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Disturbances to the climate system, both natural and anthropogenic, have far reaching impacts that are not always easy to identify or quantify using traditional climate science analyses or causal modeling techniques. In this paper, we develop a novel technique for discovering and ranking the chain of spatio-temporal downstream impacts of a climate source, referred to herein as a source-impact pathway, using Random Forest Regression (RFR) and SHapley Additive exPlanation (SHAP) feature importances. Rather than utilizing RFR for classification or regression tasks (the most common use case for RFR), we propose a fundamentally new RFR-based workflow in which we: (i) train random forest (RF) regressors on a set of spatio-temporal features of interest, (ii) calculate their pair-wise feature importances using the SHAP weights associated with those features, and (iii) translate these feature importances into a weighted pathway network (i.e., a weighted directed graph), which can be used to trace out and rank interdependencies between climate features and/or modalities. We adopt a tiered verification approach to verify our new pathway identification methodology. In this approach, we apply our method to ensembles of data generated by running two increasingly complex benchmarks: (i) a set of synthetic coupled equations, and (ii) a fully coupled simulation of the 1991 eruption of Mount Pinatubo in the Philippines performed using a modified version 2 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SMv2). We find that our RFR feature importance-based approach can accurately detect known pathways of impact for both test cases.

Periorbital segmentation and distance prediction using deep learning allows for the objective quantification of disease state, treatment monitoring, and remote medicine. However, there are currently no reports of segmentation datasets for the purposes of training deep learning models with sub mm accuracy on the regions around the eyes. All images (n=2842) had the iris, sclera, lid, caruncle, and brow segmented by five trained annotators. Here, we validate this dataset through intra and intergrader reliability tests and show the utility of the data in training periorbital segmentation networks. All the annotations are publicly available for free download. Having access to segmentation datasets designed specifically for oculoplastic surgery will permit more rapid development of clinically useful segmentation networks which can be leveraged for periorbital distance prediction and disease classification. In addition to the annotations, we also provide an open-source toolkit for periorbital distance prediction from segmentation masks. The weights of all models have also been open-sourced and are publicly available for use by the community., Comment: 12 pages, 4 figures

Periorbital distances and features around the eyes and lids hold valuable information for disease quantification and monitoring of surgical and medical intervention. These distances are commonly measured manually, a process that is both subjective and highly time-consuming. Here, we set out to developed three deep-learning methods for segmentation and periorbital distance prediction, and also evaluate the utility of periorbital distances for disease classification. The MAE of our deep learning predicted distances was less than or very close to the error observed between trained human annotators. We compared our models to the current state-of-the-art (SOTA) method for periorbital distance prediction and found that our methods outperformed SOTA on all of our datasets on all but one periorbital measurement. We also show that robust segmentation can be achieved on diseased eyes using models trained on open-source, healthy eyes, and that periorbital distances have can be used as high-quality features in downstream classification models. Leveraging segmentation networks as intermediary steps in classification has broad implications for increasing the generalizability of classification models in ophthalmic plastic and craniofacial surgery by avoiding the out-of-distribution problem observed in traditional convolutional neural networks., Comment: 16 pages, 4 figures, 4 tables

This work reports the fabrication and characterization of a NiOx/\b{eta}-Ga2O3 heterojunction diode (HJD) that uses a metallic nickel (Ni) target to deposit NiOx layers via reactive RF magnetron sputtering and lift-off processing with >3 kV breakdown voltage, record-low reverse current leakage under high reverse bias, and high junction electric fields (>3.34 MV/cm). The heterojunction diodes are fabricated via bilayer NiOx sputtering followed by self-aligned mesa-etching for field-termination on both large (1-mm2) and small area (100-{\mu}m diameter) devices. The HJD exhibits a ~135 A/cm2 forward current density at 5 V with a rectifying ratio of ~1010. The minimum differential specific on-resistance is measured to be 17.26 m{\Omega} cm2. The breakdown voltage on 100-{\mu}m diameter pads was measured to be greater than 3 kV with a noise floor-level reverse leakage current density (10-8~10-6 A/cm2) until 3 kV, accomplishing a parallel-plane junction electric field to be at least 3.34 MV/cm at 3 kV with a power figure of merit (PFOM) >0.52 GW/cm2. Temperature-dependent forward current density-voltage (J-V) measurements are performed from room temperature (25 C) to 200 C which showed a temperature coefficient of resistance ({\alpha}) equaling 1.56, higher than that of \b{eta}-Ga2O3 Schottky barrier diodes (SBDs), indicating potential conductivity degradation within NiOx at elevated temperatures., Comment: 6 pages, 5 figures, APL Journal

The Dark Energy Spectroscopic Instrument (DESI) collaboration measured a tight relation between the Hubble constant ($H_0$) and the distance to the Coma cluster using the fundamental plane (FP) relation of the deepest, most homogeneous sample of early-type galaxies. To determine $H_0$, we measure the distance to Coma by several independent routes each with its own geometric reference. We measure the most precise distance to Coma from 12 Type Ia Supernovae (SNe Ia) in the cluster with mean standardized brightness of $m_B^0=15.712\pm0.041$ mag. Calibrating the absolute magnitude of SNe Ia with the HST distance ladder yields $D_{\textrm Coma}=98.5\pm2.2$ Mpc, consistent with its canonical value of 95--100 Mpc. This distance results in $H_0=76.5 \pm 2.2$ km/s/Mpc from the DESI FP relation. Inverting the DESI relation by calibrating it instead to the Planck+$\Lambda$CDM value of $H_0=67.4$ km/s/Mpc implies a much greater distance to Coma, $D_{\textrm Coma}=111.8\pm1.8$ Mpc, $4.6\sigma$ beyond a joint, direct measure. Independent of SNe Ia, the HST Key Project FP relation as calibrated by Cepheids, Tip of the Red Giant Branch from JWST, or HST NIR surface brightness fluctuations all yield $D_{\textrm Coma}<$ 100 Mpc, in joint tension themselves with the Planck-calibrated route at $>3\sigma$. From a broad array of distance estimates compiled back to 1990, it is hard to see how Coma could be located as far as the Planck+$\Lambda$CDM expectation of $>$110 Mpc. By extending the Hubble diagram to Coma, a well-studied location in our own backyard whose distance was in good accord well before the Hubble Tension, DESI indicates a more pervasive conflict between our knowledge of local distances and cosmological expectations. We expect future programs to refine the distance to Coma and nearer clusters to help illuminate this new, local window on the Hubble Tension., Comment: v2 - team name fixed

