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Leveraging rich data on the universe of Texas high school graduates, we estimate how the relationship between geographic access to public two- and four-year postsecondary institutions and postsecondary outcomes varies across race-ethnicity and socioeconomic status. We find that students are sensitive to the distance they must travel to access public colleges and universities, but there are heterogeneous effects across students -- particularly with regard to distance to public two-year colleges (i.e., community colleges). White, Asian, and higher-income students who live in a community college desert (i.e., at least 30 minutes driving time from the nearest public two-year college) substitute towards four-year colleges and are more likely to complete bachelor's degrees. Meanwhile, Black, Hispanic, and lower-income students respond to living in a community college desert by forgoing college enrollment altogether, reducing the likelihood that they earn associate's and reducing the likelihood that they ultimately transfer to four-year colleges and earn bachelor's degrees. These relationships persist up to eight years following high school graduation, resulting in substantial long-term gaps in overall degree attainment by race-ethnicity and income in areas with limited postsecondary access.

The design of fast reactors burning MOX fuels requires accurate capture and fission cross sections. For the particular case of neutron capture on 242Pu, the NEA recommends that an accuracy of 8-12% should be achieved in the fast energy region (2 keV-500 keV) compared to their estimation of 35% for the current uncertainty. Integral irradiation experiments suggest that the evaluated cross section of the JEFF-3.1 library overestimates the 242Pu(n,{\gamma}) cross section by 14% in the range between 1 keV and 1 MeV. In addition, the last measurement at LANSCE reported a systematic reduction of 20-30% in the 1-40 keV range relative to the evaluated libraries and previous data sets. In the present work this cross section has been determined up to 600 keV in order to solve the mentioned discrepancies. A 242Pu target of 95(4) mg enriched to 99.959% was irradiated at the n TOF-EAR1 facility at CERN. The capture cross section of 242Pu has been obtained between 1 and 600 keV with a systematic uncertainty (dominated by background subtraction) between 8 and 12%, reducing the current uncertainties of 35% and achieving the accuracy requested by the NEA in a large energy range. The shape of the cross section has been analyzed in terms of average resonance parameters using the FITACS code as implemented in SAMMY, yielding results compatible with our recent analysis of the resolved resonance region.The results are in good agreement with the data of Wisshak and K\"appeler and on average 10-14% below JEFF-3.2 from 1 to 250 keV, which helps to achieve consistency between integral experiments and cross section data. At higher energies our results show a reasonable agreement within uncertainties with both ENDF/B-VII.1 and JEFF-3.2. Our results indicate that the last experiment from DANCE underestimates the capture cross section of 242Pu by as much as 40% above a few keV., Comment: 20 pages, 19 figures, submitted to Phys. Rev. C

Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called $\gamma$-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps toward such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setup at CERN n\_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C$_{6}$D$_{6}$ detectors, and one LaCl$_{3}$(Ce) detector. The performance of these detection systems is compared using $^{93}$Nb($n$,$\gamma$) data. We also developed a detailed \textsc{Geant4} Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a $\gamma$ detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigaged experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability.

This research uses the implementation of a school suspension ban in Maryland to test whether a top-down state-initiated ban on suspensions in early primary grades can influence school behavior regarding school discipline. Beginning in the fall of 2017, the State of Maryland banned the use of out-of-school suspensions for grades PK-2, unless a student posed an "imminent threat" to staff or students. This research investigates (1) what was the effect of the ban on discipline outcomes for students in both treated grades and upper elementary grades not subject to the ban? (2) did schools bypass the ban by coding more events as threatening or increasing the use of in-school suspensions? and (3) were there differential effects for students in groups that are historically suspended more often? Using a comparative interrupted time series strategy, we find that the ban is associated with a substantial reduction in, but not a total elimination of, out-of-school suspensions for targeted grades without substitution of in-school suspensions. Disproportionalities by race and other characteristics remain after the ban. Grades not subject to the ban experienced few effects, suggesting the ban did not trigger a schoolwide response that reduced exclusionary discipline.

Fast radio bursts (FRBs) are very energetic pulses of unknown physical origin. These can be used to study the intergalactic medium (IGM) thanks to their dispersion measure (DM). The DM has several contributions that can be measured (or estimated), including the contribution from the host galaxy itself, DM_host. In this work, we empirically estimate DM_host for a sample of 12 galaxy hosts, using a direct method based solely on the properties of the host galaxies themselves (DM_host_dir). We use VLT/MUSE observations of the FRB hosts for estimating DM_host_dir. The method relies on estimating the DM contribution of both the FRB host galaxy's interstellar medium and its halo separately. For comparison purposes, we also provide an alternative indirect method to estimate DM_host based on the Macquart relation (DM_host_mq). We find an average = 80+/-11 pc/cc with a standard deviation of 38 pc/cc (in the rest-frame) based on our direct method, with a systematic uncertainty of 30%. We report positive correlations between DM_host and both the stellar masses and the star-formation rates of their host galaxies. In contrast, we do not find any strong correlation between DM_host and neither redshift nor the projected distances to the FRB hosts centers. Finally, we do not find any strong correlation between DM_host_dir and DM_host_mq, although their average values are consistent. Our reported correlations could be used to improve the priors used in establishing DM_host for individual FRBs. Similarly, such correlations and the lack of a strong redshift evolution can be used to constrain models for the progenitor of FRBs. However, the lack of a DM_host_dir and DM_host_mq correlation indicates that there may still be contributions to the DM of FRBs not included in our modeling, e.g. large DMs from the FRB progenitor and/or intervening large-scale structures not accounted for in DM_host_mq., Comment: Accepted for publication in Astronomy & Astrophysics on 20 January, 2025. Abstract has been abridged

This paper is concerned with the geometry of principal orbits in quaternionic K\"ahler manifolds $M$ of cohomogeneity one. We focus on the complete cohomogeneity one examples obtained from the non-compact quaternionic K\"ahler symmetric spaces associated with the simple Lie groups of type A by the one-loop deformation. We prove that for zero deformation parameter the principal orbits form a fibration by solvsolitons (nilsolitons if $4n=\dim M=4$). The underlying solvable group is non-unimodular if $n>1$ and is the Heisenberg group if $n=1$. We show that under the deformation, the hypersurfaces remain solvmanifolds but cease to be Ricci solitons., Comment: 24 pages. Comments are welcome!

