We study the Hamiltonian truncation for the two-dimensional $λϕ^4$ theory within the framework of Hamiltonian truncation effective theory, where truncation artifacts are mitigated through a systematic inclusion of corrective terms organized in inverse powers of the ultraviolet energy cut-off $E_{\rm max}$. Building on the leading-order matching program, we develop two complementary extensions. First, we derive compact all-order expressions for the local matching corrections to the mass and quartic coupling by resumming infinite classes of diagrams sharing fixed topologies within the local approximation. Second, we extend the non-local sector by computing the next-to-next-to-local corrections contributing at $\mathcal{O}(E_{\rm max}^{-4})$, following a continuum-first matching procedure, in which the effective corrections are computed in infinite volume and the spatial direction is subsequently re-compactified to obtain a separable Hilbert-space basis on which the truncated operator construction is implemented. Our results show that an increasingly rich operator basis is necessary to describe the theory beyond leading order.

Given a $p$-adic group $G=\mathbf{G}(F)$ and a finite group $Γ\subset\mathrm{Aut}_F(\mathbf{G})$ such that the fixed-point subgroup $\mathbf{G}^Γ$ is reductive, we show that every semisimple character (in the sense of Bushnell and Kutzko) of a type for $G^Γ= \mathbf{G}^Γ(F)$ arises as the restriction of a semisimple character of a type for $G$. We achieve this by explicitly lifting the truncated Kim--Yu datum (or character-datum) that parametrizes the semisimple character for $G^Γ$ to a character-datum that parametrizes a semisimple character for $G$. Our proof, which is of independent interest, uses state-of-the-art techniques and, as a special case, defines a lift of a Howe factorization of a character of a maximal torus of $G^Γ$.

Refractometric biosensing is a vital label-free tool for the real time detection and interaction analysis of biological and chemical substances. Nanophotonic platforms like Surface Plasmon Resonance (SPR) have played a critical role in providing refractometric sensing capabilities for clinical diagnostics and environmental monitoring. However, traditional systems operating in a single-polarization state cannot fully characterize complex optical properties such as birefringence, which is crucial to resolve many complex biological interactions. Although Bloch Surface Wave (BSW) sensors can support both TE and TM modes, a key capability SPR lacks, they have historically been implemented in single-mode configurations. In this paper, we present a polarization multiplexed BSW refractometric sensing system, simultaneously tracking the resonant wavelength shifts of both TE and TM BSW modes through time. Our technique was applied to investigate single-strand DNA growth during rolling circle amplification (RCA). To accurately recover the time-dependent birefringence, capturing dynamics of the DNA growth and orientation of its chains, we implemented a two-stage modeling approach based on the TMM. First, we utilized a wavelength-dependent surface sensitivity model, confining refractive index changes to the immediate layer above the crystal, to distinguish isotropic background dynamics from birefringent signals. Following the onset of RCA, we transitioned to a model that accounted for the vertical growth of the DNA layers in time. By fitting this model to the TE and TM resonant shifts, we monitor the growth rate of the single-strand DNA layer as well as the refractive index along the two polarization components. Our findings demonstrate the platform's ability to resolve the structural evolution of complex bimolecular interactions associated with conformational changes.

Splines are central objects for the interpolation of discrete data via piecewise smooth paths. Their iterated-integral signature is an infinite collection of tensors which characterizes paths almost uniquely. We study truncations of this collection, which define algebraic maps from parameter space to tensor space. We prove that the images of these maps are given by orbits of a matrix-tensor action. Furthermore, taking the Zariski closure, we define and study varieties of spline signature tensors. We determine dimension and degree of these tensor varieties in a number of examples, relying on symbolic computations. With a view towards learning, constructing paths with a given signature tensor translates to studying the fibers of the signature map. We use computational methods to determine their cardinality, with a focus on its dependence on different classes of splines. We observe in explicit examples that reconstructing splines from a given signature tensor of a path yields close approximations of the original path.

