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Chemistry, Climate, and Transmission Spectra of TRAPPIST-1 e Explored with a Multimodel Sparse Sampled Ensemble
No full textTRAPPIST-1 e is one of a few habitable zone exoplanets that is amenable to characterization in the near term. In this study our motivations are both scientific and technical. Our technical goal is to establish a multimodel sparse sampled ensemble approach for coherently exploring large unconstrained parameter spaces typical in exoplanet science. Our science goal is to determine relationships that connect observations to the underlying climate across a large parameter space of atmospheric compositions for TRAPPIST-1 e. We consider atmospheric compositions of N₂, CO₂, CH₄, and H₂O, with water clouds and photochemical hazes. We use a 1D photochemical model, a 3D climate model, and a transmission spectral model, filtered through a quasi-Monte Carlo sparse sampling approach applied across atmospheric compositions. While clouds and hazes have significant effects on the transmission spectra, CO₂ and CH₄ can be potentially detected in ≤10 transits for certain compositional and climate states. Colder climates have better prospects for characterization, due to being relatively dry and having fewer clouds, permitting transmission observations to probe more deeply into their atmospheres. CH₄ volume mixing ratios of ≥10⁻³ trigger strong antigreenhouse cooling, where near-IR absorption simultaneously creates an inversion in the stratosphere and reduces the stellar radiation reaching the planet surface. In such cases, interpreting the disk-averaged emission and albedo at face value can yield misleading conclusions, as here low albedo and high thermal emission are associated with cold planets. Future work will use our sparse sampling approach to explore broader parameter spaces and other observationally amenable exoplanets.This material is based on work performed as part of the Consortium on Habitability and Atmospheres of M dwarf Planets (CHAMPs) team, supported by the National Aeronautics and Space Administration (NASA) under grant Nos. 80NSSC21K0905 and 80NSSC23K1399 issued through the Interdisciplinary Consortia for Astrobiology Research (ICAR) program. E.T.W. additionally acknowledges support from the NASA Habitable Worlds program grants 80NSSC20K1421 and 80NSSC21K1718. E.W.S. and M.L. additionally acknowledge support from the NASA Exoplanet Research Program via grant Nos. 80NSSC22K0235 and 80NSSC23K0039. Some computations were performed using the computer clusters and data storage resources of the UCR-HPCC, which were funded by grants from NSF (MRI-2215705, MRI-1429826) and NIH (1S10OD016290-01A1). T.J.F., R.K., and G.L.V. acknowledge support from the GSFC Sellers Exoplanet Environments Collaboration (SEEC), which is supported by the NASA Planetary Science Division’s Internal Scientist Funding Model. S.P. acknowledges support from NASA under award No. 80GSFC21M0002.https://iopscience.iop.org/article/10.3847/PSJ/ae031e/met
Testing Magnetic Field Configurations in Spider Pulsar PSR J1723-2837 with IXPE
No full textWe present the first X-ray polarimetry observations of a redback millisecond pulsar binary, PSR J1723-2837, with the Imaging X-ray Polarimetry Explorer (IXPE). Redbacks are compact binaries in which a rotation-powered millisecond pulsar interacts with a non-degenerate companion via an intrabinary shock, forming ideal laboratories for probing pulsar winds and relativistic shock physics, where ordered magnetic fields and particle acceleration shape the observed radiation. We conduct a spectro-polarimetric analysis combining IXPE data with archival Chandra, XMM-Newton, NuSTAR, and Swift observations. We explore two limiting magnetic field configurations, parallel and perpendicular to the bulk flow, and simulate their expected polarization signatures using the 3DPol radiative transport code. To account for the rapid rotation of the polarization angle predicted by these models, we implement a phase-dependent Stokes alignment procedure that preserves the polarization degree while correcting for phase-rotating PA. We also devise a new maximum-likelihood fitting strategy to determine the phase-dependence of the polarization angle by minimizing the polarization degree uncertainty. This technique shows a hint the binary may be rotating clockwise relative to the celestial north pole. We find no significant detection of polarization in the IXPE data, with PD ≲50% at 99% confidence level. Our results excludes the high-polarization degree scenario predicted by the perpendicular field model during the brightest orbital phase bin. Simulations show that doubling the current exposure would make the parallel configuration detectable. The