It is well-known that first-order methods can offer accelerated convergence rates in the presence of growth structures. Restarting schemes provide a general tool for such speed-ups. These schemes typically either require unrealistic problem knowledge, incur logarithmic overhead factors in oracle complexity, and/or have a nontrivial initial burn-in phase. We present a parameter-free approach for restarting any first-order method, avoiding these three drawbacks. Our approach dynamically deploys parallel instances of a given first-order method communicating progress in the style of Renegar and Grimmer. Our optimized scheme avoids expensive burn-ins and only requires $O(\log\log(1/ε))$ parallel processes when the accelerated rate is sublinear.

For the Sparre Andersen non-life insurance model with investments in an arbitrary Lévy process, we establish the exact power-law asymptotics of the ruin probability $Ψ(u)\sim C^* u^{-β}$ as $u\to\infty$ with a positive finite constant $C^*$; the exponent $β$ is the Cramér root of the Laplace exponent of the Lévy process describing the logarithm of the risky asset price. This strengthens previously known two-sided estimates of the order -- the existence of an exact limit had remained an open question. The proof combines a reduction to discrete time, the one-dimensional Kesten-Goldie theorem for the stationary measure of the associated affine recursion, and Goldie's result on the asymptotics of the supremum of a perpetuity.

In this work, we review gravitational-wave generation in a two-scalar-field cosmological model. The framework relies on a two-field scenario in which warm inflation is unified with the dark sector within a single theoretical description. It has recently been shown that this setup leads to a gravitational-wave spectrum potentially detectable by future experiments. Here we also demonstrate that the resulting spectrum is largely independent of the $ϕ$ field initial condition, thereby extending previous findings.

The free energy principle casts perception as variational inference, but its biological implementation is underspecified. The generalized-coordinate formalism is not a literal claim that neurons compute arbitrary Taylor expansions. This paper argues that generalized synchronization (GS) provides the missing bottom-up mechanism. Certain recurrent circuits satisfy a contraction property: nearby trajectories converge exponentially. A contracting circuit driven by structured sensory input synchronizes to driving dynamics. Under generic embedding conditions, the resulting synchronization map embeds the low-dimensional sensory manifold into neural state space. The geometry predicted by the free energy principle is not imposed from above by an explicitly Bayesian neural calculus. It arises from ordinary recurrent dynamics. I then propose a developmental extension. Hebbian plasticity acting on the correlations generated by sensory-driven synchronization shapes the embedded manifold into recurrent connectivity, producing a continuous attractor network that approximates the embedded sensory manifold. Prediction-separation results bound the representational fidelity of the resulting circuit by prediction accuracy: where the network predicts future observations well, the synchronization map separates underlying states; where prediction fails, the representation collapses. The collapses are observable as categorical perception, metameric equivalence, and discrimination thresholds. On this view, mature head-direction, grid-cell, and stimulus-driven visual manifolds are developmental products of three interacting processes: dynamical contraction, generalized synchronization, and correlation-based plasticity. The central open problems are whether the Hebbian fixed point exists and whether Hebbian dynamics produce a sufficiently accurate predictor on the relevant input distribution.

Integrated sensing and communication (ISAC) has emerged as a key technology for 6G wireless networks. In this paper, wireless sensing for the indoor multi-person tracking is explored with 6G mmWave ISAC systems. To limit the sensing overhead, a sparse deployment of sensing reference signals (RS) is applied in the orthogonal frequency-division multiplexing (OFDM) frame, where the channel state information (CSI) at the sensing RS is extracted for the multi-person tracking. To enable a robust tracking of multiple persons in a complex indoor environment, three key mechanisms are proposed: 1) a modified moving target indicator (MTI) scheme is proposed to remove the static environmental clutter under a sparse RS time spacing; 2) an effective target identification mechanism is developed to exclude false target points; 3) the Kalman filter with a penalty association algorithm is designed to associate the detected points with the right tracks, especially handling the crossover case of two tracks. With the above mechanisms, multiple persons can be effectively tracked with an extremely low sensing overhead. An mmWave bistatic ISAC prototype system at 26 GHz with 500 MHz bandwidth has been developed to validate our design, where the overhead of the sensing RS is less than 0.005\%. Experimental results demonstrate that our proposed design achieves a median position error of 12 cm for multi-person tracking with path-crossing in the indoor environment with a single receiver.

