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In the 2022-23 school year, Arizona began implementation of a "universal voucher" program through which all school-age students are eligible for a voucher, and families can use public funding to underwrite private or homeschool education for their children. Universal vouchers in Arizona are an expansion of the existing Empowerment Scholarship Account (ESA) program, which was targeted to students with special education needs or in specific circumstances. To better understand this program's impact on Arizona public schools, this report undertook a financial review of the expanded Arizona ESA program using publicly available data from the state budget, which details total state expenditures and student enrollment; Arizona Department of Education (ADE) quarterly reports to the State Board of Education, which detail the number of ESA applications received, approved, and denied; and ADE enrollment figures. The authors analyzed student enrollment in the program, the combined cost of the earlier enacted ESA program and the new universal voucher program, and their effects on education funding in the state. This report outlines the cost estimates and calculations in detail.

The $J/\psi$ and $\psi(2S)$ charmonium states, composed of $c\bar{c}$ quark pairs and known since the 1970s, are widely believed to serve as ideal probes to test quantum chromodynamics in high-energy hadronic interactions. However, there is not yet a complete understanding of the charmonium-production mechanism. Recent measurements of $J/\psi$ production as a function of event charged-particle multiplicity at the collision energies of both the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) show enhanced $J/\psi$ production yields with increasing multiplicity. One potential explanation for this type of dependence is multiparton interactions (MPI). We carry out the first measurements of self-normalized $J/\psi$ yields and the $\psi(2S)$ to $J/\psi$ ratio at both forward and backward rapidities as a function of self-normalized charged-particle multiplicity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV. In addition, detailed {\sc pythia} studies tuned to RHIC energies were performed to investigate the MPI impacts. We find that the PHENIX data at RHIC are consistent with recent LHC measurements and can only be described by {\sc pythia} calculations that include MPI effects. The forward and backward $\psi(2S)$ to $J/\psi$ ratio, which serves as a unique and powerful approach to study final-state effects on charmonium production, is found to be less dependent on the charged-particle multiplicity., Comment: 301 authors from 69 institutions, 8 pages, 3 figures. v1 is version submitted to Physical Review D Letters. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

Knitting turns a one dimensional yarn into a highly ramified three-dimensional structure. As a method of additive manufacturing, it holds promise for a new class of lightweight, ultrastrong materials. Here we present a purely geometric model to predict the three-dimensional folding of knitted fabrics made only of the two traditional stitches, knit and purl., Comment: 7 pages, 3 figures, the whole megillah

We are interested in the problem of classifying Multivariate Hawkes Processes (MHP) paths coming from several classes. MHP form a versatile family of point processes that models interactions between connected individuals within a network. In this paper, the classes are discriminated by the exogenous intensity vector and the adjacency matrix, which encodes the strength of the interactions. The observed learning data consist of labeled repeated and independent paths on a fixed time interval. Besides, we consider the high-dimensional setting, meaning the dimension of the network may be large {\it w.r.t.} the number of observations. We consequently require a sparsity assumption on the adjacency matrix. In this context, we propose a novel methodology with an initial interaction recovery step, by class, followed by a refitting step based on a suitable classification criterion. To recover the support of the adjacency matrix, a Lasso-type estimator is proposed, for which we establish rates of convergence. Then, leveraging the estimated support, we build a classification procedure based on the minimization of a $L_2$-risk. Notably, rates of convergence of our classification procedure are provided. An in-depth testing phase using synthetic data supports both theoretical results.

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 534 authors from 83 institutions, 12 pages, 7 figures. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