This paper focuses on safety filters designed based on Control Barrier Functions (CBFs): these are modifications of a nominal stabilizing controller typically utilized in safety-critical control applications to render a given subset of states forward invariant. The paper investigates the dynamical properties of the closed-loop systems, with a focus on characterizing undesirable behaviors that may emerge due to the use of CBF-based filters. These undesirable behaviors include unbounded trajectories, limit cycles, and undesired equilibria, which can be locally stable and even form a continuum. Our analysis offer the following contributions: (i) conditions under which trajectories remain bounded and (ii) conditions under which limit cycles do not exist; (iii) we show that undesired equilibria can be characterized by solving an algebraic equation, and (iv) we provide examples that show that asymptotically stable undesired equilibria can exist for a large class of nominal controllers and design parameters of the safety filter (even for convex safe sets). Further, for the specific class of planar systems, (v) we provide explicit formulas for the total number of undesired equilibria and the proportion of saddle points and asymptotically stable equilibria, and (vi) in the case of linear planar systems, we present an exhaustive analysis of their global stability properties. Examples throughout the paper illustrate the results.

Spider pulsars are binary systems composed of a millisecond pulsar and a low-mass companion. Their X-ray emission, varying with orbital phase, originates from synchrotron radiation produced by high-energy electrons accelerated at the intrabinary shock. For fast-spinning pulsars in compact binary systems, the intrabinary shock emission occurs in the fast cooling regime. Using global two-dimensional particle-in-cell simulations, we investigate the effect of synchrotron losses on the shock structure and the resulting emission, assuming that the pulsar wind is stronger than the companion wind (so, the shock wraps around the companion), as expected in black widows. We find that the shock opening angle gets narrower for greater losses; the lightcurve shows a more prominent double-peaked signature (with two peaks just before and after the pulsar eclipse) for stronger cooling; below the cooling frequency, the synchrotron spectrum displays a hard power-law range, consistent with X-ray observations., Comment: arXiv admin note: text overlap with arXiv:2404.03700

Electronic structure calculations of molecular systems are among the most promising applications for fault-tolerant quantum computing (FTQC) in quantum chemistry and drug design. However, while recent algorithmic advancements such as qubitization and Tensor Hypercontraction (THC) have significantly reduced the complexity of such calculations, they do not yet achieve computational runtimes short enough to be practical for industrially relevant use cases. In this work, we introduce several advances to electronic structure calculation for molecular systems, resulting in a two-orders-of-magnitude speedup of estimated runtimes over prior-art algorithms run on comparable quantum devices. One of these advances is a novel framework for block-invariant symmetry-shifted Tensor Hypercontraction (BLISS-THC), with which we achieve the tightest Hamiltonian factorizations reported to date. We compile our algorithm for an Active Volume (AV) architecture, a technical layout that has recently been proposed for fusion-based photonic quantum hardware. AV compilation contributes towards a lower runtime of our computation by eliminating overheads stemming from connectivity issues in the underlying surface code. We present a detailed benchmark of our approach, focusing primarily on the computationally challenging benchmark molecule P450. Leveraging a number of hardware tradeoffs in interleaving-based photonic FTQC, we estimate runtimes for the electronic structure calculation of P450 as a function of the device footprint.

Quantum Krylov subspace diagonalization is a prominent candidate for early fault tolerant quantum simulation of many-body and molecular systems, but so far the focus has been mainly on computing ground-state energies. We go beyond this by deriving analytical first-order derivatives for quantum Krylov methods and show how to obtain relaxed one and two particle reduced density matrices of the Krylov eigenstates. The direct approach to measuring these matrices requires a number of distinct measurement that scales quadratically with the Krylov dimension $D$. Here, we show how to reduce this scaling to a constant. This is done by leveraging quantum signal processing to prepare Krylov eigenstates, including exited states, in depth linear in $D$. We also compare several measurement schemes for efficiently obtaining the expectation value of an operator with states prepared using quantum signal processing. We validate our approach by computing the nuclear gradient of a small molecule and estimating its variance.

Nonrigid registration is vital to medical image analysis but remains challenging for diffusion MRI (dMRI) due to its high-dimensional, orientation-dependent nature. While classical methods are accurate, they are computationally demanding, and deep neural networks, though efficient, have been underexplored for nonrigid dMRI registration compared to structural imaging. We present a novel, deep learning framework for model-free, nonrigid registration of raw diffusion MRI data that does not require explicit reorientation. Unlike previous methods relying on derived representations such as diffusion tensors or fiber orientation distribution functions, in our approach, we formulate the registration as an equivariant diffeomorphism of position-and-orientation space. Central to our method is an $\mathsf{SE}(3)$-equivariant UNet that generates velocity fields while preserving the geometric properties of a raw dMRI's domain. We introduce a new loss function based on the maximum mean discrepancy in Fourier space, implicitly matching ensemble average propagators across images. Experimental results on Human Connectome Project dMRI data demonstrate competitive performance compared to state-of-the-art approaches, with the added advantage of bypassing the overhead for estimating derived representations. This work establishes a foundation for data-driven, geometry-aware dMRI registration directly in the acquisition space., Comment: Coauthor was inadvertently left out. This is now corrected

Let E be a transitive Courant algebroid with scalar product of neutral signature. A generalized almost complex structure \mathcal J on E is a skew-symmetric smooth field of endomorphisms of E which squares to minus the identity. We say that \mathcal J is integrable (or is a generalized complex structure) if the space of sections of its (1,0) bundle is closed under the Dorfman bracket of E. In this paper we determine, under certain natural conditions, the local form of \mathcal J around regular points. This result is analogous to Gualtieri's Darboux theorem for generalized complex structures on manifolds and extends Wang's description of skew-symmetric left-invariant complex structures on compact semisimple Lie groups., Comment: 58 pages

