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To develop a deeper understanding of who Child Care and Early Education (CCEE) educators are--and what influences impact the entry, retention, turnover, and advancement (that is, the workforce dynamics) in this industry--the Building and Sustaining the Child Care and Early Education Workforce (BASE) research team identified and documented existing literature about the CCEE workforce and strategies that are intended to strengthen it. The team conducted a literature review (among several other research activities) to identify, review, and synthesize relevant literature and the evidence base on both multilevel influences that may shape CCEE workforce dynamics and the effectiveness of strategies that aim to build a sustained, qualified CCEE workforce. The team also conducted an environmental scan--a review to identify strategies currently being implemented to build, advance, and sustain the CCEE workforce. This annotated bibliography contains a comprehensive list of the publications that were formally included in the literature review to provide researchers, practitioners, and policymakers with a quick guide to understanding the recent research landscape of the CCEE workforce. This annotated bibliography details the methods that were used to review the published literature and summarizes elements of the publications.

Child care and early education (CCEE) are essential resources for families and children across the country. Yet qualified educators are choosing to leave their positions, and young professionals are choosing not to enter the field. This instability has been a long-lasting issue and is thought to be driven largely by structural and systemic forces that shape the everyday experiences of the CCEE workforce. These issues have been exacerbated by the COVID-19 pandemic. This report lays out a conceptual framework to serve as a guide for researchers, policymakers, and administrators who are conducting research on the CCEE workforce and who are designing and implementing strategies to improve entry, retention, turnover, and advancement of the workforce. This report is also intended to inform how the field can work to build and sustain this critical workforce. The conceptual framework consists of three main components that are intended to provide a clear understanding of factors that can disrupt the stability of the CCEE workforce pipeline. By articulating the main components, the conceptual framework encourages researchers, policymakers, and administrators to consider a range of multilevel influences on workforce dynamics when designing strategies and when evaluating whether strategies are working as intended. This framework also aims to underscore that the individuals who make up the workforce--many of whom have been marginalized due to race, ethnicity, social class, and gender--interact with broader social, political, and cultural contexts that shape economic and educational policies, structures, and opportunities.

We study synthetic temporal networks whose evolution is determined by stochastically evolving node variables - synthetic analogues of, e.g., temporal proximity networks of mobile agents. We quantify the long-timescale correlations of these evolving networks by an autocorrelative measure of edge persistence. Several distinct patterns of autocorrelation arise, including power-law decay and exponential decay, depending on the choice of node-variable dynamics and connection probability function. Our methods are also applicable in wider contexts; our temporal network models are tractable mathematically and in simulation, and our long-term memory quantification is analytically tractable and straightforwardly computable from temporal network data., Comment: 15 pages, 4 figures

The energy released by AGN has the potential to heat or remove the gas of the ISM, thus likely impacting the cold molecular gas reservoir of host galaxies at first, with star formation following on longer timescales. Previous works on high-z galaxies have yielded conflicting results, possibly due to selection biases and other systematics. To provide a reliable benchmark for galaxy evolution models at cosmic noon (z=1-3), two surveys were conceived: SUPER and KASHz, both targeting unbiased X-ray-selected AGN at z>1 that span a wide bolometric luminosity range. In this paper, we assess the effects of AGN feedback on the molecular gas content of host galaxies in a statistically robust, uniformly selected, coherently analyzed sample of AGN at z=1-2.6, drawn from the KASHz and SUPER surveys. By using ALMA data in combination with dedicated SED modeling, we retrieve CO and FIR luminosity as well as $M_*$ of SUPER and KASHz AGN. We selected non-active galaxies from PHIBBS, ASPECS and multiple ALMA/NOEMA surveys of sub-mm galaxies. By matching the samples in z, $M_*$ and $L_{FIR}$, we compared the properties of AGN and non-active galaxies within a Bayesian framework. We find that AGN hosts at given $L_{FIR}$ are on average CO depleted compared to non-active galaxies, confirming what was previously found in the SUPER survey. Moreover, the molecular gas fraction distributions of AGN and non-active galaxies are statistically different, with that of of AGN being skewed to lower values. Our results indicate that AGN can indeed reduce the total cold molecular gas reservoir of their host galaxies. Lastly, by comparing our results with predictions from three cosmological simulations (TNG, Eagle and Simba) filtered to match the observed properties, we confirm already known discrepancies and highlight new ones between observations and simulations.[Abridged], Comment: 26 pages (17 in the main body of the paper and 9 in the appendix), 14 figures (11 in the main body of the paper and 3 in the appendix), 8 tables (2 in the main body of the paper and 6 in the appendix). Accepted for publication in A&A, in press

