We report the discovery and characterisation of three transiting warm Jupiters: TIC 147027702b, TIC 245076932b and TIC 87422071b. These systems were initially identified as transiting candidates using light curves generated from the full-frame images of the TESS mission. We confirmed the planetary nature of these objects with ground-based spectroscopic follow-up observations using FEROS and the new PLATOSpec spectrograph attached to the ESO 1.52 m telescope at the La Silla Observatory, and with ground-based photometric observations of the Observatoire Moana, Las Cumbres Observatory Global Telescope and ASTEP. From a global fit to the photometry and radial velocities, we determine that the planet TIC 147027702b has a low-eccentric orbit ($e = 0.13 \pm 0.05$) with a period of 44.4 days and has a mass of $1.09^{+0.07}_{-0.13}$ M$_J$ and a radius of $0.98 \pm 0.06$ R$_J$. TIC 245076932b has a moderately low mass of $0.51 \pm 0.05$ M$_J$, a radius of $0.97 \pm 0.05$ R$_J$, and an eccentric orbit ($e = 0.43 \pm 0.02$) with a period of 21.6 days. TIC 87422071b has a mass of $1.29 \pm 0.10$ M$_J$, a radius of $0.97 \pm 0.08$ R$_J$, and has a slightly eccentric orbit ($e = 0.12 \pm 0.07$) with a period of 11.3 days. These well-characterised warm Jupiters expand the currently limited sample of similar gas giants and provide valuable benchmarks for testing models of giant-planet formation, migration, and tidal evolution.

Open clusters (OCs) usually evolve gradually as the number of their members changes, which can be manifested in their morphological characteristics. We aim to investigate the morphological stability of 1,490 OCs and further explore the potential change of morphological stability of the OCs at different spatial positions, using the OC catalog from the literature. We define for the first time a new morphological stability parameter Ncore/Nouter, a ratio of member numbers between cluster core and outer areas within tidal radii, which has a significant positive correlation against N, with a slope of 1.140$\pm$0.039, significantly steeper than the 0.720$\pm$0.026 measured for Score/Souter. This demonstrates that the stellar density in the core is a more sensitive tracer for morphological stability than geometry. Spatially, the radial sample OCs have larger slopes of Ncore/Nouter and Score/Souter against N, with 1.083$\pm$0.116 and 0.733$\pm$0.080, respectively, whereas those in the tangential direction 1.013$\pm$0.110 and 0.529$\pm$0.075, respectively, which means that the impact on sample OCs from tidal forces directed toward the Galactic center is possibly stronger than that from the shear force caused by the differential rotation of the Galactic disk. Besides, the sample OCs younger than 30 Myr display a shallow slope of 0.751$\pm$0.166, with those older than 800 Myr (1.442$\pm$0.128), reflecting that young OCs likely endure both internal disruptions, such as early dynamical heating weakening core binding and more severe external disturbances, compared to older OCs.

A dynamic view of mass assembly is essential for understanding the formation of massive stars and clusters. Interpreting evolutionary diagnostics from Galactic-wide surveys, however, requires careful control of distance and environmental variations. The G316.8 filament provides an ideal laboratory: a 14-pc nearly linear structure composed of three contiguous subregions with comparable molecular gas reservoirs (~10,000 $M_\odot$ each) but spanning a clear evolutionary sequence from an infrared dark cloud (young) through a massive young stellar object (intermediate) to an HII region (evolved). As part of the Linear filament and nested cluster evolution tomography (LANCET) project, we mapped the full filament with the Atacama Compact Array at 1.3 mm, achieving 0.08 pc resolution over 17.1 pc$^2$. Combined with Herschel and APEX/ArTéMiS data, we derived high-resolution temperature and column-density maps. We quantify structural evolution using dense-fragment statistics, column-density PDFs, and $Δ$-variance analysis. From young to evolved regions, the maximum fragment mass increases from 8 to 490 $M_\odot$, while the dense-gas mass fraction ($>0.5$ g cm$^{-2}$) rises from 0.4% to 9.6%. The N-PDF develops a secondary power-law tail and the $Δ$-variance slope becomes progressively shallower, indicating ongoing assembly of dense sub-parsec structures. Our further ALMA 12m continuum and spectral line data will extend this dynamic scenarios down to 800 AU scale.