This paper investigates systematic selection of optimal grid points for grid-based Linear Parameter-Varying (LPV) and robust controller synthesis. In both settings, the objective is to identify a set of local models such that the controller synthesized for these local models will satisfy global stability and performance requirements for the entire system. Here, local models correspond to evaluations of the LPV or uncertain plant at fixed values of the scheduling signal or realizations of the uncertainty set, respectively. Then, Bayesian optimization is employed to discover the most informative points that govern the closed-loop performance of the designed LPV or robust controller for the complete system until no significant further performance increase or a user specified limit is reached. Furthermore, when local model evaluations are computationally demanding or difficult to obtain, the proposed method is capable to minimize the number of evaluations and adjust the overall computational cost to the available budget. Lastly, the capabilities of the proposed method in automatically obtaining a sufficiently informative grid set are demonstrated on three case-studies: a robust controller design for an unbalanced disk, a multi-objective robust attitude controller design for a satellite with uncertain parameters and two flexible rotating solar arrays, and an LPV controller design for a robotic arm.

We present an effective potential that allows quantum thermal expectation values of a position-dependent observable to be estimated as a classical ensemble average of the corresponding function. We follow the approach of Feynman and Hibbs, but perform the mean-field treatment of quantum fluctuations about the path starting point rather than the path centroid. Furthermore, rather than performing a full variational optimization of the potential, we explore approximate functional forms that yield a numerical robustness. The resulting closed-form potential is exact in the classical and harmonic limits; benchmarks against exact position distributions for one-dimensional quartic, Morse, and double-well potentials, show good agreement for potentials with harmonic support.

A feature-mapping framework for inverse reconstruction of density-based topology optimization results is proposed. Unlike SIMP, whose voxelized outputs are hard to interpret or reuse, the method represents designs with high-level geometric primitives mapped to a fixed analysis grid. Capsule-shaped bars (endpoints plus radius) are used, with closed-form signed distances and smooth transition functions providing derivatives up to second order. Differentiable pseudo-densities are aggregated with smooth operators, enabling gradient-based optimization with exact Hessians. Robustness is improved through asymmetric transition functions that propagate sensitivities into void regions, a reward-only objective for initialization, and geometric safeguards against degenerate configurations. Reconstruction is performed in stages (exploration, bridging, convergence) with optional refinement that can add, remove, or merge features based on residuals and geometric criteria. Experiments on canonical SIMP benchmarks, including five-bar and cantilever layouts, show high-fidelity reconstructions using a moderate number of features. p-norm and softmax aggregation yield sharp results; pruning removes redundant features and additive refinement restores coverage. Exact Hessians accelerate convergence and improve robustness compared to quasi-Newton updates, providing a bridge from voxel-based outputs to explicit parametric models.

Improved measurements of the coherence factors and strong-phase differences in $D\to K^-π^+π^+π^-$ and $D\to K^-π^+π^0$ decays are reported, using quantum-correlated $D\bar{D}$ pairs produced in $e^+e^-$ annihilation at a center-of-mass energy of $3.773\,\mathrm{GeV}$, where $D$ denotes a quantum superposition of the flavour-specific $D^{0}$ and $\bar{D}^{0}$ mesons. The analysis employs a dataset collected by the BESIII experiment, corresponding to an integrated luminosity of $7.93~\rm fb^{-1}$. The observables sensitive to the coherence factors and strong-phase differences are measured by reconstructing one $D$ meson in the signal mode and the other in a tag mode. These parameters provide essential inputs to the measurement of the angle $γ$ of the Cabibbo-Kobayashi-Maskawa Unitarity Triangle in the LHCb and Belle II experiments. The coherence factors are determined to be $R_{K3π}=0.51\pm0.04$ and $R_{Kππ^0}=0.75\pm0.03$, and the strong-phase differences are $δ_D^{K3π}=\left(182^{+14}_{-13}\right)^\circ$ and $δ_D^{Kππ^0}=\left(209^{+7}_{-8}\right)^\circ$, where the uncertainties include both statistical and systematic contributions. For $D\to K^-π^+π^+π^-$, the parameters have been further determined in four phase-space bins with improved precision compared to the previous BESIII results. The uncertainty on future $γ$ measurements from the knowledge of $D\to K^-π^+π^+π^-$ parameters is expected to be reduced to approximately 3.5$^\circ$.