Astrophysical simulations are computation, memory, and thus energy intensive, thereby requiring new hardware advances for progress. Stony Brook University recently expanded its computing cluster "SeaWulf" with an addition of 94 new nodes featuring Intel Sapphire Rapids Xeon Max series CPUs. We present a performance and power efficiency study of this hardware performed with FLASH: a multi-scale, multi-physics, adaptive mesh-based software instrument. We extend this study to compare performance to that of Stony Brook's Ookami testbed which features ARM-based A64FX-700 processors, and SeaWulf's AMD EPYC Milan and Intel Skylake nodes. Our application is a stellar explosion known as a thermonuclear (Type Ia) supernova and for this 3D problem, FLASH includes operators for hydrodynamics, gravity, and nuclear burning, in addition to routines for the material equation of state. We perform a strong-scaling study with a 220 GB problem size to explore both single- and multi-node performance. Our study explores the performance of different MPI mappings and the distribution of processors across nodes. From these tests, we determined the optimal configuration to balance runtime and energy consumption for our application., Comment: Accepted to PEARC '24 (Practice and Experience in Advanced Research Computing)

This Birds-of-a-Feather (BOF) session on 6 November 2023 was organized by leaders and members of SatHub at the International Astronomical Union Centre for the Protection of the Dark and Quiet Sky from Satellite Constellation Interference (IAU CPS). SatHub is dedicated to observations, data analysis, software, and related activities. The session opened with a talk on the current state of affairs with regards to satellite constellation mitigation, with a focus on optical astronomy, and moved to focused discussion around the top-voted topics. These included tools and techniques for forecasting satellite positions and brightnesses as well as streak detection and masking., Comment: 4 pages, 1 figure, conference proceeding from ADASS 2023

Suppose we are given two OCaml modules implementing the same signature. How do we check that they are observationally equivalent -- that is, that they behave the same on all inputs? One established technique is to use a property-based testing (PBT) tool such as QuickCheck. Currently, however, this can require significant amounts of boilerplate code and ad-hoc test harnesses. To address this issue, we present Mica, an automated tool for testing observational equivalence of OCaml modules. Mica is implemented as a PPX compiler extension, allowing users to supply minimal annotations to a module signature. These annotations guide Mica to automatically derive specialized PBT code that checks observational equivalence. We discuss the design of Mica and demonstrate its efficacy as a testing tool on various modules taken from real-world OCaml libraries., Comment: OCaml Workshop 2024

The LPC EFT workshop was held April 25-26, 2024 at the University of Notre Dame. The workshop was organized into five thematic sessions: "how far beyond linear" discusses issues of truncation and validity in interpretation of results with an eye towards practicality; "reconstruction-level results" visits the question of how best to design analyses directly targeting inference of EFT parameters; "logistics of combining likelihoods" addresses the challenges of bringing a diverse array of measurements into a cohesive whole; "unfolded results" tackles the question of designing fiducial measurements for later use in EFT interpretations, and the benefits and limitations of unfolding; and "building a sample library" addresses how best to generate simulation samples for use in data analysis. This document serves as a summary of presentations, subsequent discussions, and actionable items identified over the course of the workshop.

Random Number Generation Tasks (RNGTs) are used in psychology for examining how humans generate sequences devoid of predictable patterns. By adapting an existing human RNGT for an LLM-compatible environment, this preliminary study tests whether ChatGPT-3.5, a large language model (LLM) trained on human-generated text, exhibits human-like cognitive biases when generating random number sequences. Initial findings indicate that ChatGPT-3.5 more effectively avoids repetitive and sequential patterns compared to humans, with notably lower repeat frequencies and adjacent number frequencies. Continued research into different models, parameters, and prompting methodologies will deepen our understanding of how LLMs can more closely mimic human random generation behaviors, while also broadening their applications in cognitive and behavioral science research.

EuM2As2 (M = Zn, Cd, In, Sn etc.) is an excellent material system for studying topological properties, which can be easily tuned by magnetism involved. Theoretical calculations predict gapped and flat bands in EuZn2As2 but gapless structure in EuCd2As2. In this work, low-temperature (77 K) cleaved EuZn2As2 crystals are studied using scanning tunneling microscopy/spectroscopy (STM/S) and density functional theory (DFT) calculations. Defects-induced local density of states (LDOS) modification with a triangular shape helps identify the surface terminations: Eu versus AsZn surface. While large bandgaps (~1.5 eV at 77 K) are observed on both pristine surfaces, the bandgap width is found to be very sensitive to local heterogeneity, such as defects and step edges, with the tendency of reduction. Combining experimental data with DFT simulations, we conclude that the modified bandgap in the heterogeneous area arises from Zn vacancies and/or substitution by As atoms. Our investigation offers important information for reevaluating the electron topology of the EuM2As2 family., Comment: 17 pages, 4 figures

A biofilm is a microbial city. It consists of bacteria embedded in an extracellular polymeric substance (EPS) that functions as a protective barrier. Quorum sensing (QS) is a method of bacterial communication, where autoinducers (AIs) propagate via diffusion through the EPS and water channels within the biofilm. This diffusion process is anisotropic due to varying densities between the EPS and water channels. This study introduces a 2D anisotropic diffusion model for molecular communication (MC) within biofilms, analyzing information propagation between a point-to-point transmitter (TX) and receiver (RX) in bounded space. The channel impulse response is derived using Green's function for concentration (GFC) and is validated with particle-based simulation (PBS). The outcomes reveal similar results for both isotropic and anisotropic diffusion when the TX is centrally located due to symmetry. However, anisotropic conditions lead to greater diffusion peaks when the TX is positioned off-center. Additionally, the propagation of AIs is inversely proportional to both overall biofilm size and and diffusion coefficient values. It is hypothesized that anisotropic diffusion supports faster responses to hostile environmental changes because signals can propagate faster from the edge of the biofilm to the center.

