Halogen intercalation into the layered material tungsten ditelluride (WTe2) provides a unique pathway to tune its structural and electronic properties. In this study, we detail the synthesis and characterization of the new bromine-intercalated phases WTe2Brx (x = 0.5, 1.0, and 1.25), and reinvestigate the iodine-intercalated analogue, WTe2I. A defining feature of the bromine system is its rapid and reversible "breathing" behavior at room temperature, allowing guest molecules to be absorbed or released from the van der Waals gaps under ambient conditions. Structural analysis shows that the bromine-poor phase WTe2Br0.5 crystallizes in the orthorhombic space group Pmmn, thereby maintaining a uniform stacking sequence. In contrast, the bromine-rich WTe2Br1.25 phase (space group Imm2) adopts an architecture where two distinct types of bromine layers alternate between the host layers. For the iodine system, the compound WTe2I exhibits both incommensurate and commensurate (3+1)D modulated variants in the superspace group P21/m(α0γ)00. In the commensurate polytype, the structural modulation locks into a rational vector, q = (1/2, 0, 1/6), which can be described also as a 3D supercell. Electronic structure calculations show WTe2Br0.5 and commensurately modulated WTe2I to be metals with flat bands at the Fermi energy arising from the intercalation. These findings demonstrate the unusual stability and structural flexibility of anionic intercalation in a transition metal dichalcogenides.

In this note, we look at the diophantine equation $$ \prod_{i=1}^ta_i!=\prod_{j=1}^sn_i!, \quad n_1\geq \cdots \geq n_s\geq 2 \quad \textnormal{and}\quad n_1>a_1\geq a_2\geq\cdots \geq a_t\geq2. $$ \noindent Let $s<t$. Under the (explicit) abc conjecture, we show that it has only finitely many nontrivial solutions in a certain subset of $\mathbb{N}^{t+s}$ of positive asymptotic density.

We consider a probabilistic cellular automaton (PCA) of evaporation-deposition on the one-dimensional lattice having $n$ sites with periodic boundary conditions, in which each site, during each epoch, can be in one of two states: $0$ and $1$. Fix a positive integer $m\geqslant 2$. There are two types of transitions at each discrete time, which are as follows: (i) the first site in every contiguous block of $m$ $0$s becomes a $1$ with probability $p_1$, and (ii) the first site in every contiguous block of $(m-1)$ $0$s followed immediately by a $1$ also becomes a $1$ with probability $(1-p_2)$. As in a PCA, all of these transitions occur simultaneously. We show that the resulting discrete-time Markov chain is ergodic, and we give an explicit formula for its limiting distribution, the partition function and the density. We also propose necessary and sufficient conditions for this Markov chain to be reversible. For $m=2$, we provide a fully analytical expression for the free energy of this model.

We investigate the buckling of hollow cylindrical tubes subject to their own weight and internal pressure, inspired by the columnar cells of the palisade mesophyll in dicotyledon leaves which resemble pressurized cylindrical tubes. When the internal pressure in the cylinder is equal to the outside pressure, the problem is usually termed self-buckling, which has been studied extensively for solid rods, hollow cylinders, and thin cylindrical shells. Specifically, we perform FEM simulations and desktop-scale experiments to determine the instability thresholds for different geometrical parameters. We first test our models against self-buckling results without pressure for solid rods and hollow cylindrical tubes, and then proceed to determine the critical buckling pressure for a set of material and geometrical parameters. We find that positive internal pressures can stiffen cylinders that are unstable under their own weight, leading to an effective Young's modulus that we show scales linearly with the applied pressure. On the contrary, cylinders that are stable under self-weight, buckle under a negative pressure, resembling classical results on pressure-induced ring buckling. Our findings offer new insights on the interplay between gravity and pressure for the mechanical instability of hollow cylindrical tubes, which we hope will be useful for the study of both engineering and biological structures under similar loads.

Using $e^+e^-$ collision data corresponding to an integrated luminosity of 44 fb$^{-1}$ collected with the BESIII detector at the BEPCII collider, we report the first measurement of Born cross sections and effective form factors for $e^+e^-\toΣ^-\barΣ^+$ at centre-of-mass energies between 3.51 and 4.95 GeV. With a fit to the $\sqrt{s}$-dependent dressed cross sections, the decay $ψ(3770)\toΣ^-\barΣ^+$ is observed for the first time with a significance of 5.5$σ$, including systematic uncertainties. Upper limits at the 90\% confidence level on the product of the branching fraction and the electronic partial width are provided for other possible charmonium(-like) states. The ratios of Born cross sections for the $Σ$ isospin-triplet states are determined and can be used to test the vector-meson-dominance model.

