Search

We present the discovery of twelve metal-poor and distant pre-main sequence (PMS) candidates in the dwarf irregular galaxy Wolf-Lundmark-Melotte (WLM)~968 kpc away, at a present-day metallicity of [Fe/H] around $-$0.9. These candidates have masses between 1.25-5 M$_{\odot}$, with ages <10 Myr, and exhibit significant near-infrared excesses at 2.5 and 4.3 $\mu$m. They are concentrated within a cluster roughly 10 pc (2'') across situated in the HII region [HM95]-9. These are the most distant and metal-poor PMS stars known, and can offer new quantitative insights into star formation at low-metallicities., Comment: Accepted for publication in ApJ Letters. Comments welcome. 6 pages, 4 figures, and 1 table

We present the spectral analysis of J-138717, a post-starburst galaxy observed at $z=1.8845$ with JWST, for which we estimate a stellar mass M$_* = 3.5\pm0.2\times10^{10}$M$_\odot$ and velocity dispersion $\sigma_* = 198\pm10$ km/s. From the fits of the NIRspec low-resolution prism and medium resolution grating spectra, we estimate an age of $\sim0.9$ Gyr, a metallicity of $\sim -0.3$ dex, and a dust attenuation A$_{\rm V} \sim 0.7$ mag. From the H$\alpha$ and [OII] emission lines we derive a star-formation rate (SFR)$\sim 0.1$ M$_\odot$ yr$^{-1}$, corresponding to a specific SFR$\sim 4 \times 10^{-12}$ yr$^{-1}$. By reconstructing its SFH, we find that this galaxy formed most of its stellar mass quickly ($0.4-0.8$ Gyr) and then rapidly quenched about 0.4 Gyr lookback time. The analysis of the emission lines ([OII], [NeIII], [OIII], H$\alpha$, and [NII]) indicates a low-level residual star formation or a weak AGN as the ionization source. Further, the lack of evidence for ongoing outflows in both the absorption and emission lines tracing the neutral and ionized gas argues against the presence of strong AGN feedback. Thanks to the high quality of the data, we carried out a comprehensive analysis of the NIR spectral indices. This is the first time NIR spectral indices have been investigated at such a high redshift. We find that the observed CO and CN indices are generally weak and in better agreement with models with a lower contribution from thermally pulsating (TP-)AGB stars, indicating that either TP-AGB stars do not contribute significantly to the spectrum of J-138717 or the prescriptions in the models for these evolved phases should be substantially improved. In general, we find that all models struggle to reproduce the NIR indices consistently, pointing to the importance of improving state-of-the-art stellar population models in the NIR, especially at young ages., Comment: submitted to Astronomy & Astrophysics

This paper proposes a Direct Rational Radial Basis Functions Partition of Unity (D-RRBF-PU) approach to compute derivatives of functions with steep gradients or discontinuities. The novelty of the method concerns how derivatives are approximated. More precisely, all derivatives of the partition of unity weight functions are eliminated while we compute the derivatives of the local rational approximants in each patch. As a result, approximate derivatives are obtained more easily and quickly than those obtained in the standard formulation. The corresponding error bounds are briefly discussed. Some numerical results are presented to show the technique's potential., Comment: 7 pages, 4 figures

The study of interpolation nodes and their associated Lebesgue constants are central to numerical analysis, impacting the stability and accuracy of polynomial approximations. In this paper, we will explore the Morrow-Patterson points, a set of interpolation nodes introduced to construct cubature formulas of a minimum number of points in the square for a fixed degree $n$. We prove that their Lebesgue constant growth is ${\cal O}(n^2)$ as was conjectured based on numerical evidence about twenty years ago in the paper by Caliari, M., De Marchi, S., Vianello, M., {\it Bivariate polynomial interpolation on the square at new nodal sets}, Appl. Math. Comput. 165(2) (2005), 261--274.

