Search

Electron-capture decays of $^{125}$Xe and $^{127}$Xe, and double-electron-capture decays of $^{124}$Xe, are backgrounds in searches for weakly interacting massive particles (WIMPs) conducted by dual-phase xenon time projection chambers such as LUX-ZEPLIN (LZ). These decays produce signals with more light and less charge than equivalent-energy $\beta$ decays, and correspondingly overlap more with WIMP signals. We measure three electron-capture charge yields in LZ: the 1.1~keV M-shell, 5.2~keV L-shell, and 33.2~keV K-shell at drift fields of 193~V/cm and 96.5~V/cm. The LL double-electron-capture decay of $^{124}$Xe exhibits even more pronounced shifts in charge and light. We provide a first model of double-electron-capture charge yields using the link between ionization density and electron-ion recombination, and identify a need for more accurate calculations. Finally, we discuss the implications of the reduced charge yield of these decays and other interactions creating inner-shell vacancies for future dark matter searches., Comment: 16 pages, 11 figures

The metallicity of galaxies, and its variation with galactocentric radius, provides key insights into the formation histories of galaxies and the physical processes driving their evolution. In this work, we analyze the radial metallicity gradients of star forming galaxies in the EAGLE, Illustris, IllustrisTNG, and SIMBA cosmological simulations across a broad mass ($10^{8.0}M_\odot\leq M_\star \lesssim10^{12.0}M_\odot$) and redshift ($0\leq z\leq8$) range. We find that all simulations predict strong negative (i.e., radially decreasing) metallicity gradients at early cosmic times, likely due to their similar treatments of relatively smooth stellar feedback allowing for sustained inside-out growth. The strongest redshift evolution occurs in galaxies with stellar masses of $10^{10.0}-10^{11.0}M_\odot$, while galaxies with stellar masses $< 10^{10}M_\odot$ and $>10^{11}M_\odot$ exhibit weaker redshift evolution. Our results of negative gradients at high-redshift contrast with the many positive and flat gradients in the $16$, the negative gradients observed with JWST and ALMA are flatter than those in simulations, albeit with closer agreement than at lower redshift. Overall, we suggest that these smooth stellar feedback galaxy simulations may not sufficiently mix their metal content, and that either stronger stellar feedback or additional subgrid turbulent metal diffusion models may be required to better reproduce observed metallicity gradients., Comment: 16 pages, 4 figures, + appendices. Submitted to ApJ. Comments welcome

Recent years have seen a surge of interest in the community studying the effect of ultraviolet radiation environment, predominantly set by OB stars, on protoplanetary disc evolution and planet formation. This is important because a significant fraction of planetary systems, potentially including our own, formed in close proximity to OB stars. This is a rapidly developing field, with a broad range of observations across many regions recently obtained or recently scheduled. In this paper, stimulated by a series of workshops on the topic, we take stock of the current and upcoming observations. We discuss how the community can build on this recent success with future observations to make progress in answering the big questions of the field, with the broad goal of disentangling how external photoevaporation contributes to shaping the observed (exo)planet population. Both existing and future instruments offer numerous opportunities to make progress towards this goal., Comment: Submitted to the Open Journal of Astrophysics. Corresponding author Thomas Haworth

Gradient descent is the primary workhorse for optimizing large-scale problems in machine learning. However, its performance is highly sensitive to the choice of the learning rate. A key limitation of gradient descent is its lack of natural scaling, which often necessitates expensive line searches or heuristic tuning to determine an appropriate step size. In this paper, we address this limitation by incorporating Hessian information to scale the gradient direction. By accounting for the curvature of the function along the gradient, our adaptive, Hessian-aware scaling method ensures a local unit step size guarantee, even in nonconvex settings. Near a local minimum that satisfies the second-order sufficient conditions, our approach achieves linear convergence with a unit step size. We show that our method converges globally under a significantly weaker version of the standard Lipschitz gradient smoothness assumption. Even when Hessian information is inexact, the local unit step size guarantee and global convergence properties remain valid under mild conditions. Finally, we validate our theoretical results empirically on a range of convex and nonconvex machine learning tasks, showcasing the effectiveness of the approach.