We measure for the first time the differential photoproduction cross section $d\sigma/dt$ of the $a_2(1320)$ meson at an average photon beam energy of 8.5~GeV, using data with an integrated luminosity of 104~pb$^{-1}$ collected by the GlueX experiment. We fully reconstruct the $\gamma p \to \eta\pi^0 p$ reaction and perform a partial-wave analysis in the $a_2(1320)$ mass region with amplitudes that incorporate the linear polarization of the beam. This allows us to separate for the first time the contributions of natural- and unnatural-parity exchanges. These measurements provide novel information about the photoproduction mechanism, which is critical for the search for spin-exotic states., Comment: 8 pages, 4 figures plus supplemental material

Understanding and optimizing thin-film synthesis requires measuring the diffusion length $d_\alpha$ of adsorbed growth precursors. Despite technological advances, in-situ measurements of $d_\alpha$ are often unachievable due to harsh deposition conditions, such as high temperatures or reactive environments. In this paper, we propose a fitting approach to determine $d_\alpha$ from experimental data by leveraging inter-surface diffusion between a substrate and a strip obtained by, for example, processing a film. The substrate serves as a source or sink of precursors, influencing the growth dynamics and shaping the profile of the strip. By fitting simulated profiles to given profiles, we demonstrate that $d_\alpha$ can be determined. To achieve this, we develop a theoretical growth model, a simulation strategy, and a fitting procedure. The growth model incorporates inter-surface diffusion, adsorption, and desorption of growth precursors, with growth being proportional to the concentration of adsorbed precursors. In our simulations, a chain of nodes represents a profile, and growth is captured by the displacement of those nodes, while keeping the node density approximately constant. For strips significantly wider than $d_\alpha$, a scaled precursor concentration and $d_\alpha$ are the fitting parameters that are determined by minimizing a suitably defined measure of the distance between simulated and given profiles. We evaluate the robustness of our procedure by analyzing the effect of profile resolution and noise on the fitted parameters. Our approach can offer valuable insights into thin-film growth processes, such as those occurring during plasma-enhanced chemical vapor deposition.

This article examines the impact of Hamiltonian dynamics on the interaction graph of Boolean networks. Three types of dynamics are considered: maximum height, Hamiltonian cycle, and an intermediate dynamic between these two. The study addresses how these dynamics influence the connectivity of the graph and the existence of variables that depend on all other variables in the system. Additionally, a family of regulatory Boolean networks capable of describing these three Hamiltonian behaviors is introduced, highlighting their specific properties and limitations. The results provide theoretical tools for modeling complex systems and contribute to the understanding of dynamic interactions in Boolean networks.

Designing controllers that accomplish tasks while guaranteeing safety constraints remains a significant challenge. We often want an agent to perform well in a nominal task, such as environment exploration, while ensuring it can avoid unsafe states and return to a desired target by a specific time. In particular we are motivated by the setting of safe, efficient, hands-off training for reinforcement learning in the real world. By enabling a robot to safely and autonomously reset to a desired region (e.g., charging stations) without human intervention, we can enhance efficiency and facilitate training. Safety filters, such as those based on control barrier functions, decouple safety from nominal control objectives and rigorously guarantee safety. Despite their success, constructing these functions for general nonlinear systems with control constraints and system uncertainties remains an open problem. This paper introduces a safety filter obtained from the value function associated with the reach-avoid problem. The proposed safety filter minimally modifies the nominal controller while avoiding unsafe regions and guiding the system back to the desired target set. By preserving policy performance while allowing safe resetting, we enable efficient hands-off reinforcement learning and advance the feasibility of safe training for real world robots. We demonstrate our approach using a modified version of soft actor-critic to safely train a swing-up task on a modified cartpole stabilization problem., Comment: The first three authors contributed equally to the work. This work has been submitted to the L4DC 2025 for possible publication

Quasi-free scattering of atomic nuclei away from the stability line has reached several milestones over the past decade. The advent of gamma, charged particles, and neutron detection devices for inverse kinematics, especially in combination with RI beams, has opened new horizons in nuclear physics. Research is progressing with detection devices optimized to explore these new and challenging area of physics. While some of the new detection developments aim for high energy and angular resolution, others focus on the increasing detection efficiency or enhancing large angular acceptance. As high-intensity RI beams become available worldwide, we reflect on past detectors and provide a review of the future development of the detection devices., Comment: Contribution to review article collection for the Symposium "Direct reaction and spectroscopy with hydrogen targets: past 10 years at the RIBF and future prospects". to be submitted to PTEP

A matrix is totally positive if all of its minors are positive. This notion of positivity coincides with the type A version of Lusztig's more general total positivity in reductive real-split algebraic groups. Since skew-symmetric matrices always have nonpositive entries, they are not totally positive in the classical sense. The space of skew-symmetric matrices is an affine chart of the orthogonal Grassmannian $\mathrm{OGr}(n,2n)$. Thus, we define a skew-symmetric matrix to be totally positive if it lies in the totally positive orthogonal Grassmannian. We provide a positivity criterion for these matrices in terms of a fixed collection of minors, and show that their Pfaffians have a remarkable sign pattern. The totally positive orthogonal Grassmannian is a CW cell complex and is subdivided into Richardson cells. We introduce a method to determine which cell a given point belongs to in terms of its associated matroid., Comment: 38 pages, 6 figures, comments welcome!

Our understanding of the structure of atomic nuclei largely derives from the nuclear shell model, which has proven widely successful. Further test to our interpretation of the nuclear properties is provided by the study of shell evolution. Increasing experimental information has shown that the nuclear energy shells change when going towards the most exotic nuclei, in turn making some shell closures disappear while others arise. In particular, the $N=40$ sub-shell closure has been the subject of extensive research due to the emergence of a so-called Island of Inversion, where deformed intruder configurations dominate the wave function of the ground state. An overview of recent experimental results in the $N=40$ Island of Inversion, particularly those performed with the combination of the MINOS hydrogen target and the DALI2 $\gamma$-ray array at the RIBF are discussed., Comment: Contribution to review article collection for the Symposium "Direct reactions and spectroscopy with hydrogen targets: past 10 years at the RIBF and future prospects"

