The established equivalence between 2-crossed modules and Gray 3-groups [M. Sarikaya and E. Ulualan, 2024] serves as a benchmark for higher-dimensional algebraic models. However, to the best of our knowledge, the established definitions of 3-crossed modules [Z. Arvasi, T. S. Kuzpinari, and E. Ö. Uslu, 2009] are not clearly suited for extending this equivalence. In this paper, we propose an alternative formulation of a 3-crossed module, equipped with a new type of lifting, which is specifically designed to serve as a foundation for this higher-order categorical correspondence. As the primary results of this paper, we validate this new structure. We prove that the simplicial set induced by our 3-crossed module forms a quasi-category. Furthermore, we show that the Moore complex of length 3 associated with a simplicial group naturally admits the structure of our 3-crossed module. This work establishes our definition as a robust candidate for modeling the next level in this algebraic-categorical program.

Designs which are minimax in the presence of model misspecifications have been constructed so as to minimize the maximum, over classes of alternate response models, of the integrated mean squared error of the predicted values. This mean squared error decomposes into a term arising solely from variation, and a bias term arising from the model errors. Here we consider the problem of designing so as to minimize the variance of the predictors, subject to a bound on the maximum (over model misspecifications) bias. We consider as well designing so as to minimize the maximum bias, subject to a bound on the variance. We show that solutions to both problems are given by the minimax designs, with appropriately chosen values of their tuning constants. Conversely, any minimax design solves each problem for an appropriate choice of the bound on the maximum bias or on the variance.

This paper analyzes a service system modeled as a single-server queue, in which the service provider aims to dynamically maximize the expected revenue per unit of time. This is achieved by constructing a stochastic gradient descent algorithm that dynamically adjusts the price. A key feature of our modeling framework is that customers may choose to balk - that is, decide not to join - when facing high congestion. A notable strength of our approach is that the revenue-maximizing algorithm relies solely on information about effective arrivals, meaning that only the behavior of customers who choose not to balk is observable and used in decision-making. This results in an elaborate interplay between the pricing policy and the effective arrival process, yielding a non-standard state dependent queueing process. An important contribution of our work concerns a novel Infinitesimal Perturbation Analysis (IPA) procedure that is able to consistently estimate the stationary effective arrival rate. This is further leveraged to construct an iterative algorithm that converges, under mild regularity conditions, to the optimal price with provable asymptotic guarantees.

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present a deterministic ancilla-based method for implementing unitary and non-unitary trigonometric gates whose arguments are arbitrary Hermitian functions of qumode quadratures. As a concrete application, we develop a hybrid qubit-qumode quantum simulation of the lattice sine-Gordon model. Using these gates, we prepare ground states via quantum imaginary-time evolution, simulate real-time dynamics, compute time-dependent vertex two-point correlation functions, and extract quantum kink profiles under topological boundary conditions. Our results demonstrate that trigonometric continuous-variable gates provide a physically natural framework for simulating interacting field theories on near-term hybrid quantum hardware, while establishing a parallel route to universality beyond polynomial gate constructions. We expect that the trigonometric gates introduced here to find broader applications, including quantum simulations of condensed matter systems, quantum chemistry, and biological models.

As multi-agent systems powered by Large Language Models (LLMs) are increasingly adopted in real-world workflows, users with diverse technical backgrounds are now building and refining their own agentic processes. However, these systems can fail in opaque ways, making it difficult for users to observe, understand, and correct errors. We conducted formative interviews with 12 practitioners to identify mismatches between existing debugging tools and users' needs. Based on these insights, we designed XAgen, an explainability tool that supports users with varying AI expertise through three core capabilities: log visualization for glanceable workflow understanding, human-in-the-loop feedback to capture expert judgment, and automatic error detection via an LLM-as-a-judge. In a user study with 8 participants, XAgen helped users locate failures more easily, attribute to specific agents or steps, and iteratively improve configurations. Our findings surface human-centered design guidelines for explainable agentic AI development and highlight opportunities for more context-aware interactive debugging.

