The spatial distribution of the chemical reservoirs in protoplanetary disks is key to elucidate the composition of planets, especially habitable ones. However, the partitioning of the main elements among the refractory and volatile phases is still elusive. Key parameters such as the carbon-to-oxygen C/O elemental ratio and the ionization fraction remain poorly constrained, with the latter potentially orders of magnitude lower than in the interstellar medium. Moreover, the thermal structure of the gas is also poorly known, despite its deep influence on gas-phase chemistry. In this context, ortho-to-para ratios could provide selective and sensitive probes. Recent ALMA observations have measured the spatially resolved column density of ortho-and para-H2CO in the transition disk orbiting TW Hya and derived the radial profile of the ortho-to-para ratio. Yet, current disk models do not include the nuclear-spin-resolved chemistry required to interpret these observations. The present work aims to fill this gap, by combining a parametric disk physical model of TW Hya with the UGAN network, updated to include a comprehensive description of the nuclear-spin-resolved chemistry of formaldehyde. This new model reproduces the observed column density of H2CO to within a factor of 2, as well as the measured ortho-to-para ratio which varies from 1.5 in the outer disk to 3 inside 90au. In particular the low value of this ratio beyond 90au is well explained by our model. However, the statistical value of 3 measured below 70au cannot be reproduced, suggesting that additional processes involving ices may be involved. Our parameter space exploration shows that the abundance of H2CO is highly sensitive to the C/O elemental ratio and to the cosmic-ray ionization rate. Future observations of ortho-and para-H2CO, based on well selected rotational transitions, in a large sample of disks, appear highly desirable.

We improve the description of pion-photon interactions in the radiative return process $e^+e^-\to π^+π^-γ$ at the next-to-leading order by including the pion form factor in the Feynman rules. We present a general calculation of the new amplitudes, and provide an implementation easy to interface with any Monte Carlo generator. We incorporate this framework into the event generator $\texttt{Phokhara}$ and study several experimental configurations. Overall, we find percent-level effects appearing in angular differential cross section distributions at colliders whose centre-of-mass energies lie near the peak of the pion form factor. By contrast, total cross sections and distributions in charge-even variables show effects only at the permille level, or no visible differences at all. Finally, we compare the new predictions with KLOE measurements of the forward-backward asymmetry in order to assess the predictive power of the modifications.

We establish a microstructural foundation of the rough Bergomi model. Specifically, we consider a sequence of order driven financial market models where orders to buy or sell an asset arrive according to a Poisson process and have a long lasting impact on volatility. Using a recently established C-tightness result for càdlàg processes we establish the weak convergence of the price-volatility process to a log-normal rough volatility model. Our weak convergence result is accompanied by weak error rates that employ a recently established Clark-Ocone formula for Poisson processes and turn our microstructure model into viable alternative to classical simulation schemes. The weak error rates strongly hinge on Poisson arrival dynamics and are novel to the rough microstructure literature.

The unprecedented accuracy of JWST has led to the detection of silicate clouds in exoplanet atmospheres, allowing for the first time to probe cloud formation in extreme environments. While parametrized cloud descriptions can fit these observations, the results do not fully agree with microphysical models. To bridge this gap, we developed Nimbus, a fast microphysical cloud model that can constrain cloud formation processes from observations and utilize Virga, an equilibrium condensation model balancing gravitational settling and diffusion. Using both models, we investigate WASP-107 b, WASP-17 b, VHS-1256 b, and YSES-1 c to determine their cloud structure and constrain cloud formation processes. Our results show that all four planets have cluster-sized silicate particles (r ~ 1 nm) at high altitudes. Within Nimbus and Virga, these particles can only be explained by highly inefficient cloud particle settling (fsed < 0.1) or by inefficient growth rates due to low sticking coefficients (s < 0.0001). Our results also show that the sticking coefficient is directly linked to the vertical extent of clouds and can therefore be constrained using the broad shape of the spectral energy distribution. The sticking coefficients found for VHS-1256 b and YSES-1 c are in agreement with expectations from laboratory experiments under Earth-like conditions (0.01 < s < 0.3). Panchromatic observations were crucial to achieve these constraints. Future cloud studies should therefore aim to combine observational data from 1 micron to 10 micron whenever possible.

