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Teleoperation enables remote human support of automated vehicles in scenarios where the automation is not able to find an appropriate solution. Remote assistance concepts, where operators provide discrete inputs to aid specific automation modules like planning, is gaining interest due to its reduced workload on the human remote operator and improved safety. However, these concepts are challenging to implement and maintain due to their deep integration and interaction with the automated driving system. In this paper, we propose a solution to facilitate the implementation of remote assistance concepts that intervene on planning level and extend the operational design domain of the vehicle at runtime. Using arbitration graphs, a modular decision-making framework, we integrate remote assistance into an existing automated driving system without modifying the original software components. Our simulative implementation demonstrates this approach in two use cases, allowing operators to adjust planner constraints and enable trajectory generation beyond nominal operational design domains., Comment: 7 pages, 8 figures, handed in for possible publication at IEEE IV 2025, video demonstration available at https://www.youtube.com/watch?v=fVSO-YOeGMk

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai., Comment: 26 pages, 6 figures

Many active galaxies harbor powerful relativistic jets, however, the detailed mechanisms of their formation and acceleration remain poorly understood. To investigate the area of jet acceleration and collimation with the highest available angular resolution, we study the innermost region of the bipolar jet in the nearby low-ionization nuclear emission-line region (LINER) galaxy NGC 1052. We combined observations of NGC 1052 taken with VLBA, GMVA, and EHT over one week in the spring of 2017. For the first time, NGC 1052 was detected with the EHT, providing a size of the central region in-between both jet bases of 250 RS (Schwarzschild radii) perpendicular to the jet axes. This size estimate supports previous studies of the jets expansion profile which suggest two breaks of the profile at around 300 RS and 10000 RS distances to the core. Furthermore, we estimated the magnetic field to be 1.25 Gauss at a distance of 22 {\mu}as from the central engine by fitting a synchrotron-self absorption spectrum to the innermost emission feature, which shows a spectral turn-over at about 130 GHz. Assuming a purely poloidal magnetic field, this implies an upper limit on the magnetic field strength at the event horizon of 26000 Gauss, which is consistent with previous measurements. The complex, low-brightness, double-sided jet structure in NGC 1052 makes it a challenge to detect the source at millimeter (mm) wavelengths. However, our first EHT observations have demonstrated that detection is possible up to at least 230 GHz. This study offers a glimpse through the dense surrounding torus and into the innermost central region, where the jets are formed. This has enabled us to finally resolve this region and provide improved constraints on its expansion and magnetic field strength., Comment: 22 pages, 10 figures, published in A&A

Climate change impacts ecosystems worldwide, affecting animal behaviour and survival both directly and indirectly through changes such as the availability of food. For animals reliant on leaves as a primary food source, understanding how climate change influences leaf production of trees is crucial, yet this is understudied, especially in moist evergreen tropical forests. We analyzed a 23-year dataset of young leaf phenology from a moist tropical forest in Kibale National Park, Uganda, to examine seasonal and long-term patterns of 12 key tree species consumed by folivorous primates. We described phenological patterns and explored relationships between young leaf production of different tree species and climate variables. We also assessed the suitability of the Enhanced Vegetation Index (EVI) as a proxy for young leaf production in moist evergreen tropical forests. Our results showed that tree species exhibited distinct phenological patterns, with most species producing young leaves during two seasonal peaks aligned with the rainy seasons. Rainfall, cloud cover, and maximum temperature were the most informative predictors of seasonal variation in young leaf production. However, solar radiation and atmospheric CO$_2$ were most informative regarding long-term trends. EVI was strongly correlated with young leaf production within years but less effective for capturing inter-annual trends. These findings highlight the complex relationship between climate and young leaf phenology in moist evergreen tropical forests, and helps us understand the changes in food availability for tropical folivores., Comment: 21 pages, 6 figures

The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-K\"onigl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.

Trained neural networks (NN) are attractive as surrogate models to replace costly calculations in physical simulations, but are often unknowingly applied to states not adequately represented in the training dataset. We present the novel technique of soft checksums for scientific machine learning, a general-purpose method to differentiate between trustworthy predictions with small errors on in-distribution (ID) data points, and untrustworthy predictions with large errors on out-of-distribution (OOD) data points. By adding a check node to the existing output layer, we train the model to learn the chosen checksum function encoded within the NN predictions and show that violations of this function correlate with high prediction errors. As the checksum function depends only on the NN predictions, we can calculate the checksum error for any prediction with a single forward pass, incurring negligible time and memory costs. Additionally, we find that incorporating the checksum function into the loss function and exposing the NN to OOD data points during the training process improves separation between ID and OOD predictions. By applying soft checksums to a physically complex and high-dimensional non-local thermodynamic equilibrium atomic physics dataset, we show that a well-chosen threshold checksum error can effectively separate ID and OOD predictions., Comment: 8 pages, 3 figures

The magnetic properties of CrI$_3$ monolayers, which were recently measured, have been investigated considering electronic repulsion and localization effects in Cr 3d orbitals. In this study, we propose a DFT approach using Hubbard U corrections to improve accuracy. We compare the valence density-of-states using the HSE06 hybrid functional and the DFT+U approach, which includes U parameters for both Cr 3d and I 5p orbitals. The results of our study indicate that the optimal values for U(Cr$_{3d}$) and U(I$_{5p}$) are 3.5 eV and 2.0 eV, respectively. This approach is further applied to improve calculations of electronic and magnetic properties in CrI$_3$ monolayers and, more importantly, in bilayers combined with van der Waals functionals. These refinements hold promise for further studies of complex CrI$_3$ nanostructures, and may also be of interest for other trihalide few-layer systems., Comment: 10 pages, 5 figures

This paper introduces an extension to the arbitration graph framework designed to enhance the safety and robustness of autonomous systems in complex, dynamic environments. Building on the flexibility and scalability of arbitration graphs, the proposed method incorporates a verification step and structured fallback layers in the decision-making process. This ensures that only verified and safe commands are executed while enabling graceful degradation in the presence of unexpected faults or bugs. The approach is demonstrated using a Pac-Man simulation and further validated in the context of autonomous driving, where it shows significant reductions in accident risk and improvements in overall system safety. The bottom-up design of arbitration graphs allows for an incremental integration of new behavior components. The extension presented in this work enables the integration of experimental or immature behavior components while maintaining system safety by clearly and precisely defining the conditions under which behaviors are considered safe. The proposed method is implemented as a ready to use header-only C++ library, published under the MIT License. Together with the Pac-Man demo, it is available at github.com/KIT-MRT/arbitration_graphs., Comment: 7 pages, 5 figures, handed in for possible publication at IEEE IV 2025, source code available at github.com/KIT-MRT/arbitration_graphs, v2: Added paragraph discussing the differences between arbitration graphs and behavior trees