new PA rotation technique is also applicable to IXPE data of many sources whose intrinsic PA variation is apriori not known but is strictly periodic.We thank George Younes, Kostas Kalapotharakos, and Jorges Cortes for helpful discussions. Z. W. and H.Z. acknowledge support by NASA under award numbers 80GSFC21M0002 and 80GSFC21M0006. Z. W., M. N, and S. B. were supported in part by NASA IXPE General Observer program grant 80NSSC25K7234. H.Z. also acknowledges support by NASA under award number 80NSSC24K1173. J.H. acknowledges support from NASA under award number 80GSFC21M0002. Simulations were carried out on the NASA Pleiades cluster and NERSC Perlmutter cluster. This research has made use of data and software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC), which is a service of the Astrophysics Science Division at NASA/GSFC and the High Energy Astrophysics Division of the Smithsonian Astrophysical Observatory, and the NuSTAR Data Analysis Software (NuSTARDAS), jointly developed by the ASI Space Science Data Center (SSDC, Italy) and the California Institute of Technology (Caltech, USA). The work presented is based in part on observations with XMM-Newton, an ESA Science Mission with instruments and contributions directly funded by ESA Member states and NASA. This research has made use of data from the NuSTAR mission, a project led by Caltech, managed by the Jet Propulsion Laboratory, and funded by NASA. This work made use of Neil Gehrels Swift Observatory data supplied by the UK Swift Science Data Centre at the University of Leicester. This research has made use of data obtained from the Chandra Data Archive and software provided by the Chandra X-ray Center (CXC) in the application package CIAO. This work has relied on the NASA Astrophysics Data systemhttp://arxiv.org/abs/2509.0524
A Drag-force Analysis of Solar Wind White-light Tracers in the Inner Heliosphere
No full textWe studied the propagation of blobs, which are a subset of density mesoscale structures observed in the solar corona. The detection of blobs in white-light data was performed during Solar Cycle 23. Blobs are tracers of the solar wind and an important source of its variability. We analyzed the deprojected blob radial elongation and kinematics as they evolved in the inner heliosphere using a dynamical “drag-force” model. We characterized 13 blob-like structures detected by Large Angle Spectrometric Coronagraph and SECCHI coronagraphs aboard Solar and Heliospheric Observatory and Solar TErrestrial RElations Observatory, respectively. We applied, for the first time, analysis techniques that were typically used for coronal mass ejections to these compact plasma blobs that seem to propagate “passively” with the solar wind. This is the first time that the mass of blobs has been reported, with a mean value of 3.32 ± 0.19 × 10¹² g. In addition, blobs show a mean radial expansion rate of 1.10 ± 0.96 × 10⁻¹ R⊙ hr⁻¹. We assumed that the blob movement is governed by a force that is active at a heliocentric distance ~5 R⊙, “dragging” blobs near the Sun outward until they reached a mean final velocity of 427 ± 55 km s⁻¹ at ~15 R⊙. According to the physical parameters involved in this “drag-force” model, the best estimate of the dynamic viscosity of the ambient solar wind is 1.27 ± 0.98 × 10⁻⁴ g cm⁻¹ s⁻¹. This is also the first time that this crucial parameter for aerodynamical studies has been reported close to the Sun.The authors thank Steven R. Cranmer, A. Borgazzi, and Nicholeen Viall for helpful discussions. C.L.P. acknowledges support from the NASA–Goddard Space Flight Center Heliophysics Internal Scientist Funding Model (HISFM; competitive work package) and the Center for Astrophysics | Harvard & Smithsonian’s Visiting Researcher Program. M.P.M. is supported by National Aeronautics and Space Administration (NASA) grants 80NSSC20K1445 and 80NSSC21K0725 to the Smithsonian Astrophysical Observatory. A.L. was supported by DGAPAPAPIIT IN110511-3.https://iopscience.iop.org/article/10.3847/1538-4357/adf4d
Parallel regulatory circuits orchestrate biofilm formation in response to c-di-GMP levels and growth phase