In optimization problems involving smooth functions and real and matrix variables, that contain matrix semidefiniteness constraints, consider the following change of variables: Replace the positive semidefinite matrix $X \in \mathbb{S}^d$, where $\mathbb{S}^d$ is the set of symmetric matrices in $\mathbb{R}^{d\times d}$, by a matrix product $FF^\top$, where $F \in \mathbb{R}^{d \times d}$ or $F \in \mathbb{S}^d$. The formulation obtained in this way is termed ``squared variable," by analogy with a similar idea that has been proposed for real (scalar) variables. It is well known that points satisfying first-order conditions for the squared-variable reformulation do not necessarily yield first-order points for the original problem. There are closer correspondences between second-order points for the squared-variable reformulation and the original formulation. These are explored in this paper, along with correspondences between local minimizers of the two formulations., Comment: 34 pages

The existence of indistinguishable quantum particles provides an explanation for various physical phenomena we observe in nature. We lay out a path for the study of indistinguishable particles in general probabilistic theories (GPTs) via two frameworks: the traditional GPT framework and the diagrammatic framework of process theories. In the first approach we define different types of indistinguishable particle by the orbits of symmetric states under transformations. In the diagrammatic approach, we find a decomposition of the symmetrised state space using two key constructions from category theory: the biproduct completion and the Karoubi envelope. In both cases for pairs of indistinguishable particles in quantum theory we recover bosons and fermions.

Machine learning algorithms in high-dimensional settings are highly susceptible to the influence of even a small fraction of structured outliers, making robust optimization techniques essential. In particular, within the $\epsilon$-contamination model, where an adversary can inspect and replace up to an $\epsilon$-fraction of the samples, a fundamental open problem is determining the optimal rates for robust stochastic convex optimization (SCO) under such contamination. We develop novel algorithms that achieve minimax-optimal excess risk (up to logarithmic factors) under the $\epsilon$-contamination model. Our approach improves over existing algorithms, which are not only suboptimal but also require stringent assumptions, including Lipschitz continuity and smoothness of individual sample functions. By contrast, our optimal algorithms do not require these restrictive assumptions, and can handle nonsmooth but Lipschitz population loss functions. We complement our algorithmic developments with a tight lower bound for robust SCO.

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.

Identifying valuable measurements is one of the main challenges in computational inverse problems, often framed as the optimal experimental design (OED) problem. In this paper, we investigate nonlinear OED within a continuously-indexed design space. This is in contrast to the traditional approaches on selecting experiments from a finite measurement set. This formulation better reflects practical scenarios where measurements are taken continuously across spatial or temporal domains. However, optimizing over a continuously-indexed space introduces computational challenges. To address these, we employ gradient flow and optimal transport techniques, complemented by adaptive strategy for interactive optimization. Numerical results on the Lorenz 63 system and Schr\"odinger equation demonstrate that our solver identifies valuable measurements and achieves improved reconstruction of unknown parameters in inverse problems.

The typically large distances, extinction, and crowding of Galactic supermassive star clusters have so far hampered the identification of their very low mass members, required to extend our understanding of star and planet formation, and early stellar evolution, to starburst. This situation has now evolved thanks to the James Webb Space Telescope (JWST), and its unmatched resolution and sensitivity in the infrared. In this paper, the third of the series of the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS), we present JWST/NIRCam and JWST/MIRI observations of the supermassive star cluster Westerlund 1. These observations are specifically designed to unveil the cluster members down to the BD mass regime, and to allow us to select and study the protoplanetary disks and to study the mutual feedback between the cluster members and the surrounding environment. Westerlund 1 was observed as part of JWST GO-1905 for 23.6 hours. The data have been reduced using the JWST calibration pipeline, together with specific tools necessary to remove artifacts. Source identification and photometry were performed with DOLPHOT. The MIRI images show a plethora of different features. Diffuse nebular emission is observed around the cluster, which is typically composed of myriads of droplet-like features pointing toward the cluster center or the group of massive stars surrounding the WR star W72/A. A long pillar is also observed in the NW. The MIRI images also show resolved shells and outflows surrounding the M-type RSG W20, W26, W75, and W237, the sgB[e] star W9 and the YHG W4. The color-magnitude diagrams built using the NIRCam photometry show a clear cluster sequence, which is marked in its upper part by the 1828 NIRCam stars with X-ray counterparts. NIRCam observations using the F115W filter have reached the 23.8 mag limit with 50\% completeness (roughly corresponding to a 0.06 Msol brown dwarf)., Comment: Accepted for publication in Astronomy & Astrophysics

