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We prove that every planar graph is contained in $H_1\boxtimes H_2\boxtimes K_2$ for some graphs $H_1$ and $H_2$ both with treewidth 2. This resolves a question of Liu, Norin and Wood [arXiv:2410.20333]. We also show this result is best possible: for any $c \in \mathbb{N}$, there is a planar graph $G$ such that for any tree $T$ and graph $H$ with $\text{tw}(H) \leq 2$, $G$ is not contained in $H \boxtimes T \boxtimes K_c$., Comment: arXiv admin note: text overlap with arXiv:2410.20333

This paper explores the structure of graphs defined by an excluded minor or an excluded odd minor through the lens of graph products and tree-decompositions. We prove that every graph excluding a fixed odd minor is contained in the strong product of two graphs each with bounded treewidth. For graphs excluding a fixed minor, we strengthen the result by showing that every such graph is contained in the strong product of two digraphs with bounded indegree and with bounded treewidth. This result has the advantage that the product now has bounded degeneracy. In the setting of 3-term products, we show that every $K_t$-minor-free graph is contained in $H_1\boxtimes H_2 \boxtimes K_{c(t)}$ where $\text{tw}(H_i)\leq t-2$. This treewidth bound is close to tight: in any such result with $\text{tw}(H_i)$ bounded, both $H_1$ and $H_2$ can be forced to contain any graph of treewidth $t-5$, implying $\text{tw}(H_1)\geq t-5$ and $\text{tw}(H_2)\geq t-5$. Analogous lower and upper bounds are shown for any excluded minor, where the minimum possible bound on $\text{tw}(H_i)$ is tied to the treedepth of the excluded minor. Subgraphs of the product of two graphs with bounded treewidth have two tree-decompositions where any bag from the first decomposition intersects any bag from the second decomposition in a bounded number, $k$, of vertices, so called $k$-orthogonal tree-decompositions. We show that graphs excluding a fixed odd-minor have a tree-decomposition and a path-decomposition that are $O(1)$-orthogonal. This implies that such graphs have a tree-decomposition in which each bag has bounded pathwidth. This result is best possible in that `pathwidth' cannot be replaced by `bandwidth' or `treedepth'. Moreover, we characterize the minor-closed classes that have a tree-decomposition in which each bag has bounded bandwidth, or each bag has bounded treedepth.

Understanding the dynamic nature of protein structures is essential for comprehending their biological functions. While significant progress has been made in predicting static folded structures, modeling protein motions on microsecond to millisecond scales remains challenging. To address these challenges, we introduce a novel deep learning architecture, Protein Transformer with Scattering, Attention, and Positional Embedding (ProtSCAPE), which leverages the geometric scattering transform alongside transformer-based attention mechanisms to capture protein dynamics from molecular dynamics (MD) simulations. ProtSCAPE utilizes the multi-scale nature of the geometric scattering transform to extract features from protein structures conceptualized as graphs and integrates these features with dual attention structures that focus on residues and amino acid signals, generating latent representations of protein trajectories. Furthermore, ProtSCAPE incorporates a regression head to enforce temporally coherent latent representations., Comment: Accepted as a short paper at the 5th Molecular Machine Learning Conference (MoML 2024)

Treewidth and Hadwiger number are two of the most important parameters in structural graph theory. This paper studies graph classes in which large treewidth implies the existence of a large complete graph minor. To formalise this, we say that a graph class $\mathcal{G}$ is (tw,had)-bounded if there is a function $f$ (called the (tw,had)-bounding function) such that tw$(G)$ $\leq$ $f$(had$(G)$) for every graph $G \in \mathcal{G}$. We characterise (tw,had)-bounded graph classes as those that exclude some planar graph as an induced minor, and use this characterisation to show that every proper vertex-minor-closed class is (tw,had)-bounded. Furthermore, we demonstrate that any (tw,had)-bounded graph class has a (tw,had)-bounding function in O(had$(G)^9$polylog(had$(G)$)). Our bound comes from the bound for the Grid Minor Theorem given by Chuzhoy and Tan, and any quantitative improvement to their result will lead directly to an improvement to our result. More strongly, we conjecture that every (tw,had)-bounded graph class has a linear (tw,had)-bounding function. In support of this conjecture, we show that it holds for the class of outer-string graphs, and for a natural generalisation of outer-string graphs: intersection graphs of strings rooted at the boundary of a fixed surface. We also verify our conjecture for low-rank perturbations of circle graphs, which is an important step towards verifying it for all proper vertex-minor-closed classes., Comment: 26 pages, 6 Figures

