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Proprioceptive sensors on planetary rovers serve for state estimation and for understanding terrain and locomotion performance. While inertial measurement units (IMUs) are widely used to this effect, force-torque sensors are less explored for planetary navigation despite their potential to directly measure interaction forces and provide insights into traction performance. This paper presents an evaluation of the performance and use cases of force-torque sensors based on data collected from a six-wheeled rover during tests over varying terrains, speeds, and slopes. We discuss challenges, such as sensor signal reliability and terrain response accuracy, and identify opportunities regarding the use of these sensors. The data is openly accessible and includes force-torque measurements from each of the six-wheel assemblies as well as IMU data from within the rover chassis. This paper aims to inform the design of future studies and rover upgrades, particularly in sensor integration and control algorithms, to improve navigation capabilities.

Credit card fraud detection is a critical concern for financial institutions, intensified by the rise of contactless payment technologies. While deep learning models offer high accuracy, their lack of explainability poses significant challenges in financial settings. This paper explores the integration of fuzzy logic into Deep Symbolic Regression (DSR) to enhance both performance and explainability in fraud detection. We investigate the effectiveness of different fuzzy logic implications, specifically {\L}ukasiewicz, G\"odel, and Product, in handling the complexity and uncertainty of fraud detection datasets. Our analysis suggest that the {\L}ukasiewicz implication achieves the highest F1-score and overall accuracy, while the Product implication offers a favorable balance between performance and explainability. Despite having a performance lower than state-of-the-art (SOTA) models due to information loss in data transformation, our approach provides novelty and insights into into integrating fuzzy logic into DSR for fraud detection, providing a comprehensive comparison between different implications and methods., Comment: 10 pages, 1 figure, published for XAI FIN 24 https://easychair.org/cfp/xaifin2024

Continuous normalizing flows are known to be highly expressive and flexible, which allows for easier incorporation of large symmetries and makes them a powerful tool for sampling in lattice field theories. Building on previous work, we present a general continuous normalizing flow architecture for matrix Lie groups that is equivariant under group transformations. We apply this to lattice gauge theories in two dimensions as a proof-of-principle and demonstrate competitive performance, showing its potential as a tool for future lattice sampling tasks.

Diffusion generative models transform noise into data by inverting a process that progressively adds noise to data samples. Inspired by concepts from the renormalization group in physics, which analyzes systems across different scales, we revisit diffusion models by exploring three key design aspects: 1) the choice of representation in which the diffusion process operates (e.g. pixel-, PCA-, Fourier-, or wavelet-basis), 2) the prior distribution that data is transformed into during diffusion (e.g. Gaussian with covariance $\Sigma$), and 3) the scheduling of noise levels applied separately to different parts of the data, captured by a component-wise noise schedule. Incorporating the flexibility in these choices, we develop a unified framework for diffusion generative models with greatly enhanced design freedom. In particular, we introduce soft-conditioning models that smoothly interpolate between standard diffusion models and autoregressive models (in any basis), conceptually bridging these two approaches. Our framework opens up a wide design space which may lead to more efficient training and data generation, and paves the way to novel architectures integrating different generative approaches and generation tasks., Comment: 11 pages, 8 figures

Superfast rotators (SFRs) are small solar system objects that rotate faster than generally possible for a cohesionless rubble pile. Their rotational characteristics allow us to make inferences about their interior structure and composition. Here, we present the methods and results from a preliminary search for SFRs in the DECam Ecliptic Exploration Project (DEEP) data set. We find three SFRs from a sample of 686 main-belt asteroids, implying an occurrence rate of 0.4 -0.3/+0.1 percent - a higher incidence rate than has been measured by previous studies. We suggest that this high occurrence rate is due to the small sub-kilometer size regime to which DEEP has access: the objects searched here were as small as 500 m. We compute the minimum required cohesive strength for each of these SFRs and discuss the implications of these strengths in the context of likely evolution mechanisms. We find that all three of these SFRs require strengths that are more than that of weak regolith but consistent with many cohesive asteroid strengths reported in the literature. Across the full DEEP data set, we have identified ~70,000 Main-Belt Asteroids and expect ~300 SFRs - a result that will be assessed in a future paper.