We calculate the leading order amplitude and probability for the elastic scattering of an elementary meson and a kink in the $ϕ^4$ double-well model. Classically, the kink is reflectionless, and so the leading contribution arises at one loop. At this order, the scattering amplitude exhibits a pole when the incoming meson energy is twice the shape mode energy, corresponding to the excitation of an unstable resonance with the twice excited shape mode. We expect that higher order corrections will give this resonance a width equal to the inverse of the known lifetime of this unstable excitation.

Optimal transmission switching (OTS) improves optimal power flow (OPF) by selectively opening transmission lines, but its mixed-integer formulation increases computational complexity, especially on large grids. To address this, we propose a dispatch-aware deep neural network (DA-DNN) that accelerates DC-OTS without relying on pre-solved labels, eliminating costly OTS label generation that becomes impractical at scale. DA-DNN predicts line states and passes them through an embedded differentiable DC-OPF layer, using the resulting generation cost as the loss function so that physical network constraints are enforced throughout training and inference. To stabilize training, we adopt a customized weight and bias initialization that keeps the embedded DC-OPF feasible from the first epoch. To improve inference robustness, we incorporate a binary regularization term that reduces ambiguity in the relaxed line-status outputs prior to thresholding. Once trained, DA-DNN produces a feasible topology and dispatch pair with highly predictable computation time comparable to a single DC-OPF solve, while conventional MIP solvers can become intractable. Moreover, the embedded OPF layer enables DA-DNN to generalize to untrained system configurations, such as changes in line flow limits, and to support post-contingency corrective operation. As a result, the proposed method captures the economic advantages of OTS while maintaining scalability and generalization ability.

Sunspot groups often emerge in spatial-temporal clusters, known as nests or complexes of activity. Quantifying how frequently such nesting occurs is important for understanding the organisation and recurrence of solar magnetic fields. We introduce an automated approach based on kernel density estimation and DBSCAN clustering to identify nests in the longitude-time domain and to measure the fraction of sunspot groups that belong to them. The method combines a smooth representation of emergence patterns with a density-based clustering procedure, validated using synthetic solar-like cycles and corrected for variations in data density. We apply this method to 151 years of sunspot-group observations from the Royal Greenwich Observatory Photoheliographic Results (RGO, 1874-1976) and Kislovodsk Mountain Astronomical Station (KMAS, 1955-2025) catalogues. Across all cycles and latitude bands, the mean nesting degree is $\langle D\rangle = 0.61 \pm 0.12$, implying that about 60 percent all sunspot groups emerge within nests. Nesting is strongest at mid-latitudes (10$^\circ$-20$^\circ$), and results from the two independent datasets agree in the period of overlap. The nesting degree significantly correlates with the solar activity level, with the correlation strengthening when small groups are excluded. The characteristic inter-nest spacing contracts from $\sim$200-500~Mm at low activity to $\sim$60-100~Mm at solar maximum, approaching typical sunspot-group dimensions. The identified nests range from compact clusters to long-lived, drifting structures, offering new quantitative constraints on the persistence and organisation of solar magnetic activity.

Warm and self-interactive dark matter cosmologies have been proposed as nonbaryonic solutions to the tensions between the $Λ$ cold dark matter model and observations at the kiloparsec scale. In this paper, we used the dark matter-only runs of the \textsc{aida-tng} project, a set of cosmological simulations of different sizes and resolutions, to analyze the macroscopic impact of alternative dark matter models on the abundance, radial distribution, and clustering properties of halos. We adopted the halo occupation distribution formalism to characterize the evolution of its parameters $M_1$ and $α$ with the mass and redshift selection of our sample. By dividing the halo population into centrals and satellites, we were able to study their spatial density profile. We found that a Navarro-Frenk-White model is not accurate enough to describe the radial distribution of subhalos and that a generalized Navarro-Frenk-White model is required instead. Warm dark matter models, in particular, present a cuspier distribution of satellites, whereas self-interacting dark matter exhibits a shallower density profile. Moreover, we found that the small-scale clustering of dark matter halos provides a powerful tool for distinguishing among alternative dark matter scenarios, in preparation for a more detailed study that fully incorporates baryonic effects and for a comparison with observational data from galaxy clustering.

