Low-altitude drones can serve as dynamic nodes apparently mitigating terrain-induced impacts for quantum networks. However, it is extremely hard to establish a sable quantum link in a drone-based dynamic platform, which requires centimeter-level positioning techniques and high-precision time synchronization technologies. In this paper, we develop a single-ended polarization adaptive correction technology at both the transmitting and receiving ends. Based on this, we present the world's first kilometer-scale drone-based QKD network, achieving an 1.2 km free-space QKD link with a secure key rate of 2.76 kbps, suitable for urban quantum network deployment. We validate the feasibility of QKD between dynamic drone and ground unmanned vehicle at a relative speed of 1 m/s over a distance of 100 m, attaining a secure key rate of 70.94 kbps. This work advances drone-based QKD from static demonstrations to practical dynamic network, boasting great development potential for an airborne quantum internet.

Interfacing materials with electromagnetic cavities offers a route to modify equilibrium properties through structured vacuum fluctuations. The coupling of light with correlated electrons lacks a characteristic energy scale, making vacuum induced modifications of such systems inherently off-resonant and sensitive to the full photon mode structure. Here, we present a non-perturbative calculation of the cavity induced modification of the magnetic exchange interaction $J$ of the half-filled Hubbard model, including all cavity modes and with parameters determined from first principles. We show that the strength of the modification is controlled by a generalized Purcell factor, proportional to the frequency integrated photonic density of states. This result identifies polaritonic surface cavities as promising platforms to modify correlated systems, while standard Fabry-Pérot resonators produce negligible effects due to spectral weight cancellations upon integration. To perform the calculation, we develop a consistent quantization scheme for materials coupled to a dielectric substrate, in the Coulomb gauge, which reveals a competition between static Coulomb screening and dynamical effects arising from the vector potential. Including both effects is essential to obtain even qualitatively correct predictions. For a gold substrate the light-matter interactions lead to a net enhancement of $J$, whose magnitude is large enough to be observable in two-magnon Raman spectroscopy. Our framework establishes a concrete design principle linking cavity geometry to material response in the off-resonant regime, which will guide future experimental and theoretical explorations.

Based on the work of Dundas, Lindenstrauss and Richter we compute the topological André-Quillen homology with reduced coefficients for Eilenberg-MacLane spectra such as $H\mathbb{Z}$ and $H\mathbb{Z}/p^n$. The case of $H\mathbb{F}_p$ was settled in an unpublished work of Basterra and Mandell, which was refined later by Brantner and Mathew in the context of spectral partition Lie algebras. Our approach is similar to Cartan's calculation of the Steenrod algebra, and eventually shorter. We also present some computations relative to the $H\mathbb{Z}$ base.

Self-generated magnetic fields are commonly produced in high-power laser-plasma interactions. These fields can inhibit plasma heat-flow which makes them important in inertial fusion and controlled laboratory astrophysics experiments. In this work, we characterize the time evolution of self-generated magnetic fields using multi-view proton tomography at two timings. Tomographic reconstructions of the magnetic field show a clear transition from fields located close to the target at early time to more extended coronal fields at later time. The tomographic inversion and mesh radiography also enable a direct measurement of the magnetic-flux evolution. Comparisons with extended-MHD simulations show only moderate agreement in field structure, but good agreement in magnetic flux. This suggests that the field generation model is largely correct under these conditions, while the magnetic transport model requires additional development to reproduce the observed field structure.

Sensitivity analysis for unmeasured confounding in observational studies is commonly based on threshold quantities, such as the Cornfield condition or the E-value, which quantify how strong a confounder must be to explain away an observed association. However, these approaches do not address a fundamental inferential question: how plausible is it that such a confounder exists? In this work, we propose a Bayesian reformulation of Cornfield-type sensitivity analysis in which the strength of unmeasured confounding is treated as a random variable. Within this framework, the E-value is reinterpreted as a threshold, and the central inferential quantity becomes the posterior probability that confounding exceeds this threshold. This transforms sensitivity analysis from a descriptive diagnostic into a probabilistic assessment of robustness. We develop a simple generative model linking observed effect estimates to true causal effects and confounding bias, and we specify prior distributions reflecting plausible confounding mechanisms. The resulting framework yields posterior measures of evidential vulnerability that are directly interpretable and applicable to summary-level data. Illustrations based on empirical case studies show that the proposed approach preserves the interpretability of the E-value while providing a more nuanced and decision-relevant characterization of robustness. More broadly, the framework aligns sensitivity analysis with Bayesian principles of inference under uncertainty, offering a coherent alternative to purely threshold-based reasoning.

