15 research outputs found

    Higher order and infinite Trotter-number extrapolations in path integral Monte Carlo

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    Improvements beyond the primitive approximation in the path integral Monte Carlo method are explored both in a model problem and in real systems. Two different strategies are studied: the Richardson extrapolation on top of the path integral Monte Carlo data and the Takahashi-Imada action. The Richardson extrapolation, mainly combined with the primitive action, always reduces the number-of-beads dependence, helps in determining the approach to the dominant power law behavior, and all without additional computational cost. The Takahashi-Imada action has been tested in two hard-core interacting quantum liquids at low temperature. The results obtained show that the fourth-order behavior near the asymptote is conserved, and that the use of this improved action reduces the computing time with respect to the primitive approximation.Comment: 19 pages, RevTex, to appear in J. Chem. Phy

    High order Chin actions in path integral Monte Carlo

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    High order actions proposed by Chin have been used for the first time in path integral Monte Carlo simulations. Contrarily to the Takahashi-Imada action, which is accurate to fourth order only for the trace, the Chin action is fully fourth order, with the additional advantage that the leading fourth and sixth order error coefficients are finely tunable. By optimizing two free parameters entering in the new action we show that the time step error dependence achieved is best fitted with a sixth order law. The computational effort per bead is increased but the total number of beads is greatly reduced, and the efficiency improvement with respect to the primitive approximation is approximately a factor of ten. The Chin action is tested in a one-dimensional harmonic oscillator, a H2_2 drop, and bulk liquid 4^4He. In all cases a sixth-order law is obtained with values of the number of beads that compare well with the pair action approximation in the stringent test of superfluid 4^4He.Comment: 19 pages, 8 figure

    Equation of state of an interacting Bose gas at finite temperature: a Path Integral Monte Carlo study

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    By using exact Path Integral Monte Carlo methods we calculate the equation of state of an interacting Bose gas as a function of temperature both below and above the superfluid transition. The universal character of the equation of state for dilute systems and low temperatures is investigated by modeling the interatomic interactions using different repulsive potentials corresponding to the same s-wave scattering length. The results obtained for the energy and the pressure are compared to the virial expansion for temperatures larger than the critical temperature. At very low temperatures we find agreement with the ground-state energy calculated using the diffusion Monte Carlo method.Comment: 7 pages, 6 figure

    Adsorption and Biodegradation of Aromatic Chemicals by Bacteria Encapsulated in a Hydrophobic Silica Gel

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    An adsorbent silica biogel material was developed via silica gel encapsulation of <i>Pseudomonas</i> sp. NCIB 9816-4, a bacterium that degrades a broad spectrum of aromatic pollutants. The adsorbent matrix was synthesized using silica precursors methyltrimethoxysilane and tetramethoxysilane to maximize the adsorption capacity of the matrix while maintaining a highly networked and porous microstructure. The encapsulated bacteria enhanced the removal rate and capacity of the matrix for an aromatic chemical mixture. Repeated use of the material over four cycles was conducted to demonstrate that the removal capacity could be maintained with combined adsorption and biodegradation. The silica biogel can thus be used extensively without the need for disposal, as a result of continuous biodegradation by the encapsulated bacteria. However, an inverse trend was observed with the ratio of biodegradation to adsorption as a function of log <i>K</i><sub>ow</sub>, suggesting increasing mass-transport limitation for the most hydrophobic chemicals used (log <i>K</i><sub>ow</sub> > 4)

    Predicting partner fitness based on spatial structuring in a light-driven microbial community.

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    Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology (e.g., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed an in-silico model of a synthetic microbial consortia of sucrose-secreting Synechococcus elongatus PCC 7942 and Escherichia coli W. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function
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