We investigated the effect of 0.6 MeV proton irradiation on the superconducting and normal state properties of thin-film $\text{YBa}_{2}\text{Cu}_{3}\text{O}_{7-\delta}$ superconductors. A thin-film YBCO superconductor ($\approx$ 567 nm thick) was subject to a series of proton irradiations with a total fluence of $7.6\times10^{16}$ $\text{p/cm}^2$. Upon irradiation, $T_c$ was drastically decreased from 89.3 K towards zero with a corresponding increase in its normal state resistivity above $T_c$. This increase in resistivity which indicates the increase of defects inside the thin-film sample can be converted to the dimensionless scattering rate. We found that the relation between $T_c$ and dimensionless scattering rate obtained during proton irradiation approximates the generalized d-wave Abrikosov-Gor'kov theory better than the previous results obtained from electron irradiations. This is an unexpected result since the electron irradiation is known to be most effective to suppress superconductivity over other heavier ion irradiations such as proton irradiation. It suggests that the type of defects created by proton irradiation evolves from cascade defects (in bulk single crystals) to point-like defects (in thin-film single crystals) as the thickness decreases.

In designing an online A/B experiment, it is crucial to select a sample size and duration that ensure the resulting confidence interval (CI) for the treatment effect is the right width to detect an effect of meaningful magnitude with sufficient statistical power without wasting resources. While the relationship between sample size and CI width is well understood, the effect of experiment duration on CI width remains less clear. This paper provides an analytical formula for the width of a CI based on a ratio treatment effect estimator as a function of both sample size (N) and duration (T). The formula is derived from a mixed effects model with two variance components. One component, referred to as the temporal variance, persists over time for experiments where the same users are kept in the same experiment arm across different days. The remaining error variance component, by contrast, decays to zero as T gets large. The formula we derive introduces a key parameter that we call the user-specific temporal correlation (UTC), which quantifies the relative sizes of the two variance components and can be estimated from historical experiments. Higher UTC indicates a slower decay in CI width over time. On the other hand, when the UTC is 0 -- as for experiments where users shuffle in and out of the experiment across days -- the CI width decays at the standard parametric 1/T rate. We also study how access to pre-period data for the users in the experiment affects the CI width decay. We show our formula closely explains CI widths on real A/B experiments at YouTube.

Owens Valley Radio Observatory (OVRO) observations of supermassive black hole binary (SMBHB) candidate PKS~2131$-$021 revealed, for the first time, six likely characteristics of the phenomenology exhibited by SMBHB in blazars, of which the most unexpected and critical is sinusoidal flux density variations. We have now identified a second blazar, PKS~J0805$-$0111, showing significant sinusoidal variations, with an observed period that translates to $1.422 \pm 0.005$ yr in the rest frame of the $z = 1.388$ object. We generate $10^6$ simulated light curves to reproduce the radio variability characteristics of PKS~J0805$-$0111, and show that the global probability, considering the \textit{look-elsewhere effect}, indicates that the observed periodicity can be attributed to the red noise tail of the power spectral density, with a $p_0$ value of $7.8 \times 10^{-5}$ (i.e. 3.78$\sigma$). PKS J0805$-$0111 displays all six characteristics observed in PKS 2131$-$021. Taking into account the well-defined OVRO sample size, the false positive probability $\sim 0.22$, but the rare behavior makes this a strong SMBHB candidate. The discovery of a second SMBHB candidate exhibiting these rare characteristics reveals that PKS~2131$-$021 is not a unique, isolated case. With these two strong cases we are clearly seeing only the tip of the iceberg. We estimate that the number of SMBHB candidates amongst blazars $\sim$ 1 in 100.

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.