We present a statistical analysis for the interaction-induced central concentration of HI gas distributions and its connection with interaction-induced central star formation enhancement, using a large sample of $\sim 10^4$ galaxies from the ALFALFA and SDSS surveys. By adopting the HI profile parameter $K$, an indicator of gas concentration inferred from the integrated 21 cm emission line, we find that galaxies with more centrally concentrated HI (higher $K$ values) or enhanced specific star foramtion rate (sSFR) exhibit significantly stronger clustering and higher probability of hosting a nearby neighbor on scales below $100h^{-1}\mathrm{kpc}$, which is more pronounced in low-mass galaxies. Furthermore, by utilizing the enhancement functions for a sample of galaxy pairs, we directly trace the evolution of HI concentration and sSFR enhancement as a function of projected separation. Our findings indicate that tidal interactions drive a statistical synchrony between the central concentration of atomic gas and the enhancement of central star formation. Gas concentration appears to be a necessary condition for central star formation enhancement in interacting systems at all but the smallest separations. Compared to satellite galaxies, central galaxies exhibit stronger enhancement of gas fraction, gas concentration and sSFR, suggesting the role of environmental regulation.

A German ministry recently proposed a limit of at most one price increase per day for petrol stations. At what time should the price reset be allowed in order to lower price levels the most throughout the day? To answer this question, I infer the share of price-sensitive consumers for every hour of the day from German petrol station price data, based on a simple spatial-competition model. I focus on weekdays, which are the relevant target because commuter demand is less flexible than weekend demand. Hourly petrol station prices peak at 07:00 and bottom out at 19:00. Given the inferred composition of price-sensitivity throughout the day and hourly passenger-car traffic frequencies as a proxy for quantity, I evaluate every possible reset-hour of the new policy. The lowest traffic-weighted average price is achieved by an 11:00 reset. With this reset-hour, the resulting equilibrium price throughout the day is constant. This would lead to lower prices in the morning but higher prices in the evening, harming price-sensitive consumers but benefiting morning commuters and firms.

Aerodynamic drag reduction on highways through vehicle platooning is a well-known concept, but it has not yet seen systematic uptake, arguably because of significant technological and legislative obstacles. As a low-tech entry point to real multi-vehicle platooning, "Windbreaking-as-a-Service" (WaaS) was introduced recently. Here we use a QUBO formulation to study classical metaheuristics such as simulated annealing and tabu search, together with emerging quantum heuristics including quantum annealing and variants of the Quantum Approximate Optimization Algorithm (QAOA). These heuristic solvers do not guarantee optimality, but they traverse the same higher-order landscape using polynomial memory. They can also be parallelized aggressively, and efficient classical post-processing can be used in hybrid workflows to return only valid schedules. This paper therefore positions QUBO as a common language that allows heterogeneous classical, quantum, and hybrid solvers to address the optimization of highway platooning.

Colloidal fluids can exhibit complex phase behavior and determining phase diagrams via experiments or computer simulations can be laborious. We demonstrate that the dispersion relation $ω(k)$, obtained from dynamical density functional theory for the uniform density system, is a highly versatile tool for {\it predicting} where in the phase diagram complex crystals form. The sign of $ω(k)$ determines whether density modes with wavenumber $k$ grow or decay over time. We demonstrate the predictive power by investigating the complex phase behavior of particles interacting via core-shoulder pair potentials. With complementary Monte Carlo simulations, we show that regions of the phase diagram where $ω(k)$ has one or several unstable (growing) wavenumbers are also where crystalline phases occur. Going further, by tuning these unstable wavenumbers via the interaction-potential and state-point parameters, we design systems with quasicrystals in the phase diagram. We identify a system with a certain shoulder-range exhibiting at least 10 different phases. Our general approach accelerates considerably the mapping of complex phase diagrams, crucial for the design of new materials.