We establish a parametric supercongruence related to Whipple's ${}_5F_4$ formula and Dwork's dash operation. As a typical consequence, we obtain the following result: for any prime $p\equiv3\pmod4$ and odd integer $r\geq1$, $$ \sum_{k=0}^{p^r-1}(8k+1)\frac{(\frac14)_k^3(\frac12)_k}{(1)_k^3(\frac34)_k}\equiv 3p^r+\frac{27p^{3r}}{4}H_{(p^r-3)/4}^{(2)}\pmod{p^{r+3}}, $$ where $(x)_n=x(x+1)\cdots(x+n-1)$ is the Pochhammer symbol and $H_n^{(2)}=\sum_{k=1}^n\frac{1}{k^2}$ is the $n$-th harmonic number of order $2$. This confirms a conjecture of Guo and Zhao [Forum Math. 38 (2026), 1099-1109]. Our proof rely on a new parametric WZ pair which allows us to transform the original sum to a computable form in the sense of congruence. Another essential ingredient of our proof involves the properties of Dwork's dash operation.

We propose a novel linesearch variant of the trust region normal map-based semismooth Newton method developed in [Ouyang and Milzarek, Math. Program. 212(1-2), 389--435 (2025)] for solving a class of nonsmooth, nonconvex composite-type optimization problems. Our approach uses adaptive parameter estimation techniques, which allow us to avoid explicit and potentially expensive Lipschitz constant computations. We provide extensive convergence results including global convergence, convergence of the iterates under the Kurdyka-Łojasiewicz inequality, and transition to fast local q-superlinear convergence. Compared to the original trust region framework, the linesearch-based algorithm is simpler and the overall convergence analysis can be conducted under weaker assumptions -- in particular, without requiring explicit boundedness conditions on the Hessian approximations and iterates. Numerical experiments on sparse logistic regression, image compression, and nonlinear least squares with group penalty terms demonstrate the efficiency of the proposed approach.

It is well-known since the seminal work of Herbert Federer [Trans. of the AMS, 1959] that submanifolds of class $C^{1,1}$ have positive reach. In this paper, we extend this property to less regular submanifolds by using the notion of $μ$-reach that was introduced in the 2000's. We first show that every compact $C^1$ submanifold of the Euclidean space $\E^n$ has positive $μ$-reach for all $μ<1$. We then show that intermediate regularities $C^{1,α}$ induce more quantitative results on the norm $\|\nabla \d_M\|$ of the generalized gradient of the distance function~$\d_M$ to the submanifold. More precisely, if $M\subset \E^n$ is a submanifold of class $C^{1,α}$, with $α<1$, then there exists a constant $C>0$ such that $$\forall p\in\E^n\setminus M,\quad 1 - \| \nabla \d_M(p) \|^2 \leq C ~ \d_M(p)^{\frac{2 α}{1- α}}.$$ We finally show that the exponent $2α/(1-α)$ in this estimate is sharp.

We analyze the magnetization curve of the spin-1/2 kagome Heisenberg model in a magnetic field. Using state-of-the-art variational wavefunctions based on neural networks, we confirm the presence of robust magnetization plateaus at $m=1/3$, $5/9$ and $7/9$ of the saturation value, stabilized by a spontaneous symmetry breaking of lattice translations with a $\sqrt{3}\times \sqrt{3}$ unit cell. Regarding the more challenging $m=1/9$ plateau, we find two competing valence bond crystals depending on the system size, both breaking translation as well as point group symmetries and with a larger $3\times 3$ unit cell. Such quantum states with local modulations of the magnetization average values could be observed experimentally in the near future.