We present the localization and host galaxy of FRB 20190208A, a repeating source of fast radio bursts (FRBs) discovered using CHIME/FRB. As part of the PRECISE repeater localization program on the EVN, we monitored FRB 20190208A for 65.6 hours at $\sim1.4$ GHz and detected a single burst, which led to its VLBI localization with 260 mas uncertainty (2$\sigma$). Follow-up optical observations with the MMT Observatory ($i\gtrsim 25.7$ mag (AB)) found no visible host at the FRB position. Subsequent deeper observations with the GTC, however, revealed an extremely faint galaxy ($r=27.32 \pm0.16$ mag), very likely ($99.95 \%$) associated with FRB 20190208A. Given the dispersion measure of the FRB ($\sim580$ pc cm$^{-3}$), even the most conservative redshift estimate ($z_{\mathrm{max}}\sim0.83$) implies that this is the lowest-luminosity FRB host to date ($\lesssim10^8L_{\odot}$), even less luminous than the dwarf host of FRB 20121102A. We investigate how localization precision and the depth of optical imaging affect host association, and discuss the implications of such a low-luminosity dwarf galaxy. Unlike the other repeaters with low-luminosity hosts, FRB 20190208A has a modest Faraday rotation measure of a few tens of rad m$^{-2}$, and EVN plus VLA observations reveal no associated compact persistent radio source. We also monitored FRB 20190208A for 40.4 hours over 2 years as part of the \'ECLAT repeating FRB monitoring campaign on the Nan\c{c}ay Radio Telescope, and detected one burst. Our results demonstrate that, in some cases, the robust association of an FRB with a host galaxy will require both high localization precision, as well as deep optical follow-up., Comment: submitted to ApJL

In order to better understand manifold neural networks (MNNs), we introduce Manifold Filter-Combine Networks (MFCNs). The filter-combine framework parallels the popular aggregate-combine paradigm for graph neural networks (GNNs) and naturally suggests many interesting families of MNNs which can be interpreted as the manifold analog of various popular GNNs. We then propose a method for implementing MFCNs on high-dimensional point clouds that relies on approximating the manifold by a sparse graph. We prove that our method is consistent in the sense that it converges to a continuum limit as the number of data points tends to infinity., Comment: Accepted to NeurIPS Workshop on Symmetry and Geometry in Neural Representations (Extended Abstract Track)

We utilize serendipitous observations from the Asteroid Terrestrial-impact Last Alert System (ATLAS) and the Zwicky Transient Facility (ZTF) in addition to targeted follow-up observations from the Las Cumbres Observatory (LCO) and Liverpool Telescope to analyze the first observed instance of cometary activity by the newly-discovered Jupiter-family comet C/2023 RN3 (ATLAS), whose orbital dynamics place it close to residing on a Centaur-like orbit. Across our 7-month baseline, we observe an epoch of cometary activity commencing in August 2023 with an increase in brightness of >5.4 mag. The lightcurve of 2023 RN3 indicates the presence of continuous cometary activity across our observations, suggesting the onset of a new period of sustained activity. We find no evidence of any outbursts on top of the observed brightening, nor do we find any significant color evolution across our observations. 2023 RN3 is visibly extended in LCO and Liverpool Telescope observations, indicating the presence of a spatially-extended coma. Numerical integration of 2023 RN3's orbit reveals the comet to have recently undergone a slight increase in semimajor axis due to a planetary encounter with Jupiter, however whether this orbital change could trigger 2023 RN3's cometary activity is unclear. Our estimate for the maximum dust production metric of Afrho ~400 cm is consistent with previous measurements for the Jupiter-family comet and Centaur populations., Comment: 20 pages, 9 figures

Precision measurements of polyatomic molecules offer an unparalleled paradigm to probe physics beyond the Standard Model. The rich internal structure within these molecules makes them exquisite sensors for detecting fundamental symmetry violations, local position invariance, and dark matter. While trapping and control of diatomic and a few very simple polyatomic molecules have been experimentally demonstrated, leveraging the complex rovibrational structure of more general polyatomics demands the development of robust and efficient quantum control schemes. In this study, we present a general, reinforcement-learning-designed, quantum logic approach to prepare molecular ions in a single, pure quantum state. The reinforcement learning agent optimizes the pulse sequence, each followed by a projective measurement, and probabilistically manipulates the collapse of the quantum system to a single state. The performance of the control algorithm is numerically demonstrated in the case of a CaH$^+$ ion, with up to 96 thermally populated eigenstates and under the disturbance of environmental thermal radiation. We expect that the method developed, with physics-informed learning, will be directly implemented for quantum control of polyatomic molecular ions with densely populated structures, enabling new experimental tests of fundamental theories., Comment: Methods Section included

Sub-Neptune planets with radii smaller than Neptune (3.9 Re) are the most common type of planet known to exist in The Milky Way, even though they are absent in the Solar System. These planets can potentially have a large diversity of compositions as a result of different mixtures of rocky material, icy material and gas accreted from a protoplanetary disk. However, the bulk density of a sub-Neptune, informed by its mass and radius alone, cannot uniquely constrain its composition; atmospheric spectroscopy is necessary. GJ 1214 b, which hosts an atmosphere that is potentially the most favorable for spectroscopic detection of any sub-Neptune, is instead enshrouded in aerosols (thus showing no spectroscopic features), hiding its composition from view at previously observed wavelengths in its terminator. Here, we present a JWST NIRSpec transmission spectrum from 2.8 to 5.1 um that shows signatures of carbon dioxide and methane, expected at high metallicity. A model containing both these molecules is preferred by 3.3 and 3.6 sigma as compared to a featureless spectrum for two different data analysis pipelines, respectively. Given the low signal-to-noise of the features compared to the continuum, however, more observations are needed to confirm the carbon dioxide and methane signatures and better constrain other diagnostic features in the near-infrared. Further modeling of the planet's atmosphere, interior structure and origins will provide valuable insights about how sub-Neptunes like GJ 1214 b form and evolve., Comment: 22 pages, 11 figures, Accepted in ApJL, Please also see a companion paper Ohno et al. (2024)

