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Rapid growth of high-dimensional datasets in fields such as single-cell RNA sequencing and spatial genomics has led to unprecedented opportunities for scientific discovery, but it also presents unique computational and statistical challenges. Traditional methods struggle with geometry-aware data generation, interpolation along meaningful trajectories, and transporting populations via feasible paths. To address these issues, we introduce Geometry-Aware Generative Autoencoder (GAGA), a novel framework that combines extensible manifold learning with generative modeling. GAGA constructs a neural network embedding space that respects the intrinsic geometries discovered by manifold learning and learns a novel warped Riemannian metric on the data space. This warped metric is derived from both the points on the data manifold and negative samples off the manifold, allowing it to characterize a meaningful geometry across the entire latent space. Using this metric, GAGA can uniformly sample points on the manifold, generate points along geodesics, and interpolate between populations across the learned manifold. GAGA shows competitive performance in simulated and real world datasets, including a 30% improvement over the state-of-the-art methods in single-cell population-level trajectory inference.

The first FASER search for a light, long-lived particle decaying into a pair of photons is reported. The search uses LHC proton-proton collision data at $\sqrt{s}=13.6~\text{TeV}$ collected in 2022 and 2023, corresponding to an integrated luminosity of $57.7\text{fb}^{-1}$. A model with axion-like particles (ALPs) dominantly coupled to weak gauge bosons is the primary target. Signal events are characterised by high-energy deposits in the electromagnetic calorimeter and no signal in the veto scintillators. One event is observed, compared to a background expectation of $0.44 \pm 0.39$ events, which is entirely dominated by neutrino interactions. World-leading constraints on ALPs are obtained for masses up to $300~\text{MeV}$ and couplings to the Standard Model W gauge boson, $g_{aWW}$, around $10^{-4}$ GeV$^{-1}$, testing a previously unexplored region of parameter space. Other new particle models that lead to the same experimental signature, including ALPs coupled to gluons or photons, U(1)$_B$ gauge bosons, up-philic scalars, and a Type-I two-Higgs doublet model, are also considered for interpretation, and new constraints on previously viable parameter space are presented in this paper., Comment: 37 pages, 22 figures

Which rocky exoplanets have atmospheres, and which do not? This presumably simply question is the first that must be answered in the pathway toward understanding the prevalence of nearby habitable planets. A mere 6.9 pc from Earth, the LTT 1445A system is the closest transiting M-dwarf system, and its largest known planet, at $\rm 1.31\; R_{\oplus}$ and 424 K, is one of the best rocky targets in which to search for an atmosphere. We use HST/WFC3 transmission spectroscopy with the G280 and G141 grisms to study the spectrum of LTT 1445Ab between $\rm 0.2-1.65\;\mu m$. In doing so, we uncover a flare on the neighboring star LTT 1445C, and report one of the first simultaneous near-UV/optical spectra of an M dwarf flare. The planet spectrum is consistent with a flat line, though the infrared portion displays potential features that could be explained by known opacity sources such as HCN. Some atmospheric retrievals weakly favor ($\sim2\sigma$) an atmosphere over a flat line, but it remains challenging to discern between stellar contamination, an atmosphere, and a featureless spectrum at this time. We do, however, confidently rule out $\leq100\times$ solar metallicity atmospheres. Although stellar contamination retrievals cannot fit the infrared features well, the overall spectrum is consistent with stellar contamination from hot spots, cold spots, or both. Based on the UV/optical data, we place limits on the extent of stellar variability expected in the near-infrared ($30-40$ ppm), which will be critical for upcoming JWST observations of this highly optimal target., Comment: In Review at AJ. Submitted on 08/06/2024

In this article we study virtual nonholonomic constraints, which are relations between the generalized coordinates and momenta of a mechanical system that can be enforced via feedback control. We design a constraint which emulates gymnastics giant motion in an acrobot, and prove that this constraint can inject or dissipate energy based on the sign of a design parameter. The proposed constraint is tested both in simulation and experimentally on a real-world acrobot, demonstrating highly effective energy regulation properties and robustness to a variety of disturbances.

We present the first emission spectrum of the hot Jupiter WASP-17 b using one eclipse observation from the JWST Near Infrared Imager and Slitless Spectrograph (NIRISS) Single Object Slitless Spectroscopy (SOSS) mode. Covering a wavelength range of 0.6 to 2.8 microns, our retrieval analysis reveals a strong detection of H2O in WASP-17b dayside atmosphere (6.4sigma). Our retrievals consistently favor a super-solar dayside H2O abundance and a non-inverted temperature-pressure profile over a large pressure range. Additionally, our examination of the brightness temperature reveals excess emission below 1 microns, suggesting the possibility of a high internal temperature (600 to 700 K) and/or contributions from reflected light. We highlight that JWST emission spectroscopy retrieval results can be sensitive to whether negative eclipse depths are allowed at optical wavelengths during light curve fitting. Our findings deepen our understanding of WASP-17b atmospheric composition while also highlighting the sensitivity of our results to pressure-temperature profile parameterizations. This work is part of a series of studies by our JWST Telescope Scientist Team (JWST-TST), in which we will use Guaranteed Time Observations to perform Deep Reconnaissance of Exoplanet Atmospheres through Multi-instrument Spectroscopy (DREAMS)., Comment: Accepted for Publication in the Astronomical Journal (AJ) October 4, 2024

