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The mechanism of X-ray outbursts in Be X-ray binaries remains a mystery, and understanding their circumstellar disks is crucial for a solution of the mass-transfer problem. In particular, it is important to identify the Be star activities (e.g., pulsations) that cause mass ejection and, hence, disk formation. Therefore, we investigated the relationship between optical flux oscillations and the infrared (IR) excess in a sample of five Be X-ray binaries. Applying the Lomb-Scargle technique to high-cadence optical light curves from the Transiting Exoplanet Survey Satellite (TESS), we detected several significant oscillation modes in the 3 to 24 hour period range for each source. We also measured the IR excess (a proxy for disk growth) of those five sources, using J-band light curves from Palomar Gattini-IR. In four of the five sources, we found anti-correlations between the IR excess and the amplitude of the main flux oscillation modes. This result is inconsistent with the conventional idea that non-radial pulsations drive mass ejections. We propose an alternative scenario where internal temperature variations in the Be star cause transitions between pulsation-active and mass-ejection-active states., Comment: 17 pages, 27 figures, 6 tables, accepted for publication in MNRAS

Nowhere in the solar system are impact morphologies observed in greater variety than on the icy Galilean satellites. This is likely a consequence of the structural and thermal state of the crust at the time of impact, and perhaps impact velocity. Palimpsest-type impact features show smooth enclosed central plains surrounded by undulating plains, within which are distributed concentric arcuate ridges, and no recognizable rim. Buto Facula on Ganymede is the best resolved of any palimpsest, having mostly been imaged at 190 m/pixel and optimum lighting, allowing insight into the circumstances that form this type of impact feature. Part of an impact crater on the eastern edge of Buto Facula has been buried by undulating plains material, suggesting that at the time of their emplacement the undulating plains behaved as a low-viscosity flow advancing across the landscape around the impact zone, encroaching on landforms that it encountered. We evaluated hypotheses for the formation of undulating plains using impact and ejecta modeling. We do not attribute the source of Buto's undulating plains to "dry" impact ejecta due to the existence of impact features larger than Buto that are not surrounded by undulating plains deposits. We performed iSALE impact simulations incorporating a subsurface liquid layer (or low strength layer) at various depths. An impact into a surface with a pre-existing, 5 km-deep, 5 km-thick fluid layer results in excavation of fluid material from that layer, producing a nearly flat final surface profile that is consistent with Buto's flat profile and the distribution of its undulating plains material. A liquid layer at a depth of 20-40 km results in impact feature profiles that resemble classic impact craters. We offer tests of this shallow subsurface liquid layer hypothesis for palimpsest formation that could potentially be performed by JUICE and Europa Clipper.

Generative art is a rules-driven approach to creating artistic outputs in various mediums. For example, a fluid simulation can govern the flow of colored pixels across a digital display or a rectangle placement algorithm can yield a Mondrian-style painting. Previously, we investigated how genetic improvement, a sub-field of genetic programming, can automatically create and optimize generative art drawing programs. One challenge of applying genetic improvement to generative art is defining fitness functions and their interaction in a many-objective evolutionary algorithm such as Lexicase selection. Here, we assess the impact of each fitness function in terms of the their individual effects on generated images, characteristics of generated programs, and impact of bloat on this specific domain. Furthermore, we have added an additional fitness function that uses a classifier for mimicking a human's assessment as to whether an output is considered as "art." This classifier is trained on a dataset of input images resembling the glitch art aesthetic that we aim to create. Our experimental results show that with few fitness functions, individual generative techniques sweep across populations. Moreover, we found that compositions tended to be driven by one technique with our current fitness functions. Lastly, we show that our classifier is best suited for filtering out noisy images, ideally leading towards more outputs relevant to user preference.

We present the design and implementation of a side entry laser system designed for an ultra-high vacuum scanning transmission electron microscope. This system uses a versatile probe design enclosed in a vacuum envelope such that parts can be easily aligned, modified, or exchanged without disturbing the vacuum. The system uses a mirror mounted on the sample holder such that the sample can be illuminated without being tilted. Notably the mirror can be removed and replaced with an ablation target and a higher power laser used to ablate material directly onto the sample. We argue that new capabilities hold the potential to transform the electron microscope from an analysis tool towards a more flexible synthesis system, where atomic scale fabrication and atom-by-atom experiments can be performed.