Pixel antenna is a promising antenna technology that enables flexible adjustment of radiation characteristics and enhancement of wireless systems through antenna coding. This work proposes a novel deep learning-based antenna coding optimization algorithm. Specifically, the proposed algorithm is supported by a heterogeneous multi-head selection mechanism, whose main idea is to train multiple neural networks based on various coding schemes and select the one that leads to the best system performance. Unlike traditional heuristic searching-based algorithms that require high computational complexity to achieve satisfactory performance, the proposed data-driven deep learning approach can achieve 98\% of the performance achieved by the searching-based algorithms with significantly reduced computational complexity. Results demonstrate that in pixel antenna empowered single-input single-output systems, the proposed algorithm achieves a computational speed 81 times faster than the searching-based algorithm. For more complex pixel antenna empowered multiple-input multiple-output systems, the computational speed is 297 times faster than the existing searching-based algorithm. Benefiting from the high performance and low computational complexity, this algorithm demonstrates the significant potential of pixel antennas as a novel and practical technology to enhance wireless systems.

Mathematical Programs with Vanishing Constraints (MPVCs) are a notoriously challenging class of problems owing to their lack of constraint qualification. Therefore, to tackle these problems, relaxation-based approaches are typically used. While often yielding satisfactory results, they generally require significant manual tuning and adjustment of the relaxation parameter. To circumvent these problems, we introduce a novel approach based on piecewise gradient flows leading to first-order stationary points. We demonstrate the effectiveness of our method on several real-world MPVC instances and compare it to a common relaxation approach.

In a previous work we constructed different families of stationary electrically charged Proca stars characterized by a charge parameter $q$, by solving the Einstein--Maxwell--Proca system in spherical symmetry, and imposing a harmonic time dependence ansatz for the Proca field (Mio and Alcubierre, 2025). We showed that there is a critical value for the charge $q_c$ that corresponds to the value for which the Coulomb repulsion of the charged Proca field exactly cancels the Newtonian gravitational attraction, and we found that supercritical solutions can only exist for a limited range of charges above this critical value $q>q_c$. Here we study the dynamical stability properties of these charged Proca stars by adding a small but finite perturbation to the original stationary configurations, and then performing numerical evolutions while keeping the spherical symmetry. We show that, for any given family, the parameter space can be separated into three regions corresponding to gravitationally bound stable configurations, gravitationally bound unstable configurations, and gravitationally unbound unstable configurations. For the unstable configurations we follow the evolution in time in order to determine their final state, and find that this final state can be collapse to a charged Reissner--Nordstrom black hole, migration to a new state in the stable branch, or dispersion to infinity, depending on the value of the binding energy and the specific form of the perturbation.

Dynamic programming (DP) algorithms, such as All-Pairs Shortest Path (APSP) and genomic sequence alignment, are fundamental to many scientific domains but are severely bottlenecked by data movement on conventional architectures. While Processing-in-Memory (PIM) offers a promising solution, existing accelerators often address only a fraction of the work-flow, creating new system-level bottlenecks in host-accelerator communication and off-chip data streaming. In this work, we propose GenDRAM, a massively parallel PIM accelerator that overcomes these limitations. GenDRAM leverages the immense capacity and internal bandwidth of monolithic 3D DRAM(M3D DRAM) to integrate entire data-intensive pipelines, such as the full genomics workflow from seeding to alignment, onto a single heterogeneous chip. At its core is a novel architecture featuring specialized Search PUs for memory-intensive tasks and universal, multiplier-less Compute PUs for diverse DP calculations. This is enabled by a 3D-aware data mapping strategy that exploits the tiered latency of M3D DRAM for performance optimization. Through comprehensive simulation, we demonstrate that GenDRAM achieves a transformative performance leap, outperforming state-of-the-art GPU systems by over 68x on APSP and over 22x on the end-to-end genomics pipeline.