We investigate the direct $CP$ violation in the decay $D^\pm \to π^\pm π^+ π^-$ incorporating the $a_0^0(980)$-$f_0(980)$ mixing mechanism. The integrated mixing intensities $\overline ξ_{fa}$ and $\overline ξ_{af}$ are calculated using meson masses and coupling constants extracted from various theoretical models and experimental data, yielding values of appreciable magnitude. We find that when the invariant mass of the $π^+π^-$pair lies near the $f_0(980)$ resonance, this isospin breaking mechanism can enhance the $CP$ asymmetry. The enhancement is particularly pronounced when $f_0(980)$ carries a significant $n\bar{n}$ quark component and the $f_0(980)$ and $σ(600)$ mixing angle is approximately $26^\circ$. It is emphasized that the $a_0^0(980)$-$f_0(980)$ mixing mechanism can be taken into account in both theoretical and experimental studies of $CP$ violation in $B$ or $D$ meson decays.

Oscillatory sheared suspensions, when observed stroboscopically, exhibit a reversible-irreversible transition as a function of the strain amplitude, which is a kind of absorbing phase transition. So far studies of this transition focused on global quantities, e.g. quantifying the irreversibility on one side of the transition or the time to reach a reversible state on the other side. Here, motivated by the kin depinning transition, we focus on the intermittent dynamics near the transition. We perform simulations of a modified Random Organization Model (ROM), a minimal particle model which we recently adapted to take into account the generic presence of long-range interactions mediated by the fluid, taking the power-law-decay exponent $α$ as an additional control parameter of the model. We show that at the absorbing phase transition, this model displays power-law-distributed avalanches. We characterize the avalanche statistics in terms of avalanche size, duration and number of particles involved, and we determine the associated exponents. By varying the exponent $α$, the fractal dimension of avalanches crosses space dimension $d$, inducing a qualitative change of the spatial structure of avalanches, from compact avalanches when interactions have a short range, to sparse avalanches when interactions are long-ranged. Finally, we characterize the clusters within the avalanches, which we also find power-law distributed.

The quantum anomalous Hall effect has been observed in several magnetically doped topological insulators, where its robustness and macroscopic magnetization properties have been taken to suggest the presence of long-range ferromagnetic order. However, experiments in such systems have found evidence for both long- and short-range order, leaving the precise nature of the magnetism in these systems unclear. Here, we use scanning superconducting quantum interference device microscopy to study magnetic domains in V-doped (Bi,Sb)$_2$Te$_3$ exhibiting a quantum anomalous Hall effect with precise quantization. By imaging stray magnetic fields as a function of applied field, we map the formation and evolution of domains through magnetic reversal. We reconstruct the magnetization configuration underlying the measured stray field and find that magnetic domains and crystallographic grains are of similar size. Moreover, magnetic reversal is found to occur through domain expansion, typical of ferromagnets, rather than through nucleation at random sites. Our measurements thus reveal a coexistence of both local magnetic interactions within crystallographic grains and long-range ferromagnetic coupling between grains. This behavior in V-doped (Bi,Sb)$_2$Te$_3$ is markedly distinct from that previously reported for Cr-doped (Bi,Sb)$_2$Te$_3$.

Accurate numerical simulation of fault and fracture mechanics is critical for the performance and safety assessment of many subsurface systems. The discretized representation of discontinuity surfaces and the robust simulation of their frictional contact behavior still represent major challenges. In this work, we use the mortar method to enforce the contact constraints and allow for non-conformity around the discontinuity surface, with a set of Lagrange multipliers playing the role of interface tractions. The formulation combines piecewise linear displacements with piecewise constant multipliers defined on one side of the fault interface (the non-mortar side). This choice for the Lagrange multipliers has a number of advantages from practical and computational viewpoints, but violates the inf-sup stability constraint. In order to stabilize the proposed formulation, we develop a traction-jump stabilization term to be added to the constraint equations. We use a macro-element analysis to derive an algorithmic strategy that automatically evaluates the proper scaling of the stabilization, without requiring any additional user-selected parameter. Numerical experiments demonstrate that the proposed formulation not only restores the inf-sup stability condition, but also recovers stable traction profiles in the presence of finer non-mortar sides, where other inf-sup-stable formulations fail. The proposed method is finally used to simulate non-linear contact conditions in non-conforming corner-point grids typically used in industrial geological applications.

