Quantum Algorithm for Molecular Properties and Geometry Optimization

It is known that quantum computers, if available, would allow an exponential decrease in the computational cost of quantum simulations. We extend this result to show that the computation of molecular properties (energy derivatives) could also be sped up using quantum computers. We provide a quantum algorithm for the numerical evaluation of molecular properties, whose time cost is a constant multiple of the time needed to compute the molecular energy, regardless of the size of the system. Molecular properties computed with the proposed approach could also be used for the optimization of molecular geometries or other properties. For that purpose, we discuss the benefits of quantum techniques for Newton's method and Householder methods. Finally, global minima for the proposed optimizations can be found using the quantum basin hopper algorithm, which offers an additional quadratic reduction in cost over classical multi-start techniques.Comment: 6 page

Thermal conduction in molecular chains: Non-Markovian effects

We study the effect of non-Markovian reservoirs on the heat conduction properties of short to intermediate size molecular chains. Using classical molecular dynamics simulations, we show that the distance dependence of the heat current is determined not only by the molecular properties, rather it is also critically influenced by the spectral properties of the heat baths for both harmonic and anharmonic molecular chains. For highly correlated reservoirs the current of an anharmonic chain may exceed the flux of the corresponding harmonic system. Our numerical results are accompanied by a simple single-mode heat conduction model that can capture the intricate distance dependence obtained numerically

Statistical Properties of Fermionic Molecular Dynamics

Statistical properties of Fermionic Molecular Dynamics are studied. It is shown that, although the centroids of the single--particle wave--packets follow classical trajectories in the case of a harmonic oscillator potential, the equilibrium properties of the system are the quantum mechanical ones. A system of weakly interacting fermions as well as of distinguishable particles is found to be ergodic and the time--averaged occupation probabilities approach the quantum canonical ones of Fermi--Dirac and Boltzmann statistics, respectively.Comment: 16 pages, several postscript figures, uses 'epsfig.sty'. More information is available at http://www.gsi.de/~schnack/fmd.htm

Molecular Electronics

Molecular electronics describes the field in which molecules are utilized as the active (switching, sensing, etc.) or passive (current rectifiers, surface passivants) elements in electronic devices. This review focuses on experimental aspects of molecular electronics that researchers have elucidated over the past decade or so and that relate to the fabrication of molecular electronic devices in which the molecular components are readily distinguished within the electronic properties of the device. Materials, fabrication methods, and methods for characterizing electrode materials, molecular monolayers, and molecule/electrode interfaces are discussed. A particular focus is on devices in which the molecules or molecular monolayer are sandwiched between two immobile electrodes. Four specific examples of such devices, in which the electron transport characteristics reflect distinctly molecular properties, are discussed

Genetic optimization of training sets for improved machine learning models of molecular properties

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large datasets which exemplify the map from chemical structure to molecular property. Intelligent a priori selection of training examples is often difficult or impossible to achieve as prior knowledge may be sparse or unavailable. Ordinarily representative selection of training molecules from such datasets is achieved through random sampling. We use genetic algorithms for the optimization of training set composition consisting of tens of thousands of small organic molecules. The resulting machine learning models are considerably more accurate with respect to small randomly selected training sets: mean absolute errors for out-of-sample predictions are reduced to ~25% for enthalpies, free energies, and zero-point vibrational energy, to ~50% for heat-capacity, electron-spread, and polarizability, and by more than ~20% for electronic properties such as frontier orbital eigenvalues or dipole-moments. We discuss and present optimized training sets consisting of 10 molecular classes for all molecular properties studied. We show that these classes can be used to design improved training sets for the generation of machine learning models of the same properties in similar but unrelated molecular sets.Comment: 9 pages, 6 figure

Distinctive dielectric properties of nematic liquid crystal dimers

We provide an overview of the effect of the molecular structure on the dielectric properties of dimers exhibiting nematic and twist-bend nematic phases with special focus on how the conformational distribution changes are reflected by the dielectric behaviour. Nematic dimers show distinctive dielectric properties which differ from those of archetypical nematic liquid crystals, as for example, unusual temperature dependence of the static permittivity or dielectric spectra characterised by two low-frequency relaxation processes with correlated strengths. The interpretation of such characteristic behaviour requires that account is taken of the effect of molecular flexibility on the energetically favoured molecular shapes. The anisotropic nematic interactions greatly influence the conformational distribution. Dielectric behaviour can be used to track those conformational changes due to dependence of the averaged molecular dipole moment on the averaged molecular shape. Results for a number of dimers are compared and analysed on the basis of the influence of details of the molecular structure, using a recently developed theory for the dielectric properties of dimers.Postprint (author's final draft