The development of laser materials with absorption/emission spectra in the atmospheric transparency band 2-5 microns is of great interest for modern applications. Triple-doped zinc selenide crystals activated with chromium, cobalt, and iron ions were grown by the vertical Bridgman method under high argon pressure. Comparative X-ray diffractometry, infra-red spectroscopy, and other studies of grown crystals were conducted. Features of their growth, morphology, and optical properties related to the crystal structure were discovered.

Towers of quantum many-body scars are sets of highly-excited eigenstates of nonintegrable Hamiltonians whose dynamics shows athermal behavior and persistent oscillations in time. The preparation of such states is, however, challenging due to their entanglement content. In this work, we show that local properties of such states can be prepared by interspersing the scarred dynamics with stochastic resets to much simpler unentangled product states. Stochastic resetting amounts to reinitializing the many-body wavefunction of the system at random times to a predefined state, which we choose to be in the scarred subspace. We derive several analytical results for the ensuing dynamics, e.g., for the time evolution of the fidelity and of local observables. Resetting damps the scarred oscillations and generates spatial off-diagonal long-range order in the ensuing stationary state. The latter shows mixedness that scales logarithmically as a function of the system size, which follows from the structure of the scarred eigenstates. We prove that such stationary states are locally equivalent, in the sparse-resetting limit, to a single pure scarred eigenstate, which is determined by the reset state. This protocol thereby might represent a route to the experimental preparation of the local properties of correlated and entangled states through resetting.

(See paper for full abstract) This study reports on the benchmarking of a protocol for the adjustment of the parameters of a local leading-order (LO) T=1 (like-particle) pairing EDF that consists in adjusting the density-dependence of the 1S0 pairing gap at the chemical potential in infinite nuclear matter (INM). When using a suitably chosen reference calculation, this protocol leads to consistent results for the odd-even staggering of masses of spherical and heavy deformed nuclei and also for the rotational moments of inertia calculated in a time-reversal-breaking cranked HFB approach. The implementation of the HFB solver for infinite matter at arbitrary isospin asymmetry used for this study is sketched in appendices. Additional points that are discussed concern (i) the illustration that the gaps at the chemical potential are not necessarily sufficient to completely characterise the pairing interaction in infinite matter, and that adjusting LO pairing EDF to reproduce gaps obtained from finite-range pairing interactions in HFB or from more microscopic calculations can lead to unrealistic predictions for finite nuclei; (ii) the finding that some regions of the parameter space for the density dependence of the T=1 LO pairing EDF lead to a spurious transition to a Bose-Einstein condensate of di-nucleons in spite of producing realistic pairing correlations for well-bound nuclei; (iii) the correlation between effective mass and the parameters of the LO pairing EDF that control the form factor of the density dependence when reproducing pairing gaps in infinite matter, (iv) the significant impact on the odd-even staggering of masses made by either including or not the spin-gradient terms in the particle-hole part of the Skyrme EDF; (v) the sizeable impact of keeping or not the contribution from the density-dependent LO pairing EDF to the mean fields on the odd-even staggering of radii.

We show that the scaling limit of the random walk loop soup on suitable planar graphs is the Brownian loop soup, under a topology on multisets of unrooted, unparameterized, and macroscopic loops. The result holds assuming only convergence of simple random walk to Brownian motion, a Russo-Seymour-Welsh type crossing estimate, and the bounded density of the graphs. The proof relies on Wilson's algorithm and Schramm's finiteness theorem. Precisely, we approximate the random walk loop soup by the set of loops erased in a greedy variant of Wilson's algorithm, thereby establishing convergence. The resulting limit is identified using the result of Lawler and Ferreras arXiv:math/0409291.