Causal inference is a critical task across fields such as healthcare, economics, and the social sciences. While recent advances in machine learning, especially those based on the deep-learning architectures, have shown potential in estimating causal effects, existing approaches often fall short in handling complex causal structures and lack adaptability across various causal scenarios. In this paper, we present a novel transformer-based method for causal inference that overcomes these challenges. The core innovation of our model lies in its integration of causal Directed Acyclic Graphs (DAGs) directly into the attention mechanism, enabling it to accurately model the underlying causal structure. This allows for flexible estimation of both average treatment effects (ATE) and conditional average treatment effects (CATE). Extensive experiments on both synthetic and real-world datasets demonstrate that our approach surpasses existing methods in estimating causal effects across a wide range of scenarios. The flexibility and robustness of our model make it a valuable tool for researchers and practitioners tackling complex causal inference problems.

A ferroelectric material often exhibits a soft transvers optical (TO) phonon mode which governs it phase transition. Charge coupling to this ferroelectric soft mode may further mediate emergent physical properties, including superconductivity and defect tolerance. However, direct experimental evidence for such coupling is scarce. Here we show that a photo-launched coherent phonon couples strongly to electronic transitions across the bandgap in the van der Waals (vdW) two-dimensional (2D) ferroelectric semiconductor NbOI2. Using terahertz time-domain spectroscopy and first-principles calculations, we identify this mode as the TO phonon responsible for ferroelectric order. This exclusive coupling occurs only with above-gap electronic transition and is absent in the valence band as revealed by resonant inelastic X-ray scattering. Our findings suggest a new role of the soft TO phonon mode in electronic and optical properties of ferroelectric semiconductors., Comment: 18 pages, 5 figures, 13 pages SI

We give an overview of the science objectives and mission design of the Spectroscopic Time-Resolving Observatory for Broadband Energy X-rays (STROBE-X) observatory, which has been proposed as a NASA probe-class (~$1.5B) mission in response to the Astro2020 recommendation for an X-ray probe., Comment: 11 pages, 5 figures, accepted for publication in JATIS

Phase-field methods offer a versatile computational framework for simulating large-scale microstructure evolution. However, the applicability and predictability of phase-field models are inherently limited by their ad hoc nature, and there is currently no bottom-up theory available that enables truly first-principles predictive modeling of large-scale non-equilibrium processes. Here, we present a bottom-up framework that provides a route to the construction of mesoscopic phase-field models entirely based on atomistic information. By introducing a molecular coarse-grained system as an intermediate step, we demonstrate the approach on the example of ice nucleation dynamics, with a spatiotemporal scale-up of nearly $10^8$ times compared to the microscopic model. Our framework offers a unique approach for incorporating atomistic details into mesoscopic models, systematically bridging the gap between microscopic particle-based simulations and field-theoretic models., Comment: 6 pages, 4 figures, see ancillary file for Supplemental Material

In this paper, we study the cardinality of the smallest set of lines of the finite projective spaces $\operatorname{PG}(n,q)$ such that every plane is incident with at least one line of the set. This is the first main open problem concerning the minimum size of $(s,t)$-blocking sets in $\operatorname{PG}(n,q)$, where we set $s=2$ and $t=1$. In $\operatorname{PG}(n,q)$, an $(s,t)$-blocking set refers to a set of $t$-spaces such that each $s$-space is incident with at least one chosen $t$-space. This is a notoriously difficult problem, as it is equivalent to determining the size of certain $q$-Tur\'an designs and $q$-covering designs. We present an improvement on the upper bounds of Etzion and of Metsch via a refined scheme for a recursive construction, which in fact enables improvement in the general case as well., Comment: 21 pages

To understand how the interconnected and interdependent world of the twenty-first century operates and make model-based predictions, joint probability models for networks and interdependent outcomes are needed. We propose a comprehensive regression framework for networks and interdependent outcomes with multiple advantages, including interpretability, scalability, and provable theoretical guarantees. The regression framework can be used for studying relationships among attributes of connected units and captures complex dependencies among connections and attributes, while retaining the virtues of linear regression, logistic regression, and other regression models by being interpretable and widely applicable. On the computational side, we show that the regression framework is amenable to scalable statistical computing based on convex optimization of pseudo-likelihoods using minorization-maximization methods. On the theoretical side, we establish convergence rates for pseudo-likelihood estimators based on a single observation of dependent connections and attributes. We demonstrate the regression framework using simulations and an application to hate speech on the social media platform X in the six months preceding the insurrection at the U.S. Capitol on January 6, 2021.

