PLATO is designed to detect Earth-sized exoplanets around solar-type stars and to measure their radii with accuracy better than \(2\%\) via the transit method. Charge transfer inefficiency (CTI), a by-product of radiation damage to CCDs, can jeopardise this accuracy and therefore must be corrected. We assessed and quantified the impact of CTI on transit-depth measurements and developed a correction strategy that restores CTI-biased depths within the accuracy budget. Using a calibration dataset generated with PLATOSim to simulate a realistic stellar field, we modelled the parallel overscan signal as a sum of exponential decays and used least-squares fitting to infer the number of trap species and initial estimates for the release times (\(τ_{r,k}\)). Smearing was modelled with an exponential-plus-constant function and removed on a column-wise basis. We modelled the spatial variation in trap density with a quadratic polynomial in radial distance from the focal-plane center. The polynomial coefficients (\(a_{p,k}\)), the well-fill power index (\(β\)), and the release times (\(τ_{r,k}\)) were adjusted via an iterative application of the extended pixel edge response (EPER) method combined with a CTI correction algorithm, yielding the final calibration model. In the worst-case scenario (8-year mission, high-CTI zone), CTI induced a bias of about \(4\%\) in measured transit depth, reduced to a residual of \(0.06\%\) after correction - well within PLATO's accuracy requirements. From the calibrated parameters, we derived a correction scheme that brought the photometric measurements within PLATO's noise budget, ensuring that the mission's precision requirements are met.

Recent work has developed a formalism for computing angular power spectra directly from catalogues containing field values at discrete positions on the sky, thereby circumventing the need to create pixelised maps of the fields, as well as avoiding aliasing and finite-resolution effects. We adapt this formalism to incorporate template deprojection for mitigating systematic biases in the measured angular power spectra. We also introduce an alternative method of mitigating the `deprojection bias' - the loss of modes induced by deprojection - employing simple simulations to compute a transfer function. We find that this approach performs at least as well as existing methods, and is relatively insensitive to how well one can guess the true power spectrum of the observed field, except at the largest scales ($\ell \lesssim 3$). Additionally, we develop exact expressions for the bias introduced by deprojection in the shot-noise component, which further improves the accuracy of this approach. We test our formalism on simulated datasets, demonstrating its applicability both to discretely sampled fields, and to the special case of galaxy clustering, with the survey selection function defined in terms of a random catalogue or as a continuous sky map. After removing the bias in the shot noise and correcting for the remaining mode loss using a transfer function, our formalism produces unbiased measurements of the angular power spectrum in all scenarios tested here. Finally, we apply our formalism to real data and show it produces results consistent with the standard map-based pseudo-$C_\ell$ formalism. We implement our method in the public code NaMaster.

The SUB-Millicharge ExperimenT (SUBMET) investigates an unexplored parameter space of millicharged particles with mass $m_χ< $ 1.6 GeV/c$^2$ and charge $Q_χ< 10^{-3}e$. The detector consists of an Eljen-200 plastic scintillator coupled to a Hamamatsu Photonics R7725 photomultiplier tube (PMT). PMT afterpulses, delayed pulses produced after an energetic pulse, have been observed in the SUBMET readout system, especially following primary pulses with a large area. We present a prediction method for afterpulse rates based on measurable parameters, which reproduces the observed rate with approximately 20\% precision. This approach enables a better understanding of afterpulse contributions and, consequently, improves the reliability of background predictions.

This paper explores how time-varying increases in mass accretion onto rapidly spinning black holes influence their long-term spin evolution when affected by superradiance - a process where energy is extracted from the black hole by a surrounding axion field. Using simulations the study tracks how sudden accretion boosts affect a critical spin-down phase (the superradiance drop) during which the black hole's spin rapidly decreases while its mass remains nearly constant. The black hole spin evolution is controlled by the competition between two processes: how fast angular momentum is added through accretion, and how fast it is removed by the axion cloud. One major conclusion is that boosts to the accretion rate before the superradiance drop have the strongest effect, as they can delay or reshape the drop and significantly shrink the region of the mass-spin plane depopulated due to the superradiance. In particular, a super-Eddington accretion rate of 5 times Eddington accretion, lasting for 4 Myr and occurring 30 Myr before the superradiance drop can reduce the superradiance exclusion region in the mass-spin plane by 40 percent. In contrast, boosts to the accretion rate after the superradiance drop only cause temporary changes in the black hole spin. The study also shows that black holes with lighter axion clouds are more sensitive to these early boosts and can show observable spin changes lasting tens to hundreds of millions of years. Heavier axion clouds, however, require much stronger or longer-lasting boosts to produce similar effects, making them more stable under variable accretion.