In order to solve problems of practical importance, quantum computers will likely need to incorporate quantum error correction, where a logical qubit is redundantly encoded in many noisy physical qubits. The large physical-qubit overhead typically associated with error correction motivates the search for more hardware-efficient approaches. Here, using a microfabricated superconducting quantum circuit, we realize a logical qubit memory formed from the concatenation of encoded bosonic cat qubits with an outer repetition code of distance $d=5$. The bosonic cat qubits are passively protected against bit flips using a stabilizing circuit. Cat-qubit phase-flip errors are corrected by the repetition code which uses ancilla transmons for syndrome measurement. We realize a noise-biased CX gate which ensures bit-flip error suppression is maintained during error correction. We study the performance and scaling of the logical qubit memory, finding that the phase-flip correcting repetition code operates below threshold, with logical phase-flip error decreasing with code distance from $d=3$ to $d=5$. Concurrently, the logical bit-flip error is suppressed with increasing cat-qubit mean photon number. The minimum measured logical error per cycle is on average $1.75(2)\%$ for the distance-3 code sections, and $1.65(3)\%$ for the longer distance-5 code, demonstrating the effectiveness of bit-flip error suppression throughout the error correction cycle. These results, where the intrinsic error suppression of the bosonic encodings allows us to use a hardware-efficient outer error correcting code, indicate that concatenated bosonic codes are a compelling paradigm for reaching fault-tolerant quantum computation., Comment: Comments on the manuscript welcome!

We present a weak lensing analysis of the galaxy cluster Abell 2390 at z = 0.23 using second moment shape measurements made in 411 short 60s exposures. The exposures are obtained in three broadband photometric filters (g, r, i) using WIYN-ODI. Shape measurement in individual exposures is done using a moment matching algorithm. Forced measurement is used when the moment matching algorithm fails to converge at low signal to noise ratio (SNR). The measurements made in individual images are combined using inverse error weight to obtain accurate shape of sources and hence recover shear. We use PhoSim simulations to validate shear measurements recovered by our pipeline. We find the mass of Abell 2390 is in agreement with previously published results. We also find the E-Mode maps show filamentary structures consistent with baryonic structures and recovers most clusters/groups of galaxies found using Optical and X-Ray data. Thus we demonstrate the feasibility of using Weak Lensing to map large scale structure of the universe. We also find the central portion of the cluster has a bimodal mass distribution and the relative orientation of the peaks are similar to X-Ray. We discuss earlier research on this galaxy cluster and show that a late stage merger accounts for all the observed data., Comment: Accepted in ApJ

Let $\mathfrak{p} \subset V$ be a polytope and $\xi \in V_{\mathbb{C}}^*$. We obtain an expression for $I(\mathfrak{p}; \alpha) := \int_{\mathfrak{p}} e^{\langle \alpha, x \rangle} dx$ as a sum of meromorphic functions in $\alpha \in V^*_{\mathbb{C}}$ parametrized by the faces $\mathfrak{f}$ of $\mathfrak{p}$ on which $\langle \xi, x \rangle$ is constant. Each term only depends on the local geometry of $\mathfrak{p}$ near $\mathfrak{f}$ (and on $\xi$) and is holomorphic at $\alpha = \xi$. When $\langle \xi, \cdot \rangle$ is only constant on the vertices of $\mathfrak{p}$ our formula reduces to Brion's formula. Suppose $\mathfrak{p}$ is a rational polytope with respect to a lattice $\Lambda$. We obtain an expression for $S(\mathfrak{p}; \alpha) := \sum_{\lambda \in \mathfrak{p} \cap \Lambda} e^{\langle \alpha, \lambda \rangle}$ as a sum of meromorphic functions parametrized by the faces $\mathfrak{f}$ on which $e^{\langle \xi, x \rangle} = 1$ on a finite index sublattice of $\text{lin}(\mathfrak{f}) \cap \Lambda$. Each term only depends on the local geometry of $\mathfrak{p}$ near $\mathfrak{f}$ (and on $\xi$ and $\Lambda$) and is holomorphic at $\alpha = \xi$. When $e^{\langle \xi, \cdot \rangle} \neq 1$ at any non-zero lattice point on a line through the origin parallel to an edge of $\mathfrak{p}$, our formula reduces to Brion's formula, and when $\xi = 0$, it reduces to the Ehrhart quasi-polynomial. Our formulas are particularly useful for understanding how $I(\mathfrak{p}(h); \xi)$ and $S(\mathfrak{p}(h); \xi)$ vary in a family of polytopes $\mathfrak{p}(h)$ with the same normal fan. When considering dilates of a fixed polytope, our formulas may be viewed as polytopal analogues of Laplace's method and the method of stationary phase. Such expressions naturally show up in analysis on symmetric spaces and affine buildings., Comment: 41 pages