We present the first spectroscopic characterisation of the dayside atmosphere of WASP-17b in the mid-infrared using a single JWST MIRI/LRS eclipse observation. From forward-model fits to the 5-12 $\mu$m emission spectrum, we tightly constrain the heat redistribution factor of WASP-17b to be 0.92$\pm$0.02 at the pressures probed by this data, indicative of inefficient global heat redistribution. We also marginally detect a supersolar abundance of water, consistent with previous findings for WASP-17b, but note our weak constraints on this parameter. These results reflect the thermodynamically rich but chemically poor information content of MIRI/LRS emission data for high-temperature hot Jupiters. Using the eclipse mapping method, which utilises the signals that the spatial emission profile of an exoplanet imprints on the eclipse light curve during ingress/egress due to its partial occultation by the host star, we also construct the first eclipse map of WASP-17b, allowing us to diagnose its multidimensional atmospheric dynamics for the first time. We find a day-night temperature contrast of order 1000 K at the pressures probed by this data, consistent with our derived heat redistribution factor, along with an eastward longitudinal hotspot offset of $18.7^{+11.1\deg}_{-3.8}$, indicative of the presence of an equatorial jet induced by day-night thermal forcing being the dominant redistributor of heat from the substellar point. These dynamics are consistent with general circulation model predictions for WASP-17b. This work is part of a series of studies by the JWST Telescope Scientist Team (JWST-TST), in which we use Guaranteed Time Observations to perform Deep Reconnaissance of Exoplanet Atmospheres through Multi-instrument Spectroscopy (DREAMS)., Comment: 28 pages, 8 figures. Published in The Astronomical Journal

Physical interactions with socially assistive robots (SARs) positively affect user wellbeing. However, haptic experiences when touching a SAR are typically limited to perceiving the robot's movements or shell texture, while other modalities that could enhance the touch experience with the robot, such as vibrotactile stimulation, are under-explored. In this exploratory qualitative study, we investigate the potential of enhancing human interaction with the PARO robot through vibrotactile heartbeats, with the goal to regulate subjective wellbeing during stressful situations. We conducted in-depth one-on-one interviews with 30 participants, who watched three horror movie clips alone, with PARO, and with a PARO that displayed a vibrotactile heartbeat. Our findings show that PARO's presence and its interactive capabilities can help users regulate emotions through attentional redeployment from a stressor toward the robot. The vibrotactile heartbeat further reinforced PARO's physical and social presence, enhancing the socio-emotional support provided by the robot and its perceived life-likeness. We discuss the impact of individual differences in user experience and implications for the future design of life-like vibrotactile stimulation for SARs., Comment: 2024 33rd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on inter-continental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in October 2018. The longest-baseline detections approach 11$\,$G$\lambda$ corresponding to an angular resolution, or fringe spacing, of 19$\mu$as. The Allan deviation of the visibility phase at 870$\mu$m is comparable to that at 1.3$\,$mm on the relevant integration time scales between 2 and 100$\,$s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870$\mu$m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time., Comment: Corresponding author: S. Doeleman

With sizable volatile envelopes but smaller radii than the solar system ice giants, sub-Neptunes have been revealed as one of the most common types of planet in the galaxy. While the spectroscopic characterization of larger sub-Neptunes (2.5-4R$_\oplus$) has revealed hydrogen-dominated atmospheres, smaller sub-Neptunes (1.6--2.5R$_\oplus$) could either host thin, rapidly evaporating hydrogen-rich atmospheres or be stable metal-rich "water worlds" with high mean molecular weight atmospheres and a fundamentally different formation and evolutionary history. Here, we present the 0.6--2.8$\mu$m JWST NIRISS/SOSS transmission spectrum of GJ 9827 d, the smallest (1.98 R$_\oplus$) warm (T$_\mathrm{eq, A_B=0.3} \sim 620$K) sub-Neptune where atmospheric absorbers have been detected to date. Our two transit observations with NIRISS/SOSS, combined with the existing HST/WFC3 spectrum, enable us to break the clouds-metallicity degeneracy. We detect water in a highly metal-enriched "steam world" atmosphere (O/H of $\sim 4$ by mass and H$_2$O found to be the background gas with a volume mixing ratio of >31%). We further show that these results are robust to stellar contamination through the transit light source effect. We do not detect escaping metastable He, which, combined with previous nondetections of escaping He and H, supports the steam atmosphere scenario. In water-rich atmospheres, hydrogen loss driven by water photolysis happens predominantly in the ionized form which eludes observational constraints. We also detect several flares in the NIRISS/SOSS light-curves with far-UV energies of the order of 10$^{30}$ erg, highlighting the active nature of the star. Further atmospheric characterization of GJ 9827 d probing carbon or sulfur species could reveal the origin of its high metal enrichment., Comment: 37 pages, 18 figures, Accepted for publication in ApJL

With the increasing complexity and size of capacity expansion models, temporal aggregation has emerged as a common method to improve computational tractability. However, this approach inherently complicates the inclusion of long-duration storage (LDS) systems, whose operation involves the entire time horizon connecting all time steps. This work presents a detailed investigation of LDS modelling with temporal aggregation. A novel compact formulation is proposed to reduce the number of constraints while effectively tracking the storage content and enforcing limits on the state of charge throughout the entire time horizon. The developed method is compared with two leading state-of-the-art formulations. All three methods are implemented in the Dolphyn capacity expansion model and tested on a case study for the continental United States, considering different configurations in terms of spatial resolutions and representative periods. The performance is assessed with both the commercial solver Gurobi and the open-source solver HiGHS. Results show that the developed compact formulation consistently outperforms the other methods in terms of both runtime (30%-70% faster than other methods) and memory usage (1%-9% lower than other methods).