Outflows driven by active galactic nuclei (AGN) are seen in numerous compact sources; however, it has remained unclear how to distinguish between the driving mechanisms, such as winds and jets. Therefore, our study aims to offer observational insights from simulations to aid in this distinction. Specifically, in this paper, we investigate the evolution of wide-angled, moderately relativistic, magnetized winds and analyze their non-thermal radio emission and polarization properties. We find that the evolution of winds varies depending on factors such as power, density, and opening angle, which in turn influence their observable characteristics. Additionally, different viewing angles can lead to varying observations. Furthermore, we note distinctions in the evolution of winds compared to jets, resulting in disparities in their observable features. Jets typically exhibit a thin spine and hotspot(s). Winds manifest broader spines or an "hourglass-shaped" bright emission in the cocoon, which are capped by bright arcs. Both display high polarization coinciding with the bright spine and hotspots/arcs, although these regions are relatively compact and localized in jets when compared to winds. We emphasize the importance of high resolution, as we demonstrate that emission features from both jets and winds can become indistinguishable at lower resolutions. The distribution of polarization is largely unaffected by resolution, though lower polarization becomes more noticeable when the resolution is decreased., Comment: Accepted for publication in MNRAS

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

In analogy to the study of Scott rank/complexity of countable structures, we initiate the study of the Wadge degrees of the set of homeomorphic copies of topological spaces. One can view our results as saying that the classical characterizations of $[0,1]$ (e.g., as the unique continuum with exactly two non-cut points, and other similar characterizations), appropriated expressed, are the simplest possible characterizations of $[0,1]$. Formally, we show that the set of homeomorphic copies of $[0,1]$ is $\mathbf{\Pi}^0_4$-Wadge-complete. We also show that the set of homeomorphic copies of $S^1$ is $\mathbf{\Pi}^0_4$-Wadge-complete. On the other hand, we show that the set of homeomorphic copies of $\mathbb{R}$ is $\mathbf{\Pi}^1_1$-Wadge-complete. It is the local compactness that cannot be expressed in a Borel way; the set of homeomorphic copies of $\mathbb{R}$ is $\mathbf{\Pi}^0_4$-Wadge-complete within the locally compact spaces.

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 use of Large Language Models (LLMs) in medicine is growing, but their ability to handle both structured Electronic Health Record (EHR) data and unstructured clinical notes is not well-studied. This study benchmarks various models, including GPT-based LLMs, BERT-based models, and traditional clinical predictive models, for non-generative medical tasks utilizing renowned datasets. We assessed 14 language models (9 GPT-based and 5 BERT-based) and 7 traditional predictive models using the MIMIC dataset (ICU patient records) and the TJH dataset (early COVID-19 EHR data), focusing on tasks such as mortality and readmission prediction, disease hierarchy reconstruction, and biomedical sentence matching, comparing both zero-shot and finetuned performance. Results indicated that LLMs exhibited robust zero-shot predictive capabilities on structured EHR data when using well-designed prompting strategies, frequently surpassing traditional models. However, for unstructured medical texts, LLMs did not outperform finetuned BERT models, which excelled in both supervised and unsupervised tasks. Consequently, while LLMs are effective for zero-shot learning on structured data, finetuned BERT models are more suitable for unstructured texts, underscoring the importance of selecting models based on specific task requirements and data characteristics to optimize the application of NLP technology in healthcare., Comment: arXiv admin note: text overlap with arXiv:2402.01713

Small-scale winds driven from accretion discs surrounding active galactic nuclei (AGN) are expected to launch kpc-scale outflows into their host galaxies. However, the ways in which the structure of the interstellar medium (ISM) affects the multiphase content and impact of the outflow remains uncertain. We present a series of numerical experiments featuring a realistic small-scale AGN wind with velocity $5\times 10^3-10^4\ \rm{km/s}$ interacting with an isolated galaxy disc with a manually-controlled clumpy ISM, followed at sub-pc resolution. Our simulations are performed with AREPO and probe a wide range of AGN luminosities ($L=10^{43-47}\ \rm{erg/s}$) and ISM substructures. In homogeneous discs, the AGN wind sweeps up an outflowing, cooling shell, where the emerging cold phase dominates the mass and kinetic energy budgets, reaching a momentum flux $\dot{p} \approx 7\ L/c$. However, when the ISM is clumpy, outflow properties are profoundly different. They contain small, long-lived ($> 5\ \rm{Myr}$), cold ($T<10^{4.5}\ \rm{K}$) cloudlets entrained in the faster, hot outflow phase, which are only present in the outflow if radiative cooling is included in the simulation. While the cold phase dominates the mass of the outflow, most of the kinetic luminosity is now carried by a tenuous, hot phase with $T > 10^7 \ \rm K$. While the hot phases reaches momentum fluxes $\dot{p} \approx (1 - 5)\ L/c$, energy-driven bubbles couple to the cold phase inefficiently, producing modest momentum fluxes $\dot{p} < L/c$ in the fast-outflowing cold gas. These low momentum fluxes could lead to the outflows being misclassified as momentum-driven using common observational diagnostics. We also show predictions for scaling relations between outflow properties and AGN luminosity and discuss the challenges in constraining outflow driving mechanisms and kinetic coupling efficiencies using observed quantities., Comment: Accepted to MNRAS. 23 pages, 14 plots, 1 table. v2: minor update to Figure 11 to include observational fits from Bischetti+19