Finitely dependent processes generalize independent processes by requiring that the restrictions of the process to sufficiently separated sets are independent. The existence of stationary finitely dependent processes on combinatorial models like $\mathbb Z^d$ subshifts can be quite mysterious. For instance, Holroyd and Liggett constructed such processes on proper $4$-colorings of $\mathbb Z^d$ for all $d$ while Holroyd, Schramm and Wilson showed that there are no such processes on proper $3$-colorings of $\mathbb Z^d$ for $d>1$. In this paper, we take inspiration from these results and investigate them further. On the positive side, we show that there exists a dense set of stationary finitely dependent processes supported on subshifts with strong mixing properties like the finite extension property. On the negative side, we see that the cohomology of the subshifts can form an obstruction to the existence of such processes. In particular we use Conway-Lagarias-Thurston height functions to characterize when there exists a finitely dependent process on the space of tilings by boxes of $\mathbb Z^2$ answering the tiling problem posed by Gao, Jackson, Krohne and Seward in dimension $2$. The ideas also apply to many other models, such as graph homomorphisms and ribbon tilings. On the way, we also show that continuous cocycles on strongly irreducible subshifts valued in a special class of groups (including torsion free Gromov hyperbolic groups and free product of cyclic groups) are perturbations of group homomorphisms.

Cryogenic applications in high-energy physics (HEP) demand reliable, low-power CMOS electronics capable of operating at liquid nitrogen temperatures (77 K). The open-source SkyWater 130 nm (SKY130) CMOS process has previously been shown to operate at temperatures as low as 4 K making it a promising candidate for HEP applications. In this work, we characterize and model SKY130 low-threshold voltage transistors at 77 K, which is a temperature commonly used in modeling applications for liquid argon detectors. DC characteristic measurements were performed at both room temperature and liquid nitrogen temperature. We created a cryogenic modeling approach to produce a SPICE-compatible, isothermal BSIM4-based model for select transistor sizes at 77 K. The resulting model agrees with data at 77 K with an average error on the order of 20% (relative RMS) and shows no dependence on drain voltage. Due to the open-source nature of SKY130, we have made our models publicly available on Github. We hope this work will continue the trend for democratizing circuit design at cryogenic temperatures in high-energy physics by enabling open access to accurate CMOS device models at 77 K.

We provide analysis for the posterior distribution and expectation of $(p_1, p_2)$ where $Y|p_1,p_2 \sim \hbox{Binomial}(n, p_1 p_2)$ and $ (p_1, p_2)$ is uniformly distributed on the unit square $[0,1]^2$. We exhibit interesting expressions in terms of a truncated Beta distribution, a finite mixture of Beta distributions and harmonic numbers, and derive a simple large sample size $n$ approximation for the posterior expectations $\mathbb{E}(p_i|y)$ as well as for the normalization constant in the posterior joint density.

We present a new phenomenological model for phase transformation (PT) kinetics in metals, the "Fermi Kinetic Phase Transition (KPT) Model". It is designed such that it captures the main macroscopic features of our previously developed micro-structure dependent model, but at a fraction of the computational cost of the latter. Using four model parameters, the Fermi KPT model performs better than other phenomenological PT kinetics models in the literature, as shown by our present comparisons to experimental data for iron and tin.

