The recent Planck Legacy 2018 release has confirmed the presence of an enhanced lensing amplitude in cosmic microwave background power spectra compared with that predicted in the standard Λ cold dark matter model, where Λ is the cosmological constant. A closed Universe can provide a physical explanation for this effect, with the Planck cosmic microwave background spectra now preferring a positive curvature at more than the 99% confidence level. Here, we further investigate the evidence for a closed Universe from Planck, showing that positive curvature naturally explains the anomalous lensing amplitude, and demonstrating that it also removes a well-known tension in the Planck dataset concerning the values of cosmological parameters derived at different angular scales. We show that since the Planck power spectra prefer a closed Universe, discordances higher than generally estimated arise for most of the local cosmological observables, including baryon acoustic oscillations. The assumption of a flat Universe could therefore mask a cosmological crisis where disparate observed properties of the Universe appear to be mutually inconsistent. Future measurements are needed to clarify whether the observed discordances are due to undetected systematics, or to new physics or simply are a statistical fluctuation. The standard cosmological model assumes a flat Universe, but some model inconsistencies appear when curvature is allowed, as supported by the latest Planck Legacy 2018 power spectra. Is it time to consider new physics?
China’s FY-3/4 satellite constellation has significantly advanced global environmental monitoring capabilities. However, the inherent temporal resolution limitations of polar-orbiting satellites result in discontinuous spatiotemporal coverage of current soil moisture products, thereby constraining their application in global hydrological modeling. To overcome this challenge, this study introduces a dedicated spatiotemporal reconstruction model that enhances the spatial continuity of FY-3B satellite soil moisture datasets. The proposed model utilizes a dual-channel input architecture integrating continuous observation data with dynamic mask matrix and leverages partial convolution for effective collaborative spatiotemporal feature extraction. Contextual attention and multilayer transformer encoder are incorporated to generate seamless global daily soil moisture product (2010–2019). Validation indicate notable improvements in accuracy: 1) in situ validation increased the mean correlation coefficient from 0.542 to 0.671 and reduce the root mean square error from 0.147 to 0.143 m<sup>3</sup>/m<sup>3</sup>; 2) temporal consistency analysis confirms that the reconstructed sequence remains highly synchronized with the original soil moisture products; 3) simulated missing region experiments yielded a coorelation of 0.953 with the original products, with a bias as low as –0.004 m<sup>3</sup>/m<sup>3</sup> and an unbiased root mean square error of 0.006 m<sup>3</sup>/m<sup>3</sup>. Compared to traditional partial convolution methods, this approach enhances global accuracy by increasing the correlation by 23.8%. Notably, this research marks the first implementation of a hybrid attention-partial convolution deep learning model to generate a seamless global daily soil moisture product derived from Fengyun satellites, effectively addressing previous reconstruction limitations.
Tetiana Amashukeli, L. Farfuliak, O. Haniiev
et al.
The Carpathian region of Ukraine plays a critical role in seismic monitoring due to its tectonic setting and proximity to the Vrancea Seismic Zone, which is known for its deep‑focus earthquakes. The regional seismic network across western Ukraine, covering the Carpathian and adjacent areas, currently comprises 22 stations, of which 5 are not operational, 18 stations continue to operate with Soviet‑era long‑ or short‑period sensors. Data from these stations are archived locally and are not publicly accessible. Five stations in the Carpathians (UT.BRIU, UT.KSV, UT.MEZ, UT.RAKU, UT.STNU) were recently upgraded with modern broadband sensors (deployed alongside the existing instruments) under the ORFEUS Data Integration Grant. This grant, funded through the Geo‑INQUIRE Project and supported by in‑kind contributions from GFZ Helmholtz Centre for Geosciences, GaiaCode, and CNRS Geoazur, provided instruments and technical support that strengthened the network and enabled the station upgrades between September 2024 and March 2025. Data from the upgraded stations are available in real time through the European Integrated Data Archive (EIDA) under the FDSN network code UT, Ukrainian National Seismic Network, and can be accessed via the National Institute for Earth Physics (NIEP) EIDA node in Romania. For the first time, data from Subbotin Institute of Geophysics seismic network have been integrated into EIDA, significantly improving data accessibility and fostering international collaboration. These stations also contribute to the AdriaArray initiative, providing a dense seismic network for monitoring the Adriatic Plate and its active margins. This paper discusses the background, current state, and recent advancements in the region’s seismic network, with a focus on the upgrade of selected stations.