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

Automated drifting presents a challenge problem for vehicle control, requiring models and control algorithms that can precisely handle nonlinear, coupled tire forces at the friction limits. We present a neural network architecture for predicting front tire lateral force as a drop-in replacement for physics-based approaches. With a full-scale automated vehicle purpose-built for the drifting application, we deploy these models in a nonlinear model predictive controller tuned for tracking a reference drifting trajectory, for direct comparisons of model performance. The neural network tire model exhibits significantly improved path tracking performance over the brush tire model in cases where front-axle braking force is applied, suggesting the neural network's ability to express previously unmodeled, latent dynamics in the drifting condition., Comment: 16th International Symposium on Advanced Vehicle Control (AVEC). September 2nd-6th, 2024. Milan, Italy

Automated vehicles need to estimate tire-road friction information, as it plays a key role in safe trajectory planning and vehicle dynamics control. Notably, friction is not solely dependent on road surface conditions, but also varies significantly depending on the tire temperature. However, tire parameters such as the friction coefficient have been conventionally treated as constant values in automated vehicle motion planning. This paper develops a simple thermodynamic model that captures tire friction temperature variation. To verify the model, it is implemented into trajectory planning for automated drifting - a challenging application that requires leveraging an unstable, drifting equilibrium at the friction limits. The proposed method which captures the hidden tire dynamics provides a dynamically feasible trajectory, leading to more precise tracking during experiments with an LQR (Linear Quadratic Regulator) controller., Comment: This manuscript was accepted from IEEE Intelligent Vehicle Symposium (IV 2024) and will be published late August

In this work, we introduce a comprehensive error typology specifically designed for evaluating two distinct tasks in machine-generated patent texts: claims-to-abstract generation, and the generation of the next claim given previous ones. We have also developed a benchmark, PatentEval, for systematically assessing language models in this context. Our study includes a comparative analysis, annotated by humans, of various models. These range from those specifically adapted during training for tasks within the patent domain to the latest general-purpose large language models (LLMs). Furthermore, we explored and evaluated some metrics to approximate human judgments in patent text evaluation, analyzing the extent to which these metrics align with expert assessments. These approaches provide valuable insights into the capabilities and limitations of current language models in the specialized field of patent text generation.

We present two different approaches towards the Landau-Zener problem: (i) The Markov approximation in the integro-differential equation for one of the two probability amplitudes, and (ii) an amplitude-and-phase analysis of the linear second order differential equation for same probability amplitude. Our treatment shows that the Markov approximation neglects the non-linearity of the equation but still provides us with the exact asymptotic result.

Recent observational surveys of the outer Solar System provide evidence that Neptune's distant $n$:1 mean-motion resonances may harbor relatively large reservoirs of trans-Neptunian objects (TNOs). In particular, the discovery of two securely classified 9:1 resonators, 2015 KE$_{172}$ and 2007 TC$_{434}$, by the Outer Solar System Origins Survey is consistent with a population of order $10^4$ such objects in the 9:1 resonance with absolute magnitude $H_r < 8.66$. This work investigates whether the long-term stability of such populations in Neptune's $n$:1 resonances can be used to constrain the existence of distant $5-10M_{\oplus}$ planets orbiting at hundreds of AU. The existence of such a planet has been proposed to explain a reported clustering in the orbits of highly eccentric "extreme" trans-Neptunian objects (eTNOs), although this hypothesis remains controversial. We engage in a focused computational case-study of the 9:1 resonance, generating synthetic populations and integrating them for 1 Gyr in the presence of 81 different test planets with various masses, perihelion distances, eccentricities, and inclinations. While none of the tested planets are incompatible with the existence of 9:1 resonators, our integrations shed light on the character of the interaction between such planets and nearby $n$:1 resonances, and we use this knowledge to construct a simple, heuristic method for determining whether or not a given planet could destabilize a given resonant population. We apply this method to the currently estimated properties of Planet 9, and find that a large primordial population in the 15:1 resonance (or beyond), if discovered in the future, could potentially constrain the existence of this planet., Comment: 20 pages, 16 figures

