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There are currently no psychometrically valid tools to measure the perceived danger of robots. To fill this gap, we provided a definition of perceived danger and developed and validated a 12-item bifactor scale through four studies. An exploratory factor analysis revealed four subdimensions of perceived danger: affective states, physical vulnerability, ominousness, and cognitive readiness. A confirmatory factor analysis confirmed the bifactor model. We then compared the perceived danger scale to the Godspeed perceived safety scale and found that the perceived danger scale is a better predictor of empirical data. We also validated the scale in an in-person setting and found that the perceived danger scale is sensitive to robot speed manipulations, consistent with previous empirical findings. Results across experiments suggest that the perceived danger scale is reliable, valid, and an adequate predictor of both perceived safety and perceived danger in human-robot interaction contexts., Comment: 9 pages, 2 figures, to be published in the Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction (HRI)

Eastern Boundary Upwelling Systems (EBUS) are characterized by wind-triggered upwelling of deep waters along the coast. They are hotspots of biological productivity and diversity and therefore have a high economic, ecological and social importance. In the past, different methods using surface data have been used to estimate upwelling. Recently, the IPCC has suggested directly assessing vertical velocities as a promising method. We use this method to study the two Atlantic EBUS from CMIP6 models from the HadGEM3-GC3.1 and the CNRM6-CM6 family, for both the historical period and a high-emission future scenario with spatial resolutions in the ocean component ranging from 1{\deg}to 1/12{\deg}. The two major upwelling regions are divided in subregions depending on their seasonality. The vertical transport index shows similar values to a wind-derived Ekman index. Directly evaluating upwelling from transport processes further provides information about the depth of the upwelling, which has previously been identified as an important factor for nutrient availability. We show that depending on the subregion of the upwelling system different cell structures can be seen in terms of depth and distance to the coast of maximum velocities. When looking at possible future changes high interannual variability limits the significance of the trends but could indicate a poleward shift of the upwelling regions.A detailed comparison of the spatial structures and the distinction in subregions is important to explain contradictory trends in previous works.

We present 450$\mu$m and 850$\mu$m James Clerk Maxwell Telescope (JCMT) observations of the Corona Australis (CrA) molecular cloud taken as part of the JCMT Gould Belt Legacy Survey (GBLS). We present a catalogue of 39 starless and protostellar sources, for which we determine source temperatures and masses using SCUBA-2 450$\mu$m/850$\mu$m flux density ratios for sources with reliable 450$\mu$m detections, and compare these to values determined using temperatures measured by the Herschel Gould Belt Survey (HGBS). In keeping with previous studies, we find that SCUBA-2 preferentially detects high-volume-density starless cores, which are most likely to be prestellar (gravitationally bound). We do not observe any anti-correlation between temperature and volume density in the starless cores in our sample. Finally, we combine our SCUBA-2 and Herschel data to perform SED fitting from 160-850$\mu$m across the central Coronet region, thereby measuring dust temperature $T$, dust emissivity index $\beta$ and column density $N({\rm H}_2)$ across the Coronet. We find that $\beta$ varies across the Coronet, particularly measuring $\beta = 1.55 \pm 0.35$ in the colder starless SMM-6 clump to the north of the B star R CrA. This relatively low value of $\beta$ is suggestive of the presence of large dust grains in SMM-6, even when considering the effects of $T-\beta$ fitting degeneracy and $^{12}$CO contamination of SCUBA-2 850$\mu$m data on the measured $\beta$ values., Comment: 27 pages, 18 figures, 4 tables. Accepted for publication in MNRAS

Pre-trained Large Language Models (LLMs) encapsulate large amounts of knowledge and take enormous amounts of compute to train. We make use of this resource, together with the observation that LLMs are able to transfer knowledge and performance from one domain or even modality to another seemingly-unrelated area, to help with multivariate demand time series forecasting. Attention in transformer-based methods requires something worth attending to -- more than just samples of a time-series. We explore different methods to map multivariate input time series into the LLM token embedding space. In particular, our novel multivariate patching strategy to embed time series features into decoder-only pre-trained Transformers produces results competitive with state-of-the-art time series forecasting models. We also use recently-developed weight-based diagnostics to validate our findings.