Hoi Ming Lam, Torsten Geldsetzer, Stephen E. L. Howell
et al.
The snow cover on first-year sea ice is a critically underobserved parameter in the Arctic sea ice system, recognized by the World Meteorological Organization as an Essential Climate Variable due to its influence on energy exchange between the atmosphere and ocean through turbulent, radiative, and conductive processes. Measurements of snow properties are limited, but present and future satellite missions provide opportunities for regular and continuous monitoring. This study explores the sub-km- to km-scale spatial association between in-situ snow depth measurements, Cryo2ice satellite altimetric measurements, and RADARSAT Constellation Misson compact polarimetric (CP) synthetic aperture radar (SAR) parameters over snow-covered landfast first-year sea ice in the Canadian Arctic Archipelago. In-situ snow depth measurements were collected at four unique sites along a 75-km track of near-coincidental Cryo2ice acquisitions in early spring 2022. We find that the Cryo2ice-retrived elevation difference (altimetric snow depth) can provide an estimate of snow depth on sea ice that is within one standard deviation (∼6 to 14 cm) of the in-situ measured values, particularly where the snow salinity is concentrated in the basal snow layer (bottom 2 cm). A statistically significant correlation (−0.77 to −0.85; p<0.01) is found between CP SAR backscatter coefficients at C-band and altimetric backscatter coefficients at Ku-band, particularly where there is low snow depth and smooth ice surface topography. Inconsistent statistical relationships are found between altimetric snow depth and CP SAR backscatter parameters that vary with snow and ice topography observed at the in-situ measurement sites.
Accurate measurements of cosmic-ray fragmentation cross sections are essential for maximizing the physics potential of precise measurements of secondary and primary cosmic-ray fluxes from current balloon and space-borne experiments. NA61/SHINE, operating at the CERN SPS H2 beamline, is uniquely suited to studying these interactions at energies above 10 GeV/c per nucleon. In this contribution, we present the fragmentation cross sections for the breakup of carbon into $^{10}$B, $^{11}$B and $^{11}$C at 13.5 GeV/c per nucleon that are needed for interpreting the cosmic-ray boron-to-carbon ratio. These results are based on data from a pilot run conducted in 2018. We also give an overview of the high-statistics data-taking campaign in 2024, which covered projectile nuclei from lithium to silicon. With over 40 million recorded beam triggers, this data set will enable the reconstruction of the full reaction network required to study light secondary cosmic rays. Furthermore, we report on data collected in 2025 with a primary oxygen beam at 150 GeV/c per nucleon, aimed at verifying the expected flattening of fragmentation cross sections at high energies.
Solving inverse problems with the reverse process of a diffusion model represents an appealing avenue to produce highly realistic, yet diverse solutions from incomplete and possibly noisy measurements, ultimately enabling uncertainty quantification at scale. However, because of the intractable nature of the score function of the likelihood term (i.e., $\nabla_{\mathbf{x}_t} p(\mathbf{y} | \mathbf{x}_t)$), various samplers have been proposed in the literature that use different (more or less accurate) approximations of such a gradient to guide the diffusion process towards solutions that match the observations. In this work, I consider two sampling algorithms recently proposed under the name of Diffusion Posterior Sampling (DPS) and Pseudo-inverse Guided Diffusion Model (PGDM), respectively. In DSP, the guidance term used at each step of the reverse diffusion process is obtained by applying the adjoint of the modeling operator to the residual obtained from a one-step denoising estimate of the solution. On the other hand, PGDM utilizes a pseudo-inverse operator that originates from the fact that the one-step denoised solution is not assumed to be deterministic, rather modeled as a Gaussian distribution. Through an extensive set of numerical examples on two geophysical inverse problems (namely, seismic interpolation and seismic inversion), I show that two key aspects for the success of any measurement-guided diffusion process are: i) our ability to re-parametrize the inverse problem such that the sought after model is bounded between -1 and 1 (a pre-requisite for any diffusion model); ii) the choice of the training dataset used to learn the implicit prior that guides the reverse diffusion process. Numerical examples on synthetic and field datasets reveal that PGDM outperforms DPS in both scenarios at limited additional cost.