We derive error bounds for CUR matrix approximation using determinant-based methods that relate local projection errors to global approximation quality. For general matrices, we establish determinant identities for bordered Gramian matrices that decompose CUR approximation errors into interpretable local components. These identities connect projection errors onto submatrix column spaces directly to determinants, providing geometric insight into approximation degradation. We develop a probabilistic framework based on volume sampling that yields interpolation-type error bounds quantifying the benefits of oversampling: when $r > k$ rows are selected for $k$ columns, the expected error factor transitions linearly from $(k+1)^2$ (no oversampling) to $(k+1)$ (full oversampling). Our analysis establishes that the expected squared error is bounded by this interpolation factor times the squared error of the best rank-$k$ approximation, directly connecting CUR approximation quality to the optimal low-rank approximation. The framework applies to both CUR decomposition for general matrices and the Nyström method for symmetric positive semi-definite matrices, providing a unified theoretical foundation for determinant-based low-rank approximation analysis.

As processor designs grow more complex, verification remains bottlenecked by slow software simulation and low-quality random test stimuli. Recent research has applied software fuzzers to hardware verification, but these rely on semantically blind random mutations that may generate shallow, low-quality stimuli unable to explore complex behaviors. These limitations result in slow coverage convergence and prohibitively high verification costs. In this paper, we present Lyra, a heterogeneous RISC-V verification framework that addresses both challenges by pairing hardware-accelerated verification with an ISA-aware generative model. Lyra executes the DUT and reference model concurrently on an FPGA SoC, enabling high-throughput differential checking and hardware-level coverage collection. Instead of creating verification stimuli randomly or through simple mutations, we train a domain-specialized generative model, LyraGen, with inherent semantic awareness to generate high-quality, semantically rich instruction sequences. Empirical results show Lyra achieves up to $1.27\times$ higher coverage and accelerates end-to-end verification by up to $107\times$ to $3343\times$ compared to state-of-the-art software fuzzers, while consistently demonstrating lower convergence difficulty.

Practical quantum computers need to continuously exchange data between classical and quantum subsystems during a computation. Mid-circuit measurements of a qubits state are transferred to the classical electronics layer, and their outcome can inform feedforward operations that close the loop back to the quantum layer. These operations are crucial for fault-tolerant quantum computers, but the quantum-classical loop must be completed before the qubits decohere, presenting a substantial engineering challenge for full-scale systems comprising millions of qubits. Here we perform the first mid-circuit measurements in a system of silicon spin qubits, and show that feedforward operations can be performed without needing to route information to the classical layer. This in-layer approach leverages a backaction-driven control technique that has previously been considered a source of error. We benchmark our in-layer strategy, together with the standard FPGA-enabled approach, and analyse the performance of both methods using gate set tomography. Our results provide the first step towards moving resource-intensive classical processing into the quantum layer, an advance that could solve key engineering challenges, and drastically reduce the power budget of future quantum computers.

$N$-body simulation serves as a critical method for modeling cosmic evolution and poses a significant challenge in high-performance computing. We present CUBE2, an open-source cosmological $N$-body code emphasizing memory efficiency, computational performance, scalability and precision. The core of its algorithm utilizes multi-level Particle-Mesh (PM) method to solve the Poisson equation for matter distribution, leveraging the well-optimized Fast Fourier Transform (FFT) for computational efficiency. Precision is ensured by the optimized Green's function that seamlessly bridges gravitational interactions between multi-level PM and Particle-Particle (PP) calculations. The program design enhances per-core/node efficiency in processing $N$-body particles, while the Information Optimized Storage (IOS) addresses memory constraints for large particle counts. Using CUBE2, we run two cosmological simulations with particle counts of $6144^3$ on the Advanced Computing East China Sub-center (ACECS) to test performance and accuracy.

