Analyticity of resonances and eigenvalues and spectral properties of the massless Spin–Boson model

We extend the method of Pizzo multiscale analysis for resonances introduced in [5] in order to infer analytic properties of resonances and eigenvalues (and their eigenprojections) as well as estimates for the localization of the spectrum of dilated Hamiltonians and norm-bounds for the corresponding resolvent operators, in neighborhoods of resonances and eigenvalues. We apply our method to the massless Spin–Boson model assuming a slight infrared regularization. We prove that the resonance and the ground-state eigenvalue (and their eigenprojections) are analytic with respect to the dilation parameter and the coupling constant. Moreover, we prove that the spectrum of the dilated Spin–Boson Hamiltonian in the neighborhood of the resonance and the ground-state eigenvalue is localized in two cones in the complex plane with vertices at the location of the resonance and the ground-state eigenvalue, respectively. Additionally, we provide norm-estimates for the resolvent of the dilated Spin–Boson Hamiltonian near the resonance and the ground-state eigenvalue. The topic of analyticity of eigenvalues and resonances has let to several studies and advances in the past. However, to the best of our knowledge, this is the first time that it is addressed from the perspective of Pizzo multiscale analysis. Once the multiscale analysis is set up our method gives easy access to analyticity: Essentially, it amounts to proving it for isolated eigenvalues only and use that uniform limits of analytic functions are analytic. The type of spectral and resolvent estimates that we prove are needed to control the time evolution including the scattering regime. The latter will be demonstrated in a forthcoming publication. The introduced multiscale method to study spectral and resolvent estimates follows its own inductive scheme and is independent (and different) from the method we apply to construct resonances.     

Hexanuclear 3d − 4f metal–organic cages assembled from a carboxylic acid‐functionalized tris‐triazamacrocycle for highly selective fluorescent sensing of picric acid

Two Ln^III ions are sandwiched by dinuclear Co^II building blocks derived from a tris‐triazamacrocyclic ligand bearing pendant carboxylic acid functionality, 1,3,5‐tris((4,7‐bis(2‐carboxyethyl)‐1,4,7‐triazacyclonon‐1‐yl)methyl)‐benzene (H₆L), giving rising to two nanoscale heterometallic metal–organic cages formulated as [Co₄Ln₂(LH_2.5)₂(H₂O)₄]·(ClO₄)₆·NO₃·nH₂O [Ln = Dy, n = 12 ( 1 ); Ln = Yb, n = 9 ( 2 )], whose internal cavity accommodates a guest NO₃^? anion. Their hexanuclear cage‐like architectures are maintained both in solution and solid states as confirmed by mass spectrum as well as X‐ray diffraction experiments. These two cages display ligand‐based fluorescence emissions and therefore both were chosen to be operated as fluorescent chemosensors for the detection of nitroaromatic compounds. Attractively, these metal–organic cages allow highly selective and sensitive detection of picric acid (PA) over other nitroaromatics in solution and suspension, and the fluorescence resonance energy transfer (FRET) between the cage probes and PA is mainly responsible for the remarkable detection efficiency.     

Hydrothermal synthesis,thermal decomposition and optical properties of Fe2F5(H2O)(Htaz)(taz)(Hdma)

Crystal structure of Fe₂F₅(H₂O)(Htaz)(taz)(Hdma) which crystallizes in the triclinic system space group $\text{P}\overline{1}$ with unit cell parameters a = 8.8392(5) Å, b = 9.1948(5) Å, c = 9.5877(5) Å, α = 82.070(3)°, β = 63.699(3)°, γ = 89.202(3)°, Z = 2, and V = 690.91(7) ų, was synthesized under hydrothermal conditions at 393 K for 72 h, by a mixture of FeF₂/FeF₃, 1,2,4-triazole molecule (Htaz), and hydrofluoric acid solution (HF 4%) in dimethylformamide solvent (DMF). The main feature of this material is the coexistence of two oxidation states for iron atoms (Fe²⁺, Fe³⁺) in the unit cell, which associate by opposite fluorine corners of FeF₅N and FeF₂N₄ octahedra, and/or triazole molecule which originates the 2D produces material. The structure determination, performed from single crystal X-ray diffraction data, lead to the R₁/_WR₂ reliability factors 0.031/0.087. Thermal stability studies (TG/DTG/DTA) show that the decomposition provides in the temperature range 473–773 K and no mass loss was detected before 473 K. Mass spectrometry (MS) has been used. The optical absorption of the solid was measured at the corresponding λ_max using UV–vis diffuse-reflectance spectrum.     