This paper is about the recent notion of computably probably approximately correct learning, which lies between the statistical learning theory where there is no computational requirement on the learner and efficient PAC where the learner must be polynomially bounded. Examples have recently been given of hypothesis classes which are PAC learnable but not computably PAC learnable, but these hypothesis classes are unnatural or non-canonical in the sense that they depend on a numbering of proofs, formulas, or programs. We use the on-a-cone machinery from computability theory to prove that, under mild assumptions such as that the hypothesis class can be computably listable, any natural hypothesis class which is learnable must be computably learnable. Thus the counterexamples given previously are necessarily unnatural., Comment: This is a replacement of the earlier submission to just update the funding information

Aspera is a NASA Astrophysics Pioneers SmallSat mission designed to study diffuse OVI emission from the warm-hot phase gas in the halos of nearby galaxies. Its payload consists of two identical Rowland Circle-type long-slit spectrographs, sharing a single MicroChannel plate detector. Each spectrograph channel consists of an off-axis parabola primary mirror and a toroidal diffraction grating optimized for the 1013-1057 Angstroms bandpass. Despite the simple configuration, the optical alignment/integration process for Aspera is challenging due to tight optical alignment tolerances, driven by the compact form factor, and the contamination sensitivity of the Far-Ultraviolet optics and detectors. In this paper, we discuss implementing a novel multi-phase approach to meet these requirements using state-of-the-art optical metrology tools. For coarsely positioning the optics we use a blue-laser 3D scanner while the fine alignment is done with a Zygo interferometer and a custom computer-generated hologram. The detector focus requires iterative in-vacuum alignment using a Vacuum UV collimator. The alignment is done in a controlled cleanroom facility at the University of Arizona., Comment: Manuscript submitted for Proceedings of Astronomical Telescopes + Instrumentation 2024, Paper no. 13093-9

Understanding the noise characteristics of high quantum efficiency silicon-based ultraviolet detectors, developed by the Microdevices Lab at the Jet Propulsion Laboratory, is critical for current and proposed UV missions using these devices. In this paper, we provide an overview of our detector noise characterization test bench that uses delta-doped, photon counting, Electron-multiplying CCDs (EMCCDs) to understand the fundamental noise properties relevant to all silicon CCDs and CMOS arrays. This work attempts to identify the source of the dark current plateau that has been previously measured with photon-counting EMCCDs and is known to be prevalent in other silicon-based arrays. It is suspected that the plateau could be due to a combination of detectable photons in the tail of blackbody radiation of the ambient instrument, low-level light leaks, and a non-temperature-dependent component that varies with substrate voltage. Our innovative test setup delineates the effect of the ambient environment during dark measurements by independently controlling the temperature of the detector and surrounding environment. We present the design of the test setup and preliminary results., Comment: Submitted for Proceedings of SPIE Astronomical Telescopes+Instrumentation 2024, Paper number: 13093-26

We employ correlated density-functional theory methods (DFT + Hubbard $U$) to investigate the spin-density wave state of the bilayer Ruddlesden-Popper (RP) nickelate La$_{3}$Ni$_{2}$O$_{7}$ which becomes superconducting under pressure. We predict that the ground state of this bilayer RP material is a single spin-charge stripe phase with in-plane up$^\prime$/up/down$^\prime$/down diagonal stripes with up$^\prime$/down$^\prime$ being low spin (formally Ni$^{3+}$: $d^7$) and up/down being high spin (formally Ni$^{2+}$: $d^8$). The main feature of this solution (that is insulating even at $U=0$) is the dominant role of $d_{x^{2}-y^{2}}$ bands around the Fermi level, which would become doped with the introduction of electrons via oxygen vacancies. In spite of the similarity with cuprates in terms of the dominant role of $d_{x^{2}-y^{2}}$ bands, some differences are apparent in the magnetic ground state of La$_{3}$Ni$_{2}$O$_{7}$: the antiferromagnetic out-of-plane coupling within the bilayer (linked to the $d_{z^2}$ orbitals forming a spin-singlet-like configuration) is found to be the dominant one while in-plane interactions are reduced due to the stripe order of the ground state. With pressure, this striped magnetic ground state remains similar in nature but the increase in bandwidth quickly transitions La$_{3}$Ni$_{2}$O$_{7}$ into a metallic state with all the activity close to the Fermi level involving, to a large extent, $d_{x^2-y^2}$ orbitals. This is reminiscent of the cuprates and may provide key insights into how superconductivity arises in this material under pressure., Comment: 8 pages, 4 figures

The first study of $J/\psi\phi$ production in diffractive processes in proton-proton collisions is presented. The study is based on an LHCb dataset recorded at centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 5 fb$^{-1}$. The data disfavour a nonresonant $J/\psi\phi$ production but are consistent with a resonant model including several resonant states observed previously only in $B^+ \to J/\psi\phi K^+$ decays. The $\chi_{c0}(4500)$ state is observed with a significance over $5\sigma$ and the $\chi_{c1}(4274)$ is confirmed with a significance of more than $4\sigma$., Comment: All figures and tables, along with any supplementary material and additional information, are available at: https://lhcbproject.web.cern.ch/Publications/LHCbProjectPublic/LHCb-PAPER-2023-043.html (LHCb public pages)