The relationship between magnetic activity and Rossby number is one way through which stellar dynamos can be understood. Using measured rotation rates and X-ray to bolometric luminosity ratios of an ensemble of stars, we derive empirical convective turnover times based on recent observations and re-evaluate the X-ray activity-Rossby number relationship. In doing so, we find a sharp rise in the convective turnover time for stars in the mass range of $0.35-0.4\ \rm M_{\odot}$, associated with the onset of a fully convective internal stellar structure. Using $\texttt{MESA}$ stellar evolution models, we infer the location of dynamo action implied by the empirical convective turnover time. The empirical convective turnover time is found to be indicative of dynamo action deep within the convective envelope in stars with masses $0.1-1.2\ \rm M_{\odot}$, crossing the fully convective boundary. Our results corroborate past works suggesting that partially and fully convective stars follow the same activity-Rossby relation, possibly owing to similar dynamo mechanisms. Our stellar models also give insight into the dynamo mechanism. We find that empirically determined convective turnover times correlate with properties of the deep stellar interior. These findings are in agreement with global dynamo models that see a reservoir of magnetic flux accumulate deep in the convection zone before buoyantly rising to the surface., Comment: 9 Figures and 2 Tables

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in $^{136}$Xe using a natural-abundance xenon target. XLZD can reach a 3$\sigma$ discovery potential half-life of 5.7$\times$10$^{27}$ yr (and a 90% CL exclusion of 1.3$\times$10$^{28}$ yr) with 10 years of data taking, corresponding to a Majorana mass range of 7.3-31.3 meV (4.8-20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community., Comment: 29 pages, 7 figures

This report describes the experimental strategy and technologies for a next-generation xenon observatory sensitive to dark matter and neutrino physics. The detector will have an active liquid xenon target mass of 60-80 tonnes and is proposed by the XENON-LUX-ZEPLIN-DARWIN (XLZD) collaboration. The design is based on the mature liquid xenon time projection chamber technology of the current-generation experiments, LZ and XENONnT. A baseline design and opportunities for further optimization of the individual detector components are discussed. The experiment envisaged here has the capability to explore parameter space for Weakly Interacting Massive Particle (WIMP) dark matter down to the neutrino fog, with a 3$\sigma$ evidence potential for the spin-independent WIMP-nucleon cross sections as low as $3\times10^{-49}\rm cm^2$ (at 40 GeV/c$^2$ WIMP mass). The observatory is also projected to have a 3$\sigma$ observation potential of neutrinoless double-beta decay of $^{136}$Xe at a half-life of up to $5.7\times 10^{27}$ years. Additionally, it is sensitive to astrophysical neutrinos from the atmosphere, sun, and galactic supernovae., Comment: 32 pages, 14 figures

We report results of a search for nuclear recoils induced by weakly interacting massive particle (WIMP) dark matter using the LUX-ZEPLIN (LZ) two-phase xenon time projection chamber. This analysis uses a total exposure of $4.2\pm0.1$ tonne-years from 280 live days of LZ operation, of which $3.3\pm0.1$ tonne-years and 220 live days are new. A technique to actively tag background electronic recoils from $^{214}$Pb $\beta$ decays is featured for the first time. Enhanced electron-ion recombination is observed in two-neutrino double electron capture decays of $^{124}$Xe, representing a noteworthy new background. After removal of artificial signal-like events injected into the data set to mitigate analyzer bias, we find no evidence for an excess over expected backgrounds. World-leading constraints are placed on spin-independent (SI) and spin-dependent WIMP-nucleon cross sections for masses $\geq$9 GeV/$c^2$. The strongest SI exclusion set is $2.1\times10^{-48}$ cm$^{2}$ at the 90% confidence level at a mass of 36 GeV/$c^2$, and the best SI median sensitivity achieved is $5.0\times10^{-48}$ cm$^{2}$ for a mass of 40 GeV/$c^2$., Comment: 9 pages, 7 figures. See https://www.hepdata.net/record/155182 for a data release related to this paper

We study stellar core growth in simulations of merging massive ($M_\star>10^{11}\,\mathrm{M}_\odot$) elliptical galaxies by a supermassive black hole (SMBH) displaced by gravitational wave induced recoil velocity. With controlled, dense sampling of the SMBH recoil velocity, we find the core radius originally formed by SMBH binary scouring can grow by a factor of 2-3 when the recoil velocity exceeds $\sim50$ per cent of the central escape velocity, and the mass deficit grows by up to a factor of $\sim4$. Using Bayesian inference we predict the distribution of stellar core sizes formed through this process to peak at $\sim1\,\mathrm{kpc}$. An orbital decomposition of stellar particles within the core reveals that radial orbits dominate over tube orbits when the recoil velocity exceeds the velocity dispersion of the core, whereas tube orbits dominate for the lowest recoil kicks. A change in orbital structure is reflected in the anisotropy parameter, with a central tangential bias present only for recoil velocities less than the local stellar velocity dispersion. Emulating current integral field unit observations of the stellar line-of-sight velocity distribution, we uncover a distinct signature in the Gauss-Hermite symmetric deviation coefficient $h_4$ that uniquely constrains the core size due to binary scouring. This signature is insensitive to the later evolution of the stellar mass distribution due to SMBH recoil. Our results provide a novel method to estimate the SMBH recoil magnitude from observations of local elliptical galaxies, and implies these galaxies primarily experienced recoil velocities less than the stellar velocity dispersion of the core., Comment: 27 pages, 21 figures, as accepted

