We study mixed finite element/Crank--Nicolson discretizations of a nonlinear Oldroyd problem with general nonsingular and weakly singular memory kernels. Direct evaluation of the history term requires storing all previous velocity snapshots, which leads to $\mathcal{O}(mN)$ memory and $\mathcal{O}(mN^2)$ work over $N$ time steps, where $m$ denotes the number of spatial degrees of freedom. To reduce this burden, we compress the velocity history online by an incremental singular value decomposition and use the compressed representation in the discrete memory term. Under an approximate low-rank assumption of numerical rank $r$, the storage decreases to $\mathcal{O}((m+N)r)$, while the total history-evaluation work becomes $\mathcal{O}(mNr+rN^2)$. For nonsingular kernels, we derive a tolerance-dependent perturbation estimate showing that the baseline finite element accuracy is retained when the compression tolerance is sufficiently small. We also extend the approach to tempered weakly singular kernels via convolution quadrature. Numerical tests show near-indistinguishable solutions from the uncompressed scheme for the reported tolerances, together with substantial memory savings and reduced wall-clock time.

The universal $2$-parameter vertex algebra $\mathcal{W}_{\infty}$ of type $\mathcal{W}(2,3,\dots)$ is a classifying object for vertex algebras of type $\mathcal{W}(2,3,\dots,N)$ for some $N$; under mild hypotheses, all such vertex algebras arise as quotients of $\mathcal{W}_{\infty}$. In 2017, Gaiotto and Rapčák introduced a family of such vertex algebras called $Y$-algebras, and conjectured that they fall into groups of three that are mutually isomorphic. This is a common generalization of both Feigin-Frenkel duality and the coset realization of principal $\mathcal{W}$-algebras in type $A$, and was proven in 2021 for the simple $Y$-algebras (i.e., one label is zero) by the first and third authors. In this paper, we extend this entire story to the $\mathcal{N}=2$ superconformal setting. First, we prove the 2013 conjecture of Gaberdiel and Candu that there exists a universal $2$-parameter vertex algebra $\mathcal{W}^{\mathcal{N}=2}_{\infty}$ which is an extension of the $\mathcal{N}=2$ superconformal algebra, and has four additional generators in weights $i, i + \frac{1}{2}, i + \frac{1}{2}, i+1$, for each integer $i > 1$. This admits many $1$-parameter quotients which we call $\mathcal{N}=2$ supersymmetric $Y$-algebras, and we prove the dualities among these algebras which were conjectured in 2018 by Prochazka and Rapčák. A special case is the coset realization of the principal $\mathcal{W}$-algebra $\mathcal{W}^k(\mathfrak{sl}_{n+1|n})$ which was conjectured in 1992 by Ito. As a corollary, we obtain the strong rationality of $\mathcal{W}_k(\mathfrak{sl}_{n+1|n})$ for $k = -1 + \frac{1}{n+a+1}$ for all positive integers $n,a$, and we describe its module category. This generalizes Adamović's 1999 result on $\mathcal{N}=2$ minimal models, which is the case $n=1$.

Virtual flood experience systems, which enable users to vividly experience flooding, are attracting increasing attention as effective tools for communicating flood risks. However, existing systems typically rely on virtual cities that do not correspond to real locations and often lack sufficient photorealism, limiting users' ability to relate scenarios to their own surroundings. Although 360° video-based virtual environments offer a simple and scalable way to visually replicate real-world scenes, effective 3D flood visualization in these environments typically requires 3D building geometry of the target area, which is not readily available in many regions. To address this limitation, we propose a new virtual flood experience framework that integrates 360° videos with 3D models automatically constructed from widely available 2D building footprints. By extruding footprints to plausible heights and spatially aligning the constructed models with 360° videos, our framework enables 3D flood visualization in photorealistic environments without relying on pre-existing city models such as CityGML. We demonstrate the framework in Memuro, Hokkaido, Japan, an area vulnerable to river flooding. A user study with local residents showed that the proposed system enhances users' ability to envision location-specific flood evacuation situations, demonstrating its potential as an effective tool for disaster risk communication and education.

