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Solar active regions (ARs) are often surrounded by dark large areas of reduced emission compared to the quiet Sun, observed at various wavelengths corresponding to chromosphere, transition region (TR) and corona, and known as Dark Halos (DHs). DHs have been insufficiently studied, and the mechanisms behind their darker emission remain unclear. This study aims to investigate for the first time the fine structure of a DH observed by the EUV High Resolution Imager (HRI$_{EUV}$) onboard the ESA's Solar Orbiter (SO) mission and its appearance in the TR. We utilized the extensive 1-hour dataset from SO on 19 March 2022, which includes high-resolution observations of NOAA 12967 and part of the surrounding DH. We analyzed the dynamics of the HRI$_{EUV}$ DH fine structure and its appearance in the HRI$_{Ly\alpha}$ image and the Spectral Imaging of the Coronal Environment (SPICE) Ly$\beta$, C III, N VI, O VI and Ne VIII lines, which sample the TR in the logT (K) $\sim$ 4.0 - 5.8 range. This analysis was complemented with a simultaneous B$_{LOS}$ magnetogram taken by the High Resolution Telescope (HRT). We report the presence of a peculiar fine structure which is not observed in the quiet Sun, characterized by combined bright EUV bundles and dark regions, arranged and interconnected in such a way that they cannot be clearly separated. They form a spatial continuum extending approximately radially from the AR core, suggesting a deep connection between the DH and the AR. Additionally, we find that the bright EUV bundles are observed in all the SPICE TR lines and the HRI$_{Ly\alpha}$ band and present photospheric B$_{LOS}$ footprints in the HRT magnetogram. This spatial correlation indicates that the origin of the 174 \r{A} DH may lie in the low atmosphere, i.e. photosphere/chromosphere., Comment: 9 pages, 8 figures; accepted for A&A

Instead of testing for unanimous agreement, I propose learning how broad of a consensus favors one distribution over another (of earnings, productivity, asset returns, test scores, etc.). Specifically, given a sample from each of two distributions, I propose statistical inference methods to learn about the set of utility functions for which the first distribution has higher expected utility than the second distribution. With high probability, an "inner" confidence set is contained within this true set, while an "outer" confidence set contains the true set. Such confidence sets can be formed by inverting a proposed multiple testing procedure that controls the familywise error rate. Theoretical justification comes from empirical process results, given that very large classes of utility functions are generally Donsker (subject to finite moments). The theory additionally justifies a uniform (over utility functions) confidence band of expected utility differences, as well as tests with a utility-based "restricted stochastic dominance" as either the null or alternative hypothesis. Simulated and empirical examples illustrate the methodology., Comment: accepted manuscript

Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. In this work, we present two surface code memories operating below this threshold: a distance-7 code and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of $\Lambda$ = 2.14 $\pm$ 0.02 when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% $\pm$ 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of 2.4 $\pm$ 0.3. We maintain below-threshold performance when decoding in real time, achieving an average decoder latency of 63 $\mu$s at distance-5 up to a million cycles, with a cycle time of 1.1 $\mu$s. To probe the limits of our error-correction performance, we run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or 3 $\times$ 10$^9$ cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms., Comment: 10 pages, 4 figures, Supplementary Information

Knowledge refactoring compresses a logic program by introducing new rules. Current approaches struggle to scale to large programs. To overcome this limitation, we introduce a constrained optimisation refactoring approach. Our first key idea is to encode the problem with decision variables based on literals rather than rules. Our second key idea is to focus on linear invented rules. Our empirical results on multiple domains show that our approach can refactor programs quicker and with more compression than the previous state-of-the-art approach, sometimes by 60%.

This study investigates the band inversion of flat bands in zigzag graphene nanoribbons (ZGNRs) using a tight-binding model. The band inversion results from symmetry breaking in the transverse direction, achievable through deposition on specific substrates such as separated silicon carbide or hexagonal boron nitride sheets. Upon band inversion, ZGNRs exhibit electronic structures characterized by valley degeneracy and band gap properties, which can be modulated by transverse electric fields. To explore the impact of this level degeneracy on thermoelectric properties, we employ Green's function techniques to calculate thermoelectric quantities in ZGNR segments with staggered sublattice potentials and transverse electric fields. Two carrier transport scenarios are considered: the chemical potential is positioned above and below the highest occupied molecular orbital. We analyze thermionic-assisted transport (TAT) and direct ballistic transport (DBT). Level degeneracy enhances the electric power factors of ZGNRs by increasing electrical conductance, while the Seebeck coefficient remains robust in the TAT scenario. Conversely, in DBT, the enhancement of the power factor primarily stems from improvements in the Seebeck coefficient at elevated temperatures., Comment: 10 pages and 11 figures

Automatic metrics are extensively used to evaluate natural language processing systems. However, there has been increasing focus on how they are used and reported by practitioners within the field. In this paper, we have conducted a survey on the use of automatic metrics, focusing particularly on natural language generation (NLG) tasks. We inspect which metrics are used as well as why they are chosen and how their use is reported. Our findings from this survey reveal significant shortcomings, including inappropriate metric usage, lack of implementation details and missing correlations with human judgements. We conclude with recommendations that we believe authors should follow to enable more rigour within the field., Comment: Accepted to INLG 2024