$ν$SpaceSim is a highly-efficient (e.g., fast) module-based, end-to-end simulation package that models the physical processes of cosmic neutrino interactions that leads to detectable signals for sub-orbital and space-based instruments. Starting with an input flux of neutrinos incident on a user-specified geometry in the Earth, the flux of Earth-emergent leptons are calculated followed by their subsequent extensive air showers (EAS). Next, the EAS optical Cherenkov and radio emission, signal attenuation to the detector, and the detector response are modeled to determine the sensitivity to both the diffuse cosmic neutrinos and transient neutrino sources. Using the Earth as a tau neutrino target and the atmosphere as the signal generator effectively forms a detector with a mega-gigaton mass. Furthermore, \taon decays and neutrino neutral-current interactions within the Earth (re)generates a flux of lower energy tau neutrinos that can also interact in the Earth thus enhancing the detection probability. $ν$SpaceSim provides a tool to both understand the data from recent experiments such as EUSO-SPB2 as well as design/understand the performance the next generation of balloon- and space-based experiments, including POEMMA Balloon with Radio (PBR) and the Payload for Ultrahigh Energy Observations (PUEO). In this paper the $ν$SpaceSim software, physics modeling, and the cosmic neutrino measurement capabilities of example sub-orbital and space-based experimental configurations are presented as well as status of planned modeling upgrades.
Deepak Tapriyal, Foad Haeri, Dustin Crandall
et al.
Abstract Carbon storage technology is primarily targeted in saline formations, which is a porous rock matrix filled with brine, sealed with a low permeability caprock. There are significant variations of CO2 wetting properties, typically reported in the literature as contact angle of CO2 and brine interacting with a rock material, suggesting that CO2 could become wetting under geostorage conditions and negatively impact containment effectiveness. Here, we performed the first controlled laboratory measurements of CO2‐brine contact angles on shale rocks from low permeability sealing formations with distinctive mineralogic properties—calcite‐rich, quartz‐rich, and dolomite‐rich. We targeted temperatures at 40° and 100°C, pressures at 8.3, 34.5, and 62.1 MPa, and salinity at 35,000 and 260,000 ppm. Results show no significant change in contact angle with mineralogy, temperature, pressure, salinity, and CO2 bubble size. We conclude that caprocks will remain water‐wet at geologic CO2 storage conditions and will not lose their capillary sealing capacity.
Nicholas C. Parazoo, Gretchen Keppel‐Aleks, Stanley Sander
et al.
Abstract Surface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink‐to‐source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season.
Riddhi Dave, Fiona Darbyshire, Juan Carlos Afonso
et al.
Abstract The Archean Superior craton was formed by the assemblage of continental and oceanic terranes at ∼2.6 Ga. The craton is surrounded by multiple Proterozoic mobile belts, including the Paleoproterozoic Trans‐Hudson Orogen which brought together the Superior and Rae/Hearne cratons at ∼1.9–1.8 Ga. Despite numerous studies on Precambrian lithospheric formation and evolution, the deep thermochemical structure of the Superior craton and its surroundings remains poorly understood. Here we investigate the upper mantle beneath the region from the surface to 400 km depth by jointly inverting Rayleigh wave phase velocity dispersion data, elevation, geoid height and surface heat flow, using a probabilistic inversion to obtain a (pseudo‐)3D model of composition, density and temperature. The lithospheric structure is dominated by thick cratonic roots (>300 km) beneath the eastern and western arms of the Superior craton, with a chemically depleted signature (Mg# > 92.5), consistent with independent results from mantle xenoliths. Beneath the surrounding Proterozoic and Phanerozoic orogens, the Mid‐continent Rift and Hudson Strait, we observe a relatively thinner lithosphere and more fertile composition, indicating that these regions have undergone lithospheric modification and erosion. Our model supports the hypothesis that the core of the Superior craton is well‐preserved and has evaded lithospheric destruction and refertilization. We propose three factors playing a critical role in the craton's stability: (a) the presence of a mid‐lithospheric discontinuity, (b) the correct isopycnic conditions to sustain a strength contrast between the craton and the surrounding mantle, and (c) the presence of weaker mobile belts around the craton.