The mass cycle of solar prominences or filaments is still not completely understood. Researchers agree that these dense structures form by coronal in-situ condensations and plasma siphoning from the underlying chromosphere. In the evaporation-condensation model siphoning arises due to evaporation of chromospheric plasma from localised footpoint heating but this is challenging to justify observationally. Here, we simulate the reconnection-condensation model at extreme-resolutions down to 20.8 km within a three-dimensional magnetohydrodynamic coronal volume. We form a draining, quiescent prominence and associated coronal rain simultaneously. We show that thermal instability --acting as a trigger for local condensation formation-- by itself drives siphoning flows from the low-corona without the need of any localised heating. In addition, for the first time we demonstrate through a statistical analysis along more than 1000 magnetic field lines that cold condensations give rise to siphoning flows within magnetic threads. This siphoning arises from the strong pressure gradient along field lines induced by thermal instability. No correlation is found between siphoning flows and the prominence mass, making thermal instability the main in-situ mass collection mechanism. Our simulated prominence drains by gliding along strongly sheared, asymmetric, dipped magnetic arcades, and develops natural vertical fine-structure in an otherwise horizontal magnetic field due to the magnetic Rayleigh-Taylor instability. By synthesising our data, our model shows remarkable agreement with observations of quiescent prominences such as its dark coronal cavity in extreme-ultraviolet emission channels, fine-scale vertical structure and reconnection outflows which, for the first time, have been self-consistently obtained as the prominence evolves.

Electron-neutrino charged-current interactions with xenon nuclei were modeled in the nEXO neutrinoless double-beta decay detector (~5-tonne, 90% ${}^{136}$Xe, 10% ${}^{134}$Xe) to evaluate its sensitivity to supernova neutrinos. Predictions for event rates and detectable signatures were modeled using the MARLEY event generator. We find good agreement between MARLEY's predictions and existing theoretical calculations of the inclusive cross sections at supernova neutrino energies. The interactions modeled by MARLEY were simulated within the nEXO simulation framework and were run through an example reconstruction algorithm to determine the detector's efficiency for reconstructing these events. The simulated data, incorporating the detector response, were used to study the ability of nEXO to reconstruct the incident electron-neutrino spectrum and these results were extended to a larger xenon detector of the same isotope enrichment. We estimate that nEXO will be able to observe electron-neutrino interactions with xenon from supernovae as far as 5 to 8 kpc from earth, while the ability to reconstruct incident electron-neutrino spectrum parameters from observed interactions in nEXO is limited to closer supernovae., Comment: 17 pages, 16 figures

Pauli matrices and Pauli strings are widely used in quantum computing. These mathematical objects are useful to describe or manipulate the quantum state of qubits. They offer a convenient basis to express operators and observables used in different problem instances such as molecular simulation and combinatorial optimization. Therefore, it is important to have a well-rounded, versatile and efficient tool to handle a large number of Pauli strings and operators expressed in this basis. This is the objective behind the development of the PauliArray library presented in this work. This library introduces data structures to represent arrays of Pauli strings and operators as well as various methods to modify and combine them. Built using NumPy, PauliArray offers fast operations and the ability to use broadcasting to easily carry out otherwise cumbersome manipulations. Applications to the fermion-to-qubit mapping, to the estimation of expectation values and to the computation of commutators are considered to illustrate how PauliArray can simplify some relevant tasks and accomplish them faster than current libraries., Comment: 10 pages, 4 figures, submitted to IEEE Quantum Week 2024, GitHub repository : https://github.com/algolab-quantique/pauliarray, Documentation : https://algolab-quantique.github.io/pauliarray/index.html

Let $p>3$ be a prime number and $K$ be an imaginary quadratic field where $p$ splits. Let $K_\infty$ be the $\mathbf{Z}_p^2$-extension of $K$ and let $K_n$ be a finite subextension of $K_\infty/K$. Let $E$ be an elliptic curve with good ordinary reduction at $p$. Under some hypotheses, we show that the Mazur-Tate element attached to $E$ over $K_n$ by S. Haran generates the Fitting ideal of the dual Selmer group of $E$ over $K_n$., Comment: 16 pages