Due to entropic effects, it is possible that generic high-energy states of a quantum or classical system are ordered. This leads to spontaneous symmetry breaking at arbitrarily high temperatures. We present minimal models of entropic order that arise from very simple interactions. Our main examples are the Arithmetic Ising Model (AIM) and its quantum analogue, where usual Ising spins are replaced by non-negative integers. Using a large-flavor expansion together with numerical simulations, we find that the high-temperature phase is ordered in the classical and quantum models. We also introduce classical gas models whose interactions drive the system to a crystal at high temperatures.

Axial-vector hadronic molecules $\mathcal{M}_{\mathrm{AV}}=ΥB_{c}^{-} $ and $\widetilde{\mathcal{M}}_{\mathrm{AV}}=η_{b}B_{c}^{\ast -} $ with the quark content $bb \overline{b}\overline{c}$ are studied using QCD sum rule method. The spectroscopic parameters of these molecules are computed in the context of the two-point sum rule method. Predictions for their masses are identical to each other and confirm that they are structures unstable against dissociations to ordinary heavy mesons. We evaluate the width of the state $\mathcal{M}_{\mathrm{AV}}$ and assume that it is equal to that of $\widetilde{\mathcal{M}}_{\mathrm{AV}} $. To this end, we explore its dominant decay channels $\mathcal{M}_{\mathrm{AV}} \to ΥB_{c}^{-} $ and $\mathcal{M}_{\mathrm{AV}} \to η_{b}B_{c}^{\ast -}$. There also are subleading modes of $\mathcal{M}_{\mathrm{AV}}$ generated due to annihilation of $\overline{b}b$ quarks. We consider decays of the molecule $\mathcal{M}_{\mathrm{AV}}$ to pairs of the mesons $B^{\ast -} \overline{D}^{0}$, $\overline{B}^{\ast 0} D^{-}$, $B^{-} \overline{D} ^{\ast 0}$, $\overline{B}^{0} D^{\ast -}$, $\overline{B}_{s}^{\ast 0} D_{s}^{-}$, and $\overline{B}_{s}^{0} D_{s}^{\ast -}$. To find strong couplings at the $\mathcal{M}_{\mathrm{AV}}$-meson-meson vertices which determine the partial widths of these processes, we apply QCD three-point sum rule approach. The mass $m=(15800 \pm 90)~\mathrm{MeV}$ and width $ Γ[\mathcal{M}_{\mathrm{AV}}]=(114 \pm 17)~ \mathrm{MeV}$ of the molecule $\mathcal{M}_{\mathrm{AV}}$ are useful for experimental studies of fully heavy molecular structures at ongoing and planning experiments.

Two-dimensional (2D) materials have been proposed, among many other applications, as a efficient tool for the separation of atomic and molecular species and their corresponding isotopes, given the confinement provided by their subnanometric dimensions. In this work we present three dimensional quantum wave packet calculations revealing an enhancement in the quantum transport in bilayer over monolayer graphdiyne membranes, one of the most popular 2D materials which is commonly employed for this purpose. Besides, resonances emerge superimposed over the typical monolayer profile for transmission probabilities, a feature that is general to other bilayer nanoporous 2D heterostructures and that shows a strong dependence on the interlayer separation.

Boundary-catalytic branching processes describe a broad class of natural phenomena where the population of diffusing particles grows due to their spontaneous binary branching (e.g., division, fission or splitting) on a catalytic boundary located in a complex environment. We investigate the possibility of the geometric control of the population growth by compensating the proliferation of particles due to catalytic branching events by their absorptions in the bulk or on absorbing regions of the boundary. We identify an appropriate Steklov spectral problem to obtain the phase diagram of this out-of-equilibrium stochastic process. The principal eigenvalue determines the critical line that separates an exponential growth of the population from its extinction in a bounded domain. In other words, we establish a powerful tool for calculating the growth-regulating absorption rate that equilibrates the opposite effects of branching and absorption events and thus results in steady-state behavior of this diffusion-reaction system. Moreover, we show the existence of a critical catalytic rate above which no compensation is possible, so that the population cannot be controlled and keeps growing exponentially. The proposed framework opens promising perspectives for better understanding, modeling and control of various boundary-catalytic branching processes, with applications in physics, chemistry, and life sciences.