We present the identification of changing-look active galactic nuclei (CL-AGNs) from the Dark Energy Spectroscopic Instrument First Data Release and Sloan Digital Sky Survey Data Release 16 at z \leq 0.9. To confirm the CL-AGNs, we utilize spectral flux calibration assessment via an [O\,{\sc iii}]-based calibration, pseudo-photometry examination, and visual inspection. This rigorous selection process allows us to compile a statistical catalog of 561 CL-AGNs, encompassing 527 $\rm H\beta$, 149$\rm H\alpha$, and 129 Mg II CL behaviors. In this sample, we find 1) a 283:278 ratio of turn-on to turn-off CL-AGNs. 2) the critical value for CL events is confirmed around Eddington ratio \sim 0.01. 3) a strong correlation between the change in the luminosity of the broad emission lines (BEL) and variation in the continuum luminosity, with Mg II and $\rm H\beta$ displaying similar responses during CL phases. 4) the Baldwin-Phillips-Terlevich diagram for CL-AGNs shows no statistically difference from the general AGN catalog. 5) five CL-AGNs are associated with asymmetrical mid-infrared flares, possibly linked to tidal disruption events. Given the large CL-AGNs and the stochastic sampling of spectra, we propose that some CL events are inherently due to typical AGN variability during low accretion rates, particularly for CL events of the singular BEL. Finally, we introduce a Peculiar CL phase, characterized by a gradual decline over decades in the light curve and the complete disappearance of entire BEL in faint spectra, indicative of a real transition in the accretion disk., Comment: Submitted to ApJS, comments welcome

Many-body localization (MBL) lends remarkable robustness to nonequilibrium phases of matter. Such phases can show topological and symmetry breaking order in their ground and excited states, but they may also belong to an anomalous localized topological phase (ALT phase). All eigenstates in an ALT phase are trivial, in that they can be deformed to product states, but the entire Hamiltonian cannot be deformed to a trivial localized model without going through a delocalization transition. Using a correspondence between MBL phases with short-ranged entanglement and locality preserving unitaries - called quantum cellular automata (QCA) - we reduce the classification of ALT phases to that of QCA. This method extends to periodically (Floquet) and quasiperiodically driven ALT phases, and captures anomalous Floquet phases within the same framework as static phases. The QCA framework further generalizes to include symmetry-enriched ALT phases (SALT phases), and provides a large class of soluble models suitable for realization in quantum simulators. In systematizing the study of ALT phases, we both greatly extend the classification of interacting nonequilibrium systems and clarify a confusion in the literature which implicitly equates nontrivial Hamiltonians with nontrivial ground states., Comment: 5 pages, 3 figures + 22 pages, 2 figures (appendices); (v2) corrections to the classification with symmetry

Coupling between relativistic jets launched by accreting supermassive black holes and the surrounding gaseous media is a vital ingredient in galaxy evolution models. To constrain the environments in which this feedback takes place over cosmic time, we study the host halo properties of luminous low-frequency radio galaxies ($L_{150 \ \mathrm{MHz}} \gtrsim$ 25.25 W/Hz) selected with the International LOFAR Telescope out to $z \sim 2$ through tomographic clustering and cosmic microwave background lensing measurements. We find that these systems occupy halos characteristic of galaxy groups ($M_h = 10^{13} - 10^{14} h^{-1} M_{\odot}$), evolving at a rate consistent with the mean growth rate of halos over the past $\sim$10 Gyr. The coevolution of the clustering and the luminosity function reveals that the duty cycle of these systems is of order $\sim 10\%$ but has been mildly increasing since $z\sim 2$, while the duty cycle of quasars has been declining. We estimate the characteristic kinetic heating power injected by powerful jets per halo as a function of mass, and compare to the same quantity injected by quasar winds. We find that powerful jet heating dominates over quasar winds in halos $M_h \gtrsim 10^{13} h^{-1} M_{\odot}$ at $z < 2$. These results conform to the paradigm of galaxy evolution in which mechanical jet power feedback is the dominant heating mechanism of the gas content of groups and clusters., Comment: Accepted to ApJ