ProfileGLMM is an R package integrating Generalised Linear Mixed Models (GLMMs) as the outcome model for Bayesian profile regression. This statistical framework simultaneously i) explains the variation in the outcome and ii) clusters the observations based on a specified set of interdependent clustering covariates. The derived cluster memberships are then incorporated, alongside others, as explanatory variables in the regression to model the outcome. This framework efficiently handles complex, highly correlated covariate structures whose direct inclusion in a standard regression model would be statistically sub-optimal. ProfileGLMM significantly extends Bayesian profile regression's scope by resolving two key constraints of previous implementations: 1) it allows the analysis of hierarchical and longitudinal data structures through the inclusion of random effects, and 2) it enables the study of interactions between latent clusters and other observable covariates. ProfileGLMM accommodates various data types, supporting both continuous or binary outcomes and both categorical and continuous clustering covariates. Built on fast Rcpp code with minimal mandatory parameters, ProfileGLMM offers a flexible analytical tool. It significantly enhances the utility of profile regression for researchers in fields such as epidemiology, social sciences, and clinical studies dealing with complex data.

Background: Receiver Operating Characteristic (ROC) curves are widely used to evaluate the performance of Software Defect Prediction (SDP) models that estimate module fault-proneness, i.e., the probability that a module is faulty. A ROC curve maps a model's performance in terms of True Positive Rate and False Positive Rate for any possible threshold set on fault-proneness. The Area Under the ROC Curve (AUC) summarizes the performance of a model across all possible thresholds. Traditionally, ROC curves completely above the bisector of the ROC space are considered better than random, and high AUC values are associated with good performance. Aim: We investigate whether these beliefs are correct, hence if SDP model evaluation based on ROC curves and AUC is reliable. Method: We decorate ROC curves by highlighting the points corresponding to threshold values. We also represent True Positive Rate and False Positive Rate as functions of the threshold. Thus, we can evaluate whether a model classifies both faulty and non-faulty modules better than the random model. Results: We show that commonly used evaluation criteria may lead to wrong conclusions. Conclusions: A high value of AUC does not guarantee that both the True Positive Rate and the False Positive Rate of a model are better than the random model's for all possible thresholds. Either decorated ROC curves or alternative representations are needed to appreciate all the relevant aspects of SDP models.

We establish a higher-dimensional irrationality criterion for periods which are presented as Mellin integrals depending on many parameters. The criterion is stated as an upper bound on the multi-variate transfinite diameter of the image of the domain of integration under the Mellin arguments. Most of the paper is devoted to studying notions of transfinite diameter relative to very general multivariate Vandermonde matrices. As a proof of principle, we illustrate how this approach works with detailed computations in the case of a 5-parameter family of integrals for $ζ(2)$ on $\mathcal{M}_{0,5}$, the moduli space of curves of genus 0 with 5 marked points. This yields a `higher-dimensional' proof of the irrationality of $ζ(2)$, based on an upper bound for a certain kind of transfinite diameter associated to $\mathcal{M}_{0,5}$.

We study the emergence of symmetric oscillatory behavior in multi-agent systems where each agent incorporates a continuous memory of its past states and past rates of change, modeled by distributed retarded and neutral delays. The closed-loop dynamics are described by a system of nonlinear neutral functional differential equations (NFDEs) with a high degree of symmetry, arising from a network of homogeneous agents. By reformulating the problem as a fixed point operator equation, we apply equivariant degree theory to establish rigorous conditions for unbounded global Hopf bifurcation from the consensus equilibrium. Our main results provide sufficient conditions for the local asymptotic stability of consensus and for the existence of unbounded global branches of non-constant periodic solutions with prescribed spatio-temporal symmetries. The question of whether such periodic solutions are stable (and therefore constitute periodic multiconsensus) is not resolved by the degree method; we address it in an illustrative example via numerical simulation. The example, which models eight coupled asset markets with momentum traders and fundamentalists, demonstrates how memory-driven instability can generate periodic boom-bust cycles across clusters of assets. The numerical experiments confirm the bifurcation predictions and reveal the stability of the resulting oscillations, illustrating the power of combining symmetric bifurcation theory with targeted numerical analysis.

In this letter, a high-fidelity single-shot differential quantitative phase microscopy (dQPM) method is presented to effectively image nearly transparent biological samples. The proposed method is based on a common-path Sagnac interferometric configuration, which provides superior temporal phase stability and robustness against environmental disturbances. The proposed system exploits a pseudothermal source to achieve high spatial sensitivity and generate dense interference fringes for effective single-shot differential quantitative phase imaging. The effectiveness of the proposed system is experimentally demonstrated with various samples, including polystyrene microspheres, a USAF phase target, fixed and live HeLa cells, and mouse kidney tissue.