Neutrinos traveling over cosmic distances are ideal probes of new physics. We leverage on the approaching detection of the diffuse supernova neutrino background (DSNB) to explore whether, if the DSNB showed departures from theoretical predictions, we could attribute such modifications to new physics unequivocally. In order to do so, we focus on visible neutrino decay. Many of the signatures from neutrino decay are degenerate with astrophysical unknowns entering the DSNB modeling. Next generation neutrino observatories, such as Hyper-Kamiokande, JUNO, as well as DUNE, will set stringent limits on a neutrino lifetime over mass ratio $\tau/m \sim 10^{9}$-$10^{10}$ s eV$^{-1}$ at $90\%$ C.L., if astrophysical uncertainties and detector backgrounds were to be fully under control. However, if the lightest neutrino is almost massless and the neutrino mass ordering is normal, constraining visible decay will not be realistically possible in the coming few decades. We also assess the challenges of distinguishing among different new physics scenarios (such as visible decay, invisible decay, and quasi-Dirac neutrinos), all leading up to similar signatures in the DSNB. This work shows that the DSNB potential for probing new physics strongly depends on an improved understanding of the experimental backgrounds at next generation neutrino observatories as well as progress in the DSNB modeling., Comment: 30 pages, including 9 figures, 1 table, and 3 appendices

We have witnessed and experienced increasing compound extreme events resulting from simultaneous or sequential occurrence of multiple events in a changing climate. In addition to a growing demand for a clearer explanation of compound risks from a hydrological perspective, there has been a lack of attention paid to socioeconomic factors driving and impacted by these risks. Through a critical review and co-production approaches, we identified four types of compound hydrological events based on autocorrelated, multivariate, and spatiotemporal patterns. A framework to quantify compound risks based on conditional probability is offered, including an argument on the potential use of generative Artificial Intelligence (AI) algorithms for identifying emerging trends and patterns for climate change. Insights for practices are discussed, highlighting the implications for disaster risk reduction and knowledge co-production. Our argument centres on the importance of meaningfully considering the socioeconomic contexts in which compound risks may have impacts, and the need for interdisciplinary collaboration to effectively translate climate science to climate actions., Comment: 19 pages, 1 figure

Principal component analysis (PCA) is often used to analyze multivariate data together with cluster analysis, which depends on the number of principal components used. It is therefore important to determine the number of significant principal components (PCs) extracted from a data set. Here we use a variational Bayesian version of classical PCA, to develop a new method for estimating the number of significant PCs in contexts where the number of samples is of a similar to or greater than the number of features. This eliminates guesswork and potential bias in manually determining the number of principal components and avoids overestimation of variance by filtering noise. This framework can be applied to datasets of different shapes (number of rows and columns), different data types (binary, ordinal, categorical, continuous), and with noisy and missing data. Therefore, it is especially useful for data with arbitrary encodings and similar numbers of rows and columns, such as cultural, ecological, morphological, and behavioral datasets. We tested our method on both synthetic data and empirical datasets and found that it may underestimate but not overestimate the number of principal components for the synthetic data. A small number of components was found for each empirical dataset. These results suggest that it is broadly applicable across the life sciences., Comment: 9 pages, 2 figures

Nordic skiing provides fascinating opportunities for mathematical modelling studies that exploit methods and insights from physics, applied mathematics, data analysis, scientific computing and sports science. A typical ski course winds over varied terrain with frequent changes in elevation and direction, and so its geometry is naturally described by a three-dimensional space curve. The skier travels along a course under the influence of various forces, and their dynamics can be described using a nonlinear system of ordinary differential equations (ODEs) that are derived from Newton's laws of motion. We develop an algorithm for solving the governing equations that combines Hermite spline interpolation, numerical quadrature and a high-order ODE solver. Numerical simulations are compared with measurements of skiers on actual courses to demonstrate the effectiveness of the model., Comment: 26 pages, 10 figures

Project Euphonia, a Google initiative, is dedicated to improving automatic speech recognition (ASR) of disordered speech. A central objective of the project is to create a large, high-quality, and diverse speech corpus. This report describes the project's latest advancements in data collection and annotation methodologies, such as expanding speaker diversity in the database, adding human-reviewed transcript corrections and audio quality tags to 350K (of the 1.2M total) audio recordings, and amassing a comprehensive set of metadata (including more than 40 speech characteristic labels) for over 75\% of the speakers in the database. We report on the impact of transcript corrections on our machine-learning (ML) research, inter-rater variability of assessments of disordered speech patterns, and our rationale for gathering speech metadata. We also consider the limitations of using automated off-the-shelf annotation methods for assessing disordered speech., Comment: Interspeech 2024