Active fluids exhibit chaotic flows at low Reynolds number known as active turbulence. Whereas the statistical properties of the chaotic flows are increasingly well understood, the nature of the transition from laminar to turbulent flows as activity increases remains unclear. Here, through simulations of a minimal model of unbounded active nematics, we find that the transition to active turbulence is discontinuous. We show that the transition features a jump in the mean-squared velocity, as well as bistability and hysteresis between laminar and chaotic flows. From distributions of finite-time Lyapunov exponents, we identify the transition at a value $A^*\approx 4900$ of the dimensionless activity number. Below the transition to chaos, we find subcritical bifurcations that feature bistability of different laminar patterns. These bifurcations give rise to oscillations and to chaotic transients, which become very long close to the transition to turbulence. Overall, our findings contrast with the continuous transition to turbulence in channel confinement, where turbulent puffs emerge within a laminar background. We propose that, without confinement, the long-range hydrodynamic interactions of Stokes flow suppress the spatial coexistence of different flow states, and thus render the transition discontinuous.

Upon their evaporation via Hawking radiation, primordial black holes (PBHs) may deposit energy in the ambient plasma on scales smaller than the typical distance between two black holes, leading to the formation of hot spots around them. We investigate how the corresponding rise of the local temperature during the evaporation may act as a shield against the release of low-energy photons, affecting PBH's capacity to dissociate light nuclei after Big-Bang Nucleosynthesis through photo-dissociation. We study the different ways PBH hot spots affect the flux of low-energy photons expected from PBH evaporation, and we find that such effects can be particularly relevant to the physics of photo-dissociation during Big-Bang Nucleosynthesis for PBHs with masses between $10^{11}$g and $3\times 10^{12}$g. We emphasize that the magnitude of this effect is highly dependent on the specific shape of the temperature profile around PBHs and its time evolution. This underscores the necessity for a comprehensive study of PBH hot spots and their dynamics in the future., Comment: 10 pages, 3 figures

We study the interaction of two massive particles with a quantised gravitational field in its vacuum state using two different position observables: (i) a frame-dependent coordinate separation and (ii) a frame-independent geodesic separation. For free particles, (i) leads to purely unitary dynamics but (ii) leads to dissipation. For two particles coupled through a linear spring, (i) and (ii) lead to different cut-off dependences in the frequency shift harmonic ladder of the differential motional mode. Our findings highlight the subtle consequences of different position observables at the interface of quantum mechanics and gravity., Comment: 6 pages, 2 figures

Here, for $W$ the Coxeter group $\mathrm{D}_n$ where $n > 4$, it is proved that the maximal rank of an abstract regular polytope for $W$ is $n - 1$ if $n$ is even and $n$ if $n$ is odd. Further it is shown that $W$ has abstract regular polytopes of rank $r$ for all $r$ such that $3 \leq r \leq n - 1$, if $n$ is even, and $3 \leq r \leq n$, if $n$ is odd. The possible ranks of abstract regular polytopes for the exceptional finite irreducible Coxeter groups are also determined.

We perform a detailed study of the gravitational tidal Love numbers of extremal zero-temperature Kerr black holes. These coefficients are finite and exhibit the dissipative nature of these maximally spinning black holes. Upon considering the dynamical behavior of the tidal deformations of the extremal Kerr black holes, we provide explicit expressions of the Love numbers at low frequencies. Their calculation is simplified to specific formulas, which are directly derived using the Leaver-MST methods., Comment: 22 pages, 2 figures

The Herzberg Extensible Adaptive optics Real-Time Toolkit (HEART) is a complete framework written in C and Python for building next-generation adaptive optics (AO) system real-time controllers, with the performance needed for extremely large telescopes. With numerous HEART-based RTCs now in their design or build phases, each with different AO algorithms, target hardware, and observatory requirements, continuous automated builds and tests are a cornerstone of our development effort. In this paper we describe the many levels of testing that we perform, from low-level unit tests of individual functions, to more complex component and system-level tests that verify both numerical correctness and execution performance. Incorporating extensive testing into HEART since its inception has allowed us to continuously (and confidently) refactor and extend it to both meet the changing needs of local on-sky experiments, as well as those of the several major facility instruments that we are developing., Comment: 15 pages, 7 figures, SPIE (2024) 13101-130

Monitoring animal populations is crucial for assessing the health of ecosystems. Traditional methods, which require extensive fieldwork, are increasingly being supplemented by time-lapse camera-trap imagery combined with an automatic analysis of the image data. The latter usually involves some object detector aimed at detecting relevant targets (commonly animals) in each image, followed by some postprocessing to gather activity and population data. In this paper, we show that the performance of an object detector in a single frame of a time-lapse sequence can be improved by including spatio-temporal features from the prior frames. We propose a method that leverages temporal information by integrating two additional spatial feature channels which capture stationary and non-stationary elements of the scene and consequently improve scene understanding and reduce the number of stationary false positives. The proposed technique achieves a significant improvement of 24\% in mean average precision (mAP@0.05:0.95) over the baseline (temporal feature-free, single frame) object detector on a large dataset of breeding tropical seabirds. We envisage our method will be widely applicable to other wildlife monitoring applications that use time-lapse imaging., Comment: 18 pages, 13 figures