We introduce a novel approach to estimate the spectral index, $β_s$, of polarised synchrotron emission, combining the moment expansion of CMB and the constrained-ILC. We reconstructed the maps of the first two synchrotron moments, combining multi-frequency data, and applied the `T-T plot' technique between two moment maps to estimate the synchrotron spectral index. This approach offers a new technique for mapping the foreground spectral parameters, complementing the model-based parametric component separation methods. Applying this technique, we derived a new constraint on the spectral index of polarised synchrotron emission using QUIJOTE MFI wide-survey 11 and 13 GHz data, Wilkinson Microwave Anisotropy Probe data at K and Ka bands, and Planck LFI 30 GHz data. In the Galactic plane and North Polar Spur regions, we obtained an inverse-variance-weighted mean synchrotron index of $β_s = -3.11$ with a standard deviation of $0.21$ due to intrinsic scatter, consistent with previous results based on parametric methods using the same dataset. We find that the inverse-variance-weighted mean spectral index, including both statistical and systematic uncertainties, is $β_s^{\rm plane} = -3.05 \pm 0.01$ in the Galactic plane and $β_s^{\rm high\text{-}lat} = -3.13 \pm 0.02$ at high latitudes, indicating a moderate steepening of the spectral index from low to high Galactic latitudes. Our analysis indicates that, within the current upper limit on the Anomalous Microwave Emission polarisation fraction, our results are not subject to any appreciable bias. Furthermore, we infer the spectral index over the entire QUIJOTE survey region, partitioning the sky into 21 patches. This technique can be further extended to constrain the synchrotron spectral curvature by reconstructing higher-order moments when better-quality data become available.

With the ever faster cadence of untargeted surveys of the sky, the supernova (SN) community will capture in the coming years a growing number of shock breakouts in red-supergiant (RSG) stars. Expecting a high frequency of breakouts within circumstellar material (CSM), we have produced an extended, regular and cubic grid of models covering from low- to high-energy explosions, compact to extended CSM, moderate- to high-density CSM. Here, we document the main results from the radiation-hydrodynamics and nonlocal thermodynamic equilibrium radiative-transfer calculations over the first 15d of evolution, including the bolometric and multi-band light curves and the salient features from spectra. As before, CSM interaction is found to boost the UV brightness and shorten the optical rise time if compact. Higher ionization (e.g., as seen with OVI3820A) is obtained for more compact CSM, and is maximum for explosions in a vacuum. CSM interaction also diversifies the spectral evolution as seen in line profile morphology, with electron-scattering broadening dominating during the IIn phase. In the absence of CSM, Doppler broadening dominates immediately after shock breakout and leads to strongly blueshifted emission in lines such as HeII4686A or CIV5805A. This treasury of models will be used to analyze as well as predict future observations of RSG shock breakouts in CSM.

We compare the performance of the flat-sky approximation and Limber approximation for the clustering analysis of the photometric galaxy catalogue of Euclid. We study a 6 bin configuration representing the first data release (DR1) and a 13 bin configuration representative of the third and final data release (DR3). We find that the Limber approximation is sufficiently accurate for the analysis of the wide bins of DR1. Contrarily, the 13 bins of DR3 cannot be modelled accurately with the Limber approximation. Instead, the flat-sky approximation is accurate to below $5\%$ in recovering the angular power spectra of galaxy number counts in both cases and can be used to simplify the computation of the full power spectrum in harmonic space for the data analysis of DR3.

Regardless of model and platform details, the critical phenomena exhibit universal behaviors that are remarkably consistent across various experiments and theories, resulting in a significant scientific success of condensed matter physics. One widely known and commonly used example is the 2D quantum Hall transition; yet, its universal exponents still somewhat conflict between experiments, theoretical models, and numerical ansatzes. We study critical behaviors of quasi-2D Weyl semimetal systems with a finite thickness $L_z>1$, disorder, and external magnetic field $B_z$. By analyzing the scaling behaviors of the localization lengths and local density of states using recursive methods, we find that the finite thickness yields a deviation from the 2D quantum Hall universality ($L_z=1$ case) and a crossover toward the 3D Gaussian Unitary Ensemble ($L_z\rightarrow \infty$ limit), potentially offering another cause of the discrepancy. Our work demonstrates the often-overlooked importance of auxiliary degrees of freedom, such as thickness, and that 3D quantum Hall physics is not merely a trivial finite-thickness extension of its 2D counterpart.