Age is the most difficult fundamental stellar parameter to infer for isolated stars. While isochrone-based ages are in general imprecise for both main sequence dwarfs and red giants, precise isochrone-based ages can be obtained for stars on the subgiant branch transitioning from core to shell hydrogen burning. We synthesize Gaia DR3-based distance inferences, multiwavelength photometry from the ultraviolet to the mid infrared, and three-dimensional extinction maps to construct a sample of 289,759 solar-metallicity stars amenable to accurate, precise, and physically self-consistent age inferences. Using subgiants in the solar-metallicity open clusters NGC 2682 (i.e., M 67) and NGC 188, we show that our approach yields accurate and physically self-consistent ages and metallicities with median statistical precisions of 8\% and 0.06 dex. The inclusion of systematic uncertainties resulting from non-single or variable stars results in age and metallicity precisions of 9\% and 0.12 dex. We supplement this solar-metallicity sample with an additional 112,062 metal-poor subgiants, including over 3,000 stars with $[\text{Fe/H}]\lesssim-1.50$, 7\% age precisions, and apparent Gaia $G$-band magnitudes $G<14$. We further demonstrate that our inferred metallicities agree with those produced by multiplexed spectroscopic surveys. As an example of the scientific potential of this catalog, we show that the solar neighborhood star-formation history has three components at $([\text{Fe/H}],\tau/\text{Gyr}) \approx (+0.0,4)$, $(+0.2,7)$, and a roughly linear sequence in age--metallicity space beginning at $([\text{Fe/H}],\tau/\text{Gyr})\approx(+0.2,7)$ and extending to $(-0.5,13)$. Our analyses indicate that the solar neighborhood includes stars on disk-like orbits even at the oldest ages and lowest metallicities accessible by our samples., Comment: 31 pages, 13 figures, accepted for publication in the AAS Journals. Our input data tables, output tables of derived parameters, and an animation of the derived relationship between the dynamics and the star-formation history of solar neighbourhood subgiants, are available at: https://github.com/DavidMoiseNataf/Subgiants/

In the last decade, remarkable advances in integrated photonic technologies have enabled table-top experiments and instrumentation to be scaled down to compact chips with significant reduction in size, weight, power consumption, and cost. Here, we demonstrate an integrated continuously tunable laser in a heterogeneous gallium arsenide-on-silicon nitride (GaAs-on-SiN) platform that emits in the far-red radiation spectrum near 780 nm, with 20 nm tuning range, <6 kHz intrinsic linewidth, and a >40 dB side-mode suppression ratio. The GaAs optical gain regions are heterogeneously integrated with low-loss SiN waveguides. The narrow linewidth lasing is achieved with an extended cavity consisting of a resonator-based Vernier mirror and a phase shifter. Utilizing synchronous tuning of the integrated heaters, we show mode-hop-free wavelength tuning over a range larger than 100 GHz (200 pm). To demonstrate the potential of the device, we investigate two illustrative applications: (i) the linear characterization of a silicon nitride microresonator designed for entangled-photon pair generation, and (ii) the absorption spectroscopy and locking to the D1 and D2 transition lines of 87-Rb. The performance of the proposed integrated laser holds promise for a broader spectrum of both classical and quantum applications in the visible range, encompassing communication, control, sensing, and computing.

This paper expands on the concepts presented in Applying the Nash Bargaining Solution for a Reasonable Royalty ( arXiv:2005.10158 ). The goal is to refine the process for determining a reasonable royalty using statistical methods in cases where there is risk and uncertainty regarding each party's disagreement payoffs (opportunity costs) in the Nash Bargaining Solution (NBS). This paper uses a Bayes Cost approach to analyze Case 1, Case 2, and the Original Nash model from the authors' previous work. By addressing risk and uncertainty in the NBS, the NBS emerges as a more reliable method for estimating a reasonable royalty, aligning with the criteria outlined in Georgia Pacific factor fifteen., Comment: 12 pages, 9 figures

Recent advancements in Large Multimodal Models (LMMs) have made significant progress in the field of single-image visual question answering. However, these models face substantial challenges when tasked with queries that span extensive collections of images, similar to real-world scenarios like searching through large photo albums, finding specific information across the internet, or monitoring environmental changes through satellite imagery. This paper explores the task of Multi-Image Visual Question Answering (MIQA): given a large set of images and a natural language query, the task is to generate a relevant and grounded response. We propose a new public benchmark, dubbed "Visual Haystacks (VHs)," specifically designed to evaluate LMMs' capabilities in visual retrieval and reasoning over sets of unrelated images, where we perform comprehensive evaluations demonstrating that even robust closed-source models struggle significantly. Towards addressing these shortcomings, we introduce MIRAGE (Multi-Image Retrieval Augmented Generation), a novel retrieval/QA framework tailored for LMMs that confronts the challenges of MIQA with marked efficiency and accuracy improvements over baseline methods. Our evaluation shows that MIRAGE surpasses closed-source GPT-4o models by up to 11% on the VHs benchmark and offers up to 3.4x improvements in efficiency over text-focused multi-stage approaches., Comment: Project page: https://visual-haystacks.github.io

Predictive estimation, which comprises model calibration, model prediction, and validation, is a common objective when performing inverse uncertainty quantification (UQ) in diverse scientific applications. These techniques typically require thousands to millions of realisations of the forward model, leading to high computational costs. Surrogate models are often used to approximate these simulations. However, many surrogate models suffer from the fundamental limitation of being unable to estimate plausible high-dimensional outputs, inevitably compromising their use in the UQ framework. To address this challenge, this study introduces an efficient surrogate modelling workflow tailored for high-dimensional outputs. Specifically, a two-step approach is developed: (1) a dimensionality reduction technique is used for extracting data features and mapping the original output space into a reduced space; and (2) a multivariate surrogate model is constructed directly on the reduced space. The combined approach is shown to improve the accuracy of the surrogate model while retaining the computational efficiency required for UQ inversion. The proposed surrogate method, combined with Bayesian inference, is evaluated for a civil engineering application by performing inverse analyses on a laterally loaded pile problem. The results demonstrate the superiority of the proposed framework over traditional surrogate methods in dealing with high-dimensional outputs for sequential inversion analysis., Comment: 19 pages, 10 figures