While drastic improvements in CT technology have occurred in the past 25 years, spatial resolution is one area where progress has been limited until recently. New photon counting CT systems, are capable of much better spatial resolution than their (energy integrating) predecessors. These improvements have the potential to improve the evaluation obstructive coronary artery disease by enabling more accurate delineation between calcified plaque and coronary vessel lumen. A new set of vessel phantoms has been designed and manufactured for quantifying this improvement. Comparisons are made between an existing clinical CT system, a prototype photon counting system, with images from a micro CT system being used as the gold standard. Scans were made of the same objects on all three systems. The resulting images were registered and the luminal cross section areas were compared. Luminal cross-sections near calcified plaques were reduced due to blooming, but this effect was much less pronounced in images from the prototype photon counting system as compared to the images from the clinical CT system.

We present the DECam Ecliptic Exploration Project (DEEP) survey strategy including observing cadence for orbit determination, exposure times, field pointings and filter choices. The overall goal of the survey is to discover and characterize the orbits of a few thousand Trans-Neptunian Objects (TNOs) using the Dark Energy Camera (DECam) on the Cerro Tololo Inter-American Observatory (CTIO) Blanco 4 meter telescope. The experiment is designed to collect a very deep series of exposures totaling a few hours on sky for each of several 2.7 square degree DECam fields-of-view to achieve a magnitude of about 26.2 using a wide VR filter which encompasses both the V and R bandpasses. In the first year, several nights were combined to achieve a sky area of about 34 square degrees. In subsequent years, the fields have been re-visited to allow TNOs to be tracked for orbit determination. When complete, DEEP will be the largest survey of the outer solar system ever undertaken in terms of newly discovered object numbers, and the most prolific at producing multi-year orbital information for the population of minor planets beyond Neptune at 30 au., Comment: 29 pages, 4 figures and 4 tables

Neptune's Trojan asteroids have been observed to have a variety of optical colors, most notably red (g $-$ r < 0.75) vs. ultra-red (g $-$ r > 0.75), but the underlying cause of these different color classifications is unknown. Near-IR spectroscopy can be used as a probe of the surface composition of these objects, as broad ice bands for a variety of materials are present in the near-IR. Here, we present the first results of a spectroscopic survey of Neptune's Trojan asteroids using the NIRSpec instrument on JWST. We compare the near-IR spectra of eight Neptune Trojans (NTs) based on different optical color classifications and with model spectra of different ices. We find that most of our targets are consistent with a surface covered in a thin layer of H$_2$O and CO$_2$ ices, while the only NT to reliably be classified as ultra-red is covered in ice tholins in addition to CO$_2$. Ice tholins are a known reddening agent when subjected to irradiation, so these results support the hypothesis that differences in optical color are due to differences in irradiation of the surfaces of these bodies. Since NTs have very similar orbits and therefore generally similar levels of irradiation at the current time, our results suggest that these objects have unique origins or there is ongoing processing of the surfaces of these objects through stochastic disturbances such as impacts., Comment: 10 pages, 2 figures, Submitted to ApJL

We present the first set of trans-Neptunian objects (TNOs) observed on multiple nights in data taken from the DECam Ecliptic Exploration Project (DEEP). Of these 110 TNOs, 105 do not coincide with previously known TNOs and appear to be new discoveries. Each individual detection for our objects resulted from a digital tracking search at TNO rates of motion, using two to four hour exposure sets, and the detections were subsequently linked across multiple observing seasons. This procedure allows us to find objects with magnitudes $m_{VR} \approx 26$. The object discovery processing also included a comprehensive population of objects injected into the images, with a recovery and linking rate of at least $94\%$. The final orbits were obtained using a specialized orbit fitting procedure that accounts for the positional errors derived from the digital tracking procedure. Our results include robust orbits and magnitudes for classical TNOs with absolute magnitudes $H \sim 10$, as well as a dynamically detached object found at 76 au (semi-major axis $a\approx 77 \, \mathrm{au}$). We find a disagreement between our population of classical TNOs and the CFEPS-L7 three component model for the Kuiper belt., Comment: Accepted to AJ, companion paper do DEEP III. Objects will be released in the journal version (or contacting the authors)