Our ability to infer the true source properties of colliding black holes from gravitational wave observations requires not only accurate waveform models but also their correct use. A key property when evaluating time-domain models is when to start the waveform: choosing a time that is too late can omit low-frequency power from higher order multipoles. By focusing on binary systems with total mass $\ge 200 \, M_{\odot}$, we show that current detectors are sensitive to this missing power and biased source properties can be obtained. We show that for systems with total mass $\lesssim 300 \, M_{\odot}$, mass ratio $\gtrsim 0.33$, and signal-to-noise ratio $ρ\gtrsim 20$, templates starting at $20 \, \mathrm{Hz}$ recover biased source properties. As the total mass increases, and the component masses become more asymmetric, templates starting from $13 \, \mathrm{Hz}$ recover biased properties. If the gravitational-wave signal is observed at signal-to-noise ratio $ρ< 20$, time-domain models can start from $20\, \mathrm{Hz}$ as statistical uncertainties dominate.

Nebular phase kilonovae (KNe) have significant infra-red (IR) emission thought to be mostly forbidden emission lines from rapid neutron capture (r-process) species in neutron star merger ejecta. Lanthanide elements in particular have complex, open f-shell atomic structures with many IR transitions. Using non-local thermodynamic equilibrium (NLTE) radiative transfer simulations, we explore the impact of lanthanides on the IR spectra of KNe in the nebular phase, exploring a parameter space of ejecta mass and lanthanide fraction. We find that lanthanide impact is greater at higher densities, corresponding to earlier epochs and greater ejecta masses. The wavelengths most affected are found to be $λ\lesssim 4~μ$m, with the species Ce\,\textsc{iii} and Nd \textsc{ii} being the most important contributors to spectral formation. We also find significant emission from species proposed in observations, notably Te\,\textsc{iii} at 2.1 $μ$m, and Se\,\textsc{iii} at 4.5 and 5.7 $μ$m, while W\,\textsc{iii} is subdominant at 4.5 $μ$m. The Te\,\textsc{iii} feature at 2.1 $μ$m is always blended, particularly with Zr\,\textsc{ii}, Ce\,\textsc{iii}, and Nd\,\textsc{ii}. We do not reproduce the smooth blackbody-like continua observed in AT2023vfi. Based on our results, we argue that line opacity alone is likely insufficient to produce optically thick continua in the nebular phase, even in the case of lanthanide/actinide-rich ejecta, as our models are optically thin in the IR at these epochs. Given that lanthanide contributions are dominant below 4 $μ$m, we suggest that NIR observations best probe these elements, while MIR spectroscopy with \textit{JWST} can reliably probe non-lanthanide emission even in relatively lanthanide-rich cases.

Polycyclic Aromatic Hydrocarbons (PAHs) constitute a significant fraction of the Universe's carbon budget, playing a key role in the cosmic carbon cycle and dominating the mid-infrared spectra of astrophysical environments in which they reside. Although PAHs are known to form in the circumstellar envelopes of post-AGB stars, their formation and evolution are still not well-understood. We aim to understand how pristine complex hydrocarbons and PAHs in circumstellar environments transition to the PAHs observed in the ISM. The mid-infrared PAH spectra (5-18 micron) of the planetary nebula, NGC 7027, are investigated using spectral cubes from JWST MIRI-MRS. We report the first detection of spatially-resolved variations of the PAH spectral profiles across class A, AB, and B in all major PAH bands (6.2, 7.7, 8.6, and 11.2 micron) within a single source, NGC 7027. These variations are linked to morphological structures within NGC 7027. Clear correlations are revealed between the 6.2, 7.7, and 8.6 micron features, where the red components (6.26, 7.8, 8.65 micron) exhibit a strong correlation and the same is found for the blue components of the 6.2 and 7.7 (6.205 and 7.6 micron). The blue component of the 8.6 (8.56 micron) appears to be independent of the other components. We link this behaviour to differences in molecular structure of their PAH subpopulations. Decomposition of the 11.2 micron band confirms two previously identified components, with the broader 11.25 micron component attributed to emission from very small grains of PAH clusters rather than PAH emission. We show that PAH profile classes generally vary with proximity to the central star's UV radiation field, suggesting class B PAHs represent more processed species while class A PAHs remain relatively pristine, challenging current notions on the spectral evolution of PAHs.