We propose a new Bayesian model calibration formalism as an alternative to the Kennedy O'Hagan (KOH) framework which we term integrated bias with full uncertainty (IBFU). In KOH, calibration parameters are modeled as fixed, but unknown distributions with relatively weak prior constraints, and their posteriors are inferred jointly with an additive discrepancy Gaussian Process (GP). This formulation often provides limited regularization and leads to confounding pathologies when applied to inexact models with sparse, noisy measurements. By contrast, we represent each calibration parameter as the sum of a fixed best estimate value and a parameter correction represented by an independent GP over the input space, equipped with strong shrinkage priors. Any residual discrepancy that cannot be addressed via parameter correction is captured by an additive discrepancy GP operating on the simulator, similar to KOH. We then impose orthogonality constraints to mitigate confounding between the simulator and modeled additive discrepancy and colinearity between model parameters. Imposing strong complexity shrinkage via conservative hyperpriors forces the mean parameter correction to remain flat across the domain, resulting in predictions that essentially converge with the KOH formulation. However, upon relaxing complexity shrinkage, should the data provide evidence that the effective calibration parameter varies across the domain, the mean parameter correction is allowed to become a function of the domain in a controlled, structured manner. In this sense, our approach is more universal: it effectively nests KOH as a special case while extending it to input dependent calibration, and it is more tightly constrained, because it anchors the true values around the best estimates and the shrinkage prior actively regularizes the calibration parameters.

We study a class of content delivery network design problems in which service performance is explicitly modeled through queueing-based response times. In contrast to standard formulations relying on distance-based approximations, the resulting models incorporate congestion effects and give rise to nonlinear expressions involving ratios of affine mappings, reciprocal terms, and interactions across multiple traffic classes. To address these challenges, we develop a systematic framework based on mixed-integer conic liftings that enables exact reformulations of such expressions within a tractable optimization paradigm. The proposed approach combines McCormick-type envelopes and second-order cone representations to derive mixed-integer conic programming formulations that jointly capture geometric design decisions and stochastic service dynamics within the same system. The framework is first introduced in a single-server setting, where the optimal solution exhibits a connection with the classical Fermat--Weber problem, and is then extended to the multi-server case, leading to a general formulation that simultaneously optimizes server locations, capacity allocation, and routing decisions. Computational experiments on a realistic case study illustrate the impact of congestion-aware modeling on network design and demonstrate the effectiveness of the proposed formulations when solved using modern conic optimization solvers.

In approval-based multiwinner voting, Pareto optimality is used as an axiom capturing efficiency of committees. We study the structure of the space of Pareto optimal committees in restricted domains and in general by investigating the monotonicity and reconfigurability of such committees. For the Candidate Interval and Voter Interval domains, we propose the Single Dominance Only property, which provides a simple characterization of Pareto optimality, and show that Pareto optimal committees satisfy committee monotonicity using this property. Further, we show that, for the above domains, any Pareto optimal committee can be reconfigured into any other Pareto optimal target committee without using auxiliary candidates, meaning that the candidates in the starting but not the target committee can be replaced by candidates in the target but not the starting committee one by one while preserving Pareto optimality at every step. In addition, we adapt a polynomial-time algorithm for finding a committee satisfying EJR+, a proportionality axiom, such that it also satisfies Pareto optimality, for the above domains. We further describe a polynomial-time algorithm for counting the number of Pareto optimal committees for voting instances satisfying Voter Interval, and give a proof idea for its correctness. For the unrestricted domain, we explain the challenges of proving committee monotonicity and reconfigurability. We provide an example in which the distance of two committees in the Pareto optimality reconfiguration graph exceeds the distance proven for the above domains, and outline an approach toward showing the connectedness of the graph.

We present a theory of point estimation with e-statistics (e-values and e-processes) by introducing the "ME-estimator": the parameter that minimizes the corresponding e-statistic, or the evidence against it. Our approach is based on the intuitive idea of e-statistics as a measure of evidence and betting pay-off, and naturally generalizes the classical method of maximum likelihood estimation. First, we establish the consistency as well as the almost sure convergence rate for ME-estimators relating to the high-probability bounds on the size of the confidence set derived from thresholding the e-statistics, an approach that sets ME-estimators apart from traditional M-estimators. Second, we conduct classical M-estimator-style analysis on the consistency and asymptotic normality of ME-estimators in the bounded mean estimation setting, discussing the notion of efficiency (or lack thereof) from various choices of betting strategy. Our work brings e-statistics, a fundamental tool for inference and uncertainty quantification, to the space of estimation.