Many present-day axion searches attempt to probe the mixing of axions and photons, which occurs in the presence of an external magnetic field. While this process is well-understood in a number of simple and idealized contexts, a strongly varying or highly inhomogeneous background can impact the efficiency and evolution of the mixing in a non-trivial manner. In an effort to develop a generalized framework for analyzing axion-photon mixing in arbitrary systems, we focus in this work on directly solving the axion-modified form of Maxwell's equations across a simulation domain with a spatially varying background. We concentrate specifically on understanding resonantly enhanced axion-photon mixing in a highly magnetized plasma, which is a key ingredient for developing precision predictions of radio signals emanating from the magnetospheres of neutron stars. After illustrating the success and accuracy of our approach for simplified limiting cases, we compare our results with a number of analytic solutions recently derived to describe mixing in these systems. We find that our numerical method demonstrates a high level of agreement with one, but only one, of the published results. Interestingly, our method also recovers the mixing between the axion and magnetosonic-t and Alfv\'{e}n modes; these modes cannot escape from the regions of dense plasma, but could non-trivially alter the dynamics in certain environments. Future work will focus on extending our calculations to study resonant mixing in strongly variable backgrounds, mixing in generalized media (beyond the strong magnetic field limit), and the mixing of photons with other light bosonic fields, such as dark photons., Comment: 15 pages, 7 figures + appendix

In this paper, a new model-free anomaly detection framework is proposed for time-series induced by industrial dynamical systems. The framework lies in the category of conventional approaches which enable appealing features such as, a fast learning with reduced amount of learning data, a reduced memory, a high potential for explainability as well as easiness of incremental learning mechanism to incorporate operator feedback after an alarm is raised an analyzed. All these are crucial features towards acceptance of data-driven solution by industry but they are rarely considered in the comparisons between competing methods which generally exclusively focus on performance metrics. Moreover, the features engineering step involved in the proposed framework is inspired by the time-series being implicitly governed by physical laws as it is generally the case in industrial time-series. Two examples are given to assess the efficiency of the proposed approach., Comment: 25 pages, 2 tables, 12 figures, 1 appendix

Atmospheric escape is thought to significantly influence the evolution of exoplanets, especially for sub-Jupiter planets on short orbital periods. Theoretical models predict that hydrodynamic escape could erode the atmospheres of such gaseous planets, leaving only a rocky core. Deriving atmospheric mass-loss rates from observations is necessary to check these predictions. One of the ways to obtain mass-loss rate estimates is to fit transit spectra of the 10830 {\AA} helium or UV metal lines with Parker wind models. We aim to provide the community with a tool that enables performing this type of analysis, and present sunbather, an open-source Python code to model escaping exoplanet atmospheres and their transit spectra. sunbather incorporates the Parker wind code p-winds and the photoionization code Cloudy, with the ability to calculate any currently known spectral tracer at an arbitrary atmospheric composition. With sunbather, we investigate how the atmospheric structure of a generic hot Neptune planet depends on the metallicity. We find that the mass-loss rate drops by roughly one order of magnitude as we increase the metallicity from solar to 50 times solar. Line cooling by metal species is important already for a solar composition, and more so at higher metallicity. We then demonstrate how sunbather can be used to interpret observations of spectral lines that form in the upper atmosphere. We fit the observed helium spectrum of the mini-Neptune TOI-2134 b and show how even for helium data, the inferred mass-loss rate depends on the metallicity by up to a factor of three., Comment: Accepted to A&A

The lack of close-in Neptune-mass exoplanets evident in transit surveys has largely been attributed either to photoevaporative mass loss or high-eccentricity migration. To distinguish between these two possibilities, we investigate the origins of TOI-1259 A b, a Saturn-mass (0.4 M$_J$, 1.0 R$_J$) exoplanet lying along the upper edge of the Neptune desert. TOI-1259 A b's close-in ($P$ = 3.48 days) orbit and low bulk density make the planet particularly vulnerable to photoevaporation. Using transits observed in the 1083 nm metastable helium line, we probe the upper atmosphere of TOI-1259 A b with the Hale Telescope at Palomar Observatory and the Near-Infrared Spectrograph on Keck II. We report an excess absorption of $0.395\pm{0.072}\%$ with Palomar and a blueshifted absorption of $2.4\pm0.52\%$ with Keck, consistent with an extended escaping atmosphere. Fitting this signal with a Parker wind model, we determine a corresponding atmospheric mass loss rate of log($\dot{M}$) = $10.33\pm 0.13$ g/s for a thermosphere temperature of $8400^{+1200}_{-1000}$ K based on the Palomar absorption and log($\dot{M}$) = $10.0\pm 0.1$ g/s for a thermosphere temperature of $8200^{+1000}_{-900}$ K based on the Keck absorption. This relatively low rate suggests that this planet would not have been significantly altered by mass loss even if it formed in-situ. However, the presence of a white dwarf companion, TOI-1259 B, hints that this planet may not have formed close-in, but rather migrated inward relatively late. Given the estimated parameters of the proto-white dwarf companion, we find that high-eccentricity migration is possible for the system., Comment: Submitted to the Astronomical Journal (13 pages, 6 figures)

