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We present a deep learning-based approach to studying dynamic clinical behavioral regimes in diverse non-randomized healthcare settings. Our proposed methodology - deep causal behavioral policy learning (DC-BPL) - uses deep learning algorithms to learn the distribution of high-dimensional clinical action paths, and identifies the causal link between these action paths and patient outcomes. Specifically, our approach: (1) identifies the causal effects of provider assignment on clinical outcomes; (2) learns the distribution of clinical actions a given provider would take given evolving patient information; (3) and combines these steps to identify the optimal provider for a given patient type and emulate that provider's care decisions. Underlying this strategy, we train a large clinical behavioral model (LCBM) on electronic health records data using a transformer architecture, and demonstrate its ability to estimate clinical behavioral policies. We propose a novel interpretation of a behavioral policy learned using the LCBM: that it is an efficient encoding of complex, often implicit, knowledge used to treat a patient. This allows us to learn a space of policies that are critical to a wide range of healthcare applications, in which the vast majority of clinical knowledge is acquired tacitly through years of practice and only a tiny fraction of information relevant to patient care is written down (e.g. in textbooks, studies or standardized guidelines).

Recently, there has been interest in representing single graphs by multiple drawings; for example, using graph stories, storyplans, or uncrossed collections. In this paper, we apply this idea to orthogonal graph drawing. Due to the orthogonal drawing style, we focus on plane 4-graphs, that is, planar graphs of maximum degree 4 whose embedding is fixed. Our goal is to represent any plane 4-graph $G$ by an unbent collection, that is, a collection of orthogonal drawings of $G$ that adhere to the embedding of $G$ and ensure that each edge of $G$ is drawn without bends in at least one of the drawings. We investigate two objectives. First, we consider minimizing the number of drawings in an unbent collection. We prove that every plane 4-graph can be represented by a collection with at most three drawings, which is tight. We also give sufficient conditions for a graph to admit an unbent collection of size 2. Second, we consider minimizing the total number of bends over all drawings in an unbent collection. We show that this problem is NP-hard and give a 3-approximation algorithm. For the special case of plane triconnected cubic graphs, we show how to compute minimum-bend collections in linear time., Comment: 42 pages, 18 figures

We present a comprehensive theoretical framework describing single pion resonant production through inelastic dark fermion-nucleon interactions mediated by resonances in the GeV-scale regime. Building upon the Rein-Sehgal approach, we derive differential cross sections for processes in which an incoming dark fermion scatters off a nucleon, exciting a resonance that subsequently decays into a nucleon and a pion. Our formulation accommodates various mediator types-namely, dark photons with vector and axial couplings, as well as scalar and pseudoscalar mediators-thereby extending the conventional approach that Rein, Sehgal and Berger performed for neutrino interactions. Transition form factors for the nucleon-to-resonance conversion are computed using the relativistic harmonic-oscillator quark model from Feynman, Kislinger and Ravndal, while a Breit-Wigner prescription is employed to incorporate finite resonance widths. This framework offers a robust tool for interpreting experimental data in dark sector and matter searches and represents a contribution to elucidate the role of resonances in GeV-scale phenomenology., Comment: 16 pages, 3 figures, 1 table

We present MicroBooNE's first search for dark sector $e^+e^-$ explanations of the long-standing MiniBooNE anomaly. The MiniBooNE anomaly has garnered significant attention over the past 20 years including previous MicroBooNE investigations into both anomalous electron and photon excesses, but its origin still remains unclear. In this letter, we provide the first direct test of dark sector models in which dark neutrinos, produced through neutrino-induced scattering, decay into missing energy and visible $e^+e^-$ pairs comprising the MiniBooNE anomaly. Many such models have recently gained traction as a viable solution to the anomaly while evading past bounds. Using an exposure of $6.87 \times 10^{20}$ protons-on-target in the Booster Neutrino Beam, we implement a selection targeting forward-going, coherently produced $e^+e^-$ events. After unblinding, we observe 95 events, which we compare with the constrained background-only prediction of $69.7 \pm 17.3$. This analysis sets the world's first direct limits on these dark sector models and, at the 95\% confidence level, excludes the majority of the parameter space viable as a solution to the MiniBooNE anomaly., Comment: 7 pages, 5 figures, Supplemental Materials included in Ancillary files