The rapid collapse of decentralized game economies, often characterized by the \textit{death spiral,} remains the most formidable barrier to the mass adoption of Web3 gaming. This paper proposes that the sustainability of an open game economy is predicated on three necessary and sufficient conditions: Anti-Sybil Resilience, Anti-Capital Dominance, and Anti-Inflationary Saturation. The first section establishes a theoretical proof of these conditions, arguing that the absence of any single dimension leads to systemic failure. The second section explores the dialectical relationship between these dimensions, illustrating how unchecked automation and capital-driven monopolies accelerate asset hyperinflation. In the third section, we introduce the Identity-Bound Asset Integrity Model (IBAIM) as a comprehensive technical solution. IBAIM utilizes Zero-Knowledge (ZK) biometric hashing and Account Abstraction (AA) to anchor asset utility to unique human identities through a privacy-preserving and regulatory-compliant architecture. By exogenizing biometric verification to trusted local environments and utilizing Zero-Knowledge Proofs of Identity (zk-PoI), the model ensures absolute user privacy. Furthermore, by implementing an Asymmetric Utility Decay (AUD) engine-whereby assets suffer a vertical 50% utility cliff upon secondary transfer-and an entropy-driven thermodynamic degradation mechanism., the model successfully decouples financial speculation from in-game merit. Finally, we apply this framework to analyze prominent historical failures in the GameFi sector, demonstrating that their collapse was an inevitable consequence of violating these core economic constraints. Our findings suggest that trading a degree of asset liquidity for system integrity is the only viable path toward long-term economic viability in decentralized virtual worlds.

Axion-Like Particles (ALPs) are well-motivated candidates for dark matter and potential mediators to the dark sector. We present a search for ALPs coupled to photons, based on a reinterpretation of COMPASS data. Using the 2009 dataset consisting of $190~\text{GeV}$ $π^-$ and $μ^-$ beams impinging on a fixed nickel target, we investigate the Primakoff production of ALPs. Due to the high beam energy, ALPs in the MeV mass range are produced with a significant Lorentz boost, leading to strongly collimated decay photons. Consequently, these photons are not spatially resolved by the electromagnetic calorimeter and are instead reconstructed as a single merged cluster. This signature mimics the single-photon signal of Standard Model Primakoff Compton scattering, which was the primary focus of the original COMPASS analysis. By quantifying this potential ALP contamination in the Compton scattering sample, we derive exclusion limits on the ALP-photon coupling $g_{aγγ}$ in the mass range $0.2 \lesssim m_a \lesssim 600~\text{MeV}$. Our results exclude couplings $g_{aγγ} \gtrsim 10^{-1}~\text{GeV}^{-1}$ at 95% C.L., providing independent constraints on the parameter space that bridges beam dump experiments and high energy colliders. While current collider-based limits remain more stringent, this work establishes a novel reinterpretation framework and provides a baseline for future studies of resolved diphoton states in complementary kinematic regimes, such as Primakoff $π^0$ production.

This paper presents the hybrid solver for a $CO_2$ sequestration problem. The solver uses the IGA-ADS (IsoGeometric Analysis Alternating Directions solver) to compute the saturation scalar field update using the explicit method, and CRVPINN (Collocation-based Robust Variational Physics Informed Neural Networks solver) to compute the pressure scalar field. The study focuses on simulating the physical behavior of $CO_2$ in porous structures, excluding chemical reactions. The mathematical model is based on Darcy's Law. The CRVPINN is pretrained on the initial pressure configuration, and the time step pressure updates require only 100 iterations of the Adam method per time step. We compare our hybrid IGA-ADS solver, coupled with the CRVPINN method, with a baseline of the IGA-ADS solver coupled with the MUMPS direct solver. Our hybrid solver is over 3 times faster on a single computational node from the ARES cluster of ACK CYFRONET. Future work includes extensive testing, inverse problem solving, and potential application to $H_2$ storage problems.

