parametric downconversion process by using polarization-selective two-dimensional terahertz spectroscopy. Our work provides fundamental insights into nonlinear magnonics in antiferromagnets, laying the groundwork for forthcoming spintronic and magnonic devices based on nonlinear magnon-magnon interactions.

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired by biological active systems, various types of autonomous synthetic nano- and micromachines have been designed, which provide the basis for multifunctional, highly responsive, intelligent active materials. A major challenge for understanding and designing active matter is their inherent non-equilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Furthermore, interactions in ensembles of active agents are often non-additive and non-reciprocal. An important aspect of biological agents is their ability to sense the environment, process this information, and adjust their motion accordingly. It is an important goal for the engineering of micro-robotic systems to achieve similar functionality. With many fundamental properties of motile active matter now reasonably well understood and under control, the ground is prepared for the study of physical aspects and mechanisms of motion in complex environments, of the behavior of systems with new physical features like chirality, of the development of novel micromachines and microbots, of the emergent collective behavior and swarming of intelligent self-propelled particles, and of particular features of microbial systems. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter poses major challenges, which can only be addressed by a truly interdisciplinary effort involving scientists from biology, chemistry, ecology, engineering, mathematics, and physics.

On May 24th, 2023, the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), joined by the Advanced Virgo and KAGRA detectors, began the fourth observing run for a two-year-long dedicated search for gravitational waves. The LIGO Hanford and Livingston detectors have achieved an unprecedented sensitivity to gravitational waves, with an angle-averaged median range to binary neutron star mergers of 152 Mpc and 160 Mpc, and duty cycles of 65.0% and 71.2%, respectively, with a coincident duty cycle of 52.6%. The maximum range achieved by the LIGO Hanford detector is 165 Mpc and the LIGO Livingston detector 177 Mpc, both achieved during the second part of the fourth observing run. For the fourth run, the quantum-limited sensitivity of the detectors was increased significantly due to the higher intracavity power from laser system upgrades and replacement of core optics, and from the addition of a 300 m filter cavity to provide the squeezed light with a frequency-dependent squeezing angle, part of the A+ upgrade program. Altogether, the A+ upgrades led to reduced detector-wide losses for the squeezed vacuum states of light which, alongside the filter cavity, enabled broadband quantum noise reduction of up to 5.2 dB at the Hanford observatory and 6.1 dB at the Livingston observatory. Improvements to sensors and actuators as well as significant controls commissioning increased low frequency sensitivity. This paper details these instrumental upgrades, analyzes the noise sources that limit detector sensitivity, and describes the commissioning challenges of the fourth observing run., Comment: 26 pages, 18 figures

We report the discovery of five galaxy candidates at redshifts between $15.9

Understanding the complex ground state of van der Waals (vdW) magnets is essential for designing new materials and devices that leverage these platforms. Here, we investigate a two-dimensional vdW ferromagnet -- Fe$_5$GeTe$_2$-- with one of the highest reported Curie temperatures, to elucidate its magnetic excitations and charge order. Using Fe $L_3 - $edge resonant inelastic x-ray scattering, we find the dual character of magnetic excitations, consisting of a coherent magnon and a continuum, similar to what is reported for its sister compound Fe$_3$GeTe$_2$. The magnon has an energy of $\approx$ 36 meV at the maximum in-plane momentum transfer ($-$0.35 r.l.u.) allowed at Fe $L_3 - $edge. A broad and non-dispersive continuum extends up to 150 meV, 50$\%$ higher energy than in Fe$_3$GeTe$_2$. Its intensity is sinusoidally modulated along the $L$ direction, with a period matching the inter-slab distance. Our findings suggest that while the unconventional dual character of magnetic excitations is generic to ternary Fe-Ge-Te vdW magnets, the correlation length of the out-of-plane magnetic interaction increases in Fe$_5$GeTe$_2$ as compared to Fe$_3$GeTe$_2$, supporting a stronger three-dimensional character for the former. Furthermore, by investigating the $\pm$(1/3, 1/3, $L$) peaks by resonant x-ray diffraction, we conclude these to have structural origin rather than charge order -- as previously reported -- and suggest doubling of the structural unit cell along the $c-$axis., Comment: 17 pages, 3 figures