Palomar Gattini-IR is a wide-field, synoptic infrared time domain survey covering $\approx 15000$ sq. deg. of the sky at $\approx 1-3$ night cadence to a depth of $J\approx 13.0$ and $\approx 14.9$ Vega mag in and outside the Galactic plane, respectively. Here, we present the first data release of $J$-band light curves of 2MASS sources within the survey footprint covering approximately the first four years of operations. We describe the construction of the source catalog based on the 2MASS point sources, followed by exposure filtering criteria and forced PSF photometry. The catalog contains light curves of $\approx 286$ million unique sources with 2MASS magnitudes of $J < 15.5$ mag, with a total of $\approx 50$ billion photometric measurements and $\approx 20$ billion individual source detections at signal-to-noise-ratio $> 3$. We demonstrate the photometric fidelity of the catalog by i) quantifying the magnitude-dependent accuracy and uncertainty of the photometry with respect to 2MASS and ii) comparing against forced PGIR aperture photometry for known variable sources. We present simple filtering criteria for selecting reliable photometric measurements as well as example Python notebooks for users. This catalog is the largest compilation of nightly cadence, synoptic infrared light curves to date, comparable to those in the largest optical surveys, providing a stepping stone to upcoming infrared surveys in the coming decade., Comment: 10 Pages, 5 figures, submitted to PASP. Full catalog will be available upon publication, individual requests welcome!

We present a detailed mathematical study of the Monte Carlo replica method as applied in the global fitting literature from the high-energy physics theory community. For the first time, we provide a rigorous derivation of the parameter distributions implied by the method, and show that, whilst they agree with Bayesian posteriors for linear models, they disagree otherwise. We proceed to numerically quantify the disagreement between the Monte Carlo replica method and the Bayesian method in the context of two phenomenologically relevant scenarios: fits of the SMEFT Wilson coefficients, and fits of PDFs (albeit in a toy scenario). In both scenarios, we find that uncertainty estimates of the quantities of interest are discrepant between the two approaches when non-linearity is relevant. Our findings motivate future investigation of Bayesian methodologies for global PDF fits, especially in the context of simultaneous determination of PDFs and SMEFT Wilson coefficients., Comment: 38 pages. 13 figures

The icy Galilean satellites display impact crater morphologies that are rare in the Solar System. They deviate from the archetypal sequence of crater morphologies as a function of size found on rocky bodies and other icy satellites: they exhibit central pits in place of peaks, followed by central dome craters, anomalous dome craters, penepalimpsests, palimpsests, and multi-ring structures. Understanding the origin of these features will provide insight into the geophysical factors that operate within the icy Galilean satellites. Pit craters above a size threshold feature domes. This trend, and the similarity in morphology between the two classes, suggest a genetic link between pit and dome craters. We propose that dome craters evolve from pit craters through topographic relaxation, facilitated by remnant heat from the impact. Our finite element simulations show that, for the specific crater sizes where we see domes on Ganymede and Callisto, domes form from pit craters within 10 Myr. Topographic relaxation eliminates the stresses induced by crater topography and restores a flat surface: ice flows downwards from the rim and upwards from the crater depression driven by gravity. When the starting topography is a pit crater, the heat left over from the impact is concentrated below the pit. Since warm ice flows more rapidly, the upward flow is enhanced beneath the pit, leading to the emergence of a dome. Given the timescales and the dependence on heat flux, this model could be used to constrain the thermal history and evolution of these moons.