Super-puffs are planets with exceptionally low densities ($\rho \lesssim 0.1$~g~cm$^{-3}$) and core masses ($M_c \lesssim 5 M_\oplus$). Many lower-mass ($M_p\lesssim10M_\oplus$) super-puffs are expected to be unstable to catastrophic mass loss via photoevaporation and/or boil-off, whereas the larger gravitational potentials of higher-mass ($M_p\gtrsim10M_\oplus$) super-puffs should make them more stable to these processes. We test this expectation by studying atmospheric loss in the warm, higher-mass super-puff TOI-1420b ($M = 25.1M_\oplus$, $R = 11.9R_\oplus$, $\rho = 0.08$~g~cm$^{-3}$, $T_\mathrm{eq} = 960$~K). We observed one full transit and one partial transit of this planet using the metastable helium filter on Palomar/WIRC and found that the helium transits were $0.671\pm0.079\%$ (8.5$\sigma$) deeper than the TESS transits, indicating an outflowing atmosphere. We modeled the excess helium absorption using a self-consistent 1D hydrodynamics code to constrain the thermal structure of the outflow given different assumptions for the stellar XUV spectrum. These calculations then informed a 3D simulation which provided a good match to the observations with a modest planetary mass-loss rate of $10^{10.82}$~g~s$^{-1}$ ($M_p/\dot{M}\approx70$~Gyr). Super-puffs with $M_p\gtrsim10M_\oplus$, like TOI-1420b and WASP-107b, appear perfectly capable of retaining atmospheres over long timescales; therefore, these planets may have formed with the unusually large envelope mass fractions they appear to possess today. Alternatively, tidal circularization could have plausibly heated and inflated these planets, which would bring their envelope mass fractions into better agreement with expectations from core-nucleated accretion., Comment: 18 pages, 8 figures, accepted to AJ

We present a multidimensional data analysis framework for the analysis of ordinal response variables. Underlying the ordinal variables, we assume a continuous latent variable, leading to cumulative logit models. The framework includes unsupervised methods, when no predictor variables are available, and supervised methods, when predictor variables are available. We distinguish between dominance variables and proximity variables, where dominance variables are analyzed using inner product models, whereas the proximity variables are analyzed using distance models. An expectation-majorization-minimization algorithm is derived for estimation of the parameters of the models. We illustrate our methodology with data from the International Social Survey Programme.

We propose a new mapping tool for supervised and unsupervised analysis of multivariate binary data with multiple items, questions, or response variables. The mapping assumes an underlying proximity response function, where participants can have multiple reasons to disagree or say ``no'' to a question. The probability to endorse, or to agree with an item depends on an item specific parameter and the distance in a joint space between a point representing the item and a point representing the participant. The item specific parameter defines a circle in the joint space around the location of the item such that for participants positioned within the circle the probability is larger than 0.5. For map estimation, we develop and test an MM-algorithm in which the negative likelihood function is majorized with a weighted least squares function. The weighted least squares function can be minimized with standard algorithms for multidimensional unfolding, except that negative working dissimilarities may occur in the iterative process. To illustrate the new mapping, two empirical data sets are analyzed. The mappings are interpreted in detail and the unsupervised map is compared to a visualization based on correspondence analysis. In a Monte Carlo study, we test the performance of the algorithm in terms of recovery of population parameters and conclude that this recovery is adequate. A second Monte Carlo study investigates the predictive performance of the new mapping compared to a similar mapping with a monotone response function.

