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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)

Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems may be broadly assessed by their range of reliably accessible states and the strength of magnon coupling phenomena and nonlinearities. Increasingly, nanomagnetic systems are expanding into three-dimensional architectures. This has enhanced the range of available magnetic microstates and functional behaviours, but engineering control over 3D states and dynamics remains challenging. Here, we introduce a 3D magnonic metamaterial composed from multilayered artificial spin ice nanoarrays. Comprising two magnetic layers separated by a non-magnetic spacer, each nanoisland may assume four macrospin or vortex states per magnetic layer. This creates a system with a rich $16^N$ microstate space and intense static and dynamic dipolar magnetic coupling. The system exhibits a broad range of emergent phenomena driven by the strong inter-layer dipolar interaction, including ultrastrong magnon-magnon coupling with normalised coupling rates of $\frac{\Delta \omega}{\gamma} = 0.57$, GHz mode shifts in zero applied field and chirality-selective magneto-toroidal microstate programming and corresponding magnonic spectral control.

Escaping exoplanet atmospheres have been observed as deep transit signatures in a few specific spectral lines. Detections have been made in the hydrogen Ly-$\alpha$ line, the metastable helium line at 10830 {\AA} and some UV lines of metallic species. Observational challenges, unexpected non-detections and model degeneracies have generally made it difficult to draw definitive conclusions about the escape process for individual planets. Expanding on the suite of spectral tracers used may help to mitigate these challenges. We present a new framework for modeling the transmission spectrum of hydrodynamically escaping atmospheres. We predict FUV to NIR spectra for systems with different planet and stellar types and identify new lines that can potentially be used to study their upper atmospheres. Measuring the radius in the atmosphere at which the strongest lines form puts them into context within the upper atmospheric structure. Targeting a set of complementary spectral lines for the same planet will help us to better constrain the outflow properties., Comment: Accepted for publication in A&A

In California, approximately 47,000 students live in foster care (in 2018-19, around 0.7% of the student population). The reasons for entry into foster care are multiple, complex, and often intertwined with the social and environmental challenges associated with poverty. The COVID-19 pandemic has further exacerbated the social and environmental challenges facing students. Because many schools, child welfare agencies, courts, and other businesses and agencies closed for much of the 2019-20 and 2020-21 school years, students in foster care experienced reduced access to in-person education and supports. As the state and schools work to recover from the pandemic, sustained attention will be necessary to ensure these students have access to the services they need to succeed. Using pre-COVID-19 statewide education data and interviews with foster youth services coordinators at county offices of education, this report examines the school conditions and education outcomes for students in foster care; the organizational, logistical, and data challenges to providing coordinated support; and promising practices for future supports.