Background: Type I X-Ray bursts (XRBs) are energetic stellar explosions that occur on the surface of a neutron star in an accreting binary system with a low-mass H/He-rich companion. The rate of the $^{34}$Ar($\alpha,p$)$^{37}$K reaction may influence features of the light curve that results from the underlying thermonuclear runaway, as shown in recent XRB stellar modelling studies. Purpose: In order to reduce the uncertainty of the rate of this reaction, properties of resonances in the compound nucleus $^{38}$Ca, such as resonance energies, spins, and particle widths, must be well constrained. Method: This work discusses a study of resonances in the $^{38}$Ca compound nucleus produced in the $^{34}$Ar($\alpha,p$) reaction. The experiment was performed at the National Superconducting Cyclotron Laboratory, with the ReA3 facility by measuring proton scattering using an unstable $^{37}$K beam. The kinematics were designed specifically to identify and characterize resonances in the Gamow energy window for the temperature regime relevant to XRBs. Results: The spins and proton widths of newly identified and previously known states in $^{38}$Ca in the energy region of interest for the $^{34}$Ar($\alpha,p$)$^{37}$K reaction have been constrained through an R-Matrix analysis of the scattering data. Conclusions: Using these constraints, a newly estimated rate is applied to an XRB model built using Modules for Experiments in Stellar Astrophysics (MESA), to examine its impact on observables, including the light curve. It is found that the newly determined reaction rate does not substantially affect the features of the light curve.

The precision measurement of the tritium $\beta$-decay spectrum performed by the KATRIN experiment provides a unique way to search for general neutrino interactions (GNI). All theoretical allowed GNI terms involving neutrinos are incorporated into a low-energy effective field theory, and can be identified by specific signatures in the measured tritium $\beta$-spectrum. In this paper an effective description of the impact of GNI on the $\beta$-spectrum is formulated and the first constraints on the effective GNI parameters are derived based on the 4 million electrons collected in the second measurement campaign of KATRIN in 2019. In addition, constraints on selected types of interactions are investigated, thereby exploring the potential of KATRIN to search for more specific new physics cases, including a right-handed W boson, a charged Higgs or leptoquarks.

We present IR photometry and HST imaging and spectroscopy of Sab galaxy NGC 4826. Schwarzschild dynamical modeling is used to measure its central black hole mass $M$. Photometric decomposition is used to enable a comparison of $M$ to published scaling relations between black hole masses and properties of host bulges. This decomposition implies that NGC 4826 contains classical and pseudo bulges of approximately equal mass. The classical bulge has best-fit S\'ersic index $n=3.27$. The pseudobulge is made up of three parts, an inner lens ($n=0.18$ at $r\lesssim4^{\prime\prime}$), an outer lens ($n=0.17$ at $r \lesssim 45^{\prime\prime}$), and a $n=0.58$ component required to match the surface brightness between the lens components. The total $V$-band luminosity of the galaxy is $M_{VT}=-21.07$, the ratio of classical bulge to total light is $B/T\simeq0.12$, and the ratio of pseudobulge to total light is $PB/T\simeq0.13$. The outer disk is exponential ($n=1.07$) and makes up $D/T=0.75$ of the light of the galaxy. Our best-fit Schwarzschild model has a black hole mass with $1\sigma$ uncertainties of $M=8.4^{+1.7}_{-0.6}\times10^6\ M_\odot$ and a stellar $K$-band mass-to-light ratio of $\Upsilon_K=0.46\pm0.03\ M_{\odot}\ \mathrm{L}_{\odot}^{-1}$ at the assumed distance of 7.27 Mpc. Our modeling is marginally consistent with $M=0$ at the $3\sigma$ limit. These best-fit parameters were calculated assuming the black hole is located where the velocity dispersion is largest; this is offset from the maximum surface brightness, probably because of dust absorption. The black hole mass -- one of the smallest measured by modeling stellar dynamics -- satisfies the well known correlations of $M$ with the $K$-band luminosity, stellar mass, and velocity dispersion of the classical bulge only in contrast to total (classical plus pseudo) bulge luminosity., Comment: Accepted by ApJ. 27 or so pages, 18 figures I think. Online data is available at https://doi.org/10.7302/kr8z-fj98

A new image-reconstruction algorithm, PRIMO, applied to the interferometric data of the M87 black hole collected with the Event Horizon Telescope (EHT), resulted in an image that reached the native resolution of the telescope array. PRIMO is based on learning a compact set of image building blocks obtained from a large library of high-fidelity, physics-based simulations of black hole images. It uses these building blocks to fill the sparse Fourier coverage of the data that results from the small number of telescopes in the array. In this paper, we show that this approach is readily justified. Since the angular extent of the image of the black hole and of its inner accretion flow is finite, the Fourier space domain is heavily smoothed, with a correlation scale that is at most comparable to the sizes of the data gaps in the coverage of Fourier space with the EHT. Consequently, PRIMO or other machine-learning algorithms can faithfully reconstruct the images without the need to generate information that is unconstrained by the data within the resolution of the array. We also address the completeness of the eigenimages and the compactness of the resulting representation. We show that PRIMO provides a compact set of eigenimages that have sufficient complexity to recreate a broad set of images well beyond those in the training set., Comment: Submitted to the Astrophysical Journal

Object detectors encounter challenges in handling domain shifts. Cutting-edge domain adaptive object detection methods use the teacher-student framework and domain adversarial learning to generate domain-invariant pseudo-labels for self-training. However, the pseudo-labels generated by the teacher model tend to be biased towards the majority class and often mistakenly include overconfident false positives and underconfident false negatives. We reveal that pseudo-labels vulnerable to adversarial attacks are more likely to be low-quality. To address this, we propose a simple yet effective framework named Adversarial Attacked Teacher (AAT) to improve the quality of pseudo-labels. Specifically, we apply adversarial attacks to the teacher model, prompting it to generate adversarial pseudo-labels to correct bias, suppress overconfidence, and encourage underconfident proposals. An adaptive pseudo-label regularization is introduced to emphasize the influence of pseudo-labels with high certainty and reduce the negative impacts of uncertain predictions. Moreover, robust minority objects verified by pseudo-label regularization are oversampled to minimize dataset imbalance without introducing false positives. Extensive experiments conducted on various datasets demonstrate that AAT achieves superior performance, reaching 52.6 mAP on Clipart1k, surpassing the previous state-of-the-art by 6.7%.