Let $X$ be a projective nested product of fields and let $δ_X(d)$ be the minimum distance in degree $d\geq 1$ of the projective nested Cartesian code $C_X(d)$. The regularity index ${\rm reg}(δ_X)$ of the minimum distance function $δ_X$ is the minimum integer $d_0\geq 0$ such that $δ_X(d)=1$ for $d\geq d_0$. We give a formula for ${\rm reg}(δ_X)$ by determining an indicator function of least degree for each point of $X$ and using the fact that ${\rm reg}(δ_X)$ is the ${\rm v}$-number of the vanishing ideal $I_X$ of $X$. Then we give an arithmetical criterion that characterizes when $X$ is Cayley--Bacharach.

The interaction between lattice vibrations of nuclear clusters and superfluid phonons associated with neutron superfluidity plays an important role in the dynamics of the neutron-star inner crust. While this coupling has been discussed mainly within macroscopic approaches such as hydrodynamics and effective field theory, its microscopic origin and the value of the effective coupling constant have remained unclear. In this work, we derive the interaction between nuclear clusters and superfluid phonons starting from a microscopic description of inner-crust matter. Using nuclear density functional theory, we analyze the response of a neutron superfluid around a single nuclear cluster within the quasiparticle random-phase approximation. From this microscopic response, we obtain the interaction between the cluster and the surrounding superfluid. Matching this result to the long-wavelength effective description, we determine the coupling constant in an effective Hamiltonian describing the mixing between lattice and superfluid phonons. The resulting coupling strength is found to be significantly smaller than previous hydrodynamical estimates. This reduction originates from the suppression of the superfluid phonon amplitude inside and around the nuclear cluster. Our results provide a microscopic determination of the coupling parameter governing lattice-superfluid phonon mixing in the neutron-star inner crust.

Accurate antenna array calibrations and measurements of aspects such as active element pattern (AEP) are critical for enabling integrated sensing and communication (ISAC) technologies such as directional modulation. One reliable way of obtaining accurate and repeatable AEP measurements is to spin the antenna array on a turntable, but many turntables designed for antenna array measurements are prohibitively expensive for small labs and may not be designed with RF considerations, such as cable phase stability, in mind. This paper details the design of a motorized 3D printed turntable for use in directional modulation and in-situ measurement experiments that will allow for rotation of an antenna array around a point, such that the far field of the antenna pattern can be measured by a stationary receiver.

We present a complete analysis of the angular momentum selection rules and electromagnetic backgrounds that constrain any spectroscopic search for the gravitomagnetic spin-quadrupole coupling in highly charged ions. A sequence of four barriers is identified: (i)~the Wigner-Eckart theorem mandates $j \geq 3/2$ electronic states for sensitivity to the rank-2 gravitomagnetic operator, excluding the deformation-immune $j=1/2$ states; (ii)~the nuclear electric quadrupole hyperfine interaction (HFS-E2) generates an $\sim 18$-orders-of-magnitude electromagnetic background in the required $j=3/2$ channel; (iii)~second-order HFS mixing between fine-structure levels leaves a residual $\sim 10^{-6}$ eV even after centroid extraction; (iv)~tensor nuclear polarizability (TNP), scaling with $B(E2)$ rather than $Q_s$, introduces an independent rank-2 background of $\sim 10^{-12}$ eV. We derive the algebraic conditions under which a multi-isotope, multi-transition Generalized King Plot can separate these backgrounds from the gravitational signal, and show that the minimum experimental topology requires three transitions and $N_{\text{odd}} \geq N_{\text{bkg}} + 1$ odd-spin isotopes with linearly independent nuclear parameters. For the molybdenum chain, this yields a first laboratory-derivable bound $|χ- 1| \lesssim 10^{8} - 10^9$ on the gyrogravitational ratio, limited by current precision on nuclear quadrupole moments and transition rates. We quantify the experimental milestones needed to improve this bound by each order of magnitude, providing a roadmap for future searches.

Chemical composition provides a powerful route to tune the electronic ground state of iron-based superconductors and other quantum materials, yet access to highly doped phases remains limited. Here we demonstrate that high-pressure thermal decomposition of hydrogen-rich precursors enables over-hydrogenation of LaFeSi. Using anthracene, we synthesize tetragonal superconducting LaFeSiH, including a single hydrogen site, while ammonia borane yields a structurally distorted over-hydrogenated phase, LaFeSiH1+x, with an orthorhombic structure. Chemical analysis reveal excess hydrogen (x ~ 0.6), implying a second H site in LaFeSiH1.6 whose localization and occupancy are determined by neutron diffraction. In contrast to metallic LaFeSi and superconducting LaFeSiH, orthorhombic LaFeSiH1.6 exhibits semiconductor-like behavior. Upon hydrogen release near 100 °C, it transforms into tetragonal superconducting LaFeSiH1+δ (δ << 0.6). These results establish the chemical flexibility of the layered LaFeSiX (X = H, O, F) family and provide access to a high hydrogen-doping regime, creating new opportunities to investigate superconductivity in Fe-based silicides.