An exact channel impulse response (CIR) for the three-dimensional point-to-sphere absorbing channel under drift has remained unavailable due to symmetry breaking. This letter closes this gap by deriving an exact analytical CIR for a fully absorbing spherical receiver under uniform drift with arbitrary direction. By formulating the problem in terms of joint first-hitting time-location statistics and applying a Girsanov-based measure change, drift effects are isolated into an explicit multiplicative factor, yielding an exact series representation. The resulting CIR provides a rigorous reference model and enables efficient, noise-free evaluation of key channel metrics without relying on Monte Carlo simulations.

A systematic study of fission barrier heights and static properties of even-even actinide nuclei from Th to Cf has been performed within the Warsaw macroscopic-microscopic model using the five-dimensional Fourier-over-Spheroid (FoS) shape parameterization. The use of a large deformation grid, containing about $1.3\times10^{8}$ points for each nucleus, allows for a refined and numerically complete exploration of the potential energy landscape without dividing the configuration space into subregions or applying interpolation. Barrier heights, extracted via the Immersion Water Flow method, show good agreement with empirical evaluations (including the new IAEA RIPL-4 dataset) with mean deviations below 1 MeV. Special attention is given to the long-debated third, hyperdeformed minimum. For Th isotopes, a shallow but distinct third well appears, whereas it's absent in heavier actinides (U, Pu).

This paper investigates the (fractional) heat equation with a nonlocal nonlinearity involving a Riesz potential: \begin{equation*} u_{t}+(-Δ)^{\fracβ{2}} u= I_α(|u|^{p}),\qquad x\in \mathbb{R}^n,\,\,\,t>0, \end{equation*} where $α\in(0,n)$, $β\in(0,2]$, $n\geq1$, $p>1.$ We introduce the Fujita-type critical exponent $p_{\mathrm{Fuj}}(n,β,α)=1+(β+α)/(n-α)$, which characterizes the global behavior of solutions: global existence for small initial data when $p>p_{\mathrm{Fuj}}(n,β,α),$ and finite-time blow-up when $p\leq p_{\mathrm{Fuj}}(n,β,α)$. It is remarkable that the critical Fujita exponent is not determined by the usual scaling argument that yields $p_{sc}=1+(β+α)/n$, but instead arises in an unconventional manner, similar to the results of Cazenave et al. [Nonlinear Analysis, 68 (2008), 862-874] for the heat equation with a nonlocal nonlinearity of the form $\int_0^t(t-s)^{-γ}|u(s)|^{p-1}u(s)ds,\,0\leq γ<1.$ The result on global existence for $p>p_{\mathrm{Fuj}}(n,2,α),$ provides a positive answer to the hypothesis proposed by Mitidieri and Pohozaev in [Proc. Steklov Inst. Math., 248 (2005) 164-185]. We further establish global nonexistence results for the above heat equation, where the Riesz potential term $I_α(|u|^{p})$ is replaced by a more general convolution operator $(\mathcal{K}\ast |u|^p),\,\mathcal{K}\in L^1_{loc}$, thereby extending the Mitidieri-Pohozaev's results established in the aforementioned work. Proofs of the blow-up results are obtained using a nonlinear capacity method specifically adapted to the structure of the problem, while global existence is established via a fixed-point argument combined with the Hardy-Littlewood-Sobolev inequality.