Computer vision systems have been deployed in various applications involving biometrics like human faces. These systems can identify social media users, search for missing persons, and verify identity of individuals. While computer vision models are often evaluated for accuracy on available benchmarks, more annotated data is necessary to learn about their robustness and fairness against semantic distributional shifts in input data, especially in face data. Among annotated data, counterfactual examples grant strong explainability characteristics. Because collecting natural face data is prohibitively expensive, we put forth a generative AI-based framework to construct targeted, counterfactual, high-quality synthetic face data. Our synthetic data pipeline has many use cases, including face recognition systems sensitivity evaluations and image understanding system probes. The pipeline is validated with multiple user studies. We showcase the efficacy of our face generation pipeline on a leading commercial vision model. We identify facial attributes that cause vision systems to fail., Comment: Paper under review. Full text and results will be updated after acceptance

The ability of Language Models (LMs) to understand natural language makes them a powerful tool for parsing human instructions into task plans for autonomous robots. Unlike traditional planning methods that rely on domain-specific knowledge and handcrafted rules, LMs generalize from diverse data and adapt to various tasks with minimal tuning, acting as a compressed knowledge base. However, LMs in their standard form face challenges with long-horizon tasks, particularly in partially observable multi-agent settings. We propose an LM-based Long-Horizon Planner for Multi-Agent Robotics (LLaMAR), a cognitive architecture for planning that achieves state-of-the-art results in long-horizon tasks within partially observable environments. LLaMAR employs a plan-act-correct-verify framework, allowing self-correction from action execution feedback without relying on oracles or simulators. Additionally, we present MAP-THOR, a comprehensive test suite encompassing household tasks of varying complexity within the AI2-THOR environment. Experiments show that LLaMAR achieves a 30% higher success rate compared to other state-of-the-art LM-based multi-agent planners., Comment: 27 pages, 4 figures, 5 tables

Recent (sub)millimeter polarization observations of protoplanetary disks reveal toroidally aligned, effectively prolate dust grains large enough (at least ~100 $\mu$m) to efficiently scatter millimeter light. The alignment mechanism for these grains remains unclear. We explore the possibility that gas drag aligns grains through gas-dust relative motion when the grain's center of mass is offset from its geometric center, analogous to a badminton birdie's alignment in flight. A simple grain model of two non-identical spheres illustrates how a grain undergoes damped oscillations from flow-induced restoring torques which align its geometric center in the flow direction relative to its center of mass. Assuming specular reflection and subsonic flow, we derive an analytical equation of motion for spheroids where the center of mass can be shifted away from the spheroid's geometric center. We show that a prolate or an oblate grain can be aligned with the long axis parallel to the gas flow when the center of mass is shifted along that axis. Both scenarios can explain the required effectively prolate grains inferred from observations. Application to a simple disk model shows that the alignment timescales are shorter than or comparable to the orbital time. The grain alignment direction in a disk depends on the disk (sub-)structure and grain Stokes number (St) with azimuthal alignment for large St grains in sub-Keplerian smooth gas disks and for small St grains near the gas pressure extrema, such as rings and gaps., Comment: 21 pages, 12 figures, submitted to MNRAS

Haystack and Owens Valley Radio Observatory (OVRO) observations recently revealed strong sinusoidal total flux density variations that maintained coherence between 1975 and 2021 in the blazar PKS 2131-021 ($z=1.283)$. This was interpreted as possible evidence of a supermassive black hole binary (SMBHB). Extended observations through 2023 show coherence over 47.9~years, with an observed period $P_\textrm{15 GHz}=(1739.3 \pm 1.2) \, {\rm days}$. We reject, with $p$-value = $5.3 \times 10^{-7}$, the hypothesis that the variations are due to random fluctuations in the red noise tail of the power spectral density. There is clearly a constant-period physical phenomenon in PKS 2131-021 producing coherent intermittent sinusoidal flux density variations. We find the coherent sinusoidal intensity variations extend from below 2.7 GHz to optical frequencies, from which we derive an observed period $P_\textrm{optical}=(1764 \pm 36)$ days. Across this broad frequency range there is a monotonic phase shift in the sinusoidal variations with frequency. The same coherent periodicity is possibly also observed at $\gamma$-ray energies. The importance of well-vetted SMBHB candidates to searches for gravitational waves is pointed out. We estimate the fraction of blazars that are SMBHB candidates to be $>1$ in 100. Thus monitoring programs covering tens of thousands of blazars could discover hundreds of SMBHB candidates., Comment: 23 pages, 17 figures, 5 tables, submitted to ApJ