SDO-FM is a foundation model using data from NASA's Solar Dynamics Observatory (SDO) spacecraft; integrating three separate instruments to encapsulate the Sun's complex physical interactions into a multi-modal embedding space. This model can be used to streamline scientific investigations involving SDO by making the enormous datasets more computationally accessible for heliophysics research and enable investigations that require instrument fusion. We discuss four key components: an ingestion pipeline to create machine learning ready datasets, the model architecture and training approach, resultant embeddings and fine-tunable models, and finally downstream fine-tuned applications. A key component of this effort has been to include subject matter specialists at each stage of development; reviewing the scientific value and providing guidance for model architecture, dataset, and training paradigm decisions. This paper marks release of our pretrained models and embedding datasets, available to the community on Hugging Face and sdofm.org.

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational Science Award (CTSA) Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. With the rapid advancement of GenAI technologies, including large language models (LLMs), healthcare institutions face unprecedented opportunities and challenges. This research explores the current status of GenAI integration, focusing on stakeholder roles, governance structures, and ethical considerations by administering a survey among leaders of health institutions (i.e., representing academic medical centers and health systems) to assess the institutional readiness and approach towards GenAI adoption. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The study highlights significant variations in governance models, with a strong preference for centralized decision-making but notable gaps in workforce training and ethical oversight. Moreover, the results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis also reveals concerns regarding GenAI bias, data security, and stakeholder trust, which must be addressed to ensure the ethical and effective implementation of GenAI technologies. This study offers valuable insights into the challenges and opportunities of GenAI integration in healthcare, providing a roadmap for institutions aiming to leverage GenAI for improved quality of care and operational efficiency.

We present a comprehensive study of the star formation histories of massive-quenched galaxies at $z=3$ in 3 semi-analytic models (SHARK, GAEA, GALFORM) and 3 cosmological hydrodynamical simulations (EAGLE, IllustrisTNG, Simba). We study the predicted number density and stellar mass function of massive-quenched galaxies, their formation and quenching timescales and star-formation properties of their progenitors. Predictions are disparate in all these diagnostics, for instance: (i) some simulations reproduce the observed number density of very massive-quenched galaxies ($>10^{11}\rm M_{\odot}$) but underpredict the high density of intermediate-mass ones, while others fit well the lower masses but underpredict the higher ones; (ii) In most simulations, except for GAEA and EAGLE, most massive-quenched galaxies had starburst periods, with the most intense ones happening at $4300\rm M_{\odot}\,yr^{-1}$; (iii) quenching timescales are in the range $\approx 20-150$~Myr depending on the simulation; among other differences. These disparate predictions can be tied to the adopted Active Galactic Nuclei (AGN) feedback model. For instance, the explicit black-hole (BH) mass dependence to trigger the "radio mode" in IllustrisTNG and Simba makes it difficult to produce quenched galaxies with intermediate stellar masses, also leading to higher baryon collapse efficiencies ($\approx 15-30$%); while the strong bolometric luminosity dependence of the AGN outflow rate in GAEA leads to BHs of modest mass quenching galaxies. Current observations are unable to distinguish between these different predictions due to the small sample sizes. However, these predictions are testable with current facilities and upcoming observations, allowing a "true physics experiment" to be carried out., Comment: Accepted for publication in MNRAS in December 2024 after minor changes

Understanding space weather is vital for the protection of our terrestrial and space infrastructure. In order to predict space weather accurately, large amounts of data are required, particularly in the extreme ultraviolet (EUV) spectrum. An exquisite source of information for such data is provided by the Solar Dynamic Observatory (SDO), which has been gathering solar measurements for the past 13 years. However, after a malfunction in 2014 affecting the onboard Multiple EUV Grating Spectrograph A (MEGS-A) instrument, the scientific output in terms of EUV measurements has been significantly degraded. Building upon existing research, we propose to utilize deep learning for the virtualization of the defective instrument. Our architecture features a linear component and a convolutional neural network (CNN) -- with EfficientNet as a backbone. The architecture utilizes as input grayscale images of the Sun at multiple frequencies -- provided by the Atmospheric Imaging Assembly (AIA) -- as well as solar magnetograms produced by the Helioseismic and Magnetic Imager (HMI). Our findings highlight how AIA data are all that is needed for accurate predictions of solar irradiance. Additionally, our model constitutes an improvement with respect to the state-of-the-art in the field, further promoting the idea of deep learning as a viable option for the virtualization of scientific instruments., Comment: Submission to Machine Learning and the Physical Sciences Workshop, NeurIPS 2023