The development of high-performance electron sources requires theoretical frameworks that accurately link the microscopic electronic properties of cathode materials to their macroscopic photoemission observables. Here, we present a many-body extension of the three-step photoemission model for semiconducting photocathodes, directly integrating the $GW$ approximation and the solution of the Bethe-Salpeter equation on top of density functional theory (DFT). This approach overcomes the intrinsic limitations of standard DFT by explicitly accounting for quasiparticle and excitonic effects in the photoexcitation process. The quantum efficiency (QE) is evaluated by combining the ab initio absorption with an emission probability derived as an exciton-weighted average. We validate this model on representative alkali antimonides and demonstrate that a qualitative many-body description successfully captures complex spectral features that empirical models fail to reproduce. Furthermore, by incorporating macroscopic optical effects such as thin-film interference and polarization via Fresnel post-processing, we achieve quantitative agreement with experimental QE values without any adjustment. Minor discrepancies near the photoemission threshold are attributed to the idealized surface barrier adopted in the model and impurity effects in the samples, highlighting specific directions for future refinements. This work establishes a robust, parameter-free ab initio tool that bridges microscopic electronic correlation with macroscopic observables, providing a critical pathway for the rational design of next-generation electron sources.

In preparation for development of both key technologies and instrument concept studies to use those technologies, the Habitable Worlds Observatory Technology Maturation Project Office at the NASA Goddard Space Flight Center has compiled a series of statements of state of the art for those same key technologies. These statements are being provided to the public as exemplars and suggestions for possible future collaboration for those same instrument concept studies, but without mandate, to enable proposing teams to be able to find the technical solutions they need to field a compelling proposal. This information resides in the public domain and is presented without prejudice.

We investigate Taylor-Couette flow with realistic no-slip boundary conditions at all surfaces through direct numerical simulations (DNS) and theoretical analysis. Imposing physically consistent end-wall conditions at the top and bottom lids significantly alters the flow dynamics compared to that for periodic boundary conditions. We extend the classical angular-momentum-flux framework to account for axial transport, which leads to a significantly improved agreement with the Eckhardt-Grossmann-Lohse model (Eckhardt et al. 2007). A systematic exploration of the parameter space $(Re, n) $ uncovers multiple long-lived states with different roll number $n$ configurations at identical Reynolds numbers $Re$, giving rise to pronounced hysteresis loops occurring under realistic boundary conditions. Our DNS for no-slip axial end caps reveal a sequence of structural transitions: as the inner-cylinder Reynolds number increases, the flow evolves from Taylor vortex flow through chaotic wavy vortex flow and turbulent wavy vortex flow to an axisymmetric turbulent Taylor vortex flow. Using modal energy budgets we identify transition mechanisms and quantify how the accessible phase-space volume and associated roll-specific angular momentum flux depend on control parameters and the specific flow state. Our findings demonstrate the impact of realistic boundary conditions on the dynamics in Taylor-Couette flow, and how they change the stability landscape of multiple states. The coexistence of distinct flow patterns and their stability analysis offers promising insights into transition dynamics between laminar and turbulent regimes in closed sheared flows.

Neural quantum states (NQS) provide a flexible and highly expressive parameterization of wave functions for strongly correlated problems in quantum chemistry. Despite rapid advances in network architectures, the evaluation of electronic energies remains almost exclusively based on variational Monte Carlo (VMC). While VMC is effective for structured systems such as spin chains, its accuracy and efficiency for electronic Hamiltonians are hindered by sharply peaked distributions, stochastic gradient noise, and slow convergence with sample size. In this letter, we assess the capability of NQS-VMC to efficiently capture correlation in electronic ground states by comparing it to a recently developed NQS-based selected configuration (NQS-SC) approach. We set up a systematic comparison of the ground-state optimizations obtained with NQS-VMC and NQS-SC for molecular systems dominated by either static or dynamical correlation. The comparison demonstrates a clear advantage of NQS-SC over NQS-VMC in both energy accuracy and wave-function coefficients, particularly for statically correlated molecules. Moreover, NQS-SC exhibits robust systematic improvability, whereas NQS-VMC does not. These findings position NQS-SC as the new default approach over NQS-VMC for electronic structure calculations. We further observe that neither NQS-SC nor NQS-VMC can efficiently capture dynamical correlation, highlighting the need for future hybrid methods, such as multiconfigurational perturbation theories built on top of NQS solutions.