We have performed topographic and geological mapping of 19 large impact features on Ganymede and Callisto in order to gather morphometric and crater age data that allow us to quantify how the diverse morphologies of these features transition with size and age. The impact features are divided into two main morphological groups, craters and penepalimpsests/palimpsests. The morphologies of pit and dome craters are independent of age or geologic context, indicating that the impacts that formed them were small enough to only ever penetrate into a cold, rigid ice layer, with evolution of a pocket of impact melt contributing to the development of their central pits and surrounding raised annuli, while the domes formed mainly via viscous relaxation of the pit topography. The subdued rims of anomalous dome craters indicate the increasing effect of a warm subsurface ice layer on impact feature morphology with increasing size. The low topographic relief of penepalimpsests and palimpsests indicates that these impacts penetrated the ice shell to liberate large volumes of underlying, pre-existing liquid. Penepalimpsests show a higher frequency of concentric ridges within their interiors, indicating a more robust subsurface state that could support the rotation and uplift of solid material during impact. The size and age overlap of anomalous dome craters, penepalimpsests, and palimpsests, with a few impact features appearing to be transitional between anomalous dome craters and penepalimpsests, indicates that impactor size, time of impact, and variation in temperature gradient across the satellite are all factors in determining which of these morphologies emerges.

Stars in the Asymptotic Giant Branch (AGB) phase, dominated by low to intermediate-mass stars in the late stage of evolution, undergo periodic pulsations, with periods of several hundred days, earning them the name Long Period Variables (LPVs). These stars gradually shed their mass through stellar winds and mass ejections, enveloping themselves in dust. Infrared (IR) surveys can probe these dust-enshrouded phases and uncover populations of LPV stars in the Milky Way. In this paper, we present a catalog of 159,696 Long Period Variables using near-IR lightcurves from the Palomar Gattini - IR (PGIR) survey. PGIR has been surveying the entire accessible northern sky ($\delta > -28^{\circ}$) in the J-band at a cadence of 2-3 days since September 2018, and has produced J-band lightcurves for more than 60 million sources. We used a gradient-boosted decision tree classifier trained on a comprehensive feature set extracted from PGIR lightcurves to search for LPVs in this dataset. We developed a parallelized and optimized code to extract features at a rate of ~0.1 seconds per lightcurve. Our model can successfully distinguish LPVs from other stars with a true positive rate and weighted g-mean of 0.95. 73,346 (~46%) of the sources in our catalog are new, previously unknown LPVs., Comment: 15 pages, 15 figures

We present the open-source SIMUnet code, designed to fit Standard Model Effective Field Theory (SMEFT) Wilson coefficient alongside Parton Distribution Functions (PDFs) of the proton. SIMUnet can perform SMEFT global fits, as well as simultaneous fits of the PDFs and of an arbitrarily large number of SMEFT degrees of freedom, by including both PDF-dependent and PDF-independent observables. SIMUnet can also be used to determine whether the effects of any New Physics models can be fitted away in a global fit of PDFs. SIMUnet is built upon the open-source NNPDF code and is released together with documentation, and tutorials. To illustrate the functionalities of the new tool, we present a new global analysis of the SMEFT Wilson coefficients accounting for their interplay with the PDFs. We increment our previous analysis of the LHC Run II top quark data with both (i) the Higgs production and decay rates data from the LHC, and (ii) the precision electroweak and diboson measurements from LEP and the LHC., Comment: 28 pages, 11 figures, full code documentation at https://hep-pbsp.github.io/SIMUnet/ and public code at https://github.com/HEP-PBSP/SIMUnet

Multivariate time series data are ubiquitous in the application of machine learning to problems in the physical sciences. Chemiresistive sensor arrays are highly promising in chemical detection tasks relevant to industrial, safety, and military applications. Sensor arrays are an inherently multivariate time series data collection tool which demand rapid and accurate classification of arbitrary chemical analytes. Previous research has benchmarked data-agnostic multivariate time series classifiers across diverse multivariate time series supervised tasks in order to find general-purpose classification algorithms. To our knowledge, there has yet to be an effort to survey machine learning and time series classification approaches to chemiresistive hardware sensor arrays for the detection of chemical analytes. In addition to benchmarking existing approaches to multivariate time series classifiers, we incorporate findings from a model survey to propose the novel \textit{ChemTime} approach to sensor array classification for chemical sensing. We design experiments addressing the unique challenges of hardware sensor arrays classification including the rapid classification ability of classifiers and minimization of inference time while maintaining performance for deployed lightweight hardware sensing devices. We find that \textit{ChemTime} is uniquely positioned for the chemical sensing task by combining rapid and early classification of time series with beneficial inference and high accuracy., Comment: 14 pages, 12 figures