In complex production lines, it is essential to have strict, fast-acting rules to determine whether the system is In Control (InC) or Out of Control (OutC). This study explores a bio-inspired method that digitally mimics ant colony behavior to classify InC/OutC states and forecast imminent transitions requiring maintenance. A case study on industrial potato chip frying provides the application context. During each two-minute frying cycle, sequences of eight temperature readings are collected. Each sequence is treated as a digital ant depositing virtual pheromones, generating a Base Score. New sequences, representing new ants, can either reinforce or weaken this score, leading to a Modified Base Score that reflects the system's evolving condition. Signals such as extreme temperatures, large variations within a sequence, or the detection of change-points contribute to a Threat Score, which is added to the Modified Base Score. Since pheromones naturally decay over time unless reinforced, an Environmental Score is incorporated to reflect recent system dynamics, imitating real ant behavior. This score is calculated from the Modified Base Scores collected over the past hour. The resulting Total Score, obtained as the sum of the Modified Base Score, Threat Score, and Environmental Score, is used as the main indicator for real-time system classification and forecasting of transitions from InC to OutC. This ant colony optimization-inspired approach provides an adaptive and interpretable framework for process monitoring and predictive maintenance in industrial environments.

Qudits offer significant advantages over qubit-based architectures, including more efficient gate compilation, reduced resource requirements, improved error-correction primitives, and enhanced capabilities for quantum communication and cryptography. Yet, one of the most promising families of quantum error correction codes, namely quantum low-density parity-check (LDPC) codes, have so far been mostly restricted to qubits. Here, we generalize recent advancements in LDPC codes from qubits to qudits. We introduce a general framework for finding qudit LDPC codes and apply our formalism to several promising types of LDPC codes. We generalize bivariate bicycle codes, including their coprime variant; hypergraph product codes, including the recently proposed La-cross codes; subsystem hypergraph product (SHYPS) codes; high-dimensional expander codes, which make use of Ramanujan complexes; and fiber bundle codes. Using the qudit generalization formalism, we then numerically search for and decode several novel qudit codes compatible with near-term hardware. Our results highlight the potential of qudit LDPC codes as a versatile and hardware-compatible pathway toward scalable quantum error correction.

This is the second paper in the HOWLS (higher-order weak lensing statistics) series exploring the usage of non-Gaussian statistics for cosmology inference within Euclid. With respect to our first paper, we develop a full tomographic analysis based on realistic photometric redshifts that allows us to derive Fisher forecasts in the ($σ_8$, $w_0$) plane for a Euclid-like data release 1 (DR1) setup. We find that the five higher-order statistics (HOS) that satisfy the Gaussian likelihood assumption of the Fisher formalism (one-point probability distribution function, $\ell$1-norm, peak counts, Minkowski functionals, and Betti numbers) each outperform the shear two-point correlation functions by a factor of $2.5$ on the $w_0$ forecasts, with only marginal improvement when used in combination with two-point estimators, suggesting that every HOS is able to retrieve both the non-Gaussian and Gaussian information of the matter density field. The similar performance of the different estimators is explained by a homogeneous use of multi-scale and tomographic information, optimized to lower computational costs. These results hold for the three mass mapping techniques of the Euclid pipeline, aperture mass, Kaiser--Squires, and Kaiser--Squires plus, and they are unaffected by the application of realistic star masks. Finally, we explored the use of HOS with the Bernardeau--Nishimichi--Taruya (BNT) nulling scheme approach, finding promising results toward applying physical scale cuts to HOS.

We argue that interacting conformal line defects in free quantum field theories can exist, provided that inversion symmetry is broken. Important for our demonstration is the existence of a special cross ratio for bulk-defect-defect three point functions that is invariant under the conformal group but picks up a sign under inversion. We examine the particular case of a free scalar field in detail, and provide a toy model example where this bulk field interacts via a Yukawa term with fermions on the line. We expect nontrivial line defects may also exist for free Maxwell theory in four dimensions and free bulk fermions.