Quantum algorithms for selecting a subspace of Hamiltonians to diagonalize have emerged as a promising alternative to variational algorithms in the NISQ era. So far, such algorithms, which include the quantum selected configuration interaction (QSCI) and sample-based quantum diagonalization (SQD), have been formulated in second-quantization in Fock space, which leads to inefficient usage of qubit resources. We introduce the first QSCI algorithm developed in the CI-matrix (CIM) framework, which is known to have optimal qubit scaling of exactly $\lceil \log_2 (N_{CSF}) \rceil$ where $N$ is the size of the CIM. In addition, we introduce a novel single-bit flip error mitigation which comes at the overhead of a single qubit and we combine this with a stochastic approximate Trotterization evolution adapted from qDRIFT. Simulating benchmark N$_2$ and naphthalene molecules on quantum hardware, our results achieved similar accuracy as SQD methods but with significantly less quantum resources. However, our CIM-QSCI algorithm and SQD methods could not match the performance of classical heat-bath CI (HCI) for the same task. Hence, we introduce an augmented version of QSCI called quantum selected heat-bath CI (QSHCI). This variant replaces classical heat-bath sampling with quantum sampling from QSCI to achieve performance comparable to HCI. We note that a current drawback of our approach is the preprocessing cost of $\mathcal{O}(N^2\log N)$ for constructing the CIM and performing the Pauli decomposition. This can be further improved by considering efficient CIM access models for the stochastic Trotter evolution.

We consider complex-valued functions on the complex plane and the task of computing their zeros from samples taken along a finite grid. We introduce PhaseJumps, an algorithm based on comparing changes in the complex phase and local oscillations among grid neighboring points. The algorithm is applicable to possibly non-analytic input functions, and also computes the direction of phase winding around zeros. PhaseJumps provides a first effective means to compute the zeros of the short-time Fourier transform of an analog signal with respect to a general analyzing window, and makes certain recent signal processing insights more widely applicable, overcoming previous constraints to analytic transformations. We study the performance of (a variant of) PhaseJumps under a stochastic input model motivated by signal processing applications and show that the input instances that may cause the algorithm to fail are fragile, in the sense that they are regularized by additive noise (smoothed analysis). Precisely, given samples of a function on a grid with spacing $δ$, we show that our algorithm computes zeros with accuracy $\sqrtδ$ in the Wasserstein metric with failure probability $O\big(\log^2(\tfrac{1}δ) δ\big)$, while numerical experiments suggests even better performance.

The exoALMA Large Program has revealed a wealth of substructures in the dust and molecular line emission of several protoplanetary discs, suggesting that planet formation may unfold within highly dynamic environments. Using synthetic observations of planet-disc interactions and disc instabilities, we demonstrate how the origin of these substructures can be investigated through a tomographic study of molecular lines, extending the scope of the analysis beyond line-centroid kinematics alone. Our results indicate that with only a few hours of ALMA integration at moderate angular resolution ($0.15''-0.30''$), it is possible to identify the key signatures driven by planets more massive than 0.1% of the stellar mass. These signatures manifest not only as deviations from Keplerian motion but also as localized line broadening, enabling accurate constraints on the orbital radius and azimuthal location of the planets. We further show that a diagnostic based on line skewness in spectrally resolved observations can help distinguish between planetary and instability-driven signatures, owing to the distinct degrees of velocity coherence associated with each mechanism. Finally, we apply this tomographic analysis to exoALMA CO line data for the discs of HD 135344B and MWC 758. In HD 135344B, we identify strongly localized velocity and line-width perturbations, suggesting the possibility of three massive planets embedded in the disc: one at $R=95$ au, exterior to the continuum substructures, and two within dust gaps at $R=41$ au and $R=73$ au. For MWC 758, the dominance of vertical-velocity spirals over localized signatures is consistent with predictions from models of moderate disc eccentricities or warps, potentially induced by a substellar companion in the inner regions of the system.

Practitioners monitoring deployed probabilistic models face a fundamental trap: any fixed-sample test applied repeatedly over an unbounded stream will eventually raise a false alarm, even when the model remains perfectly stable. Existing methods typically lack formal error guarantees, conflate alarm time with changepoint location, and monitor indirect signals that do not fully characterize calibration. We present PITMonitor, an anytime-valid calibration-specific monitor that detects distributional shifts in probability integral transforms via a mixture e-process, providing Type I error control over an unbounded monitoring horizon as well as Bayesian changepoint estimation. On river's FriedmanDrift benchmark, PITMonitor achieves detection rates competitive with the strongest baselines across all three scenarios, although detection delay is substantially longer under local drift.