Enhanced geothermal systems (EGS) involve strongly coupled, advection-dominated flow and heat transfer in fractured porous media. Conventional models typically assume local thermal equilibrium with a single effective fluid temperature or, at best, an averaged pore-fluid temperature, so the thermal evolution of injected cold fluid is only inferred indirectly. In this work, we develop a local thermal non-equilibrium (LTNE) model that explicitly resolves the temperature of injected fluid as it moves through the reservoir and exchanges heat with the hot rock and resident fluid. The key ingredient is a concentration variable that tracks the injected fluid and induces a three-way LTNE coupling among rock, resident-fluid, and injected-fluid temperatures. This framework distinguishes, at the continuum scale, how newly injected fluid parcels are heated by conductive and convective exchange, and predicts production-well temperatures without relying on bulk averages. To discretize the resulting nonlinear, advection-dominated system, we employ an enriched Galerkin (EG) finite element method for Darcy flow, temperature, and concentration, providing local mass conservation with relatively few degrees of freedom. We further design a flux-corrected transport (FCT) strategy for the EG concentration and temperature equations to enforce a discrete maximum principle and suppress nonphysical oscillations while preserving local conservation. Time integration uses an IMPES-type splitting combined with a strong-stability-preserving Runge--Kutta scheme. Numerical experiments for fractured EGS problems show that the proposed LTNE--EG--FCT framework captures injected-fluid heating paths and thermal breakthrough behavior not resolved by standard single-temperature or averaged LTNE models.

ThCr$_2$Si$_2$-type intermetallics are layered conductors in which crystallographic anisotropy and multiband electronic states often give rise to characteristic magnetotransport phenomena. Here, we report the molecular-beam epitaxy growth of LaAg$_2$Ge$_2$ thin films on MgO(001) and their magnetotransport properties. The Hall effect and magnetoresistance are captured by an effective two-carrier description with a high-mobility electron band, yielding a positive magnetoresistance of 22.5% at 9 T. Angle-dependent magnetoresistance exhibits a dominant twofold anisotropy and additional reproducible dip/peak features at characteristic tilt angles that are nearly independent of field and temperature. These results extend our understanding of the anisotropic electronic transport in thin-film germanides within the ThCr$_2$Si$_2$ family.

We describe the design and performance of a 260-liter liquid argon (LAr) cryogenic test stand for liquid argon detector research and development at BNL. The system uses gas-phase argon purification with continuous pump-free circulation, in which boil-off argon gas is purified, recondensed, and returned to the cryostat by gravity without a mechanical recirculation pump; it also incorporates an upgraded condenser that increases the effective thermal contact area by a factor of 13 relative to the previously developed 20-liter system reported perviously. A liquid argon purity monitor is installed to measure the electron lifetime directly in LAr, enabling quantitative characterization of charge attenuation due to electronegative impurities. Under the operating conditions reported here, the demonstrated electron lifetime is 0.5 ms. The system is designed to enable rapid iteration of detector components in complete operational cycles, including pump-down, leak verification, cryogenic fill, stable operation, and warm-up, which can be completed within 7 days. Such a fast turnaround time, together with the medium-scale liquid volume and direct purity diagnostics, makes the facility well suited for testing and refining detector designs in support of large liquid argon time projection chamber (LArTPC) experiments.

Direct satellite uplink is severely constrained by limited link budgets, which hinder the exploitation of wideband resources, and ultimately limit the throughout. This paper presents a pilot-less coded modulation scheme based on sparse superposition coding (SSC) to enable efficient wideband usage in coverage-limited scenarios. This scheme leverages the structured Zadoff-Chu quasi-orthogonal (ZC-QO) dictionary to support scalable transmission. To address decoding complexity, the SSC transmitted signal embeds root index information via indicator sequences, allowing the receiver to restrict the decoding search space. In addition, a multi-codeword transmission framework with repetition and stop-feedback is developed, enabling reliable communication and better resource utilization. Simulation results show that the proposed scheme achieves throughput gains compared to a more conventional narrow-band multi-dimensional constellation-based approach.