In many randomized trials, outcomes such as essays or open-ended responses must be manually scored as a preliminary step to impact analysis, a process that is costly and limiting. Model-assisted estimation offers a way to combine surrogate outcomes generated by machine learning or large language models with a human-coded subset, yet typical implementations use simple random sampling and therefore overlook systematic variation in surrogate prediction error. We extend this framework by incorporating stratified sampling to more efficiently allocate human coding effort. We derive the exact variance of the stratified model-assisted estimator, characterize conditions under which stratification improves precision, and identify a Neyman-type optimal allocation rule that oversamples strata with larger residual variance. We evaluate our methods through a comprehensive simulation study to assess finite-sample performance. Overall, we find stratification consistently improves efficiency when surrogate prediction errors exhibit structured bias or heteroskedasticity. We also present two empirical applications, one using data from an education RCT and one using a large observational corpus, to illustrate how these methods can be implemented in practice using ChatGPT-generated surrogate outcomes. Overall, this framework provides a practical design-based approach for leveraging surrogate outcomes and strategically allocating human coding effort to obtain unbiased estimates with greater efficiency. While motivated by text-as-data applications, the methodology applies broadly to any setting where outcome measurement is costly or prohibitive, and can be applied to comparisons across groups or estimating the mean of a single group.

We fabricated a C60-based molecular spin photovoltaic device that integrated a photovoltaic response with the spin transport across the molecular layer. The photovoltaic response can be modified under the application of a small magnetic field, with a magnetophotovoltage of up to 5% at room temperature. Device functionalities include a magnetic current inverter and the presence of diverging magnetocurrent at certain illumination levels that could be useful for sensing. Completely spin-polarized currents could be created by balancing the external partially spin polarized injection with the photogenerated carriers.

Identifying whether a many-body ground state is gapped or gapless is a fundamental yet challenging problem, especially in quantum spin liquids. In this work, we develop a gap-diagnostic scheme based on the polarization amplitude defined via a twist operator, evaluated within the infinite density-matrix renormalization group (iDMRG) framework. As a benchmark, analysis of the spin-$1/2$ XXZ chain demonstrates that the polarization amplitude clearly distinguishes the gapless Tomonaga-Luttinger liquid from the gapped Néel phase. We then extend this framework to infinite cylinders of the spin-$1/2$ XY-$J_χ$ model on the square lattice. We find that the polarization amplitude sharply detects the transition between the gapless XY phase and the gapped chiral spin liquid phase. These results show that polarization amplitudes provide a strong energy-gap diagnostic in two-dimensional frustrated quantum magnets, including quantum spin liquids.

Virtual Production (VP) professionals often face challenges accessing tacit knowledge and creative intent, which are important in forming common ground with collaborators and in contributing more effectively and efficiently to the team. From our formative study (N=23) with a follow-up interview (N=6), we identified the significance and prevalence of this challenge. To help professionals access knowledge, we present GroundLink, a Unity add-on that surfaces meeting-derived knowledge directly in the editor to support establishing common ground. It features a meeting knowledge dashboard for capturing and reviewing decisions and comments, constraint-aware feedforward that proactively informs the editor environment, and cross-modal synchronization that provides referential links between the dashboard and the editor. A comparative study (N=12) suggested that GroundLink help users build common ground with their team while improving perceived confidence and ease of editing the 3D scene. An expert evaluation with VP professionals (N=5) indicated strong potential for GroundLink in real-world workflows.