We present 4,110 strong gravitational lens candidates, 3,887 of which are new discoveries, selected from a sample of 5,837,154 luminous red galaxies (LRGs) observed with the Dark Energy Spectroscopic Instrument (DESI). Candidates are identified via the presence of background ionized oxygen [O II] nebular emission lines in the foreground LRG spectra which may originate from the lensing of higher redshift star-forming galaxies. Using the measured foreground redshift, background redshift, and integrated flux of the background [O II] doublet, we integrate over impact parameters to compute the probability that each candidate is a lens. We expect 53% of candidates to be true lenses with Einstein radii ranging from 0.1'' to 4'', which can be confirmed with high-resolution imaging. Confirmed strong lenses from this sample will form a valuable cosmological dataset, as strong gravitational lensing is the only method to directly measure dark matter halo substructure at cosmological distances. We independently recover the host of the multiply imaged gravitationally lensed type Ia supernova iPTF16geu. Monitoring these lenses for future multiply lensed transients will enable (a) H0 measurements via time-delay cosmography and (b) substructure measurements via flux ratios.

VOXES is a Von Hamos X-ray spectrometer developed at the INFN National Laboratories of Frascati for high-resolution laboratory X-ray spectroscopy in the 5--20~keV range. It uses curved mosaic crystals and motorized positioning stages to perform wavelength-dispersive X-ray fluorescence (WD-XRF) with sub-10~eV tunable resolution for extended and dilute samples. Recent developments include the integration of an energy-dispersive X-ray fluorescence (ED-XRF) line based on a silicon pin-diode detector, which enables flux monitoring and simultaneous ED and WD measurements. In addition, a dedicated liquid-sample holder has been introduced, and a Y-shaped support geometry, crucial for switching to a transmission layout, provides mechanical compatibility with laboratory XAS, now under implementation. These upgrades expand the versatility and automation of VOXES, strengthening its role as a table-top platform for laboratory X-ray spectroscopy.

The influence of kinematic constraints and event selection on the emergence of the alignment phenomenon observed in cosmic-ray experiments is studied within the HYDJET++ model. It is demonstrated that the high degree of alignment, previously identified for realistic values of the transverse momentum disbalance of the most energetic particles, is also observed at the level of the most energetic clusters. In high-multiplicity events, the clustering procedure plays a crucial role in resolving individual particle groups on the detection plane, allowing a more accurate characterization of alignment patterns. These results highlight the combined effects of cluster formation and momentum conservation in shaping the observed azimuthal correlations.

Much recent work on distributed quantum computing have focused on the use of entangled pairs and distributed two qubit gates. But there has also been work on efficient schemes for achieving multipartite entanglement between nodes in a single shot, removing the need to generate multipartite entangled states using many entangled pairs. This paper looks at how multipartite entanglement resources (e.g., GHZ states) can be useful for distributed fan-out operations; we also consider the use of qudits of dimension four for distributed quantum circuit compression. In particular, we consider how such fan-out operations and qudits can be used to implement circuits which are challenging for distributed quantum computation, involving pairwise qubit interactions, i.e., what has been called global gates (a.k.a. global Mølmer-Sørensen gates). Such gates have been explored to possibly yield more efficient computations via reduced circuit depth, and can be carried out efficiently in some types of quantum hardware (e.g., trapped-ion quantum computers); we consider this as an exploration of an ``extreme'' case for distribution given the global qubit-qubit interactions. We also conclude with some implications for future work on quantum circuit compilation and quantum data centre design.

We discuss graviton dark radiation produced by the decay of a secluded scalar field that couples to the Standard Model (SM) only through gravity. Such scalar fields are long-lived, and their decay channels generically include gravitons. If such particles existed and dominated the early universe, a sizable branching ratio into gravitons would yield non-negligible dark radiation that significantly alters the subsequent thermal history of the universe. In this work, we focus on the dark glueball as a representative secluded hidden scalar and compare the decay rates into SM particles via a non-minimal coupling to gravity with those into gravitons, paying attention to how the breaking of conformal invariance affects the amount of graviton dark radiation. We find that decays into the SM are dominated by two-body decay channels into Higgs bosons and gluons. In particular, when the Higgs field has a large non-minimal coupling to gravity, the production of graviton dark radiation is naturally suppressed in the metric formalism, and the SM sector is preferentially reheated and energy transfer to other hidden sectors is suppressed. Finally, we present the expected gravitational-wave spectrum resulting from dark glueball domination.