Microwave dressing of Rydberg ions creates tunable eigenstates with controllable polarizability and interaction strength, but coherent navigation between these states has remained elusive. Here, we report on the first demonstration of coherent population transfer between different Rydberg states of a trapped ion. We investigate both microwave-mediated Rabi oscillations between Rydberg S and P states and adiabatic transfer between microwave-dressed Rydberg states. Between Rydberg S and P states we achieve a population transfer efficiency of 91.5(5)% in a single microwave $π$-pulse. Microwave dressing hybridizes the S and P Rydberg states into new eigenstates with tunable polarizability, enabling both noise-resilient zero-polarizability states and maximally interacting states. We demonstrate adiabatic transfer between these zero-polarizability and maximally dressed states, enabling experiments that combine noise-resilient excitation with strong dipole-dipole interactions and Förster resonance control within a single measurement sequence.

Controlling nitrogen doping in diamond is key to advancing nitrogen-vacancy (NV) center devices. We harness the hillock, a typically undesirable surface feature, to incorporate high densities of grown-in, aligned NV-centers on a (001)-oriented substrate. Enhanced cathodoluminescence at hillock sidewalls is correlated via nanoSIMS to up to 1000x greater nitrogen incorporation compared to the planar film. We find that these hillocks are associated with stacking faults and edge-type dislocations, consistent with an origin in surface preparation rather than substrate screw dislocations. Yet, the growth is orderly enough that each of the four hillock sidewalls hosts a distinct NV orientation. A 1.7-2% grown-in NV/substitutional nitrogen (P1) ratio, 4x higher than typical (001)-oriented growth, is measured via NV decoherence analysis. By revealing that spontaneously formed hillocks act as natural laboratories for dense, aligned NV formation, this work motivates systematic investigation of facet-dependent nitrogen incorporation and preferential NV alignment in (001) diamond.

This work investigates the FeII emission in active galactic nuclei (AGN), combining observational data from optical and near-infrared (NIR) spectra of the prototypical FeII emitter IZw1 with state-of-the-art photoionization modeling. Using updated FeII atomic datasets (Smyth et al. 2019; Tayal & Zatsarinny 2018; Bautista et al. 2015), we explore a wide parameter space to determine the physical conditions of FeII-emitting regions in the broad-line region (BLR). Our results show that optical ($R_{\rm 4570}$) and NIR ($R_{\rm 1μm}$) FeII emission can be simultaneously reproduced under consistent conditions, with the best agreement obtained using the Smyth et al. (2019) dataset, for hydrogen densities of $10^{11.0}$ to $10^{12.0}$ cm$^{-3}$ and near-solar metallicity. We quantify, for the first time, the impact of Lyman-$α$ fluorescence on the physical conditions of FeII emission in both regimes, revealing its dominant role in the NIR and, in contrast, highlighting the stronger influence of collisional processes in the optical. Additionally, for the first time, we compare optical and NIR FeII emission simultaneously with OI and the CaII triplet (CaT), reinforcing their connection to similar spatial regions and physical properties, as well as their usefulness as better proxies for optical FeII. Our findings support the idea of a vertical BLR structure, with NIR FeII and OI originating in less dense regions of the cloud than optical FeII and CaT.

We construct matrices that shift the scaling dimension of scalar fields for arbitrary de Sitter Feynman diagrams. Acting on a set of master integrals, these weight-shifting matrices shift the scaling dimensions of individual edges of a given diagram by an integer. They can thus be applied to a broader range of problems and are simpler to implement than earlier derivative-based approaches. By introducing a Kronecker product representation of our matrix formulation, we generalise weight-shifting operators beyond four-point functions to arbitrary tree-level diagrams. As an application, we obtain explicit expressions for several massless wavefunction coefficients in four-dimensional de Sitter space, starting from conformally coupled seed functions. Our construction provides a systematic and graph-local approach to generating cosmologically relevant correlators from simpler master integrals.