X-ray Thomson scattering (XRTS) has emerged as a powerful tool for the diagnostics of matter under extreme conditions. In principle, it gives one access to important system parameters such as the temperature, density, and ionization state, but the interpretation of the measured XRTS intensity usually relies on theoretical models and approximations. In this work, we show that it is possible to extract the Rayleigh weight -- a key property that describes the electronic localization around the ions -- directly from the experimental data without the need for any model calculations or simulations. As a practical application, we consider an experimental measurement of strongly compressed Be at the National Ignition Facility (NIF) [D\"oppner \emph{et al.}, \textit{Nature} \textbf{618}, 270-275 (2023)]. In addition to being interesting in their own right, our results will open up new avenues for diagnostics from \emph{ab initio} simulations, help to further constrain existing chemical models, and constitute a rigorous benchmark for theory and simulations.

We introduce VistaFormer, a lightweight Transformer-based model architecture for the semantic segmentation of remote-sensing images. This model uses a multi-scale Transformer-based encoder with a lightweight decoder that aggregates global and local attention captured in the encoder blocks. VistaFormer uses position-free self-attention layers which simplifies the model architecture and removes the need to interpolate temporal and spatial codes, which can reduce model performance when training and testing image resolutions differ. We investigate simple techniques for filtering noisy input signals like clouds and demonstrate that improved model scalability can be achieved by substituting Multi-Head Self-Attention (MHSA) with Neighbourhood Attention (NA). Experiments on the PASTIS and MTLCC crop-type segmentation benchmarks show that VistaFormer achieves better performance than comparable models and requires only 8% of the floating point operations using MHSA and 11% using NA while also using fewer trainable parameters. VistaFormer with MHSA improves on state-of-the-art mIoU scores by 0.1% on the PASTIS benchmark and 3% on the MTLCC benchmark while VistaFormer with NA improves on the MTLCC benchmark by 3.7%.

Context. Relativistic jets in active galactic nuclei are known for their exceptional energy output, and imaging the synthetic synchrotron emission of numerical jet simulations is essential for a comparison with observed jet polarization emission. Aims. Through the use of 3D hybrid fluid-particle jet simulations (with the PLUTO code), we overcome some of the commonly made assumptions in relativistic magnetohydrodynamic (RMHD) simulations by using non-thermal particle attributes to account for the resulting synchrotron radiation. Polarized radiative transfer and ray-tracing (via the RADMC-3D code) highlight the differences in total intensity maps when (i) the jet is simulated purely with the RMHD approach, (ii) a jet tracer is considered in the RMHD approach, and (iii) a hybrid fluid-particle approach is used. The resulting emission maps were compared to the example of the radio galaxy Centaurus A. Methods. We applied the Lagrangian particle module implemented in the latest version of the PLUTO code. This new module contains a state-of-the-art algorithm for modeling diffusive shock acceleration and for accounting for radiative losses in RMHD jet simulations. The module implements the physical postulates missing in RMHD jet simulations by accounting for a cooled ambient medium and strengthening the central jet emission. Results. We find a distinction between the innermost structure of the jet and the back-flowing material by mimicking the radio emission of the Seyfert II radio galaxy Centaurus A when considering an edge-brightened jet with an underlying purely toroidal magnetic field. We demonstrate the necessity of synchrotron cooling as well as the improvements gained when directly accounting for non-thermal synchrotron radiation via non-thermal particles.

In the realm of music recommendation, sequential recommender systems have shown promise in capturing the dynamic nature of music consumption. Nevertheless, traditional Transformer-based models, such as SASRec and BERT4Rec, while effective, encounter challenges due to the unique characteristics of music listening habits. In fact, existing models struggle to create a coherent listening experience due to rapidly evolving preferences. Moreover, music consumption is characterized by a prevalence of repeated listening, i.e., users frequently return to their favourite tracks, an important signal that could be framed as individual or personalized popularity. This paper addresses these challenges by introducing a novel approach that incorporates personalized popularity information into sequential recommendation. By combining user-item popularity scores with model-generated scores, our method effectively balances the exploration of new music with the satisfaction of user preferences. Experimental results demonstrate that a Personalized Most Popular recommender, a method solely based on user-specific popularity, outperforms existing state-of-the-art models. Furthermore, augmenting Transformer-based models with personalized popularity awareness yields superior performance, showing improvements ranging from 25.2% to 69.8%. The code for this paper is available at https://github.com/sisinflab/personalized-popularity-awareness., Comment: Accepted by RecSys'24 as an LBR paper

If individuals at the highest mortality risk are also least likely to lapse a life insurance policy, then lapse-supported premiums magnify adverse selection costs. As an example, we model 'Term to 100' contracts, and risk as revealed by genetic test results. We identify three methods of managing lapse surplus: eliminating it by design; disposing of it retrospectively (through participation); or disposing of it prospectively (through lapse-supported premiums). We then assume a heterogeneous population in which: (a) insurers cannot identify individuals at high mortality risk; (b) a secondary market exists that prevents high-risk policies from lapsing; (c) financial underwriting is lax or absent; and (d) life insurance policies may even be initiated by third parties as a financial investment (STOLI). Adverse selection losses under (a) are typically very small, but under (b) can be increased by multiples, and under (c) and (d) increased almost without limit. We note that the different approaches to modeling lapses used in studies of adverse selection and genetic testing appear to be broadly equivalent and robust., Comment: 32 pages, 2 figures