Use real word data to evaluate the performance of the electrocardiographic markers of GEH as features in a machine learning model with Standard ECG features and Risk Factors in Predicting Outcome of patients in a population referred to a tertiary cardiology hospital. Patients forwarded to specific evaluation in a cardiology specialized hospital performed an ECG and a risk factor anamnesis. A series of follow up attendances occurred in periods of 6 months, 12 months and 15 months to check for cardiovascular related events (mortality or new nonfatal cardiovascular events (Stroke, MI, PCI, CS), as identified during 1-year phone follow-ups. The first attendance ECG was measured by a specialist and processed in order to obtain the global electric heterogeneity (GEH) using the Kors Matriz. The ECG measurements, GEH parameters and risk factors were combined for training multiple instances of XGBoost decision trees models. Each instance were optmized for the AUCPR and the instance with higher AUC is chosen as representative to the model. The importance of each parameter for the winner tree model was compared to better understand the improvement from using GEH parameters. The GEH parameters turned out to have statistical significance for this population specially the QRST angle and the SVG. The combined model with the tree parameters class had the best performance. The findings suggest that using VCG features can facilitate more accurate identification of patients who require tertiary care, thereby optimizing resource allocation and improving patient outcomes. Moreover, the decision tree model's transparency and ability to pinpoint critical features make it a valuable tool for clinical decision-making and align well with existing clinical practices.

Previous Hubble Space Telescope (HST) observations of the star-forming cluster NGC 346 in the Small Magellanic Cloud (SMC) had revealed a large population of pre-main sequence (PMS) candidates, characterised by Halpha excess emission in their photometry. However, without access to spectroscopy, the nature of these objects remained unclear. Using the NIRSpec instrument on board JWST, we studied a sample of these stars, with masses in the range ~0.9-1.8 Msun, effective temperatures in the range 4,500-8,000 K, and PMS ages between ~0.1 and 30 Myr. Here we present the first spectra of solar-mass PMS stars in the metal-poor SMC (Z=1/8 Zsun) and discuss the physical properties of ten representative sources with good signal-to-noise ratio. The observations indicate that even the oldest of these PMS candidates are still accreting gas with typical rates of ~10^{-8} Msun/yr for stars older than ~10 Myr, confirming their PMS nature. The spectra also reveal near-infrared excess and molecular hydrogen excitation lines consistent with the presence of discs around these stars. These findings suggest that in a low-metallicity environment circumstellar discs can live longer than previously thought., Comment: 17 pages, 7 figures, to be published in The Astrophysical Journal, Vol 977, Article 214

Models of blazar jets, that explain observations of their photon spectra, typically predict too few neutrinos to be possibly seen by existing telescopes. In particular, they fall short in reproducing the first neutrino ever detected from a blazar, TXS 0506+056, by IceCube in 2017. We predict larger neutrino fluxes by using the same jet models, extended to include deep inelastic scatterings between protons within the jets and sub-GeV dark matter (DM) around the central black holes of blazars. In this way we succeed in explaining neutrino observations of TXS 0506+056, for DM parameters allowed by all laboratory, direct and indirect searches. Our proposal will be tested by DM searches, as well as by the observation of more neutrinos from blazars. Our findings motivate to implement DM-nuclei interactions in jet models and to improve our knowledge of DM spikes around active galactic nuclei., Comment: v2: clarifications added, Supplemental Material extended with more details; 12 pages (including Supplemental Material), 6 captioned figures, 1 table

Hydrogen emission lines are routinely used to estimate the mass accretion rate of pre-main-sequence stars. Despite the clear correlation between the accretion luminosity of a star and hydrogen line luminosities, the physical origin of these lines is still unclear, with magnetospheric accretion and magneto-centrifugal winds as the two most often invoked mechanisms. Using a combination of HST photometry and new JWST NIRSpec spectra, we have analysed the SED and emission line spectra of five sources in order to determine their underlying photospheric properties, and to attempt to reveal the physical origin of their hydrogen emission lines. These sources reside in NGC 3603, a Galactic massive star forming region. We have fitted the SED of the five sources employing a Markov Chain Monte Carlo exploration to estimate $T_{eff}$, $R_{*}$, $M_{*}$ and $A(V)$ for each source. We have performed a kinematic analysis across three spectral series of hydrogen lines, Paschen, Brackett, and Pfund, totalling $\ge 15$ lines. The FWHM and optical depth of the spectrally resolved lines have been studied in order to constrain the emission origin. The five sources all have SEDs consistent with young intermediate-mass stars. We have classified three of these sources as Herbig Ae type stars based on their effective temperature. Their hydrogen lines show broad profiles with FWHMs $\ge 200$ km s$^{-1}$. Hydrogen lines with high upper energy levels $n_{up}$ tend to be significantly broader than lines with lower $n_{up}$. The optical depth of the emission lines is also highest for the high velocity component of each line, becoming optically thin in the low velocity component. This is consistent with emission from a magnetospheric accretion flow, and cannot be explained as originating in a magneto-centrifugal wind, or other line emission mechanisms thought to be present in protoplanetary disks.