No full textBiofilm formation is a highly regulated process that contributes to the environmental fitness of microorganisms, including pathogenic bacteria. The second messenger c-di-GMP is a critical regulator of biofilm formation whose cellular levels are tightly regulated by the abundance and activity of diguanylate cyclases (DGCs) and phosphodiesterases (PDEs). These enzymes synthesize and degrade c-di-GMP, respectively. The Vibrio cholerae VpvABC system encodes a DGC and is critical for biofilm formation; however, much remains unknown about its regulation. Here we demonstrate that the vpvABC system is transcriptionally regulated by c-di-GMP and the master biofilm regulators VpsT and VpsR. However, we also identify the alternative sigma factor RpoS as a positive regulator of vpvABC. RpoS is involved in the regulation of many c-di-GMP metabolism genes and plays a role in biofilm architecture, likely mediated in part through vpvC. In mature biofilms, vpvA transcription was highest near the biofilm substratum and VpsT, VpsR, and RpoS were critical for vpvABC transcription. Overall, our genetic dissection reveals the vpvABC system is regulated by two parallel circuits: a c-di-GMP sensing-circuit acting through VpsT and VpsR and a stationary growth phase circuit via RpoS. These findings underscore the multilayered regulatory mechanisms that precisely govern biofilm formation by a pathogen.This work was supported by NIAID NIH HHS/United States R01AI102584 to F.H.Y and NIH IS10 OD023528 to F.H.Y. G.K. and M.A.T were supported in part by ARCS (Achievement Rewards for College Scientists Fellowship). The funders had no role in study design, data collection and analysis, the decision to publish, or the preparation of the manuscript.https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.101187
Learning What Matters: Causal Time Series Modeling for Arctic Sea Ice Prediction
No full textInternational Joint Conferences on Artificial Intelligence,August 16 - 22, 2025,Montreal, CanadaConventional machine learning and deep learning models typically rely on correlation-based learning, which often fails to distinguish genuine causal relationships from spurious associations, limiting their robustness, interpretability, and ability to generalize. To overcome these limitations, we introduce a causality-aware deep learning framework that integrates Multivariate Granger Causality (MVGC) and PCMCI+ for causal feature selection within a hybrid neural architecture. Leveraging 43 years (1979-2021) of Arctic Sea Ice Extent (SIE) data and associated ocean-atmospheric variables at daily and monthly resolutions, the proposed method identifies causally influential predictors, prioritizes direct causes of SIE dynamics, reduces unnecessary features, and enhances computational efficiency. Experimental results show that incorporating causal inputs leads to improved prediction accuracy and interpretability across varying lead times. While demonstrated on Arctic SIE forecasting, the framework is broadly applicable to other dynamic, high-dimensional domains, offering a scalable approach that advances both the theoretical foundations and practical performance of causality-informed predictive modeling.This work is supported by iHARP: NSF HDR Institute for Harnessing Data and Model Revolution in the Polar Regions (Award# 2118285). The views expressed in this work do not necessarily reflect the policies of the NSF, and endorsement by the Federal Government should not be inferred.http://arxiv.org/abs/2509.0912
Exploring SEP Transport in Widespread Events with Different Heliospheric Current Sheet Models
No full textUnderstanding solar energetic particle transport in wide-longitude events remains a significant question in heliophysics. By utilizing the increasing number of available observers at various heliographic distances and longitudes, such as Parker Solar Probe and Solar Orbiter, we are able to further our understanding of these widespread events. This study presents 3D test particle modeling of three widespread events during the Parker era, each detected by at least four observers. The role of the heliospheric current sheet (HCS) in transporting particles to the wide longitudes observed in these events is evaluated. A newly updated and more sophisticated HCS model is used, incorporating three different configurations derived from the Wilcox Solar Observatory, Air Force Data Assimilative Photospheric Flux Transport, and Solar Dynamics Observatory/Helioseismic and Magnetic Imager (HMI) data (via Predictive Science, PSI) for each event. The modeled proton flux profiles at each observer location are compared against energetic proton measurements for each HCS configuration. We find that inclusion of the HCS is essential to reproduce both the wide longitudinal spread of particles and the observed flux profiles in all three events. For events with longitudinal separations exceeding 100°, the most intense fluxes, both observed and modeled, are associated with observers located nearest to the HCS. This is observed for the 2023 March 13 event, where two observers were located closer in longitude and radial distance than other observers to the source region, yet observed no solar energetic particle signatures due to their lack of proximity to the HCS. Among the three configurations, the HMI-PSI-derived HCS consistently yields the best agreement between observed and modeled flux profiles.This research is supported by the NASA Living With a Star Jack Eddy Postdoctoral Fellowship Program, administered by UCAR’s Cooperative Programs for the Advancement of Earth System Science (CPAESS) under award 80NSSC22M0097. S.D. acknowledges support from the UK STFC (grant ST/ Y002725/1)https://iopscience.iop.org/article/10.3847/1538-4357/adf8d