The recovery of unknown signals from quadratic measurements finds extensive applications in fields such as phase retrieval, power system state estimation, and unlabeled distance geometry. This paper investigates the finite sample properties of weakly convex--concave regularized estimators in high-dimensional quadratic measurements models. By employing a weakly convex--concave penalized least squares approach, we establish support recovery and $\ell_2$-error bounds for the local minimizer. To solve the corresponding optimization problem, we adopt two proximal gradient strategies, where the proximal step is computed either in closed form or via a weighted $\ell_1$ approximation, depending on the regularization function. Numerical examples demonstrate the efficacy of the proposed method.

We measure the velocity anisotropy profile $β(r)$ of different galaxy cluster member populations by analysing the stacked projected phase space of nine massive ($M_\mathrm{200c}>7\times10^{14}$ M$_\odot$) galaxy clusters at intermediate redshifts ($0.18 < z < 0.45$). We select our sample of galaxy clusters by choosing the most round and virialised objects among the targets of the CLASH-VLT spectroscopic program, which offers a large spectral database. Complementary MUSE observations on most of these clusters allowed us to identify an unprecedented number of cluster members, strongly enhancing the precision of our measurement with respect to previous studies. Our sample of cluster members is divided in four classes: red and blue by colour, and high- and low-mass by stellar mass. We employ two parallel techniques, namely the MAMPOSSt method (parametric in $β(r)$) and the Jeans equation inversion (non parametric in $β(r)$). The results from both techniques are found in agreement for any given cluster member population, and suggest that the orbital anisotropy in galaxy clusters grows from the centre (where $β\approx 0.2-0.4$) to the virial radius ($β\gtrsim 0.8$), and it is similar for the different cluster member populations. We also find an interesting dynamical feature in the Jeans inversion results, that is a drop in $β(r)$ at a distance of $\sim 250$ kpc from the cluster centre. We provide robust anisotropy estimates by exploring a highly significant number of model combinations: 72 with MAMPOSSt (varying the mass, surface number density, $β(r)$ model, and galaxy population) and 18 (varying total mass model and galaxy population) in the Jeans inversion. Such an extensive investigation of the $β(r)$ profile in galaxy clusters is a wide basis for future studies on cluster dynamical masses and cluster cosmology in the era of large spectroscopic surveys

We derive analytical nuclear gradients for state-averaged orbital-optimized configuration interaction singles (SACIS) and its spin-projected extension (SAECIS), enabling efficient geometry optimization and minimum-energy conical intersection (MECX) searches within a low-cost CIS-based framework. The formulation employs a Lagrangian approach and explicitly removes null-space contributions in the coupled perturbed equations to ensure numerically stable gradients. For twisted-pyramidalized ethylene, both SACIS and SAECIS qualitatively reproduce the correct conical intersection topology, in sharp contrast to conventional CIS and ECIS. Benchmark calculations on twelve MECXs demonstrate that both methods reproduce geometries with mean RMSDs below 0.1~Å relative to high-level reference methods. SACIS captures the essential degeneracy through variational orbital relaxation, which alleviates ground-state Hartree--Fock (HF) orbital bias and effectively incorporates static correlation through localization effects; notably, spin projection is found to be non-essential for the qualitative description of these intersections. Overall, SACIS and SAECIS provide qualitatively reliable CX descriptions at mean-field computational cost in a black-box manner. Given their comparable accuracy and the additional overhead associated with spin projection, SACIS offers a more favorable cost-performance balance for general applications, whereas SAECIS may become advantageous when higher excited states with significant double-excitation character are involved.