Sampling problems are promising candidates for demonstrating quantum advantage, and one approach known as quantum-enhanced Markov chain Monte Carlo [Layden, D. et al., Nature 619, 282-287 (2023)] uses quantum samples as a proposal distribution to accelerate convergence to a target distribution. On the other hand, many practical problems are large-scale and constrained, making it difficult to construct efficient proposal distributions in classical methods and slowing down MCMC mixing. In this work, we propose a divide-and-conquer neural network surrogate framework for quantum sampling to accelerate MCMC under fixed Hamming weight constraints. Our method divides the interaction graph for an Ising problem into subgraphs, generates samples using QAOA for those subproblems with an XY mixer, and trains neural network surrogates conditioned on the Hamming weight to provide proposal distributions for each subset while preserving the constraint. In numerical experiments of Boltzmann sampling on 3-regular graphs, our method consistently accelerated mixing as the system size $N$ increased, with average improvements in the autocorrelation decay rate constant by speedup factors of about $20.3$ and $7.6$ over classical pair-flip methods based on nearest-neighbor and non-nearest-neighbor exchanges, respectively. We also applied the method to an MNIST feature mask optimization problem with $N=784$, obtaining faster energy convergence and a $2.03\%$ higher classification accuracy. These results show that our method enables efficient and scalable MCMC and can outperform classical methods for practical applications on NISQ devices.

For $q\in\mathbb{R}\backslash\{0\}$, the generalized Laplacian of a graph $X$ is the matrix $\mathscr{L}=Δ+qA$, where $Δ$ is the degree matrix and $A$ is the adjacency matrix of $X$. In this paper, we investigate perfect state transfer (PST) on graphs with possible loops equipped with non-trivial involutions, where we take the generalized Laplacian matrix as the Hamiltonian of the underlying spin network. We establish an equivalence between the existence of PST between certain pair (or plus states) in such a graph and PST between vertices in a subgraph induced by the involution. This allows us to prove that for almost all simple unweighted planar graphs (resp., almost all simple unweighted trees), the assignment of loops of weight one to exactly two vertices in the graph produces PST between pair states relative to $\mathscr{L}$. We also show that a path on $n$ vertices admits PST between end vertices relative to $\mathscr{L}$ if and only if $n =2$, or $(n,q)=(3,\frac{k^2-l^2}{8l^2})$ where $k>l$ are integers with $k \not\equiv l \pmod{2}$. For cycles, we show that the addition of an extra edge does not yield PST between vertices relative to Laplacian and signless Laplacian matrices. Furthermore, we show that the addition of a few suitable edges (including loops) in complete bipartite graphs, cycles, and paths yields PST between pair states.

We systematically explore the design space of ferroelectric hafnium-zirconium oxide (H0.5Z0.5O or HZO) heterostructures for reliable high temperature operation. HZO films are deposited using thermal and plasma-enhanced atomic layer deposition (Th-ALD and PE-ALD) on tungsten (W) and titanium nitride (TiN) bottom electrodes (BE), while maintaining identical top electrodes. We demonstrate that PE-ALD HZO capacitors integrated with W BE exhibit wake-up-free switching up to 125C, along with significantly improved endurance compared to Th-ALD HZO/W devices across a wide temperature range (85-125C). By decoupling the contributions of the plasma-deposited HZO film and the oxidized bottom interface inherently formed during PE-ALD, we identify the oxidized W interfacial layer (WOx) as the primary factor governing endurance enhancement and wake-up suppression at elevated temperatures, while the PE-ALD HZO film provides secondary benefits in reducing wake-up. In contrast, PE-ALD HZO capacitors fabricated on TiN BE show no substantial improvement in wake-up behavior or endurance relative to Th-ALD HZO/TiN devices, despite the formation of an unintentional TiOxNy interfacial layer, and instead exhibit degraded polarization. This difference arises from the significantly weaker endurance enhancement and no wake-up suppression provided by oxidized TiN compared to oxidized W under comparable oxidation conditions. Overall, PE-ALD HZO films enable superior ferroelectric performance at elevated temperatures only when deposited on W BE, while Th-ALD HZO films remain a viable option for high temperature operation on TiN BE. These findings clarify the interplay between deposition technique, electrode chemistry, and interfacial oxidation, and provide design guidelines for integrating ferroelectric memories into monolithic 3D systems under stringent thermal constraints.