This article reports the measurement of the transverse-momentum ($p_{\rm T}$) differential production cross section of B$^0$ mesons in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=13.6$ TeV with the ALICE detector at the CERN LHC. For the first time, the B$^0$ production cross section is measured at midrapidity ($|y|<0.5$) down to $p_{\rm T}=1~\mathrm{GeV}/c$ at LHC energies. The B$^0$ mesons and their charge conjugates were reconstructed via the B$^{0}\to$D$^{-}π^+$ decay channel, followed by the D$^-\to$K$^+π^-π^-$ decay. The measured $p_{\rm T}$-differential production cross section is described within uncertainties by state-of-the-art models based on perturbative quantum-chromodynamics calculations. Its rapidity dependence is also studied by computing the $p_{\rm T}$-differential ratios between the ALICE measurement and the one of B$^+$ mesons performed by the LHCb Collaboration at forward rapidity. The B$^0$ production cross section per unit of rapidity at midrapidity is ${\rm d}σ({\rm B^0})/{\rm d} y|_{|y|<0.5} = 24.2 \pm 1.4~(\text{stat.}) \pm 2.6~(\text{syst.})_{-0.3}^{+0.2}~(\text{extrap.})~μ{\rm b}$.

In this paper, we develop a Markov decision process (MDP) formulation for the low--temperature metastable Ising model evolving according to Kawasaki dynamics in a finite box of the two--dimensional square lattice. We analyze how an external controller can guide the system to the all--occupied state by appropriately adding and moving particles at specified moments in time. To this end, we construct a reduced MDP on a constrained family of configurations having a single cluster, a regime where particle attachment is more likely than detachment. We investigate two reward structures: one that depends solely on the time to reach the target configuration, and another that incorporates action--dependent energy costs. Within this MDP framework, we characterize the exact optimal policies under both reward structures, which turn out to have a different behavior: while a purely efficiency--based criterion promotes the growth from the boundary centers of the cluster, an energy--based reward function favours the growth at the corners of the cluster.

A two-color laser-induced fluorescence (2C-LIF) technique is presented for investigating droplet impact on thin liquid films, enabling simultaneous, spatially and temporally resolved measurements of film thickness and scalar concentration. The method is applied to water droplets impacting thin liquid films over a range of Reynolds numbers, Weber numbers and dimensionless film thicknesses, providing direct access to early-time mixing processes during impact. To quantify scalar transport within the liquid film, the reconstructed concentration fields are evaluated using a coefficient-of-variaton (CV) approach, providing a quantitative measure of mixture homogeneity. This enables identification of the transition from inertia-dominated convective transport to diffusion-controlled mixing. Based on this analysis, an empirical correlation describing the evolution of CV as a function of Reynolds number and film thickness is formulated. Finally, the applicability of the 2C-LIF method is demonstrated for binary ethanol-water films, where additional transport mechanisms influence and modify the mixing dynamics.

Polycyclic aromatic hydrocarbons (PAHs) are fundamental to understanding the interstellar medium (ISM) of several astrophysical objects. Normally present in Starburst (SB) galaxies, they have also been more frequently detected in active galaxy nuclei (AGNs), suggesting an inner dusty torus that can shield the radiation from the central black role. In this work, we analyze the 6.2 $μ$m PAH band of SB-, AGN- and mixed-dominated spectra from 175 IDEOS database galaxies. After fitting of the band, the sources were distributed into the Peeters' A, B and C classes according to their profile peak positions. Class A objects are predominant in 80% of the entire sample, which could indicate the presence of PAHs with nitrogen incorporation. The water ice absorption at 6.0 $μ$m was also studied in eleven objects, and it affected the PAH band poorly. A prominent second spectral feature after 6.3 $μ$m is present in ten galaxies. Fitting both PAH profiles at 6.2 $μ$m changes all the fit results: the first profile is consistently blue-shifted and classified as class A due to the presence of the second component. Further studies are needed to better comprehend these PAH trends in galactic environments.