The projected sensitivity of the effective electron neutrino-mass measurement with the KATRIN experiment is below 0.3 eV (90 % CL) after five years of data acquisition. The sensitivity is affected by the increased rate of the background electrons from KATRIN's main spectrometer. A special shifted-analysing-plane (SAP) configuration was developed to reduce this background by a factor of two. The complex layout of electromagnetic fields in the SAP configuration requires a robust method of estimating these fields. We present in this paper a dedicated calibration measurement of the fields using conversion electrons of gaseous $^\mathrm{83m}$Kr, which enables the neutrino-mass measurements in the SAP configuration., Comment: 19 pages, 11 figures

We report the detection of 239 trans-Neptunian Objects discovered through the on-going New Horizons survey for distant minor bodies being performed with the Hyper Suprime-Cam mosaic imager on the Subaru Telescope. These objects were discovered in images acquired with either the r2 or the recently commissioned EB-gri filter using shift and stack routines. Due to the extremely high stellar density of the search region down stream of the spacecraft, new machine learning techniques had to be developed to manage the extremely high false positive rate of bogus candidates produced from the shift and stack routines. We report discoveries as faint as r2$\sim26.5$. We highlight an overabundance of objects found at heliocentric distances $R\gtrsim70$~au compared to expectations from modelling of the known outer Solar System. If confirmed, these objects betray the presence of a heretofore unrecognized abundance of distant objects that can help explain a number of other observations that otherwise remain at odds with the known Kuiper Belt, including detections of serendipitous stellar occultations, and recent results from the Student Dust Counter on-board the New Horizons spacecraft., Comment: Accepted for publication in the Planetary Science Journal, 28 pages, 7 figures, 3 tables

The Chandra Source Catalog (CSC) is a virtual X-ray astrophysics facility that enables both detailed individual source studies and statistical studies of large samples of X-ray sources detected in ACIS and HRC-I imaging observations obtained by the Chandra X-ray Observatory. The catalog provides carefully-curated, high-quality, and uniformly calibrated and analyzed tabulated positional, spatial, photometric, spectral, and temporal source properties, as well as science-ready X-ray data products. The latter includes multiple types of source- and field-based FITS format products that can be used as a basis for further research, significantly simplifying followup analysis of scientifically meaningful source samples. We discuss in detail the algorithms used for the CSC Release 2 Series, including CSC 2.0, which includes 317,167 unique X-ray sources on the sky identified in observations released publicly through the end of 2014, and CSC 2.1, which adds Chandra data released through the end of 2021 and expands the catalog to 407,806 sources. Besides adding more recent observations, the CSC Release 2 Series includes multiple algorithmic enhancements that provide significant improvements over earlier releases. The compact source sensitivity limit for most observations is ~5 photons over most of the field of view, which is ~2x fainter than Release 1, achieved by co-adding observations and using an optimized source detection approach. A Bayesian X-ray aperture photometry code produces robust fluxes even in crowded fields and for low count sources. The current release, CSC 2.1, is tied to the Gaia-CRF3 astrometric reference frame for the best sky positions for catalog sources., Comment: 66 pages, 17 figures, 16 tables, accepted for publication in The Astrophysical Journal Supplement Series

We obtained New Horizons LORRI images to measure the cosmic optical background (COB) intensity integrated over $0.4\lesssim\lambda\lesssim0.9{~\rm\mu m}.$ The survey comprises 16 high Galactic-latitude fields selected to minimize scattered diffuse Galactic light (DGL) from the Milky Way galaxy, as well as scattered light from bright stars. This work supersedes an earlier analysis based on observations of one of the present fields. Isolating the COB contribution to the raw total sky levels measured in the fields requires subtracting the remaining scattered light from bright stars and galaxies, intensity from faint stars within the fields fainter than the photometric detection-limit, and the DGL foreground. DGL is estimated from Planck HFI $350 {~\rm\mu m}$ and $550 {~\rm\mu m}$ intensities, using a new self-calibrated indicator based on the 16 fields augmented with eight additional DGL calibration fields obtained as part of the survey. The survey yields a highly significant detection ($6.8\sigma$) of the COB at ${\rm 11.16\pm 1.65~(1.47~sys,~0.75~ran) ~nW ~m^{-2} ~sr^{-1}}$ at the LORRI pivot wavelength of 0.608 $\mu$m. The estimated integrated intensity from background galaxies, ${\rm 8.17\pm 1.18 ~nW ~m^{-2} ~sr^{-1}},$ can account for the great majority of this signal. The rest of the COB signal, ${\rm 2.99\pm2.03~ (1.75~sys,~1.03~ran) ~nW ~m^{-2} ~sr^{-1}},$ is formally classified as anomalous intensity but is not significantly different from zero. The simplest interpretation is that the COB is completely due to galaxies., Comment: Accepted for publication in the Astrophysical Journal; 30 pages, 14 figures. v3 has updated version of fig 14 to show total error value for Symons et al. 2023 result

The frequency dependence of soil electromagnetic properties contain valuable information of the porous material due to strong contributions to the dielectric relaxation behavior by interactions between aqueous pore solution and mineral phases due to interface effects. Soil hydraulic properties such as matric potential are also influenced by different surface bonding forces due to interface processes. For this reason, a new analysis methodology was developed, which allows a simultaneous determination of the soil water characteristic curve and the dielectric relaxation behavior of undisturbed soil samples. This opens the possibility to systematically analyze coupled hydraulic/dielectric soil properties for the development of pedotransfer functions to estimate physico-chemical parameters with broadband HF-EM measurement techniques., Comment: 2012 IEEE IGARSS

The fact that neutrinos carry a non-vanishing rest mass is evidence of physics beyond the Standard Model of elementary particles. Their absolute mass bears important relevance from particle physics to cosmology. In this work, we report on the search for the effective electron antineutrino mass with the KATRIN experiment. KATRIN performs precision spectroscopy of the tritium $\beta$-decay close to the kinematic endpoint. Based on the first five neutrino-mass measurement campaigns, we derive a best-fit value of $m_\nu^{2} = {-0.14^{+0.13}_{-0.15}}~\mathrm{eV^2}$, resulting in an upper limit of $m_\nu < {0.45}~\mathrm{eV}$ at 90 % confidence level. With six times the statistics of previous data sets, amounting to 36 million electrons collected in 259 measurement days, a substantial reduction of the background level and improved systematic uncertainties, this result tightens KATRIN's previous bound by a factor of almost two., Comment: 61 pages, 20 figures, 2 tables