The interplay between half-metallic ferromagnetism and spin-orbit coupling within the inversion symmetry-broken structure of half Heuslers provides an ideal platform for various spintronics functionalities. Taking advantage of good lattice matching, it is highly desired to epitaxially integrate promising Heuslers into III-V semiconductor-based devices. PtMnSb is one of the first half Heuslers predicted to be an above-room-temperature half-metal with large spin orbit coupling, however, its half-metallicity and potential as a spintronics material has remained elusive due to lack of high quality samples. Here we demonstrate epitaxial growth of single crystal PtMnSb(001) film on GaSb(001) substrates using molecular beam epitaxy. Direct observation of the band structure via angle-resolved photoemission spectroscopy and many-body perturbation theory within the quasiparticle self-consistent GW approximation (QPGW) reveal that PtMnSb hosts rather a near-halfmetallic state with both spin bands crossing the Fermi level and with high spin polarization over 90%. Temperature dependence of magnetization also shows an anomalous enhancement below 60 K, which can be associated with the development of such a near-half-metallic state at low temperatures. Epitaxial growth of high crystalline PtMnSb on a III-V paves the way for systematic clarification of its spin transport properties with fine-tuning of strain in heterostructure devices., Comment: 20 pages, 6 figures

Cathodoluminescence microscopy is now a well-established and powerful tool for probing the photonic properties of nanoscale materials, but in many cases, nanophotonic materials are easily damaged by the electron-beam doses necessary to achieve reasonable cathodoluminescence signal-to-noise ratios. Two-dimensional materials have proven particularly susceptible to beam-induced modifications, yielding both obstacles to high spatial-resolution measurement and opportunities for beam-induced patterning of quantum photonic systems. Here pan-sharpening techniques are applied to cathodoluminescence microscopy in order to address these challenges and experimentally demonstrate the promise of pan-sharpening for minimally-perturbative high-spatial-resolution spectrum imaging of beam-sensitive materials.

Modern time-series forecasting models often fail to make full use of rich unstructured information about the time series themselves. This lack of proper conditioning can lead to obvious model failures; for example, models may be unaware of the details of a particular product, and hence fail to anticipate seasonal surges in customer demand in the lead up to major exogenous events like holidays for clearly relevant products. To address this shortcoming, this paper introduces a novel forecast post-processor -- which we call LLMForecaster -- that fine-tunes large language models (LLMs) to incorporate unstructured semantic and contextual information and historical data to improve the forecasts from an existing demand forecasting pipeline. In an industry-scale retail application, we demonstrate that our technique yields statistically significantly forecast improvements across several sets of products subject to holiday-driven demand surges., Comment: Presented at NeurIPS Time Series in the Age of Large Models (2024)

The CHaracterising ExOPlanet Satellite (CHEOPS) is a partnership between the European Space Agency and Switzerland with important contributions by 10 additional ESA member States. It is the first S-class mission in the ESA Science Programme. CHEOPS has been flying on a Sun-synchronous low Earth orbit since December 2019, collecting millions of short-exposure images in the visible domain to study exoplanet properties. A small yet increasing fraction of CHEOPS images show linear trails caused by resident space objects crossing the instrument field of view. To characterize the population of satellites and orbital debris observed by CHEOPS, all and every science images acquired over the past 3 years have been scanned with a Hough transform algorithm to identify the characteristic linear features that these objects cause on the images. Thousands of trails have been detected. This statistically significant sample shows interesting trends and features such as an increased occurrence rate over the past years as well as the fingerprint of the Starlink constellation. The cross-matching of individual trails with catalogued objects is underway as we aim to measure their distance at the time of observation and deduce the apparent magnitude of the detected objects. As space agencies and private companies are developing new space-based surveillance and tracking activities to catalogue and characterize the distribution of small debris, the CHEOPS experience is timely and relevant. With the first CHEOPS mission extension currently running until the end of 2026, and a possible second extension until the end of 2029, the longer time coverage will make our dataset even more valuable to the community, especially for characterizing objects with recurrent crossings., Comment: 9 pages, 8 figures, Special Issue of the Journal of Space Safety Engineering