We study the possibility of generating light Dirac neutrino mass via scotogenic mechanism where singlet-doublet fermion Dark Matter (DM) plays non-trivial role in generating one-loop neutrino mass, anomalous magnetic moment of muon: (g − 2)μ as well as additional relativistic degrees of freedom ∆Neff within reach of cosmic microwave background (CMB) experiments. We show that the Dirac nature of neutrinos can bring interesting correlations within the parameter space satisfying the (g − 2)μ, DM relic density and the effective relativistic degrees of freedom ∆Neff. While we stick to thermal singlet-doublet DM with promising detection prospects, both thermal and non-thermal origin of ∆Neff have been explored. In addition to detection prospects of the model at DM, (g − 2)μ and other particle physics experiments, it remains verifiable at future CMB experiments like CMB-S4 and SPT-3G.
M. Monelli, Eiichiro Komatsu, Tommaso Ghigna
et al.
Polarization of the cosmic microwave background (CMB) can help probe the fundamental physics behind cosmic inflation via the measurement of primordial B modes. As this requires exquisite control over instrumental systematics, some next-generation CMB experiments plan to use a rotating half-wave plate (HWP) as polarization modulator. However, the HWP non-idealities, if not properly treated in the analysis, can result in additional systematics. In this paper, we present a simple, semi-analytical end-to-end model to propagate the HWP non-idealities through the macro-steps that make up any CMB experiment (observation of multi-frequency maps, foreground cleaning, and power spectra estimation) and compute the HWP-induced bias on the estimated tensor-to-scalar ratio, r. We find that the effective polarization efficiency of the HWP suppresses the polarization signal, leading to an underestimation of r. Laboratory measurements of the properties of the HWP can be used to calibrate this effect, but we show how gain calibration of the CMB temperature can also be used to partially mitigate it. On the basis of our findings, we present a set of recommendations for the HWP design that can help maximize the benefits of gain calibration.
D. Anbajagane, Chihway L. Chang, Hayden Lee
et al.
Primordial non-Gaussianities (PNGs) are signatures in the density field that encode particle physics processes from the inflationary epoch. Such signatures have been extensively studied using the Cosmic Microwave Background, through constraining their amplitudes, fX NL, with future improvements expected from large-scale structure surveys; specifically, the galaxy correlation functions. We show that weak lensing fields can be used to achieve competitive and complementary constraints. This is shown via the Ulagam suite of N-body simulations, a subset of which evolves primordial fields with four types of PNGs. We create full-sky lensing maps and estimate the Fisher information from three summary statistics measured on the maps: the moments, the cumulative distribution function, and the 3-point correlation function. We find that the year 10 sample from the Rubin Observatory Legacy Survey of Space and Time (LSST) can constrain PNGs to σ(f NL eq) ≈ 110, σ(f NL or, lss) ≈ 120, σ(f NL loc) ≈ 40. For the former two, this is better than or comparable to expected galaxy clustering-based constraints from the Dark Energy Spectroscopic Instrument (DESI). The PNG information in lensing fields is on non-linear scales and at low redshifts (z ≲ 1.25), with a clear origin in the evolution history of massive halos. The constraining power degrades by ∼60% under scale cuts of ≳ 20 Mpc, showing there is still significant information on scales mostly insensitive to small-scale systematic effects (e.g., baryons). We publicly release the Ulagam suite to enable more survey-focused analyses.