The use of in-situ digital sensors for water quality monitoring is becoming increasingly common worldwide. While these sensors provide near real-time data for science, the data are prone to technical anomalies that can undermine the trustworthiness of the data and the accuracy of statistical inferences, particularly in spatial and temporal analyses. Here we propose a framework for detecting anomalies in sensor data recorded in stream networks, which takes advantage of spatial and temporal autocorrelation to improve detection rates. The proposed framework involves the implementation of effective data imputation to handle missing data, alignment of time-series to address temporal disparities, and the identification of water quality events. We explore the effectiveness of a suite of state-of-the-art statistical methods including posterior predictive distributions, finite mixtures, and Hidden Markov Models (HMM). We showcase the practical implementation of automated anomaly detection in near-real time by employing a Bayesian recursive approach. This demonstration is conducted through a comprehensive simulation study and a practical application to a substantive case study situated in the Herbert River, located in Queensland, Australia, which flows into the Great Barrier Reef. We found that methods such as posterior predictive distributions and HMM produce the best performance in detecting multiple types of anomalies. Utilizing data from multiple sensors deployed relatively near one another enhances the ability to distinguish between water quality events and technical anomalies, thereby significantly improving the accuracy of anomaly detection. Thus, uncertainty and biases in water quality reporting, interpretation, and modelling are reduced, and the effectiveness of subsequent management actions improved.

In this paper we explore independently for the first time three chemical potentials (baryon $\mu_B$, charged $\mu_Q$, and strange $\mu_S$) in the Chiral mean-field (CMF) model. We designed and implemented \texttt{CMF++}, a new version of the CMF model rewritten in \texttt{C++} that is optimized, modular, and well-documented. \texttt{CMF++} has been integrated into the MUSES Calculation Engine as a free and open source software module. The runtime improved in more than 4 orders of magnitude across all 3 chemical potentials, when compared to the legacy code. Here we focus on the zero temperature case and study stable, as well as metastable and unstable, vacuum, hadronic, and quark phases, showing how phase boundaries vary with the different chemical potentials. Due to the significant numerical improvements in \texttt{CMF++}, we can calculate for the first time high-order susceptibilities within the CMF framework to study the properties of the quark deconfinement phase transition. We found phases of matter that include a light hadronic phase, strangeness-dominated hadronic phase, and quark deconfinement within our $\mu_B$, $\mu_S$, $\mu_Q$ phase space. The phase transitions are of first, second (quantum critical point), and third order between these phases and we even identified a tricritical point., Comment: 63 pages, 22 figures

We report on the successful numerical evolution of the compactified hyperboloidal initial value problem in general relativity using generalized harmonic gauge. We work in spherical symmetry, using a massless scalar field to drive dynamics. Our treatment is based on the dual-foliation approach, proceeding either by using a height function or by solving the eikonal equation to map between frames. Both are tested here with a naive implementation and with hyperboloidal layers. We present a broad suite of numerical evolutions, including pure gauge perturbations, constraint violating and satisfying data with and without scalar field matter. We present calculations of spacetimes with a regular center. For black hole spacetimes we use excision to remove part of the black hole interior. We demonstrate both pointwise and norm convergence at the expected rate of our discretization. We present evolutions in which the scalar field collapses to form a black hole. Evolving nonlinear scalar field perturbations of the Schwarzschild spacetime, we recover the expected quasinormal frequencies and tail decay rates from linear theory., Comment: 21 pages, 10 figures

Plasma detachment involves interactions of the plasma with impurities and neutral particles, leading to significant losses of plasma power, momentum, and particles. Accurate mapping of plasma emissivity in the divertor and X-point region is essential for assessing the relationship between particle flux and radiative detachment. The recently validated InfraRed Video Bolometer (IRVB) diagnostic, in MAST-U enables this mapping with higher spatial resolution than more established methods like resistive bolometers. In previous preliminary work, the evolution of radiative detachment was characterised in L-mode (power entering the scrape-off layer, PSOL ~0.4MW). With a conventional divertor the inner leg consistently detached ahead of the outer leg, and radiative detachment preceded particle flux detachment. This work presents results also from the third MAST-U experimental campaign, fuelled from the low field side instead of the high field side, including Ohmic and beam heated L-mode shots (with a power exiting the core up to PSOL ~1-1.5MW). The radiation peak moves upstream from the target at lower upstream densities than the ion target flux roll-over (typically considered the detachment onset), while the inner leg detaches before the outer one. The movement of the radiation is in partial agreement with the expectations from the DLS model, predicting a sudden shift from the target to the X-point. The energy confinement is found to be related to detachment, but there seems to be some margin between the radiation on the inner leg reaching the X-point and confinement being affected, a beneficial characteristic if it could be extrapolated to future reactors. For increasing PSOL the particle flux roll over is almost unaffected, while radiative detachment occurs at higher density in both legs, but much higher on the outer, suggesting an uneven distribution of the power exiting the core., Comment: Submitted to Nuclear Materials and Energy

After shipment to the Daresbury Lab and return to Fermilab, the prototype HB650 cryomodule underwent another phase of 2K RF testing to ascertain any performance issues that may have arisen from the transport of the cryomodule. While measurements taken at room temperature after the conclusion of shipment indicated that there were no negative impacts on cavity alignment, beamline vacuum, or cavity frequency, testing at 2K was required to validate other aspects such as tuner operation, cavity coupling, cryogenic system integrity, and cavity performance. Results of this latest round of limited 2K testing will be presented., Comment: 32nd Linear Accelerator Conference (LINAC 2024)