NGC 3603 is the optically brightest massive star forming region (SFR) in the Milky Way, representing a small scale starburst region. Studying young stars in regions like this allows us to assess how star and planet formation proceeds in a dense clustered environment with high levels of UV radiation. JWST provides the sensitivity, unbroken wavelength coverage, and spatial resolution required to study individual pre-main-sequence (PMS) stars in distant massive SFRs in detail for the first time. Using the Micro-Shutter Assembly (MSA) onboard the Near InfraRed Spectrograph (NIRSpec), multi-object spectroscopy was performed, yielding 100 stellar spectra. We fit the PMS spectra to derive their photospheric properties, extinction, and NIR veiling. From this, we determined the masses and ages of our sources by placing them on the Hertzsprung-Russel diagram (HRD). Their accretion rates were determined by converting the luminosity of hydrogen emission lines to an accretion luminosity. We have classified 42 as actively accreting. Our sources span a range of masses from 0.5 to 7 $M_{\odot}$. Twelve of these accreting sources have ages consistent with $\ge$ 10 Myrs, with four having ages of $\ge$ 15 Myrs. Their mass accretion rates span 5 orders of magnitude and are systematically higher for a given stellar mass than for a comparative sample taken from low-mass SFRs. We report an environmental relationship between $\dot{M}_{acc}$ and the density of ambient molecular gas as traced by nebular $H_2$ emission.

Optical data center networks (DCNs) are emerging as a promising solution for cloud infrastructure in the post-Moore's Law era, particularly with the advent of 'fast-switched' optical architectures capable of circuit reconfiguration at microsecond or even nanosecond scales. However, frequent reconfiguration of optical circuits introduces a unique challenge: in-flight packets risk loss during these transitions, hindering the deployment of many mature optical hardware designs due to the lack of suitable routing solutions. In this paper, we present Unified Routing for Optical networks (URO), a general routing framework designed to support fast-switched optical DCNs across various hardware architectures. URO combines theoretical modeling of this novel routing problem with practical implementation on programmable switches, enabling precise, time-based packet transmission. Our prototype on Intel Tofino2 switches achieves a minimum circuit duration of 2us, ensuring end-to-end, loss-free application performance. Large-scale simulations using production DCN traffic validate URO's generality across different hardware configurations, demonstrating its effectiveness and efficient system resource utilization.

Optical data center networks (DCNs) are emerging as a promising design for cloud infrastructure. However, existing optical DCN architectures operate as closed ecosystems, tying software solutions to specific optical hardware. We introduce Lighthouse, an open research framework that decouples software from hardware, allowing them to evolve independently. Central to Lighthouse is the time-flow table abstraction, serving as a common interface between optical hardware and software. We develop Lighthouse on programmable switches, achieving a minimum optical circuit duration of 2 {\mu}s, the shortest duration realized by commodity devices to date. We demonstrate Lighthouse's generality by implementing six optical architectures on an optical testbed and conducted extensive benchmarks on a 108-ToR setup, highlighting system efficiency. Additionally, we present case studies that identify potential research topics enabled by Lighthouse.

Polynomial reproduction plays a relevant role in deriving error estimates for various approximation schemes. Local reproduction in a quasi-uniform setting is a significant factor in the estimation of error and the assessment of stability but for some computationally relevant schemes, such as Rescaled Localized Radial Basis Functions (RL-RBF), it becomes a limitation. To facilitate the study of a greater variety of approximation methods in a unified and efficient manner, this work proposes a framework based on fast decaying polynomial reproduction: we do not restrict to compactly supported basis functions, but we allow the basis function decay to infinity as a function of the separation distance. Implementing fast decaying polynomial reproduction provides stable and convergent methods, that can be smooth when approximating by moving least squares otherwise very efficient in the case of linear programming problems. All the results presented in this paper concerning the rate of convergence, the Lebesgue constant, the smoothness of the approximant, and the compactness of the support have been verified numerically, even in the multivariate setting.