The MIRI Exoplanets Orbiting White dwarfs (MEOW) Survey is a cycle 2 JWST program to search for exoplanets around dozens of nearby white dwarfs via infrared excess and direct imaging. In this paper, we present the detection of mid-infrared excess at 18 and 21 microns towards the bright (V = 11.4) metal-polluted white dwarf WD 0310-688. The source of the IR excess is almost certainly within the system; the probability of background contamination is $<0.1\%$. While the IR excess could be due to an unprecedentedly small and cold debris disk, it is best explained by a $3.0^{+5.5}_{-1.9}$ M$_{\rm Jup}$ cold (248$^{+84}_{-61}$ K) giant planet orbiting the white dwarf within the forbidden zone (the region where planets are expected to be destroyed during the star's red giant phase). We constrain the source of the IR excess to an orbital separation of 0.1-2 AU, marking the first discovery of a white dwarf planet candidate within this range of separations. WD 0310-688 is a young remnant of an A or late B-type star, and at just 10.4 pc it is now the closest white dwarf with a known planet candidate. Future JWST observations could distinguish the two scenarios by either detecting or ruling out spectral features indicative of a planet atmosphere., Comment: Accepted for publication to ApJL

Transformer-based recommender systems, such as BERT4Rec or SASRec, achieve state-of-the-art results in sequential recommendation. However, it is challenging to use these models in production environments with catalogues of millions of items: scaling Transformers beyond a few thousand items is problematic for several reasons, including high model memory consumption and slow inference. In this respect, RecJPQ is a state-of-the-art method of reducing the models' memory consumption; RecJPQ compresses item catalogues by decomposing item IDs into a small number of shared sub-item IDs. Despite reporting the reduction of memory consumption by a factor of up to 50x, the original RecJPQ paper did not report inference efficiency improvements over the baseline Transformer-based models. Upon analysing RecJPQ's scoring algorithm, we find that its efficiency is limited by its use of score accumulators for each item, which prevents parallelisation. In contrast, LightRec (a non-sequential method that uses a similar idea of sub-ids) reported large inference efficiency improvements using an algorithm we call PQTopK. We show that it is also possible to improve RecJPQ-based models' inference efficiency using the PQTopK algorithm. In particular, we speed up RecJPQ-enhanced SASRec by a factor of 4.5 x compared to the original SASRec's inference method and by a factor of 1.56 x compared to the method implemented in RecJPQ code on a large-scale Gowalla dataset with more than a million items. Further, using simulated data, we show that PQTopK remains efficient with catalogues of up to tens of millions of items, removing one of the last obstacles to using Transformer-based models in production environments with large catalogues., Comment: Accepted by RecSys 2024

Transmission spectroscopy is the most widely used technique for studying exoplanet atmospheres. Since the planetary nightside faces the observer during a transit, highly irradiated giant exoplanets with warm nightsides emit thermal radiation that can contaminate transmission spectra. Observations of ultra-hot Jupiters in the near- and mid-infrared with JWST are especially susceptible to nightside contamination. However, nightside thermal emission is generally not considered in atmospheric retrievals of exoplanet transmission spectra. Here, we quantify the potential biases from neglecting nightside thermal emission in multidimensional atmospheric retrievals of an ultra-hot Jupiter. Using simulated JWST transmission spectra of the ultra-hot Jupiter WASP-33b (0.8-12 $\mu$m), we find that transmission spectra retrievals without nightside emission can overestimate molecular abundances by almost an order-of-magnitude and underestimate the dayside temperature by $\gtrsim$ 400 K. We show that a modified retrieval prescription, including both transmitted light and nightside thermal emission, correctly recovers the atmospheric properties and is favored by Bayesian model comparisons. Nightside thermal contamination can be readily implemented in retrieval models via a first-order approximation, and we provide formulae to estimate whether this effect is likely to be significant for a given planet. We recommend that nightside emission should be included as standard practice when interpreting ultra-hot Jupiter transmission spectra with JWST., Comment: 21 pages, 11 figures. Accepted for publication in ApJ

Reinforcement Learning (RL) has been widely used to solve tasks where the environment consistently provides a dense reward value. However, in real-world scenarios, rewards can often be poorly defined or sparse. Auxiliary signals are indispensable for discovering efficient exploration strategies and aiding the learning process. In this work, inspired by intrinsic motivation theory, we postulate that the intrinsic stimuli of novelty and surprise can assist in improving exploration in complex, sparsely rewarded environments. We introduce a novel sample-efficient method able to learn directly from pixels, an image-based extension of TD3 with an autoencoder called \textit{NaSA-TD3}. The experiments demonstrate that NaSA-TD3 is easy to train and an efficient method for tackling complex continuous-control robotic tasks, both in simulated environments and real-world settings. NaSA-TD3 outperforms existing state-of-the-art RL image-based methods in terms of final performance without requiring pre-trained models or human demonstrations.