In this paper we study the Cayley graph $\mathrm{Cay}(S_n,T)$ of the symmetric group $S_n$ generated by a set of transpositions $T$. We show that for $n\geq 5$ the Cayley graph is normal. As a corollary, we show that its automorphism group is a direct product of $S_n$ and the automorphism group of the transposition graph associated to $T$. This provides an affirmative answer to a conjecture raised by Ganesan in arXiv:1703.08109, showing that $\mathrm{Cay}(S_n,T)$ is normal if and only if the transposition graph is not $C_4$ or $K_n$., Comment: 10 pages, 3 figures

Approximately 1.3 million public school students in the United States were identified by their schools or districts as experiencing some form of homelessness in 2019-20. The housing instability faced by these students is associated with a range of acute needs, including transportation, food security, health care, and emotional and mental health. These challenges have negative impacts for student learning and are associated with lower academic achievement and attainment. This brief reviews major federal and state sources of funding for students experiencing homelessness. It finds that federal funding is insufficient to achieve the goals of federal law and is unevenly distributed. Further, only four states provide dedicated funding to support students experiencing homelessness. Recommendations include increases in funding and an entitlement formula for the McKinney-Vento Act, as well as expansion of allowable uses of funds to cover acute needs, and more informative data about resource use. [For the full report, see ED630219.]

Approximately 1.3 million public school students in the United States were identified as experiencing some form of homelessness in 2019-20. Due to their unstable living situations, students experiencing homelessness often have additional educational, social, emotional, and material needs compared to their stably housed peers. Housing instability can result in increased absences from school and can lead to students changing schools midyear. Each school move can disrupt students' education and limit opportunities to learn. The multiple challenges associated with homelessness negatively impact student learning outcomes. Reading, mathematics, and science scores for students experiencing homelessness tend to be lower than those of their peers, including those from economically disadvantaged but residentially stable families. While there is a need to focus attention on students experiencing homelessness, school districts may face barriers supporting them. These barriers include unstable funding or funding that is inadequate to meet student needs, and restrictions on the allowable uses of federal funds, which limits district ability to support noneducational expenses, such as for emergency housing. In addition, prior research has found that funding may help districts identify students experiencing homelessness, and without sufficient funding, fewer students are able to be identified as needing support, leading to inadequate services. The purpose of the report is to examine the federal and state funding sources directed to schools to support students experiencing homelessness. [For the research brief, see ED630220.]

The PHENIX experiment has performed a systematic study of identified charged-hadron ($\pi^\pm$, $K^\pm$, $p$, $\bar{p}$) production at midrapidity in $p$$+$Al, $^3$He$+$Au, Cu$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV and U$+$U collisions at $\sqrt{s_{_{NN}}}=193$ GeV. Identified charged-hadron invariant transverse-momentum ($p_T$) and transverse-mass ($m_T$) spectra are presented and interpreted in terms of radially expanding thermalized systems. The particle ratios of $K/\pi$ and $p/\pi$ have been measured in different centrality ranges of large (Cu$+$Au, U$+$U) and small ($p$$+$Al, $^3$He$+$Au) collision systems. The values of $K/\pi$ ratios measured in all considered collision systems were found to be consistent with those measured in $p$$+$$p$ collisions. However the values of $p/\pi$ ratios measured in large collision systems reach the values of $\approx0.6$, which is $\approx2$ times larger than in $p$$+$$p$ collisions. These results can be qualitatively understood in terms of the baryon enhancement expected from hadronization by recombination. Identified charged-hadron nuclear-modification factors ($R_{AB}$) are also presented. Enhancement of proton $R_{AB}$ values over meson $R_{AB}$ values was observed in central $^3$He$+$Au, Cu$+$Au, and U$+$U collisions. The proton $R_{AB}$ values measured in $p$$+$Al collision system were found to be consistent with $R_{AB}$ values of $\phi$, $\pi^\pm$, $K^\pm$, and $\pi^0$ mesons, which may indicate that the size of the system produced in $p$$+$Al collisions is too small for recombination to cause a noticeable increase in proton production., Comment: 480 authors from 78 institutions, 18 pages, 6 tables, 16 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