Hybrid organic-inorganic semiconductors with strong electron-phonon interactions provide a programmable platform for developing a variety of electronic, optoelectronic, and quantum materials by controlling these interactions. However, in current hybrid semiconductors, such as halide perovskites, anharmonic vibrations with rapid dephasing hinder the ability to coherently manipulate phonons. Here, we report the observation of long-lived coherent phonons in lead organic chalcogenides (LOCs), a new family of hybrid two-dimensional semiconductors. These materials feature harmonic phonon dynamics despite distorted lattices, combining long phonon dephasing times with tunable semiconducting properties. Dephasing time as long as 75 ps at 10 K, with up to 500 cycles of phonon oscillation between scattering events, was observed, corresponding to a dimensionless harmonicity parameter more than an order of magnitude larger than that of halide perovskites. The phonon dephasing time is significantly influenced by anharmonicity and centrosymmetry, both of which can be tuned through the design of the organic ligands thanks to the direct bonding between the organic and inorganic motifs. This research opens new opportunities for the manipulation of electronic properties with coherent phonons in hybrid semiconductors.

Fusion is a potentially transformational energy technology, which promises limitless clean energy. Yet, it requires continued scientific and technological development to realize its potential. The conditions necessary for fusion energy gain in terms of the product of plasma pressure $P$ and confinement time $\tau$ have been known for many decades. An underappreciated fact is that pulsed magnetic fusion has demonstrated $P \tau$ performance on par with laser-driven ICF and tokamaks despite receiving only a small fraction of investment relative to those concepts. In light of this demonstrated performance, well-established scaling relations, and opportunities for further innovations, here we advocate for pulsed magnetic fusion as the most attractive path towards commercialization of fusion energy.

At the low-redshift end ($z<0.05$) of the Hubble diagram with Type Ia Supernovae (SNe Ia), the contribution to Hubble residual scatter from peculiar velocities is of similar size to that due to the standardization of the SN Ia light curve. A way to improve the redshift measurement of the SN host galaxy is to utilize the average redshift of the galaxy group, effectively averaging over small-scale/intracluster peculiar velocities. One limiting factor is the fraction of SN host galaxies in galaxy groups, previously found to be 30% using (relatively incomplete) magnitude-limited galaxy catalogs. Here, we do the first analysis of N-body simulations to predict this fraction, finding $\sim$66% should have associated groups and group averaging should improve redshift precision by $\sim$120 km s$^{-1}$. Furthermore, using spectroscopic data from the Anglo-Australian Telescope, we present results from the first pilot program to evaluate whether or not 23 previously unassociated SN Ia hosts belong in groups. We find that 91% of these candidates can be associated with groups, consistent with predictions from simulations given the sample size. Combining with previously assigned SN host galaxies in Pantheon+, we demonstrate improvement in Hubble residual scatter equivalent to 145 km s$^{-1}$, also consistent with simulations. For new and upcoming low-$z$ samples from, for example, the Zwicky Transient Facility and the Rubin Observatory's Legacy Survey of Space and Time, a separate follow-up program identifying galaxy groups of SN hosts is a highly cost-effective way to enhance their constraining power., Comment: 17 pages, 12 figures. Submitted to ApJ

In this article, we investigate the in-situ growth of Al$_2$O$_3$ on $\beta$-Ga$_2$O$_3$ using metal-organic chemical vapor deposition (MOCVD) at a high temperature of 800{\deg}C. The Al$_2$O$_3$ is grown within the same reactor as the $\beta$-Ga$_2$O$_3$, employing trimethylaluminum (TMAl) and O$_2$ as precursors without breaking the vacuum. We characterize the shallow and deep-level traps through stressed capacitance-voltage (C-V) and photo-assisted C-V methods. The high-temperature deposited dielectric demonstrates an impressive breakdown field of approximately 10 MV/cm. Furthermore, we evaluate the reliability and lifetime of the dielectrics using time-dependent dielectric breakdown (TDDB) measurements. By modifying the dielectric deposition process to include a high-temperature (800{\deg}C) thin interfacial layer and a low-temperature (600{\deg}C) bulk layer, we report a 10-year lifetime under a stress field of 3.5 MV/cm along a breakdown field of 7.8 MV/cm.

Understanding how people behave in strategic settings--where they make decisions based on their expectations about the behavior of others--is a long-standing problem in the behavioral sciences. We conduct the largest study to date of strategic decision-making in the context of initial play in two-player matrix games, analyzing over 90,000 human decisions across more than 2,400 procedurally generated games that span a much wider space than previous datasets. We show that a deep neural network trained on these data predicts people's choices better than leading theories of strategic behavior, indicating that there is systematic variation that is not explained by those theories. We then modify the network to produce a new, interpretable behavioral model, revealing what the original network learned about people: their ability to optimally respond and their capacity to reason about others are dependent on the complexity of individual games. This context-dependence is critical in explaining deviations from the rational Nash equilibrium, response times, and uncertainty in strategic decisions. More broadly, our results demonstrate how machine learning can be applied beyond prediction to further help generate novel explanations of complex human behavior.