While conformal transformations in metric scalar-tensor theories recover General Relativity, this feature is notably absent in standard non-metricity-based theories. We demonstrate that by introducing the boundary term C, a non-metricity scalar-tensor theory can recover Symmetric Teleparallel Equivalent of General Relativity (STEGR) in the Einstein frame. Motivated by this, we propose a novel gravity model where a scalar field couples nonminimally to both the non-metricity scalar Q and the boundary term C. We focus in the cosmological scenario where we present the covariant formulation and a unified autonomous system framework that treats generic affine-connection choices, including coincident and non-coincident gauges, on an equal footing. Our dynamical analysis across three connection branches reveals standard thermal histories and stable de Sitter attractors. These results show that boundary-term couplings provide a well-posed, geometrically flexible route to addressing late-time cosmic acceleration.

We investigate reconfigurable intelligent surfaces (RISs) for the task of position and velocity estimation in non-LOS (NLOS) indoor scenarios, using a snapshot based multi-step estimation algorithm. We evaluate a compound RIS structure prototype composed of four RIS tiles with 1-bit phase control per RIS unit cell. Numerical simulation results taking the antenna patterns into account are presented for an 3 m x 3 m area of interest. We demonstrate that the initial grid search step using the far field assumption is not robust enough for small distances to the RIS center and propose a more robust algorithm. Furthermore, we show that the effect of the antenna pattern causes an increased position and velocity error. Our modified three-step algorithm achieves a position error of 7 mm and a velocity error of 0.12 m/s at a distance of 2 m to the RIS center under a realistic numerical propagation model.

The recent discovery of three off-nuclear tidal disruption events (EP240222a, AT2024tvd, and AT2025abcr) - following the first such source, 3XMM J2150$-$05 - reveals a small but robust population of off-nuclear, or `wandering', black holes (WBHs) with masses $M_\bullet > 10^4 M_\odot$. Two demographic trends are already apparent: (i) all events occur in massive, early-type parent galaxies with stellar masses $10.8 \lesssim \log_{10}(M_\star/M_\odot) \lesssim 11.1$; and (ii) events at larger halo-centric radii ($R_{\rm TDE}/R_{200}$) are associated with dwarf satellites ($M_\star \sim 10^7 M_\odot$), while those closer to halo centers lack detected stellar counterparts. Using results from the \texttt{ROMULUS} cosmological simulation, we show that both trends naturally arise from hierarchical galaxy formation. By combining the simulation with empirical constraints on the local galaxy population, we compute the volumetric density of WBHs, $ϕ_{\rm WBH}(M_\star)$, finding that it peaks at $\log_{10}(M_\star/M_\odot)=11.10^{+0.05}_{-0.10}$ and that more than half of all WBHs in the local Universe reside in galaxies with $10.7 \lesssim \log_{10}(M_\star/M_\odot) \lesssim 11.2$, explaining (i) and predicting its persistence as the sample grows. We further show that ii), i.e., the observed link between detection of stellar counterparts and $R_{\rm TDE}/R_{200}$, is also expected from tidal stripping. These results demonstrate that off-nuclear TDEs are powered by the population of WBHs long predicted by cosmological simulations.

We present CryptoChoreo, a choreography language for the specification of cryptographic protocols. Choreographies can be regarded as an extension of Alice-and-Bob notation, providing an intuitive high-level view of the protocol as a whole (rather than specifying each protocol role in isolation). The extensions over standard Alice-and-Bob notation that we consider are non-deterministic choice, conditional branching, and mutable long-term memory. We define the semantics of CryptoChoreo by translation to a process calculus. This semantics entails an understanding of the protocol: it determines how agents parse and check incoming messages and how they construct outgoing messages, in the presence of an arbitrary algebraic theory and non-deterministic choices made by other agents. While this semantics entails algebraic problems that are in general undecidable, we give an implementation for a representative theory. We connect this translation to ProVerif and show on a number of case studies that the approach is practically feasible.