In exascale-oriented GPU clusters, rigid-topology jobs leave behind a fragmented post-landing ecology in which long-resident workloads and highly transient tasks compete for unstable residual capacity. Existing centralized, hierarchical, and local-first decentralized schedulers incur growing coordination and retry-amplification costs in this regime and typically stop their explicit responsibility at execution start, leaving runtime survival to indiscriminate host-level OOM heuristics. We present Laminar, a decentralized probe-first, execute-later scheduling paradigm that keeps hot-path control-plane work near $\mathcal{O}(1)$ through Zone-level probabilistic flow splitting, bounded in-Zone probing by persistent lightweight agents, and node-local arbitration. Laminar further introduces Airlock, a bounded node-local runtime-survival layer that converts severe memory pressure into an ordered policy of suspension, in-situ recovery, bounded secondary re-addressing, or reclamation. By enforcing priority-ordered survival under pressure, Laminar enables lifecycle-aware scheduling that preserves high-value long-resident work and operates closer to physical saturation without relying on protocol-level overcommitment.

We introduce $\texttt{GPUmonty}$, a CUDA/C-based Monte Carlo radiative transfer code accelerated using graphics processing units (GPUs). $\texttt{GPUmonty}$ derives from the CPU-based code $\texttt{grmonty}$ and offloads the most computationally expensive stages of the calculation -- superphoton generation, sampling, tracking, and scattering -- to the GPU. Whereas $\texttt{grmonty}$ handles photons sequentially, $\texttt{GPUmonty}$ processes large numbers of superphotons concurrently, leveraging the single-instruction, multiple-thread (SIMT) execution model of modern GPUs. Benchmarks demonstrate a speedup of about $12\times$ relative to the original CPU implementation on a single GPU, with runtime limited primarily by register pressure rather than compute or memory bandwidth saturation. We validate the implementation through analytic tests for a optically thin synchrotron sphere, as well as comparisons with $\texttt{igrmonty}$ for scattering synchrotron sphere and GRMHD simulation data. Relative errors remain below a percent level and convergence is consistent with the expected $N_{\rm s}^{-1/2}$ Monte Carlo scaling. By significantly reducing computational costs, GPUmonty enables the extensive parameter space surveys and faster spectra modeling required to interpret horizon-scale observations of supermassive black holes. $\texttt{GPUmonty}$ is publicly available under the GNU General Public License.

LOFAR observations of diffuse interstellar polarization at meter wavelengths reveal intricate polarized intensity structures with an unexpected correlation with neutral HI filaments that could not be reproduced in simulations with low cold neutral medium (CNM) abundance. We investigate whether MHD simulations of thermally bi-stable neutral interstellar medium, with a range of CNM fraction, can reproduce the properties of the 3C196 field, the high Galactic latitude test field. Using 50 pc simulations with varying levels of turbulence and compressibility, we generated synthetic 21 cm and synchrotron observations, including instrumental noise and beam effects, for different line-of-sight orientations relative to the magnetic field. We developed MOOSE, a code to generate synthetic synchrotron polarization and Faraday tomography. We also developed a metric based on the HOG algorithm, to quantify the relative contribution of cold and warm neutral medium structures to the Faraday tomographic data. The synthetic observations show levels of polarization intensity and RM values comparable to the 3C196 field, indicating that thermal electrons associated with the neutral HI phase can account for a significant fraction of the synchrotron polarized emission at 100-200 MHz. The simulations consistently reveal a correlation between CNM and Faraday tomographic structures that depends on turbulence level, magnetic field orientation, and observational noise, but only weakly on CNM fraction. We found slightly weaker CNM-Synchrotron polarized emission correlation level than observed in the 3C196 field. These results suggest that low-frequency polarimetric observations provide a valuable probe of magnetic-field morphology in the multi-phase Solar-neighborhood ISM, while simultaneously underscoring the need for improved modeling of the turbulent, multi-phase, and partially ionized interstellar medium.