Local complement is a graph operation formalized by Bouchet which replaces the neighborhood of a chosen vertex with its edge-complement. This operation induces an equivalence relation on graphs; determining the size of the resulting equivalence classes is a challenging problem in general. Bouchet obtained formulas only for paths and cycles, and brute-force methods are limited to very small graphs. In this work, we extend these results by deriving explicit formulas for several broad families of distance-hereditary graphs, including complete multipartite graphs, clique-stars, and repeater graphs. Our approach uses a technique known as split decomposition to establish upper bounds on equivalence class sizes, and we prove these bounds are tight through a combinatorial enumeration of the graphs' decomposed structure up to symmetry.

When a dark matter halo falls into a more massive object and becomes a subhalo, it typically loses much of its mass through tidal stripping. The reverse process is also possible in principle. The subhalo may gravitationally capture material from its host. If sufficiently efficient, this process could make an initially starless subhalo visible. We use high-resolution N-body simulations to estimate the efficiency of capture. We find that after an extended period orbiting within its host, at most $\sim 10^{-4}$ of a subhalo's remaining mass has been acquired since infall. This captured material is less concentrated to subhalo centre than material retained from before infall. It is also very much less abundant than host material that is instantaneously passing through the subhalo on almost unperturbed orbits. Captured stars are not sufficiently spatially concentrated to be distinguished from the dominant background of "field" stars, and their concentration in velocity space is no greater than that of typical stellar streams in the halo. Unfortunately, stellar capture is not efficient enough to allow initially starless low-mass subhaloes to be detected.

We begin by establishing two fundamental results on standard parabolic subgroups of virtual Artin groups. We first show that a standard parabolic subgroup is naturally isomorphic to a virtual Artin group. Second, we prove that the intersection of two standard parabolic subgroups is a standard parabolic subgroup. Our main result is that, if all free of infinity standard parabolic subgroups of a given virtual Artin group VA[Γ] have a solvable word problem, then VA[Γ] itself has a solvable word problem. It follows that virtual Artin groups of FC type and, more generally, of affine-FC type, have a solvable word problem. We also prove that, if a virtual Artin group VA[Γ] has a solvable word problem, then the strong membership problem for any standard parabolic subgroup in VA[Γ] is solvable.

In this paper, we investigate the asymptotic behavior of the eigenvalues and eigenfunctions of a biharmonic Steklov problem defined on a thin domain in the $n$ dimensional Euclidean space degenerating to a segment. For $n=2$ the problem models the vibrations of a thin elastic plate with cross section represented by the given domain and mass concentrated on a free boundary. The problem under consideration depends on a parameter $σ$ that in the theory of elastic plates represents the Poisson ratio of the material. Our analysis points out a distortion in the limiting problem depending on $σ$ and the space dimension $n$.

New tests are developed for two-way ANOVA models with heterogeneous error variances. The testing problems are considered for testing the significant interaction effects, simple effects, and treatment effects. The likelihood ratio tests (LRTs) and simultaneous comparison tests are derived for all three problems. Hill climbing algorithms have been proposed to compute the maximum likelihood estimators (MLEs) of parameters under the restrictions on the null and alternative hypotheses. It is proved that the proposed algorithms converge to the MLEs. A parametric bootstrap algorithm is provided for the computation of the critical points. The simulated power values of the proposed tests are compared with two existing tests. For testing main effects in the additive ANOVA model, the LRT appears to be about $30\%$ to $50\%$ gain in power over the available tests. Also, the proposed tests for the interaction and simple effects are seen to have comparable power and size performance to the existing tests. The behavior of the proposed tests under the non-normal error distribution is also discussed. Four real data sets are used to demonstrate the application of the proposed tests. A software package is made in `R' to make it simple to apply the tests to experimental data sets.

We report on a comb-locked cavity ring-down spectrometer developed for high-precision, SI-traceable, molecular spectroscopy of air-broadened CO2 gas samples. The experimental setup relies on the use of a singly-resonant optical parametric oscillator that acts as an intermediate link between a 2 micron external-cavity diode laser and an optical frequency comb stabilized against a GPS-disciplined Rb-clock. Absorption spectra of the R(50) ro-vibrational component of the CO2 20012-00001 band have been recorded with high precision and fidelity. As a result of a refined spectral analysis, based on the implementation of the modified Hartmann-Tran profile, line center frequencies, pressure broadening and pressure shifting coefficients have been determined. Finally, we demonstrate the measurement of CO2 mole fractions with a subpromille statistical uncertainty