The behavior of dimensionless quantities defined as ratios of partition functions is analyzed to investigate phase transitions and critical phenomena. At criticality, the universal values of these ratios can be predicted from conformal field theory (CFT) through the modular-invariant partition functions on a torus. We perform numerical calculations using the bond-weighted tensor renormalization group for three two-dimensional models belonging to different universality classes: the Ising model, the three-state Potts model, and the four-state Potts model. The partition-function ratios obey the same finite-size scaling form as the Binder parameter, and their critical values agree well with the universal values predicted by CFT. In the four-state Potts model, we observe logarithmic corrections in the system-size dependence of these ratios.

We present an experimental method to fabricate centimetric thin elastic capsules with highly uniform thickness and negligible bending stiffness using silicone elastomers. In our experiments, the capsules thickness is tunable at fabrication, while internal pressure and hoop (circumferential) stress are adjustable via hydrostatic inflation once the capsules are filled and immersed in water. Capsules mechanics are probed through hydro-elastic waves generated by weak mechanical perturbations at the capsule interface. By analyzing the surface wave dynamics in the Fourier domain, we extract the in-plane stress and demonstrate that the hydro-elastic waves are exclusively governed by hoop stress. This \reponse{provides a controllable macroscopic analogue of liquid drops} characterised by an effective surface tension, allowing the capsules to be modeled as large-scale ``elasto-drops'' with an inflation and thickness tunable effective surface tension. \reponse{In this limit, bending stiffness is negligible over the experimentally relevant wavelengths, so that the shell dynamics are governed primarily by in-plane tension.} Our work demonstrates that elasto-drops serve as a robust model system for parametric studies of large-scale \reponse{analogues of} liquid drops with experimentally adjustable surface tension.

Auto-differentiation is a powerful tool for computing derivatives of simulation results with respect to given parameters. In this letter, we have applied this tool to investigate the instability of a dynamics system that is governed by 21 ordinary differential equations. This second-order instability (named envelope instability) is driven by space-charge effects and has significant impact on the operational regimes of particle accelerators. Our study delves into the three-dimensional envelope instability, incorporating both transverse and longitudinal coupling. Conventionally, analyzing this complex system would necessitate solving 441 ordinary differential equations, which is computationally intractable. However, by employing auto-differentiation, we were able to track only 21 equations. This approach allowed us to uncover an additional instability stopband, which arises from space-charge-induced coupling and has not been reported in previous studies. This research highlights the significant advantages of auto-differentiation in analyzing complicated dynamical systems involving a large number of ordinary differential equations.

We couple projective limits of probability measures to direct limits of their symmetry groups. We show that the direct limit group is the group of symmetries of the projective limit probability measure. If projective systems of probability measures represent point processes in increasingly larger finite regions of the same infinite space, then we show that under some additional niceness and consistency assumptions, an extension of the direct limit group is the symmetry group of the projective limit point process in the whole infinite space. The application of these results to random graph limits provides ``shortest paths'' to graphons and graphexes as it recovers these random graph limits as trivial corollaries. Another application example encompasses a broad class of limits of random graphs with bounded average degrees. This class includes a representative collection of paradigmatic random graph models that have attracted significant research attention in diverse areas of science. Our approach thus provides a general unified framework to study limits of very different types of random graphs.

We extend the complete census of orientable cusped hyperbolic $3$-manifolds to $10$ tetrahedra, giving the next $150730$ manifolds and their $496638$ minimal ideal triangulations. As applications, we find the precisely $439898$ exceptional Dehn fillings on them, revealing the next $1849$ simplest hyperbolic knot exteriors in $S^3$. We also give the simplest example of an orientable cusped hyperbolic $3$-manifold containing a closed totally geodesic surface.