In this paper we study the following three-dimensional parabolic-parabolic chemo-repulsion model with potential production, logistic reaction and bilinear control, defined in $Q=(0,T)\timesΩ$: \begin{equation*}\label{eq0} \left\{ \begin{array}{rcl} \partial_tu-Δu&=&\nabla\cdot(u\nabla v)+r\,u-μ\, u^p,\\ \partial_tv-Δv+v&=&u^p+f\,v\, 1_{Ω_c}, \end{array} \right. \end{equation*} where $1< p<+\infty$, $r,μ\geq 0$, and $f=f(t,x)$ is the control function acting on a subdomain $(0,T)\times Ω_c $, with $Ω_c\subseteqΩ$. This system is endowed with initial and non-flux boundary conditions. We prove the existence of global weak solutions of this controlled problem when $f\in L^{5/2}(0,T;L^{5/2}(Ω_c))$, analyzing the role of the diffusion and the logistic terms to get energy estimates. In particular, the logistic competition term $μ\, u^p$ is necessary only for $p>5/3$. Secondly, if $f\in L^{5/2}(0,T;L^{5/2+}(Ω_c))$, any weak solution $(u,v)$ satisfying the regularity criterion $u\in L^{5p/2}(Q)\cap L^{10/3}(Q)$ is in fact more regular, arriving in particular to $u,\nabla v\in L^5(Q)$ for $p\le 2$ and $u,\nabla v\in L^{5(p-1)}(Q)$ for $p> 2$ which is the critical regularity to solve a related optimal bilinear control problem. In fact, this setting let us to prove the existence of global optimal solutions, and the differentiability of the control-to-state mapping via the Implicit Function Theorem in Banach spaces. Then, we can identify the gradient of the (reduced) cost with respect to the control solving the adjoint problem by duality. In particular, we derive first-order necessary optimality conditions for local optimal solutions.

Large Language Models (LLMs) have been progressively exhibiting there capabilities in various areas of research. The performance of the LLMs in acute maternal healthcare area, predominantly in low resource languages like Telugu, Hindi, Tamil, Urdu etc are still unstudied. This study presents how ChatGPT-4o, GeminiAI, and Perplexity AI respond to pregnancy related questions asked in different languages. A bilingual dataset is used to obtain results by applying the semantic similarity metrics (BERT Score) and expert assessments from expertise gynecologists. Multiple parameters like accuracy, fluency, relevance, coherence and completeness are taken into consideration by the gynecologists to rate the responses generated by the LLMs. Gemini excels in other LLMs in terms of producing accurate and coherent pregnancy relevant responses in Telugu, while Perplexity demonstrated well when the prompts were in Telugu. ChatGPT's performance can be improved. The results states that both selecting an LLM and prompting language plays a crucial role in retrieving the information. Altogether, we emphasize for the improvement of LLMs assistance in regional languages for healthcare purposes.

In this paper, we introduce and study the $S$-versions of several fundamental elements in commutative rings. Specifically, for a commutative ring $R$ with identity and a multiplicative subset $S$, we define and investigate the notions of $S$-invertible, $S$-idempotent, $S$-von Neumann regular, and $S$-$π$-regular elements. We establish their basic properties, interrelations, and structural inclusions, and use them to characterize classes of rings. Special attention is given to the uniform $S$-counterparts of Boolean and $π$-regular rings, where we provide examples distinguishing these from their classical analogues. Several transfer results under homomorphisms and direct product constructions are established, and connections with existing $S$-counterparts (uniformly $S$-von Neumann regular, uniformly $S$-Artinian, etc.) are highlighted. Throughout the paper, we point out several open problems, offering directions for further research.

In this work we introduce a new optimal control algorithm for the Keller-Segel chemo-attraction system, where both boundary and distributed controls are considered and both are associated with introducing/removing the amount of chemical substances in the system. The key idea of our approach is to design the optimal control algorithm after discretizing the state problem system, which is done using an upwind finite volume scheme in space and a semi-implicit finite difference in time. Then, the discrete optimal control is approximated identifying the gradient of the reduced discrete cost via the discrete adjoint scheme. Finally, to minimize the reduced cost functional, we use a gradient descent type method (Adam scheme). Moreover, several numerical results are presented to illustrate the efficiency of the proposed approach.

Using an expansion beyond the eikonal regime, we derive relatively compact and accurate analytic expressions for the gravitational quasinormal modes of an asymptotically flat black hole supported by a Dehnen-type dark-matter halo. The spacetime admits a simple analytic metric describing a supermassive black hole embedded in a galactic environment, with the lapse function $f(r)=1-\frac{2 M r^{2}}{(r+a)^{3}}.$ The parameter $a$ sets the characteristic scale of the surrounding halo and controls the regularization of the central region. The axial gravitational sector splits into two distinct channels, referred to as the "up" and "down" perturbations, which are not isospectral.