This work proposes to model the space environment as a stochastic dynamic network where each node is a group of objects of a given class, or species, and their relationship is represented by stochastic links. A set of stochastic dynamic equations, governing the evolution of the network, are derived from the network structure and topology. It will be shown that the proposed system of stochastic dynamic equations well reproduces existing results on the evolution of the space environment. The analysis of the structure of the network and relationships among node can help to understand which species of objects and orbit regimes are more critical and affect the most the future evolution of the space environment. In analogy with ecological networks, we develop a theory of the carrying capacity of space based on the stability of equilibria of the network dynamics. Some examples are presented starting from the current population of resident objects and different launch traffic forecast models. It will be shown how the proposed network model can be used to study the effect of the adoption of different policies on the execution of collision avoidance and post mission disposal manoeuvres., Comment: 40 pages, 28 figures, 8 tables

Shapley values have seen widespread use in machine learning as a way to explain model predictions and estimate the importance of covariates. Accurately explaining models is critical in real-world models to both aid in decision making and to infer the properties of the true data-generating process (DGP). In this paper, we demonstrate that while model-based Shapley values might be accurate explainers of model predictions, machine learning models themselves are often poor explainers of the DGP even if the model is highly accurate. Particularly in the presence of interrelated or noisy variables, the output of a highly predictive model may fail to account for these relationships. This implies explanations of a trained model's behavior may fail to provide meaningful insight into the DGP. In this paper we introduce a novel variable importance algorithm, Shapley Marginal Surplus for Strong Models, that samples the space of possible models to come up with an inferential measure of feature importance. We compare this method to other popular feature importance methods, both Shapley-based and non-Shapley based, and demonstrate significant outperformance in inferential capabilities relative to other methods.

The aim of the present work is a comparative study of different persistence kernels applied to various classification problems. After some necessary preliminaries on homology and persistence diagrams, we introduce five different kernels that are then used to compare their performances of classification on various datasets. We also provide the Python codes for the reproducibility of results., Comment: 23 pages, 13 figures

Necessary optimality conditions in Lagrangian form and the augmented Lagrangian framework are extended to mixed-integer nonlinear optimization, without any convexity assumptions. Building upon a recently developed notion of local optimality for problems with polyhedral and integrality constraints, a characterization of local minimizers and critical points is given for problems including also nonlinear constraints. This approach lays the foundations for developing affordable sequential minimization algorithms with convergence guarantees to critical points from arbitrary initializations. A primal-dual perspective, a local saddle point property, and the dual relationships with the proximal point algorithm are also advanced in the presence of integer variables., Comment: 18 pages, added motivating example

Focusing on minimization problems with structured objective function and smooth constraints, we present a flexible technique that combines the beneficial regularization effects of (exact) penalty and interior-point methods. Working in the fully nonconvex setting, a pure barrier approach requires careful steps when approaching the infeasible set, thus hindering convergence. We show how a tight integration with a penalty scheme overcomes such conservatism, does not require a strictly feasible starting point, and thus accommodates equality constraints. The crucial advancement that allows us to invoke generic (possibly accelerated) subsolvers is a marginalization step: closely related to a conjugacy operation, this step effectively merges (exact) penalty and barrier into a smooth, full domain functional object. When the penalty exactness takes effect, the generated subproblems do not suffer the ill-conditioning typical of barrier methods, nor do they exhibit the nonsmoothness of exact penalty terms. We provide a theoretical characterization of the algorithm and its asymptotic properties, deriving convergence results for fully nonconvex problems. Stronger conclusions are available for the convex setting, where optimality can be guaranteed. Illustrative examples and numerical simulations demonstrate the wide range of problems our theory and algorithm are able to cover.

Context. A necessary ingredient in understanding the star formation history of a young cluster is knowledge of the extinction towards the region. This has typically been done by making use of the colour-difference method with photometry, or similar methods utilising the colour-colour diagram. Aims. The colour-excess can be independently determined by studying the decrements of the recombination lines produced by the nebular gas. Having access to many recombination lines from the same spectral series removes the need of adopting an extinction curve. Methods. Using the Micro-Shutter Assembly (MSA) on board the Near InfraRed Spectrograph (NIRSpec), multi-object spectroscopy was performed, yielding 600 nebular spectra from the Galactic massive star formation region NGC 3603. The recombination line intensity ratios were used to determine independent values of colour-excess. Results. The extinction characteristics of NGC 3603 are similar to other Galactic HII regions like Orion, as well as starburst regions such 30 Doradus in the Large Magellanic Cloud, in that we find a relatively large value of total-to-selective extinction of 4.8 $\pm$ 1.06, larger than the Galactic average of 3.1. We find a typical value for the colour-excess of 0.64 $\pm$ 0.27, significantly lower than values determined in previous studies. We also present a stacked nebular spectrum with a typical continuum S/N = 70. This spectrum highlights the recombination lines of the HII region, several s-process elements such as Kr III and Se IV, and molecular H2 emission lines. Conclusions. Using ratios of hydrogen recombination lines, we calculated the total-to-selective extinction, colour-excess and visual extinction for > 200 lines of sight across NGC 3603. An extinction curve with a total-to-selective extinction of 4.8 $\pm$ 1.06 was found, corresponding to a colour-excess of 0.64 $\pm$ 0.27.