This paper develops a quantized Q-learning algorithm for the optimal control of controlled diffusion processes on $\mathbb{R}^d$ under both discounted and ergodic (average) cost criteria. We first establish near-optimality of finite-state MDP approximations to discrete-time discretizations of the diffusion, then introduce a quantized Q-learning scheme and prove its almost-sure convergence to near-optimal policies for the finite MDP. These policies, when interpolated to continuous time, are shown to be near-optimal for the original diffusion model under discounted costs and -- via a vanishing-discount argument -- also under ergodic costs for sufficiently small discount factors. The analysis applies under mild conditions (Lipschitz dynamics, non-degeneracy, bounded continuous costs, and Lyapunov stability for ergodic case) without requiring prior knowledge of the system dynamics or restrictions on control policies (beyond admissibility). Our results complement recent work on continuous-time reinforcement learning for diffusions by providing explicit near-optimality rates and extending rigorous guarantees both for discounted cost and ergodic cost criteria for diffusions with unbounded state space.

Thermal Kinetic Inductance Detectors (TKIDs) inherently combine the phonon-limited noise performance of traditional bolometers with the array scalability and responsivity of superconducting kinetic inductance detectors. Using a superconducting resonator as the thermally sensitive element provides high responsivity and tunable dynamic range, with phonon noise set by the cryogenic operating temperature of the free-standing membrane. In this work, MgB$_2$-based TKIDs are demonstrated operating from below 1 K up to 20 K with characterized noise-equivalent power (NEP) using integrated on-membrane heaters. A comprehensive characterization of electrical, thermal, and noise properties is presented. Phonon noise-limited performance is demonstrated from 4 to 8 K.

We quantify which-path information in the absorption and emission of light by a quantum dot along a Ramsey-like sequence. The quantum dot is excited by two successive classical $π/2$-pulses with tunable relative phase, yielding the spontaneous release of coherent superpositions of zero- and one-photon Fock states into two successive time bins. Along the sequence, the first time bin extracts information on the quantum dot energy state, behaving as a which-path detector for the Ramsey interferometer. The which-path information increases over time, and is accessed through the reduction of contrast of the Ramsey fringes. After the second pulse, the information still present in the first time bin controls the emission of coherent light into the second time bin, which is measurable through the reduction of the contrast of self-homodyne interference fringes in a Mach-Zehnder interferometer. Both measurements are in remarkable agreement with theoretical predictions. Our results quantitatively illustrate how which-path information and more generally quantum correlations impact light-matter energy exchanges in the quantum realm.

OpenClaw-like agents offer substantial productivity benefits, yet they are insecure by default because they combine untrusted inputs, autonomous action, extensibility, and privileged system access within a single execution loop. We use OpenClaw as an exemplar of a broader class of agents that interact with interfaces, manipulate files, invoke tools, and install extensions in real operating environments. Consequently, their security should be treated as a software engineering problem rather than as a product-specific concern. To address these architectural vulnerabilities, we propose a blueprint for defensible design. We present a risk taxonomy, secure engineering principles, and a practical research agenda to institutionalize safety in agent construction. Our goal is to transition the community focus from isolated vulnerability patching toward systematic defensive engineering and robust deployment practices.

Global QCD analyses of nuclear parton distribution functions (nPDFs) have traditionally relied on the Hessian method for uncertainty estimation. However, the inherent Gaussian approximation and reliance on local curvature often prove insufficient for nPDF fits, which are frequently characterized by limited data constraints and non-Gaussian likelihoods. In this paper, we present the first nPDF determination based on Markov Chain Monte Carlo (MCMC) techniques, implemented within the nCTEQ framework using an adaptive Metropolis-Hastings algorithm. The MCMC approach enables a direct mapping of the posterior distribution and reveals a highly non-trivial parameter-space structure, including multiple modes and pronounced non-Gaussian behavior, particularly for the valence PDFs. We perform the first single-nucleus global analysis of lead PDFs using exclusively lead data and compare it to a multi-nuclei fit employing a standard analytic A dependence. The inclusion of lighter nuclei reduces quark uncertainties and modifies the shape of the lead PDFs, while leaving the gluon distribution largely unaffected. A complementary Hessian analysis exposes systematic limitations of the Gaussian approximation. Our results demonstrate that MCMC methods provide a more reliable framework for uncertainty quantification in nPDF determinations.