Ultrasonic processing of solidifying metals in additive manufacturing can provide grain refinement and advantageous mechanical properties. However, the specific physical mechanisms of microstructural refinement relevant to laser-based additive manufacturing have not been directly observed because of sub-millimeter length scales and rapid solidification rates associated with melt pools. Here, high-speed synchrotron X-ray imaging is used to observe the effect of ultrasonic vibration directly on melt pool dynamics and solidification of Al6061 alloy. The high temporal and spatial resolution enabled direct observation of cavitation effects driven by a 20.2 kHz ultrasonic source. We utilized multiphysics simulations to validate the postulated connection between ultrasonic treatment and solidification. The X-ray results show a decrease in melt pool and keyhole depth fluctuations during melting and promotion of pore migration toward the melt pool surface with applied sonication. Additionally, the simulation results reveal increased localized melt pool flow velocity, cooling rates, and thermal gradients with applied sonication. This work shows how ultrasonic treatment can impact melt pools and its potential for improving part quality.

We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables

Large language models (LLMs) are trained from vast repositories of text authored by millions of distinct authors, reflecting an enormous diversity of human traits. While these models bear the potential to be used as approximations of human subjects in behavioral studies, prior efforts have been limited in steering model responses to match individual human users. In this work, we introduce "Anthology", a method for conditioning LLMs to particular virtual personas by harnessing open-ended life narratives, which we refer to as "backstories." We show that our methodology enhances the consistency and reliability of experimental outcomes while ensuring better representation of diverse sub-populations. Across three nationally representative human surveys conducted as part of Pew Research Center's American Trends Panel (ATP), we demonstrate that Anthology achieves up to 18% improvement in matching the response distributions of human respondents and 27% improvement in consistency metrics. Our code and generated backstories are available at https://github.com/CannyLab/anthology.

Pre-fault tolerant quantum computers have already demonstrated the ability to estimate observable values accurately, at a scale beyond brute-force classical computation. This has been enabled by error mitigation techniques that often rely on a representative model on the device noise. However, learning and maintaining these models is complicated by fluctuations in the noise over unpredictable time scales, for instance, arising from resonant interactions between superconducting qubits and defect two-level systems (TLS). Such interactions affect the stability and uniformity of device performance as a whole, but also affect the noise model accuracy, leading to incorrect observable estimation. Here, we experimentally demonstrate that tuning of the qubit-TLS interactions helps reduce noise instabilities and consequently enables more reliable error-mitigation performance. These experiments provide a controlled platform for studying the performance of error mitigation in the presence of quasi-static noise. We anticipate that the capabilities introduced here will be crucial for the exploration of quantum applications on solid-state processors at non-trivial scales., Comment: 8 pages, 4 figures (13 pages, 8 figures for supplementary material), reference numbering has been fixed at v2

RR Lyrae stars are excellent tracers of stellar populations for old, metal-poor components in the Milky Way Galaxy and the Local Group. Their luminosities have a metallicity-dependence, but determining spectroscopic [Fe/H] metallicities for RR Lyrae stars, especially at distances outside the solar neighbourhood, is challenging. Using 40 RRLs with metallicities derived from both Fe(II) and Fe(I) abundances, we verify the calibration between the [Fe/H] of RR Lyrae stars from the Calcium triplet. Our calibration is applied to all RR Lyrae stars with Gaia RVS spectra in Gaia DR3 as well as to 80 stars in the inner Galaxy from the BRAVA-RR survey. The co-added Gaia RVS RR Lyrae spectra provide RR Lyrae metallicities with an uncertainty of 0.25~dex, which is a factor of two improvement over the Gaia photometric RR Lyrae metallicities. Within our Galactic bulge RR Lyrae star sample, we find a dominant fraction with low energies without a prominent rotating component. Due to the large fraction of such stars, we interpret these stars as belonging to the $in-situ$ metal-poor Galactic bulge component, although we can not rule out that a fraction of these belong to an ancient accretion event such as Kraken/Heracles., Comment: accepted for publication in The Astronomical Journal

The parametric greedy latent space dynamics identification (gLaSDI) framework has demonstrated promising potential for accurate and efficient modeling of high-dimensional nonlinear physical systems. However, it remains challenging to handle noisy data. To enhance robustness against noise, we incorporate the weak-form estimation of nonlinear dynamics (WENDy) into gLaSDI. In the proposed weak-form gLaSDI (WgLaSDI) framework, an autoencoder and WENDy are trained simultaneously to discover intrinsic nonlinear latent-space dynamics of high-dimensional data. Compared to the standard sparse identification of nonlinear dynamics (SINDy) employed in gLaSDI, WENDy enables variance reduction and robust latent space discovery, therefore leading to more accurate and efficient reduced-order modeling. Furthermore, the greedy physics-informed active learning in WgLaSDI enables adaptive sampling of optimal training data on the fly for enhanced modeling accuracy. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including viscous and inviscid Burgers' equations, time-dependent radial advection, and the Vlasov equation for plasma physics. With data that contains 5-10% Gaussian white noise, WgLaSDI outperforms gLaSDI by orders of magnitude, achieving 1-7% relative errors. Compared with the high-fidelity models, WgLaSDI achieves 121 to 1,779x speed-up.