We compute the flux of relic neutrino background (R$\nu$B) up-scattered by ultra-high-energy (UHE) cosmic rays (CRs) in clusters that act as CR-reservoirs. The long trapping times of UHECRs make this flux larger than that of R$\nu$B up-scattered by UHECRs on their way to Earth, which we also compute. We find that IceCube excludes R$\nu$B weighted overdensities larger than $10^{10}$ in clusters, and that PUEO, RNO-G, GRAND and IceCube-Gen2 will test values down to $10^{8}$. Our treatment incorporates the momentum transfer dependence of the neutrino-nucleus cross section, deep inelastic scattering, a mixed UHECR composition, and flavour information on the up-scattered R$\nu$B fluxes for both cases of neutrino mass spectrum with normal and inverted ordering, providing new handles to possibly disentangle the up-scattered R$\nu$B from cosmogenic neutrinos., Comment: 13 pages (with appendices), 4 figures, 1 table. Version accepted for publication in Physical Review D

In this work, we study the Kantorovich variant of max-min neural network operators, in which the operator kernel is defined in terms of sigmoidal functions. Our main aim is to demonstrate the $L^{p}$-convergence of these nonlinear operators for $1\leq p<\infty$, which makes it possible to obtain approximation results for functions that are not necessarily continuous. In addition, we will derive quantitative estimates for the rate of approximation in the $L^{p}$-norm. We will provide some explicit examples, studying the approximation of discontinuous functions with the max-min operator, and varying additionally the underlying sigmoidal function of the kernel. Further, we numerically compare the $L^{p}$-approximation error with the respective error of the Kantorovich variants of other popular neural network operators. As a final application, we show that the Kantorovich variant has advantages compared to the sampling variant of the max-min operator and Kantorovich variant of the max-product operator when it comes to approximate noisy functions as for instance biomedical ECG signals., Comment: 23 pages, 6 figures

We present a JWST imaging survey with NIRCam and MIRI of NGC 346, the brightest star-forming region in the Small Magellanic Cloud (SMC). By combining aperture and point spread function (PSF) photometry of eleven wavelength bands across these two instruments, we have detected more than 200,000 unique sources. Using near-infrared (IR) color analysis, we observe various evolved and young populations, including 196 young stellar objects (YSOs) and pre-main sequence stars suitable for forthcoming spectroscopic studies. We expand upon this work, creating mid-IR color-magnitude diagrams and determining color cuts to identify 833 reddened sources which are YSO candidates. We observe that these candidate sources are spatially associated with regions of dusty, filamentary nebulosity. Furthermore, we fit model YSO spectral energy distributions (SEDs) to a selection of sources with detections across all of our MIRI bands. We classify with a high degree of confidence 23 YSOs in this sample and estimate their radii, bolometric temperatures, luminosities, and masses. We detect YSOs approaching 1 solar mass, the lowest-mass extragalactic YSOs confirmed to date.

JWST/NIRCam obtained high angular-resolution (0.05-0.1''), deep near-infrared 1--5 micron imaging of Supernova (SN) 1987A taken 35 years after the explosion. In the NIRCam images, we identify: 1) faint H2 crescents, which are emissions located between the ejecta and the equatorial ring, 2) a bar, which is a substructure of the ejecta, and 3) the bright 3-5 micron continuum emission exterior to the equatorial ring. The emission of the remnant in the NIRCam 1-2.3 micron images is mostly due to line emission, which is mostly emitted in the ejecta and in the hot spots within the equatorial ring. In contrast, the NIRCam 3-5 micron images are dominated by continuum emission. In the ejecta, the continuum is due to dust, obscuring the centre of the ejecta. In contrast, in the ring and exterior to the ring, synchrotron emission contributes a substantial fraction to the continuum. Dust emission contributes to the continuum at outer spots and diffuse emission exterior to the ring, but little within the ring. This shows that dust cooling and destruction time scales are shorter than the synchrotron cooling time scale, and the time scale of hydrogen recombination in the ring is even longer than the synchrotron cooling time scale. With the advent of high sensitivity and high angular resolution images provided by JWST/NIRCam, our observations of SN 1987A demonstrate that NIRCam opens up a window to study particle-acceleration and shock physics in unprecedented details, probed by near-infrared synchrotron emission, building a precise picture of how a SN evolves., Comment: Accepted for publication in MNRAS; 18 pages