The exoALMA large program provided an unprecedented view of the morphology and kinematics of 15 circumstellar disks, offering a biased but homogenous and well-characterized sample for population-level analysis. Continuum observations revealed numerous dust substructures, known to be potential signatures of embedded planets. We analyze the observed dust morphologies with the simulation-based inference tool DBNets2.0, assuming these are due to embedded planets at fixed locations, to infer the system properties. We estimate the putative planet mass, the disk $α$-viscosity, scale-height, and dust Stokes number that would reproduce 19 substructures in 13 of the 15 exoALMA disks. We compare our results with literature estimates derived with different methods, and find good agreement in most cases. We further explore the implications of the inferred disk properties for accretion, showing that for the Herbig stars in our sample, the implied viscous accretion timescales are too long to account for their observed stellar accretion rates. Regarding planet migration, our results favor inward migration, with only three putative planets expected to migrate outward. Finally, we check for correlations of the inferred disk and planet properties with the disks' gas-to-dust mass ratio, non-axisymmetry index, and masses of the gas, dust, and host stars, finding no remarkable trend.

Stage-IV galaxy surveys will provide the opportunity to test cosmological models and the underlying theory of gravity with unparalleled precision. In this context, it is crucial for the Euclid mission to leverage its spectroscopic and photometric probes to systematically investigate and incorporate non-standard cosmological models, including modified gravity, alternative dark energy scenarios, massive neutrinos, and primordial non-Gaussianity. We produce and release publicly simulated galaxy catalogues from a broad suite of non-standard cosmological simulations, which we processed through a model-independent analytical pipeline, making use of Rockstar for halo identification, and a modified version of the SciPic library for the galaxy-halo connection using the halo occupation distribution framework. We investigate their galaxy-clustering characteristics via the multipoles of the 2PCF in redshift space and VDG, a highly performant model for galaxy clustering. Across a wide range of models, the linear growth rate multiplied by the matter density within spheres of radius 12,Mpc, fs12, exhibits a notable robustness to the choice of cosmological template. Compared to previous works, our study extends this result to numerous scenarios with markedly distinct gravitational or dark energy dynamics. We find that the most of the scatter in cosmological parameter inference already appears when using the cosmological model of the simulations as templates. Using a `wrong' template can also introduce an additional scatter, although with smaller amplitude. Often, we find deviations much larger than error bars, meaning that the Gaussian approximation for the covariance might need to be further studied. Future cosmological investigations must broaden their scope to include a diverse array of non-standard theoretical frameworks, extending beyond LCDM and rudimentary dynamic dark energy models.

Traditional lock-free parallel algorithms for combinatorial optimization problems, such as shortest paths, stable matching, and job scheduling require programmers to write problem-specific routines and synchronization code. We propose a general-purpose lock-free runtime, LLP-FW that can solve all combinatorial optimization problems that can be formulated as a Lattice-Linear Predicate by advancing all forbidden local states in parallel until a solution emerges. The only problem-specific code is a definition of the forbiddenness check and a definition of the advancement. We show that LLP-FW can solve several different combinatorial optimization problems, such as Single Source Shortest Paths (SSSP), Breadth-First Search (BFS), Stable Marriage, Job Scheduling, Transitive Closure, Parallel Reduction, and 0-1 Knapsack. We compare LLP-FW against hand-tuned, custom solutions for these seven problems and show that it compares favorably in the majority of cases.

Diamond detectors are attractive for operation in harsh radiation environments because they combine radiation tolerance, fast signal formation, and low leakage current. Realistic detector-response simulations require an accurate description of charge-carrier mobility and trapping, which determine both signal amplitude and timing. In this work, we extend \allpix{}, a modular end-to-end detector simulation framework, with diamond-specific transport models. The implementation includes field-dependent mobility parameterizations for electrons and holes and an effective trapping model based on the charge collection distance (CCD), providing a detector-level interface to material quality and radiation-damage measurements. The mobility description is validated in the negligible-trapping limit using single-crystalline CVD diamond by comparing simulated drift velocities and transient-current signals with published reference data. For polycrystalline CVD diamond, the CCD-based trapping model is evaluated using experimentally measured CCD values and compared with laboratory transient-current-technique waveforms. The simulations reproduce the measured drift-velocity behavior in scCVD and the reduced charge collection and degraded transient response observed in pcCVD. The presented implementation enables detector-level studies of charge collection, pulse formation, and timing performance in diamond sensors using experimentally accessible transport and trapping parameters, and provides a practical framework for simulation-driven detector development and radiation-damage studies.