When using graphs and graph transformations to model systems, consistency is an important concern. While consistency has primarily been viewed as a binary property, i.e., a graph is consistent or inconsistent with respect to a set of constraints, recent work has presented an approach to consistency as a graduated property. This allows living with inconsistencies for a while and repairing them when necessary. For repairing inconsistencies in a graph, we use graph transformation rules with so-called {\em impairment-indicating and repair-indicating application conditions} to understand how much repair gain certain rule applications would bring. Both types of conditions can be derived from given graph constraints. Our main theorem shows that the difference between the number of actual constraint violations before and after a graph transformation step can be characterized by the difference between the numbers of violated impairment-indicating and repair-indicating application conditions. This theory forms the basis for algorithms with look-ahead that rank graph transformations according to their potential for graph repair. An evaluation shows that graph repair can be well supported by rules with these new types of application conditions in terms of effectiveness and scalability., Comment: 46 pages, 24 Figures, new, mor efficient method for constructing application conditions, theoretical comparison to other concepts of consistency, extended evaluation

With growing complexity and criticality of automated driving functions in road traffic and their operational design domains (ODD), there is increasing demand for covering significant proportions of development, validation, and verification in virtual environments and through simulation models. If, however, simulations are meant not only to augment real-world experiments, but to replace them, quantitative approaches are required that measure to what degree and under which preconditions simulation models adequately represent reality, and thus, using their results accordingly. Especially in R&D areas related to the safety impact of the "open world", there is a significant shortage of real-world data to parameterize and/or validate simulations - especially with respect to the behavior of human traffic participants, whom automated driving functions will meet in mixed traffic. We present an approach to systematically acquire data in public traffic by heterogeneous means, transform it into a unified representation, and use it to automatically parameterize traffic behavior models for use in data-driven virtual validation of automated driving functions., Comment: 8 pages, 5 figures

Existing object detectors encounter challenges in handling domain shifts between training and real-world data, particularly under poor visibility conditions like fog and night. Cutting-edge cross-domain object detection methods use teacher-student frameworks and compel teacher and student models to produce consistent predictions under weak and strong augmentations, respectively. In this paper, we reveal that manually crafted augmentations are insufficient for optimal teaching and present a simple yet effective framework named Adversarial Defense Teacher (ADT), leveraging adversarial defense to enhance teaching quality. Specifically, we employ adversarial attacks, encouraging the model to generalize on subtly perturbed inputs that effectively deceive the model. To address small objects under poor visibility conditions, we propose a Zoom-in Zoom-out strategy, which zooms-in images for better pseudo-labels and zooms-out images and pseudo-labels to learn refined features. Our results demonstrate that ADT achieves superior performance, reaching 54.5% mAP on Foggy Cityscapes, surpassing the previous state-of-the-art by 2.6% mAP.

Validating robotic systems in safety-critical appli-cations requires testing in many scenarios including rare edgecases that are unlikely to occur, requiring to complement real-world testing with testing in simulation. Generative models canbe used to augment real-world datasets with generated data toproduce edge case scenarios by sampling in a learned latentspace. Autoencoders can learn said latent representation for aspecific domain by learning to reconstruct the input data froma lower-dimensional intermediate representation. However, theresulting trajectories are not necessarily physically plausible, butinstead typically contain noise that is not present in the inputtrajectory. To resolve this issue, we propose the novel Physics-Informed Trajectory Autoencoder (PITA) architecture, whichincorporates a physical dynamics model into the loss functionof the autoencoder. This results in smooth trajectories that notonly reconstruct the input trajectory but also adhere to thephysical model. We evaluate PITA on a real-world dataset ofvehicle trajectories and compare its performance to a normalautoencoder and a state-of-the-art action-space autoencoder.

Connected automated vehicles (CAV), which incorporate vehicle-to-vehicle (V2V) communication into their motion planning, are expected to provide a wide range of benefits for individual and overall traffic flow. A frequent constraint or required precondition is that compatible CAVs must already be available in traffic at high penetration rates. Achieving such penetration rates incrementally before providing ample benefits for users presents a chicken-and-egg problem that is common in connected driving development. Based on the example of a cooperative driving function for bottleneck traffic flows (e.g. at a roadblock), we illustrate how such an evolutionary, incremental introduction can be achieved under transparent assumptions and objectives. To this end, we analyze the challenge from the perspectives of automation technology, traffic flow, human factors and market, and present a principle that 1) accounts for individual requirements from each domain; 2) provides benefits for any penetration rate of compatible CAVs between 0 % and 100 % as well as upward-compatibility for expected future developments in traffic; 3) can strictly limit the negative effects of cooperation for any participant and 4) can be implemented with close-to-market technology. We discuss the technical implementation as well as the effect on traffic flow over a wide parameter spectrum for human and technical aspects., Comment: 8 pages, 7 figures

The Local Volume Complete Cluster Survey (LoVoCCS) is an on-going program to observe nearly a hundred low-redshift X-ray-luminous galaxy clusters (redshifts $0.0310^{44}$ erg/s) with the Dark Energy Camera (DECam), capturing data in $u,g,r,i,z$ bands with a $5\sigma$ point source depth of approximately 25-26th AB magnitudes. Here, we map the aperture masses in 58 galaxy cluster fields using weak gravitational lensing. These clusters span a variety of dynamical states, from nearly relaxed to merging systems, and approximately half of them have not been subject to detailed weak lensing analysis before. In each cluster field, we analyze the alignment between the 2D mass distribution described by the aperture mass map, the 2D red-sequence (RS) galaxy distribution, and the brightest cluster galaxy (BCG). We find that the orientations of the BCG and the RS distribution are strongly aligned throughout the interiors of the clusters: the median misalignment angle is 19 deg within 2 Mpc. We also observe the alignment between the orientations of the RS distribution and the overall cluster mass distribution (by a median difference of 32 deg within 1 Mpc), although this is constrained by galaxy shape noise and the limitations of our cluster sample size. These types of alignment suggest long-term dynamical evolution within the clusters over cosmic timescales., Comment: 40 pages, 16 figures, 5 tables; revised and accepted for publication in ApJ