Iterative Bleaching Extends multipleXity (IBEX) is a versatile method for highly multiplexed imaging of diverse tissues. Based on open science principles, we created the IBEX Knowledge-Base, a resource for reagents, protocols and more, to empower innovation., Comment: 8 pages, 1 figure, 9 references

This paper develops an approach to classify instances of product failure in a complex textiles manufacturing dataset using explainable techniques. The dataset used in this study was obtained from a New Zealand manufacturer of woollen carpets and rugs. In investigating the trade-off between accuracy and explainability, three different tree-based classification algorithms were evaluated: a Decision Tree and two ensemble methods, Random Forest and XGBoost. Additionally, three feature selection methods were also evaluated: the SelectKBest method, using chi-squared as the scoring function, the Pearson Correlation Coefficient, and the Boruta algorithm. Not surprisingly, the ensemble methods typically produced better results than the Decision Tree model. The Random Forest model yielded the best results overall when combined with the Boruta feature selection technique. Finally, a tree ensemble explaining technique was used to extract rule lists to capture necessary and sufficient conditions for classification by a trained model that could be easily interpreted by a human. Notably, several features that were in the extracted rule lists were statistical features and calculated features that were added to the original dataset. This demonstrates the influence that bringing in additional information during the data preprocessing stages can have on the ultimate model performance., Comment: Accepted at the 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE 2024), awaiting publication Contains seven pages and five figures

In this study, state-of-the-art unsupervised detection models were evaluated for the purpose of automated anomaly inspection of wool carpets. A custom dataset of four unique types of carpet textures was created to thoroughly test the models and their robustness in detecting subtle anomalies in complex textures. Due to the requirements of an inline inspection system in a manufacturing use case, the metrics of importance in this study were accuracy in detecting anomalous areas, the number of false detections, and the inference times of each model for real-time performance. Of the evaluated models, the student-teacher network based methods were found on average to yield the highest detection accuracy and lowest false detection rates. When trained on a multi-class dataset the models were found to yield comparable if not better results than single-class training. Finally, in terms of detection speed, with exception to the generative model, all other evaluated models were found to have comparable inference times on a GPU, with an average of 0.16s per image. On a CPU, most of these models typically produced results between 1.5 to 2 times the respective GPU inference times., Comment: Accepted at the 2023 Australasian Conference on Robotics and Automation (ACRA 2023) Publication url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184380272&partnerID=40&md5=74fde263f4a24a1bff75d6560b423994 ISSN: 14482053 Contains 10 pages and three figures

Our recent work shows how M-Earth climates and transmission spectra depend on the amount of ice-free ocean on the planet's dayside and the mass of N2 in its atmosphere. M-Earths with more ice-free ocean and thicker atmospheres are hotter and more humid, and have larger water vapour features in their transmission spectra. In this paper, we describe a climate transition in high-pN2 simulations from the traditional ``eyeball" M-Earth climate, in which only the substellar region is temperate, to a ``temperate nightside" regime in which both the dayside and the nightside are entirely ice-free. Between these two states, there is a ``transition" regime with partial nightside ice cover. We use 3D climate simulations to describe the climate transition from frozen to deglaciated nightsides. We attribute this transition to increased advection and heat transport by water vapour in thicker atmospheres. We find that the nightside transitions smoothly back and forth between frozen and ice-free when the instellation or pCO2 is perturbed, with no hysteresis. We also find an analogous transition in colder planets: those with thin atmospheres can have a dayside hotspot when the instellation is low, whereas those with more massive atmospheres are more likely to be in the ``snowball" regime, featuring a completely frozen dayside, due to the increased advection of heat away from the substellar point. We show how both of these climate transitions are sensitive to instellation, land cover, and atmosphere mass. We generate synthetic transmission spectra and phase curves for the range of climates in our simulations., Comment: 20 pages, 17 figures, submitted to ApJ

We introduce EuroCropsML, an analysis-ready remote sensing machine learning dataset for time series crop type classification of agricultural parcels in Europe. It is the first dataset designed to benchmark transnational few-shot crop type classification algorithms that supports advancements in algorithmic development and research comparability. It comprises 706 683 multi-class labeled data points across 176 classes, featuring annual time series of per-parcel median pixel values from Sentinel-2 L1C data for 2021, along with crop type labels and spatial coordinates. Based on the open-source EuroCrops collection, EuroCropsML is publicly available on Zenodo., Comment: 5 pages, 5 figures

Many fascinating properties discovered in graphene and transition metal dichalcogenide (TMD) moir\'e superlattices originate from flat bands and enhanced many-body effects. Here, we discover new many-electron excited states in TMD homobilayers. As optical resonances evolve with twist angle and doping in MoSe$_2$ bilayers, a unique type of ``charge-transfer" trions is observed when gradual changes in atomic alignment between the layers occur. In real space, the optically excited electron-hole pair mostly resides in a different site from the doped hole in a moir\'e supercell. In momentum space, the electron-hole pair forms in the single-particle-band $K$-valley, while the hole occupies the $\Gamma$-valley. The rich internal structure of this trion resonance arises from the ultra-flatness of the first valence band and the distinct influence of moir\'e potential modulation on holes and excitons. Our findings open new routes to realizing photon-spin transduction or implementing moir\'e quantum simulators with independently tunable fermion and boson densities., Comment: 11 pages, 10 figures