It is well known that, in potentials that are quadratic near the minimum but shallower away, such as small $α$ ($\ll M_P^2$) attractors, the inflaton condensate fragments into localized compact objects known as oscillons during self-resonance preheating. In this work we investigate the self-resonance in deformed $α$-attractor T-model with a Gaussian feature near the minimum, distant from inflation's end. Linear analysis reveals altered resonance bands and deformed Floquet charts dependent on feature parameters. In fully nonlinear lattice simulations, we find that the gradient energy transfer is largely independent of the potential feature parameter $h$. In contrast, after resonance terminates, the subsequent evolution of gradient energy becomes strongly dependent on $h$. Statistical analysis reveals that models with the potential feature produce larger number of smaller oscillons, with a reduced energy stored in these objects, increasingly suppressed as the magnitude of $h$ grows. By tracking the total energy and the gradient energy contained in oscillons, we find that in models with nonzero $h$ oscillons are systematically shorter-lived, with this effect strengthening for larger $h$. The gravitational wave emission is dominated by the resonance stage and is strongly suppressed once oscillons form. Potential features leave the low-frequency spectrum largely unchanged but significantly modify the high-frequency tail. Although a complete reheating description requires external couplings and higher-resolution simulations, clear qualitative differences of cosmic expansion history already emerge within our simulated time window. These results highlight the important role of potential features in shaping reheating dynamics and their cosmological implications, and provide a deeper understanding of preheating dynamics and the properties of oscillons.

The PCIe400 is a generic readout board designed for high-throughput data acquisition in future high-energy physics experiments. It interfaces up to 48 bidirectional links supporting custom protocols from 1 to 26 Gbps to modern back-end systems providing up to 400 Gbps bandwidth.The board is developed as a technological demonstrator for the LHCb Upgrade II, which foresees an aggregated throughput of approximately 200 Tbps. In addition to increased bandwidth, the PCIe400 targets deterministic clock distribution to front-end electronics. At a maximum instantaneous luminosity of $1.5~\times~10^{34}~cm^{-2}s^{-1}$, up to 40 proton-proton interactions per bunch crossing are expected in LHCb Upgrade II. The adoption of 4D tracking detectors with time resolutions down to 20 ps motivates clock distribution with phase determinism below 10 ps peak-to-peak across large-scale systems exceeding 2000 nodes. This paper presents the qualification of the PCIe400 prototype board, focusing on high-bandwidth interfaces, including next-generation QSFP112 links, and phase-deterministic clock distribution.

Superconducting resonators and qubits are limited by dielectric losses from surface oxides. Surface oxides are mitigated through various strategies such as the addition of a metal capping layer, surface passivation, and acid processing. In this study, we demonstrate the use of X-ray photoelectron spectroscopy (XPS) as a rapid characterization tool to study the effectiveness cap layers for niobium for further device fabrication. We non-destructively evaluate 17 capping layers to characterize their ability to prevent oxygen diffusion, and the effects of standard fabrication processes -- annealing, resist stripping, and acid cleaning. We downselect for resilient capping layers and test their microwave resonator performance.

Empirical studies of research software are hard to compare because the literature operationalizes ``research software'' inconsistently. Motivated by the research software supply chain (RSSC) and its security risks, we introduce an RSSC-oriented taxonomy that makes scope and operational boundaries explicit for empirical research software security studies. We conduct a targeted scoping review of recent repository mining and dataset construction studies, extracting each work's definition, inclusion criteria, unit of analysis, and identification heuristics. We synthesize these into a harmonized taxonomy and a mapping that translates prior approaches into shared taxonomy dimensions. We operationalize the taxonomy on a large community-curated corpus from the Research Software Encyclopedia (RSE), producing an annotated dataset, a labeling codebook, and a reproducible labeling pipeline. Finally, we apply OpenSSF Scorecard as a preliminary security analysis to show how repository-centric security signals differ across taxonomy-defined clusters and why taxonomy-aware stratification is necessary for interpreting RSSC security measurements.