Human Digital Twins (HDTs) are a fast-emerging technology with significant potential in fields ranging from healthcare to sports. HDTs extend the traditional understanding of Digital Twins by representing humans as the underlying physical entity. This has introduced several significant challenges, including ambiguity in the definition of HDTs and a lack of guidance for their design. This survey brings together the recent advances in the field of HDTs to guide future developers by proposing a first cross-domain definition of HDTs based on their characteristics, as well as eleven key design considerations that emerge from the associated challenges., Comment: This paper is an extension of the following paper: Lauer-Schmaltz MW, Cash P, Hansen JP, Maier A. Designing Human Digital Twins for Behaviour-Changing Therapy and Rehabilitation: A Systematic Review. Proceedings of the Design Society. 2022;2:1303-1312. doi:10.1017/pds.2022.132

3C84 is a nearby radio source with a complex total intensity structure, showing linear polarisation and spectral patterns. A detailed investigation of the central engine region necessitates the use of VLBI above the hitherto available maximum frequency of 86GHz. Using ultrahigh resolution VLBI observations at the highest available frequency of 228GHz, we aim to directly detect compact structures and understand the physical conditions in the compact region of 3C84. We used EHT 228GHz observations and, given the limited (u,v)-coverage, applied geometric model fitting to the data. We also employed quasi-simultaneously observed, multi-frequency VLBI data for the source in order to carry out a comprehensive analysis of the core structure. We report the detection of a highly ordered, strong magnetic field around the central, SMBH of 3C84. The brightness temperature analysis suggests that the system is in equipartition. We determined a turnover frequency of $\nu_m=(113\pm4)$GHz, a corresponding synchrotron self-absorbed magnetic field of $B_{SSA}=(2.9\pm1.6)$G, and an equipartition magnetic field of $B_{eq}=(5.2\pm0.6)$G. Three components are resolved with the highest fractional polarisation detected for this object ($m_\textrm{net}=(17.0\pm3.9)$%). The positions of the components are compatible with those seen in low-frequency VLBI observations since 2017-2018. We report a steeply negative slope of the spectrum at 228GHz. We used these findings to test models of jet formation, propagation, and Faraday rotation in 3C84. The findings of our investigation into different flow geometries and black hole spins support an advection-dominated accretion flow in a magnetically arrested state around a rapidly rotating supermassive black hole as a model of the jet-launching system in the core of 3C84. However, systematic uncertainties due to the limited (u,v)-coverage, however, cannot be ignored., Comment: 15 pages, 6 figures, published in A&A

Sequential model synchronisation is the task of propagating changes from one model to another correlated one to restore consistency. It is challenging to perform this propagation in a least-changing way that avoids unnecessary deletions (which might cause information loss). From a theoretical point of view, so-called short-cut (SC) rules have been developed that enable provably correct propagation of changes while avoiding information loss. However, to be able to react to every possible change, an infinite set of such rules might be necessary. Practically, only small sets of pre-computed basic SC rules have been used, severely restricting the kind of changes that can be propagated without loss of information. In this work, we close that gap by developing an approach to compute more complex required SC rules on-the-fly during synchronisation. These higher-order SC rules allow us to cope with more complex scenarios when multiple changes must be handled in one step. We implemented our approach in the model transformation tool eMoflon. An evaluation shows that the overhead of computing higher-order SC rules on-the-fly is tolerable and at times even improves the overall performance. Above that, completely new scenarios can be dealt with without the loss of information.

The acceptor removal phenomenon (ARP), which hampers the functionality of low-gain avalanche detectors (LGAD), is discussed in frame of the A_Si-Si_i-defect model. The assumption of fast diffusion of interstitial silicon is shown to be superfluous for the explanation of the B_Si-Si_i-defect formation under irradiation, particular at very low temperatures. The experimentally observed properties of the ARP are explained by the donor properties of the B_Si-Si_i-defect in its ground state. Additionally, low temperature photoluminescence spectra are reported for quenched boron doped silicon showing so far unidentified PL lines, which change due to well-known light-induced degradation (LID) treatments.

Fixed-frequency superconducting qubits demonstrate remarkable success as platforms for stable and scalable quantum computing. Cross-resonance gates have been the workhorse of fixed-coupling, fixed-frequency superconducting processors, leveraging the entanglement generated by driving one qubit resonantly with a neighbor's frequency to achieve high-fidelity, universal CNOTs. Here, we use on-resonant and off-resonant microwave drives to go beyond cross-resonance, realizing natively interesting two-qubit gates that are not equivalent to CNOTs. In particular, we implement and benchmark native ISWAP, SWAP, $\sqrt{\text{ISWAP}}$, and BSWAP gates. Furthermore, we apply these techniques for an efficient construction of the B-gate: a perfect entangler from which any two-qubit gate can be reached in only two applications. We show these native two-qubit gates are better than their counterparts compiled from cross-resonance gates. We elucidate the resonance conditions required to drive each two-qubit gate and provide a novel frame tracking technique to implement them in Qiskit., Comment: added new section, more data, improved presentation

The Event Horizon Telescope (EHT) observed in 2017 the supermassive black hole at the center of the Milky Way, Sagittarius A* (Sgr A*), at a frequency of 228.1 GHz ($\lambda$=1.3 mm). The fundamental physics tests that even a single pulsar orbiting Sgr A* would enable motivate searching for pulsars in EHT datasets. The high observing frequency means that pulsars - which typically exhibit steep emission spectra - are expected to be very faint. However, it also negates pulse scattering, an effect that could hinder pulsar detections in the Galactic Center. Additionally, magnetars or a secondary inverse Compton emission could be stronger at millimeter wavelengths than at lower frequencies. We present a search for pulsars close to Sgr A* using the data from the three most-sensitive stations in the EHT 2017 campaign: the Atacama Large Millimeter/submillimeter Array, the Large Millimeter Telescope and the IRAM 30 m Telescope. We apply three detection methods based on Fourier-domain analysis, the Fast-Folding-Algorithm and single pulse search targeting both pulsars and burst-like transient emission; using the simultaneity of the observations to confirm potential candidates. No new pulsars or significant bursts were found. Being the first pulsar search ever carried out at such high radio frequencies, we detail our analysis methods and give a detailed estimation of the sensitivity of the search. We conclude that the EHT 2017 observations are only sensitive to a small fraction ($\lesssim$2.2%) of the pulsars that may exist close to Sgr A*, motivating further searches for fainter pulsars in the region., Comment: 33 pages, 7 figures, 6 Tables. Accepted for publication in ApJ