This paper presents a study of the radiation hardness of the hadronic Tile Calorimeter of the ATLAS experiment in the LHC Run 2. Both the plastic scintillators constituting the detector active media and the wavelength-shifting optical fibres collecting the scintillation light into the photodetector readout are elements susceptible to radiation damage. The dedicated calibration and monitoring systems of the detector (caesium radioactive sources, laser and minimum bias integrator) allow to assess the response of these optical components. Data collected with these systems between 2015 and 2018 are analysed to measure the degradation of the optical instrumentation across Run 2. Moreover, a simulation of the total ionising dose in the calorimeter is employed to study and model the degradation profile as a function of the exposure conditions, both integrated dose and dose rate. The measurement of the relative light output loss in Run 2 is presented and extrapolations to future scenarios are drawn based on current data. The impact of radiation damage on the cell response uniformity is also analysed., Comment: 31 pages in total, 18 figures, 2 tables, submitted to JINST

This paper studies the design of controllers for discontinuous dynamics that ensure the safety of non-smooth sets. The safe set is represented by arbitrarily nested unions and intersections of 0-superlevel sets of differentiable functions. We show that any optimization-based controller that satisfies only the point-wise active safety constraints is generally un-safe, ruling out the standard techniques developed for safety of continuous dynamics. This motivates the introduction of the notion of transition functions, which allow us to incorporate even the inactive safety constraints without falling into unnecessary conservatism. These functions allow system trajectories to leave a component of the nonsmooth safe set to transition to a different one. The resulting controller is then defined as the solution to a convex optimization problem, which we show is feasible and continuous wherever the system dynamics is continuous. We illustrate the effectiveness of the proposed design approach in a multi-agent reconfiguration control problem.

The survival of the domestic cat (Felis catus) in various ecosystems has become increasingly relevant due to its impact on wildlife, public health, and society. In countries like Mexico, social factors such as abandonment have led to the feralization of the species and an unexpected increase in its population in urban areas. To design and implement effective population control methods, a thorough analysis of the species' population dynamics, along with the social factors influencing it, is necessary. We propose a reaction-diffusion model to simulate the natural dispersal of the population within a bounded domain. After exploring the species' spreading ability, we construct a complex dynamical system based on the biological characteristics of cats and their intraspecific and interspecific interactions, which we explain and study in detail. Both deterministic and stochastic parameters are considered to enhance the realism of the simulations. Our results indicate that the population reaches equilibrium, highlighting the need for control methods combined with social regulations to achieve sustainability in the system.

Multiplicity studies greatly benefit from focusing on M dwarfs because they are often paired in a variety of configurations with both stellar and substellar objects, including exoplanets. We aim to address the observed multiplicity of M dwarfs by conducting a systematic analysis using the latest available astrophotometric data. For every star in a sample of 2214 M dwarfs from the CARMENES catalogue, we investigated the existence of resolved and unresolved physical companions in the literature and in all-sky surveys, especially in Gaia DR3 data products. We covered a very wide range of separations, from known spectroscopic binaries in tight arrangements $\sim$0.01 au to remarkably separated ultra-wide pairs ($\sim$10$^5$ au). We identified 835 M dwarfs in 720 multiple systems, predominantly binaries. Thus, we propose 327 new binary candidates based on Gaia data. If these candidates are finally confirmed, we expect the multiplicity fraction of M dwarfs to be 40.3$^{+2.1}_{-2.0}$ %. When only considering the systems already identified, the multiplicity fraction is reduced to 27.8$^{+1.9}_{-1.8}$ %. This result is in line with most of the values published in the literature. We also identified M-dwarf multiple systems with FGK, white dwarf, ultra-cool dwarf, and exoplanet companions, as well as those in young stellar kinematic groups. We studied their physical separations, orbital periods, binding energies, and mass ratios. We argue that based on reliable astrometric data and spectroscopic investigations from the literature (even when considering detection biases), the multiplicity fraction of M dwarfs could still be significantly underestimated. This calls for further high-resolution follow-up studies to validate these findings.

Monthly demand charges form a significant portion of the electric bill for microgrids with variable renewable energy generation. A battery energy storage system (BESS) is commonly used to manage these demand charges. Economic model predictive control (EMPC) with a reference trajectory can be used to dispatch the BESS to optimize the microgrid operating cost. Since demand charges are incurred monthly, EMPC requires a full-month reference trajectory for asymptotic stability guarantees that result in optimal operating costs. However, a full-month reference trajectory is unrealistic from a renewable generation forecast perspective. Therefore, to construct a practical EMPC with a reference trajectory, an EMPC formulation considering both non-coincident demand and on-peak demand charges is designed in this work for 24 to 48 h prediction horizons. The corresponding reference trajectory is computed at each EMPC step by solving an optimal control problem over 24 to 48 h reference (trajectory) horizon. Furthermore, BESS state of charge regulation constraints are incorporated to guarantee the BESS energy level in the long term. Multiple reference and prediction horizon lengths are compared for both shrinking and rolling horizons with real-world data. The proposed EMPC with 48 h rolling reference and prediction horizons outperforms the traditional EMPC benchmark with a 2% reduction in the annual cost, proving its economic benefits., Comment: 13 pages, 6 figures, 2 tables, Submitted to IEEE Transactions on Smart Grid

Leveraging the large body of work devoted in recent years to describe redundancy and synergy in multivariate interactions among random variables, we propose a novel approach to quantify cooperative effects in feature importance, one of the most used techniques for explainable artificial intelligence. In particular, we propose an adaptive version of a well-known metric of feature importance, named Leave One Covariate Out (LOCO), to disentangle high-order effects involving a given input feature in regression problems. LOCO is the reduction of the prediction error when the feature under consideration is added to the set of all the features used for regression. Instead of calculating the LOCO using all the features at hand, as in its standard version, our method searches for the multiplet of features that maximize LOCO and for the one that minimize it. This provides a decomposition of the LOCO as the sum of a two-body component and higher-order components (redundant and synergistic), also highlighting the features that contribute to building these high-order effects alongside the driving feature. We report the application to proton/pion discrimination from simulated detector measures by GEANT., Comment: 11 pages, 3 figures