We study dynamical correlations of interacting hard-core anyons on a one-dimensional lattice at infinite temperature. This is a setting in which the many-body spectrum is independent of the statistical phase $θ$, while dynamical correlators remain sensitive to $θ$ through nonlocal Jordan-Wigner strings. We compute single-particle Green's functions, spectral functions, and density-density correlators, thereby separating the effects of fractional statistics on one-body coherence from those on density transport in a maximally mixed ensemble. In the noninteracting case $V=0$, high-temperature averaging leads to inversion-symmetric Green's functions for all $θ$ despite the presence of anyonic strings. Finite nearest-neighbor interactions $V$ generate, however, a pronounced left-right asymmetry in the Green's functions for $0<θ<π$, with the strongest chirality appearing at intermediate couplings $V\sim J$ where interactions and hopping compete most effectively. In this regime, the Green's function decays exponentially in time with a statistical-angle-dependent decay rate. At strong coupling, the dynamics crosses over to an atomic-limit regime in which the dependence on $θ$ is reduced. Here the Green's function decays universally as $t^{-1}$ and the corresponding spectral function displays a three-band structure. In contrast, density-density correlations are insensitive to statistics and recover the known infinite-temperature transport regimes of the XXZ chain, including ballistic, superdiffusive and diffusive behaviours. These results identify dynamical correlation functions as direct probes of fractional statistics in high-entropy quantum systems.

In this work, we experimentally investigate the gradient stress (sigma1) in 128 deg Y-cut transferred thin film lithium niobate (TFLN) films with thicknesses from 100 to 460 nm using cantilever curvature analysis. The results reveal a strong dependence of sigma1 on both crystallographic orientation and film thickness, with stress-free orientations at approximately 55 deg and 125 deg for 220-460 nm films, shifting to approximately 20 deg and 160 deg for 100 nm films. The extracted normalized sigma1 ranges from -0.1 to 3.4 MPa/nm (100 nm), -0.8 to 0.34 MPa/nm (220 nm), and -0.12 to 0.08 MPa/nm (460 nm), indicating a pronounced thickness-dependent through-thickness stress gradient. Finite element simulations show excellent agreement with the measurements, validating the curvature-based extraction method and confirming that sigma1 originates from an orientation-dependent residual stress gradient. To mitigate this effect, a bilayer TFLN structure with opposite crystallographic orientations, forming a periodically poled piezoelectric film (P3F), is investigated, enabling partial cancellation of sigma1. A 90/110 nm P3F bilayer reduces the equivalent normalized sigma1 to -0.4 to -0.04 MPa/nm, resulting in significantly reduced deformation. These results establish gradient stress engineering through orientation, thickness, and bilayer design as an effective strategy for achieving mechanically stable and scalable TFLN microelectromechanical systems (MEMS) devices.

We study the random-cluster model on trees and treelike graphs at low temperatures. This is a model of dependent percolation parametrized by an edge probability $p\in (0,1)$ and a clustering weight $q\in [1,\infty)$, generalizing independent Bernoulli percolation ($q=1$) and closely related to the classical ferromagnetic Ising and Potts spin systems at integer $q$. For $q>2$, approximately sampling from this model on graphs of degree at most $Δ$ is computationally hard. At parameter $p$ below the tree uniqueness threshold $p_{\mathsf{u}}(q,Δ)$, it is expected that sampling is easy and local Markov chains mix rapidly on all bounded degree graphs. On typical graphs (e.g., random regular graphs), the same is predicted at $p > p_{\mathsf{s}}(q,Δ)$, where $p_{\mathsf{s}}(q,Δ)$ is a second uniqueness transition point on the $Δ$-regular wired tree. Our first result establishes this non-uniqueness/uniqueness phase transition at $p_{\mathsf{s}}(q,Δ)$ for all $q$ on the infinite $Δ$-regular wired tree, resolving a conjecture of H{ä}ggstr{ö}m (1996). For this, we establish weak spatial mixing at $p>p_{\mathsf{s}}(q,Δ)$ under sufficiently wired boundary conditions. We use this understanding of decay of correlations to show that on the wired tree on $n$ vertices, whenever $q>1$ and $p>p_{\mathsf{s}}(q,Δ)$, the mixing time of random-cluster Glauber dynamics is a near-optimal $n^{1+o(1)}$. We then extend these results on spatial and temporal mixing from the tree to treelike geometries with mostly wired boundaries and use them to show that the random-cluster Glauber dynamics mix rapidly on the random $Δ$-regular graph for all $p>p_{\mathsf{s}}(q,Δ)$ as long as $q \ge C \log Δ$, providing an efficient sampling algorithm for both the random-cluster and Potts models in this context.