AI models are increasingly prevalent in high-stakes environments, necessitating thorough assessment of their capabilities and risks. Benchmarks are popular for measuring these attributes and for comparing model performance, tracking progress, and identifying weaknesses in foundation and non-foundation models. They can inform model selection for downstream tasks and influence policy initiatives. However, not all benchmarks are the same: their quality depends on their design and usability. In this paper, we develop an assessment framework considering 46 best practices across an AI benchmark's lifecycle and evaluate 24 AI benchmarks against it. We find that there exist large quality differences and that commonly used benchmarks suffer from significant issues. We further find that most benchmarks do not report statistical significance of their results nor allow for their results to be easily replicated. To support benchmark developers in aligning with best practices, we provide a checklist for minimum quality assurance based on our assessment. We also develop a living repository of benchmark assessments to support benchmark comparability, accessible at betterbench.stanford.edu., Comment: Accepted as a Spotlight Poster to NeurIPS 2024

Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increasingly relies on computational scale, with recent protein language models (pLM) training on hundreds of graphical processing units (GPUs). We introduce the BioNeMo Framework to facilitate the training of computational biology and chemistry AI models across hundreds of GPUs. Its modular design allows the integration of individual components, such as data loaders, into existing workflows and is open to community contributions. We detail technical features of the BioNeMo Framework through use cases such as pLM pre-training and fine-tuning. On 256 NVIDIA A100s, BioNeMo Framework trains a three billion parameter BERT-based pLM on over one trillion tokens in 4.2 days. The BioNeMo Framework is open-source and free for everyone to use.

Demand forecasting faces challenges induced by Peak Events (PEs) corresponding to special periods such as promotions and holidays. Peak events create significant spikes in demand followed by demand ramp down periods. Neural networks like MQCNN and MQT overreact to demand peaks by carrying over the elevated PE demand into subsequent Post-Peak-Event (PPE) periods, resulting in significantly over-biased forecasts. To tackle this challenge, we introduce a neural forecasting model called Split Peak Attention DEcomposition, SPADE. This model reduces the impact of PEs on subsequent forecasts by modeling forecasting as consisting of two separate tasks: one for PEs; and the other for the rest. Its architecture then uses masked convolution filters and a specialized Peak Attention module. We show SPADE's performance on a worldwide retail dataset with hundreds of millions of products. Our results reveal an overall PPE improvement of 4.5%, a 30% improvement for most affected forecasts after promotions and holidays, and an improvement in PE accuracy by 3.9%, relative to current production models.

We present a new semi-analytical model for the evolution of galaxies and supermassive black holes (SMBHs) that is based on the extended Press-Schechter formalism and phenomenological modelling of star formation. The model yields BH mass-stellar mass relations that reproduce both the JWST and pre-JWST observations. If the efficiency for BH mergers is high the JWST data prefer light seeds while the pre-JWST data prefers heavy seeds. The fit improves for a smaller merger efficiency, $O(0.1)$, for which both data prefer heavy seeds, while also accommodating the PTA GW background data., Comment: 5 pages, 4 figures

The rich diversity of multi-planetary systems and their architectures is greatly contrasted by the uniformity exhibited within many of these systems. Previous studies have shown that compact Kepler systems tend to exhibit a peas-in-a-pod architecture: Planets in the same system tend to have similar sizes and masses and be regularly spaced in orbits with low eccentricities and mutual inclinations. This work extends on previous research and examines a larger and more diverse sample comprising all the systems with a minimum of three confirmed planets, resulting in 282 systems and 991 planets. We investigated the system architectures, focusing on the orbital spacings between adjacent planets as well as their relationships with the planets' sizes and masses. We also quantified the similarities of the sizes, masses, and spacings of planets within each system, conducting both intra- and inter-system analyses. Our results corroborate previous research showing that planets orbiting the same star tend to be regularly spaced and that pairs of adjacent planets with radii<1 R_Earth predominantly have orbital period ratios (PRs)<2. In contrast to other studies, we identified a significant similarity of adjacent orbital spacings not only at PRs<4 but also at 1.17

Achieving the EU's climate neutrality goal requires retrofitting existing buildings to reduce energy use and emissions. A critical step in this process is the precise assessment of geometric building envelope characteristics to inform retrofitting decisions. Previous methods for estimating building characteristics, such as window-to-wall ratio, building footprint area, and the location of architectural elements, have primarily relied on applying deep-learning-based detection or segmentation techniques on 2D images. However, these approaches tend to focus on planar facade properties, limiting their accuracy and comprehensiveness when analyzing complete building envelopes in 3D. While neural scene representations have shown exceptional performance in indoor scene reconstruction, they remain under-explored for external building envelope analysis. This work addresses this gap by leveraging cutting-edge neural surface reconstruction techniques based on signed distance function (SDF) representations for 3D building analysis. We propose BuildNet3D, a novel framework to estimate geometric building characteristics from 2D image inputs. By integrating SDF-based representation with semantic modality, BuildNet3D recovers fine-grained 3D geometry and semantics of building envelopes, which are then used to automatically extract building characteristics. Our framework is evaluated on a range of complex building structures, demonstrating high accuracy and generalizability in estimating window-to-wall ratio and building footprint. The results underscore the effectiveness of BuildNet3D for practical applications in building analysis and retrofitting.