A complete understanding of the initial conditions of high-mass star formation and what processes determine multiplicity require the study of the magnetic field (B-field) in young, massive cores. Using ALMA 250 GHz polarization (0.3" = 1000 au) and ALMA 220 GHz high-angular resolution observations (0.05" = 160 au), we have performed a full energy analysis including the B-field at core scales and have assessed what influences the multiplicity inside a massive core previously believed to be in the prestellar phase. With 31 Msun, the G11.92 MM2 core has a young CS outflow with a dynamical time scale of a few thousand years. At high-resolution, the MM2 core fragments into a binary system with a projected separation of 505 au and a binary mass ratio of 1.14. Using the DCF method with an ADF analysis, we estimate in this core a B-field strength of 6.2 mG and a mass-to-flux ratio of 18. The MM2 core is strongly subvirialized with a virial parameter of 0.064, including the B-field. The high mass-to-flux ratio and low virial parameter indicate that this massive core is very likely undergoing runaway collapse, which is in direct contradiction with the core-accretion model. The MM2 core is embedded in a filament that has a velocity gradient consistent with infall. In line with clump-fed scenarios, the core can grow in mass at a rate of 1.9--5.6 x 10^-4 Msun/yr. In spite of the B-field having only a minor contribution to the total energy budget at core scales, it likely plays a more important role at smaller scales by setting the binary properties. Considering energy ratios and a fragmentation criterion at the core scale, the binary could have been formed by core fragmentation. The binary properties (separation and mass ratio), however, are also consistent with radiation-magnetohydrodynamic simulations with super-Alfvenic, supersonic (or sonic) turbulence that form binaries by disk fragmentation., Comment: Accepted for publications in ApJ (9 pages, 3 figures, Appendix)

The paper ``Tropical Geometry of Deep Neural Networks'' by L. Zhang et al. introduces an equivalence between integer-valued neural networks (IVNN) with activation $\text{ReLU}_{t}$ and tropical rational functions, which come with a map to polytopes. Here, IVNN refers to a network with integer weights but real biases, and $\text{ReLU}_{t}$ is defined as $\text{ReLU}_{t}(x)=\max(x,t)$ for $t\in\mathbb{R}\cup\{-\infty\}$. For every poset with $n$ points, there exists a corresponding order polytope, i.e., a convex polytope in the unit cube $[0,1]^n$ whose coordinates obey the inequalities of the poset. We study neural networks whose associated polytope is an order polytope. We then explain how posets with four points induce neural networks that can be interpreted as $2\times 2$ convolutional filters. These poset filters can be added to any neural network, not only IVNN. Similarly to maxout, poset convolutional filters update the weights of the neural network during backpropagation with more precision than average pooling, max pooling, or mixed pooling, without the need to train extra parameters. We report experiments that support our statements. We also prove that the assignment from a poset to an order polytope (and to certain tropical polynomials) is one to one, and we define the structure of algebra over the operad of posets on tropical polynomials., Comment: Poster presentation in NeuroIPS WIML 2024

The first spectroscopy of $^{52}$K was investigated via in-beam $\gamma$-ray spectroscopy at the RIKEN Radioactive Isotope Beam Factory after one-proton and one-neutron knockout from $^{53}$Ca and $^{53}$K beams impinging on a 15-cm liquid hydrogen target at $\approx$ 230~MeV/nucleon. The energy level scheme of $^{52}$K was built using single $\gamma$ and $\gamma$-$\gamma$ coincidence spectra. The spins and parities of the excited states were established based on momentum distributions of the fragment after the knockout reaction and based on exclusive cross sections. The results were compared to state-of-the-art shell model calculations with the SDPF-Umod interaction and ab initio IMSRG calculations with chiral effective field theory nucleon-nucleon and three-nucleon forces.

Artificial Intelligence (AI) has driven innovations and created new opportunities across various sectors. However, leveraging domain-specific knowledge often requires automated tools to design and configure models effectively. In the case of Deep Neural Networks (DNNs), researchers and practitioners usually resort to Neural Architecture Search (NAS) approaches, which are resource- and time-intensive, requiring the training and evaluation of numerous candidate architectures. This raises sustainability concerns, particularly due to the high energy demands involved, creating a paradox: the pursuit of the most effective model can undermine sustainability goals. To mitigate this issue, zero-cost proxies have emerged as a promising alternative. These proxies estimate a model's performance without the need for full training, offering a more efficient approach. This paper addresses the challenges of model evaluation by automatically designing zero-cost proxies to assess DNNs efficiently. Our method begins with a randomly generated set of zero-cost proxies, which are evolved and tested using the NATS-Bench benchmark. We assess the proxies' effectiveness using both randomly sampled and stratified subsets of the search space, ensuring they can differentiate between low- and high-performing networks and enhance generalizability. Results show our method outperforms existing approaches on the stratified sampling strategy, achieving strong correlations with ground truth performance, including a Kendall correlation of 0.89 on CIFAR-10 and 0.77 on CIFAR-100 with NATS-Bench-SSS and a Kendall correlation of 0.78 on CIFAR-10 and 0.71 on CIFAR-100 with NATS-Bench-TSS., Comment: Submitted to CVPR 2025

BabyIAXO is the intermediate stage of the International Axion Observatory (IAXO) to be hosted at DESY. Its primary goal is the detection of solar axions following the axion helioscope technique. Axions are converted into photons in a large magnet that is pointing to the sun. The resulting X-rays are focused by appropriate X-ray optics and detected by sensitive low-background detectors placed at the focal spot. The aim of this article is to provide an accurate quantitative description of the different components (such as the magnet, optics, and X-ray detectors) involved in the detection of axions. Our efforts have focused on developing robust and integrated software tools to model these helioscope components, enabling future assessments of modifications or upgrades to any part of the IAXO axion helioscope and evaluating the potential impact on the experiment's sensitivity. In this manuscript, we demonstrate the application of these tools by presenting a precise signal calculation and response analysis of BabyIAXO's sensitivity to the axion-photon coupling. Though focusing on the Primakoff solar flux component, our virtual helioscope model can be used to test different production mechanisms, allowing for direct comparisons within a unified framework., Comment: 36 pages, 18 figures, 4 tables, Submitted to JHEP