In this paper we provide a highly accurate value for the binding energy of benzene to proton-ordered crystalline water ice (XIh), as a model for interstellar ices. We compare our computed value to the latest experimental data available from temperature programmed desorption (TPD) experiments and find that our binding energy value agrees well with data obtained from binding to either crystalline or amorphous ice. Importantly, our new value is lower than that used in most astrochemical networks by about nearly half its value. We explore the impact of this revised binding energy value for both an AGB outflow and a protoplanetary disk. We find that the lower value of the binding energy predicted here compared with values used in the literature (4050 K versus 7587 K) leads to less depletion of gas-phase benzene in an AGB outflow, and leads to a shift outwards in the benzene snowline in the midplane of a protoplanetary disk. Using this new value, the AGB model predicts lower abundances of benzene in the solid phase throughout the outflow. The disk model also predicts a larger reservoir of gas-phase benzene in the inner disk, which is consistent with the recent detections of benzene for the first time in protoplanetary disks with JWST.

We consider two-dimensional hydroelastic waves, in which a free fluid surface separates two fluids of infinite vertical extent. Elastic effects are accounted for at the interface, with a parameter measuring the elastic bending force and another parameter measuring the mass of the elastic sheet. In prior work, the authors have demonstrated well-posedness of this initial value problem in Sobolev spaces. We now take the limit as these two parameters vanish. Since the size of the time interval of existence given by this prior theory vanishes as the mass and bending parameters go to zero, we now establish estimates which are uniform with respect to these parameters. We may then make an additional estimate which demonstrates that the solutions form a Cauchy sequence as the parameters go to zero, so that the limit may be taken. This demonstrates that the vortex sheet with surface tension is the zero mass, zero bending limit of hydroelastic waves in two spatial dimensions., Comment: 40 pages

The ability to control the stress-induced phase transformation of the shape memory alloy, NiTi, is an important technological challenge that must be understood for their wide application in devices that can exploit their reversible strain properties. This study elucidates the direct relationship between dislocation density and the \textit{R}-phase transformation, including its formation temperature from interrupted annealing of rolled NiTi samples. Deformation is shown to determine the enthalpy change required for the B2$\rightarrow$\textit{R}-phase transformation, with associated transformation temperatures being modifiable via dislocation density and recovery processes. Recovery is shown to be rapid, highly heterogeneous and sensitive to crystal orientation. Grains with a $\langle100\rangle$ direction close to the macroscopic rolling direction recover more rapidly than $\langle110\rangle$ and $\langle111\rangle$ orientated grains. Considered to be governed by processing induced residual stresses and resultant crystallographic dependent annihilation/slip pathways, there are opportunities to tune B2$\rightarrow$\textit{R}-phase transformation on either a grain-averaged or an orientation dependant per-grain basis.

We present the first X-ray spectropolarimetric results for Cygnus X-1 in its soft state from a campaign of five IXPE observations conducted during 2023 May-June. Companion multiwavelength data during the campaign are likewise shown. The 2-8 keV X-rays exhibit a net polarization degree PD=1.99%+/-0.13% (68% confidence). The polarization signal is found to increase with energy across IXPE's 2-8 keV bandpass. The polarized X-rays exhibit an energy-independent polarization angle of PA=-25.7+/-1.8 deg. East of North (68% confidence). This is consistent with being aligned to Cyg X-1's AU-scale compact radio jet and its pc-scale radio lobes. In comparison to earlier hard-state observations, the soft state exhibits a factor of 2 lower polarization degree, but a similar trend with energy and a similar (also energy-independent) position angle. When scaling by the natural unit of the disk temperature, we find the appearance of a consistent trendline in the polarization degree between soft and hard states. Our favored polarimetric model indicates Cyg X-1's spin is likely high (a* above ~0.96). The substantial X-ray polarization in Cyg X-1's soft state is most readily explained as resulting from a large portion of X-rays emitted from the disk returning and reflecting off the disk surface, generating a high polarization degree and a polarization direction parallel to the black hole spin axis and radio jet. In IXPE's bandpass, the polarization signal is dominated by the returning reflection emission. This constitutes polarimetric evidence for strong gravitational lensing of X-rays close to the black hole., Comment: 20 pages, accepted for publication in ApJL