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20\% increase in the efficiency of sub-1\,cm vertex reconstruction across all neutrino flavours., Comment: 32 pages, 18 figures

Data plane programming enables the programmability of network devices with domain-specific programming languages, like P4. One commonly used P4-programmable hardware target is the Intel Tofino switching ASIC. The runtime behavior of an implemented P4 program on Tofino can be configured with shell scripts or a Python library from Barefoot provided with the Tofino. Both are limited in their capabilities and usability. This paper introduces the Rust Barefoot Runtime (RBFRT), a Rust-based control plane library. The RBFRT provides a fast and memory-safe interface to configure the Intel Tofino. We showed that the RBFRT achieves a higher insertion rate for MAT entries and has a shorter response time compared to the Python library.

P4TG is a hardware-based traffic generator (TG) running on the Intel Tofino 1 ASIC and was programmed using the programming language P4. In its initial version, P4TG could generate up to 10x100 Gb/s of traffic and directly measure rates, packet loss, and other metrics in the data plane. Many researchers and industrial partners requested new features to be incorporated into P4TG since its publication in 2023. With the recently added features, P4TG supports the generation of packets encapsulated with a customizable VLAN, QinQ, VxLAN, MPLS, and SRv6 header. Further, generation of IPv6 traffic is added and P4TG is ported to the Intel Tofino 2 platform enabling a generation capability of up to 10x400 Gb/s. The improvement in user experience focuses on ease of operation. Features like automated ARP replies, improved visualization, report generation, and automated testing based on the IMIX distribution and RFC 2544 are added. Future work on P4TG includes NDP to facilitate IPv6 traffic, and a NETCONF integration to further ease the configuration.

The synthesis of aluminum substituted strontium hexaferrite nanoparticles (SrFe12-xAlxO19 with x = 0-3), via three different preparation methods, is investigated. The synthesis methods are hydrothermal autoclave (AC) synthesis, a citrate sol-gel (SG) synthesis and a solid-salt matrix (SSM) sol-gel synthesis. Evaluation of macroscopic magnetic properties and of lattice parameters obtained by Rietveld analysis of powder X-ray diffraction (PXRD) data indicate that successful substitution of Al into the crystal structure is only achieved for the SG method. For the SG sample with x = 3, the coercivity was found to increase by 73% to 830 kA/m, while the saturation magnetization was reduced by 68% to 22.6 Am2/kg compared to the non-substituted x = 0 SG sample. The SSM and AC samples did not show any significant changes in their magnetic properties. To examine the nature of the Al insertion in detail, neutron powder diffraction (NPD) data were collected on the SSM and SG samples. Combined Rietveld refinements of the PXRD and NPD data confirm that effective substitution of the Al ions is only achieved for the SG sample and reveal that Al occupies mainly the (2a)Oh and (12k)Oh sites and to a lesser extent the (4e)BP, (4f)Oh and (4f)Td sites. Moreover, the relative degree of site occupation varies with increasing Al substitution. The intrinsic magnetization according to the refined atomic magnetic moments and Al site occupation fractions was extracted from the NPD data and compared with the measured macroscopic magnetization. A remarkable agreement exists between the two, confirming the robustness and accuracy of the Rietveld analysis.

The evidence of a Stochastic Gravitational Wave Background (SGWB) in the nHz frequency range is posed to open a new window on the Universe. A preferred explanation relies on a supercooled first order phase transition at the 100 MeV - GeV scale. In this article, we address the feasibility going from the particle physics model to the production of the gravitational waves. We take a minimal approach for the dark sector model introducing the fewest ingredients required, namely a new U(1) gauge group and a dark scalar that dynamically breaks the symmetry. Supercooling poses challenges in the analysis that put under question the feasibility of this explanation: we address them, going beyond previous studies by carefully considering the effects of a vacuum domination phase and explicitly tracking the phase transition from its onset to its completion. We find that the proposed model can successfully give origin to the observed PTA SGWB signal. The strong supercooling imposes a correlation between the new gauge coupling and the scalar quartic one, leading to a significant hierarchy between the (heavier) gauge boson and the dark scalar. Ultimately, information on phase transitions from SGWB observations could provide a direct probe of the microphysics of the Early Universe and be used to guide future searches of dark sector in laboratories.

