Publications

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We present Poblano v1.0, a Matlab toolbox for solving gradient-based unconstrained optimization problems. Poblano implements three optimization methods (nonlinear conjugate gradients, limited-memory BFGS, and truncated Newton) that require only first order derivative information. In this paper, we describe the Poblano methods, provide numerous examples on how to use Poblano, and present results of Poblano used in solving problems from a standard test collection of unconstrained optimization problems.

The difficulty of calculating the ambient properties of molecular crystals, such as the explosive PETN, has long hampered much needed computational investigations of these materials. One reason for the shortcomings is that the exchange-correlation functionals available for Density Functional Theory (DFT) based calculations do not correctly describe the weak intermolecular van der Waals' forces present in molecular crystals. However, this weak interaction also poses other challenges for the computational schemes used. We will discuss these issues in the context of calculations of lattice constants and structure of PETN with a number of different functionals, and also discuss if these limitations can be circumvented for studies at non-ambient conditions.

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This presentation discusses the following topics: (1) Red Sky Background; (2) 3D Torus Interconnect Concepts; (3) Difficulties of Torus in IB; (4) New Routing Code for IB a 3D Torus; (5) Red Sky 3D Torus Implementation; and (6) Managing a Large IB Machine. Computing at Sandia: (1) Capability Computing - Designed for scaling of single large runs, Usually proprietary for maximum performance, and Red Storm is Sandia's current capability machine; (2) Capacity Computing - Computing for the masses, 100s of jobs and 100s of users, Extreme reliability required, Flexibility for changing workload, Thunderbird will be decommissioned this quarter, Red Sky is our future capacity computing platform, and Red Mesa machine for National Renewable Energy Lab. Red Sky main themes are: (1) Cheaper - 5X capacity of Tbird at 2/3 the cost, Substantially cheaper per flop than our last large capacity machine purchase; (2) Leaner - Lower operational costs, Three security environments via modular fabric, Expandable, upgradeable, extensible, and Designed for 6yr. life cycle; and (3) Greener - 15% less power-1/6th power per flop, 40% less water-5M gallons saved annually, 10X better cooling efficiency, and 4x denser footprint.

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Constructing high-fidelity control pulses that are robust to control and system/environment fluctuations is a crucial objective for quantum information processing (QIP). We combine dynamical decoupling (DD) with optimal control (OC) to identify control pulses that achieve this objective numerically. Previous DD work has shown that general errors up to (but not including) third order can be removed from {pi}- and {pi}/2-pulses without concatenation. By systematically integrating DD and OC, we are able to increase pulse fidelity beyond this limit. Our hybrid method of quantum control incorporates a newly-developed algorithm for robust OC, providing a nested DD-OC approach to generate robust controls. Motivated by solid-state QIP, we also incorporate relevant experimental constraints into this DD-OC formalism. To demonstrate the advantage of our approach, the resulting quantum controls are compared to previous DD results in open and uncertain model systems.

Alkali nitrate eutectic mixtures are finding application as industrial heat transfer fluids in concentrated solar power generation systems. An important property for such applications is the melting point, or phase coexistence temperature. We have computed melting points for lithium, sodium and potassium nitrate from molecular dynamics simulations using a recently developed method, which uses thermodynamic integration to compute the free energy difference between the solid and liquid phases. The computed melting point for NaNO3 was within 15K of its experimental value, while for LiNO3 and KNO3, the computed melting points were within 100K of the experimental values [4]. We are currently extending the approach to calculate melting temperatures for binary mixtures of lithium and sodium nitrate.

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