We derive a dS$_4 \times \mathbb R$ quotient spacetime that is asymptotically dS$_4$, where the quotient makes its past boundary oppositely oriented relative to its future boundary. This introduces a lightlike singularity that severs the antipodes of the spacetime and simplifies its global vacuum to a trivial product on antipodal static patches. We show that this state is conformal to the vacuum of an infinite orientable cover of a non-orientable AdS$_3$ spacetime with an S$^2$ bundle. The vacuum's separability extends to its holographic dual, which is a product of Cardy states. We find that this candidate dS$_4$ vacuum state is perturbatively unstable within quantum gravity due to a vanishing Hagedorn temperature.

Quantum-enhanced interferometry is often discussed in terms of ideal resources and asymptotic scalings, whereas in practice its performance is set by a delicate interplay between losses, state imbalance, and photon number. We address this interplay in a folded Franson interferometer fed with partially entangled N00N states, treating asymmetric losses and tunable input imbalance on equal footing. From exact detection probabilities we obtain closed-form expressions for the fringe visibility and the Fisher information, and show that these two figures of merit respond very differently to imperfections. In particular, we demonstrate that perfect interference contrast can always be recovered by compensating loss asymmetry with an appropriate input imbalance, while the Fisher information generally peaks at a distinct operating point, reflecting the irreducible trade-off between coherence restoration and signal attenuation. By determining the exact optima and benchmarking against single-photon strategies, we identify the critical loss and minimum entanglement required to maintain a genuine quantum advantage over optimized single-photon strategies under identical loss conditions, and establish their scaling with the photon number N . Beyond delineating the fundamental trade-offs between loss, entanglement, and sensitivity, this work establishes a comprehensive theoretical framework that both underpins and extends the experimental demonstration of quantum advantage reported in [1], providing a unified description of the relevant operating regimes.

The Mayer-Vietoris theorem is known for its wide applications, especially in determining homology. In fact, this theorem provides us with a long exact sequence, where the underlying homology groups fit in. However, this theorem does not provide an explicit way to compute homology. In this paper we prove an ``effective" version of the Mayer-Vietoris theorem using discrete Morse theory. Suppose, we have a Mayer-Vietoris type setup, i.e., let $X$ be a simplicial complex and $A$ and $B$ be two subcomplexes of $X$, such that $A \cup B=X$. Moreover, let $\mathcal{W}_A$, $\mathcal{W}_{B}$ and $\mathcal{W}_{A \cap B}$ be gradient vector fields on $A$, $B$ and $A \cap B$ respectively (which need not be ``coherent", i.e., they do not need to coincide on their intersection). Then, the main theorem of our paper provides an explicit way to compute the homology groups of $X$, using the combinatorial information regarding the trajectories of the aforementioned gradient vector fields, we do not even need to know the individual homology groups $H_{*}(A)$, $H_{*}(B)$ and $H_{*}(A \cap B)$. In principle, the homology of $X$ can always be computed explicitly using our theorem irrespective of the choice of the gradient vector fields. Further, if we choose the subcomplexes $A$ and $B$ wisely so that each of $A$, $B$ and $A \cap B$ admits an efficient gradient vector field, then the computation of the homology groups is considerably reduced.

We present a detailed analysis of the structural parameters of the globular cluster M 15 using g- and i-band photometric data from Pan-STARRS1 DR2. The central coordinates ($X_{\rm{C}}, Y_{\rm{C}}$), ellipticity ($ε$), and position angle (PA) are derived via two independent methods: ellipse fitting of the two-dimensional stellar number isodensity distribution and Markov Chain Monte Carlo (MCMC) sampling. Our analysis of 38 stellar density intervals reveals a cluster center offset by only $4\,.\!\!^{\prime\prime}1\pm9\,.\!\!^{\prime\prime}6$ from the commonly accepted in the literature value, a good agreement on the order of our map resolution. We find a radial variation in the ellipticity, with a mean value of $ε=0.09\pm0.02$ for the inner region ($R\leq4\,.\!\!^{\prime}5$) and $ε=0.04\pm0.02$ for the outer region ($R>4\,.\!\!^{\prime}5$), where the errors correspond to $1σ$. The MCMC analysis of 75 datasets yields a mean $ε=0.022\pm0.005$ for the entire cluster. The PA remains constant with increasing distance from the cluster center, $\rm{PA}=44\,.\!\!{\rm{^\circ}}4\pm16\,.\!\!{\rm{^\circ}}2$, and the MCMC method providing a consistent value of $\rm{PA}=46\,.\!\!{\rm{^\circ}}6\pm7\,.\!\!{\rm{^\circ}}1$. Our results are in agreement with some recent studies but challenge others, suggesting that a single $ε$ value may be insufficient to fully characterize the overall oblateness of M 15 due to incompleteness and crowding effects in its core.