Generative recommendation provides a novel paradigm in which each item is represented by a discrete semantic ID (SID) learned from rich content. Most existing methods treat SIDs as predefined and train recommenders under static indexing. In practice, SIDs are typically optimized only for content reconstruction rather than recommendation accuracy. This leads to an objective mismatch: the system optimizes an indexing loss to learn the SID and a recommendation loss for interaction prediction, but because the tokenizer is trained independently, the recommendation loss cannot update it. A natural approach is to make semantic indexing differentiable so that recommendation gradients can directly influence SID learning, but this often causes codebook collapse, where only a few codes are used. We attribute this issue to early deterministic assignments that limit codebook exploration, resulting in imbalance and unstable optimization. In this paper, we propose DIGER (Differentiable Semantic ID for Generative Recommendation), a first step toward effective differentiable semantic IDs for generative recommendation. DIGER introduces Gumbel noise to explicitly encourage early-stage exploration over codes, mitigating codebook collapse and improving code utilization. To balance exploration and convergence, we further design two uncertainty decay strategies that gradually reduce the Gumbel noise, enabling a smooth transition from early exploration to exploitation of learned SIDs. Extensive experiments on multiple public datasets demonstrate consistent improvements from differentiable semantic IDs. These results confirm the effectiveness of aligning indexing and recommendation objectives through differentiable SIDs and highlight differentiable semantic indexing as a promising research direction. Our code is released under https://github.com/junchen-fu/DIGER.

To enable Integrated Communications and Sensing (ICAS) in a peer-to-peer vehicular network, precise synchronization in frequency and phase among the communicating entities is required. In addition, self-driving cars need accurate position estimates of the surrounding vehicles. In this work, we propose a joint, distributed synchronization and localization scheme for a network of communicating entities. Our proposed scheme is mostly signal-agnostic and therefore can be applied to a wide range of possible ICAS signals. We also mitigate the effect of finite sampling frequencies, which otherwise would degrade the synchronization and localization performance severely.

Qhronology is a novel scientific-computing package for studying quantum models of closed timelike curves (CTCs) and simulating general quantum information processing and computation. Written in Python, the program provides a comprehensive framework for analyzing quantum theories of antichronological time travel, including functionality to calculate quantum resolutions to temporal paradoxes. It also operates as a complete quantum circuit simulator, enabling the examination of quantum algorithms and protocols in both numerical and symbolic capacities. In this paper, we formally introduce Qhronology, beginning with discussion on aspects of its design philosophy and architecture. An overview of its basic usage is then presented, along with a collection of examples demonstrating its various capabilities within a variety of distinct contexts. Lastly, the performance of the package's circuit simulation component is characterized by way of some simple empirical benchmarking.

The detection of strong, large-scale magnetic fields at the surface of only the oldest population of white dwarfs might point towards a hidden internal magnetic field slowly rising to the surface. In addition, strong magnetic fields have recently been measured through asteroseismology in the radiative interiors of red giant stars, the progenitors of white dwarfs. To investigate the potential connection between these observations, we revisit the fossil field framework by using the asteroseismic detections to constrain the strength of such magnetic fields as they evolve to the white dwarf stage. We assume that the magnetic field was either created during the main sequence core convection or that it fills the radiative interior as the star evolves on the red giant branch. From these, we evolve the magnetic flux, allowing for magnetic diffusion along the evolution of a 1.5Msun modelled star. We find that measured field strengths in red giants attributed to the hydrogen-burning shell are compatible with the field amplitudes and emergence timescales of magnetized white dwarfs. On the contrary, magnetic fields generated solely from a convective-core dynamo on the main-sequence and detectable during the red giant branch would be buried too deep in the star and not match the breakout timescales and the field strengths of magnetic white dwarfs. A broadly magnetized internal radiative zone during the red giant branch is therefore key for the fossil field theory to connect magnetic fields observed along the late evolution of stars.