Kinetics of carbon steel dissolution in ammonium chloride solution containing sodium thiosulfate

The dissolution behavior of carbon steel in ammonium chloride (NH₄Cl) solution containing sodium thiosulfate (Na₂S₂O₃) of various concentrations (0.01 and 0.1 M) was investigated using electrochemical impedance spectroscopy (EIS) and other nonelectrochemical techniques. The weight loss and polarization measurements indicate a significant increase in the NH₄Cl corrosion rate of carbon steel on addition of Na₂S₂O_3. The EIS measurements exhibited two capacitive loops at multiple direct current (dc) potentials for both the concentrations. Electrical equivalent circuit (EEC) and reaction mechanism analysis (RMA) were employed to analyze the impedance data. A four-step mechanism with two intermediate adsorbate species of same charge was proposed to explain the dissolution behavior of carbon steel in the given system. The surface coverage values enumerated that the surface was entirely covered with adsorbed species unlike in the pure NH₄Cl system. Charge transfer resistance and polarization resistance values estimated from RMA parameters indicate the increase in a dissolution rate with dc potential. The surface morphology was inspected via field emission scanning electron microscopy, and the corrosion products including surface state of carbon steel electrode were analyzed using energy dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy.     

Continuum versus discrete networks,graph Laplacians,and reproducing kernel Hilbert spaces

Motivated by applications to machine learning, we construct a reversible and irreducible Markov chain whose state space is a certain collection of measurable sets of a chosen l.c.h. space $\mathfrak{X}$. We study the resulting network (connected undirected graph), including transience, Royden and Riesz decompositions, and kernel factorization. We describe a construction for Hilbert spaces of signed measures which comes equipped with a new notion of reproducing kernels and there is a unique solution to a regularized optimization problem involving the approximation of $L^2$ functions by functions of finite energy. The latter has applications to machine learning (for Markov random fields, for example).     

An adaptive multilevel wavelet framework for scale‐selective WENO reconstruction schemes

We put forth a dynamic computing framework for scale‐selective adaptation of weighted essential nonoscillatory (WENO) schemes for the simulation of hyperbolic conservation laws exhibiting strong discontinuities. A multilevel wavelet‐based multiresolution procedure, embedded in a conservative finite volume formulation, is used for a twofold purpose. (i) a dynamic grid adaptation of the solution field for redistributing grid points optimally (in some sense) according to the underlying flow structures, and (ii) a dynamic minimization of the in built artificial dissipation of WENO schemes. Taking advantage of the structure detection properties of this multiresolution algorithm, the nonlinear weights of the conventional WENO implementation are selectively modified to ensure lower dissipation in smoother areas. This modification is implemented through a linear transition from the fifth‐order upwind stencil at the coarsest regions of the adaptive grid to a fully nonlinear fifth‐order WENO scheme at areas of high irregularity. Therefore, our computing algorithm consists of a dynamic grid adaptation strategy, a scale‐selective state reconstruction, a conservative flux calculation, and a total variation diminishing Runge‐Kutta scheme for time advancement. Results are presented for canonical examples drawn from the inviscid Burgers, shallow water, Euler, and magnetohydrodynamic equations. Our findings represent a novel direction for providing a scale‐selective dissipation process without a compromise on shock capturing behavior for conservation laws, which would be a strong contender for dynamic implicit large eddy simulation approaches.     

Shape morphing and topology optimization of fluid channels by explicit boundary tracking

An integrated shape morphing and topology optimization approach based on the deformable simplicial complex methodology is developed to address Stokes and Navier‐Stokes flow problems. The optimized geometry is interpreted by a set of piecewise linear curves embedded in a well‐formed triangular mesh, resulting in a physically well‐defined interface between fluid and impermeable regions. The shape evolution is realized by deforming the curves while maintaining a high‐quality mesh through adaption of the mesh near the structural boundary, rather than performing global remeshing. Topological changes are allowed through hole merging or splitting of islands. The finite element discretization used provides smooth and stable optimized boundaries for simple energy dissipation objectives. However, for more advanced problems, boundary oscillations are observed due to conflicts between the objective function and the minimum length scale imposed by the meshing algorithm. A surface regularization scheme is introduced to circumvent this issue, which is specifically tailored for the deformable simplicial complex approach. In contrast to other filter‐based regularization techniques, the scheme does not introduce additional control variables, and at the same time, it is based on a rigorous sensitivity analysis. Several numerical examples are presented to demonstrate the applicability of the approach.     

基于NPP-VIIRS夜间灯光数据的山西省GDP空间化模拟

选取山西省为研究对象，以美国国家极轨合作仪件-可见红外成像辐射计套件（NPP-VIIRS）夜间灯光数据、GDP统计数据等为数据源，构建GDP空间化拟合模型，建立山西省GDP密度图，据此研究山西省经济的空间差异性。通过对NPP-VIIRS夜间灯光数据的空间化处理，提取灯光指数，并将其与GDP进行回归拟合，建立最佳回归模型，得到GDP密度拟合图；利用县级GDP数据进行线性纠正，从而提高GDP的模拟精度。结果表明：（1）NPP-VIIRS夜间灯光数据与GDP的相关性较高，可用于山西省GDP模拟；（2）与GDP分区建模相比，GDP整体建模的精度更高；（3）山西省GDP的空间分布整体呈由城市中心逐渐向周边辐射的特点，构成GDP过渡带。