The penguin loop-suppressed $B\toϕK$ decays are highly sensitive to contributions of hypothetical heavy new particles. Particularly interesting probes for testing the Standard Model and revealing such phenomena are provided by CP violation in the $B^0_d\toϕK_{\rm S}$ decay. Standard-Model estimates for the corresponding CP-violating observables are theoretically limited by doubly Cabibbo-suppressed penguin contributions. We study these effects using a factorization approach, and provide predictions for CP asymmetries, to be contrasted with future measurements. To gain additional insight into these hadronic effects, we propose the $B_s^0\toϕK_{\rm S}$ decay as a new channel. We predict the observables for this decay for which currently no measurements exist. By comparing $B^0_d\toϕK_{\rm S}$ and $B^+ \to ϕK^+$, we further derive state-of-the-art constraints on isospin observables within the Standard Model. The same framework enables probing of possible New-Physics contributions, including general effects and those with non-trivial isospin structure. Interesting prospects arise for the high-precision era of flavour physics ahead.

We report on our continued efforts to measure the glueball and meson spectra in SU($N$) Yang-Mills theory and QCD with the aim of extrapolating to the large-$N$ limit. In particular, we document the computation of the low-lying SU($6$) spectrum. We employ a multilevel sampling algorithm to measure glueball correlators to reduce statistical noise in the large-time separation limit. The gluon operator basis is composed of spatial Wilson loop measured at different levels of (APE) smearing, with vanishing momentum selected to maximise the orthonogality of the operators and their overlap with the lowest lying states. We also report on analogous computations for the $J=0,1$ non-singlet meson spectrum with two degenerate quark flavors.

We investigate a specific emergent dark energy scenario, known as critically emergent dark energy (CEDE), in which dark energy is effectively absent in the early Universe and becomes dynamically relevant only after a critical cosmic epoch through a phase transition. We constrain this model using recent cosmological observations, including cosmic microwave background (CMB) data from \emph{Planck} 2018, baryon acoustic oscillation (BAO) measurements from SDSS and DESI DR2, and two independent Type Ia supernova compilations, PantheonPlus and Union3. Our results show that within the CEDE framework a dark energy phase transition is not ruled out. In particular, CMB-only, CMB+SDSS, and CMB+DESI datasets provide evidence for a nonzero transition scale factor and, according to standard statistical indicators such as $Δχ^2$ and Bayesian evidence, can favor CEDE over the $Λ$CDM model. At the same time, we find that CEDE does not fully resolve the Hubble constant tension. Overall, our analysis indicates that dark energy models featuring a phase transition remain a viable and phenomenologically interesting extension of the standard cosmological framework. Upcoming high-precision cosmological surveys will be essential to further assess whether such emergent dark energy scenarios represent a genuine departure from $Λ$CDM or an effective description of current data.

This paper proposes a unified decision making and local trajectory planning framework based on Time-Varying Artificial Potential Fields (TVAPFs). The TVAPF explicitly models the predicted motion via bounded uncertainty of dynamic obstacles over the planning horizon, using information from perception and V2X sources when available. TVAPFs are embedded into a finite horizon optimal control problem that jointly selects the driving maneuver and computes a feasible, collision free trajectory. The effectiveness and real-time suitability of the approach are demonstrated through a simulation test in a multi-actor scenario with real road topology, highlighting the advantages of the unified TVAPF-based formulation.

We establish a variant of the log-Sobolev and transport-information inequalities for mixture distributions. If a probability measure $π$ can be decomposed into components that individually satisfy such inequalities, then any measure $μ$ close to $π$ in relative Fisher information is close in relative entropy or transport distance to a reweighted version of $π$ with the same mixture components but possibly different weights. This provides a user-friendly interpretation of Fisher information bounds for non-log-concave measures and explains phenomena observed in the analysis of Langevin Monte Carlo for multimodal distributions.