Model-driven software engineering is a suitable method for dealing with the ever-increasing complexity of software development processes. Graphs and graph transformations have proven useful for representing such models and changes to them. These models must satisfy certain sets of constraints. An example are the multiplicities of a class structure. During the development process, a change to a model may result in an inconsistent model that must at some point be repaired. This problem is called model repair. In particular, we will consider rule-based graph repair which is defined as follows: Given a graph $G$, a constraint $c$ such that $G$ does not satisfy $c$, and a set of rules $R$, use the rules of $\mathcal{R}$ to transform $G$ into a graph that satisfies $c$. Known notions of consistency have either viewed consistency as a binary property, either a graph is consistent w.r.t. a constraint $c$ or not, or only viewed the number of violations of the first graph of a constraint. In this thesis, we introduce new notions of consistency, which we call consistency-maintaining and consistency-increasing transformations and rules, respectively. This is based on the possibility that a constraint can be satisfied up to a certain nesting level. We present constructions for direct consistency-maintaining or direct consistency-increasing application conditions, respectively. Finally, we present an rule-based graph repair approach that is able to repair so-called \emph{circular conflict-free constraints}, and so-called circular conflict-free sets of constraints. Intuitively, a set of constraint $C$ is circular conflict free, if there is an ordering $c_1, \ldots, c_n$ of all constraints of $C$ such that there is no $j

We present the final legacy version of stellar photometry for the Panchromatic Hubble Andromeda Treasury (PHAT) survey. We have reprocessed all of the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) and Advanced Camera for Surveys (ACS) near ultraviolet (F275W, F336W), optical (F475W, F814W), and near infrared (F110W, F160W) imaging from the PHAT survey using an improved method that optimized the survey depth and chip gap coverage by including all overlapping exposures in all bands in the photometry. An additional improvement was gained through the use of charge transfer efficiency (CTE) corrected input images, which provide more complete star finding as well as more reliable photometry for the NUV bands, which had no CTE correction in the previous version of the PHAT photometry. While this method requires significantly more computing resources and time than earlier versions where the photometry was performed on individual pointings, it results in smaller systematic instrumental completeness variations as demonstrated by cleaner maps in stellar density, and it results in optimal constraints on stellar fluxes in all bands from the survey data. Our resulting catalog has 138 million stars, 18% more than the previous catalog, with lower density regions gaining as much as 40% more stars. The new catalog produces nearly seamless population maps which show relatively well-mixed distributions for populations associated with ages older than 1-2 Gyr, and highly structured distributions for the younger populations., Comment: 28 pages, 4 tables, 18 figures, accepted for publication in The Astrophysical Journal Supplement Series

The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifying behavior analysis is often challenging without deep understanding of animal behavior and technical machine learning knowledge. To limit this gap, we introduce AmadeusGPT: a natural language interface that turns natural language descriptions of behaviors into machine-executable code. Large-language models (LLMs) such as GPT3.5 and GPT4 allow for interactive language-based queries that are potentially well suited for making interactive behavior analysis. However, the comprehension capability of these LLMs is limited by the context window size, which prevents it from remembering distant conversations. To overcome the context window limitation, we implement a novel dual-memory mechanism to allow communication between short-term and long-term memory using symbols as context pointers for retrieval and saving. Concretely, users directly use language-based definitions of behavior and our augmented GPT develops code based on the core AmadeusGPT API, which contains machine learning, computer vision, spatio-temporal reasoning, and visualization modules. Users then can interactively refine results, and seamlessly add new behavioral modules as needed. We benchmark AmadeusGPT and show we can produce state-of-the-art performance on the MABE 2022 behavior challenge tasks. Note, an end-user would not need to write any code to achieve this. Thus, collectively AmadeusGPT presents a novel way to merge deep biological knowledge, large-language models, and core computer vision modules into a more naturally intelligent system. Code and demos can be found at: https://github.com/AdaptiveMotorControlLab/AmadeusGPT., Comment: demo available https://github.com/AdaptiveMotorControlLab/AmadeusGPT

Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated significant impact in various domains including traffic management, urban planning, and health sciences. In this paper, we present the emerging domain of mobility data science. Towards a unified approach to mobility data science, we envision a pipeline having the following components: mobility data collection, cleaning, analysis, management, and privacy. For each of these components, we explain how mobility data science differs from general data science, we survey the current state of the art and describe open challenges for the research community in the coming years., Comment: Updated to reflect the major revision for ACM Transactions on Spatial Algorithms and Systems (TSAS). This version reflects the final version accepted by ACM TSAS

We present a new reconstruction of the Event Horizon Telescope (EHT) image of the M87 black hole from the 2017 data set. We use PRIMO, a novel dictionary-learning based algorithm that uses high-fidelity simulations of accreting black holes as a training set. By learning the correlations between the different regions of the space of interferometric data, this approach allows us to recover high-fidelity images even in the presence of sparse coverage and reach the nominal resolution of the EHT array. The black hole image comprises a thin bright ring with a diameter of $41.5\pm0.6\,\mu$as and a fractional width that is at least a factor of two smaller than previously reported. This improvement has important implications for measuring the mass of the central black hole in M87 based on the EHT images., Comment: 7 pages, 5 figures

The High-Altitude Water Cherenkov (HAWC) observatory is a second-generation continuously operated, wide field-of-view, TeV gamma-ray observatory. The HAWC observatory and its analysis techniques build on experience of the Milagro experiment in using ground-based water Cherenkov detectors for gamma-ray astronomy. HAWC is located on the Sierra Negra volcano in M\'exico at an elevation of 4100 meters above sea level. The completed HAWC observatory principal detector (HAWC) consists of 300 closely spaced water Cherenkov detectors, each equipped with four photomultiplier tubes to provide timing and charge information to reconstruct the extensive air shower energy and arrival direction. The HAWC observatory has been optimized to observe transient and steady emission from sources of gamma rays within an energy range from several hundred GeV to several hundred TeV. However, most of the air showers detected are initiated by cosmic rays, allowing studies of cosmic rays also to be performed. This paper describes the characteristics of the HAWC main array and its hardware., Comment: Accepted for publications in Nuclear Inst. and Methods in Physics Research, A (2023) 168253 ( https://www.sciencedirect.com/science/article/abs/pii/S0168900223002437 ); 39 pages, 14 Figures