In data from the New Horizons encounter with Pluto in 2015, attention was called to a crater named Kiladze and its surroundings because of the water ice spectral properties, which contrast with the primarily methane ice regional surface composition. The water ice carries the spectral signature of an ammoniated compound, similar to that seen at two other sites on Pluto where cryovolcanism has been identified. The faulted structure of Kiladze, including shaping by numerous collapse pits and the distorted shape of the crater, are compatible with the surroundings in Hayabusa Terra, east of Spunik Planitia. They are further compatible with an interpretation as a resurgent caldera formed during a past era of active cryovolcanic period that appears to be significantly more recent than the overall age of the planet's surface, possibly in the last several million years. In view of the size of the caldera and the large scale of the surrounding distribution of water ice, we propose that Kiladze is a "supervolcano" in which one or more explosive events has scattered more than ~1000 km$^{3}$ of icy cryomagma erupted from the interior onto the surface., Comment: 22 pages, 6 figures, submitted to Icarus

Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected $350{,}757$ coin flips to test the counterintuitive prediction from a physics model of human coin tossing developed by Diaconis, Holmes, and Montgomery (DHM; 2007). The model asserts that when people flip an ordinary coin, it tends to land on the same side it started -- DHM estimated the probability of a same-side outcome to be about 51%. Our data lend strong support to this precise prediction: the coins landed on the same side more often than not, $\text{Pr}(\text{same side}) = 0.508$, 95% credible interval (CI) [$0.506$, $0.509$], $\text{BF}_{\text{same-side bias}} = 2359$. Furthermore, the data revealed considerable between-people variation in the degree of this same-side bias. Our data also confirmed the generic prediction that when people flip an ordinary coin -- with the initial side-up randomly determined -- it is equally likely to land heads or tails: $\text{Pr}(\text{heads}) = 0.500$, 95% CI [$0.498$, $0.502$], $\text{BF}_{\text{heads-tails bias}} = 0.182$. Furthermore, this lack of heads-tails bias does not appear to vary across coins. Additional exploratory analyses revealed that the within-people same-side bias decreased as more coins were flipped, an effect that is consistent with the possibility that practice makes people flip coins in a less wobbly fashion. Our data therefore provide strong evidence that when some (but not all) people flip a fair coin, it tends to land on the same side it started. Our data provide compelling statistical support for the DHM physics model of coin tossing.

Purpose: Demonstrating and assessing self-supervised machine learning fitting of the VERDICT (Vascular, Extracellular and Restricted DIffusion for Cytometry in Tumours) model for prostate. Methods: We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares (NLLS) and supervised deep learning. We do this quantitatively on simulated data, by comparing the Pearson's correlation coefficient, mean-squared error (MSE), bias, and variance with respect to the simulated ground truth. We also calculate in vivo parameter maps on a cohort of 20 prostate cancer patients and compare the methods' performance in discriminating benign from cancerous tissue via Wilcoxon's signed-rank test. Results: In simulations, ssVERDICT outperforms the baseline methods (NLLS and supervised DL) in estimating all the parameters from the VERDICT prostate model in terms of Pearson's correlation coefficient, bias, and MSE. In vivo, ssVERDICT shows stronger lesion conspicuity across all parameter maps, and improves discrimination between benign and cancerous tissue over the baseline methods. Conclusion: ssVERDICT significantly outperforms state-of-the-art methods for VERDICT model fitting, and shows for the first time, fitting of a complex three-compartment biophysical model with machine learning without the requirement of explicit training labels., Comment: 12 pages, 5 figures. Submitted to Magnetic Resonance in Medicine

We report on a study of the mounds that dominate the appearance of Kuiper Belt Object (KBO) (486958) Arrokoth's larger lobe, named Wenu. We compare the geological context of these mounds, measure and intercompare their shapes, sizes/orientations, reflectance, and colors. We find the mounds are broadly self-similar in many respects and interpret them as the original building blocks of Arrokoth. It remains unclear why these building blocks are so similar in size, and this represents a new constrain and challenge for solar system formation models. We then discuss the interpretation of this interpretation., Comment: 24 pages, 8 figures