Pd$_3$Bi$_2$Se$_2$ is a rare realization of a superconducting metal with a non-zero $Z_2$ topological invariant. We report the growth of high-quality single crystals of layered Pd$_3$Bi$_2$Se$_2$ with a superconducting transition at $T_c$ ~ 0.80 K and upper critical fields of ~10 mT and ~5 mT for the in-plane and out-of-plane directions, respectively. Our density functional theory (DFT) calculations reveal three pairs of doubly degenerate bands crossing the Fermi level, all displaying clear three-dimensional dispersion consistent with the overall low electronic anisotropy (<2). The multiband electronic nature of Pd$_3$Bi$_2$Se$_2$ is evident in magneto-transport measurements, yielding a sign-changing Hall resistivity at low temperatures. The magnetoresistance is non-saturating and follows Kohler's scaling rule. We interpret the magneto-transport data in terms of open orbits that are revealed in the DFT-calculated Fermi surface. de Haas-van Alphen (dHvA) oscillation measurements using torque magnetometry on single crystals yield four frequencies for out-of-plane fields: $F_\alpha = (150 \pm 26)$T, $F_\beta = (293 \pm 10)$T, $F_\gamma = (375 \pm 20)$T, and $F_\eta = (1017 \pm 12)$T, with the low frequency dominating the spectrum. Through the measurement of angular dependent dHvA oscillations and DFT calculations, we identify the $F_\alpha$ frequency with an approximately ellipsoidal electron pocket centered on the $L_2$ point of the Brillouin zone. Lifshitz-Kosevich analysis of the dHvA oscillations reveals a small cyclotron effective mass: $m^* = (0.11 \pm 0.02) m_0$ and a nontrivial Berry phase for the dominant orbit. The presence of nontrivial topology in a bulk superconductor positions Pd$_3$Bi$_2$Se$_2$ as a potential candidate for exploring topological superconductivity., Comment: 30 pages, 5 figures

It is often said that well-entangled and fast-breaking living polymers (such as wormlike micelles) exhibit a single relaxation time in their reptation dynamics, but the full story is somewhat more complicated. Understanding departures from single-Maxwell behavior is crucial for fitting and interpreting experimental data, but in some limiting cases numerical methods of solving living polymer models can struggle to produce reliable predictions/interpretations. In this work, we develop an analytic solution for the shuffling model of living polymers. The analytic solution is a converging infinite series, and it converges fastest in the fast-breaking limit where other methods can struggle., Comment: 11 pages, 2 figures

The DArk Matter In CCDs at Modane (DAMIC-M) experiment is designed to search for light dark matter (m$_{\chi}$<10\,GeV/c$^2$) at the Laboratoire Souterrain de Modane (LSM) in France. DAMIC-M will use skipper charge-coupled devices (CCDs) as a kg-scale active detector target. Its single-electron resolution will enable eV-scale energy thresholds and thus world-leading sensitivity to a range of hidden sector dark matter candidates. A DAMIC-M prototype, the Low Background Chamber (LBC), has been taking data at LSM since 2022. The LBC provides a low-background environment, which has been used to characterize skipper CCDs, study dark current, and measure radiopurity of materials planned for DAMIC-M. It also allows testing of various subsystems like readout electronics, data acquisition software, and slow control. This paper describes the technical design and performance of the LBC.

We report on metalorganic chemical vapor deposition (MOCVD) growth of controllably Si-doped 4.5 $\mu$m thick $\beta$-Ga$_2$O$_3$ films with electron concentrations in the 10$^{15}$ cm$^{-3}$ range and record-high room temperature Hall electron mobilities of up to 200 cm$^2$/V.s, reaching the predicted theoretical maximum room temperature mobility value for $\beta$-Ga$_2$O$_3$. Growth of the homoepitaxial films was performed on Fe-doped (010) $\beta$-Ga$_2$O$_3$ substrates at a growth rate of 1.9 $\mu$m/hr using TEGa as the Gallium precursor. To probe the background electron concentration, an unintentionally doped film was grown with a Hall concentration of 3.43 x 10$^{15}$ cm$^{-3}$ and Hall mobility of 196 cm$^2$/V.s. Growth of intentionally Si-Doped films was accomplished by fixing all growth conditions and varying only the silane flow, with controllable Hall electron concentrations ranging from 4.38 x 10$^{15}$ cm$^{-3}$ to 8.30 x 10$^{15}$ cm$^{-3}$ and exceptional Hall mobilities ranging from 194 - 200 cm$^2$/V.s demonstrated. C-V measurements showed a flat charge profile with the N$_D^+$ - N$_A^-$ values correlating well with the Hall-measured electron concentration in the films. SIMS measurements showed the silicon atomic concentration matched the Hall electron concentration with Carbon and Hydrogen below detection limit in the films. The Hall, C-V, and SIMS data indicate the growth of high-quality 4.5 $\mu$m thick $\beta$-Ga$_2$O$_3$ films and controllable doping into the mid 10$^{15}$ cm$^{-3}$ range. These results demonstrate MOCVD growth of electronics grade record-high mobility, low carrier density, and thick $\beta$-Ga$_2$O$_3$ drift layers for next generation vertical $\beta$-Ga$_2$O$_3$ power devices., Comment: 16 Pages, 10 Figures, 2 Tables

We present new VLTI/GRAVITY near-infrared interferometric measurements of the angular size of the innermost hot dust continuum for 14 type 1 AGNs. The angular sizes are resolved on scales of ~0.7 mas and the inferred ring radii range from 0.028 to 1.33 pc, comparable to those reported previously and a factor 10-20 smaller than the mid-infrared sizes in the literature. Combining our new data with previously published values, we compile a sample of 25 AGN with bolometric luminosity ranging from $10^{42}$ to $10^{47} \rm erg~s^{-1}$, with which we study the radius-luminosity (R-L) relation for the hot dust structure. Our interferometric measurements of radius are offset by a factor 2 from the equivalent relation derived through reverberation mapping. Using a simple model to explore the dust structure's geometry, we conclude that this offset can be explained if the 2 um emitting surface has a concave shape. Our data show that the slope of the relation is in line with the canonical $R \propto L^{0.5}$ when using an appropriately non-linear correction for bolometric luminosity. In contrast, using optical luminosity or applying a constant bolometric correction to it results in a significant deviation in the slope, suggesting a potential luminosity dependence on the spectral energy distribution. Over four orders of magnitude in luminosity, the intrinsic scatter around the R-L relation is 0.2 dex, suggesting a tight correlation between innermost hot dust structure size and the AGN luminosity., Comment: 14 pages, 5 figures, 4 tables, accepted for publication in A&A