High-redshift (z > 2) massive quiescent (MQ) galaxies provide an opportunity to probe the key physical processes driving the fuelling and quenching of star formation in the early Universe. Observational evidence suggests a possible evolutionary link between MQs and dusty star-forming galaxies (DSFGs; or submillimetre galaxies), another extreme high-redshift population. However, galaxy formation models have historically struggled to reproduce these populations - especially simultaneously - limiting our understanding of their formation and connection, particularly in light of recent JWST findings. In previous work, we presented a re-calibrated version of the L-Galaxies semi-analytic model that provides an improved match to observationally-inferred number densities of both DSFG and MQ populations. In this work, we use this new model to investigate the progenitors of MQs at z > 2 and the physical mechanisms that lead to their quenching. We find that most MQs at z > 2 were sub-millimetre-bright ($S_{870}$ > 1 mJy) at some point in their cosmic past. The stellar mass of MQs is strongly correlated with the maximum submillimetre flux density attained over their history, and this relation appears to be independent of redshift. However, only a minority of high-redshift DSFGs evolve into MQs by z = 2. The key distinction between typical DSFGs and MQ progenitors lies in their merger histories: MQ progenitors experience an early major merger that triggers a brief, intense starburst and rapid black hole growth, depleting their cold gas reservoirs. In our model, AGN feedback subsequently prevents further gas cooling, resulting in quenching. In contrast, the broader DSFG population remains sub-millimetre-bright, with star formation proceeding primarily via secular processes, becoming quenched later.

The Energetic Particle Radiation Environment Model (EPREM) solves the focused transport equation (FTE) on a Lagrangian grid in a frame co-moving with the solar wind plasma and simulates the acceleration and transport of solar energetic particles (SEP) in the heliosphere. When not coupled to an external magnetohydrodynamic model, EPREM functions in an uncoupled mode where an ideal cone-shock is injected into a homogeneous background solar wind. We carried out an analysis of the effects of multiple physical parameters in producing widespread SEP events simulated by the uncoupled EPREM using a relatively simple model of a strong magnetized shock propagating radially outward through the inner heliosphere to produce the requisite MHD quantities for EPREM's sophisticated model of proton acceleration and transport. We compared a baseline simulation with seven variations in which the value of a single parameter differed from its baseline value. All simulations exhibit complex profiles of SEP flux as a function of time and energy, with clear dependence on parameters related to diffusion, mean free path, and shock profile. Moreover, while all simulations exhibit significant longitudinal spread in SEP flux, for certain parameter values there exists a decrease or absence in SEP flux at observers located $\geq 90^\circ$ from the shock origin. Relating the differences in SEP flux to the specific values of each parameter in the simulations provides insight into the morphology of observed SEP events and the state of the solar wind through which the driving CME propagates.

We introduce SpectraPyle, a versatile spectral stacking pipeline developed for the Euclid mission's NISP spectroscopic surveys, aimed at extracting faint emission lines and spectral features from large galaxy samples in the Wide and Deep Surveys. Designed for computational efficiency and flexible configuration, SpectraPyle supports the processing of extensive datasets critical to Euclid's non-cosmological science goals. We validate the pipeline using simulated spectra processed to match Euclid's expected final data quality. Stacking enables robust recovery of key emission lines, including Halpha, Hbeta, [O III], and [N II], below individual detection limits. However, the measurement of galaxy properties such as star formation rate, dust attenuation, and gas-phase metallicity are biased at stellar mass below log10(M*/Msol) ~ 9 due to the flux-limited nature of Euclid spectroscopic samples, which cannot be overcome by stacking. The SFR-stellar mass relation of the parent sample is recovered reliably only in the Deep survey for log10(M*/Msol) > 10, whereas the metallicity-mass relation is recovered more accurately over a wider mass range. These limitations are caused by the increased fraction of redshift measurement errors at lower masses and fluxes. We examine the impact of residual redshift contaminants that arises from misidentified emission lines and noise spikes, on stacked spectra. Even after stringent quality selections, low-level contamination (< 6%) has minimal impact on line fluxes due to the systematically weaker emission of contaminants. Percentile-based analysis of stacked spectra provides a sensitive diagnostic for detecting contamination via coherent spurious features at characteristic wavelengths. While our simulations include most instrumental effects, real Euclid data will require further refinement of contamination mitigation strategies.