We present a Myhill-Nerode style characterization for languages recognized by one-clock deterministic timed automata (1-DTA). Although there is only one clock, distinct automata may reset it differently along the same word. This adds a significant challenge in the search for a canonical automaton. Our characterization is based on a new perspective of 1-DTAs in terms of "half-integral" words that they accept, along with the reset information encoded by them. We apply our results to develop L* style algorithms that learn the canonical 1-DTA.

The theoretical relationship between the macroscopic textural quality and microscopic structural quality appearing in the phase inversion processes from fresh cream via whipped cream to butter is revealed by the multi-scale simulation of coupled map lattice (CML) based on the mesoscopic elementary processes of the emulsion interfaces. Using the Young-Laplace equation, we derive the microscopic particle quantities of the size and density of air bubbles and butter grains in an emulsion from the macroscopic rheological quantities of the overrun and viscosity of the emulsion. In doing so, we focus on the size determined by the "tug-of-war" between air bubbles and butter grains via their cohesion pressures, and on the density determined by the "costume change" of the emulsion molecular complexes (clad particles, e.g., butter grain-clad air bubbles) to their suitable size. Using the obtained microscopic particle quantities, we now propose a microscopic state diagram, the size-density plane, in addition to the previously proposed macroscopic state diagram, the viscosity-overrun plane. These state diagrams reveal that while the two well-known different phase inversion processes at high and low whipping temperatures appear as the two parallel processes of viscosity dominance and overrun dominance in the viscosity-overrun plane, they appear as the two orthogonal processes of isodensity/size dominance and isosize/density dominance in the size-density plane. This theoretical simulation result is significant for the quality design of butter because it demonstrates that differences in macroscopic textural quality can be easily controlled by differences in microscopic structural quality.

The unprecedented wavelength coverage and sensitivity of the James Webb Space Telescope (JWST) permits to measure the absorption features of a wide range of condensate species from Silicates to Titan tholins. Atmospheric retrievals are uniquely suited to analyse these datasets and characterize the aerosols present in exoplanet atmospheres. However, including the optical properties of condensed particles within retrieval frameworks remains computationally expensive, limiting our ability to fully exploit JWST observations. In this work, we improve the computational efficiency and scaling behavior of aerosol models in atmospheric retrievals, enabling in-depth studies including multiple condensate species within practical time scales. Rather than computing the aerosol Mie coefficients for each sampled model, we pre-compute extinction efficiency (Qext), scattering efficiency (Qscat) and asymmetry parameter (g) grids for seven condensate species relevant in exoplanet atmospheres (Mg2SiO4 amorph sol - gel, MgSiO3 amorph glass, MgSiO3 amorph sol - gel, SiO2 alpha, SiO2 amorph, SiO and Titan tholins). The pre-computed Qext grids significantly reduce computation time between 1.4 and 17 times with negligible differences on the retrieved parameters. They also scale effortlessly with the number of aerosol species while maintaining the accuracy of cloud models. Thereby enabling more complex retrievals as well as broader population studies without increasing the overall error budget. The Qext, Qscat and g grids are freely available on Zenodo as well as a public TauREx plugin -TauREx-PCQ- that utilize them.