We present a new iterative deblending method to separate the host galaxy (HG) and their Active Galactic Nuclei (AGN) emission with the use of Integral Field spectroscopic (IFS) data. The method decomposes the resolved HG emission from the unresolved AGN emission by modelling the two-dimensional surface brightness (SB) profile of the point-spread function (PSF) and the two-dimensional SB HG continuum simultaneously per each monochromatic slide. Our method does not require any prior information about the observed SB profile or a detailed fitting of the PSF, making it ideal for the automatic analysis of large galaxy samples. In this work, we test the quality of our method, its advantages, and its disadvantages. We test our method by using a set of IFS mock data cubes to quantify the reliability of our deblending process and further compare our method with the {\sc QDeblend3D} analysis tool. Furthermore, we applied our method to three data cubes selected from the MaNGA survey according to the dominance of either its HG or its AGN. We show that our deblending method is capable of disengaging the bright, nonresolved AGN emission from the HG continuum and its narrow emission lines. However, the decoupling depends on how well the IFS spatially resolves the PSF, and on the relative flux intensity of the HG-AGN. Therefore, the method is ideal for disentangling the bright-flux contribution from AGN-dominated spectra., Comment: 25 pages, 18 figures, accepted for publication on the MNRAS

We explore quantum-thermodynamic effects in a phosphorous (P)-doped graphene monolayer subjected to biaxial tensile strain. Introducing substitutional P atoms in the graphene lattice generates a tunable spin magnetic moment controlled by the strain control parameter $\varepsilon$. This leads to a magnetic quantum phase transition (MQPT) at zero temperature modulated by $\varepsilon$. The system transitions from a magnetic phase, characterized by an out-of-plane $sp^3$ type hybridization of the P-carbon (P-C) bonds, to a non-magnetic phase when these bonds switch to in-plane $sp^2$ hybridization. Employing a Fermi-Dirac statistical model, we calculate key thermodynamic quantities as the electronic entropy $S_e$ and electronic specific heat $C_e$. At finite temperatures, we find the MQPT is reflected in both $S_e$ and $C_e$, which display a distinctive $\Lambda$-shaped profile as a function of $\varepsilon$. These thermodynamic quantities sharply increase up to $\varepsilon = 5\% $ in the magnetic regime, followed by a sudden drop at $\varepsilon = 5.5\% $, transitioning to a linear dependence on $\varepsilon$ in the nonmagnetic regime. Notably, $S_e$ and $C_e$ capture the MQPT behavior for low and moderate temperature ranges, providing insights into the accessible electronic states in P-doped graphene. This controllable magnetic-to-nonmagnetic switch offers potential applications in electronic nanodevices operating at finite temperatures.

The reconfiguration of electrical power distribution systems is a crucial optimization problem aimed at minimizing power losses by altering the system topology through the operation of interconnection switches. This problem, typically modelled as a mixed integer nonlinear program demands high computational resources for large scale networks and requires specialized radiality constraints for maintaining the tree like structure of distribution networks. This paper presents a comprehensive analysis that integrates and compares the computational burden associated with different radiality constraint formulations proposed in the specialized literature for the reconfiguration of distribution systems. By using consistent hardware and software setups, we evaluate the performance of these constraints across several well known test cases. Our findings reveal significant differences in computational efficiency depending on the chosen set of radiality constraints, providing valuable insights for optimizing reconfiguration strategies in practical distribution networks.

We report the discovery of a super-Earth candidate orbiting the nearby mid M dwarf Gl\,725A using the radial velocity (RV) method. The planetary signal has been independently identified using high-precision RVs from the SOPHIE and SPIRou spectrographs, in the optical and near-infrared domains, respectively. We modelled the stellar activity signal jointly with the planet using two Gaussian Processes, one for each instrument to account for the chromaticity of the stellar activity and instrumental systematics, along with a Keplerian model. The signal is significantly detected with a RV semi-amplitude of $1.67\pm0.20$ m/s. The planet Gl 725A b is found to be in an orbit compatible with circular with a period of $11.2201\pm0.0051$ days. We analysed 27 sectors of TESS photometry on which no transit event was found. We determined a minimum mass of $M_{p}\sin{i}=2.78\pm0.35\,M_{\oplus}$ which places the planet in the super-Earth regime. Using Mass-Radius relationships we predict a planetary radius to be between 1.2 and $2.0\,R_{\oplus}$. The proximity of Gl 725A, of only 3.5 pc, makes this new exoplanet one of the closest to Earth and joins the group of S-type low-mass planets in short orbits ($P<15$ d) around close M dwarfs., Comment: 26 pages, 17 figures. Accepted in A&A

A new model to follow the complete evolution of a drop in Leidenfrost state is presented in this work. The main ingredients of the phenomenon were considered, including: 1) the shape and weight of a sessile drop, according to its size, compared to the capillary length, using the Young-Laplace equation; 2) the evaporation at the entire surface of the drop, due to the heat transfer across the vapor film, to the proximitiy of a hot plate and to the diffusion in air; 3) the velocity, pressure and temperature fields at the vapor film, between the drop and the hot plate, which are recovered by means of a Hankel transform method, being valid for any size of drops and any thickness of vapor films (below the vapor film stability threshold); 4) an estimation of the thermo-capillary Marangoni convection flow, without simulating numerically the flow within the drop. The aforementioned features were addressed and calculated, in order to include their effect within a single non-linear ODE, describing the temporal evolution of the size of the drop, through the Bond number. Three dimensionless parameters, relating the thermophysical properties of the drop fluid and the surrounding air, control the development of the phenomenon. All those properties were calculated according to the ideal gas approximation and to widely used empirical correlations, without any fitting parameter. The model predictions were compared against experimental results, using different organic and inorganic compounds, for which a good agreement has been found, when no bounce or rotation of the drop spontaneously occurs., Comment: 15 pages, 9 figures