Big data and large-scale machine learning have had a profound impact on science and engineering, particularly in fields focused on forecasting and prediction. Yet, it is still not clear how we can use the superior pattern matching abilities of machine learning models for scientific discovery. This is because the goals of machine learning and science are generally not aligned. In addition to being accurate, scientific theories must also be causally consistent with the underlying physical process and allow for human analysis, reasoning, and manipulation to advance the field. In this paper, we present a case study on discovering a new symbolic model for oceanic rogue waves from data using causal analysis, deep learning, parsimony-guided model selection, and symbolic regression. We train an artificial neural network on causal features from an extensive dataset of observations from wave buoys, while selecting for predictive performance and causal invariance. We apply symbolic regression to distill this black-box model into a mathematical equation that retains the neural network's predictive capabilities, while allowing for interpretation in the context of existing wave theory. The resulting model reproduces known behavior, generates well-calibrated probabilities, and achieves better predictive scores on unseen data than current theory. This showcases how machine learning can facilitate inductive scientific discovery, and paves the way for more accurate rogue wave forecasting.

We consider the steady state limiting current that can be carried by an infinite periodic array of thin electron sheets spaced by period p in a planar diode of gap voltage V and gap separation d. Our primary assumptions are (1) electron motion is restricted by an infinite magnetic field to the direction normal to the electrode surfaces, (2) all electrons are emitted from the cathode with initial kinetic energy Ein, and (3) electron motion is non-relativistic. The limiting current density, averaged over a period and normalized to the classical 1D Child-Langmuir (CL) current density (including a factor that accounts for non-zero Ein), is found to depend only on the two dimensionless parameters p/d and Ein/eV. This average limiting current density is computed from the maximum current density for which the iterative solution of a non-linear integral equation converges. Numerical results and empirical curve fits for the limiting current are presented, together with an analysis as p/d and Ein/eV approach zero or infinity, in which cases previously published results are recovered. Our main finding is that, while the local anode current density within each electron sheet is infinite in our model (that is, it exceeds the classical 1D CL value by an 'infinite' factor), the period average anode current density is in fact still bounded by the classical 1D CL value. This study therefore provides further evidence that the classical 1D Child-Langmuir current density is truly a fundamental limit that cannot be circumvented., Comment: This material has been submitted to Physics of Plasmas. After it is published, it will be found at https://pubs.aip.org/aip/pop

Advocating for a sustainable, resilient and human-centric industry, the three pillars of Industry 5.0 call for an increased understanding of industrial processes and manufacturing systems, as well as their energy sustainability. One of the most fundamental elements of comprehension is knowing when the systems are operated, as this is key to locating energy intensive subsystems and operations. Such knowledge is often lacking in practice. Activation statuses can be recovered from sensor data though. Some non-intrusive sensors (accelerometers, current sensors, etc.) acquire mixed signals containing information about multiple actuators at once. Despite their low cost as regards the fleet of systems they monitor, additional signal processing is required to extract the individual activation sequences. To that end, sparse regression techniques can extract leading dynamics in sequential data. Notorious dictionary learning algorithms have proven effective in this regard. This paper considers different industrial settings in which the identification of binary subsystem activation sequences is sought. In this context, it is assumed that each sensor measures an extensive physical property, source signals are periodic, quasi-stationary and independent, albeit these signals may be correlated and their noise distribution is arbitrary. Existing methods either restrict these assumptions, e.g., by imposing orthogonality or noise characteristics, or lift them using additional assumptions, typically using nonlinear transforms.