Interpretation of resolved polarized images of black holes by the Event Horizon Telescope (EHT) requires predictions of the polarized emission observable by an Earth-based instrument for a particular model of the black hole accretion system. Such predictions are generated by general relativistic radiative transfer (GRRT) codes, which integrate the equations of polarized radiative transfer in curved spacetime. A selection of ray-tracing GRRT codes used within the EHT collaboration is evaluated for accuracy and consistency in producing a selection of test images, demonstrating that the various methods and implementations of radiative transfer calculations are highly consistent. When imaging an analytic accretion model, we find that all codes produce images similar within a pixel-wise normalized mean squared error (NMSE) of 0.012 in the worst case. When imaging a snapshot from a cell-based magnetohydrodynamic simulation, we find all test images to be similar within NMSEs of 0.02, 0.04, 0.04, and 0.12 in Stokes I, Q, U , and V respectively. We additionally find the values of several image metrics relevant to published EHT results to be in agreement to much better precision than measurement uncertainties., Comment: Accepted for publication in ApJ

This paper extends standard results from learning theory with independent data to sequences of dependent data. Contrary to most of the literature, we do not rely on mixing arguments or sequential measures of complexity and derive uniform risk bounds with classical proof patterns and capacity measures. In particular, we show that the standard classification risk bounds based on the VC-dimension hold in the exact same form for dependent data, and further provide Rademacher complexity-based bounds, that remain unchanged compared to the standard results for the identically and independently distributed case. Finally, we show how to apply these results in the context of scenario-based optimization in order to compute the sample complexity of random programs with dependent constraints.

This paper deals with the scenario approach to robust optimization. This relies on a random sampling of the possibly infinite number of constraints induced by uncertainties in the parameters of an optimization problem. Solving the resulting random program yields a solution for which the quality is measured in terms of the probability of violating the constraints for a random value of the uncertainties, typically unseen before. Another central issue is the determination of the sample complexity, i.e., the number of random constraints (or scenarios) that one must consider in order to guarantee a certain level of reliability. In this paper, we introduce the notion of margin to improve upon standard results in this field. In particular, using tools from statistical learning theory, we show that the sample complexity of a class of random programs does not explicitly depend on the number of variables. In addition, within the considered class, that includes polynomial constraints among others, this result holds for both convex and nonconvex instances with the same level of guarantees. We also derive a posteriori bounds on the probability of violation and sketch a regularization approach that could be used to improve the reliability of computed solutions on the basis of these bounds.

In order to protect vulnerable road users (VRUs), such as pedestrians or cyclists, it is essential that intelligent transportation systems (ITS) accurately identify them. Therefore, datasets used to train perception models of ITS must contain a significant number of vulnerable road users. However, data protection regulations require that individuals are anonymized in such datasets. In this work, we introduce a novel deep learning-based pipeline for face anonymization in the context of ITS. In contrast to related methods, we do not use generative adversarial networks (GANs) but build upon recent advances in diffusion models. We propose a two-stage method, which contains a face detection model followed by a latent diffusion model to generate realistic face in-paintings. To demonstrate the versatility of anonymized images, we train segmentation methods on anonymized data and evaluate them on non-anonymized data. Our experiment reveal that our pipeline is better suited to anonymize data for segmentation than naive methods and performes comparably with recent GAN-based methods. Moreover, face detectors achieve higher mAP scores for faces anonymized by our method compared to naive or recent GAN-based methods., Comment: 6 pages, 5 figures

MACS0647$-$JD is a triply-lensed $z\sim11$ galaxy originally discovered with the Hubble Space Telescope. Here we report new JWST imaging, which clearly resolves MACS0647$-$JD as having two components that are either merging galaxies or stellar complexes within a single galaxy. Both are very small, with stellar masses $\sim10^8\,M_\odot$ and radii $r<100\,\rm pc$. The brighter larger component "A" is intrinsically very blue ($\beta\sim-2.6$), likely due to very recent star formation and no dust, and is spatially extended with an effective radius $\sim70\,\rm pc$. The smaller component "B" appears redder ($\beta\sim-2$), likely because it is older ($100-200\,\rm Myr$) with mild dust extinction ($A_V\sim0.1\,\rm mag$), and a smaller radius $\sim20\,\rm pc$. We identify galaxies with similar colors in a high-redshift simulation, finding their star formation histories to be out of phase. With an estimated stellar mass ratio of roughly 2:1 and physical projected separation $\sim400\,\rm pc$, we may be witnessing a galaxy merger 400 million years after the Big Bang. We also identify a candidate companion galaxy C $\sim3\,{\rm kpc}$ away, likely destined to merge with galaxies A and B. The combined light from galaxies A+B is magnified by factors of $\sim$8, 5, and 2 in three lensed images JD1, 2, and 3 with F356W fluxes $\sim322$, $203$, $86\,\rm nJy$ (AB mag 25.1, 25.6, 26.6). MACS0647$-$JD is significantly brighter than other galaxies recently discovered at similar redshifts with JWST. Without magnification, it would have AB mag 27.3 ($M_{UV}=-20.4$). With a high confidence level, we obtain a photometric redshift of $z=10.6\pm0.3$ based on photometry measured in 6 NIRCam filters spanning $1-5\rm\mu m$, out to $4300\,\r{A}$ rest-frame. JWST NIRSpec observations planned for January 2023 will deliver a spectroscopic redshift and a more detailed study of the physical properties of MACS0647$-$JD., Comment: 27 pages, 14 figures, accepted for publication in ApJL

Superconducting qubit lifetimes must be both long and stable to provide an adequate foundation for quantum computing. This stability is imperiled by two-level systems (TLSs), currently a dominant loss mechanism, which exhibit slow spectral dynamics that destabilize qubit lifetimes on hour timescales. Stability is also threatened at millisecond timescales, where ionizing radiation has recently been found to cause bursts of correlated multi-qubit decays, complicating quantum error correction. Here we study both ionizing radiation and TLS dynamics on a 27-qubit processor, repurposing the standard transmon qubits as sensors of both radiation impacts and TLS dynamics. Unlike prior literature, we observe resilience of the qubit lifetimes to the transient quasiparticles generated by the impact of radiation. However, we also observe a new interaction between these two processes, "TLS scrambling," in which a radiation impact causes multiple TLSs to jump in frequency, which we suggest is due to the same charge rearrangement sensed by qubits near a radiation impact. As TLS scrambling brings TLSs out of or in to resonance with the qubit, the lifetime of the qubit increases or decreases. Our findings thus identify radiation as a new contribution to fluctuations in qubit lifetimes, with implications for efforts to characterize and improve device stability, Comment: 14 pages, 10 figures