The broad physics reach of the LUX-ZEPLIN (LZ) experiment covers rare phenomena beyond the direct detection of dark matter. We report precise measurements of the extremely rare decay of $^{124}$Xe through the process of two-neutrino double electron capture (2$\nu$2EC), utilizing a $1.39\,\mathrm{kg} \times \mathrm{yr}$ isotopic exposure from the first LZ science run. A half-life of $T_{1/2}^{2\nu2\mathrm{EC}} = (1.09 \pm 0.14_{\text{stat}} \pm 0.05_{\text{sys}}) \times 10^{22}\,\mathrm{yr}$ is observed with a statistical significance of $8.3\,\sigma$, in agreement with literature. First empirical measurements of the KK capture fraction relative to other K-shell modes were conducted, and demonstrate consistency with respect to recent signal models at the $1.4\,\sigma$ level., Comment: 15 pages, 3 figures

We present the most comprehensive and deepest X-ray study to date of the properties of the richest Wolf-Rayet (WR) population observed in a single stellar cluster, Westerlund 1 (Wd1). This work is based on 36 Chandra observations obtained from the "Extended Westerlund 1 and 2 Open Clusters Survey" (EWOCS) project, plus 8 archival Chandra observations. The overall exposure depth (~1.1 Ms) and baseline of the EWOCS observations extending over more than one year enable us to perform a detailed photometric, colour, and spectral analysis, as well as to search for short- and long-term periodicity. In X-rays, we detect 20 out of the 24 known Wolf-Rayet stars in Wd1 down to an observed luminosity of ~7$\times10^{29}$erg s$^{-1}$ (assuming a distance of 4.23 kpc to Wd1), with 8 WR stars being detected in X-rays for the first time. Nine stars show clear evidence of variability over the year-long baseline, with clear signs of periodicity. The X-ray colours and spectral analysis reveal that the vast majority of the WR stars are hard X-ray sources (kT$\geq$2.0keV). The Fe XXV emission line at ~6.7 keV, which commonly originates from the wind-wind collision zone in binary systems, is detected for the first time in the spectra of 17 WR stars in Wd1. In addition the ~6.4 keV fluorescent line is observed in the spectra of three stars, indicating that dense cold material coexists with the hot gas in these systems. Overall, our X-ray results alone suggest a very high binary fraction ($\geq$80%) for the WR star population in Wd1. When combining our results with properties of the WR population from other wavelengths, we estimate a binary fraction of $\geq$92%, which could even reach unity. This suggests that either all the most massive stars are found in binary systems within Wd1, or that binarity is essential for the formation of such a rich population of WR stars., Comment: 20 pages, 11 figures, 6 tables, accepted for publication in A&A

Utilizing the Apostle--Auriga simulations, which start from the same zoom-in initial conditions of Local Group-like systems but run with different galaxy formation subgrid models and hydrodynamic solvers, we study the impact of stellar feedback models on the evolution of angular momentum in disc galaxies. At $z = 0$, Auriga disc galaxies tend to exhibit higher specific angular momenta compared to their cross-matched Apostle counterparts. By tracing the evolution history of the Lagrangian mass tracers of the in-situ star particles in the $z = 0$ galaxies, we find that the specific angular momentum distributions of the gas tracers from the two simulations at the halo accretion time are relatively similar. The present-day angular momentum difference is mainly driven by the physical processes occurring inside dark matter haloes, especially galactic fountains. Due to the different subgrid implementations of stellar feedback processes, Auriga galaxies contain a high fraction of gas that has gone through recycled fountain (${\sim} 65$ per cent) which could acquire angular momentum through mixing with the high angular momentum circumgalactic medium (CGM). In Apostle, however, the fraction of gas that has undergone the recycled fountain process is significantly lower (down to ${\sim} 20$ per cent for Milky Way-sized galaxies) and the angular momentum acquisition from the CGM is marginal. As a result, the present-day Auriga galaxies overall have higher specific angular momenta., Comment: after revised, accepted for publication in MNRAS