Observations and simulations of decay phases of Solar Energetic Particle events
No full text39th International Cosmic Ray Conference (ICRC2025),July 15-24,2025,Geneva, SwitzerlandThe properties of solar energetic particle (SEP) event profiles have been researched extensively to investigate the acceleration and transport of SEPs. The effects on SEP intensity profiles of particle-filled magnetic flux tubes corotating with the Sun are generally considered to be negligible. However, corotation has recently been suggested to have an effect on SEP decay phases, based on results of test particle simulations. This is expected to be dependent on the location of the observer with respect to the active region (AR) associated with the event. To determine if corotation effects are discernible in observations, we analyse multi-spacecraft observations of SEP intensity profiles from 11 events between 2020 and 2022, using data from Solar Orbiter, Parker Solar Probe, STEREO-A, and SOHO. We also aim to study how the properties of the flares and coronal mass ejections (CMEs) associated with the events affect the parameters of the decay phase. Using 3 energy channels; electrons ∼1 MeV, protons ∼25 MeV, and protons ∼60 MeV, we derive the decay time constant, τ, and study the dependence of τ on the longitudinal separation, Δϕ, between the source active region and the spacecraft’s magnetic footpoint on the Sun. We find that within individual events there is a tendency for τ to decrease with increasing Δϕ: test particle simulations show that this is a signature of corotation, not present when the latter is neglected. Thus we conclude that corotation has an effect on the decay phase of an SEP event and should be included in simulations and interpretations of these events. We characterise the magnitude of the solar event that produced the SEPs using the intensity of the associated flare, speed of the associated coronal mass ejection and SEP peak flux as proxies. Our results show that the magnitude of the solar event influences the measured τ values and are likely the cause of the observed large inter-event variability, along with varying solar wind and interplanetary magnetic field conditions. Further we introduce a new methodology to incorporate turbulence-induced perpendicular scattering within 3D test particle simulations in an approximate way. At randomly generated times the particle’s position is displaced in the direction perpendicular to the interplanetary magnetic field according to a prescribed distribution. In future work we will compare the results of simulations including this implementation of perpendicular scattering with those that neglect it, with emphasis on differences in the decay phase and on how corotation effects vary between the two types of simulations.We acknowledge that the data analysis in these proceedings are based on the paper by the same authors, DOI: 10.1051/0004-6361/202453012 [20]. R.H. acknowledges funding from the Moses Holden Studentship for her PhD and funding from the Royal Astronomical Society for attendance at the ICRC 2025. T.L. and S.D. acknowledge support from the UK Science and Technology Facilities Council (STFC) through grants ST/V000934/1 and ST/Y002725/1. A.H. would like to acknowledge support from the University of Maryland Baltimore County (UMBC), the Partnership for Heliophysics and Space Environment Research (PHaSER), and NASA/GFSC. We acknowledge use of solar energetic particle data from the SOHO, STEREO-A, Solar Orbiter and PSP spacecraft and thank the instrument teams for their work on making the data available and science-ready. Solar Orbiter is a mission of international cooperation between ESA and NASA, operated by ESA. Thanks to the Integrated Science Investigation of the Sun (IS?IS) Science Team (PI: David McComas, Princeton University), and the Energetic Particle Detector (EPD) Team (PI: Javier Rodríguez-Pacheco, University of Alcalá, Spain). We acknowledge use of SERPENTINE tools, which were developed with funding from the European Union’s Horizon 2020 research and innovation program, and of the Solar-MACH tool. The use of the data made available via the NSSDC CDAWeb is acknowledged.https://pos.sissa.it/501/1302
The Crock of Shh: A Whispering Water Interface for Reshaping Reality