In these lecture notes, a group-theoretical introduction to BMS symmetries is provided in a self-contained manner. More precisely, all definitions and structures are purely based on geometrical and group-theoretical notions defined at null infinity and valid in any dimension, in a way that circumvents its traditional bulk realisation as asymptotic symmetries. The topics which are reviewed are: the definition of BMS transformations as conformal Carrollian isometries of null infinity, the semidirect structure of the BMS group, the holographic reconstruction of Minkowski spacetime in terms of good cuts, the one-to-one correspondence between good cut subspaces and Poincaré subgroups (aka vacua), as well as a basic introduction to unitary representations of the BMS group.

We present the development and characterization of a compact low-energy ion beam diagnostic for the WISArD (Weak Interaction Studies with $\mathrm{^{32}Ar}$ Decay) experiment at ISOLDE/CERN. The microchannel plate (MCP) detector, which is configured in a Z-stack and has a resistive position sensitive anode, was tested with both stable and radioactive beams. This work focuses on the image reconstruction method, which corrects the pincushion distortion inherent to the square-shaped resistive anode, and investigates the influence of the magnetic field on the detector performance. Our results demonstrate that the detector achieves beam profile measurements with sub-millimeter accuracy, while coping with the spatial and high-magnetic field (4 T) constraints of the experiment. These capabilities meet the precision requirements of the WISArD experiment for extracting the modified beta-neutrino angular correlation coefficient, ã$_{βν}$, with an uncertainty of 0.1%.

Two-dimensional (2D) superconductors attracted growing interest in condensed-matter physics research. In this work, we explore the superconducting properties of surface-functionalized, out-of-plane ordered double transition-metal MXenes (o-MXenes), which exhibit distinctive structural and electronic characteristics. Using first-principles calculations, we investigate the effects of electronic structure, electron-phonon coupling (EPC), anharmonicity, and anisotropy effect in superconductivity properties of o-MXenes. We examine a wide range of o-MXene systems, M$_{2}$M$^\prime$X$_{2}$T$_{2}$ (M = Mo, W; M$^\prime$ = Sc, Ti, V, Mo, Zr, Nb, Ta; X = C, N), functionalized with F, O, Cl, and H groups. Out of 128 candidates, 32 compounds are found to be mechanically, dynamically, and thermodynamically stable, exhibiting superconducting transition temperatures (T$_{c}$) from 0.1 K to 52 K. Notably, the Mo$_{2}$ScN$_{2}$O$_{2}$ compound achieves the highest T$_{c}$ of 52 K, with a superconducting gap of $\sim$10 meV. Solving the anisotropic Eliashberg equation reveals that Mo$_{2}$ScN$_{2}$O$_{2}$ is an anisotropic two-gap superconductor, and incorporating anharmonic effects decreases its T$_{c}$ slightly. We further analyze flat-band-induced EPC enhancement and present EPC matrix elements as functions of phonon wavevector q for distinct vibrational modes that show anharmonic behavior of these materials.

In the Maximize Phylogenetic Diversity problem, we are given a phylogenetic tree that represents the genetic proximity of species, and we are asked to select a subset of species of maximum phylogenetic diversity to be preserved through conservation efforts, subject to budgetary constraints that allow only k species to be saved. This neglects that it is futile to preserve a predatory species if we do not also preserve at least a subset of the prey it feeds on. Thus, in the Optimizing PD with Dependencies ($ε$-PDD) problem, we are additionally given a food web that represents the predator-prey relationships between species. The goal is to save a set of k species of maximum phylogenetic diversity such that for every saved species, at least one of its prey is also saved. This problem is NP-hard even when the phylogenetic tree is a star. The $α$-PDD problem alters PDD by requiring that at least some fraction $α$ of the prey of every saved species are also saved. In this paper, we study the parameterized complexity of $α$-PDD. We prove that the problem is W[1]-hard and in XP when parameterized by the solution size k, the diversity threshold D, or their complements. When parameterized by the vertex cover number of the food web, $α$-PDD is fixed-parameter tractable (FPT). A key measure of the computational difficulty of a problem that is FPT is the size of the smallest kernel that can be obtained. We prove that, when parameterized by the distance to clique, 1-PDD admits a linear kernel. Our main contribution is to prove that $α$-PDD does not admit a polynomial kernel when parameterized by the vertex cover number plus the diversity threshold D, even if the phylogenetic tree is a star. This implies the non-existence of a polynomial kernel for $α$-PDD also when parameterized by a range of structural parameters of the food web, such as its dist[...]