Ultrawide-bandgap rutile GeO2 is emerging as a promising semiconductor for power electronics, where efficient heat dissipation is essential to suppress self-heating and ensure device reliability. However, the temperature dependence and microscopic origin of its anisotropic heat transport have remained experimentally unresolved. Here, temperature-dependent time-domain thermoreflectance measurements combined with first-principles phonon transport calculations are used to quantify the thermal conductivity of single-crystal rutile GeO2 from 80 to 350 K along [001] and [110]. At 295 K, the thermal conductivity reaches 47.5 W m^-1 K^-1 along [001] and 32.5 W m^-1 K^-1 along [110], corresponding to an anisotropy ratio of 1.46, in good agreement with theory. Rather than following a simple T^(-1) law, the thermal conductivity exhibits an approximate T^(-1.4) dependence, indicating additional scattering beyond purely three-phonon-limited transport. Mode-resolved analysis reveals that the room-temperature anisotropy originates from the combined effect of larger phonon group velocities along [001] and direction-dependent phonon lifetimes. Upon cooling, depopulation of high-frequency phonons progressively suppresses their contribution to heat transport and reduces the anisotropy. The temperature-dependent thermal boundary conductance of Al/rutile GeO2 interfaces is further resolved, and the scaled conductance indicates predominantly elastic interfacial transport. These findings establish the microscopic basis of bulk and interfacial heat transport in rutile GeO2 and position this material as a promising thermally robust platform for ultrawide-bandgap electronics.

Rayleigh-Bénard convection under an imposed inductionless magnetic field is analysed statistically from the perspective of single-point and multi-scale energy budgets. The data is obtained from direct numerical simulations with a Rayleigh number of $10^6$, a Prandtl number of $1$ and Hartmann numbers of $0$, $20$, $40$ and $80$. Wall-parallel and wall-normal magnetic fields are considered as two separate cases. The initial analysis focuses qualitatively on the influence of the magnetic field upon the coherent structures. A central contribution of this work is the interpretation of these structural modifications through magnetohydrodynamically modified turbulent kinetic energy budgets. For example, in the wall-normal case, the thinning of the thermal plumes can be attributed to the damping of the pressure-diffusion mechanisms due to the Lorentz dissipation. In the wall-parallel configuration, Joule dissipation induces a pressure-strain redistribution mechanism that preferentially transfers kinetic energy from the wall-normal velocity component to the field-perpendicular, wall-parallel velocity component but less so to the field-parallel velocity component. This description is then extended to scale-space by considering budgets relating second- and third-order structure functions. Here, the anisotropy is accounted for by analysing directional structure functions. Despite the anisotropy, the Lorentz force appears as an isotropic sink damping intermediate and large scales of motion. The result of this is a lack of transfer between scales of motion and hence a flow with suppressed small-scale turbulence. These results establish a link between qualitative observations and long-term energy balances, providing new insight into magnetoconvective turbulence and informing future modelling and theoretical approaches to such flows.

We investigate turbulent spin-down dynamics in self-gravitating Bose-Einstein condensates, comparing purely bosonic and axionic (higher-order interacting) systems. Through simulations of the Gross-Pitaevskii-Poisson system, we study condensates pinned to a crust potential undergoing rapid rotation slowdown. We find that axionic condensates exhibit more uniform density profiles and smaller sizes compared to their bosonic counterparts for similar interaction strengths, which facilitates earlier vortex entry. The sudden spin-down triggers vortex depinning and a turbulent cascade. For comparable sizes, both systems exhibit a short-lived Kolmogorov energy cascade ($k^{-5/3}$ scaling) followed by a transition to Vinen turbulence ($k^{-1}$ scaling). Crucially, their responses diverge with increasing interaction strength (and thus condensate size): the axionic system increasingly deviates from Kolmogorov scaling because of enhanced vortex retention, a trend quantitatively confirmed by analyzing the vortex fraction and its dependence on the final rotation frequency. Spectral analysis reveals that the growth of incompressible energy is primarily driven by quantum pressure during vortex detachment, rather than by compressible flows. The compressible spectrum shows thermalization ($k$ scaling). Our results demonstrate how distinct nonlinearities govern vortex dynamics and turbulent dissipation in self-gravitating quantum fluids.