Excitons in transition metal dichalcogenides (TMDs) have emerged as a promising platform for novel applications ranging from optoelectronic devices to quantum optics and solid state quantum simulators. While much progress has been made towards characterizing and controlling excitons in TMDs, manipulating their properties during the course of their lifetime - a key requirement for many optoelectronic device and information processing modalities - remains an outstanding challenge. Here we combine long-lived interlayer excitons in angle-aligned MoSe$_2$/WSe$_2$ heterostructures with fast electrical control to realize dynamical control schemes, in which exciton properties are not predetermined at the time of excitation but can be dynamically manipulated during their lifetime. Leveraging the out-of-plane exciton dipole moment, we use electric fields to demonstrate dynamical control over the exciton emission wavelength. Moreover, employing a patterned gate geometry, we demonstrate rapid local sample doping and toggling of the radiative decay rate through exciton-charge interactions during the exciton lifetime. Spatially mapping the exciton response reveals charge redistribution, offering a novel probe of electronic transport in twisted TMD heterostructures. Our results establish the feasibility of dynamical exciton control schemes, unlocking new directions for exciton-based information processing and optoelectronic devices, and the realization of excitonic phenomena in TMDs., Comment: 37 pages, 4 figures in main text, 6 figures in supplemental materials; (v2) corrected funding acknowledgements

We present 1.8 years of near-daily Swift monitoring of the bright, strongly variable Type 1 AGN Fairall 9. Totaling 575 successful visits, this is the largest such campaign reported to date. Variations within the UV/optical are well-correlated, with longer wavelengths lagging shorter wavelengths in the direction predicted by thin disk/lamp-post models. The correlations are improved by detrending; subtracting a second-order polynomial fit to the UV/optical light curves to remove long-term trends that are not of interest to this study. Extensive testing indicates detrending with higher-order polynomials removes too much intrinsic variability signal on reverberation timescales. These data provide the clearest detection to date of interband lags within the UV, indicating that neither emission from a large disk nor diffuse continuum emission from the broad-line region can independently explain the full observed lag spectrum. The observed X-ray flux variations are poorly correlated with those in the UV/optical. Further, subdivision of the data into four ~160 day light curves shows that the UV/optical lag spectrum is highly stable throughout the four periods, but the X-ray to UV lags are unstable, significantly changing magnitude and even direction from one period to the next. This indicates the X-ray to UV relationship is more complex than predicted by the simple reprocessing model often adopted for AGN. A bowl model (lamp-post irradiation and blackbody reprocessing on a disk with a steep rim) fit suggests the disk thickens at a distance (~10 lt-day) and temperature (~8000K) consistent with the inner edge of the BLR., Comment: 20 pages, 9 figures, to appear in ApJ

In this paper, we propose Varying Effects Regression with Graph Estimation (VERGE), a novel Bayesian method for feature selection in regression. Our model has key aspects that allow it to leverage the complex structure of data sets arising from genomics or imaging studies. We distinguish between the predictors, which are the features utilized in the outcome prediction model, and the subject-level covariates, which modulate the effects of the predictors on the outcome. We construct a varying coefficients modeling framework where we infer a network among the predictor variables and utilize this network information to encourage the selection of related predictors. We employ variable selection spike-and-slab priors that enable the selection of both network-linked predictor variables and covariates that modify the predictor effects. We demonstrate through simulation studies that our method outperforms existing alternative methods in terms of both feature selection and predictive accuracy. We illustrate VERGE with an application to characterizing the influence of gut microbiome features on obesity, where we identify a set of microbial taxa and their ecological dependence relations. We allow subject-level covariates including sex and dietary intake variables to modify the coefficients of the microbiome predictors, providing additional insight into the interplay between these factors.

There has been a large number of studies in interpretable and explainable ML for cybersecurity, in particular, for intrusion detection. Many of these studies have significant amount of overlapping and repeated evaluations and analysis. At the same time, these studies overlook crucial model, data, learning process, and utility related issues and many times completely disregard them. These issues include the use of overly complex and opaque ML models, unaccounted data imbalances and correlated features, inconsistent influential features across different explanation methods, the inconsistencies stemming from the constituents of a learning process, and the implausible utility of explanations. In this work, we empirically demonstrate these issues, analyze them and propose practical solutions in the context of feature-based model explanations. Specifically, we advise avoiding complex opaque models such as Deep Neural Networks and instead using interpretable ML models such as Decision Trees as the available intrusion datasets are not difficult for such interpretable models to classify successfully. Then, we bring attention to the binary classification metrics such as Matthews Correlation Coefficient (which are well-suited for imbalanced datasets. Moreover, we find that feature-based model explanations are most often inconsistent across different settings. In this respect, to further gauge the extent of inconsistencies, we introduce the notion of cross explanations which corroborates that the features that are determined to be impactful by one explanation method most often differ from those by another method. Furthermore, we show that strongly correlated data features and the constituents of a learning process, such as hyper-parameters and the optimization routine, become yet another source of inconsistent explanations. Finally, we discuss the utility of feature-based explanations.