We describe the cryogenic system being developed for Taurus: a super-pressure balloon-borne microwave polarimeter scheduled to fly in 2027. The Taurus cryogenic system consists of a 660L liquid helium cryostat which achieves a base temperature of <100mK with the help of a capillary-fed superfluid tank and a closed cycle dilution refrigerator. The main tank is supported with fiberglass flexures and is encased in two layers of vapor-cooled shields which allow Taurus to make full use of the extended flight time offered by the super-pressure balloon platform. The Taurus cryostat is projected to hold for over 50 days while weighing under 1000lbs. We present the design, testing, and thermal analysis of the Taurus cryogenic systems.

We propose that a dark matter (DM) spike around the Galactic Center's (GC) supermassive black hole, Sgr A*, could account for most of the bulge's measured 511 keV line intensity while remaining cosmologically compatible. DM annihilation can be the primary source of the 511 keV line emission without violating constraints from disk emission observations and in-flight positron annihilation with the interstellar medium, provided the disk emission is dominated by an astrophysical source of low-energy positrons. We find that a DM mass up to approximately 20 MeV, either with a Gondolo-Silk spike or one softened by stellar heating, could explain the observed 511 keV bulge emission profile. Our proposal can be tested by future observations of the continuum diffuse emission close to the GC., Comment: 18 pages of main text containing 7 figures and one table. 3 appendices with other 7 figures

In-falling cosmic dust has left evidence of meteoritic polymer amide in stromatolites, both fossil and modern. In search of evidence for continued present day in-fall sea foam was collected from two beaches in Rhode Island and subjected to Folch extraction to concentrate amphiphilic components in a chloroform water-methanol interphase layer. Hemoglycin polymer amide molecules previously characterized by MALDI mass spectrometry in meteorites and stromatolites were identified in sea foam either directly, or via their fragmentation patterns. Residual isotope enrichment pointed to an extra-terrestrial origin. The unique resiliency of sea foam may be due to the formation of extended hemoglycin lattices that stabilize its closed-cell structure and its lightness can potentially be explained by photolytic hydrogen production., Comment: 32 pages, 11 figures, 4 Tables

Let $f(x)=x^{12}+ax^6+b \in \mathbb{Q}[x]$ be an irreducible polynomial, $g_4(x)=x^4+ax^2+b$, $g_6(x)=x^6+ax^3+b$, and let $G_4$ and $G_6$ be the Galois group of $g_4(x)$ and $g_6(x)$, respectively. We show that $G_6$ can be completely classified by determining whether $3(4b-a^2)$ is a rational square, $b$ is a rational cube, and $x^3-3bx+ab$ is reducible. We also show that the Galois group of $f(x)$ can be uniquely identified by knowing $(G_4,G_6)$ and testing whether at most two expressions involving $a$ and $b$ are rational squares. This gives us an elementary characterization for all sixteen possible Galois groups of $f(x)$.

Calculating the out-of-equilibrium dynamics of many-body quantum systems theoretically is a challenging problem. Essentially exact results can be obtained for the out-of-equilibrium correlations in the Bose-Hubbard model in one dimension, but higher dimensions require approximate methods. One such method is the two-particle irreducible strong coupling (2PISC) approach [M.R.C. Fitzpatrick and M.P. Kennett, Nucl. Phys. B 930, 1 (2018)]. Calculations of the single-particle correlations using this method yield values of the velocity for correlation spreading that match well with exact methods in one dimension and experiments in one and two dimensions. However, the 2PISC method is less accurate for determining the amplitude of correlations, especially in the regime where interactions are not very strong. Viewing the calculation of the single-particle correlations as an image correction problem, we train a neural network (NN) to take input from the 2PISC approach to reproduce the output of exact diagonalization calculations. We show that the predictions of the NN improve on 2PISC results for parameters outside the training region. Our approach is not specific to the Bose-Hubbard model and may find application to the out-of-equilibrium dynamics of other quantum many-body systems., Comment: 12 pages, 16 figures