We present a detailed study of the centre of NGC4654, a Milky Way-like spiral galaxy in the Virgo cluster that has been reported to host a double stellar nucleus, thus promising a rare view of ongoing star cluster infall into a galaxy nucleus. Analysing JWST NIRSpec integral-field spectroscopic data and Hubble Space Telescope imaging of the inner 330 $\times$ 330 pc, we find that the nucleus harbours in fact three massive star clusters. Maps of infrared emission lines from NIRSpec show different morphologies for the ionised and molecular gas components. The emission from molecular hydrogen gas is concentrated at the NSC location, while emission from hydrogen recombination lines is more extended beyond the central cluster. The velocity fields of both gas and stars indicate that the three clusters are part of a complicated dynamical system, with the NSC having an elevated velocity dispersion in line with its high stellar mass. To investigate the stellar populations of the three clusters in more detail, we use surface brightness modelling to measure their fluxes from ultraviolet to mid-infrared wavelengths and fit their spectral energy distributions (SEDs). Two of the clusters are UV-bright and well described by single stellar populations with young ages ($\sim$ 3 and 5 Myr) and low masses ($M_\ast \sim 4 \times 10^{4} - 10^{5} M_\odot$), whereas the central cluster is much more massive ($3 \times 10^7 M_\odot$), and cannot be fitted by a single stellar population. Instead, we find that a minor young population ($\sim$ 1 Myr) embedded in a dominant old population ($\sim$ 8 Gyr) is needed to explain its SED. Given its complex composition and the close proximity of two young star clusters that are likely to merge with it within a few hundred million years, we consider NGC4654 a unique laboratory to study NSC growth from both in-situ star formation and the infall of star clusters., Comment: Main text: 13 pages, 8 figures, accepted for publication in A&A

In this letter we present the first systematic spectroscopic measurements of the Near-InfraRed (NIR) hydrogen recombination lines Paschen alpha ($Pa_{\alpha}$ $\lambda = 1.875 \mu m$) and Brackett beta ($Br_{\beta}$ $\lambda = 2.626 \mu m$), produced by pre-main-sequence (PMS) stars. These stars, consisting of T Tauri and Herbig AeBe stars are located in the massive Galactic star-formation region NGC 3603. The measurements were obtained from JWST NIRSpec, using multi-object spectroscopy (MOS) mode. Utilising existing empirical relations between $L_{acc}$ and $L_{Br_{\gamma}}$, we have used our new measurements to formulate, for the first time, an empirical relationship between the accretion luminosity $L_{acc}$ of the stars, and the line luminosities $L_{line}$ of both $Pa_{\alpha}$ and $Br_{\beta}$. These relationships are: $\log_{10}( \frac{L_{acc}}{L_{\odot}}) = 1.42 (\pm 0.18) \times \log_{10}( \frac{L_{Pa_{\alpha}}}{L_{\odot}}) + 3.33 (\pm 0.42)$ and $\log_{10}( \frac{L_{acc}}{L_{\odot}}) = 1.47 (\pm 0.18) \times \log_{10}( \frac{L_{Br_{\beta}}}{L_{\odot}}) + 4.60 (\pm 0.57)$. These new relationships are key for roughly estimating the accretion rates for large samples of PMS stars with JWST.