Aerosol interactions with clouds represent a significant uncertainty in our understanding of the Earth system. Deep convective clouds may respond to aerosol perturbations in several ways that have proven difficult to elucidate with observations. Here, we leverage the two busiest maritime shipping lanes in the world, which emit aerosol particles and their precursors into an otherwise relatively clean tropical marine boundary layer, to make headway on the influence of aerosol on deep convective clouds. The recent seven-fold change in allowable fuel sulfur by the International Maritime Organization allows us to test the sensitivity of the lightning to changes in ship plume aerosol size distributions. We find that, across a range of atmospheric thermodynamic conditions, the previously documented enhancement of lightning over the shipping lanes has fallen by over 40%. The enhancement is therefore at least partially aerosol-mediated, a conclusion that is supported by observations of droplet number at cloud base, which show a similar decline over the shipping lane. These results have fundamental implications for our understanding of aerosol-cloud interactions, suggesting that deep convective clouds are impacted by the aerosol number distribution in the remote marine environment.

We revisit the problem of federated learning (FL) with private data from people who do not trust the server or other silos/clients. In this context, every silo (e.g. hospital) has data from several people (e.g. patients) and needs to protect the privacy of each person's data (e.g. health records), even if the server and/or other silos try to uncover this data. Inter-Silo Record-Level Differential Privacy (ISRL-DP) prevents each silo's data from being leaked, by requiring that silo i's communications satisfy item-level differential privacy. Prior work arXiv:2106.09779 characterized the optimal excess risk bounds for ISRL-DP algorithms with homogeneous (i.i.d.) silo data and convex loss functions. However, two important questions were left open: (1) Can the same excess risk bounds be achieved with heterogeneous (non-i.i.d.) silo data? (2) Can the optimal risk bounds be achieved with fewer communication rounds? In this paper, we give positive answers to both questions. We provide novel ISRL-DP FL algorithms that achieve the optimal excess risk bounds in the presence of heterogeneous silo data. Moreover, our algorithms are more communication-efficient than the prior state-of-the-art. For smooth loss functions, our algorithm achieves the optimal excess risk bound and has communication complexity that matches the non-private lower bound. Additionally, our algorithms are more computationally efficient than the previous state-of-the-art., Comment: The 41st International Conference on Machine Learning (ICML 2024)

The metal content of galaxies is a direct probe of the baryon cycle. A hallmark example is the relationship between a galaxy's stellar mass, star formation rate (SFR), and gas-phase metallicity: the Fundamental Metallicity Relation (FMR). While low-redshift ($z\lesssim4$) observational studies suggest that the FMR is redshift-invariant, recent high-$z$ JWST data indicate deviations from the FMR established at low-$z$. In this study, we utilize the FMR to predict the evolution of the normalisation of the mass-metallicity relation (MZR) using the cosmological simulations Illustris, IllustrisTNG, EAGLE, and SIMBA. Our findings demonstrate that a $z = 0$ calibrated FMR struggles to predict the evolution in the MZR of each simulation. To quantify the divergence of the predictions, we introduce the concepts of a ``static'' FMR, where the role of the SFR in setting the normalization of the MZR does not change with redshift, and a ``dynamic'' FMR, where the role of SFR evolves over time. We find static FMRs in SIMBA and dynamic FMRs in Illustris, IllustrisTNG and EAGLE. We suggest that the differences between these models likely points to the subtle differences in the implementation of the baryon cycle. Moreover, we echo recent JWST results at $z > 4$ by finding significant offsets from the FMR in IllustrisTNG and EAGLE, suggesting that the observed FMR may have a similar dynamic trend as these simulations. Overall, our findings imply that the current FMR framework neglects important time variations of these simulations' baryon cycles., Comment: Accepted to MNRAS. 17 pages, 8 Figures. See also paper one of series (arXiv:2403.08856)

The recent discoveries of Neptune-sized ultra-short period planets (USPs) challenge existing planet formation theories. It is unclear whether these residents of the Hot Neptune Desert have similar origins to smaller, rocky USPs, or if this discrete population is evidence of a different formation pathway altogether. We report the discovery of TOI-3261b, an ultra-hot Neptune with an orbital period $P$ = 0.88 days. The host star is a $V = 13.2$ magnitude, slightly super-solar metallicity ([Fe/H] $\simeq$ 0.15), inactive K1.5 main sequence star at $d = 300$ pc. Using data from the Transiting Exoplanet Survey Satellite and the Las Cumbres Observatory Global Telescope, we find that TOI-3261b has a radius of $3.82_{-0.35}^{+0.42}$ $R_{\oplus}$. Moreover, radial velocities from ESPRESSO and HARPS reveal a mass of $30.3_{-2.4}^{+2.2}$ $M_{\oplus}$, more than twice the median mass of Neptune-sized planets on longer orbits. We investigate multiple mechanisms of mass loss that can reproduce the current-day properties of TOI-3261b, simulating the evolution of the planet via tidal stripping and photoevaporation. Thermal evolution models suggest that TOI-3261b should retain an envelope potentially enriched with volatiles constituting $\sim$5% of its total mass. This is the second highest envelope mass fraction among ultra-hot Neptunes discovered to date, making TOI-3261b an ideal candidate for atmospheric follow-up observations., Comment: 20 pages, 11 figures, accepted to AJ