The X-ray Integral Field Unit (X-IFU) is an instrument of ESA's future NewAthena space observatory, with the goal to provide high-energy resolution ($<$ 4 eV at X-ray energies up to 7 keV) and high-spatial resolution (9") spectroscopic imaging over the X-ray energy range from 200 eV to 12 keV, by means of an array of about 1500 transition-edge sensors (TES) read out via SQUID time-division multiplexing (TDM). A TDM-based laboratory test-bed has been assembled at SRON, hosting an array of $75\times 75\ \upmu$m$^2$ TESs that are read out via 2-column $\times$ 32-row TDM. A system component that is critical to high-performance operation is the wiring harness that connects the room-temperature electronics to the cryogenic readout componentry. We report here on our characterization of such a test-bed, whose harness has a length close to what envisioned for X-IFU, which allowed to achieve a co-added energy resolution at a level of 2.7~eV FWHM at 6~keV via 32-row readout. In addition, we provide an outlook on the integration of TDM readout into the X-IFU Focal-Plane Assembly Development Model., Comment: Submitted for publication to Journal of Astronomical Telescopes, Instrumentation and Systems. arXiv admin note: text overlap with arXiv:2403.02978

Recent James Webb Space Telescope observations of high-redshift massive galaxy candidates have initiated renewed interest in the important mystery around the formation and evolution of our Universe's largest supermassive black holes (SMBHs). We consider the possibility that some of them were seeded by the direct collapse of primordial density perturbations from inflation into primordial black holes and analyze the consequences of this on current dark matter substructures assuming non-Gaussian primordial curvature perturbation distributions. We derive bounds on the enhanced curvature perturbation amplitude from the number of dwarf spheroidal galaxies in our Galaxy, observations of stellar streams and gravitational lensing. We find this bound region significantly overlaps with that required for SMBH seed formation and enables us to probe Gaussian and non-Gaussian curvature perturbations corresponding to the SMBH seeds in the range ${\cal O}(10^5$-$10^{12}) M_\odot$., Comment: 10 pages, 6 figures

Measurements of the obliquities in exoplanet systems have revealed some remarkable architectures, some of which are very different from the Solar System. Nearly 200 obliquity measurements have been obtained through observations of the Rossiter-McLaughlin (RM) effect. Here we report on observations of 19 planetary systems that led to 17 clear detections of the RM effect and 2 less secure detections. After adding the new measurements to the tally, we use the entire collection of RM measurements to investigate four issues that have arisen in the literature. i) Does the obliquity distribution show a peak at approximately 90$^\circ$? We find tentative evidence that such a peak does exist when restricting attention to the sample of sub-Saturn planets and hot Jupiters orbiting F stars. ii) Are high obliquities associated with high eccentricities? We find the association to be weaker than previously reported, and that a stronger association exists between obliquity and orbital separation, possibly due to tidal obliquity damping at small separations. iii) How low are the lowest known obliquities? Among hot Jupiters around cool stars, we find the dispersion to be $1.4\pm0.7^\circ$, smaller than the 6$^\circ$ obliquity of the Sun, which serves as additional evidence for tidal damping. iv) What are the obliquities of stars with compact and flat systems of multiple planets? We find that they generally have obliquities lower than $10^\circ$, with several remarkable exceptions possibly caused by wide-orbiting stellar or planetary companions., Comment: 47 pages, 43 figures. Accepted for publication in A&A

Hot and warm Jupiters might have undergone the same formation and evolution path, but the two populations exhibit different distributions of orbital parameters, challenging our understanding on their actual origin. The present work, which is the results of our warm Jupiters survey carried out with the CHIRON spectrograph within the KESPRINT collaboration, aims to address this challenge by studying two planets that could help bridge the gap between the two populations. We report the confirmation and mass determination of a hot Jupiter (orbital period shorter than 10 days), TOI-2420\,b, and a warm Jupiter, TOI-2485\,b. We performed a joint analysis using a wide variety of spectral and photometric data in order to characterize these planetary systems. We found that TOI-2420\,b has an orbital period of P$_{\rm b}$=5.8 days, a mass of M$_{\rm b}$=0.9 M$_{\rm J}$ and a radius of R$_{\rm b}$=1.3 R$_{\rm J}$, with a planetary density of 0.477 \gc; while TOI-2485\,b has an orbital period of P$_{\rm b}$=11.2 days, a mass of M$_{\rm b}$=2.4 M$_{\rm J}$ and a radius of R$_{\rm b}$=1.1 R$_{\rm J}$ with density 2.36 \gc. With current parameters, the migration history for TOI-2420\,b and TOI-2485\,b is unclear: the high-eccentricity migration scenarios cannot be ruled out, and TOI-2485\,b's characteristics may rather support this scenario.