Optical-field sampling using second-harmonic generation (SHG) from strong-field ionization enables ultrabroadband terahertz detection, but the microscopic origin of the SHG signal and its ultrabroadband response have been unclear. Here we show that the target field lifts the half-cycle cancellation of photoelectron dipole emission, generating the SHG signal used for field sampling. Time-dependent Schrodinger-equation simulations, supported by classical-trajectory Monte Carlo analysis, demonstrate that the SHG yield directly encodes the instantaneous target electric field at the ionization time, enabling waveform retrieval by scanning the probe-target delay. Because the SHG response is gated by a subcycle ionization window rather than the probe envelope, the detection bandwidth can extend far beyond the probe duration. We further quantify practical constraints on retrieval, including intrinsic probe asymmetry and SHG back-action, providing a predictive framework to optimize sensitivity, temporal resolution, and fidelity through controlled electron dynamics.

Topological bound states emerging at domain walls of dimerized chains provide a robust platform for exploring correlation effects beyond single-particle physics. When such a soliton state is coupled to a metallic substrate, local Coulomb interactions can give rise to Kondo screening. Here we demonstrate analytically and numerically that, in an interacting Su-Schrieffer-Heeger (SSH) chain, the Kondo temperature is directly controlled by the topological mass that governs the bulk gap. Near the topological transition, the Kondo scale collapses linearly with the mass parameter while retaining its exponential sensitivity to hybridization. This establishes a minimal mechanism by which a bulk topological parameter quantitatively determines an emergent many-body energy scale. Our results clarify the strong configuration dependence of soliton-induced Kondo signatures observed in graphene nanoribbon systems on Au(111) and provide experimentally testable predictions for scanning tunneling spectroscopy.

Weighted automata over the nonnegative reals form a fundamental model for quantitative languages. We show that, up to scaling, this model collapses to probabilistic automata. Concretely, we prove that every weighted automaton whose transition matrix has spectral radius strictly less than one can be normalised, by a semantics-preserving rescaling of transition weights, into an equivalent locally stochastic probabilistic automaton. Thus, finite-mass weighted automata and probabilistic automata coincide up to normalisation. The construction is effective and relies on Perron-Frobenius theory. We further characterise probabilistic automata by stochastic regular expressions equipped with a geometrically weighted star. Beyond the finite-mass setting, we show that the behaviour of an arbitrary weighted automaton admits a decomposition into an exponential growth rate and a normalised probabilistic component, separating quantitative growth from stochastic structure.

Finding spanning structures with many distinct colours in properly edge-coloured graphs is a central theme in extremal combinatorics. A classical result of Andersen shows that every proper edge-colouring of the complete graph $K_n$ contains a Hamilton cycle with $n - O(n^{1/2})$ distinct colours. In the bipartite setting, the analogous question for perfect matchings is closely related to permutations in Latin squares. In this paper, we investigate how a Dirac-type minimum degree condition forces colour diversity in spanning structures. For every constant $1/2 < c \le 1$, we prove the following. $\bullet$ Every properly edge-coloured graph $G$ on $n$ vertices with $δ(G)\ge cn$ contains a Hamilton cycle with at least $cn - O(n^{1/2})$ distinct colours. $\bullet$ Every subset of an $n\times n$ Latin square with at least $cn$ cells in each row and each column contains a permutation with at least $cn - O(n^{2/3})$ distinct symbols. Both bounds are best possible up to the error term.

We introduce a Bochner integral approach to projective norm attainment in tensor products of Banach spaces by defining the class of integral projective norm-attaining tensors. This framework provides a broader, measure-theoretic approach to the study of projective norm attainment in tensor products of Banach spaces. We show that every integral norm-attaining tensor can be approximated in norm by norm-attaining tensors with finite representations. As a consequence, the Bishop-Phelps type density problem for classical norm-attaining tensors is equivalent to the corresponding density problem for integral norm-attaining tensors. Moreover, we prove that if an integral projective norm-attaining tensor represented by a Radon measure is an extreme point, then it must be an elementary tensor. We further investigate weaker topological versions of integral norm-attainment, including weak and weak$^*$ integral representations, providing sufficient conditions for the existence of Bochner representations. Finally, we extend known constructions of projective tensor products containing non-norm-attaining tensors to the integral setting. We show, for instance, that $L_1\widehat{\otimes}_πL_p$ and the real $c_0\widehat{\otimes}_πL_p$ contain non-norm-attaining tensors for $1<p<\infty$.