Recent measurements of the reactor antineutrino emission show that there exists a spectral excess (the "bump") in the 5-7 MeV region when compared to the Huber-Muller prediction based on the conversion method. Analysis within an alternate prediction technique, the summation method, suggests that the bump could be due to excess contributions from a certain few of the beta-decaying fission products. However, it has been shown that when updated fission yield values are used in the summation method, the predicted excess vanishes. In the present preliminary study, fission yields for nuclides suspected of causing the neutrino spectral bump are investigated using gamma-ray spectroscopy of U-235 and Pu-239 samples freshly irradiated using the High Flux Isotope Reactor. For several of the suspect nuclides, the derived fission yields are consistent with JEFF3.3 fission yield library. The exception is the case of Cs-140 from Pu-239, where the discrepancy between the fitted and expected values suggests a potential error in the fission yield library. This highlights the importance of using accurate nuclear data libraries in the analysis of the reactor antineutrino spectra, and the need for ongoing efforts to improve these libraries., Comment: 7 pages

We consider the limiting current from an emitting patch whose size is much smaller than the anode-cathode spacing. The limiting current is formulated in terms of an integral equation. It is solved iteratively, first to numerically recover the classical one-dimensional Child-Langmuir law, including Jaffe's extension to a constant, nonzero electron emission velocity. We extend to 2-dimensions in which electron emission is restricted to an infinitely long stripe with infinitesimally narrow stripe width, so that the emitted electrons form an electron sheet. We next extend to 3-dimensions in which electron emission is restricted to a square tile (or a circular patch) with an infinitesimally small tile size (or patch radius), so that the emitted electrons form a needle-like line charge. Surprisingly, for the electron needle problem, we only find the null solution for the total line charge current, regardless of the assumed initial electron velocity. For the electron sheet problem, we also find only the null solution for the total sheet current if the electron emission velocity is assumed to be zero, and the total maximum sheet current becomes a finite, nonzero value if the electron emission velocity is assumed to be nonzero. These seemingly paradoxical results are shown to be consistent with the earlier works of the Child-Langmuir law of higher dimensions. They are also consistent with, or perhaps even anticipated by, the more recent theories and simulations on thermionic cathodes that used realistic work function distributions to account for patchy, nonuniform electron emission. The mathematical subtleties are discussed.

Recent work has shown that axions can be efficiently produced via non-stationary pair plasma discharges in the polar cap region of pulsars. Here, we point out that for axion masses $10^{-9} \, {\rm eV} \lesssim m_a \lesssim 10^{-4} \, \rm eV$, a sizable fraction of the sourced axion population will be gravitationally confined to the neutron star. These axions accumulate over astrophysical timescales, thereby forming a dense `axion cloud' around the star. We argue that the existence of such a cloud, with densities reaching and potentially exceeding $\mathcal{O}(10^{22}) \, {\rm GeV \, cm^{-3}}$, is a generic expectation across a wide range of parameter space. For axion masses $m_a \gtrsim 10^{-7} \, \rm eV$, energy is primarily radiated from the axion cloud via resonant axion-photon mixing, generating a number of distinctive signatures that include: a sharp line in the radio spectrum of each pulsar (located at the axion mass, and with a percent-level width), and transient events arising from the reconfiguration of charge densities in the magnetosphere. While a deeper understanding of the systematic uncertainties in these systems is required, our current estimates suggest that existing radio telescopes could improve sensitivity to the axion-photon coupling by more than an order of magnitude., Comment: 17 pages, 14 figures

Photoevaporative mass-loss rates are expected to be highest when planets are young and the host star is more active, but to date there have been relatively few measurements of mass-loss rates for young gas giant exoplanets. In this study we measure the present-day atmospheric mass-loss rate of TOI-1268b, a young (110 - 380 Myr) and low density (0.71$^{+0.17}_{-0.13}$~g~cm$^{-3}$) hot Saturn located near the upper edge of the Neptune desert. We use Palomar/WIRC to search for excess absorption in the 1083~nm helium triplet during two transits of TOI-1268b. We find that it has a larger transit depth ($0.285_{-0.050}^{+0.048}\%$ excess) in the helium bandpass than in the TESS observations, and convert this excess absorption into a mass-loss rate by modeling the outflow as a Parker wind. Our results indicate that this planet is losing mass at a rate of $\log \dot{M} = 10.2 \pm 0.3$~g~s$^{-1}$ and has a thermosphere temperature of 6900$^{+1800}_{-1200}$~K. This corresponds to a predicted atmospheric lifetime much larger than 10 Gyr. Our result suggests that photoevaporation is weak in gas giant exoplanets even at early ages., Comment: Published at The Astronomical Journal (9 pages, 4 figures)