Although chemical bonding is the fundamental mechanistic bridge connecting atomic structure to macroscopic material properties, current data-driven materials science largely treats it as an implicit "black box". Existing machine learning (ML) models rely predominantly on geometric coordinates, forcing them to implicitly relearn complex quantum mechanics from scratch. This lack of intermediate physical features limits model interpretability and generalizability, particularly when training data is scarce. To solve this problem, we introduce MattKeyBond, a bond-centric materials database that explicitly maps the local electronic landscape and bonding interactions of materials. Building on this, we propose Bonding Attractivity (BA), a novel element-specific descriptor that quantifies the intrinsic capability of atoms to form covalent networks. By providing pre-calculated, energy-dimensional bonding descriptors, MattKeyBond transforms the implicit "black box" into physically interpretable features. This strategy relieves ML models from the burden of deducing physical laws from pure geometry, enabling accurate predictions even with limited data and seamlessly integrating electronic structure theory into modern AI workflows.

The color-octet (CO) mechanism is a cornerstone of non-relativistic QCD, yet its long-distance matrix elements remain limited, preventing stringent tests of the theory. We demonstrate that the Artru-Collins asymmetry in hadronic decays of the $P$-wave bottomonium state $χ_{b2}$ provides a direct probe of CO dynamics. The asymmetry arises exclusively from the CO decay channel, whereas the color-singlet (CS) contribution affects only the unpolarized rate, so that a nonzero signal constitutes unambiguous evidence of the CO mechanism. This observable provides a novel way to extract the ratio $ρ_8$ between CO and CS matrix elements. Focusing on $e^+e^-\toΥ(2S)\toγ\,χ_{b2}$ at Belle, we show that the asymmetric beam configuration preserves the asymmetry in the laboratory frame and avoids the strong suppression present in the center-of-mass frame. With the Belle II dataset, $ρ_8$ could be determined with sufficient precision to address the long-standing discrepancy between the lattice calculations and phenomenological determinations.

Clustered sampling is prevalent in empirical regression discontinuity (RD) designs, but it has not received much attention in the theoretical literature. In this paper, we introduce a general model-based framework for such settings and derive high-level conditions under which the standard local linear RD estimator is asymptotically normal. We verify that our high-level assumptions hold across a wide range of empirical designs, including settings of growing cluster sizes. We further show that clustered standard errors that are currently used in practice can be either inconsistent or overly conservative in finite samples. To address these issues, we propose a novel nearest-neighbor-type variance estimator and illustrate its properties in a diverse set of empirical applications.

Fermionic Gaussian circuits can be simulated efficiently on a classical computer, but become universal when supplemented with non-Gaussian operations. Similar to stabilizer circuits augmented with non-stabilizer resources, these non-Gaussian circuits can be simulated classically using rank- or extent-based methods. These methods decompose non-Gaussian states or operations into Gaussian ones, with runtimes that scale polynomially with measures of non-Gaussianity such as the rank and the extent -- quantities that typically grow exponentially with the number of non-Gaussian resources. Current fermionic rank- and extent-based simulators are limited to Gaussian circuits with magic-state injection. Extending them to mixed states and non-unitary channels has been hindered by the lack of known extent-optimized decompositions for physically relevant gates and noisy channels. In this work, we address this gap. First, we derive analytic decompositions for key non-Gaussian gates and channels, including decompositions for arbitrary two-qubit fermionic gates which are provably optimal for diagonal gates or those acting on Jordan-Wigner-adjacent qubit pairs. Second, we show that stochastic Pauli noise can reduce the effective extent of non-Gaussian rotation gates, but that fermionic magic is substantially more robust to such noise than stabilizer magic. Finally, we demonstrate how these decompositions can accelerate classical sampling from the output distribution of a quantum circuit. This involves a generalization of existing sparsification methods, previously limited to convex-unitary channels, to circuits involving intermediate measurements and feed-forward. Our decompositions also yield speedups for emulating noisy Pauli rotations with quasiprobability simulators in the large-angle/arbitrary-strength-noise and small-angle/low-noise parameter regimes.

We derive an identity that relates a class of multiple integrals involving Vandermonde polynomials to divided differences. Alternatively the identity can be viewed as an integral formula for divided differences. As part of the derivation we show that both sums of pure partial derivatives and mixed partial derivatives of Vandermonde polynomials are zero, which might be of independent interest.