Context: Star clusters, composed of stars born from the same molecular cloud, serve as invaluable natural laboratories for understanding the fundamental processes governing stellar formation and evolution. Aims: This study aims to investigate correlations between the Mean Interdistance ($\bar{D_{i}}$), Mean Closest Interdistance ($\bar{D_{c}}$) and Median Weighted Central Interdistance ($\bar{D_{cc}}$) with the age of star clusters, examining their evolutionary trends and assessing the robustness of these quantities as possible age indicators. Methods: We selected a sample of open clusters in the solar region and with a representative number of members (e.g. well populated and without outliers). The interdistances are derived from the spatial distribution of member stars within a cluster. Their evolution over time allows us to use them as an age indicators for star clusters. Results: Our investigation reveals a high-significant correlation between the interdistances and cluster age. Considering the full sample of clusters between 7 and 9 kpc, the relationship is very broad. This is due to uncertainties in parallax, which increase with increasing distance. In particular, we must limit the sample to a maximum distance from the Sun of about 200 pc to avoid artificial effects on cluster shape and on the spatial distribution of their stars along the line of sight. Conclusions: By conservatively restraining the distance to a maximum of $\sim$200 pc, we have established a relationship between the interdistances and the age of the clusters. In our sample, the relationship is mainly driven by the internal expansion of the clusters, and is marginally affected by external perturbative effects. Such relation might enhance our comprehension of cluster dynamics and might be used to derive cluster dynamical ages., Comment: This paper was accepted for publication in Astronomy & Astrophysics on June 28, 2024. The document includes 9 main figures and 4 additional figures in the appendix. Additionally, it contains one main table and an extract of another table in the appendix, available at the CDS

We report the discovery and validation of HD 21520 b, a transiting planet found with TESS and orbiting a bright G dwarf (V=9.2, $T_{eff} = 5871 \pm 62$ K, $R_{\star} = 1.04\pm 0.02\, R_{\odot}$). HD 21520 b was originally alerted as a system (TOI-4320) consisting of two planet candidates with periods of 703.6 and 46.4 days. However, our analysis supports instead a single-planet system with an orbital period of $25.1292\pm0.0001$ days and radius of $2.70 \pm 0.09\, R_{\oplus}$. Three full transits in sectors 4, 30 and 31 match this period and have transit depths and durations in agreement with each other, as does a partial transit in sector 3. We also observe transits using CHEOPS and LCOGT. SOAR and Gemini high-resolution imaging do not indicate the presence of any nearby companions, and MINERVA-Australis and CORALIE radial velocities rule out an on-target spectroscopic binary. Additionally, we use ESPRESSO radial velocities to obtain a tentative mass measurement of $7.9^{+3.2}_{-3.0}\, M_{\oplus}$, with a 3-$\sigma$ upper limit of 17.7 $M_{\oplus}$. Due to the bright nature of its host and likely significant gas envelope of the planet, HD 21520 b is a promising candidate for further mass measurements and for atmospheric characterization., Comment: Submitted to MNRAS

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of $1.5\times10^{-46}$~cm$^2$ at a 90\% confidence level for a WIMP mass of 33~GeV/c$^2$ for this interaction.

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. The hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described., Comment: 18 pages, 24 figures

The spatial-kinematic structure of 48 young star clusters and associations is investigated. Moran's $I$ statistic is used to quantify the degree of kinematic substructure in each region, and the results are compared to those expected assuming the hierarchical or monolithic models of star cluster formation. Of the observed regions, 39 are found to have significant kinematic substructure, such that they are compatible with the hierarchical model and incompatible with the monolithic model. This includes multiple regions whose $Q$ parameter shows the region to be centrally concentrated and clustered. The remaining nine are compatible with both models. From this it is concluded that the kinematic substructure of the observed star clusters represents strong evidence in favour the hierarchical model of star cluster formation over the monolithic model., Comment: Accepted for publication in MNRAS. 13 pages, 10 figures