Identifying and quantifying $γ$-emitting radionuclides, considering spectral deformation from $γ$-interactions in radioactive source surroundings, present a significant challenge in $γ$-ray spectrometry. In that context, a hybrid machine learning method has been previously proposed to jointly estimate the counting and spectral signatures of $γ$-emitters under conditions of spectral variability. This paper addresses the uncertainty quantification of the estimators (i.e., the counting and the variable $λ$ which characterizes the spectral signatures) obtained by this spectral unmixing algorithm. The focus is on the coverage interval, as defined by the GUM, which corresponds closely to a credible interval in the Bayesian framework. Given the inverse problem and the constraints associated with spectral deformation, two Bayesian methods - Laplace approximation and Markov Chain Monte Carlo - have been developed for uncertainty quantification to ensure robust decision-making. The Laplace approximation technique approximates the posterior distribution by a Gaussian distribution, while the Markov Chain Monte Carlo technique samples the posterior distribution. This study evaluates these two methods in terms of precision of coverage interval based on repeated Monte Carlo samples using the long-run success rate. Numerical experiments show that both methods yield similar results close to the expected success rate of 95.4$\%$ when constraints related to spectral signatures deformation and counting are inactive. However, when constraints are active or the background counting significantly dominates other radionuclides, the Laplace approximation method deviates from the expected long-run success rate due to the non-Gaussian posterior distribution. In such cases, the Markov Chain Monte Carlo method still provides robust results.

We study unidirectional transverse scattering in a two-dimensional acoustic dimer composed of two isotropic subwavelength scatterers. Using a coupled multipole model, we show that inter-particle coupling enables effective monopole-dipole interference and supports a transverse Kerker effect under plane wave excitation. In contrast to a single non-absorbing isotropic particle, where Kerker-type cancellation is only approached in the weak-scattering limit, the dimer can combine pronounced directionality with strong overall scattering. This regime is promising for compact acoustic beam steering and directional wave routing.

Understanding how biochemical systems settle into stable states, such as how protein concentrations reach equilibrium, is central to explaining cellular behavior and designing synthetic biological circuits. However, existing analytical tools for computing these equilibria, such as COMPILES, are limited by computational bottlenecks and can only be applied to a restricted class of reaction networks. In this work, we introduce CRITERIA (Computing paRametrized posITive EquilibRIA), a new computational framework that makes equilibrium analysis more efficient and broadly applicable. CRITERIA uses a graph-based approach built on elementary flux modes to streamline key steps in the computation. It also changes how the problem is solved by combining subnetworks into a single system before computing equilibria, which avoids complicated symbolic calculations required in previous methods. We demonstrate the usefulness of CRITERIA by studying biologically important systems, including the EnvZ-OmpR signaling pathway and a synthetic CRISPRi circuit. Our approach enables faster and more scalable analysis, allowing researchers to better understand how complex biochemical networks behave over time.

Cutoff independence is an essential requirement for the predictive power of nuclear \textit{ab initio} calculations based on effective field theory (EFT). While it is conventionally assumed that such invariance necessitates high-order interactions and complex many-body forces, we present a minimal chiral nuclear force that exhibits remarkable cutoff independence across a broad range from light to medium-mass nuclei and sub-saturated nuclear matter. Our framework comprises only contact terms up to next-to-leading order, a single three-nucleon contact force, and a leading-order one-pion-exchange potential, all constrained strictly in the $A \leq 3$ sector. Despite its simplicity, this interaction accurately reproduces experimental binding energies up to $^{40}\text{Ca}$ with unexpectedly small residual cutoff dependencies of only a few MeV. We demonstrate that the use of a lattice-inspired \emph{absolute}-momentum regulator efficiently suppresses high-momentum modes, resolving the overbinding problem for soft chiral forces without invoking complex many-body forces. These results establish a robust and economic foundation for EFT-based \textit{ab initio} calculations in both continuum and lattice frameworks.