We present a careful calibration of the exciton fraction of polaritons in high-$Q$ ($\sim 300,000$), long-lifetime ($\sim 300$ ps), GaAs/AlGaAs microcavities.This is a crucial parameter for many-body theories which include the polariton-polariton interactions.It is much harder to establish this number in high-$Q$ structures compared to low-$Q$ structures, because the upper polariton is nearly invisible in high-$Q$ cavities.We present a combination of photoluminescence, photoluminescence excitation, and reflectivity measurements to highly constrain the fit model, and compare the results of this model to the results from low-$Q$ structures.We present a fitted curve of exciton fraction as a function of the lower polariton energy for multiple samples which have been used in prior experiments., Comment: 16 pages, 11 figures

The mechanisms that govern a previously unexplained hardening effect of a single phase Cu-30wt%Zn {\alpha}-brass after heating have been investigated. After cold-work, the alloy possesses an increased yield strength and hardening rate only when heat treated to temperatures close to 220{^\circ}C, and is otherwise softer. Crystallographic texture and microstructure, explored using electron backscatter diffraction (EBSD), describe the deformation heterogeneity including twin development, as a function of heat treatment. When heated, an increased area fraction of deformation twins is observed, with dimensions reaching a critical size that maximises the resistance to dislocation slip in the parent grains. The effect is shown to dominate over other alloy characteristics including short range order, giving serrated yielding during tensile testing which is mostly eliminated after heating. In-situ X-ray diffraction during tensile testing corroborates these findings; dislocation-related line broadening and lattice strain development between as worked and heated {\alpha}-brass is directly related to the interaction between the dislocations and the population of deformation twins. The experiments unambiguously disprove that other thermally-induced microstructure features contribute to thermal hardening. Specifically, the presence of recrystallised grains or second phases do not play a role. As these heat treatments match annealing conditions subjected to {\alpha}-brass during deformation-related manufacturing processes, the results here are considered critical to understand, predict and exploit, where appropriate, any beneficial process-induced structural behaviour.

We review approaches to statistical inference based on randomization. Permutation tests are treated as an important special case. Under a certain group invariance property, referred to as the ``randomization hypothesis,'' randomization tests achieve exact control of the Type I error rate in finite samples. Although this unequivocal precision is very appealing, the range of problems that satisfy the randomization hypothesis is somewhat limited. We show that randomization tests are often asymptotically, or approximately, valid and efficient in settings that deviate from the conditions required for finite-sample error control. When randomization tests fail to offer even asymptotic Type 1 error control, their asymptotic validity may be restored by constructing an asymptotically pivotal test statistic. Randomization tests can then provide exact error control for tests of highly structured hypotheses with good performance in a wider class of problems. We give a detailed overview of several prominent applications of randomization tests, including two-sample permutation tests, regression, and conformal inference.

Background: External validations are essential to assess clinical prediction models (CPMs) before deployment. Apart from model misspecification, differences in patient population and other factors influence a model's AUC (c-statistic). We aimed to quantify variation in AUCs across external validation studies and adjust expectations of a model's performance in a new setting. Methods: The Tufts-PACE CPM Registry contains CPMs for cardiovascular disease prognosis. We analyzed the AUCs of 469 CPMs with a total of 1,603 external validations. For each CPM, we performed a random effects meta-analysis to estimate the between-study standard deviation $\tau$ among the AUCs. Since the majority of these meta-analyses has only a handful of validations, this leads to very poor estimates of $\tau$. So, we estimated a log normal distribution of $\tau$ across all CPMs and used this as an empirical prior. We compared this empirical Bayesian approach with frequentist meta-analyses using cross-validation. Results: The 469 CPMs had a median of 2 external validations (IQR: [1-3]). The estimated distribution of $\tau$ had a mean of 0.055 and a standard deviation of 0.015. If $\tau$ = 0.05, the 95% prediction interval for the AUC in a new setting is at least +/- 0.1, regardless of the number of validations. Frequentist methods underestimate the uncertainty about the AUC in a new setting. Accounting for $\tau$ in a Bayesian approach achieved near nominal coverage. Conclusion: Due to large heterogeneity among the validated AUC values of a CPM, there is great irreducible uncertainty in predicting the AUC in a new setting. This uncertainty is underestimated by existing methods. The proposed empirical Bayes approach addresses this problem which merits wide application in judging the validity of prediction models.

Recently, Conditional Neural Fields (NeFs) have emerged as a powerful modelling paradigm for PDEs, by learning solutions as flows in the latent space of the Conditional NeF. Although benefiting from favourable properties of NeFs such as grid-agnosticity and space-time-continuous dynamics modelling, this approach limits the ability to impose known constraints of the PDE on the solutions -- e.g. symmetries or boundary conditions -- in favour of modelling flexibility. Instead, we propose a space-time continuous NeF-based solving framework that - by preserving geometric information in the latent space - respects known symmetries of the PDE. We show that modelling solutions as flows of pointclouds over the group of interest $G$ improves generalization and data-efficiency. We validated that our framework readily generalizes to unseen spatial and temporal locations, as well as geometric transformations of the initial conditions - where other NeF-based PDE forecasting methods fail - and improve over baselines in a number of challenging geometries.