We present the results of the Distant Giants Survey, a three-year radial velocity (RV) campaign to search for wide-separation giant planets orbiting Sun-like stars known to host an inner transiting planet. We defined a distant giant to have $a$ = 1--10 AU and $M_{p} \sin i = 70-4000$ \mearth~ = 0.2-12.5 \mj, and required transiting planets to have $a<1$ AU and $R_{p} = 1-4$ \rearth. We assembled our sample of 47 stars using a single selection function, and observed each star at monthly intervals to obtain $\approx$30 RV observations per target. The final catalog includes a total of twelve distant companions: four giant planets detected during our survey, two previously known giant planets, and six objects of uncertain disposition identified through RV/astrometric accelerations. Statistically, half of the uncertain objects are planets and the remainder are stars/brown dwarfs. We calculated target-by-target completeness maps to account for missed planets. We found evidence for a moderate enhancement of distant giants (DG) in the presence of close-in small planets (CS), P(DG|CS) = $30^{+14}_{-12}\%$, over the field rate of P(DG) = $16^{+2}_{-2}\%$. No enhancement is disfavored ($p \sim$ 8%). In contrast to a previous study, we found no evidence that stellar metallicity enhances P(DG|CS). We found evidence that distant giant companions are preferentially found in systems with multiple transiting planets and have lower eccentricities than randomly selected giant planets. This points toward dynamically cool formation pathways for the giants that do not disturb the inner systems., Comment: 32 pages, 20 figures, 4 tables. Comments welcome

Disparities in access to healthcare have been well-documented in the United States, but their effects on electronic health record (EHR) data reliability and resulting clinical models are poorly understood. Using an All of Us dataset of 134,513 participants, we investigate the effects of access to care on the medical machine learning pipeline, including medical condition rates, data quality, outcome label accuracy, and prediction performance. Our findings reveal that patients with cost constrained or delayed care have worse EHR reliability as measured by patient self-reported conditions for 78% of examined medical conditions. We demonstrate in a prediction task of Type II diabetes incidence that clinical risk predictive performance can be worse for patients without standard care, with balanced accuracy gaps of 3.6 and sensitivity gaps of 9.4 percentage points for those with cost-constrained or delayed care. We evaluate solutions to mitigate these disparities and find that including patient self-reported conditions improved performance for patients with lower access to care, with 11.2 percentage points higher sensitivity, effectively decreasing the performance gap between standard versus delayed or cost-constrained care. These findings provide the first large-scale evidence that healthcare access systematically affects both data reliability and clinical prediction performance. By revealing how access barriers propagate through the medical machine learning pipeline, our work suggests that improving model equity requires addressing both data collection biases and algorithmic limitations. More broadly, this analysis provides an empirical foundation for developing clinical prediction systems that work effectively for all patients, regardless of their access to care., Comment: Presented at ML4H 2024

Superparamagnetic tunnel junctions (sMTJs) are emerging as promising components for stochastic units in neuromorphic computing, owing to their tunable random switching behavior. Conventional MTJ control methods, such as spin-transfer torque (STT) and spin-orbit torque (SOT), often require substantial power. Here, we introduce the voltage-controlled exchange coupling (VCEC) mechanism, enabling switching between antiparallel and parallel states in sMTJs with an ultralow power consumption of only 40 nW, approximately two orders of magnitude lower than conventional STT-based sMTJs. This mechanism yields a sigmoid-shaped output response, making it ideally suited for neuromorphic computing applications. Furthermore, we validate the feasibility of integrating VCEC with the SOT current control, offering an additional dimension for magnetic state manipulation. This work marks the first practical demonstration of VCEC effect in sMTJs, highlighting its potential as a low-power control solution for probabilistic bits in advanced computing systems., Comment: 20 pages, 4 figures