Non-stabilizerness, also known as ``magic,'' quantifies how far a quantum state departs from the stabilizer set. It is a central resource behind quantum advantage and a useful probe of the complexity of quantum many-body states. Yet standard magic quantifiers, such as the stabilizer Rényi entropy (SRE) for qubits and the mana for qutrits, are costly to evaluate numerically, with the computational complexity growing rapidly with the number $N$ of qudits. Here we introduce efficient, numerically exact algorithms that exploit the fast Hadamard transform to compute the SRE for qubits ($d=2$) and the mana for qutrits ($d=3$) for pure states given as state vectors. Our methods compute SRE and mana at cost $O(N d^{2N})$, providing an exponential improvement over the naive $O(d^{3N})$ scaling, with substantial parallelism and straightforward GPU acceleration. We further show how to combine the fast Hadamard transform with Monte Carlo sampling to estimate the SRE of state vectors, and we extend the approach to compute the mana of mixed states. All algorithms are implemented in the open-source Julia package HadaMAG ( https://github.com/bsc-quantic/HadaMAG.jl/ ), which provides a high-performance toolbox for computing SRE and mana with built-in support for multithreading, MPI-based distributed parallelism, and GPU acceleration. The package, together with the methods developed in this work, offers a practical route to large-scale numerical studies of magic in quantum many-body systems.

Over the split-octonion algebra defined over an arbitrary field, we solve all polynomial equations whose coefficients are scalar except for the constant term. As an application, we determine the square and cubic roots of an octonion.

The guiding-center dynamics of charged particles moving in a doubly-symmetric screw-pinch magnetic field is investigated. In particular, we verify that Kruskal's adiabatic-invariant series expansion of the radial action integral associated with the reduced full-orbit radial motion matches the perturbation expansion of the magnetic-moment gyroaction up to first order in magnetic-field non-uniformity. Because the radial action integral is an exact invariant of the full-orbit dynamics, the magnetic moment is therefore represented as non-perturbative integral expression, which can be used to test the validity of the guiding-center approximation.

We study leveraging adaptive retrieval to ensure sufficient "bridge" documents are retrieved for reasoning-intensive retrieval. Bridge documents are those that contribute to the reasoning process yet are not directly relevant to the initial query. While existing reasoning-based reranker pipelines attempt to surface these documents in ranking, they suffer from bounded recall. Naive solution with adaptive retrieval into these pipelines often leads to planning error propagation. To address this, we propose REPAIR, a framework that bridges this gap by repurposing reasoning plans as dense feedback signals for adaptive retrieval. Our key distinction is enabling mid-course correction during reranking through selective adaptive retrieval, retrieving documents that support the pivotal plan. Experimental results on reasoning-intensive retrieval and complex QA tasks demonstrate that our method outperforms existing baselines by 5.6%pt.

Multi-speaker automatic speech recognition (MASR) aims to predict ''who spoke when and what'' from multi-speaker speech, a key technology for multi-party dialogue understanding. However, most existing approaches decouple temporal modeling and speaker modeling when addressing ''when'' and ''who'': some inject speaker cues before encoding (e.g., speaker masking), which can cause irreversible information loss; others fuse identity by mixing speaker posteriors after encoding, which may entangle acoustic content with speaker identity. This separation is brittle under rapid turn-taking and overlapping speech, often leading to degraded performance. To address these limitations, we propose TellWhisper, a unified framework that jointly models speaker identity and temporal within the speech encoder. Specifically, we design TS-RoPE, a time-speaker rotary positional encoding: time coordinates are derived from frame indices, while speaker coordinates are derived from speaker activity and pause cues. By applying region-specific rotation angles, the model explicitly captures per-speaker continuity, speaker-turn transitions, and state dynamics, enabling the attention mechanism to simultaneously attend to ''when'' and ''who''. Moreover, to estimate frame-level speaker activity, we develop Hyper-SD, which casts speaker classification in hyperbolic space to enhance inter-class separation and refine speaker-activity estimates. Extensive experiments demonstrate the effectiveness of the proposed approach.