Active Galactic Nuclei (AGN) are prime candidate sources of the high-energy, astrophysical neutrinos detected by IceCube. This is demonstrated by the real-time multi-messenger detection of the blazar TXS 0506+056 and the recent evidence of neutrino emission from NGC 1068 from a separate time-averaged study. However, the production mechanism of the astrophysical neutrinos in AGN is not well established which can be resolved via correlation studies with photon observations. For neutrinos produced due to photohadronic interactions in AGN, in addition to a correlation of neutrinos with high-energy photons, there would also be a correlation of neutrinos with photons emitted at radio wavelengths. In this work, we perform an in-depth stacking study of the correlation between 15 GHz radio observations of AGN reported in the MOJAVE XV catalog, and ten years of neutrino data from IceCube. We also use a time-dependent approach which improves the statistical power of the stacking analysis. No significant correlation was found for both analyses and upper limits are reported. When compared to the IceCube diffuse flux, at 100 TeV and for a spectral index of 2.5, the upper limits derived are $\sim3\%$ and $\sim9\%$ for the time-averaged and time-dependent case, respectively., Comment: 14 Pages 7 Figures

We present a search for an eV-scale sterile neutrino using 7.5 years of data from the IceCube DeepCore detector. The analysis uses a sample of 21,914 events with energies between 5 and 150 GeV to search for sterile neutrinos through atmospheric muon neutrino disappearance. Improvements in event selection and treatment of systematic uncertainties provide greater statistical power compared to previous DeepCore sterile neutrino searches. Our results are compatible with the absence of mixing between active and sterile neutrino states, and we place constraints on the mixing matrix elements $|U_{\mu 4}|^2 < 0.0534$ and $|U_{\tau 4}|^2 < 0.0574$ at 90% CL under the assumption that $\Delta m^2_{41}\geq 1\;\mathrm{eV^2}$. These null results add to the growing tension between anomalous appearance results and constraints from disappearance searches in the 3+1 sterile neutrino landscape., Comment: 11 pages, 5 figures. Version accepted by Physical Review D for publication

In order for AI systems to communicate effectively with people, they must understand how we make decisions. However, people's decisions are not always rational, so the implicit internal models of human decision-making in Large Language Models (LLMs) must account for this. Previous empirical evidence seems to suggest that these implicit models are accurate -- LLMs offer believable proxies of human behavior, acting how we expect humans would in everyday interactions. However, by comparing LLM behavior and predictions to a large dataset of human decisions, we find that this is actually not the case: when both simulating and predicting people's choices, a suite of cutting-edge LLMs (GPT-4o & 4-Turbo, Llama-3-8B & 70B, Claude 3 Opus) assume that people are more rational than we really are. Specifically, these models deviate from human behavior and align more closely with a classic model of rational choice -- expected value theory. Interestingly, people also tend to assume that other people are rational when interpreting their behavior. As a consequence, when we compare the inferences that LLMs and people draw from the decisions of others using another psychological dataset, we find that these inferences are highly correlated. Thus, the implicit decision-making models of LLMs appear to be aligned with the human expectation that other people will act rationally, rather than with how people actually act.

The recent IceCube detection of TeV neutrino emission from the nearby active galaxy NGC 1068 suggests that active galactic nuclei (AGN) could make a sizable contribution to the diffuse flux of astrophysical neutrinos. The absence of TeV $\gamma$-rays from NGC 1068 indicates neutrino production in the vicinity of the supermassive black hole, where the high radiation density leads to $\gamma$-ray attenuation. Therefore, any potential neutrino emission from similar sources is not expected to correlate with high-energy $\gamma$-rays. Disk-corona models predict neutrino emission from Seyfert galaxies to correlate with keV X-rays, as they are tracers of coronal activity. Using through-going track events from the Northern Sky recorded by IceCube between 2011 and 2021, we report results from a search for individual and aggregated neutrino signals from 27 additional Seyfert galaxies that are contained in the BAT AGN Spectroscopic Survey (BASS). Besides the generic single power-law, we evaluate the spectra predicted by the disk-corona model. Assuming all sources to be intrinsically similar to NGC 1068, our findings constrain the collective neutrino emission from X-ray bright Seyfert galaxies in the Northern Hemisphere, but, at the same time, show excesses of neutrinos that could be associated with the objects NGC 4151 and CGCG 420-015. These excesses result in a 2.7$\sigma$ significance with respect to background expectations., Comment: 17 pages, 9 figures

The Infra-Red Video Bolometer (IRVB) is a diagnostic equipped with an infra-red camera that measures the total radiated power in thousands of LOSs within a large field of view (FOV). Recently validated in MAST-U, it offers a high spatial resolution map of the radiated power in the divertor region, where large gradients are expected. The IRVB's sensing element comprises a thin layer of high Z absorbing material, typically Platinum, usually coated with Carbon to reduce reflections. It is here explored the possibility of using a relatively inert material like Titanium, that can be produced in layers up to 1mum compared to 2.5mum for Pt, and then coat it with Pt of the desired thickness (0.3mum per side here) and Carbon. This leads to a higher temperature signal (2 to 3 times), and better spatial resolution (about 4 times), resulting in higher accuracy in the measured power. This assembly is also expected to improve foil uniformity, as the Pt layer is obtained via deposition rather than mechanical processes. Given its multi-material composition, measuring the thermal properties of the foil assembly is vital. Various methods using a calibrated laser as a heat source have been developed, analysing the temperature profile shape or fitting the calculated laser power for different intensities and frequencies. It is here presented a simpler approach, that relies on analysing the separate components of the foil heat equation for a single laser exposure in a given area. This can then be iterated over the entire foil to capture local deviations., Comment: Submitted to Review of Scientific Instruments

