An Efficient Implementation of High-Order Coupled-Cluster Techniques Applied to Quantum Magnets

We illustrate how the systematic inclusion of multi-spin correlations of the quantum spin–lattice systems can be efficiently implemented within the framework of the coupled-cluster method by examining the ground-state properties of both the square-lattice and the frustrated triangular-lattice quantum antiferromagnets. The ground-state energy and the sublattice magnetization are calculated for the square-lattice and triangular-lattice Heisenberg antiferromagnets, and our best estimates give values for the sublattice magnetization which are 62% and 51% of the classical results for the square and triangular lattices, respectively. We furthermore make a conjecture as to why previous series expansion calculations have not indicated Néel-like long-range order for the triangular-lattice Heisenberg antiferromagnet. We investigate the critical behavior of the anisotropic systems by obtaining approximate values for the positions of phase transition points.     

Minimum-Time Control of a Crane with Simultaneous Traverse and Hoisting Motions

The problem of the minimum-time control of a crane having simultaneous traverse and hoisting motions is considered. We propose an approach that converts this problem into a finite-dimensional optimization problem via control parametrization with an appropriate basis function. Such an approach simplifies the treatment of the constraints and allows for the easy satisfaction of the endpoint constraints. This optimization problem is solved using a novel two-stage optimization process. Under additional conditions, the solution obtained from this process can be shown to be the optimum. When these conditions are not met, a near-optimal solution is obtained. Several numerical examples are provided, including the case where there is unequal cable length at the endpoints. The validity of the solution is verified experimentally on a test rig.     

On the Inexistence of Additive Equi-Lipschitzian Parametrizations of Compact Convex Subsets

A Banach space of dimension at least 2 does not admit an equi-Lipschitzian family of additive mappings parametrizing all non-empty compact convex sets. Examples of linear Lipschitzian as well as positively homogeneous equi-Lipschitzian parametrizations exist in the literature.     

Toward force fields for atomistic simulations of iridium‐containing complexes

The structural and energetic characterization of metal complexes is important in catalysis and photochemical applications. Unraveling their modes‐of‐action can be greatly assisted by computation, which typically is restricted to computationally demanding methods including electronic structure calculations with density functional theory. Here, we present an empirical force field based on valence bond theory applicable to a range of octahedral Ir(III) complexes with different coordinating ligands, including iridium complexes with a chiral P,N ligand. Using an approach applicable to metal‐containing complexes in general, it is shown that with one common parametrization 85% of the 116 diastereomers—all within 21 kcal/mol of the lowest energy conformation of each series—can be correctly ranked. For neutral complexes, all diastereomers are ranked correctly. This helps to identify the most relevant diastereomers which, if necessary, can be further investigated by more demanding computational methods. Furthermore, if one specific complex is considered, the root mean square deviation between reference data from electronic structure calculations and the force field is . This, together with the possibility to carry out explicit simulations in solution paves the way for an atomistic understanding of iridium‐containing complexes in catalysis. © 2013 Wiley Periodicals, Inc.     

Update on phosphate and charged post‐translationally modified amino acid parameters in the GROMOS force field

In this study, we propose newly derived parameters for phosphate ions in the context of the GROMOS force field parameter sets. The non‐bonded parameters used up to now lead to a hydration free energy, which renders the dihydrogen phosphate ion too hydrophobic when compared to experimentally derived values, making a reparametrization of the phosphate moiety necessary. Phosphate species are of great importance in biomolecular simulations not only because of their crucial role in the backbone of nucleic acids but also as they represent one of the most important types of post‐translational modifications to protein side‐chains and are an integral part in many lipids. Our re‐parametrization of the free dihydrogen phosphate (H PO ) and three derivatives (methyl phosphate, dimethyl phosphate, and phenyl phosphate) leads, in conjunction with the previously updated charged side‐chains in the GROMOS parameter set 54A8, to new nucleic acid backbone parameters and a 54A8 version of the widely used GROMOS protein post‐translational modification parameter set. © 2017 Wiley Periodicals, Inc.     

On the convergence domains of hypergeometric series in several variables

We improve Horn’s result on the convergence domains of hypergeometric series in several variables.     

An Adaptive Dual Parametrization Algorithm for Quadratic Semi-infinite Programming Problems

The so called dual parametrization method for quadratic semi-infinite programming (SIP) problems is developed recently for quadratic SIP problems with a single infinite constraint. A dual parametrization algorithm is also proposed for numerical solution of such problems. In this paper, we consider quadratic SIP problems with positive definite objective and multiple linear infinite constraints. All the infinite constraints are supposed to be continuously dependent on their index variable on a compact set which is defined by a number equality and inequalities. We prove that in the multiple infinite constraint case, the minimu parametrization number, just as in the single infinite constraint case, is less or equal to the dimension of the SIP problem. Furthermore, we propose an adaptive dual parametrization algorithm with convergence result. Compared with the previous dual parametrization algorithm, the adaptive algorithm solves subproblems with much smaller number of constraints. The efficiency of the new algorithm is shown by solving a number of numerical examples.