21cm-galaxy cross-correlation will play a key role in confirming the cosmological 21cm signal. We investigate which survey configurations detect the 21cm-LAE cross-correlation signal, and assess its ability to distinguish reionisation scenarios. Our pipeline computes observational uncertainties for the 21cm-galaxy cross-power spectrum, accounting for key survey parameters: the field of view (FoV), limiting luminosity of galaxy surveys $L_α$, redshift uncertainty $σ_z$, and 21cm foreground wedge assumptions. We calculate the signal-to-noise ratio (SNR) of the 21cm-Lyman-$α$ emitter (LAE) cross-power spectrum for two scenarios: one where reionisation is driven by faint or by bright galaxies. We find: (i) SNR increases with larger FoV, fainter $L_α$, and smaller $σ_z$, with the FoV having the strongest impact when $σ_z$ is small. (ii) Under a moderate foreground wedge, photometric-like surveys yield insufficient SNR, and medium-deep ($L_α\gtrsim10^{42.5}$erg s$^{-1}$), wide-area (FoV>20deg$^2$) slitless spectroscopic surveys are needed. (iii) Under an optimistic foreground wedge, detection is possible with deep ($L_α\gtrsim10^{42.3}$erg s$^{-1}$), wide-area (FoV$\gtrsim80$deg$^2$) photometric-like or shallower, small-area (FoV$\simeq2-3$deg$^2$) slitless spectroscopic surveys. (iv) To distinguish the two reionisation scenarios at z=7, moderate foreground wedge scenarios require deep-wide spectroscopic surveys; under an optimistic foreground wedge, shallower, medium-area (FoV$\simeq10$deg$^2$) slitless spectroscopic surveys suffice. (v) Maximising the SNR for detection and model discrimination requires sampling the large-scale peak of the cross-power spectrum, which shifts to larger physical scales as reionisation proceeds and the less ionisation fronts follow the gas density - making surveys at z>7 more promising despite lower galaxy number densities.

Ultra-diffuse Galaxies (UDGs) are a subset of Low Surface Brightness Galaxies (LSBGs), showing mean effective surface brightness fainter than $24\ \rm mag\ \rm arcsec^{-2}$ and a diffuse morphology, with effective radii larger than 1.5 kpc. Due to their elusiveness, traditional methods are challenging to be used over large sky areas. Here we present a catalog of ultra-diffuse galaxy (UDG) candidates identified in the full 1350 deg$^2$ area of the Kilo-Degree Survey (KiDS) using deep learning. In particular, we use a previously developed network for the detection of low surface brightness systems in the Sloan Digital Sky Survey \citep[LSBGnet,][]{su2024lsbgnet} and optimised for UDG detection. We train this new UDG detection network for KiDS (UDGnet-K), with an iterative approach, starting from a small-scale training sample. After training and validation, the UGDnet-K has been able to identify $\sim3300$ UDG candidates, among which, after visual inspection, we have selected 545 high-quality ones. The catalog contains independent re-discovery of previously confirmed UDGs in local groups and clusters (e.g NGC 5846 and Fornax), and new discovered candidates in about 15 local systems, for a total of 67 {\it bona fide} associations. Besides the value of the catalog {\it per se} for future studies of UDG properties, this work shows the effectiveness of an iterative approach to training deep learning tools in presence of poor training samples, due to the paucity of confirmed UDG examples, which we expect to replicate for upcoming all-sky surveys like Rubin Observatory, Euclid and the China Space Station Telescope.

As the scientific exploitation of the Square Kilometre Array (SKA) approaches, there is a need for new advanced data analysis and visualization tools capable of processing large high-dimensional datasets. In this study, we aim to generalize the YOLO-CIANNA deep learning source detection and characterization method for 3D hyperspectral HI emission cubes. We present the adaptations we made to the regression-based detection formalism and the construction of an end-to-end 3D convolutional neural network (CNN) backbone. We then describe a processing pipeline for applying the method to simulated 3D HI cubes from the SKA Observatory Science Data Challenge 2 (SDC2) dataset. The YOLO-CIANNA method was originally developed and used by the MINERVA team that won the official SDC2 competition. Despite the public release of the full SDC2 dataset, no published result has yet surpassed MINERVA's top score. In this paper, we present an updated version of our method that improves our challenge score by 9.5%. The resulting catalog exhibits a high detection purity of 92.3%, best-in-class characterization accuracy, and contains 45% more confirmed sources than concurrent classical detection tools. The method is also computationally efficient, processing the full ~1TB SDC2 data cube in 30 min on a single GPU. These state-of-the-art results highlight the effectiveness of 3D CNN-based detectors for processing large hyperspectral data cubes and represent a promising step toward applying YOLO-CIANNA to observational data from SKA and its precursors.