We investigate the diffusion coefficients and mean-squared displacements in a polydisperse granular gas in a homogeneous cooling state by considering the roughness of the particles. We study their dependence on the normal and tangential restitution coefficients. We show that the motility of particles is strongly affected by their mechanical properties and surface characteristics.

We consider a particular Hayashi $R$-matrix and using the FRT-bialgebra technique and Woronowicz's method of construction, we construct a concrete compact quantum group $U_{q,Θ}(3)$ for non zero real $q$ and modulus one complex deformation parameters $θ_{ij}$. We then study in detail the irreducible $*$-representations of the $C^*$-algebra $C(U_{q,Θ}(3))$, using the representations associated with the three dimensional noncommutative torus.

Multidimensional item response theory (MIRT) provides an important psychometric framework for modeling how multiple latent traits jointly influence observed item responses. In most existing estimation procedures, the latent trait distribution is assumed to be Gaussian. Although computationally convenient, this assumption can be restrictive in many applications where the latent distribution exhibits skewness, heavy tails, or multimodality. More importantly, misspecifying the latent distribution may bias the estimation of item parameters and latent traits. To address this limitation, we propose a data-driven flow-based framework for MIRT models that can capture a broad class of non-Gaussian latent distributions. The proposed approach represents the latent distribution as an invertible transformation of a simple base distribution. For efficient estimation, we further introduce a conditional flow as a function of both the observed response and the noise to approximate the posterior distribution. Under this framework, the item parameters, latent distribution, and posterior approximation can be learned jointly. Comprehensive simulation studies show that the proposed method improves item-parameter and latent-trait recovery when the true latent distribution is non-normal. An application to a personality dataset further illustrates the practical utility of the proposed framework for modeling complex latent trait distributions in large-scale data.

We consider polynomial rings over finite fields and rings of integers of imaginary quadratic fields $\mathbb{Q}(\sqrt{-D})$. In this paper, we formulate the density of squarefree elements divisible by all elements of $T$ but by none of $P$, where $T$ and $P$ are subsets of squarefree elements and $T$ is finite. We also define Mersenne irreducibles in order to estimate the density of squarefree elements divisible by none of $P$.

Classical portfolio optimization treats expected returns, covariances, and allocations as deterministic. Modern practice replaces at least one by a distribution: a posterior over parameters, a law of future returns, a stochastic allocation policy, or a distributional-robustness set. We call distributional portfolio optimization (DPO) the unified framework in which weights, returns, and parameters are all modeled as probability measures, organized around the joint coupling Gamma_theta(dw,dr) and its marginal triple (W,R,P). The contribution is synthetic and structural: we organize Bayesian, robust, chance-constrained, stochastic-allocation, and distributional reinforcement-learning portfolio methods through this coupling and prove boundary results connecting them, including a portfolio specialization of Wasserstein-CVaR duality, a static no-randomization theorem, a Bayesian credible-radius calibration of Wasserstein DRO, a Gaussian-isotropic second-order conservatism bound, a conditional two-sided rate W_1 = Theta(n^{-(1+alpha)/2}) governed by the local boundary Holder exponent alpha in [0,1], and a risk-shifted distributional Bellman contraction. A controlled experiment shows that across factor models at K in {10,25,50}, the credible-radius rule lands within 3-7 bp of the oracle out-of-sample tail risk and beats a 24-month validation-tuned radius while spending no validation data. On a K=25 DJIA backtest, equal-weight, no-view Black-Litterman, and Ledoit-Wolf shrinkage attain higher Sharpe than every distributional method; the operational claim is therefore confined to calibration-without-validation and turnover, not raw-return dominance.