We investigate the angle of repose $θ_r$ of dense suspensions of colloidal silica particles ($d = 2$ $μm$ to $7$ $μm$) in water-filled microfluidic rotating drums experiments, to probe the crossover between the thermal (colloidal) and athermal (granular) regimes. For the smallest particles, thermal agitation promotes slow creep flows, and piles always flatten completely regardless of their initial inclination angle, resulting in $θ_r = 0$. Above a critical particle size, piles of colloids stop flowing at a finite angle of repose, which increases with particle size but remains below the minimal value expected for athermal frictionless granular materials: $0 < θ_r < θ_{ath} \approx 5.8°$. We quantify the arrest dynamics as a function of the gravitational Péclet number $Pe_g$, which characterizes the competition between particle weight and thermal agitation. Our measurements are consistent with a recent rheological model [Billon et al., Phys. Rev. Fluids 8, 034302, 2023], in which the arrested state stems from a crossover between glass and jamming transitions as the granular pressure in the pile increases relative to the thermal pressure.

Elastodynamic cohesive-zone models for defects such as cracks or dislocations (such as the Geubelle-Rice model for cracks, or the Dynamic Peierls Equation for flat-core dislocations), feature the same stress-response convolution kernel in space and time. It accounts for in-plane elastic wave propagation, while its associated instantaneous radiative term accounts for radiative losses in the surrounding medium. These objects are well-known for isotropic elasticity, with their space-time representations involving generalized functions. For anisotropic elasticity they were unknown. The paper presents a derivation using the Stroh formalism. Their Fourier representation rests exclusively on the so-called prelogarithmic Lagrangian factor $L(v)$, while their space-time form involves its derivative $p(v)=L'(v)$, the prelogarithmic impulsion function. A straightforward consequence is the reformulation of the stress in the Weertman model of steadily-moving dislocations in terms of $L(v)$. Special care being paid to the causality constraint, the theory covers indifferently subsonic, intersonic and supersonic regimes of motion. The theory proposed is suitable to phase-field-type Fourier-based numerical codes for planar systems of defects in anisotropic elastodynamics.

Model-based policy optimization is a well-established framework for designing reliable and high-performance controllers across a wide range of control applications. Recently, this approach has been extended to model predictive control policies, where explicit dynamical models are embedded within the control law. However, the performance of the resulting controllers, and the convergence of the associated optimization algorithms, critically depends on the accuracy of the models. In this paper, we demonstrate that combining gradient-based policy optimization with recursive system identification ensures convergence to an optimal controller design and showcase our finding in several control examples.

The local solar gravitational potential forms a basin for ultralight dark matter (ULDM), with discrete energy levels. Even if barely populated, it introduces a new characteristic timescale in DM dynamics. This necessitates a generalization of the notion of coherence time. We find that, at long times, the phenomenon of recoherence emerges, whereby a subcomponent of ULDM exhibits a formally divergent coherence time. The fact that this generalized coherence time can significantly exceed the naive estimate implies an enhanced sensitivity for dark matter searches that accumulate data over extended observation periods.

We investigate the sensitivity of the Electron-Ion Collider (EIC) to invisible final states in coherent exclusive electroproduction. The characteristic signal is a forward proton with reduced energy and little additional detector activity. Using the excellent particle detection capabilities and kinematics reconstruction at the EIC, we argue that backgrounds can be strongly suppressed. While our analysis applies to various states, we specifically focus on pseudoscalar particles: (i) neutral mesons ($π^0,η^{(\prime)}$), whose invisible Standard Model decays are extremely suppressed, and (ii) gluon-coupled axion-like particles (ALPs) decaying invisibly to a dark sector. Depending on the meson species and the achievable background rejection, the EIC could strengthen existing bounds on invisible decays of pseudoscalar mesons by up to four orders of magnitude, probing branching ratios as small as ${\rm BR}(η^{(\prime)}\to{\rm inv})\sim 10^{-8}$. In addition, the EIC would directly probe invisibly decaying ALPs with the couplings up to $f_a\sim 10^5\,\text{GeV}$ and masses in the range $0.1$-$2\,\text{GeV}$.