Dense young star clusters (YSCs) are ideal environments for dynamical interactions between stars and stellar mass black holes (BHs). In such dense environments, stars can undergo close encounters with BHs and fall within their tidal radius, resulting in micro-tidal disruption events (micro-TDEs), transient phenomena with potential multi-messenger signatures. We performed a suite of direct N-body simulations using the PETAR code, to which we implemented new prescriptions for modeling micro-TDEs. We constructed a set of realistic YSC models including primordial binaries, based on the observed Milky Way population. Our simulations incorporate stellar and binary evolution, supernova kicks, and stellar winds using the BSE code, and account for the Galactic tidal field via the GALPY library. We identify three dynamical channels for micro-TDE production: single star-single BH encounters, binary-mediated interactions (including supernova-kick triggers), and interactions involving higher-order multiple systems such as hierarchical triples and quadruples, as well as chaotic few-body interactions. Multiple encounters are the most efficient production channel, which dominates the total rate: 350-450 Gpc$^{-3}$ yr$^{-1}$. Micro-TDEs from YSCs are expected to be detectable by upcoming surveys, particularly the Legacy Survey of Space and Time, with detection rates potentially up to hundreds per year. The gravitational wave (GW) signals expected from micro-TDEs peak in the deci-Hertz band, making them accessible to future instruments such as the Lunar Gravitational Wave Antenna and the Deci-Hertz Interferometer Gravitational-wave Observatory. Micro-TDEs emerge as promising multi-messenger sources, potentially offering unique insights into star cluster dynamics, stellar collisions, and the population of dormant stellar-mass BHs, through both electromagnetic and GW observations.

We provide evidence that three-party entanglement signals in holography obey a relation that is not satisfied by generalized Greenberger-Horne-Zeilinger (GHZ) states. Using proposed holographic duals for these entanglement signals, we provide a geometric argument establishing this relation. This is the first known inequality on the structure of pure three-party holographic states, and shows that time-symmetric holographic states can never have purely GHZ-like entanglement. We also discuss similar relations for four parties.

Mechanical modulation of recoilless nuclear transitions allows the dynamic control of $γ$-ray emission and absorption. Accessing modulation frequencies well above the nuclear linewidth enables coherent manipulation of the nuclear response. Here we demonstrate high frequency control via efficient coupling a film of enriched $^{57}$Fe to a $97.9~\mathrm{MHz}$ surface acoustic wave, nearly two orders of magnitude higher than the nuclear linewidth. The mechanical drive produces a comb of absorption sidebands in the Mössbauer spectrum, reflecting the periodic time modulation of the nuclear transitions. This constitutes the highest frequency mechanically driven Mössbauer resonance to date. Our solid-state, monolithic platform establishes a new interface between nuclear transitions and high-frequency acoustics, with applications in $γ$-ray quantum optics and precision nuclear spectroscopy.

The nucleolus is a central solution concept in cooperative game theory. While its computation is NP-hard in general, it can be computed in polynomial time for convex games; however, the only published polynomial-time algorithm relies on the ellipsoid method. We develop a combinatorial alternative based on reduced games and iterative least-core value computations. Leveraging submodular function minimization and polyhedral structure in a novel way, we obtain a faster combinatorial algorithm for computing the least-core value, improving the oracle complexity by a factor $n^3$ over previous approaches. As a consequence, we obtain a new strongly polynomial-time and combinatorial algorithm for computing the nucleolus in convex games. Preliminary analysis indicates an improved oracle complexity compared to the ellipsoid-based algorithm.