The mechanisms that lead to dry Age-related Macular Degeneration are largely unelucidated, which prevents the introduction of effective therapies. Experimental support exists in the literature for the hypothesis that choroidal endothelial cell (ChEC) dysfunction precedes the loss of macular retinal pigmented epithelial (RPE), which may be only a secondary consequence of inadequate blood supply. If so, interventions at the level of ChEC could constitute an under investigated therapeutic strategy. Datasets regarding the transcriptional changes in early or intermediate dry AMD are publicly available, but for some some of them the information about ChECs have not been analyzed, or not analyzed using the most powerful and recent software tools. We present here new data generated by our bioinformatics analysis of these datasets. The main new finding is that angiogenesis is initiated in dry AMD, as it is in wet AMD. However, contrary to wet AMD, in dry AMD angiogenesis fails to execute, and therefore the blood supply that supports the RPE becomes gradually insufficient, leading to their dysfunctionality and death. The data support a unitary hypothesis of the origin / initiation / etiology of both dry and wet AMD, namely that both are initiated by ChEC dysfunction - either insufficient / abortive angiogenesis in dry AMD, or excessive angiogenesis in wet AMD. Pathway analysis also reveals as perturbed Notch and TNF signaling, endothelial to mesenchymal transition (EndoMT), mitochondria, "fluid shear stress", "osteoclast differentiation" and "calcification/osteoporosis". Overall, the new data provide a rationale for experimental studies, to validate and further characterize these perturbations, and investigate strategies to correct them.

Accurate loss characterization is essential for the design of high-frequency power magnetic components. State-of-the-art resonant characterization methods are attractive for high accuracy and low sensitivity, especially at the MHz regime. However, they predominantly rely on manual tuning and computationally intensive Fast Fourier Transform (FFT) analysis to identify resonant conditions, causing both inefficiencies and inaccuracies. To ensure accuracy and expedite the process, this paper proposes a fully automated measurement architecture, the core innovation of which lies in the integration of digitally-controlled switched capacitor sequences and onboard signal processing circuits,enabling automated sweeping of both frequency and drive level for complete and rapid characterization with no human intervention. A design guideline for the switched capacitor sequence is presented and common commercial electromechanical power relays are characterized to enable sub-MHz measurements. Experimental results for several different magnetic materials demonstrate that the proposed system has great accuracy and is able to collect more than 1000 data points within 20 seconds, providing a very fast and robust solution for high-frequency magnetic characterization.

We explore the role of the stability operator in regulating the evolution of marginally outer trapped surfaces (MOTSs). In 2005, Andersson, Mars and Simon showed that if the stability operator is invertible, then the time evolution of a MOTS is unique. Here we focus on moments at which that stability operator is not invertible. Understanding MOTSs as analogous to fixed points, and the stability operator as a linearization of the system of the MOTS-defining equations, bifurcation theory can be used to classify possible non-unique evolutions. MOTS pair creation/annihilation is an example of a saddle-node bifurcation but other possibilities can occur, including pitchfork and transcritical bifurcations. Analytical and numerical tools are used to identify examples of the various bifurcations in a variety of spacetimes. To help analyze those results, we define a generalized MOTS stability operator and discuss the (partial) barrier properties of unstable MOTSs. Spherically symmetric examples are given in Reissner-Nordström-de Sitter spacetime and axisymmetric examples are studied in Reissner-Nordström and Weyl-distorted Schwarzschild. This application of bifurcation theory is very general and so applies to any theory of gravity containing MOTSs (or some generalization thereof). Possible bifurcations of those structures are constrained in any such theory in the same way.

We present a quantum code implementable on a regular $2$D hex grid with an estimated encoding rate up to $4.5\times$ of that of a rotated surface code patch using circuit-level noise in a one- and two-qubit $10^{-3}$ error uniform depolarizing model. Our approach is based on yoking a dense packing of surface code twist defects, enabled by new stabilizer measurement cycles with an optimal four layers of nearest-neighbor two-qubit gates, almost no distance-reducing hook errors, and efficient decoding. We demonstrate a space-efficient architecture for computing on densely packed logical qubits, including new padding-free lattice surgery protocols in an optimal bounding box of $2d^2$ data and measurement qubits per patch. Assuming a $1μ$s surface code cycle time and a $10μ$s reaction time, these developments enable chemically accurate ground state phase estimation of a broad class of `utility-scale' electronic structure simulation problems such as the $108$ spin-orbital FeMoco-based nitrogen fixation catalyst in under a month with $89$k noisy superconducting qubits. We elucidate a Pareto frontier of space-time trade-offs and find a minimum physical quantum volume of $1.3$ mega-qubit-hours. These correspond to a $36\times$ space and $6.6\times$ spacetime improvement, respectively, over our previous state-of-the-art minimum-Toffoli resource estimates (Phys. Rev. X 15, 041016).