Determining the full five-parameter grain boundary characteristics from experiments is essential for understanding grain boundaries impact on material properties, improving related models, and designing advanced alloys. However, achieving this is generally challenging, in particular at nanoscale, due to their 3D nature. In our study, we successfully determined the grain boundary characteristics of an annealed nickel-tungsten alloy (NiW) nanocrystalline needle-shaped specimen (tip) containing twins using Scanning Precession Electron Diffraction (SPED) Tomography. The presence of annealing twins in this face-centered cubic (fcc) material gives rise to common reflections in the SPED diffraction patterns, which challenges the reconstruction of orientation-specific virtual dark field (VDF) images required for tomographic reconstruction of the 3D grain shapes. To address this, an automated post-processing step identifies and deselects these shared reflections prior to the reconstruction of the VDF images. Combined with appropriate intensity normalization and projection alignment procedures, this approach enables high-fidelity 3D reconstruction of the individual grains contained in the needle-shaped sample volume. To probe the accuracy of the resulting boundary characteristics, the twin boundary surface normal directions were extracted from the 3D voxelated grain boundary map using a 3D Hough transform. For the sub-set of coherent Sigma 3 boundaries, the expected {111} grain boundary plane normals were obtained with an angular error of less than 3{\textdegree} for boundary sizes down to 400 nm${}^2$. This work advances our ability to precisely characterize and understand the complex grain boundaries that govern material properties.

We study the effect of localized housing price hikes on renters' mobility, consumption, and credit outcomes. Consistent with a spatial equilibrium model, we find that the consumption responses vary greatly for movers and stayers. While movers increase their consumption, purchase homes, and cars, stayers are relatively unaffected.

The tilt-to-length coupling during the LISA Pathfinder mission has been numerically and analytically modeled for particular timespans. In this work, we investigate the long-term stability of the coupling coefficients of this noise. We show that they drifted slowly (by 1\,$\mu$m/rad and 6$\times10^{-6}$ in 100 days) and strongly correlated to temperature changes within the satellite (8\,$\mu$m/rad/K and 30$\times10^{-6}$/K). Based on analytical TTL coupling models, we attribute the temperature-driven coupling changes to rotations of the test masses and small distortions in the optical setup. Particularly, we show that LISA Pathfinder's optical baseplate was bent during the cooldown experiment, which started in late 2016 and lasted several months.

Many physical, biological, and even social systems are faced with the problem of how to efficiently harvest free energy from any of many possible environmental states, yet only have a limited number of harvesting strategies to choose among. We formalize this general situation within the framework of work extraction from nonequilibirum systems using feedback control. Specifically, we analyze the combined and separate effects of noisy measurements, memory limitations, and the access to only a limited set of possible control operations, quantifying the amount of extractable work under all such constraints. Such analysis allows us to provide a general recipe to construct repertoires of allowed control operations that minimize the expected losses during the feedback protocol, i.e., that minimize expected entropy production. Our results highlight the importance and benefits of feedback control over uninformed (random) actions beyond the information gain under control restrictions and are applied to several situations including uncertain initial distributions., Comment: 13 pages, 1 figure

Temperature is known to impact Li-ion battery performance and safety, however, understanding its effect on Li-ion batteries has largely been limited to uniform high or low temperatures. While the insights gathered from such research are important, much less information is available on the effects of non-uniform temperatures which more accurately reflect the environments that Li-ion batteries are exposed to in real world applications. In this paper, we characterize the impact of a microscale, temperature hotspot on a Li-ion battery using a combination of in situ micro-Raman spectroscopy, in situ optical microscopy and COMSOL Multiphysics thermal simulations. Our results show that mild temperature heterogeneity induced by the micro-Raman laser can cause lithium to locally leach out from different lithiated graphite phases (LiC6 and LiC12) in the absence of an applied current. The Li metal is found to be largely localized to the region heated by the micro-Raman laser and is not observed upon uniform heating to comparable temperatures suggesting that temperature heterogeneity is uniquely responsible for causing Li to leach out from lithiated graphite phases. A mechanism whereby localized temperature heterogeneity induced by the laser induces heterogeneity in the degree of lithiation across the graphite anode is proposed to explain the localized Li leaching. This study highlights the sensitivity of lithiated graphite phases to minor temperature heterogeneity in the absence of an applied current.

Background: The high dimensionality of radiomic feature sets, the variability in radiomic feature types and potentially high computational requirements all underscore the need for an effective method to identify the smallest set of predictive features for a given clinical problem. Purpose: Develop a methodology and tools to identify and explain the smallest set of predictive radiomic features. Materials and Methods: 89,714 radiomic features were extracted from five cancer datasets: low-grade glioma, meningioma, non-small cell lung cancer (NSCLC), and two renal cell carcinoma cohorts (n=2104). Features were categorized by computational complexity into morphological, intensity, texture, linear filters, and nonlinear filters. Models were trained and evaluated on each complexity level using the area under the curve (AUC). The most informative features were identified, and their importance was explained. The optimal complexity level and associated most informative features were identified using systematic statistical significance analyses and a false discovery avoidance procedure, respectively. Their predictive importance was explained using a novel tree-based method. Results: MEDimage, a new open-source tool, was developed to facilitate radiomic studies. Morphological features were optimal for MRI-based meningioma (AUC: 0.65) and low-grade glioma (AUC: 0.68). Intensity features were optimal for CECT-based renal cell carcinoma (AUC: 0.82) and CT-based NSCLC (AUC: 0.76). Texture features were optimal for MRI-based renal cell carcinoma (AUC: 0.72). Tuning the Hounsfield unit range improved results for CECT-based renal cell carcinoma (AUC: 0.86). Conclusion: Our proposed methodology and software can estimate the optimal radiomics complexity level for specific medical outcomes, potentially simplifying the use of radiomics in predictive modeling across various contexts.