In recent years, intensity interferometry has been successfully applied to the Imaging Atmospheric Cherenkov Telescopes H.E.S.S. , MAGIC, and VERITAS. All three telescope systems have proven the feasibility and capability of this method. After our first campaign in 2022, when two of the H.E.S.S. telescopes in Namibia were equipped with our external setup and the angular diameter of two stars was measured, our setup was upgraded for a second campaign in 2023, where the goal is to perform simultaneous two colour measurements. The second campaign not only involves a third equipped telescope, but also each mechanical setup now includes two interference filters at two different wavelengths (375 nm and 470 nm) with a broader bandwidth of 10 nm. This enables having simultaneous two colour measurements, which yields information about the star's physical size at different wavelengths. This is the first time that simultaneous dual-waveband intensity interferometry measurements are performed. The angular diameter results of the 4 stars, Mimosa (beta Cru), Eta Centauri (eta Cen), Nunki (sigma Sgr) and Dschubba (delta Sco), are reported, where the effects of limb darkening are also taken into account.

The Radio Neutrino Observatory in Greenland (RNO-G) is the first in-ice radio array in the northern hemisphere for the detection of ultra-high energy neutrinos via the coherent radio emission from neutrino-induced particle cascades within the ice. The array is currently in phased construction near Summit Station on the Greenland ice sheet, with 7~stations deployed during the first two boreal summer field seasons of 2021 and 2022. In this paper, we describe the installation and system design of these initial RNO-G stations, and discuss the performance of the array as of summer 2024.

White dwarfs offer a compelling avenue for probing interactions of dark matter particles, particularly in the challenging sub-GeV mass regime. The constraints derived from these celestial objects strongly depend on the existence of high dark matter densities in the corresponding regions of the Universe, where white dwarfs are observed. This implies that excluding the parameter space using local white dwarfs would present a significant challenge, primarily due to the low dark matter density in the solar neighbourhood. This limitation prompts the exploration of alternative scenarios involving dark matter particles with a diverse spectrum of kinetic energies. In this work, we investigate how these dark matter particles traverse the star, interact with stellar matter, and ultimately get captured. To accomplish this, we approximate the dark matter flux as a delta function and inspired on the Three Portal Model, we assume that fermionic dark matter interacts with stellar matter either through a broken $U(1)$ gauge vector mediator or a scalar. In our computations, we consider how interactions might vary across different energy regimes, from high-energy deep inelastic scattering and inelastic scatterings via the production of $N-$ and $\Delta-$ resonances to lower-energy elastic interactions with nucleons and nuclei. Our study models these inelastic resonant interactions with dark matter and vector or scalar mediators for the very first time. We provide insights into the specific conditions required for successfully boosted dark matter capture in white dwarfs. We found that, in general, dark matter capture is most likely to occur at low energies, as expected. However, in the high-energy regime, there remains a small window for capture through resonant and deep inelastic scattering processes., Comment: 24 pages, 7 figures

Effective spoken dialog systems should facilitate natural interactions with quick and rhythmic timing, mirroring human communication patterns. To reduce response times, previous efforts have focused on minimizing the latency in automatic speech recognition (ASR) to optimize system efficiency. However, this approach requires waiting for ASR to complete processing until a speaker has finished speaking, which limits the time available for natural language processing (NLP) to formulate accurate responses. As humans, we continuously anticipate and prepare responses even while the other party is still speaking. This allows us to respond appropriately without missing the optimal time to speak. In this work, as a pioneering study toward a conversational system that simulates such human anticipatory behavior, we aim to realize a function that can predict the forthcoming words and estimate the time remaining until the end of an utterance (EOU), using the middle portion of an utterance. To achieve this, we propose a training strategy for an encoder-decoder-based ASR system, which involves masking future segments of an utterance and prompting the decoder to predict the words in the masked audio. Additionally, we develop a cross-attention-based algorithm that incorporates both acoustic and linguistic information to accurately detect the EOU. The experimental results demonstrate the proposed model's ability to predict upcoming words and estimate future EOU events up to 300ms prior to the actual EOU. Moreover, the proposed training strategy exhibits general improvements in ASR performance., Comment: Submitted to ICASSP2025