We study the molecular beam epitaxy of self-assembled Al$\mathrm{_{1-x}}$Sc$\mathrm{_{x}}$N nanowires on conductive TiN layers and demonstrate their application in piezoelectric nanogenerators. Wurtzite Al$\mathrm{_{1-x}}$Sc$\mathrm{_{x}}$N nanowires with uniform Sc incorporation are grown across a wide composition range (0<x<0.35). At substrate temperatures below 700 $^\circ{}$C, these nanowires exhibit an inversely tapered morphology, whereas higher temperatures favor the nucleation of additional branches due to a phase separation of Al$\mathrm{_{1-x}}$Sc$\mathrm{_{x}}$N into wurtzite AlN and rock-salt ScN. Phase-pure Al$\mathrm{_{1-x}}$Sc$\mathrm{_{x}}$N nanowires are integrated into vertical nanogenerators, where the metallic TiN substrate serves as bottom electrode. The fabricated polymer-nanowire composite devices achieve effective piezoelectric charge coefficients of up to 8.5 pC N$^{-1}$ at x=0.32, thus exceeding the piezoelectric response of bulk AlN by nearly a factor of two. Although the charge response remains lower compared to Al$\mathrm{_{1-x}}$Sc$\mathrm{_{x}}$N thin films, the reduced effective dielectric permittivity of the nanowire-polymer composites compensates the reduction in piezoelectric charge coefficient, eventually yielding a higher voltage response and comparable energy harvesting efficiency. Finally, effective medium modeling reveals that the device architecture is the primary factor limiting performance, providing general design principles for highly efficient nanowire-based piezoelectric energy harvesters.

Modern time-domain surveys produce alert streams at a scale that makes exhaustive manual inspection infeasible, requiring automated methods to identify unusual transients for follow-up. In this work, we present an unsupervised anomaly detection pipeline applied to the ZTF alert stream using the Lasair broker. We define normal objects as SN Ia, SN II, and SN Ib/c. Anomalous objects include (i) more exotic transients (AGN, TDEs, SLSNe, CVs, and nuclear transients) and (ii) supernova-labeled objects, either spectroscopically or by Lasair, with anomalous properties, such as incorrect or absent host associations, or non-supernova-like light curves. Our pipeline consists of three independently trained simple autoencoders operating on distinct alert stream data products: object features, triplet image cutouts, and light curves. Each model is trained on predominantly normal transients, and performance is assessed using the recall of exotic objects and the purity of all anomalous objects across both a spectroscopically classified held-out test set and the live alert stream. In the test set, performance is evaluated at a fixed rank corresponding to the top ten scoring candidates, while in the alert stream it is evaluated using an anomaly threshold defined from test set behavior. Across both settings, the algorithms consistently recover exotic transients and anomalous supernovae among their top-ranked candidates. Over 25 days of live alert stream application, we identify 87 unusual supernova candidates for follow-up. The overlap between anomalies flagged by different autoencoders in the test set is non-existent, and in the alert stream is small, with maximum overlap between any two algorithms being 11 objects. The framework is data-efficient, requiring only a few thousand training examples, making it well suited for early and ongoing application to the Rubin Observatory alert stream.