Models involving hybrid systems are versatile in their application but difficult to optimize efficiently due to their combinatorial nature. This work presents a method to cope with hybrid optimal control problems which, in contrast to decomposition techniques, does not require relaxing the integrality constraints. Based on the discretize-then-optimize approach, our scheme addresses mixed-integer nonlinear problems under mild assumptions. The proposed numerical algorithm builds upon the augmented Lagrangian framework, whose subproblems are handled using successive mixed-integer linearizations with trust regions. We validate the performance of the numerical routine with extensive investigations using hybrid optimal control problems from different fields of application. Promising preliminary results are presented for a motion planning task with hysteresis and a Lotka-Volterra fishing problem with total variation., Comment: 11 pages, 4 figures, 1 algorithm, 1 table

We examine over 68,000 refereed publications based on data from 25 missions in the ESA Science Programme and 11 additional missions in which ESA is involved as a junior partner. The publications cover the fields of astronomy, planetary science, and heliophysics and are spread over almost 50 years, spanning the period between the year a mission was launched and the end of 2021. We study the number of papers as a function of time and the evolution of several metrics, including citations and other indices. We also investigate the geographical distribution of the authors, and for ESA Member States we correlate the various indices with the level of financial contribution of the individual countries to the ESA Science Programme. We find that in general the involvement of the scientific communities in the various Member States follows the distribution expected from the countries' gross domestic products, with communities in some field and countries, both large and small, being particularly effective at turning data into scientific discoveries. We also analyse the differences between papers written by investigators directly involved in the provision of the payloads or in the definition of the scientific projects and those written by other scientists not directly involved in the process. We find that the latter, the so-called "archival papers", represent more than 50\,\% of the literature based on data from ESA Space Science missions, and have a similar impact on the literature in the respective fields, as judged by the number of citations. This highlights the importance of sharing and preserving the scientific data produced by the missions., Comment: To be submitted to Springer for publication in the ISSI Scientific Reports series

The 30 Doradus region in the Large Magellanic Cloud (LMC) is the most energetic star-forming region in the Local Group. It is powered by the feedback from the massive stars in R136, the 1-2 Myr old central massive cluster. 30 Doradus has therefore long been regarded as a laboratory for studying star and star cluster formation under conditions reminiscent of the early Universe. We use JWST NIRCam observations to analyse how star formation proceeds in the region. Using selections based on theoretical isochrones on colour-magnitude diagrams, we identify populations of different ages. We select pre-main-sequence (PMS) stars and young stellar objects that show excess emission from warm dust or emission lines. Studying the spatial distribution of the different populations, we find that the youngest PMS stars with ages < 0.5 Myr are located in an elongated structure that stretches towards the north-east from the central cluster. The same structure is found in the sources that show an infrared excess, appears to be overlapping with cold molecular gas, and covers previously investigated sites of ongoing star formation. Pre-main-sequence stars with ages between 1 and 4 Myr and upper main-sequence stars are concentrated in the centre of R136, while older stars are more uniformly distributed across the field and likely belong to the LMC field population. Nonetheless, we find stars with excess emission from on dust or emission lines as far as 100 pc from the centre, indicating extended recent star formation. We interpret the elongated structure formed by the youngest PMS stars to be an indication of the still-ongoing hierarchical assembly of the R136 cluster. Additionally, the lower density of old PMS stars with emission due to ongoing accretion in the central region suggests that feedback from the R136 stars is effective in disrupting the disks of PMS stars., Comment: Accepted for publication in A&A, 16 pages, 15 figures

Nonlinear optimal control problems for trajectory planning with obstacle avoidance present several challenges. While general-purpose optimizers and dynamic programming methods struggle when adopted separately, their combination enabled by a penalty approach is capable of handling highly nonlinear systems while overcoming the curse of dimensionality. Nevertheless, using dynamic programming with a fixed state space discretization limits the set of reachable solutions, hindering convergence or requiring enormous memory resources for uniformly spaced grids. In this work we solve this issue by incorporating an adaptive refinement of the state space grid, splitting cells where needed to better capture the problem structure while requiring less discretization points overall. Numerical results on a space manipulator demonstrate the improved robustness and efficiency of the combined method with respect to the single components.