Active Galactic Nuclei (AGN) are promising candidate sources of high-energy astrophysical neutrinos since they provide environments rich in matter and photon targets where cosmic ray interactions may lead to the production of gamma rays and neutrinos. We searched for high-energy neutrino emission from AGN using the $\textit{Swift}$-BAT Spectroscopic Survey (BASS) catalog of hard X-ray sources and 12 years of IceCube muon track data. First, upon performing a stacked search, no significant emission was found. Second, we searched for neutrinos from a list of 43 candidate sources and found an excess from the direction of two sources, Seyfert galaxies NGC 1068 and NGC 4151. We observed NGC 1068 at flux $\phi_{\nu_{\mu}+\bar{\nu}_{\mu}}$ = $4.02_{-1.52}^{+1.58} \times 10^{-11}$ TeV$^{-1}$ cm$^{-2}$ s$^{-1}$ normalized at 1 TeV, with power-law spectral index, $\gamma$ = 3.10$^{+0.26}_{-0.22}$, consistent with previous IceCube results. The observation of a neutrino excess from the direction of NGC 4151 is at a post-trial significance of 2.9$\sigma$. If interpreted as an astrophysical signal, the excess observed from NGC 4151 corresponds to a flux $\phi_{\nu_{\mu}+\bar{\nu}_{\mu}}$ = $1.51_{-0.81}^{+0.99} \times 10^{-11}$ TeV$^{-1}$ cm$^{-2}$ s$^{-1}$ normalized at 1 TeV and $\gamma$ = 2.83$^{+0.35}_{-0.28}$.

Ongoing advances in microbiome profiling have allowed unprecedented insights into the molecular activities of microbial communities. This has fueled a strong scientific interest in understanding the critical role the microbiome plays in governing human health, by identifying microbial features associated with clinical outcomes of interest. Several aspects of microbiome data limit the applicability of existing variable selection approaches. In particular, microbiome data are high-dimensional, extremely sparse, and compositional. Importantly, many of the observed features, although categorized as different taxa, may play related functional roles. To address these challenges, we propose a novel compositional regression approach that leverages the data-adaptive clustering and variable selection properties of the spiked Dirichlet process to identify taxa that exhibit similar functional roles. Our proposed method, Bayesian Regression with Agglomerated Compositional Effects using a dirichLET process (BRACElet), enables the identification of a sparse set of features with shared impacts on the outcome, facilitating dimension reduction and model interpretation. We demonstrate that BRACElet outperforms existing approaches for microbiome variable selection through simulation studies and an application elucidating the impact of oral microbiome composition on insulin resistance.

We present the first three-parameter fit to a 3+1 sterile neutrino model using 7.634 years of data from the IceCube Neutrino Observatory on $\nu_\mu+\overline{\nu}_\mu$ charged-current interactions in the energy range 500-9976 GeV. Our analysis is sensitive to the mass-squared splitting between the heaviest and lightest mass state ($\Delta m_{41}^2$), the mixing matrix element connecting muon flavor to the fourth mass state ($|U_{\mu4}|^2$), and the element connecting tau flavor to the fourth mass state ($|U_{\tau4}|^2$). Predicted propagation effects in matter enhance the signature through a resonance as atmospheric neutrinos from the Northern Hemisphere traverse the Earth to the IceCube detector at the South Pole. The result is consistent with the no-sterile neutrino hypothesis with a probability of 4.3 %. Profiling the likelihood of each parameter yields the 90 % confidence levels: $ 2.4\,\mathrm{eV}^{2} < \Delta m_{41}^2 <9.6\,\mathrm{eV}^{2} $ , $0.0081 < |U_{\mu4}|^2 < 0.10$ , and $|U_{\tau4}|^2< 0.035$, which narrows the allowed parameter-space for $|U_{\tau4}|^2$. However, the primary result of this analysis is the first map of the 3+1 parameter space exploring the interdependence of $\Delta m_{41}^2$, $|U_{\mu4}|^2$, and $|U_{\tau4}|^2$.

The MANTA (Modular Adjustable Negative Triangularity ARC-class) design study investigated how negative-triangularity (NT) may be leveraged in a compact, fusion pilot plant (FPP) to take a ``power-handling first" approach. The result is a pulsed, radiative, ELM-free tokamak that satisfies and exceeds the FPP requirements described in the 2021 National Academies of Sciences, Engineering, and Medicine report ``Bringing Fusion to the U.S. Grid". A self-consistent integrated modeling workflow predicts a fusion power of 450 MW and a plasma gain of 11.5 with only 23.5 MW of power to the scrape-off layer (SOL). This low $P_\text{SOL}$ together with impurity seeding and high density at the separatrix results in a peak heat flux of just 2.8 MW/m$^{2}$. MANTA's high aspect ratio provides space for a large central solenoid (CS), resulting in ${\sim}$15 minute inductive pulses. In spite of the high B fields on the CS and the other REBCO-based magnets, the electromagnetic stresses remain below structural and critical current density limits. Iterative optimization of neutron shielding and tritium breeding blanket yield tritium self-sufficiency with a breeding ratio of 1.15, a blanket power multiplication factor of 1.11, toroidal field coil lifetimes of $3100 \pm 400$ MW-yr, and poloidal field coil lifetimes of at least $890 \pm 40$ MW-yr. Following balance of plant modeling, MANTA is projected to generate 90 MW of net electricity at an electricity gain factor of ${\sim}2.4$. Systems-level economic analysis estimates an overnight cost of US\$3.4 billion, meeting the NASEM FPP requirement that this first-of-a-kind be less than US\$5 billion. The toroidal field coil cost and replacement time are the most critical upfront and lifetime cost drivers, respectively.