(Abridged) Mechanisms for quenching star formation in galaxies remain hotly debated, with galaxy mergers an oft-proposed pathway. In Ellison et al. (2022) we tested this scenario by quantifying the fraction of recently and rapidly quenched post-starbursts (PSBs) in a sample of post-merger galaxies identified in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS). With our recent development of the Multi-Model Merger Identifier (MUMMI) neural network ensemble (Ferreira et al. 2024a,b), we are now additionally able to predict the time since coalescence (T_PM) for the UNIONS post-merger galaxies up to T_PM = 1.8 Gyr, allowing us to further dissect the merger sequence and measure more precisely when quenching occurs. Based on a sample of 5927 z<0.3 post-mergers identified in UNIONS, we find that the post-coalescence population evolves from one dominated by star-forming (and starbursting) galaxies at 0 < T_PM < 0.16 Gyr, through to a population that is dominated by quenched galaxies by T_PM ~ 1.5 Gyr. We find a PSB excess throughout the post-merger regime, but with a clear peak at 0.16 < T_PM < 0.48 Gyr. In this post-merger time range PSBs are more common than in control galaxies by factors of 30-100, an excess that drops sharply at longer times since merger. We also quantify the fraction of PSBs that are mergers and find that the majority (75%) of classically selected E+A are identified as mergers, with a lower merger fraction (60%) amongst PCA selected PSBs. Our results demonstrate that 1) galaxy-galaxy interactions can lead to rapid post-merger quenching within 0.5 Gyr of coalescence, 2) the majority of (but not all) PSBs at low z are linked to mergers and 3) quenching pathways are diverse, with different PSB selection techniques likely identifying galaxies quenched by different physical processes with an additional dependence on stellar mass., Comment: To be submitted to the Open Journal of Astrophysics. 15 pages, 11 figures. For a temporal view of star formation in the post-merger regime see companion paper Ferreira et al. 2024c

Galaxy mergers can enhance star formation rates throughout the merger sequence, with this effect peaking around the time of coalescence. However, owing to a lack of information about their time of coalescence, post-mergers could only previously be studied as a single, time-averaged population. We use timescale predictions of post-coalescence galaxies in the UNIONS survey, based on the Multi-Model Merger Identifier deep learning framework (\textsc{Mummi}) that predicts the time elapsed since the last merging event. For the first time, we capture a complete timeline of star formation enhancements due to galaxy mergers by combining these post-merger predictions with data from pre-coalescence galaxy pairs in SDSS. Using a sample of $564$ galaxies with $M_* \geq 10^{10} M_\odot$ at $0.005 < z < 0.3$ we demonstrate that: 1) galaxy mergers enhance star formation by, on average, up to a factor of two; 2) this enhancement peaks within 500 Myr of coalescence; 3) enhancements continue for up to 1~Gyr after coalescence; and 4) merger-induced star formation significantly contributes to galaxy mass assembly, with galaxies increasing their final stellar masses by, $10\%$ to $20\%$ per merging event, producing on average $\log(M_*/M_\odot) = {9.56_{-0.19}^{+0.13}}$ more mass than non-interacting star-forming galaxies solely due to the excess star formation., Comment: Letter Submitted to MNRAS, 6 pages, 4 figures. For a temporal view of quenching in the post-merger regime see companion paper Ellison et al. 2024

We report the detection of broad, flat-topped emission in the fine-structure lines of [Ne V], [Ne VI], and [O IV] in mid-infrared spectra of the O9 V star 10 Lacertae obtained with JWST/MIRI. Optically thin emission in these high ions traces a hot, low-density component of the wind. The observed line fluxes imply a mass-loss rate of 2-4 x 10^8 Msun/yr, which is an order of magnitude larger than previous estimates based on UV and optical diagnostics. The presence of this hot component reconciles measured values of the mass-loss rate with theoretical predictions, and appears to solve the "weak wind" problem for the particular case of 10 Lac., Comment: 8 pages, 5, figures, submitted to ApJL

We introduce a black-box auxiliary field quantum Monte Carlo (AFQMC) approach to perform highly accurate electronic structure calculations using configuration interaction singles and doubles (CISD) trial states. This method consistently provides more accurate energy estimates than coupled cluster singles and doubles with perturbative triples (CCSD(T)), often regarded as the gold standard in quantum chemistry. This level of precision is achieved at a lower asymptotic computational cost, scaling as $O(N^6)$ compared to the $O(N^7)$ scaling of CCSD(T). We provide numerical evidence supporting these findings through results for challenging main group and transition metal-containing molecules., Comment: 17 pages, 11 figures

Despite being operational for only a short time, the Einstein Probe mission has already significantly advanced the study of rapid variability in the soft X-ray sky. We report the discovery of luminous and variable radio emission from the Einstein Probe fast X-ray transient EP240414a, the second such source with a radio counterpart. The radio emission at $3\,\rm{GHz}$ peaks at $\sim30$ days post explosion and with a spectral luminosity $\sim2\times10^{30}\,\rm{erg}\,\rm{s}^{-1}\,\rm{Hz}^{-1}$, similar to what is seen from long gamma-ray bursts, and distinct from other extra-galactic transients including supernovae and tidal disruption events, although we cannot completely rule out emission from engine driven stellar explosions e.g. the fast blue optical transients. An equipartition analysis of our radio data reveals that an outflow with at least a moderate bulk Lorentz factor ($\Gamma\gtrsim1.6$) with a minimum energy of $\sim10^{48}\,\rm{erg}$ is required to explain our observations. The apparent lack of reported gamma-ray counterpart to EP240414a could suggest that an off-axis or choked jet could be responsible for the radio emission, although a low luminosity gamma-ray burst may have gone undetected. Our observations are consistent with the hypothesis that a significant fraction of extragalactic fast X-ray transients are associated with the deaths of massive stars., Comment: 11 pages, 6 figures, submitted to ApJL