We present a detailed study of the observational biases of the DECam Ecliptic Exploration Project's (DEEP) B1 data release and survey simulation software that enables direct statistical comparisons between models and our data. We inject a synthetic population of objects into the images, and then subsequently recover them in the same processing as our real detections. This enables us to characterize the survey's completeness as a function of apparent magnitudes and on-sky rates of motion. We study the statistically optimal functional form for the magnitude, and develop a methodology that can estimate the magnitude and rate efficiencies for all survey's pointing groups simultaneously. We have determined that our peak completeness is on average 80\% in each pointing group, and our magnitude drops to $25\%$ of this value at $m_{25} = 26.22$. We describe the freely available survey simulation software and its methodology. We conclude by using it to infer that our effective search area for objects at 40 au is $14.8\deg^2$, and that our lack of dynamically cold distant objects means that there at most $8\times 10^3$ objects with $60 < a < 80$ au and absolute magnitudes $H \leq 8$., Comment: Accepted to AJ, companion paper to DEEP VI

The DECam Ecliptic Exploration Project (DEEP) is a deep survey of the trans-Neptunian solar system being carried out on the 4-meter Blanco telescope at Cerro Tololo Inter-American Observatory in Chile using the Dark Energy Camera (DECam). By using a shift-and-stack technique to achieve a mean limiting magnitude of $r \sim 26.2$, DEEP achieves an unprecedented combination of survey area and depth, enabling quantitative leaps forward in our understanding of the Kuiper Belt populations. This work reports results from an analysis of twenty 3 sq.\ deg.\ DECam fields along the invariable plane. We characterize the efficiency and false-positive rates for our moving-object detection pipeline, and use this information to construct a Bayesian signal probability for each detected source. This procedure allows us to treat all of our Kuiper Belt Object (KBO) detections statistically, simultaneously accounting for efficiency and false positives. We detect approximately 2300 candidate sources with KBO-like motion at S/N $>6.5$. We use a subset of these objects to compute the luminosity function of the Kuiper Belt as a whole, as well as the Cold Classical (CC) population. We also investigate the absolute magnitude ($H$) distribution of the CCs, and find consistency with both an exponentially tapered power-law, which is predicted by streaming instability models of planetesimal formation, and a rolling power law. Finally, we provide an updated mass estimate for the Cold Classical Kuiper Belt of $M_{CC}(H_r < 12) = 0.0017^{+0.0010}_{-0.0004} M_{\oplus}$, assuming albedo $p = 0.15$ and density $\rho = 1$ g cm$^{-3}$., Comment: Accepted by PSJ

This paper introduces Qatent PatFig, a novel large-scale patent figure dataset comprising 30,000+ patent figures from over 11,000 European patent applications. For each figure, this dataset provides short and long captions, reference numerals, their corresponding terms, and the minimal claim set that describes the interactions between the components of the image. To assess the usability of the dataset, we finetune an LVLM model on Qatent PatFig to generate short and long descriptions, and we investigate the effects of incorporating various text-based cues at the prediction stage of the patent figure captioning process., Comment: accepted to the ICCV 2023, CLVL: 5th Workshop on Closing the Loop Between Vision and Language

We present the methods and results from the discovery and photometric measurement of 26 bright (VR $>$ 24 trans-Neptunian objects (TNOs) during the first year (2019-20) of the DECam Ecliptic Exploration Project (DEEP). The DEEP survey is an observational TNO survey with wide sky coverage, high sensitivity, and a fast photometric cadence. We apply a computer vision technique known as a progressive probabilistic Hough transform to identify linearly-moving transient sources within DEEP photometric catalogs. After subsequent visual vetting, we provide a photometric and astrometric catalog of our TNOs. By modeling the partial lightcurve amplitude distribution of the DEEP TNOs using Monte Carlo techniques, we find our data to be most consistent with an average TNO axis ratio b/a $<$ 0.5, implying a population dominated by non-spherical objects. Based on ellipsoidal gravitational stability arguments, we find our data to be consistent with a TNO population containing a high fraction of contact binaries or other extremely non-spherical objects. We also discuss our data as evidence that the expected binarity fraction of TNOs may be size-dependent.