No full text27th International Conference on Multimodal Interaction,October 13 - 17, 2025,Canberra,AustraliaThe Crock of Shh is a water dispenser interface designed for typing messages to water. Instead of dispensing water quickly, users must press the nozzle repeatedly to scroll through whispered positive words representing letters of the alphabet. Each short press releases a small amount of water, slowing the process and creating time for reflection. Users listen to the whispered words by placing their ear near the water tank, which resonates the sounds through an audio exciter. Four buttons on the interface allow users to scroll forward or backward through the spelling alphabet, select letters, insert spaces, and print messages on a Dymo label printer. The printed labels, in black ink on transparent material, can be attached to a water cup or the dispenser jug. The printed labels transmit positive messages, fostering a connection between the user and the water. The work builds on ideas of slow technology, embodied interaction, and placebo effects.https://dl.acm.org/doi/10.1145/3716553.375708
SLA-MORL: SLA-Aware Multi-Objective Reinforcement Learning for HPC Resource Optimization
No full textDynamic resource allocation for machine learning workloads in cloud environments remains challenging due to competing objectives of minimizing training time and operational costs while meeting Service Level Agreement (SLA) constraints. Traditional approaches employ static resource allocation or single-objective optimization, leading to either SLA violations or resource waste. We present SLA-MORL, an adaptive multi-objective reinforcement learning framework that intelligently allocates GPU and CPU resources based on user-defined preferences (time, cost, or balanced) while ensuring SLA compliance. Our approach introduces two key innovations: (1) intelligent initialization through historical learning or efficient baseline runs that eliminates cold-start problems, reducing initial exploration overhead by 60%, and (2) dynamic weight adaptation that automatically adjusts optimization priorities based on real-time SLA violation severity, creating a self-correcting system. SLA-MORL constructs a 21-dimensional state representation capturing resource utilization, training progress, and SLA compliance, enabling an actor-critic network to make informed allocation decisions across 9 possible actions. Extensive evaluation on 13 diverse ML workloads using production HPC infrastructure demonstrates that SLA-MORL achieves 67.2% reduction in training time for deadline-critical jobs, 68.8% reduction in costs for budget-constrained workloads, and 73.4% improvement in overall SLA compliance compared to static baselines. By addressing both cold-start inefficiency and dynamic adaptation challenges, SLA-MORL provides a practical solution for cloud resource management that balances performance, cost, and reliability in modern ML training environments.http://arxiv.org/abs/2508.0350
The Fight to End Food Insecurity Through Community Gardens and the Spaces They Create
No full textThis study investigated the role of community gardens in addressing food insecurity, fostering sociocultural interactions, and providing educational opportunities in a Maryland county. Using semi-structured interviews, sentence completion activities, and a focus group, the lived experiences of 16 participants involved in two community gardens, one urban and one suburban, were explored. Participants from diverse racial and employment backgrounds highlight the inclusivity and evolving role of community gardens as multimodal spaces that blend physical and theoretical domains. Participants shared how these spaces offer not only fresh, affordable produce but also a sense of belonging, opportunities for collaboration, and platforms for cultural exchange. Key themes included sustainability, inclusivity, and the importance of food preservation. Participants emphasized the need for greater access to preservation education and broader inclusion within community gardens. Gardens emerged as dynamic environments that support not only individual well-being but also community resilience and environmental stewardship. Implications suggest that integrating educational programming into community gardens can strengthen their role in addressing systemic challenges like food insecurity and cultural disconnection. By supporting experiential learning, intergenerational knowledge sharing, and inclusive design, these spaces can bridge gaps in food access and promote equitable, sustainable communities. Study findings offer practical insights and recommendations for expanding educational opportunities, fostering inclusivity, and supporting policy initiatives that position community gardens as vital resources in the fight against food insecurity and the pursuit of community empowerment