As the United Kingdom wind fleet increases in size, wind lulls and slews will increasingly challenge the stability of its electricity system. The paper describes the use of models based on real time records and including solar slews, to investigate the most extreme wind variations likely to be encountered in future, enabling strategies to be devised to mitigate them. Wind lulls are surprisingly frequent, occasionally lasting a week or more, and are always likely to be beyond the capabilities of stored or imported electrical energy to mitigate them. The models indicate that there will be a continuing need for gas powered generation to mitigate wind lulls. Currently, Combined Cycle Gas Turbines (CCGTs) provide most of the dispatchable generation. However, CCGTs are not sufficiently fast acting to cope with the wind and solar slews anticipated in future. The paper suggests that a range of already proven fast-acting sources of dispatchable generation, including Open Cycle Gas Turbines (OCGTs), Internal Combustion Gas-Fired Reciprocating engines (ICGRs) and stored electrical energy systems, should be capable of coping with the largest wind and solar slews likely to be encountered up to the year 2035. Examples are given of the recent introduction of these fast-acting sources of generation which, it is suggested, will progressively replace CCGTs as the wind and solar fleets increase in size. Moreover, we see the pattern of recent investments, summarised in the paper, as a good indication of likely future investments, with OCGT investments mainly serving the 440 kV grid, and ICGRs and stored electrical energy more local networks., Comment: 13 pages, 8 figures, 3 tables

We describe the spectrophotometric calibration of the Mid-Infrared Instrument's (MIRI) Medium Resolution Spectrometer (MRS) aboard the James Webb Space Telescope (JWST). This calibration is complicated by a time-dependent evolution in the effective throughput of the MRS; this evolution is strongest at long wavelengths, approximately a factor of 2 at 25um over the first two years of the mission. We model and correct for this evolution through regular observations of internal calibration lamps. Pixel flatfields are constructed from observations of the infrared-bright planetary nebula NGC 7027, and photometric aperture corrections from a combination of theoretical models and observations of bright standard stars. We tie the 5--18um flux calibration to high signal/noise (S/N; ~ 600-1000) observations of the O9 V star 10 Lacertae, scaled to the average calibration factor of nine other spectrophotometric standards. We calibrate the 18--28um spectral range using a combination of observations of main belt asteroid 515 Athalia and the circumstellar disk around young stellar object SAO 206462. The photometric repeatability is stable to better than 1% in the wavelength range 5--18um, and the S/N ratio of the delivered spectra is consistent between bootstrapped measurements, pipeline estimates, and theoretical predictions. The MRS point-source calibration agrees with that of the MIRI imager to within 1% from 7 to 21um and is approximately 1% fainter than prior Spitzer observations, while the extended source calibration agrees well with prior Cassini/CIRS and Voyager/IRIS observations., Comment: 29 pages, 32 figures. Submitted to AJ

The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI), combined with the ability to generate large-scale experimental data, present novel opportunities to model cells. Here we propose a vision of leveraging advances in AI to construct virtual cells, high-fidelity simulations of cells and cellular systems under different conditions that are directly learned from biological data across measurements and scales. We discuss desired capabilities of such AI Virtual Cells, including generating universal representations of biological entities across scales, and facilitating interpretable in silico experiments to predict and understand their behavior using virtual instruments. We further address the challenges, opportunities and requirements to realize this vision including data needs, evaluation strategies, and community standards and engagement to ensure biological accuracy and broad utility. We envision a future where AI Virtual Cells help identify new drug targets, predict cellular responses to perturbations, as well as scale hypothesis exploration. With open science collaborations across the biomedical ecosystem that includes academia, philanthropy, and the biopharma and AI industries, a comprehensive predictive understanding of cell mechanisms and interactions has come into reach.

The Mittelman-di Cicco-Walker (MDW) H$\alpha$ Sky Survey is an autonomously-operated and ongoing all-sky imaging survey in the narrowband H$\alpha$ wavelength. The survey was founded by amateur astronomers, and is presented here in its first stage of refinement for rigorous scientific use. Each field is exposed through an H$\alpha$ filter with a 3nm bandwidth for a total of four hours, with a pixel scale of 3.2 arcsec. Here, we introduce the first Data Release of the MDW H$\alpha$ Survey (Data Release 0, or DR0), spanning 238 fields in the region of Orion (~3100 deg$^2$). DR0 includes: calibrated mean fields, star-removed mean fields, a point source catalog matched to Data Release 1 of the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS1) and the INT Galactic Plane Survey (IGAPS), and mosaics.