A precise characterization of the magnetic properties of LISA Pathfinder free falling test-masses is of special interest for future gravitational wave observatory in space. Magnetic forces have an important impact on the instrument sensitivity in the low frequency regime below the millihertz. In this paper we report on the magnetic injection experiments performed throughout LISA Pathfinder operations. We show how these experiments allowed a high precision estimate of the instrument magnetic parameters. The remanent magnetic moment was found to have a modulus of $(0.245\pm0.081)\,\rm{nAm}^2$, the x-component of the background magnetic field within the test masses position was measured to be $(414 \pm 74)$ nT and its gradient had a value of $(-7.4\pm 2.1)\,\mu$T/m. Finally, we also measured the test mass magnetic susceptibility to be $(-3.35\pm0.15)\times$10$^{-5}$ in the low frequency regime. All results are in agreement with on-ground estimates.

LISA Pathfinder was a mission designed to test key technologies required for gravitational wave detection in space. Magnetically driven forces play a key role in the instrument sensitivity in the low-frequency regime, which corresponds to the measurement band of interest for future space-borne gravitational wave observatories. Magnetic-induced forces couple to the test mass motion, introducing a contribution to the relative acceleration noise between the free falling test masses. In this Letter we present the first complete estimate of this term of the instrument performance model. Our results set the magnetic-induced acceleration noise during the February 2017 noise run of $\rm 0.25_{-0.08}^{+0.15}\,fm\,s^{-2}/\sqrt{Hz}$ at 1 mHz and $\rm 1.01_{-0.24}^{+0.73}\, fm\,s^{-2}/\sqrt{Hz}$ at 0.1 mHz. We also discuss how the non-stationarities of the interplanetary magnetic field can affect these values during extreme space weather conditions.

We present spatially resolved VLT/SINFONI spectroscopy with adaptive optics of type-2 active galactic nuclei (AGN) from the SINFONI Survey for Unveiling the Physics and Effect of Radiative feedback (SUPER), which targeted X-ray bright ($L_{2-10 keV}\gtrsim10^{42}$ erg s$^{-1}$) AGN at Cosmic Noon ($z\sim2$). Our analysis of the rest-frame optical spectra unveils ionised outflows in all seven examined targets, as traced via [OIII]$\lambda$5007 line emission, moving at $v\gtrsim600$ km s$^{-1}$. In six objects these outflows are clearly spatially resolved and extend on 2-4 kpc scales, whereas marginally resolved in the remaining one. Interestingly, these SUPER type-2 AGN are all heavily obscured sources ($N_{H}\gtrsim10^{23}$ cm$^{-2}$) and host faster ionised outflows than their type-1 counterparts within the same range of bolometric luminosity ($L_{bol} \sim 10^{44.8-46.5}$ erg s$^{-1}$). SUPER has hence provided observational evidence that the type-1/type-2 dichotomy at $z\sim2$ might not be driven simply by projection effects, but might reflect two distinct obscuring life stages of active galaxies, as predicted by evolutionary models. Within this picture, SUPER type-2 AGN might be undergoing the 'blow-out' phase, where the large amount of obscuring material efficiently accelerates large-scale outflows via radiation pressure on dust, eventually unveiling the central active nucleus and signal the start of the bright, unobscured type-1 AGN phase. Moreover, the overall population of ionised outflows detected in SUPER has velocities comparable with the escape speed of their dark matter halos, and in general high enough to reach 30-50 kpc distances from the centre. These outflows are hence likely to sweep away the gas (at least) out of the baryonic disk and/or to heat the host gas reservoir, thus reducing and possibly quenching star formation., Comment: 21 pages, 13 figures. Key figure is 8. Accepted for publication in A&A

Decompilers are widely used by security researchers and developers to reverse engineer executable code. While modern decompilers are adept at recovering instructions, control flow, and function boundaries, some useful information from the original source code, such as variable types and names, is lost during the compilation process. Our work aims to predict these variable types and names from the remaining information. We propose STRIDE, a lightweight technique that predicts variable names and types by matching sequences of decompiler tokens to those found in training data. We evaluate it on three benchmark datasets and find that STRIDE achieves comparable performance to state-of-the-art machine learning models for both variable retyping and renaming while being much simpler and faster. We perform a detailed comparison with two recent SOTA transformer-based models in order to understand the specific factors that make our technique effective. We implemented STRIDE in fewer than 1000 lines of Python and have open-sourced it under a permissive license at https://github.com/hgarrereyn/STRIDE.

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.