Aims. Our goals are to characterise the kinematic properties and to identify young and old stars among the M dwarfs of the CARMENES input catalogue. Methods. We compiled the spectral types, proper motions, distances, and radial velocities for 2187 M dwarfs. We used the public code SteParKin to derive their galactic space velocities and identify members in the different galactic populations. We also identified candidate members in young stellar kinematic groups, with ages ranging from 1 Ma to 800 Ma with SteParKin, LACEwING, and BANYAN {\Sigma}. We removed known close binaries and perform an analysis of kinematic, rotation, and activity indicators (rotational periods and projected velocities, Halpha, X-rays, and UV emission) for 1546 M dwarfs. We defined five rotation-activity-colour relations satisfied by young ({\tau} <= 800 Ma) stars. Results. We identified 191 young M dwarf candidates (~12%), 113 of which are newly recognised in this work. In this young sample, there are 118 very active stars based on H{\alpha} emission, fast rotation, and X-ray and UV emission excess. Of them, 27 have also strong magnetic fields, 9 of which are likely younger than 50 Ma. Additionally, there are 87 potentially young stars and 99 stars with a dubious youth classification, which may increase the fraction of young stars to an astounding 24%. Only one star out of the 2187 exhibits kinematics typical of the old Galactic halo. Conclusions. A combined analysis of kinematic and rotation-activity properties provides a robust method for identifying young M dwarfs from archival data. However, more observational efforts are needed to ascertain the true nature of numerous young star candidates in the field and, perhaps more importantly, to precisely quantify their age.

Light-induced phase transitions offer a method to dynamically modulate topological states in bulk complex materials. Yet, next-generation devices demand nanoscale architectures with contact resistances near the quantum limit and precise control over local electronic properties. The layered material WTe$_2$ has gained attention as a likely Weyl semimetal, with topologically protected linear electronic band crossings hosting massless chiral fermions. Here, we demonstrate a topological phase transition facilitated by light-induced shear motion of a single atomic layer at the surface of bulk WTe$_2$, thereby opening the door to nanoscale device concepts. Ultrafast terahertz fields enhanced at the apex of an atomically sharp tip resonantly couple to the key interlayer shear mode of WTe$_2$ via a ferroelectric dipole at the interface, inducing a structural phase transition at the surface to a metastable state. Subatomically resolved differential imaging, combined with hybrid-level density functional theory, reveals a shift of 7 $\pm$ 3 picometres in the top atomic plane. Tunnelling spectroscopy links electronic changes across the phase transition with the electron and hole pockets in the band structure, suggesting a reversible, light-induced annihilation of the topologically-protected Fermi arc surface states in the top atomic layer.

The research aims to expand tactile feedback beyond vibrations to various modes of stimuli, such as indentation, vibration, among others. By incorporating soft material into the design of a novel tactile actuator, we can achieve multi-modality and enhance the device's wearability, which encompasses compliance, safety, and portability. The proposed tactile device can elevate the presence and immersion in VR by enabling diverse haptic feedback such as, force indentation, vibration and other arbitrary force outputs. This approach enables the rendering of haptic interactions with virtual objects, such as grasping of aa 3D virtual object to feel its stiffness - action that was difficult to achieve using widely adopted vibrotactile motors., Comment: Part of proceedings of 6th International Conference AsiaHaptics 2024

Generative Artificial Intelligence (AI) technologies are in a phase of unprecedented rapid development following the landmark release of Chat-GPT, which brought the phenomenon to wide public attention. As the deployment of AI products rises geometrically, considerable attention is being given to the threats and opportunities that AI technologies offer, and to the need for regulatory and standards initiatives to ensure that use of the technology aligns with societal needs and generates broad benefits while mitigating risks and threats. This manuscript is the third of a series of White Papers informing the development of IEEE-SA's p3995 {\it `Standard for the Implementation of Safeguards, Controls, and Preventive Techniques for Artificial Intelligence Models'} \cite{P3395}, Chair Marina Cort\^{e}s. This part focuses on assessing calmly and objectively, as far as is possible, the current state of Artificial Intelligence (AI) technology development and identifying predominant trends, prospects, and ensuing risks. It necessarily forms a snapshot of the current instant of a rapidly-evolving landscape, with new products and innovations emerging continuously. While our main focus is on software and hardware developments and their corporate context, we also briefly review progress on robotics within the AI context and describe some implications of the substantial and growing AI energy demand., Comment: This is an interim version of our p3395 WG White Paper, Part III. We will update this version, until publication by IEEE-SA, Sponsor Committee - Artificial Intelligence Standards Committee (C/AISC); https://standards.ieee.org/ieee/3395/11378/ This White Paper is companion to Part I available at arXiv:2410.01808

A promising way to test the physics of the accelerated expansion of the Universe is by studying the growth rate of matter fluctuations, which can be parameterized by the matter energy density parameter to the power $\gamma$, the so-called growth index. It is well-known that the $\Lambda$CDM cosmology predicts $\gamma=0.55$. However, using observational data, Ref. \citep{Nguyen:2023fip} measured a much higher $\gamma=0.633^{+0.025}_{-0.024}$, excluding the $\Lambda$CDM value within $3.7\sigma$. In this work, we analyze whether Dark Energy (DE) with the Equation of State (EoS) parameter described by the CPL parametrization can significantly modify $\gamma$ with respect to the $\Lambda$CDM one. Besides the usual Smooth DE (SDE) scenario, where DE perturbations are neglected on small scales, we also consider the case of Clustering Dark Energy (CDE), which has more potential to impact the growth of matter perturbations. In order to minimally constrain the background evolution and assess the largest meaningful $\gamma$ distribution, we use data from $32$ Cosmic Chronometers, $H(z$), data points. In this context, we found that both SDE and CDE models described by the CPL parametrization can not provide a significant number of $\gamma$ samples compatible with the value determined in Nguyen et al. (2023). Therefore, explaining the measured value of $\gamma$ is a challenge for DE models. Moreover, we present new fitting functions for $\gamma$, which are more accurate and general than the one proposed in Linder (2005) for SDE, and, for the first time, fitting functions for CDE models., Comment: 10 pages, 7 figures and 4 tables

This study investigates the role of college major choices in labor market outcomes, with a focus on racial minorities and immigrants. Drawing upon research on school-to-work linkages, we examine two measures, linkage, the connection between college majors and specific occupations in the labor market, and match, the alignment of workers' occupations with their college majors. Analyzing data from the American Community Survey, 2013-2017, we show that linkage positively predicts earnings, particularly for workers in matched occupations, and negatively predicts unemployment. Notably, Black, Hispanic, and foreign-born workers in matched occupations benefit more from linkage strength than their White and U.S.-born counterparts. This advantage is more pronounced in states that are popular destinations for immigrants. Our findings suggest that earnings and unemployment disparities experienced among racial minorities and immigrants may diminish if they pursue majors closely tied to jobs in the labor market and secure jobs related to their college majors.