The absolute flux calibration of the Mid-Infrared Instrument Imaging and Coronagraphy is based on observations of multiple stars taken during the first 2.5 years of JWST operations. The observations were designed to ensure that the flux calibration is valid for a range of flux densities, different subarrays, and different types of stars. The flux calibration was measured by combining observed aperture photometry corrected to infinite aperture with predictions based on previous observations and models of stellar atmospheres. A subset of these observations were combined with model point-spread-functions to measure the corrections to infinite aperture. Variations in the calibration factor with time, flux density, background level, type of star, subarray, integration time, rate, and well depth were investigated, and the only significant variations were with time and subarray. Observations of the same star taken approximately every month revealed a modest time-dependent response loss seen mainly at the longest wavelengths. This loss is well characterized by a decaying exponential with a time constant of ~200 days. After correcting for the response loss, the band-dependent scatter around the corrected average (aka repeatability) was found to range from 0.1 to 1.2%. Signals in observations taken with different subarrays can be lower by up to 3.4% compared to FULL frame. After correcting for the time and subarray dependencies, the scatter in the calibration factors measured for individual stars ranges from 1 to 4% depending on the band. The formal uncertainties on the flux calibration averaged for all observations are 0.3 to 1.0%, with longer-wavelength bands generally having larger uncertainties., Comment: 26 pages, 17 figures, submitted to AJ

Previously, a synchrotron-based horizontal proton beamline (87.2 MeV) was successfully commissioned to deliver radiation doses in FLASH and conventional dose rate modes to small fields and volumes. In this study, we developed a strategy to increase the effective radiation field size using a custom robotic motion platform to automatically shift the positions of biological samples. The beam was first broadened with a thin tungsten scatterer and shaped by customized brass collimators for irradiating cell/organoid cultures in 96-well plates (a 7-mm-diameter circle) or for irradiating mice (1-cm2 square). Motion patterns of the robotic platform were written in G-code, with 9-mm spot spacing used for the 96-well plates and 10.6-mm spacing for the mice. The accuracy of target positioning was verified with a self-leveling laser system. The dose delivered in the experimental conditions was validated with EBT-XD film attached to the 96-well plate or the back of the mouse. Our film-measured dose profiles matched Monte Carlo calculations well (1D gamma pass rate >95%). The FLASH dose rates were 113.7 Gy/s for cell/organoid irradiation and 191.3 Gy/s for mouse irradiation. These promising results indicate that this robotic platform can be used to effectively increase the field size for preclinical experiments with proton FLASH.

Entangled two-photon absorption (ETPA) may be a viable technique to continuously drive an excited state population in plasma for high-bandwidth spectroscopy measurements of localized plasma turbulence or impurity density. Classical two-photon absorption commonly requires a high-intensity, pulsed laser, but entangled photons with short entanglement time and high time correlation may allow for ETPA using a lower intensity, continuous-wave laser. Notably, ETPA with non-collinear entangled photon generation allows for cross-beam spatial localization of the absorption or fluorescence signal using a single laser source. Entangled photon generation, the ETPA cross-section, candidate transitions for an Ar-II species, and plans for a proof-of-principle measurement in a helicon plasma are discussed.

Planet-planet occultations (PPOs) occur when one exoplanet occults another exoplanet in the same system as seen from the Earth's vantage point. PPOs may provide a unique opportunity to observe radio "spillover" from extraterrestrial intelligences' (ETIs) radio transmissions or radar being transmitted from the further exoplanet towards the nearer one for the purposes of communication or scientific exploration. Planetary systems with many tightly packed, low-inclination planets, such as TRAPPIST-1, are predicted to have frequent PPOs. Here, the narrowband technosignature search code turboSETI was used in combination with the newly developed NbeamAnalysis filtering pipeline to analyze 28 hours of beamformed data taken with the Allen Telescope Array (ATA) during late October and early November 2022, from 0.9--9.3~GHz, targeting TRAPPIST-1. During this observing window, 7 possible PPO events were predicted using the NbodyGradient code. The filtering pipeline reduced the original list of 25 million candidate signals down to 6 million by rejecting signals that were not sky-localized and, from these, identified a final list of 11127 candidate signals above a power law cutoff designed to segregate signals by their attenuation and morphological similarity between beams. All signals were plotted for visual inspection, 2264 of which were found to occur during PPO windows. We report no detection of signals of non-human origin, with upper limits calculated for each PPO event exceeding EIRPs of 2.17--13.3 TW for minimally drifting signals and 40.8--421 TW in the maximally drifting case. This work constitutes the longest single-target radio SETI search of TRAPPIST-1 to date.

In this work we investigate anharmonic vibrational polaritons formed due to strong light-matter interactions in an optical cavity between radiation modes and anharmonic vibrations beyond the long-wavelength limit. We introduce a conceptually simple description of light-matter interactions, where spatially localized cavity radiation modes couple to localized vibrations. Within this theoretical framework, we employ self-consistent phonon theory and vibrational dynamical mean-field theory to efficiently simulate momentum-resolved vibrational-polariton spectra, including effects of anharmonicity. Numerical simulations in model systems demonstrate the accuracy and applicability of our approach., Comment: 10 pages, 6 figures

Molecular dynamics (MD) simulations provide crucial insight into molecular interactions and biomolecular function. With interactive MD simulations in VR (iMD-VR), chemists can now interact with these molecular simulations in real-time. Our sense of touch is essential for exploring the properties of physical objects, but recreating this sensory experience for virtual objects poses challenges. Furthermore, employing haptics in the context of molecular simulation is especially difficult since \textit{we do not know what molecules actually feel like}. In this paper, we build upon previous work that demonstrated how VR-users can distinguish properties of molecules without haptic feedback. We present the results of a gamified two-alternative forced choice (2AFC) psychophysics user study in which we quantify the threshold at which iMD-VR users can differentiate the stiffness of molecular bonds. Our preliminary analysis suggests that participants can sense differences between buckminsterfullerene molecules with different bond stiffness parameters and that this limit may fall within the chemically relevant range. Our results highlight how iMD-VR may facilitate a more embodied way of exploring complex and dynamic molecular systems, enabling chemists to sense the properties of molecules purely by interacting with them in VR., Comment: 9 pages, 2 figures, and was published in the proceedings of the International Conference on eXtended Reality 2024 (XR SALENTO 2024)