We discuss the present state and planned updates of C osmo L attice, a cutting-edge code for lattice simulations of non-linear dynamics of scalar-gauge field theories in an expanding background. We first review the current capabilities of the code, including the simulation of interacting singlet scalars and of Abelian and non-Abelian scalar-gauge theories. We also comment on new features recently implemented, such as the simulation of gravitational waves from scalar and gauge fields. Secondly, we discuss new extensions of C osmo L attice that we plan to release publicly. We comment on new physics modules, which include axion-gauge interactions ϕFF~ , non-minimal gravitational couplings ϕ2R , creation and evolution of cosmic-defect networks, and magnetohydrodynamics. We also discuss new technical features, including evolvers for non-canonical interactions, arbitrary initial conditions, simulations in 2+1 dimensions, and higher-accuracy spatial derivatives.
The presence of axion strings in the Universe after recombination can leave an imprint on the polarization pattern of the cosmic microwave background radiation through the phenomenon of axion-string-induced birefringence via the hyperlight axion-like particle's coupling to electromagnetism. Across the sky, the polarization rotation angle is expected to display a patchwork of uniform regions with sharp boundaries that arise as the `shadow' of axion string loops. The statistics of such a birefringence sky map are therefore necessarily non-Gaussian. In this article we quantify the non-Gaussianity in axion-string-induced birefringence using two techniques, kurtosis and bispectrum, which correspond to 4- and 3-point correlation functions. If anisotropic birefringence were detected in the future, a measurement of its non-Gaussian properties would facilitate a discrimination across different new physics sources generally, and in the context of axion strings specifically, it would help to break degeneracies between the axion-photon coupling and properties of the string network.
Unanswered questions surrounding neutrinos have motivated investigations into physics beyond the standard model (SM) of particle physics. In particular, generalized neutrino interactions (GNI) provide a broader framework for studying these effects compared to the commonly studied non-standard neutrino interactions. These interactions are described by higher dimensional operators while maintaining the gauge symmetries of the SM. Furthermore, the cosmic neutrino background, a predicted component of the SM and standard cosmology, has yet to be directly detected. To shed light on this elusive phenomenon, we conduct a comprehensive analysis of the relevant GNI, specifically focusing on their implications for the proposed cosmic neutrino detector PTOLEMY. We make an attempt to see the capabilities and the limitations of PTOLEMY in sensing GNI while remaining optimistic regarding PTOLEMY's experimental resolution. These interactions play a significant role in modifying the electron spectrum resulting from the capture of cosmic neutrinos on radioactive tritium. This work also explores how the presence of these interactions influences the differential electron spectrum, taking into account factors such as finite experimental resolution, the mass of the lightest neutrino eigenstate, the strength of the interactions, and the ordering of neutrino mass.
The stochastic gravitational wave background (SGWB) offers a new opportunity to observe signals of primordial features from inflationary models. We study their detectability with future space-based gravitational waves experiments, focusing our analysis on the frequency range of the LISA mission. We compute gravitational wave spectra from primordial features by exploring the parameter space of a two-field inflation model capable of generating different classes of features. Fine-tuning in scales and amplitudes is necessary for these signals to fall in the observational windows. In some cases the scalar power spectrum can significantly exceed the ns=5 limit in single-field inflation and grow as fast as ns=9.1. Once they show up, several classes of frequency-dependent oscillatory signals, characteristic of different underlying inflationary physics, may be distinguished and the SGWB provides a window on dynamics of the primordial universe independent of cosmic microwave background and large-scale structure. To connect with future experimental data, we discuss two approaches of how the results may be applied to data analyses. First, we discuss the possibility of reconstructing the signal with LISA, which requires a high signal-to-noise ratio. The second more sensitive approach is to apply templates representing the spectra as estimators. For the latter purpose, we construct templates that can accurately capture the spectral features of several classes of feature signals and compare them with the SGWB produced by other physical mechanisms.