Classical computation with quantum systems

As semiconductor electronic devices scale to the nanometer range and quantum structures (molecules, fullerenes, quantum dots, nanotubes) are investigated for use in information processing and storage, it, becomes useful to explore the limits imposed by quantum mechanics on classical computing. To formulate the problem of a quantum mechanical description of classical computing, electronic device and logic gates are described as quantum sub-systems with inputs treated as boundary conditions, outputs expressed.is operator expectation values, and transfer characteristics and logic operations expressed through the sub-system Hamiltonian. with constraints appropriate to the boundary conditions. This approach, naturally, leads to a description of the subsystem.,, in terms of density matrices. Application of the maximum entropy principle subject to the boundary conditions (inputs) allows for the determination of the density matrix (logic operation), and for calculation of expectation values of operators over a finite region (outputs). The method allows for in analysis of the static properties of quantum sub-systems.

Independent particle descriptions of tunneling using the many-body quantum transport approach

Currents across thin insulators are commonly taken as single electrons moving across classically forbidden regions; this independent particle picture is well-known to describe most tunneling phenomena. Examining quantum transport from a different perspective, i.e., by explicit treatment of electron-electron interactions, we evaluate different single particle approximations with specific application to tunneling in metal-molecule-metal junctions. We find maximizing the overlap of a Slater determinant composed of single-particle states to the many-body current-carrying state is more important than energy minimization for defining single-particle approximations in a system with open boundary conditions. Thus the most suitable single particle effective potential is not one commonly in use by electronic structure methods, such as the Hartree-Fock or Kohn-Sham approximations.

Development of complex classical force fields through force matching to ab initio data: Application to a room-temperature ionic liquid

Recent experimental neutron diffraction data and ab initio molecular dynamics simulation of the ionic liquid dimethylimidazolium chloride ([dmim]Cl) have provided a structural description of the system at the molecular level. However, partial radial distribution functions calculated from the latter, when compared to previous classical simulation results, highlight some limitations in the structural description offered by force fieldbased simulations. With the availability of ab initio data it is possible to improve the classical description of [dmim]Cl by using the force matching approach, and the strategy for fitting complex force fields in their original functional form is discussed. A self-consistent optimization method for the generation of classical potentials of general functional form is presented and applied, and a force field that better reproduces the observed first principles forces is obtained. When used in simulation, it predicts structural data which reproduces more faithfully that observed in the ab initio studies. Some possible refinements to the technique, its application, and the general suitability of common potential energy functions used within many ionic liquid force fields are discussed.

Power dissipation in nanoscale conductors: classical, semi-classical and quantum dynamics

Modelling Joule heating is a difficult problem because of the need to introduce correct correlations between the motions of the ions and the electrons. In this paper we analyse three different models of current induced heating (a purely classical model, a fully quantum model and a hybrid model in which the electrons are treated quantum mechanically and the atoms are treated classically). We find that all three models allow for both heating and cooling processes in the presence of a current, and furthermore the purely classical and purely quantum models show remarkable agreement in the limit of high biases. However, the hybrid model in the Ehrenfest approximation tends to suppress heating. Analysis of the equations of motion reveals that this is a consequence of two things: the electrons are being treated as a continuous fluid and the atoms cannot undergo quantum fluctuations. A means for correcting this is suggested.

Modulation of surface charge, particle size and morphological properties of chitosan-TPP nanoparticles intended for gene delivery

This work investigates the polyanion initiated gelation process in fabricating chitosan-TPP (tripolyphosphate) nanoparticles in the size range of 100-250 nm intended to be used as carriers for the delivery of gene or protein macromolecules. It demonstrates that ionic gelation of cationic chitosan molecules offers a flexible and easily controllable process for systematically and predictably manipulating particle size and surface charge which are important properties in determining gene transfection efficacy if the nanoparticles are used as non-viral vectors for gene delivery, or as delivery carriers for protein molecules. Variations in chitosan molecular weight, chitosan concentration, chitosan to TPP weight ratio and solution pH value were examined systematically for their effects on nanoparticle size, intensity of surface charge, and tendency of particle aggregation so as to enable speedy fabrication of chitosan nanoparticles with predetermined properties. The chitosan-TPP nanoparticles exhibited a high positive surface charge across a wide pH range, and the isoelectric point (IEP) of the nanoparticles was found to be at pH 9.0. Detailed imaging analysis of the particle morphology revealed that the nanoparticles possess typical shapes of polyhedrons (e.g., pentagon and hexagon), indicating a similar crystallisation mechanism during the particle formation and growth process. This study demonstrates that systematic design and modulation of the surface charge and particle size of chitosan-TPP nanoparticles can be readily achieved with the right control of critical processing parameters, especially the chitosan to TPP weight ratio. (c) 2005 Elsevier B.V. All rights reserved.

Measles virus and classical Hodgkin lymphoma: no evidence for a direct association.

A proportion of Hodgkin lymphoma (HL) cases are causally associated with the Epstein-Barr virus (EBV) but the aetiology of the remaining cases remains obscure. Over the last 3 decades several studies have found an association between HL and measles virus (MV) including a recent cohort study describing the detection of MV antigens in Hodgkin and Reed-Sternberg cells, the tumour cells in HL. In the present study we looked at the relationship between history of MV infection and risk of developing HL in a population-based, case/control study of HL. In addition we used immunohistochemistry and RT-PCR to look for direct evidence of MV in HL biopsies. There was no significant difference in the proportion of cases reporting previous measles compared to controls in the entire data set or when young adults were considered separately. Using a robust immunohistochemical assay for MV infection, we failed to find evidence of MV in biopsies from 97 cases of HL and RT-PCR studies similarly gave negative results. This study therefore provides no evidence that MV is directly involved in the development of HL. However, when age at first reported MV infection was investigated, significant differences emerged with children infected before school-age having higher risk, especially of EBV-ve HL, when compared with children infected at older ages; the interpretation of these latter results is unclear.

Solving the advection-dispersion equation using the discrete puff particle method

A flexible, mass-conservative numerical technique for solving the advection-dispersion equation for miscible contaminant transport is presented. The method combines features of puff transport models from air pollution studies with features from the random walk particle method used in water resources studies, providing a deterministic time-marching algorithm which is independent of the grid Peclet number and scales from one to higher dimensions simply. The concentration field is discretised into a number of particles, each of which is treated as a point release which advects and disperses over the time interval. The dispersed puff is itself discretised into a spatial distribution of particles whose masses can be pre-calculated. Concentration within the simulation domain is then calculated from the mass distribution as an average over some small volume. Comparison with analytical solutions for a one-dimensional fixed-duration concentration pulse and for two-dimensional transport in an axisymmetric flow field indicate that the algorithm performs well. For a given level of accuracy the new method has lower computation times than the random walk particle method.