Recently, Neural Fields have emerged as a powerful modelling paradigm to represent continuous signals. In a conditional neural field, a field is represented by a latent variable that conditions the NeF, whose parametrisation is otherwise shared over an entire dataset. We propose Equivariant Neural Fields based on cross attention transformers, in which NeFs are conditioned on a geometric conditioning variable, a latent point cloud, that enables an equivariant decoding from latent to field. Our equivariant approach induces a steerability property by which both field and latent are grounded in geometry and amenable to transformation laws if the field transforms, the latent represents transforms accordingly and vice versa. Crucially, the equivariance relation ensures that the latent is capable of (1) representing geometric patterns faitfhully, allowing for geometric reasoning in latent space, (2) weightsharing over spatially similar patterns, allowing for efficient learning of datasets of fields. These main properties are validated using classification experiments and a verification of the capability of fitting entire datasets, in comparison to other non-equivariant NeF approaches. We further validate the potential of ENFs by demonstrate unique local field editing properties., Comment: Preprint for Neurips submission

The well-known mapping between 1D quasiperiodic systems and 2D integer quantum Hall matter can also be applied in the presence of driving. Here we explore the effect of time-varying electric fields on the transport properties and phase diagram of Harper-Hofstadter materials. We consider light of arbitrary polarization illuminating a 2D electron gas at high magnetic field; this system maps to a 1D quasicrystal subjected to simultaneous phasonic and dipolar driving. We show that this generalized driving generates a tessellated phase diagram featuring a nested duality-protected pattern of metal-insulator transitions. Circularly or elliptically polarized light can create an extended critical phase, opening up a new route to achieving wavefunction multifractality without fine-tuning to a critical point, as well as induce Floquet topological insulators. We describe in detail a path to experimental realization of these phenomena using lattice-trapped ultracold atoms., Comment: Corrected typos. 15 pages, 10 figures including appendices. Comments are welcome!

Regions of magnetic field with near-radial, Parker Spiral-like geometry known as quiescent regions have been observed in Parker Solar Probe data. These regions have very low $\delta B / \langle |B| \rangle$ compared to non-quiescent solar wind at the same heliocentric distances. Quiescent regions are observed to have lower solar wind bulk speeds, lower proton temperatures, and lower proton density, consistent with properties of the slow solar wind. Inside of 15 Rs, identified quiescent regions show distinct thermal properties, having higher proton temperature anisotropies and lower parallel plasma betas compared to switchback patches observed at the same heliocentric distances. When placed on $\mathcal{R}$ vs $\beta_{\parallel p}$ plots (where $\mathcal{R}$ is the proton temperature anisotropy), quiescent region solar wind is shown to be more stable to proton cyclotron and firehose instabilities than non-quiescent solar wind at the same heliocentric distances. It is shown that quiescent regions evolve similarly to the surrounding non-quiescent solar wind, but quiescent solar wind begins at a different location in the $\mathcal{R}$ vs $\beta_{\parallel p}$ parameter space, suggesting that these regions have separate origins than the more turbulent non-quiescent solar wind. Namely, enhanced temperature anisotropies and enhanced magnetic field strength may be consistent with magnetic field lines which have undergone less magnetic field expansion compared to non-quiescent wind at the same heliocentric distances., Comment: 26 pages, 7 figures

Since volcanic activity was first discovered on Io from Voyager images in 1979, changes on Io's surface have been monitored from both spacecraft and ground-based telescopes. Here, we present the highest spatial resolution images of Io ever obtained from a ground-based telescope. These images, acquired by the SHARK-VIS instrument on the Large Binocular Telescope, show evidence of a major resurfacing event on Io's trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images show that a plume deposit from a powerful eruption at Pillan Patera has covered part of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io's surface using adaptive optics at visible wavelengths., Comment: 15 pages, 4 figures

Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators. Unlocking the full potential of such systems toward this goal requires flexible initial state preparation, precise time evolution, and extensive probes for final state characterization. We present a quantum simulator comprising 69 superconducting qubits which supports both universal quantum gates and high-fidelity analog evolution, with performance beyond the reach of classical simulation in cross-entropy benchmarking experiments. Emulating a two-dimensional (2D) XY quantum magnet, we leverage a wide range of measurement techniques to study quantum states after ramps from an antiferromagnetic initial state. We observe signatures of the classical Kosterlitz-Thouless phase transition, as well as strong deviations from Kibble-Zurek scaling predictions attributed to the interplay between quantum and classical coarsening of the correlated domains. This interpretation is corroborated by injecting variable energy density into the initial state, which enables studying the effects of the eigenstate thermalization hypothesis (ETH) in targeted parts of the eigenspectrum. Finally, we digitally prepare the system in pairwise-entangled dimer states and image the transport of energy and vorticity during thermalization. These results establish the efficacy of superconducting analog-digital quantum processors for preparing states across many-body spectra and unveiling their thermalization dynamics.