Hundreds of exoplanets between 1-1.8 times the size of the Earth have been discovered on close in orbits. However, these planets show such a diversity in densities that some appear to be made entirely of iron, while others appear to host gaseous envelopes. To test this diversity in composition, we update the masses of 5 rocky exoplanets (HD 93963 A b, Kepler-10 b, Kepler-100 b, Kepler-407 b, and TOI-1444 b) and present the confirmation of a new planet (TOI-1011) using 187 high precision RVs from Gemini/MAROON-X and Keck/KPF. Our updated planet masses suggest compositions closer to that of the Earth than previous literature values for all planets in our sample. In particular, we report that two previously identified ``super-Mercuries'' (Kepler-100 b and HD 93963 A b) have lower masses that suggest less iron-rich compositions. We then compare the ratio of iron to rock-building species to the abundance ratios of those elements in their host stars. These updated planet compositions do not suggest a steep relationship between planet and host star compositions, contradictory to previous results, and suggest that planets and host stars have similar abundance ratios., Comment: Submitted to AJ 09/30/2024

Field Programmable Gate Arrays (FPGAs) play a significant role in computationally intensive network processing due to their flexibility and efficiency. Particularly with the high-level abstraction of the P4 network programming model, FPGA shows a powerful potential for packet processing. By supporting the P4 language with FPGA processing, network researchers can create customized FPGA-based network functions and execute network tasks on accelerators directly connected to the network. A feature of the P4 language is that it is stateless; however, the FPGA implementation in this research requires state information. This is accomplished using P4 externs to describe the stateful portions of the design and to implement them on the FPGA using High-Level Synthesis (HLS). This paper demonstrates using an FPGA-based SmartNIC to efficiently extract source-destination IP address information from network packets and construct anonymized network traffic matrices for further analysis. The implementation is the first example of the combination of using P4 and HLS in developing network functions on the latest AMD FPGAs. Our design achieves a processing rate of approximately 95 Gbps with the combined use of P4 and High-level Synthesis and is able to keep up with 100 Gbps traffic received directly from the network.

We have developed a new set of Application-Specific Integrated Circuits (ASICs) of the TARGET family (CTC and CT5TEA), designed for the readout of signals from photosensors in cameras of Imaging Atmospheric Cherenkov Telescopes (IACTs) for ground-based gamma-ray astronomy. We present the performance and design details. Both ASICs feature 16 channels, with CTC being a Switched-Capacitor Array (SCA) sampler at 0.5 to 1 GSa/s with a 16,384 sample deep storage buffer, including the functionality to digitize full waveforms at arbitrary times. CT5TEA is its companion trigger ASIC (though may be used on its own), which provides trigger information for the analog sum of four (and 16) adjacent channels. Since sampling and triggering takes place in two separate ASICs, the noise due to interference from the SCA is suppressed, and allows a minimal trigger threshold of $\leq$ 2.5 mV (0.74 photo electrons (p.e.)) with a trigger noise of $\leq$ 0.5 mV (0.15 p.e.). For CTC, a maximal input voltage range from $-$0.5 V up to 1.7 V is achieved with an effective bit range of $>$ 11.6 bits and a baseline noise of 0.7 mV. The cross-talk improved to $\leq$ 1% over the whole $-$3 dB bandwidth of 220 MHz and even down to 0.2% for 1.5 V pulses of 10 ns width. Not only is the performance presented, but a temperature-stable calibration routine for pulse mode operation is introduced and validated. The resolution is found to be $\sim$ 2.5% at 33.7 mV (10 p.e.) and $\leq$ 0.3% at 337 mV (100 p.e.) with an integrated non-linearity of $<$ 1.6 mV. Developed for the Small-Sized Telescope (SST) and Schwarzschild-Couder Telescope (SCT) cameras of the Cherenkov Telescope Array Observatory (CTAO), CTC and CT5TEA are deployed for both prototypes and shall be integrated into the final versions., Comment: 18 pages, 26 figures, 1 table