Molecular dynamics simulations are a crucial computational tool for researchers to understand and engineer molecular structure and function in areas such as drug discovery, protein engineering, and material design. Despite their utility, MD simulations are expensive, owing to the high dimensionality of molecular systems. Interactive molecular dynamics in virtual reality (iMD-VR) has recently been developed as a 'human-in-the-loop' strategy, which leverages high-performance computing to accelerate the researcher's ability to solve the hyperdimensional sampling problem. By providing an immersive 3D environment that enables visualization and manipulation of real-time molecular motion, iMD-VR enables researchers and students to efficiently and intuitively explore and navigate these complex, high-dimensional systems. iMD-VR platforms offer a unique opportunity to quickly generate rich datasets that capture human experts' spatial insight regarding molecular structure and function. This paper explores the possibility of employing user-generated iMD-VR datasets to train AI agents via imitation learning (IL). IL is an important technique in robotics that enables agents to mimic complex behaviors from expert demonstrations, thus circumventing the need for explicit programming or intricate reward design. We review the utilization of IL for manipulation tasks in robotics and discuss how iMD-VR recordings could be used to train IL models for solving specific molecular 'tasks'. We then investigate how such approaches could be applied to the data captured from iMD-VR recordings. Finally, we outline the future research directions and potential challenges of using AI agents to augment human expertise to efficiently navigate conformational spaces, highlighting how this approach could provide valuable insight across domains such as materials science, protein engineering, and computer-aided drug design., Comment: (Accepted for presentation at the First Workshop on "eXtended Reality \& Intelligent Agents" (XRIA24) @ ECAI24, Santiago De Compostela (Spain), 20 October 2024)

Wildfire frequency is increasing as the climate changes, and the resulting air pollution poses health risks. Just as people routinely use weather forecasts to plan their activities around precipitation, reliable air quality forecasts could help individuals reduce their exposure to air pollution. In the present work, we evaluate several existing forecasts of fine particular matter (PM2.5) within the continental United States in the context of individual decision-making. Our comparison suggests there is meaningful room for improvement in air pollution forecasting, which might be realized by incorporating more data sources and using machine learning tools. To facilitate future machine learning development and benchmarking, we set up a framework to evaluate and compare air pollution forecasts for individual decision making. We introduce a new loss to capture decisions about when to use mitigation measures. We highlight the importance of visualizations when comparing forecasts. Finally, we provide code to download and compare archived forecast predictions., Comment: 22 pages, 3 figures

The ideal magnetohydrodynamic torus instability can drive the eruption of coronal mass ejections. The critical threshold of magnetic field strength decay for the onset of the torus instability occurs at different heights in different solar active regions, and understanding this variation could therefore improve space weather prediction. In this work, we aim to find out how the critical torus instability height evolves throughout the solar activity cycle. We study a significant subset of HMI and MDI Space-Weather HMI Active Region Patches (SHARPs and SMARPs) from 1996-2023, totalling 21584 magnetograms from 4436 unique active region patches. For each magnetogram, we compute the critical height averaged across the main polarity inversion line, the total unsigned magnetic flux and the separation between the positive and negative magnetic polarities. We find the critical height in active regions varies with the solar cycle, with higher (lower) average critical heights observed around solar maximum (minimum). We conclude this is because the critical height is proportional to the separation between opposite magnetic polarities, which in turn is proportional to the total magnetic flux in a region, and more magnetic regions with larger fluxes and larger sizes are observed at solar maximum. This result is noteworthy because, despite the higher critical heights, more CMEs are observed around solar maximum than at solar minimum., Comment: Accepted to ApJ. 14 pages, 6 Figures, 1 Table

Sign Language Processing (SLP) provides a foundation for a more inclusive future in language technology; however, the field faces several significant challenges that must be addressed to achieve practical, real-world applications. This work addresses multi-view isolated sign recognition (MV-ISR), and highlights the essential role of 3D awareness and geometry in SLP systems. We introduce the NGT200 dataset, a novel spatio-temporal multi-view benchmark, establishing MV-ISR as distinct from single-view ISR (SV-ISR). We demonstrate the benefits of synthetic data and propose conditioning sign representations on spatial symmetries inherent in sign language. Leveraging an SE(2) equivariant model improves MV-ISR performance by 8%-22% over the baseline., Comment: Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at the 41 st International Conference on Machine Learning, Vienna, Austria. PMLR 251, 2024

