Reaction dynamics for the Cl(2^2P) + XCl →\to XCl + Cl(2^2P) (X = H, D, Mu) reaction on a high-fidelity ground state potential energy surface

Globally accurate full-dimensional ground state potential energy surface (PES) for the Cl($^2$P) + XCl $\to$ HCl + Cl($^2$P) reaction, a prototypical heavy-light-heavy abstract reaction, is developed using permutation invariant polynomial neural network (PIP-NN) method and embedded atom neural network (EANN) method, with the corresponding total root mean square error (RMSE) being only 0.043 and 0.056 kcal/mol, respectively. The saddle point of this reaction system is found to be nonlinear. A full-dimensional approximate quantum mechanical method, ring-polymer molecular dynamics (RPMD) with Cayley propagator, is employed to calculate the thermal rate coefficients and kinetic isotopic effects of title reactions Cl($^2$P) + XCl $\to$ XCl + Cl($^2$P) (X = H, D, Mu) on both new PESs. The results reproduce the experimental results at high temperatures perfectly, but with moderate accuracy at lower temperatures. The similar kinetic behavior is supported by quantum dynamics using wave packet calculations as well.Comment: 23 pages,5 figure

Retraction-based first-order feasible methods for difference-of-convex programs with smooth inequality and simple geometric constraints

In this paper, we propose first-order feasible methods for difference-of-convex (DC) programs with smooth inequality and simple geometric constraints. Our strategy for maintaining feasibility of the iterates is based on a "retraction" idea adapted from the literature of manifold optimization. When the constraints are convex, we establish the global subsequential convergence of the sequence generated by our algorithm under strict feasibility condition, and analyze its convergence rate when the objective is in addition convex according to the Kurdyka-Lojasiewicz (KL) exponent of the extended objective (i.e., sum of the objective and the indicator function of the constraint set). We also show that the extended objective of a large class of Euclidean norm (and more generally, group LASSO penalty) regularized convex optimization problems is a KL function with exponent $\frac12$; consequently, our algorithm is locally linearly convergent when applied to these problems. We then extend our method to solve DC programs with a single specially structured nonconvex constraint. Finally, we discuss how our algorithms can be applied to solve two concrete optimization problems, namely, group-structured compressed sensing problems with Gaussian measurement noise and compressed sensing problems with Cauchy measurement noise, and illustrate the empirical performance of our algorithms

Single-conductor co-planar quasi-symmetry unequal power divider based on spoof surface plasmon polaritons of bow-tie cells

In this paper, the spoof surface plasmon polaritons (SSPPs) transmission line (TL) of periodical grooved bow-tie cells is proposed. The complex propagation constant and characteristic impedance of the SSPPs TLs and microstrip lines (MLs) are extracted using the analytical method of generalized lossy TL theory. The properties of the SSPPs TLs with different substrates and the same geometrical configuration are experimented. Then, for comparison, two ML counterparts are also experimented, which shows that the SSPPs TL is less sensitive to the thickness, dielectric constant and loss tangent of the chosen substrate below the cutoff frequency, compared with the ML ones. The single-conductor co-planar quasi-symmetry unequal power divider based on this SSPPs TL is presented in microwave frequencies. For experimental validation, the 0-dB, 2-dB, and 5-dB power dividers are designed, fabricated, and measured. Both simulated and measured results verify that the unequal power divider is a flexible option, which offers massive advantages including single-conductor co-planar quasi-symmetry structures, wide-band operation, and convenient implementations of different power-dividing ratios. Hence, it can be expected that the proposed unequal power dividers will inspire further researches on SSPPs for future design of novel planar passive and active microwave components, circuits and systems

Wideband Filtering Power Divider With Ultra-Wideband Harmonic Suppression and Isolation

In this paper, a wideband filtering power divider (PD) with ultra-wideband harmonic suppression and isolation is proposed. The dual coupled-line sections are embedded to the conventional quarter-wavelength transmission lines, which helps to extend the passband of the PD. With the introduction of the short-circuit stubs shunted at the output ports and the coupled lines with the open-circuit stubs, the ultra-wide stopband can be implemented more efficiently, thus resulting in five transmission zeros from 2 to 6 GHz. Furthermore, the improved isolation structure with series connected a resistor and a capacitor can be utilized to realize the ultra-wide isolation frequency band. Using a single resistor between two output ports, we have achieved an excellent in-band isolation. For demonstration, a wideband filtering PD operating at 1 GHz with a 20-dB bandwidth of 50% and an ultra-wide stopband better than 20 dB from 2 to 6 GHz is designed, fabricated, and measured. The measured results agree well with the anticipation

Arbitrary Multi-way Parallel Mathematical Operations Based on Planar Discrete Metamaterials

Multi-way parallel mathematical operations along arbitrary transmission paths are constructed based on realizable planar discrete metamaterials in this paper. The introduced method of “computational metamaterials” is used to perform the desired mathematical operations. For producing high-efficiency devices, the function of multi-way parallel mathematical operations is indispensable in advanced analog computers. Therefore, in this paper, we propose the arbitrary transmission paths that can be implemented by the bending of the electromagnetic waves based on the finite embedded coordinate transformations, which has a strong potential to realize the function of multi-way parallel computation. Nevertheless, owing to the inherent inhomogeneous property, metamaterials are difficult to be achieved in nature currently. In order to make it possible for fabricating in practical applications, the planar discrete metamaterial is a promising medium due to its homogeneous property. Numerical simulations validate the novel and effective design method for parallel optical computation

Molecular dynamics simulation of the transformation of Fe-Co alloy by machine learning force field based on atomic cluster expansion

The force field describing the calculated interaction between atoms or molecules is the key to the accuracy of many molecular dynamics (MD) simulation results. Compared with traditional or semi-empirical force fields, machine learning force fields have the advantages of faster speed and higher precision. We have employed the method of atomic cluster expansion (ACE) combined with first-principles density functional theory (DFT) calculations for machine learning, and successfully obtained the force field of the binary Fe-Co alloy. Molecular dynamics simulations of Fe-Co alloy carried out using this ACE force field predicted the correct phase transition range of Fe-Co alloy.Comment: 17 pages, 6 figure