TOI-6255~b (GJ 4256) is an Earth-sized planet (1.079$\pm0.065$ $R_\oplus$) with an orbital period of only 5.7 hours. With the newly commissioned Keck Planet Finder (KPF) and CARMENES spectrographs, we determined the planet's mass to be 1.44$\pm$0.14 $M_{\oplus}$. The planet is just outside the Roche limit, with $P_{\rm orb}/P_{\rm Roche}$ = 1.13 $\pm0.10$. The strong tidal force likely deforms the planet into a triaxial ellipsoid with a long axis that is $\sim$10\% longer than the short axis. Assuming a reduced stellar tidal quality factor $Q_\star^\prime \approx10^7$, we predict that tidal orbital decay will cause TOI-6255 to reach the Roche limit in roughly 400 Myr. Such tidal disruptions may produce the possible signatures of planet engulfment that have been on stars with anomalously high refractory elemental abundances compared to its conatal binary companion. TOI-6255 b is also a favorable target for searching for star-planet magnetic interactions, which might cause interior melting and hasten orbital decay. TOI-6255 b is a top target (Emission Spectroscopy Metric of about 24) for phase curve observations with the James Webb Space Telescope., Comment: 18 pages, 7 figures, 5 tables, accepted to AAS Journals. The first RV mass measurement from the Keck Planet Finder

Planet formation is expected to be severely limited in disks of low metallicity, owing to both the small solid mass reservoir and the low opacity accelerating the disk gas dissipation. While previous studies have found a weak correlation between the occurrence rates of small planets ($\leq$4R$_\oplus$) and stellar metallicity, so far no studies have probed below the metallicity limit beyond which planet formation is predicted to be suppressed. Here, we constructed a large catalog of ~110,000 metal-poor stars observed by the TESS mission with spectroscopically-derived metallicities, and systematically probed planet formation within the metal-poor regime ([Fe/H] $\leq$ -0.5) for the first time. Extrapolating known higher-metallicity trends for small, short-period planets predicts the discovery of ~68 superEarths around these stars (~85,000 stars) after accounting for survey completeness; however, we detect none. As a result, we have placed the most stringent upper limit on super-Earth occurrence rates around metal-poor stars (-0.75 < [Fe/H] $\leq$ -0.5) to date, $\leq$ 1.67%, a statistically significant (p-value=0.000685) deviation from the prediction of metallicity trends derived with Kepler and K2. We find a clear host star metallicity cliff for super-Earths that could indicate the threshold below which planets are unable to grow beyond an Earth-mass at short orbital periods. This finding provides a crucial input to planet formation theories, and has implications for the small planet inventory of the Galaxy and the galactic epoch at which the formation of small planets started., Comment: Accepted to AJ

In recent years, the gauge group $U(1)_{L_\mu-L_\tau}$ has received a lot of attention since it can, in principle, account for the observed excess in the anomalous muon magnetic moment $(g-2)_\mu$, as well as the Hubble tension. Due to unavoidable, loop-induced kinetic mixing with the SM photon and $Z$, the $U(1)_{L_\mu-L_\tau}$ gauge boson $A'$ can contribute to stellar cooling via decays into neutrinos. In this work, we perform for the first time an \textit{ab initio} computation of the neutrino emissivities of white dwarf stars due to plasmon decay in a model of gauged $U(1)_{L_\mu-L_\tau}$. A key result is that current observations of the early-stage white dwarf neutrino luminosity at the 30\% level exclude previously allowed regions of the parameter space favoured by a simultaneous explanation of the $(g-2)_\mu$ and $H_0$ anomalies. In this work, we present the relevant white dwarf cooling limits over the entire $A'$ mass range. In particular, we have performed a rigorous computation of the luminosities in the resonant regime, where the $A'$ mass is comparable to the white dwarf plasma frequencies., Comment: 17 pages, 6 figures, 2 data files; v2: improved discussion of the cooling limit, matches journal version to appear in JHEP