The Atlantic Meridional Overturning Circulation (AMOC) is a major tipping element in the present-day climate, and could potentially collapse under sufficient freshwater or CO2-forcing. While the effect of the Bering Strait on AMOC stability has been well studied, it is unknown whether a constructed closure of this Strait can prevent an AMOC collapse under climate change. Here, we show in an Earth system Model of Intermediate Complexity that an artificial closure of the Strait can extend the safe carbon budget of the AMOC, provided that the AMOC is strong enough at the closure time. Specifically, for this model, an equilibrium AMOC with a reduction below (6.1 +/- 0.5)% from pre-industrial has an additional budget up to 500PgC given a sufficiently early closure, while for a weaker AMOC a closure reduces this budget. This indicates that constructing this closure could be a feasible climate intervention strategy to prevent an AMOC collapse.

Magnetic singularities known as Bloch points (BPs) present a fundamental challenge for micromagnetic theory, which is based on the assumption of a fixed magnetization vector length. Due to the divergence of the effective field at a BP, classical micromagnetics fails to adequately describe BP dynamics. To address this issue, we propose a regularized micromagnetic model in which the magnetization vector can vary in length but not exceed a threshold value. More specifically, the magnetization is treated as an order parameter constrained to a S3-sphere. This constraint respects fundamental properties of local spin expectation values in quantum systems. We derive the corresponding regularized Landau-Lifshitz-Gilbert equation and the analogue of the Thiele equation describing the steady motion of spin textures under various external stimuli. We demonstrate the applicability of our theory by modeling the dynamics of several magnetic textures containing BPs, including domain walls in nanowires, chiral bobbers, and magnetic dipolar strings. The presented results extend micromagnetic theory by incorporating a regularized description of BP dynamics.

We investigate the impact of radiation pressure on the circumbinary discs surrounding accreting massive black hole binaries (MBHBs) at milli-parsec separations, using 3D hyper-Lagrangian resolution hydrodynamic simulations. The circumbinary discs in our simulations evolve under an adiabatic equation of state. The gas temperature is therefore allowed to change through viscous heating, black-body cooling and self-gravity. We take a significant step further by including the contribution of radiation pressure in the simulations. We model binaries with a total mass of $10^6 \, M_{\odot}$, eccentricities $e=0,0.45,0.9$ and mass ratios $q= 0.7, 1$. We find that the radiation pressure significantly alters the vertical and thermal structure of the disc, resulting in a geometrically thinner, therefore colder configuration. This leads to a reduced accretion rate onto the binary and suppresses cavity eccentricity growth and precession in circular equal mass binaries. The binary eccentricity remains approximately constant, while the semi-major axis decreases over time due to net negative torque, regardless of the initial binary orbital parameters.

Deuteron inelastic scattering on $^{86}$Kr was measured in inverse kinematics with the gaseous active target CAT-M, as part of a systematic investigation aimed at determining the nuclear matter incompressibility. The isoscalar monopole strength distribution was extracted via multipole decomposition analysis, and the energy of the isoscalar giant monopole resonance was determined to be 17 $\pm$ 1 MeV. The nuclear incompressibility of $^{86}$Kr and the isospin-dependent term of the nuclear matter incompressibility are discussed.

We present a parameter-free variant of the halo model that significantly improves the precision of matter clustering predictions, particularly in the challenging 1-halo to 2-halo transition regime, where standard halo models often fail. Unlike HMcode-2020, which relies on 12 phenomenological parameters, our approach achieves comparable or superior accuracy without any free fitting parameters. This new web-halo model (WHM) extends the traditional halo model by incorporating structures that have collapsed along two dimensions (filaments) and one dimension (sheets), in addition to haloes, and combines these with 1-loop Lagrangian Perturbation Theory (1$\ell$-LPT) in a consistent framework. We show that WHM matches N-body simulation power spectra within the precision of state-of-the-art emulators at the 2-halo to 1-halo transition regime at all redshifts. Specifically, the WHM achieves better than 2\% accuracy up to scales of $k = 0.4\, h\,\mathrm{Mpc}^{-1}$, $0.7\, h\,\mathrm{Mpc}^{-1}$, and $1.3\, h\,\mathrm{Mpc}^{-1}$ at redshifts $z = 0.0$, $0.8$, and $1.5$, respectively, for both the baccoemu and EuclidEmu2 emulators, across their full $w_0w_a\mathrm{CDM} + \sum m_ν$ cosmological parameter space. This marks a substantial improvement over 1$\ell$-LPT and HMcode-2020, the latter of which performs similarly at low redshift but deteriorates at higher redshifts despite its 12 tuned parameters. We publicly release WHM as WHMcode, integrated into existing HMcode implementations for CAMB and CLASS.