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In this whitepaper, we outline how recent technological advances and ongoing developments open qualitatively new science opportunities in cosmology, fundamental physics, and quantum astrophysics. First, intensity interferometry can contribute to one of the most foundational observables in cosmology: the expansion rate of the Universe. Its angular resolution allows it to resolve the angular extent of extragalactic objects such as supernovae or quasars; combined with a physical scale local to the source, this yields an angular diameter distance and hence a 'Hubble diagram'. Second, the nature of dark matter can be probed via the astrometric lensing signatures of tiny dark matter halos. Third, intensity interferometry gives direct access to second-order coherence properties of astrophysical emission, opening a window onto genuinely quantum aspects of astrophysical light.
Reversible addition-fragmentation chain transfer (RAFT) agents can be employed to control radical polymerization processes in the synthesis of anion-exchange membranes (AEMs) via radiation-induced grafting (RIG). However, the influence of the RAFT agent content on the performance of anion-exchange membrane fuel cells (AEMFCs) remains largely unexplored. Herein, we present a flexible method for AEM preparation that combines the radiation chemistry of polymers with RAFT polymerization. Low-density polyethylene (LDPE) films were simultaneously irradiated with vinylbenzyl chloride (VBC) monomer and RAFT agent to achieve rigorous control over the molecular weight of the grafted side chains. The incorporation of RAFT agent into the LDPE-grafted polymer chains significantly reduced the degree of grafting, and gel permeation chromatography (GPC) measurements confirmed the reduction in molecular weight. Cross-sectional Raman microscopy revealed that the RAFT protocol also improved graft homogeneity across the polymer matrix. Furthermore, the mechanical properties and surface morphology of the resulting AEMs were enhanced by the use of the RAFT method. The membranes were subsequently characterized in terms of ion-exchange capacity, water uptake, in-plane and through-plane swelling, thermal stability, and hydroxide conductivity. Single-AEMFC tests, as well as chemical stability measurements, demonstrated that RAFT-based AEMs maintained high performance (similar to 1.3 Wcm(-2)), while exhibiting a markedly lower IEC loss (similar to 30 %) compared to non-RAFT AEMs, thus contributing significantly to AEMFC stability.
We assess whether tabular foundation models can be used as off-the-shelf probabilistic photometric-redshift estimators for quasars in the 12-band S-PLUS DR6 survey, where colour-redshift degeneracies produce multi-modal posteriors and spectroscopic training sets are shifted relative to the photometric population. TabPFN 2.5, RealTabPFN 2.5, and TabICL are benchmarked against eight task-specific baselines, including linear conditional Gaussians, FlexZBoost, mixture-density networks, normalising flows, random forests, and gradient-boosted trees, with training sets from 500 to 121,626 quasars, using both density and point-prediction metrics, together with importance-weighted scores that approximate deployment on the photometric target sample. TabPFN 2.5 is best or statistically tied for best on all metrics except the unweighted CDE loss, on which the normalising flow is statistically tied and attains the lowest mean value; its largest gains occur for small training sets and in difficult regimes (very bright and faint sources, high redshift), while retaining near-nominal calibration under covariate shift. Its main practical cost is inference: with frozen weights, large support and target catalogues require substantial GPU/accelerator memory, and full-catalogue deployment may need support-set subsampling or distillation. SHAP attributions identify WISE W1/W2 as the strongest individual predictors, with UV and optical bands offering non-negligible refinements. We conclude that TabPFN 2.5 is a strong default for probabilistic quasar photo-z estimation, particularly when training data are limited or when calibration under covariate shift is critical.
Natural satellites are common around planets in our Solar system, suggesting that exosatellites are likely prevalent around extrasolar planets as well. Detecting these satellites, however, remains challenging due to observational limitations and the subtle photometric signals they produce. Transit Timing Variations (TTV) and Transit Duration Variations (TDV) offer indirect methods to detect exosatellite by measuring the gravitational influence of a satellite on its host planet. In this paper, we perform thousands of N-body numerical simulations of star-planet-satellite and star-planet-planet systems to characterize how to distinct signatures produced by satellite to those induced by a second planet. Our numerical results showed that TTV and TDV induced by satellite have identical oscillation periods and comparable amplitudes, whereas perturbations from additional planet generally produce signals with different TTV and TDV periods. In most planet-planet cases, the TDV period is larger than the TTV period, and the TTV amplitudes are overwhelmingly larger than the TDV amplitudes. Additionally, we investigate the influence of the physical and orbital parameters of both the planet and the satellite on the TTV and TDV signals. Our results are consistent with the equations present in the literature, which describe the dependence of the TTV and TDV amplitudes on system parameters. We further show that the TTV and TDV periods induced by a satellite are related to short-period perturbations in the oscillation of the planet's longitude of pericenter, as well as with variations in the semimajor axis and eccentricity of the planet-satellite barycenter.
Modeling the Milky Way stellar halo requires well-determined density and velocity anisotropy profiles. However, it has been challenging to gather a large sample of stars with six-dimensional data that extend beyond 40 kpc to map the outer halo. Our work investigates the velocity anisotropy in the Milky Way stellar halo with more than 10,000 blue horizontal-branch stars, combining Gaia astrometric data and spectroscopic data from SEGUE, DESI and LAMOST. This large sample allows us to obtain a detailed profile of up to $\sim$70 kpc. Radial velocities are predominant in the inner halo ($< 30$ kpc), and the anisotropy presents a smooth decrease before rapidly dropping to negative values, becoming dominated by tangential dispersion velocities. Removing the main known accreted structures of the Milky Way, makes the anisotropy profile radially-dominated at all radii. Our profile clearly shows an increase in the anisotropy from the center of the Galaxy, in accordance to the simulations. We also investigate the correlation of anisotropy with metallicity and with color. The lack of correlation between metallicity and anisotropy in our clean sample reinforces that this relation is driven by merger events. The initial exploration with color indicates a relation between kinematics and age, showing that older stars are dynamically colder and present less radial orbits than younger stars in the inner halo.