Complex architectures for wireless communications, digital electronics and space-based navigation interlink several oscillator-based devices such as clocks, transponders and synthesizers. Estimators characterizing their stability are critical for addressing the impact of random fluctuations (noise) on the overall system performance. Manufacturers typically specify this as an Allan/Hadamard Variance (AVAR/HVAR) profile in the _integration_ time domain, yet, stochastic processes governing the noise take place in the _Fourier_ frequency domain in the shape of a Power Spectral Density (PSD) function. Both are second-moment measures of the time series, however, it is only possible to translate unambiguously from the PSD to the AVAR/HVAR, not vice versa, except in the case of a single noise type, which is severely limiting in real-life applications. This note elaborates an analytical method to generate an approximated PSD expressed as a set of power-laws defined in specific intervals in the frequency domain, starting from an AVAR/HVAR expressed a set of power-laws in the time domain. The proposed algorithm is straightforward to implement, applicable to all noise types (and combinations thereof) and can be self-validated by reconstructing the corresponding AVAR/HVAR by direct calculus. We also report on its limitations of and analytical expressions of the continuous version of this algorithm. Coupling with well-established algorithms relying on the PSD for power-law noise generation, the ensuing method encompasses the capability for generating multi-colored noise in end-to-end simulations, as demonstrated hereby for NASA's Deep Space Atomic Clock., Comment: 18 pages, 9 figures

Bringing together nonlinear optimization with polyhedral and integrality constraints enables versatile modeling, but poses significant computational challenges. We investigate a method to address these problems based on sequential mixed-integer linearization with trust region safeguard, computing feasible iterates via calls to a generic mixed-integer linear solver. Convergence to critical, possibly suboptimal, feasible points is established for arbitrary starting points. Finally, we present numerical applications in nonsmooth optimal control and optimal network design and operation., Comment: 16 pages, 4 figures, 2 tables, 1 algorithm

JWST NIRCam observations at 1.5-4.5 $\mu$m have provided broad and narrow band imaging of the evolving remnant of SN 1987A with unparalleled sensitivity and spatial resolution. Comparing with previous marginally spatially resolved Spitzer IRAC observations from 2004-2019 confirms that the emission arises from the circumstellar equatorial ring (ER), and the current brightness at 3.6 and 4.5 $\mu$m was accurately predicted by extrapolation of the declining brightness tracked by IRAC. Despite the regular light curve, the NIRCam observations clearly reveal that much of this emission is from a newly developing outer portion of the ER. Spots in the outer ER tend to lie at position angles in between the well-known ER hotspots. We show that the bulk of the emission in the field can be represented by 5 standard spectral energy distributions (SEDs), each with a distinct origin and spatial distribution. This spectral decomposition provides a powerful technique for distinguishing overlapping emission from the circumstellar medium (CSM) and the supernova (SN) ejecta, excited by the forward and reverse shocks respectively., Comment: Accepted for publication in ApJ. 16 pages, 12 figures. 2 animations not included here

A broad class of optimization problems can be cast in composite form, that is, considering the minimization of the composition of a lower semicontinuous function with a differentiable mapping. This paper investigates the versatile template of composite optimization without any convexity assumptions. First- and second-order optimality conditions are discussed. We highlight the difficulties that stem from the lack of convexity when dealing with necessary conditions in a Lagrangian framework and when considering error bounds. Building upon these characterizations, a local convergence analysis is delineated for a recently developed augmented Lagrangian method, deriving rates of convergence in the fully nonconvex setting., Comment: 36 pages

Deep Learning (DL) requires lots of time and data, resulting in high computational demands. Recently, researchers employ Active Learning (AL) and online distillation to enhance training efficiency and real-time model adaptation. This paper evaluates a set of query strategies to achieve the best training results. It focuses on Human Pose Estimation (HPE) applications, assessing the impact of selected frames during training using two approaches: a classical offline method and a online evaluation through a continual learning approach employing knowledge distillation, on a popular state-of-the-art HPE dataset. The paper demonstrates the possibility of enabling training at the edge lightweight models, adapting them effectively to new contexts in real-time.

2D materials with high charge carrier mobility and tunable electronic band gaps have attracted intense research effort for their potential use as active components in nanoelectronics. 2D-conjugated polymers (2DCP) constitute a promising sub-class due to the fact that the electronic band structure can be manipulated by varying the molecular building blocks, while at the same time preserving the key features of 2D materials such as Dirac cones and high charge mobility. The major challenge for their use in technological applications is to fabricate mesoscale ordered 2DCP networks since current synthetic routes yield only small domains with a high density of defects. Here we demonstrate the synthesis of a mesoscale ordered 2DCP with semiconducting properties and Dirac cone structures via Ullmann coupling on Au(111). This material has been obtained by combining rigid azatriangulene precursors and a hot dosing approach which favours molecular diffusion and reduces the formation of voids in the network. These results open opportunities for the synthesis of 2DCP Dirac cone materials and their integration into devices., Comment: 21 pages, 3 figures