LUX-ZEPLIN (LZ) is a tonne-scale experiment searching for direct dark matter interactions and other rare events. It is located at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. The core of the LZ detector is a dual-phase xenon time projection chamber (TPC), designed with the primary goal of detecting Weakly Interacting Massive Particles (WIMPs) via their induced low energy nuclear recoils. Surrounding the TPC, two veto detectors immersed in an ultra-pure water tank enable reducing background events to enhance the discovery potential. Intricate calibration systems are purposely designed to precisely understand the responses of these three detector volumes to various types of particle interactions and to demonstrate LZ's ability to discriminate between signals and backgrounds. In this paper, we present a comprehensive discussion of the key features, requirements, and performance of the LZ calibration systems, which play a crucial role in enabling LZ's WIMP-search and its broad science program. The thorough description of these calibration systems, with an emphasis on their novel aspects, is valuable for future calibration efforts in direct dark matter and other rare-event search experiments.

The first science run of the LUX-ZEPLIN (LZ) experiment, a dual-phase xenon time project chamber operating in the Sanford Underground Research Facility in South Dakota, USA, has reported leading limits on spin-independent WIMP-nucleon interactions and interactions described from a non-relativistic effective field theory (NREFT). Using the same 5.5~t fiducial mass and 60 live days of exposure we report on the results of a relativistic extension to the NREFT. We present constraints on couplings from covariant interactions arising from the coupling of vector, axial currents, and electric dipole moments of the nucleon to the magnetic and electric dipole moments of the WIMP which cannot be described by recasting previous results described by an NREFT. Using a profile-likelihood ratio analysis, in an energy region between 0~keV$_\text{nr}$ to 270~keV$_\text{nr}$, we report 90% confidence level exclusion limits on the coupling strength of five interactions in both the isoscalar and isovector bases., Comment: 7 pages, 4 figures

The most active phases of star formation and black hole accretion are strongly affected by dust extinction, making far-infrared (far-IR) observations the best way to disentangle and study the co-evolution of galaxies and super massive black holes. The plethora of fine structure lines and emission features from dust, ionised and neutral atomic and warm molecular gas in the rest-frame mid- and far-IR provide unmatched diagnostic power to determine the properties of gas and dust, measure gas-phase metallicities and map cold galactic outflows in even the most obscured galaxies. By combining multi-band photometric surveys with low and high-resolution far-IR spectroscopy, the PRobe far-Infrared Mission for Astrophysics (PRIMA), a concept for a far-IR, 1.8m-diameter, cryogenically cooled observatory, will revolutionise the field of galaxy evolution by taking advantage of this IR toolkit to find and study dusty galaxies across galactic time. In this work, we make use of the phenomenological simulation SPRITZ and the Santa Cruz semi-analytical model to describe how a moderately deep multi-band PRIMA photometric survey can easily reach beyond previous IR missions to detect and study galaxies down to $10^{11}\,L_{\odot}$ beyond cosmic noon and at least up to z=4, even in the absence of gravitational lensing. By decomposing the spectral energy distribution (SED) of these photometrically selected galaxies, we show that PRIMA can be used to accurately measure the relative AGN power, the mass fraction contributed by polycyclic aromatic hydrocarbon (PAH) and the total IR luminosity. At the same time, spectroscopic follow up with PRIMA will allow to trace both the star formation and black hole accretion rates (SFR, BHAR), the gas phase metallicities and the mass outflow rates of cold gas in hundreds to thousands of individual galaxies to z=2., Comment: 16 pages, 17 figures, accepted for publication in A&A

Optical imaging quality can be severely degraded by system and sample induced aberrations. Existing adaptive optics systems typically rely on iterative search algorithm to correct for aberrations and improve images. This study demonstrates the application of convolutional neural networks to characterise the optical aberration by directly predicting the Zernike coefficients from two to three phase-diverse optical images. We evaluated our network on 600,000 simulated Point Spread Function (PSF) datasets randomly generated within the range of -1 to 1 radians using the first 25 Zernike coefficients. The results show that using only three phase-diverse images captured above, below and at the focal plane with an amplitude of 1 achieves a low RMSE of 0.10 radians on the simulated PSF dataset. Furthermore, this approach directly predicts Zernike modes simulated extended 2D samples, while maintaining a comparable RMSE of 0.15 radians. We demonstrate that this approach is effective using only a single prediction step, or can be iterated a small number of times. This simple and straightforward technique provides rapid and accurate method for predicting the aberration correction using three or less phase-diverse images, paving the way for evaluation on real-world dataset., Comment: 12 pages, 6 figures, 4 tables