The Radio Neutrino Observatory - Greenland (RNO-G) seeks discovery of ultra-high energy neutrinos from the cosmos through their interactions in ice. The science program extends beyond particle astrophysics to include radioglaciology and, as we show herein, solar observations, as well. Currently seven of 35 planned radio-receiver stations (24 antennas/station) are operational. These stations are sensitive to impulsive radio signals with frequencies between 80 and 700 MHz and feature a neutrino trigger threshold for recording data close to the thermal floor. RNO-G can also trigger on elevated signals from the Sun, resulting in nanosecond resolution time-domain flare data; such temporal resolution is significantly shorter than from most dedicated solar observatories. In addition to possible RNO-G solar flare polarization measurements, the Sun also represents an extremely useful above-surface calibration source. Using RNO-G data recorded during the summers of 2022 and 2023, we find signal excesses during solar flares reported by the solar-observing Callisto network and also in coincidence with $\sim$2/3 of the brightest excesses recorded by the SWAVES satellite. These observed flares are characterized by significant time-domain impulsivity. Using the known position of the Sun, the flare sample is used to calibrate the RNO-G absolute pointing on the radio signal arrival direction to sub-degree resolution. We thus establish the Sun as a regularly observed astronomical calibration source to provide the accurate absolute pointing required for neutrino astronomy.

The problem Level Planarity asks for a crossing-free drawing of a graph in the plane such that vertices are placed at prescribed y-coordinates (called levels) and such that every edge is realized as a y-monotone curve. In the variant Constrained Level Planarity (CLP), each level $y$ is equipped with a partial order $\prec_y$ on its vertices and in the desired drawing the left-to-right order of vertices on level $y$ has to be a linear extension of $\prec_y$. Ordered Level Planarity (OLP) corresponds to the special case of CLP where the given partial orders $\prec_y$ are total orders. Previous results by Br\"uckner and Rutter [SODA 2017] and Klemz and Rote [ACM Trans. Alg. 2019] state that both CLP and OLP are NP-hard even in severely restricted cases. In particular, they remain NP-hard even when restricted to instances whose width (the maximum number of vertices that may share a common level) is at most two. In this paper, we focus on the other dimension: we study the parameterized complexity of CLP and OLP with respect to the height (the number of levels). We show that OLP parameterized by the height is complete with respect to the complexity class XNLP, which was first studied by Elberfeld et al. [Algorithmica 2015] (under a different name) and recently made more prominent by Bodlaender et al. [FOCS 2021]. It contains all parameterized problems that can be solved nondeterministically in time $f(k) n^{O(1)}$ and space $f(k) \log n$ (where $f$ is a computable function, $n$ is the input size, and $k$ is the parameter). If a problem is XNLP-complete, it lies in XP, but is W[$t$]-hard for every $t$. In contrast to the fact that OLP parameterized by the height lies in XP, it turns out that CLP is NP-hard even when restricted to instances of height 4. We complement this result by showing that CLP can be solved in polynomial time for instances of height at most 3., Comment: A preliminary version of this paper appeared in the proceedings of the 40th International Symposium on Computational Geometry (SoCG 2024)

We collected near-infrared spectra of 65 cool stars with the NASA InfraRed Telescope Facility (IRTF) and analyze them to calculate accurate metallicities and stellar parameters. The sample of 55 M dwarfs and 10 K dwarfs includes 25 systems with confirmed planets and 27 systems with planet candidates identified by the K2 and TESS missions. Three of the 25 confirmed planetary systems host multiple confirmed planets and two of the 27 planet candidate systems host multiple planet candidates. Using the new stellar parameters, we re-fit the K2 and TESS light curves to calculate updated planet properties. In general, our updated stellar properties are more precise than those previously reported and our updated planet properties agree well with those in the literature. Lastly, we briefly examine the relationship between stellar mass, stellar metallicity, and planetary system properties for targets in our sample and for previously characterized planet-hosting low-mass stars. We provide our spectra, stellar parameters, and new planetary fits to the community, expanding the sample available with which to investigate correlations between stellar and planetary properties for low-mass stars., Comment: 4 tables, 6 figures