The elemental and isotopic abundances of volatiles like carbon, oxygen, and nitrogen may trace a planet's formation location relative to H$_2$O, CO$_2$, CO, NH$_3$, and N$_2$ "snowlines", or the distance from the star at which these volatile elements sublimate. By comparing the C/O and $^{12}$C/$^{13}$C ratios measured in giant exoplanet atmospheres to complementary measurements of their host stars, we can determine whether the planet inherited stellar abundances from formation inside the volatile snowlines, or non-stellar C/O and $^{13}$C enrichment characteristic of formation beyond the snowlines. To date, there are still only a handful of exoplanet systems where we can make a direct comparison of elemental and isotopic CNO abundances between an exoplanet and its host star. Here, we present a $^{12}$C/$^{13}$C abundance analysis for host star WASP-77A (whose hot Jupiter's $^{12}$C/$^{13}$C abundance was recently measured). We use MARCS stellar atmosphere models and the radiative transfer code TurboSpectrum to generate synthetic stellar spectra for isotopic abundance calculations. We find a $^{12}$C/$^{13}$C ratio of $51\pm 6$ for WASP-77A, which is sub-solar ($\sim 91$) but may still indicate $^{13}$C-enrichment in its companion planet WASP-77A b ($^{12}$C/$^{13}$C = 26 $\pm$ 16, previously reported). Together with the inventory of carbon and oxygen abundances in both the host and companion planet, these chemical constraints point to WASP-77A b's formation beyond the H$_2$O and CO$_2$ snowlines and provide chemical evidence for the planet's migration to its current location $\sim$0.024 AU from its host star., Comment: 21 pages, 4 figures, 3 tables Accepted for publication in ApJ (8/14/2024)

The main purpose of this work is the derivation of a functional partial differential equation (FPDE) for the calculations of equity-linked insurance policies, where the payment stream may depend on the whole past history of the financial asset. To this end, we employ variational techniques from the theory of functional It\^o calculus.

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.

Underperformance of ASR systems for speakers of African American Vernacular English (AAVE) and other marginalized language varieties is a well-documented phenomenon, and one that reinforces the stigmatization of these varieties. We investigate whether or not the recent wave of Self-Supervised Learning (SSL) speech models can close the gap in ASR performance between AAVE and Mainstream American English (MAE). We evaluate four SSL models (wav2vec 2.0, HuBERT, WavLM, and XLS-R) on zero-shot Automatic Speech Recognition (ASR) for these two varieties and find that these models perpetuate the bias in performance against AAVE. Additionally, the models have higher word error rates on utterances with more phonological and morphosyntactic features of AAVE. Despite the success of SSL speech models in improving ASR for low resource varieties, SSL pre-training alone may not bridge the gap between AAVE and MAE. Our code is publicly available at https://github.com/cmu-llab/s3m-aave., Comment: INTERSPEECH 2024

Transiting giant exoplanets around M-dwarf stars (GEMS) are rare, owing to the low-mass host stars. However, the all-sky coverage of TESS has enabled the detection of an increasingly large number of them to enable statistical surveys like the \textit{Searching for GEMS} survey. As part of this endeavour, we describe the observations of six transiting giant planets, which includes precise mass measurements for two GEMS (K2-419Ab, TOI-6034b) and statistical validation for four systems, which includes validation and mass upper limits for three of them (TOI-5218b, TOI-5616b, TOI-5634Ab), while the fourth one -- TOI-5414b is classified as a `likely planet'. Our observations include radial velocities from the Habitable-zone Planet Finder on the Hobby-Eberly Telescope, and MAROON-X on Gemini-North, along with photometry and high-contrast imaging from multiple ground-based facilities. In addition to TESS photometry, K2-419Ab was also observed and statistically validated as part of the K2 mission in Campaigns 5 and 18, which provides precise orbital and planetary constraints despite the faint host star and long orbital period of $\sim 20.4$ days. With an equilibrium temperature of only 380 K, K2-419Ab is one of the coolest known well-characterized transiting planets. TOI-6034 has a late F-type companion about 40\arcsec~away, making it the first GEMS host star to have an earlier main-sequence binary companion. These confirmations add to the existing small sample of confirmed transiting GEMS., Comment: Accepted in AJ

We demonstrate nonlinearity-free transmission of Terabit/s/lambda PCS-64QAM signals through an HCF-based optical recirculating loop, which yields ~17.4% higher capacity than SMF-based loop under 23-dBm launch power (~13.5 dBm/channel) after 25 loops. Both lab experiment and field trial show HCF exhibits ~1.6-us/km lower latency than SMF., Comment: ECOC 2024 - 50th European Conference and Exhibition on Optical Communication Th1B.4 at 09:45am SC05: Optical transmission systems

Unlike coffee and cream that homogenize when stirred, growing micro-organisms (e.g., bacteria, baker's yeast) can actively kill each other and avoid mixing. How do such antagonistic interactions impact the growth and survival of competing strains, while being spatially advected by turbulent flows? By using numerical simulations of a continuum model, we study the dynamics of two antagonistic strains that are dispersed by incompressible turbulent flows in two spatial dimensions. A key parameter is the ratio of the fluid transport time to that of biological reproduction, which determines the winning strain that ultimately takes over the whole population from an initial heterogeneous state. By quantifying the probability and mean time for fixation along with the spatial structure of concentration fluctuations, we demonstrate how turbulence raises the threshold for biological nucleation and antagonism suppresses flow-induced mixing by depleting the population at interfaces. Our work highlights the unusual biological consequences of the interplay of turbulent fluid flows with antagonistic population dynamics, with potential implications for marine microbial ecology and origins of biological chirality., Comment: 7 pages, 4 figures