We present here the DECam Ecliptic Exploration Project (DEEP), a three year NOAO/NOIRLab Survey that was allocated 46.5 nights to discover and measure the properties of thousands of trans-Neptunian objects (TNOs) to magnitudes as faint as VR~27, corresponding to sizes as small as 20 km diameter. In this paper we present the science goals of this project, the experimental design of our survey, and a technical demonstration of our approach. The core of our project is "digital tracking," in which all collected images are combined at a range of motion vectors to detect unknown TNOs that are fainter than the single exposure depth of VR~23 mag. Through this approach we reach a depth that is approximately 2.5 magnitudes fainter than the standard LSST "wide fast deep" nominal survey depth of 24.5 mag. DEEP will more than double the number of known TNOs with observational arcs of 24 hours or more, and increase by a factor of 10 or more the number of known small (<50 km) TNOs. We also describe our ancillary science goals, including measuring the mean shape distribution of very small main belt asteroids, and briefly outline a set of forthcoming papers that present further aspects of and preliminary results from the DEEP program., Comment: AJ, in press. First in a series of papers

In the study of the arithmetic degrees (the degree structure induced by relative arithmetic definability, ($\leq_{a}$) the $\omega$-REA sets play a role analogous to the role the r.e. degrees play in the study of the Turing degrees. However, much less is known about the arithmetic degrees and the role of the $\omega$-REA sets in that structure than about the Turing degrees. Indeed, even basic questions such as the existence of a $\omega$-REA set of minimal arithmetic degree are open. This paper makes progress on this question by demonstrating that some promising approaches inspired by the analogy with the r.e sets fail to show that no $\omega$-REA set is arithmetically minimal. Finally, it constructs a $\Pi^0_2$ singleton of minimal arithmetic degree. Not only is this a result of considerable interest in it's own right, constructions of $\Pi^0_2$ singletons often pave the way for constructions of $\omega$-REA sets with similar properties. Along the way, a number of interesting results relating arithmetic reducibility and rates of growth are established.

In 2018, Jewitt identified the "The Trojan Color Conundrum", namely that Neptune's Trojan asteroids (NTs) had no ultra-red members, unlike the the nearby Kuiper Belt. Since then, numerous ultra-red NTs have been discovered, seemingly resolving this conundrum (Lin et al. 2019; Bolin et al.12 2023). However, it is still unclear whether or not the Kuiper Belt has a color distribution consistent with the NT population, as would be expected if it were the source population. In this work, we present a new photometric survey of 15 out of 31 NTs. We utilized the Sloan g'r'i'z' filters on the IMACS f/4 instrument which is mounted on the 6.5m Baade telescope. In this survey, we identify four NTs as being ultra-red using a Principal Component Analysis (PCA). This result brings the ratio of red to ultra-red NTs to 7.75:1, more consistent with the corresponding Trans-Neptunian Object (TNO) ratio of 4-11:1. We also identify three targets as being blue (nearly Solar) in color. Such objects may be C-type surfaces, but we see more of these blue NTs than has been observed in the Kuiper Belt (Seccull et al. 2018). Finally, we show that there are hints of a color-absolute magnitude (H) correlation, with larger H (smaller sized, lower albedo) tending to be more red, but more data is needed to confirm this result. The origin of such a correlation remains an open question which will be addressed by future observations of the surface composition of these targets and their rotational properties., Comment: 15 pages, 8 figures, accepted to PSJ