AI agents have been evaluated in isolation or within small groups, where interactions remain limited in scope and complexity. Large-scale simulations involving many autonomous agents -- reflecting the full spectrum of civilizational processes -- have yet to be explored. Here, we demonstrate how 10 - 1000+ AI agents behave and progress within agent societies. We first introduce the PIANO (Parallel Information Aggregation via Neural Orchestration) architecture, which enables agents to interact with humans and other agents in real-time while maintaining coherence across multiple output streams. We then evaluate agent performance in agent simulations using civilizational benchmarks inspired by human history. These simulations, set within a Minecraft environment, reveal that agents are capable of meaningful progress -- autonomously developing specialized roles, adhering to and changing collective rules, and engaging in cultural and religious transmission. These preliminary results show that agents can achieve significant milestones towards AI civilizations, opening new avenues for large simulations, agentic organizational intelligence, and integrating AI into human civilizations., Comment: 35 pages, 14 figures

Let $\ell$ be a prime number, $k$ a positive integer and consider the group $\Gamma_{\ell^k} :=\langle a,b\ \vert\ a^{\ell^k(\ell^k-1)}ba^{-\ell^k}b^{-2}\rangle$. We prove that $\Gamma_{\ell^k}$ is not $\mathrm{SL}_2$-weakly integral with obstruction at exactly the prime $\ell$. We also give a general description of the character varieties of $2$-generated groups with a relation of the form $a^{n_1} b^{m_1} a^{n_2} b^{m_2} = 1$., Comment: Correct two typos on the abstract, improve one of main results, add references

A major challenges of deep learning (DL) is the necessity to collect huge amounts of training data. Often, the lack of a sufficiently large dataset discourages the use of DL in certain applications. Typically, acquiring the required amounts of data costs considerable time, material and effort. To mitigate this problem, the use of synthetic images combined with real data is a popular approach, widely adopted in the scientific community to effectively train various detectors. In this study, we examined the potential of synthetic data-based training in the field of intelligent transportation systems. Our focus is on camera-based traffic sign recognition applications for advanced driver assistance systems and autonomous driving. The proposed augmentation pipeline of synthetic datasets includes novel augmentation processes such as structured shadows and gaussian specular highlights. A well-known DL model was trained with different datasets to compare the performance of synthetic and real image-based trained models. Additionally, a new, detailed method to objectively compare these models is proposed. Synthetic images are generated using a semi-supervised errors-guide method which is also described. Our experiments showed that a synthetic image-based approach outperforms in most cases real image-based training when applied to cross-domain test datasets (+10% precision for GTSRB dataset) and consequently, the generalization of the model is improved decreasing the cost of acquiring images., Comment: 10 pages

After over three decades of unsuccessful attempts, we report the first detection of molecular gas emission in Malin 1, the largest spiral galaxy observed to date, and one of the most iconic giant low surface brightness galaxies. Using ALMA, we detect significant $^{12}$CO(J=1-0) emission in the galaxy's central region and tentatively identify CO emission across three regions on the disc. These observations allow for a better estimate of the H$_2$ mass and molecular gas mass surface density, both of which are remarkably low given the galaxy's scale. By integrating data on its HI mass, we derive a very low molecular-to-atomic gas mass ratio. Overall, our results highlight the minimal presence of molecular gas in Malin 1, contrasting sharply with its extensive, homogeneous atomic gas reservoir. For the first time, we position Malin 1 on the Kennicutt-Schmidt (K-S) diagram, where it falls below the main sequence for normal spirals, consistent with previous upper limits but now with more accurate figures. These findings are crucial for constraining our understanding of star formation processes in environments characterized by extremely low molecular gas densities and for refining models of galaxy formation, thereby improving predictions concerning the formation, evolution, and distribution of these giant, elusive galaxies., Comment: Accepted for publication in The Astrophysical Journal Letters. Published

Evanescently coupled waveguide arrays provide a tabletop platform to realize a variety of Hamiltonians, where physical waveguides correspond to the individual sites of a tight-binding lattice. Nontrivial spatial structure of the waveguide modes enriches this picture and uncovers further possibilities. Here, we demonstrate that the effective coupling between $p$-like modes of adjacent photonic waveguides changes its sign depending on their relative orientation vanishing for a proper alignment at a so-called magic angle. Using femtosecond laser-written waveguides, we demonstrate this experimentally for $p$-mode dimers and graphene-like photonic lattices exhibiting quasi-flat bands at this angle. We observe diffraction-free propagation of corner and bulk states providing a robust experimental evidence of a two-dimensional Aharonov-Bohm-like caging in an optically switchable system., Comment: 7 pages, 5 figures, 8 page-long Supplementary Materials

The higher-rank numerical range is a convex compact set generalizing the classical numerical range of a square complex matrix, first appearing in the study of quantum error correction. We will discuss some of the real algebraic and convex geometry of these sets, including a generalization of Kippenhahn's theorem, and describe an algorithm to explicitly calculate the higher-rank numerical range of a given matrix., Comment: 26 pages, 8 figures

Bias assessment of news sources is paramount for professionals, organizations, and researchers who rely on truthful evidence for information gathering and reporting. While certain bias indicators are discernible from content analysis, descriptors like political bias and fake news pose greater challenges. In this paper, we propose an extension to a recently presented news media reliability estimation method that focuses on modeling outlets and their longitudinal web interactions. Concretely, we assess the classification performance of four reinforcement learning strategies on a large news media hyperlink graph. Our experiments, targeting two challenging bias descriptors, factual reporting and political bias, showed a significant performance improvement at the source media level. Additionally, we validate our methods on the CLEF 2023 CheckThat! Lab challenge, outperforming the reported results in both, F1-score and the official MAE metric. Furthermore, we contribute by releasing the largest annotated dataset of news source media, categorized with factual reporting and political bias labels. Our findings suggest that profiling news media sources based on their hyperlink interactions over time is feasible, offering a bird's-eye view of evolving media landscapes., Comment: Accepted to CLEF 2024