The sparse interferometric coverage of the Event Horizon Telescope (EHT) poses a significant challenge for both reconstruction and model fitting of black-hole images. PRIMO is a new principal components analysis-based algorithm for image reconstruction that uses the results of high-fidelity general relativistic, magnetohydrodynamic simulations of low-luminosity accretion flows as a training set. This allows the reconstruction of images that are both consistent with the interferometric data and that live in the space of images that is spanned by the simulations. PRIMO follows Monte Carlo Markov Chains to fit a linear combination of principal components derived from an ensemble of simulated images to interferometric data. We show that PRIMO can efficiently and accurately reconstruct synthetic EHT data sets for several simulated images, even when the simulation parameters are significantly different from those of the image ensemble that was used to generate the principal components. The resulting reconstructions achieve resolution that is consistent with the performance of the array and do not introduce significant biases in image features such as the diameter of the ring of emission., Comment: Accepted to ApJ on Dec. 12, 2022, 23 pages, 19 figures, replaced with accepted version

The New Horizons spacecraft returned images and compositional data showing that terrains on Pluto span a variety of ages, ranging from relatively ancient, heavily cratered areas to very young surfaces with few-to-no impact craters. One of the regions with very few impact craters is dominated by enormous rises with hummocky flanks. Similar features do not exist anywhere else in the imaged solar system. Here we analyze the geomorphology and composition of the features and conclude this region was resurfaced by cryovolcanic processes, of a type and scale so far unique to Pluto. Creation of this terrain requires multiple eruption sites and a large volume of material (>104 km^3) to form what we propose are multiple, several-km-high domes, some of which merge to form more complex planforms. The existence of these massive features suggests Pluto's interior structure and evolution allows for either enhanced retention of heat or more heat overall than was anticipated before New Horizons, which permitted mobilization of water-ice-rich materials late in Pluto's history., Comment: 22 pages, including both main paper and supplement as one pdf

For many applications, analyzing the uncertainty of a machine learning model is indispensable. While research of uncertainty quantification (UQ) techniques is very advanced for computer vision applications, UQ methods for spatio-temporal data are less studied. In this paper, we focus on models for online handwriting recognition, one particular type of spatio-temporal data. The data is observed from a sensor-enhanced pen with the goal to classify written characters. We conduct a broad evaluation of aleatoric (data) and epistemic (model) UQ based on two prominent techniques for Bayesian inference, Stochastic Weight Averaging-Gaussian (SWAG) and Deep Ensembles. Next to a better understanding of the model, UQ techniques can detect out-of-distribution data and domain shifts when combining right-handed and left-handed writers (an underrepresented group).

Clouds play a key role in regulating climate change but are difficult to simulate within Earth system models (ESMs). Improving the representation of clouds is one of the key tasks towards more robust climate change projections. This study introduces a new machine-learning based framework relying on satellite observations to improve understanding of the representation of clouds and their relevant processes in climate models. The proposed method is capable of assigning distributions of established cloud types to coarse data. It facilitates a more objective evaluation of clouds in ESMs and improves the consistency of cloud process analysis. The method is built on satellite data from the MODIS instrument labelled by deep neural networks with cloud types defined by the World Meteorological Organization (WMO), using cloud type labels from CloudSat as ground truth. The method is applicable to datasets with information about physical cloud variables comparable to MODIS satellite data and at sufficiently high temporal resolution. We apply the method to alternative satellite data from the Cloud\_cci project (ESA Climate Change Initiative), coarse-grained to typical resolutions of climate models. The resulting cloud type distributions are physically consistent and the horizontal resolutions typical of ESMs are sufficient to apply our method. We recommend outputting crucial variables required by our method for future ESM data evaluation. This will enable the use of labelled satellite data for a more systematic evaluation of clouds in climate models., Comment: Main Paper 16 pages, 11 figures. Supporting material 7 Pages, 8 figures. This work has been submitted to the IEEE for possible publication

Quantification of behavior is critical in applications ranging from neuroscience, veterinary medicine and animal conservation efforts. A common key step for behavioral analysis is first extracting relevant keypoints on animals, known as pose estimation. However, reliable inference of poses currently requires domain knowledge and manual labeling effort to build supervised models. We present a series of technical innovations that enable a new method, collectively called SuperAnimal, to develop unified foundation models that can be used on over 45 species, without additional human labels. Concretely, we introduce a method to unify the keypoint space across differently labeled datasets (via our generalized data converter) and for training these diverse datasets in a manner such that they don't catastrophically forget keypoints given the unbalanced inputs (via our keypoint gradient masking and memory replay approaches). These models show excellent performance across six pose benchmarks. Then, to ensure maximal usability for end-users, we demonstrate how to fine-tune the models on differently labeled data and provide tooling for unsupervised video adaptation to boost performance and decrease jitter across frames. If the models are fine-tuned, we show SuperAnimal models are 10-100$\times$ more data efficient than prior transfer-learning-based approaches. We illustrate the utility of our models in behavioral classification in mice and gait analysis in horses. Collectively, this presents a data-efficient solution for animal pose estimation., Comment: Models and demos available at http://modelzoo.deeplabcut.org

A near surface thermal model for Arrokoth is developed based on the recently released $10^5$ facet model of the body. This thermal solution takes into account Arrokoth's surface re-radiation back onto itself. The solution method exploits Arrokoth's periodic orbital character to develop a thermal response using a time-asymptotic solution method, which involves a Fourier transform solution of the heat equation, an approach recently used by others. We display detailed thermal solutions assuming that Arrokoth's near surface material's thermal inertia ${\cal I} = $ 2.5 W/m$^{-2}$K$^{-1}$s$^{1/2}$. We predict that at New Horizons' encounter with Arrokoth its encounter hemisphere surface temperatures were $\sim$ 57-59 K in its polar regions, 30-40 K on its equatorial zones, and 11-13 K for its winter hemisphere. Arrokoth's orbitally averaged temperatures are around 30-35 K in its polar regions, and closer to 40 K near its equatorial zones. Thermal reradiation from the surrounding surface amounts to less than 5\% of the total energy budget, while the total energy ensconced into and exhumed out Arrokoth's interior via thermal conduction over one orbit is about 0.5\% of the total energy budget. As a generalized application of this thermal modeling together with other KBO origins considerations, we favor the interpretation that New Horizons' REX instrument's $29 \pm 5$K brightness temperature measurement is consistent with Arrokoth's near surface material's being made of sub-to-few mm sized tholin-coated amorphous \water ice grains with 1 W/m$^{-2}$K$^{-1}$s$^{1/2}$ $< {\cal I} < $10-20 W/m$^{-2}$K$^{-1}$s$^{1/2}$, and which are characterized by an X-band emissivity in the range 0.9 and 1., Comment: Accepted on Feb. 21, 2022 for publication in Planetary Science Journal (PSJ)