CXOU J005245.0-722844 is an X-ray source in the Small Magellanic Cloud (SMC) that has long been known as a Be/X-ray binary (BeXRB) star, containing an OBe main sequence star and a compact object. In this paper, we report on a new very fast X-ray outburst from CXOU J005245.0-722844. X-ray observations taken by Swift constrain the duration of the outburst to less than 16 days and find that the source reached super-Eddington X-ray luminosities during the initial phases of the eruption. The XRT spectrum of CXOU J005245.0-722844 during this outburst reveals a super-soft X-ray source, best fit by an absorbed thermal blackbody model. Optical and Ultraviolet follow-up observations from the Optical Gravitational Lensing Experiment (OGLE), Asteroid Terrestrial-impact Last Alert System (ATLAS), and Swift identify a brief ~0.5 magnitude optical burst coincident with the X-ray outburst that lasted for less than 7 days. Optical photometry additionally identifies the orbital period of the system to be 17.55 days and identifies a shortening of the period to 17.14 days in the years leading up to the outburst. Optical spectroscopy from the Southern African Large Telescope (SALT) confirms that the optical companion is an early-type OBe star. We conclude from our observations that the compact object in this system is a white dwarf (WD), making this the seventh candidate Be/WD X-ray binary. The X-ray outburst is found to be the result of a very-fast, ultra-luminous nova similar to the outburst of MAXI J0158-744.

Grant Free Random Access (GFRA) is a popular protocol in the Internet of Things (IoT) to reduce the control signaling. GFRA is a framed protocol where each frame is split into two parts: device identification; and data transmission part which can be viewed as a form of Frame Slotted ALOHA (FSA). A common assumption in FSA is device homogeneity; that is the probability that a device seeks to transmit data in a particular frame is common for all devices and independent of the other devices. Recent work has investigated the possibility of tuning the FSA protocol to the statistics of the network by changing the probability for a particular device to access a particular slot. However, power control with a successive interference cancellation (SIC) receiver has not yet been considered to further increase the performance of the tuned FSA protocols. In this paper, we propose algorithms to jointly optimize both the slot selection and the transmit power of the devices to minimize the outage of the devices in the network. We show via a simulation study that our algorithms can outperform baselines (including slotted ALOHA) in terms of expected number of devices transmitting without outage and in term of transmit power.

Grant-free random access (GFRA) is now a popular protocol for large-scale wireless multiple access systems in order to reduce control signaling. Resource allocation in GFRA can be viewed as a form of frame slotted ALOHA, where a ubiquitous design assumption is device homogeneity. In particular, the probability that a device seeks to transmit data is common to all devices. Recently, there has been an interest in designing frame slotted ALOHA algorithms for networks with heterogeneous activity probabilities. These works have established that the throughput can be significantly improved over the standard uniform allocation. However, the algorithms for optimizing the probability a device accesses each slot require perfect knowledge of the active devices within each frame. In practice, this assumption is limiting as device identification algorithms in GFRA rarely provide activity estimates with zero errors. In this paper, we develop a new algorithm based on stochastic gradient descent for optimizing slot allocation probabilities in the presence of activity estimation errors. Our algorithm exploits importance weighted bias mitigation for stochastic gradient estimates, which is shown to provably converge to a stationary point of the throughput optimization problem. In moderate size systems, our simulations show that the performance of our algorithm depends on the type of error distribution. We study symmetric bit flipping, asymmetric bit flipping and errors resulting from a generalized approximate message passing (GAMP) algorithm. In these scenarios, we observe gains up to 40\%, 66\%, and 19\%, respectively.

Due to its rigid foldability and predictable kinematics, the reverse fold is the fundamental mechanism behind some of the most well known origami kinematic structures, including the Miura Ori, Yoshimura, and waterbomb patterns. However, the reverse fold only has one parameter to control its behavior: the starting fold angle. In this paper I introduce an alternative to the traditional reverse fold, based on the spring into action pattern, called the spring joint. This novel rigidly foldable mechanism is able to couple multiple reverse folds into a compact space to amplify the kinematic output of a traditional reverse fold by up to ten times, and to add one parameter for each reverse fold, giving more programmatic control of origami structures. Methods of parameterizing both the starting angle, the path of travel, and the axis of motion are also introduced. Unfortunately, this versatility comes at the cost of a large buildup of layers, making the spring joint impractical for thick origami mechanisms. To solve this problem, I also introduce a modular alternative to the spring joint that has no additional layers, with the same kinematic properties. Both of these mechanisms are tested as replacements for the reverse fold in both traditional and custom origami structures., Comment: 14 pages, 10 figures