The $^{13}$C($α$,$n$)$^{16}$O reaction at low energies is studied by constructing an effective field theory. We choose a separation scale at $E=1$~MeV, where $E$ is the initial $α$-$^{13}$C energy in center-of-mass frame, just below the sharp resonant $5/2^+$ state of $^{17}$O, and include two open channels, $α$-$^{13}$C and $n$-$^{16}$O, and resonant $1/2^+$, $5/2^-$, $3/2^+$ states of $^{17}$O in the study. Parameters of the theory are fitted to experimental data, $S$ factor of $^{13}$C($α$,$n$)$^{16}$O at the energies below $E=1$~MeV, including the data sets recently reported by the LUNA and JUNA collaborations, and the $S$ factor of $^{13}$C($α$,$n$)$^{16}$O is extrapolated to the Gamow peak energy $E_G= 0.19$~MeV in the low mass AGB stars. We discuss an uncertainty in the estimate of the $S$ factor and confirm that the main part of the uncertainty emerges from the parameter fit of the near-breakup threshold $1/2^+$ state of $^{17}$O.

Point cloud processing is a computational bottleneck in autonomous driving systems, especially for real-time applications, while energy efficiency remains a critical system constraint. This work presents FPPS, an FPGA-accelerated point cloud processing system designed to optimize the iterative closest point (ICP) algorithm, a classic cornerstone of 3D localization and perception pipelines. Evaluated on the widely used KITTI benchmark dataset, the proposed system achieves up to 35$\times$ (and a runtime-weighted average of 15.95x) speedup over a state-of-the-art CPU baseline while maintaining equivalent registration accuracy. Notably, the design improves average power efficiency by 8.58x, offering a compelling balance between performance and energy consumption. These results position FPPS as a viable solution for resource-constrained embedded autonomous platforms where both latency and power are key design priorities.

In the present paper we perfomrm molecular dynamics simulation of liquid carbon with a machine-learning potential GAP-20. We show that within the framework of this model carbon demonstrates a relatively low critical temperature, which can affect the results of experimental measurements of melting point of graphite.

Stellar winds interact with the partially ionized interstellar medium (ISM), forming astrospheres. A key feature of this interaction is the hydrogen wall - secondary interstellar atoms produced via charge exchange near the tangential discontinuity separating the stellar wind from the ionized ISM component. This secondary component is decelerated and heated compared to primary interstellar hydrogen, making the hydrogen wall detectable through Lyman-$α$ absorption spectra toward nearby stars. Such structures have been observed by the Hubble Space Telescope around the Sun and other stars. In this paper, we propose that another feature of the stellar wind/partially ionized ISM interaction may also be detectable in Lyman-$α$ spectra: the neutral stellar wind. It forms via charge exchange between supersonic stellar wind protons and interstellar atoms penetrating deep into the astrosphere due to their long mean free paths. We present a parametric numerical analysis of astrospheric structures and their synthetic Lyman-$α$ absorption spectra. Using a 2D kinetic-hydrodynamic model, we vary the terminal wind velocity while maintaining constant dynamic pressure to keep the astrosphere size consistent. For winds slower than the solar wind (terminal velocities $V_0 \lesssim 200$ km/s), charge exchange efficiency in the supersonic region increases dramatically, producing a distinct and observable absorption feature from the neutral wind. This signature is negligible for solar-like winds ($V_0 \approx 400$ km/s) but emerges as a direct spectroscopic diagnostic for winds up to $\sim 200$ km/s. Detecting this neutral wind absorption offers a novel method to directly constrain stellar wind velocities.

This text was written to support a Bourbaki seminar given in January 2026 on the subject of the model theory of perfectoid fields, especially on the work of Jahnke and Kartas in their paper "Beyond the Fontaine-Wintenberger theorem", J. Amer. Math. Soc. 38 (4), pp. 997-1047, 2025.