Neural networks -- especially those that use large, pre-trained language models -- have improved search engines in various ways. Most prominently, they can estimate the relevance of a passage or document to a user's query. In this work, we depart from this direction by exploring whether neural networks can effectively predict which of a document's passages are unlikely to be relevant to any query submitted to the search engine. We refer to this query-agnostic estimation of passage relevance as a passage's quality. We find that our novel methods for estimating passage quality allow passage corpora to be pruned considerably while maintaining statistically equivalent effectiveness; our best methods can consistently prune >25% of passages in a corpora, across various retrieval pipelines. Such substantial pruning reduces the operating costs of neural search engines in terms of computing resources, power usage, and carbon footprint -- both when processing queries (thanks to a smaller index size) and when indexing (lightweight models can prune low-quality passages prior to the costly dense or learned sparse encoding step). This work sets the stage for developing more advanced neural "learning-what-to-index" methods., Comment: SIGIR 2024

The recent inference of sulphur dioxide (SO$_2$) in the atmosphere of the hot ($\sim$1100 K), Saturn-mass exoplanet WASP-39b from near-infrared JWST observations suggests that photochemistry is a key process in high temperature exoplanet atmospheres. This is due to the low ($<$1 ppb) abundance of SO$_2$ under thermochemical equilibrium, compared to that produced from the photochemistry of H$_2$O and H$_2$S (1-10 ppm). However, the SO$_2$ inference was made from a single, small molecular feature in the transmission spectrum of WASP-39b at 4.05 $\mu$m, and therefore the detection of other SO$_2$ absorption bands at different wavelengths is needed to better constrain the SO$_2$ abundance. Here we report the detection of SO$_2$ spectral features at 7.7 and 8.5 $\mu$m in the 5-12 $\mu$m transmission spectrum of WASP-39b measured by the JWST Mid-Infrared Instrument (MIRI) Low Resolution Spectrometer (LRS). Our observations suggest an abundance of SO$_2$ of 0.5-25 ppm (1$\sigma$ range), consistent with previous findings. In addition to SO$_2$, we find broad water vapour absorption features, as well as an unexplained decrease in the transit depth at wavelengths longer than 10 $\mu$m. Fitting the spectrum with a grid of atmospheric forward models, we derive an atmospheric heavy element content (metallicity) for WASP-39b of $\sim$7.1-8.0 $\times$ solar and demonstrate that photochemistry shapes the spectra of WASP-39b across a broad wavelength range., Comment: Published in Nature

Transition metal dichalcogenide (TMD) twisted homobilayers have been established as an ideal platform for studying strong correlation phenomena, as exemplified by the recent discovery of fractional Chern insulator (FCI) states in twisted MoTe2 and Chern insulators (CI) and unconventional superconductivity in twisted WSe2. In these systems, nontrivial topology in the strongly layer-hybridized regime can arise from a spatial patterning of interlayer tunneling amplitudes and layer-dependent potentials that yields a lattice of layer skyrmions. Here we report the direct observation of skyrmion textures in the layer degree of freedom of Rhombohedral-stacked (R-stacked) twisted WSe2 homobilayers. This observation is based on scanning tunneling spectroscopy that separately resolves the {\Gamma}-valley and K-valley moir\'e electronic states. We show that {\Gamma}-valley states are subjected to a moir\'e potential with an amplitude of ~ 120 meV. At ~150 meV above the {\Gamma}-valley, the K-valley states are subjected to a weaker moir\'e potential of ~30 meV. Most significantly, we reveal opposite layer polarization of the K-valley at the MX and XM sites within the moir\'e unit cell, confirming the theoretically predicted skyrmion layer-texture. The dI/dV mappings allow the parameters that enter the continuum model for the description of moir\'e bands in twisted TMD bilayers to be determined experimentally, further establishing a direct correlation between the shape of LDOS profile in real space and topology of topmost moir\'e band.

LHS 1140 b is the second-closest temperate transiting planet to the Earth with an equilibrium temperature low enough to support surface liquid water. At 1.730$\pm$0.025 R$_\oplus$, LHS 1140 b falls within the radius valley separating H$_2$-rich mini-Neptunes from rocky super-Earths. Recent mass and radius revisions indicate a bulk density significantly lower than expected for an Earth-like rocky interior, suggesting that LHS 1140 b could either be a mini-Neptune with a small envelope of hydrogen ($\sim$0.1% by mass) or a water world (9--19% water by mass). Atmospheric characterization through transmission spectroscopy can readily discern between these two scenarios. Here, we present two JWST/NIRISS transit observations of LHS 1140 b, one of which captures a serendipitous transit of LHS 1140 c. The combined transmission spectrum of LHS 1140 b shows a telltale spectral signature of unocculted faculae (5.8 $\sigma$), covering $\sim$20% of the visible stellar surface. Besides faculae, our spectral retrieval analysis reveals tentative evidence of residual spectral features, best-fit by Rayleigh scattering from an N$_2$-dominated atmosphere (2.3 $\sigma$), irrespective of the consideration of atmospheric hazes. We also show through Global Climate Models (GCM) that H$_2$-rich atmospheres of various compositions (100$\times$, 300$\times$, 1000$\times$solar metallicity) are ruled out to $>$10 $\sigma$. The GCM calculations predict that water clouds form below the transit photosphere, limiting their impact on transmission data. Our observations suggest that LHS 1140 b is either airless or, more likely, surrounded by an atmosphere with a high mean molecular weight. Our tentative evidence of an N$_2$-rich atmosphere provides strong motivation for future transmission spectroscopy observations of LHS 1140 b., Comment: 26 pages, 14 figures, 3 tables, accepted for publication in ApJL