We compute the small quantum cohomology ring of a Verra fourfold. Using the theory of atoms recently developped by Katzarkov--Kontsevich--Pantev--Yu, and building on recent papers of the authors, we deduce that a Verra fourfold is never birational to a very general cubic fourfold, nor to a very general Gushel--Mukai fourfold, whereas it was previously known that a general Verra fourfold is birational to a general nodal Gushel--Mukai fourfold. More precisely, we show that for every smooth cubic fourfold or smooth Gushel--Mukai fourfold that is birational to some Verra fourfold, the primitive cohomology is isomorphic, as a rational Hodge structure, to the middle cohomology of some projective K3 surface.

We study the impact of neutrinos emitted from evaporating Primordial Black Holes (PBHs) on the global 21-cm absorption signal during the dark ages and pre-reionization epochs. PBHs emit neutrinos over a wide energy range through Hawking evaporation. We investigate the possibility that radiative scattering between these neutrinos and the Cosmic Neutrino Background (C$ν$B) generates secondary photons, leading to additional heating of the neutral hydrogen gas. This modifies the thermal history of the intergalactic medium and increases the global 21-cm brightness temperature relative to the standard cosmological prediction. Using the absorption feature at redshift $z\simeq17$, we derive new constraints on the PBH fraction for PBH masses in the range $10^{15}\mathrm{g}\lesssim m_{\rm BH,0}\lesssim10^{25}\mathrm{g}$. We further use existing PBH limits to constrain neutrino self-interaction couplings over a broad range of mediator masses. Our analysis complements previous studies that focused on direct photon injection from PBH evaporation and highlights the importance of neutrino-induced effects within a multimessenger framework for probing PBHs and beyond-standard-model neutrino interactions.

Higher-dimensional black holes have been extensively studied over the years, primarily from heuristic and fundamental perspectives or within the context of holographic applications. However, their interaction with ordinary matter confined to the brane is also of particular interest in cosmology. In this work, we revisit accretion within the Randall-Sundrum type II framework, employing the covariant Shiromizu-Maeda-Sasaki formalism together with the Gauss-Codazzi and energy conservation equations. We analyse information propagation in the cosmological fluid and implement a fully relativistic treatment of accretion following Michel's prescription. We find that braneworld effects play a significant role in the early Universe, strongly impacting the evolution of light primordial black holes (PBHs). In particular, the mapping between initial conditions and present-day PBH populations is substantially modified by an extended phase of early-time accretion that is significantly more efficient than previously found. For certain regions of parameter space, PBHs that could contribute to the present-day dark matter abundance may have formed with masses below the effective four-dimensional Planck scale. The discrepancy between our black hole masses and the most optimistic previous estimates grows as $t^{0.34}$-a significant difference that reaches up to several orders of magnitude by the end of the strong-accretion epoch, particularly for black holes that form early and for small values of the fundamental Planck scale $M_5$, reaching up to $\sim 10^5$ for the smallest $M_5$ permitted by observations.

Given two Blaschke products $A$, $B$ of the same degree, a \emph{welding homeomorphism} of $A$, $B$ is a circle homeomorphism $k: \mathbb{T} \rightarrow \mathbb{T}$ satisfying $A\circ k=B$ on $\mathbb{T}$. We show that any two pairs of Blaschke products sharing a welding homeomorphism must factor through a common pair of Blaschke products, and we give a criterion for detecting whether two Blaschke products admit such a factorization.