Quantum nuclear extension of electron nuclear dynamics on folded effective-potential surfaces.

A perennial problem in quantum scattering calculations is accurate theoretical treatment of low energy collisions. We propose a method of extracting a folded, nonadiabatic, effective potential energy surface from electron nuclear dynamics (END) trajectories; we then perform nuclear wave packet dynamics on that surface and calculate differential cross sections for two-center, one (active) electron systems.

Comment on "A minimal implementation of the AMBER-GAUSSIAN interface for ab initio QM/MM-MD simulation".

We comment upon the recent critique of use of the Program for User Package Interfacing and Linking (PUPIL) system for linking AMBER and GAUSSIAN in a multiscale quantum mechanical/molecular mechanics (QM/MM) simulation (Okamoto et al., J. Comput. Chem. 2011, 32, 932). Specifically, their method for computing forces on the MM particles from the QM region via the GAUSSIAN-03 electrical field was already implemented in PUPIL version 1.3, publicly available beginning December 2009. Some other doubtful characterizations of PUPIL are discussed briefly in the context of current awareness of open-source codes more generally.

Application of Quantum Computing to Biochemical Systems: A Look to the Future.

Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.

A versatile AMBER-Gaussian QM/MM interface through PUPIL.

The PUPIL package (Program for User Package Interfacing and Linking) originally was developed to interface different programs for multiscale calculations in materials sciences (Torras et al., J Comput Aided Mater Des 2006, 13, 201; Torras et al., Comput Phys Commun 2007, 177, 265). Here we present an extension of PUPIL to computational chemistry by interfacing two widely used computational chemistry programs: AMBER (molecular dynamics) and Gaussian (quantum chemistry). The benefit is to allow the application of the advanced MD techniques available in AMBER to a hybrid QM/MM system in which the forces and energy on the QM part can be computed by any of the methods available in Gaussian. To illustrate, we present two example applications: A MD calculation of alanine dipeptide in explicit water, and a use of the steered MD capabilities in AMBER to calculate the free energy of reaction for the dissociation of Angeli's salt.

Fracture, water dissociation, and proton conduction in SiO2 nanochains.

A basic issue in nanoscale systems is whether large-scale behavior occurs or not. At and above the mesoscale, the water-silica interaction is known to have large effects, e.g., the geological importance of hydrolytic weakening. Here, we show that water not only substantially weakens a silica nanochain that has been the focus of much recent research but also leads to novel proton conduction. The SiO2 chain consists of a string of orthogonal (planes alternating vertically and horizontally) two-membered rings. We treat two cases of adjacent water to understand both local and collective motion in the system. The first is two water molecules, the second is a water monolayer film that coats the entire chain. Structure, charge separation, stress dependent bond breaking and formation, and proton conduction are discussed based on results obtained at the room temperature. The simulations have been performed using both first-principles molecular dynamics and a novel multiscale quantum-classical software system.

Integral algorithm and density matrix integration scheme for ab initio band structure calculations on polymeric systems.

A new program for band structure calculations of periodic one-dimensional systems has been constructed. It is distinguishable from other codes by the efficient two-electron integral evaluation and the integration schemes of the density matrix in the first Brillouin zone. The computation of polymeric two-electron integrals is based on the McMurchie Davidson algorithm and builds batches of the different cell indices included in the polymeric system. Consequently it presents efficient scaling with respect to the number of unit cells taken into account. Our algorithm takes into account fully the polymeric symmetry rather than the molecular symmetry. A semidirect procedure where only exchange integrals are computed at each SCF cycle is proposed in order to maintain balance between computation time and disk space. In addition, the integration of the density matrix over a large number of cell indices can be performed by different methods, such as Gauss-Legendre, Clenshaw-Curtis, Filon, and Alaylioglu-Evans-Hyslop. This last scheme is able to obtain an accuracy of 10(-13) a.u. on each individual density matrix element for all cell indices with only 48 k-points.