Retrieval-augmented generation (RAG) offers an effective approach for addressing question answering (QA) tasks. However, the imperfections of the retrievers in RAG models often result in the retrieval of irrelevant information, which could introduce noises and degrade the performance, especially when handling multi-hop questions that require multiple steps of reasoning. To enhance the multi-hop reasoning ability of RAG models, we propose TRACE. TRACE constructs knowledge-grounded reasoning chains, which are a series of logically connected knowledge triples, to identify and integrate supporting evidence from the retrieved documents for answering questions. Specifically, TRACE employs a KG Generator to create a knowledge graph (KG) from the retrieved documents, and then uses an Autoregressive Reasoning Chain Constructor to build reasoning chains. Experimental results on three multi-hop QA datasets show that TRACE achieves an average performance improvement of up to 14.03% compared to using all the retrieved documents. Moreover, the results indicate that using reasoning chains as context, rather than the entire documents, is often sufficient to correctly answer questions.

Peaks and troughs in the subsynchronous impedance spectrum of a distribution feeder may be a useful indication of oscillation risk, or more importantly lack of oscillation risk, if inverter-based resource (IBR) deployments are increased on that feeder. GridSweep is a new instrument for measuring the subsynchronous impedance spectra of distribution feeders. It combines an active probing device that modulates a 120-volt 1-kW load sinusoidally at a user-selected GPS-phase locked frequency from 1.0 to 40.0 Hz, and with a recorder that takes ultra-high-precision continuous point-on-wave (CPOW) 120-volt synchrowaveforms at 4 kHz. This paper presents a computer simulation of GridSweep's probing and measurement capability. We construct an electromagnetic transient (EMT) simulation of a single-phase distribution feeder equipped with multiple inverter-based resources (IBRs). We include a model of the GridSweep probing device, then demonstrate the model's capability to measure the subsynchronous apparent impedance spectrum of the feeder. Peaks in that spectrum align with the system's dominant oscillation modes caused by IBRs., Comment: 10 pages, 18 figures

The topological magnetoelectric effect (TME) is a defining property of 3-dimensional $\mathbb{Z}_{2}$ topological insulators that was predicted on theoretical grounds more than a decade ago, but has still not been directly measured. In this Letter we propose a strategy for direct measurement of the TME, and discuss the precision of the effect in real devices with charge and spin disorder., Comment: 5 + 1 pages, 3 figures

The low-energy collective excitations of semiconductors and insulators often couple strongly to light, allowing them to be probed optically. We argue here that in fractional Chern insulators intra-band collective excitations are dark in the sense that they couple anomalously weakly to light. This conclusion is based on a relationship between ideal quantum geometry and the structure factor of a Chern band, and on a classical plasma analogy motivated by the vortexibility property of ideal Chern bands., Comment: Main text: 5 pages, 3 figures, Supmat: 5 pages, 1 figure; Comments are welcome

Mosaic crystals, with their high integrated reflectivities, are widely-employed in spectrometers used to diagnose high energy density systems. X-ray Thomson scattering (XRTS) has emerged as a powerful diagnostic tool of these systems, providing in principle direct access to important properties such as the temperature via detailed balance. However, the measured XRTS spectrum is broadened by the spectrometer instrument function (IF), and without careful consideration of the IF one risks misdiagnosing system conditions. Here, we consider in detail the IF of 40 $\mu$m and 100 $\mu$m mosaic HAPG crystals, and how the broadening varies across the spectrometer in an energy range of 6.7-8.6 keV. Notably, we find a strong asymmetry in the shape of the IF towards higher energies. As an example, we consider the effect of the asymmetry in the IF on the temperature inferred via XRTS for simulated 80 eV CH plasmas, and find that the temperature can be overestimated if an approximate symmetric IF is used. We therefore expect a detailed consideration of the full IF will have an important impact on system properties inferred via XRTS in both forward modelling and model-free approaches., Comment: 19 pages, 13 figures

Spin and valley flavor polarization plays a central role in the many-body physics of flat band graphene, with fermi surface reconstructions often accompanied by quantized anomalous Hall and superconducting state observed in a variety of experimental systems. Here we describe an optical technique that sensitively and selectively detects flavor textures via the exciton response of a proximal transition metal dichalcogenide layer. Through a systematic study of rhombohedral and rotationally faulted graphene bilayers and trilayers, we show that when the semiconducting dichalcogenide is in direct contact with the graphene, the exciton response is most sensitive to the large momentum rearrangement of the Fermi surface, providing information that is distinct from and complementary to electrical compressibility measurements. The wide-field imaging capability of optical probes allows us to obtain spatial maps of flavor orders with high throughput, and with broad temperature and device compatibility. Our work paves the way for optical probing and imaging of flavor orders in flat band graphene systems., Comment: 29 pages, 4 figures, with supplementary materials