The International Standards Organization (ISO) is developing a new standard for Graph Query Language, with a particular focus on graph patterns with repeating paths. The Linked Database Benchmark Council (LDBC) has developed benchmarks to test proposed implementations. Their Financial Benchmark includes a novel requirement for truncation of results. This paper presents an open-source implementation of the benchmark workloads and truncation., Comment: 5 pages, 4 figures

This paper reviews the changes for database technology represented by the current development of the draft international standard ISO 39075 (Database Languages - GQL), which seeks a unified specification for property graphs and knowledge graphs. This paper examines these current developments as part of our review of the evolution of database technology, and their relation to the longer-term goal of supporting the Semantic Web using relational technology., Comment: 10 pages, 2 figures

Recent standardization work for database languages has reflected the growing use of typed graph models (TGM) in application development. Such data models are frequently only used early in the design process, and not reflected directly in underlying physical database. In previous work, we have added support to a relational database management system (RDBMS) with role-based structures to ensure that relevant data models are not separately declared in each application but are an important part of the database implementation. In this work, we implement this approach for the TGM: the resulting database implementation is novel in retaining the best features of the graph-based and relational database technologies., Comment: 12 pages, 8 figures, 2 tables. arXiv admin note: text overlap with arXiv:2303.12376

We present a method for the computation of the Generalized Alignment Index (GALI), a fast and effective chaos indicator, using a multi-particle approach that avoids variational equations. We show that this approach is robust and accurate by deriving a leading-order error estimation for both the variational (VM) and the multi-particle (MPM) methods, which we validate by performing extensive numerical simulations on two prototypical models: the two degrees of freedom H\'enon-Heiles system and the multidimensional $\beta$-Fermi-Pasta-Ulam-Tsingou chain of oscillators. The dependence of the accuracy of the GALI on control parameters such as the renormalization time, the integration time step and the deviation vector size is studied in detail. We test the MPM implemented with double precision accuracy ($\varepsilon \approx 10^{-16}$) and find that it performs reliably for deviation vector sizes $d_0\approx \varepsilon^{1/2}$, renormalization times $\tau \lesssim 1$, and relative energy errors $E_r \lesssim \varepsilon^{1/2}$. These results hold for systems with many degrees of freedom and demonstrate that the MPM is a robust and efficient method for studying the chaotic dynamics of Hamiltonian systems. Our work makes it possible to explore chaotic dynamics with the GALI in a vast number of systems by eliminating the need for variational equations., Comment: 17 pages, 13 figures, Accepted for publication in Communications in Nonlinear Science and Numerical Simulation

Taurus is a balloon-borne cosmic microwave background (CMB) experiment optimized to map the E-mode polarization and Galactic foregrounds at the largest angular scales ($\ell$ $\lt$ 30) and improve measurements of the optical depth to reionization ($\tau$). This will pave the way for improved measurements of the sum of neutrino masses in combination with high-resolution CMB data while also testing the $\Lambda CDM$ model on large angular scales and providing high-frequency maps of polarized dust foregrounds to the CMB community. These measurements take advantage of the low-loading environment found in the stratosphere and are enabled by NASA's super-pressure balloon platform, which provides access to 70% of the sky with a launch from Wanaka, New Zealand. Here we describe a general overview of Taurus, with an emphasis on the instrument design. Taurus will employ more than 10,000 100 mK transition edge sensor bolometers distributed across two low-frequency (150, 220 GHz) and one high-frequency (280, 350 GHz) dichroic receivers. The liquid helium cryostat housing the detectors and optics is supported by a lightweight gondola. The payload is designed to meet the challenges in mass, power, and thermal control posed by the super-pressure platform. The instrument and scan strategy are optimized for rigorous control of instrumental systematics, enabling high-fidelity linear polarization measurements on the largest angular scales.

Heavy vector boson dark matter at the TeV scale or higher may be produced non-thermally in a first-order phase transition taking place at a lower energy scale. While the production of vector dark matter has previously been studied for bubble wall collisions, here we calculate production by bubble wall expansion in a plasma, which can be the dominant production mechanism. We compute the results numerically and provide an analytical fit for the vector dark matter density. The numerical fit is also validated for scalar dark matter production, obtaining results in agreement with past literature. We find that vector pair production leads to bubble wall friction with a novel boost factor scaling behaviour compared to transition radiation emission of a single vector. We conclude that TeV-scale WIMP vector dark matter can be efficiently produced non-thermally by first-order phase transitions in a wide region of parameter space where thermal freeze-out is inefficient. In this scenario, the phase transition scale is predicted to be in the sub-GeV to $\mathcal{O}(10)$ TeV range and could therefore be accessible to future gravitational wave detectors., Comment: 39 pages, 13 figures