We develop an iterative refinement method that improves the accuracy of a user-chosen subset of $k$ eigenvectors ($k\ll n$) of an $n\times n$ real symmetric matrix. Using an orthogonal matrix represented in compact WY form, the method expresses the eigenvector error through a correction matrix that can be approximated efficiently from Rayleigh quotients and residuals. Unlike refinement methods for a single eigenpair or for a full eigenbasis, the proposed method refines only the selected $k$ eigenvectors using $\mathcal{O}(nk)$ additional storage, and its dominant work can be organized as matrix--matrix multiplications. Under an eigenvalue separation condition, the refinement converges linearly; we also provide a conservative sufficient condition. Practical variants of the separation condition (e.g., via shifting) enable targeting other extremal parts of the spectrum. For tightly clustered eigenvalues, we discuss limitations and show that preprocessing can restore convergence in a representative sparse example. Numerical experiments on dense test matrices and sparse matrices from the SuiteSparse Matrix Collection illustrate attainable accuracy and problem-dependent convergence.

Using the ZeroDegree multi-reflection time-of-flight mass spectrograph of the CRISMASS project at RIKEN Radioactive Isotope Beam Factory, we performed high-precision mass measurements of proton-rich nuclei near the doubly magic nucleus 100Sn, achieving uncertainties on the order of 10 keV. The masses of 91Rh, 92Pd, and 96Cd were determined for the first time with high precision, and the accuracy of several additional masses was substantially improved. Incorporating the new data into X-ray burst simulations significantly reduces the abundance uncertainties in the $A$ = 90-100 region, shifting the reaction flow toward $A$ = 90 production and suppressing the synthesis of heavier nuclei. Further investigation of the $νp$-process indicates that 99Rh plays a significant role in the reaction flow within the mass region studied. These high-precision mass measurements refine the mass surface near 100Sn and provide critical constraints on models of proton-rich nucleosynthesis.

The derivation and application of Stein identities have received considerable research interest in recent years, especially for continuous or discrete-univariate distributions. In this paper, we complement the existing literature by deriving and investigating Stein-type characterizations for the three most common types of bivariate count distributions, namely the bivariate Poisson, binomial, and negative-binomial distribution. Then, we demonstrate the practical relevance of these novel Stein identities by a couple of applications, namely the deduction of sophisticated moment expressions, of flexible goodness-of-fit tests, and of novel tests for the symmetry of bivariate count distributions. The paper concludes with an analysis of real-world data examples.

Selective image encryption is common in remote sensing systems because it protects sensitive regions of interest (ROI) while limiting computational cost. However, many selective designs enable cross-tile structural leakage under chosen-plaintext attacks when secret-dependent transformations are reused across spatial positions. This paper proposes Tilewise Domain-Separated Selective Encryption (TDS-SE), where per-tile (and optionally per-frame) keys are derived from a master secret via HKDF with explicit domain separation, and ROI masks are treated strictly as external side information. Structural leakage is evaluated using two reconstruction-based distinguishers -- a linear model and a lightweight convolutional neural network -- under multiple attack settings. Experiments on RESISC45 and SEN12MS cover ablation tests, cross-position transferability, cross-sample generalization, and ROI-knowledge asymmetry. Results show that per-tile domain separation reduces position-conditioned transfer for the linear probe, and that adding frame freshness improves robustness to imperfect ROI assumptions for the CNN probe. Cross-sample generalization exhibits mixed behavior across settings, consistent with an empirical evaluation perspective, while selective-encryption functionality is preserved under the same tiling and ROI policy. Beyond the method itself, the paper provides a structured protocol for evaluating selective encryption under realistic attacker capabilities.

Flexible antenna arrays (FAAs) can physically reshape their geometry to add new spatial degrees of freedom, whereas transmit beamforming adjusts the complex element weights to electronically steer and shape the array's radiation pattern, thereby significantly improving communication performance. This paper is the first to explore the integration of FAA geometry control and beamforming for physical layer security enhancement, where a base station equipped with an FAA communicates with a legitimate user in the presence of passive eavesdroppers. To safeguard confidential transmissions, we formulate a new secrecy rate maximization problem that jointly optimizes the transmit beamforming vector and a continuous FAA shape control parameter. Due to the non convex nature of the problem, an alternating optimization algorithm is developed to decompose the joint design into tractable subproblems, which are solved iteratively to refine both the FAA geometry and beamforming strategy. Simulation results confirm that the proposed joint optimization framework significantly outperforms conventional fixed shape or beamforming only schemes, demonstrating the potential of FAA enabled reconfigurability for secure wireless communications.