This comprehensive study investigates charge transport through the multiple end zigzag edge states of finite-size armchair graphene nanoribbons/boron nitride nanoribbons (n-AGNR/w-BNNR) junctions under a longitudinal electric field, where n and w denote the widths of the AGNRs and the BNNRs, respectively. In 13-atom wide AGNR segments, the edge states exhibit a blue Stark shift in response to the electric field, with only the long decay length zigzag edge states showing significant interaction with the red Stark shift subband states. Charge tunneling through such edge states assisted by the subband states is elucidated in the spectra of the transmission coefficient. In the 13-AGNR/6-BNNR heterojunction, notable influences on the energy levels of the end zigzag edge states of 13-AGNRs induced by BNNR segments are observed. We demonstrate the modulation of these energy levels in resonant tunneling situations, as depicted by bias-dependent transmission coefficient spectra. Intriguing nonthermal broadening of tunneling current shows a significant peak-to-valley ratio. Our findings highlight the promising potential of n-AGNR/w-BNNR heterojunctions with long decay length edge states in the realm of GNR-based single electron transistors at room temperature., Comment: In the revised manuscript, we have added new references

We present Einstein coefficient spectra and a detailed-balance derivation of generalized Einstein relations between them that is based on the connection between spontaneous and stimulated emission. If two broadened levels or bands overlap in energy, transitions between them need not be purely absorptive or emissive. Consequently, spontaneous emission can occur in both transition directions, and four Einstein coefficient spectra replace the three Einstein coefficients for a line. At equilibrium, the four different spectra obey five pairwise relationships and one lineshape generates all four. These relationships are independent of molecular quantum statistics and predict the Stokes' shift between forward and reverse transitions required by equilibrium with blackbody radiation. For Boltzmann statistics, the relative strengths of forward and reverse transitions depend on the formal chemical potential difference between the initial and final bands, which becomes the standard chemical potential difference for ideal solutes. The formal chemical potential of a band replaces both the energy and degeneracy of a quantum level. Like the energies of quantum levels, the formal chemical potentials of bands obey the Rydberg-Ritz combination principle. Each stimulated Einstein coefficient spectrum gives a frequency-dependent transition cross section. Transition cross sections obey causality and a detailed-balance condition with spontaneous emission, but do not directly obey generalized Einstein relations. Even with an energetic width much less than the photon energy, an absorptive forward transition with an energetic width much greater than the thermal energy can have such an extreme Stokes' shift that its reverse transition cross section becomes predominantly absorptive rather than emissive., Comment: 15 pages, 4 figures; changed "Bose statistics" to "Bose photon number distribution" and corrected equation in note 38; corrected derivatives to partial derivatives in group velocity and added missing acknowledgment section

Evaluating anomaly detection algorithms in time series data is critical as inaccuracies can lead to flawed decision-making in various domains where real-time analytics and data-driven strategies are essential. Traditional performance metrics assume iid data and fail to capture the complex temporal dynamics and specific characteristics of time series anomalies, such as early and delayed detections. We introduce Proximity-Aware Time series anomaly Evaluation (PATE), a novel evaluation metric that incorporates the temporal relationship between prediction and anomaly intervals. PATE uses proximity-based weighting considering buffer zones around anomaly intervals, enabling a more detailed and informed assessment of a detection. Using these weights, PATE computes a weighted version of the area under the Precision and Recall curve. Our experiments with synthetic and real-world datasets show the superiority of PATE in providing more sensible and accurate evaluations than other evaluation metrics. We also tested several state-of-the-art anomaly detectors across various benchmark datasets using the PATE evaluation scheme. The results show that a common metric like Point-Adjusted F1 Score fails to characterize the detection performances well, and that PATE is able to provide a more fair model comparison. By introducing PATE, we redefine the understanding of model efficacy that steers future studies toward developing more effective and accurate detection models., Comment: Accepted by ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2024), Research Track. (Preprint version)

Multi-wavelength polarimetry and radio observations of Swift J1727.8-1613 at the beginning of its recent 2023 outburst suggested the presence of a bright compact jet aligned in the north-south direction, which could not be confirmed without high angular resolution images. Using the Very Long Baseline Array and the Long Baseline Array, we imaged Swift J1727.8-1613, during the hard/hard-intermediate state, revealing a bright core and a large, two-sided, asymmetrical, resolved jet. The jet extends in the north-south direction, at a position angle of $-0.60\pm0.07\deg$ East of North. At 8.4 GHz, the entire resolved jet structure is $\sim110 (d/2.7\,\text{kpc})/\sin i$ AU long, with the southern approaching jet extending $\sim80 (d/2.7\,\text{kpc})/\sin i$ AU from the core, where $d$ is the distance to the source and $i$ is the inclination of the jet axis to the line of sight. These images reveal the most resolved continuous X-ray binary jet, and possibly the most physically extended continuous X-ray binary jet ever observed. Based on the brightness ratio of the approaching and receding jets, we put a lower limit on the intrinsic jet speed of $\beta\geq0.27$ and an upper limit on the jet inclination of $i\leq74\deg$. In our first observation we also detected a rapidly fading discrete jet knot $66.89\pm0.04$ mas south of the core, with a proper motion of $0.66\pm0.05$ mas hour$^{-1}$, which we interpret as the result of a downstream internal shock or a jet-ISM interaction, as opposed to a transient relativistic jet launched at the beginning of the outburst., Comment: Accepted in ApJL