Atomic radius and charge parameter uncertainty in biomolecular solvation energy calculations

Atomic radii and charges are two major parameters used in implicit solvent electrostatics and energy calculations. The optimization problem for charges and radii is under-determined, leading to uncertainty in the values of these parameters and in the results of solvation energy calculations using these parameters. This paper presents a new method for quantifying this uncertainty in implicit solvation calculations of small molecules using surrogate models based on generalized polynomial chaos (gPC) expansions. There are relatively few atom types used to specify radii parameters in implicit solvation calculations; therefore, surrogate models for these low-dimensional spaces could be constructed using least-squares fitting. However, there are many more types of atomic charges; therefore, construction of surrogate models for the charge parameter space requires compressed sensing combined with an iterative rotation method to enhance problem sparsity. We demonstrate the application of the method by presenting results for the uncertainties in small molecule solvation energies based on these approaches. The method presented in this paper is a promising approach for efficiently quantifying uncertainty in a wide range of force field parameterization problems, including those beyond continuum solvation calculations.The intent of this study is to provide a way for developers of implicit solvent model parameter sets to understand the sensitivity of their target properties (solvation energy) on underlying choices for solute radius and charge parameters

Group Leaders Optimization Algorithm

We present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique which is designed into a group architecture. To demonstrate the efficiency of the method, a standard suite of single and multidimensional optimization functions along with the energies and the geometric structures of Lennard-Jones clusters are given as well as the application of the algorithm on quantum circuit design problems. We show that as an improvement over previous methods, the algorithm scales as N^2.5 for the Lennard-Jones clusters of N-particles. In addition, an efficient circuit design is shown for two qubit Grover search algorithm which is a quantum algorithm providing quadratic speed-up over the classical counterpart

New Mechanism for Electronic Energy Relaxation in Nanocrystals

The low-frequency vibrational spectrum of an isolated nanometer-scale solid differs dramatically from that of a bulk crystal, causing the decay of a localized electronic state by phonon emission to be inhibited. We show, however, that an electron can also interact with the rigid translational motion of a nanocrystal. The form of the coupling is dictated by the equivalence principle and is independent of the ordinary electron-phonon interaction. We calculate the rate of nonradiative energy relaxation provided by this mechanism and establish its experimental observability.Comment: 4 pages, Submitted to Physical Review

Ill-posedness of degenerate dispersive equations

In this article we provide numerical and analytical evidence that some degenerate dispersive partial differential equations are ill-posed. Specifically we study the K(2,2) equation $u_t = (u^2)_{xxx} + (u^2)_{x}$ and the "degenerate Airy" equation $u_t = 2 u u_{xxx}$. For K(2,2) our results are computational in nature: we conduct a series of numerical simulations which demonstrate that data which is very small in $H^2$ can be of unit size at a fixed time which is independent of the data's size. For the degenerate Airy equation, our results are fully rigorous: we prove the existence of a compactly supported self-similar solution which, when combined with certain scaling invariances, implies ill-posedness (also in $H^2$)

Topology of Knotted Optical Vortices

Optical vortices as topological objects exist ubiquitously in nature. In this paper, by making use of the $\phi$-mapping topological current theory, we investigate the topology in the closed and knotted optical vortices. The topological inner structure of the optical vortices are obtained, and the linking of the knotted optical vortices is also given.Comment: 11 pages, no figures, accepted by Commun. Theor. Phys. (Beijing, P. R. China

Determination of differential emission measure from solar extreme ultraviolet images

The Atmospheric Imaging Assembly (AIA) on board the Solar Dynamic Observatory (SDO) has been providing high-cadence, high-resolution, full-disk UV-visible/extreme ultraviolet (EUV) images since 2010, with the best time coverage among all the solar missions. A number of codes have been developed to extract plasma differential emission measures (DEMs) from AIA images. Although widely used, they cannot effectively constrain the DEM at flaring temperatures with AIA data alone. This often results in much higher X-ray fluxes than observed. One way to solve the problem is by adding more constraint from other data sets (such as soft X-ray images and fluxes). However, the spatial information of plasma DEMs are lost in many cases. In this Letter, we present a different approach to constrain the DEMs. We tested the sparse inversion code and show that the default settings reproduce X-ray fluxes that could be too high. Based on the tests with both simulated and observed AIA data, we provided recommended settings of basis functions and tolerances. The new DEM solutions derived from AIA images alone are much more consistent with (thermal) X-ray observations, and provide valuable information by mapping the thermal plasma from ~0.3 to ~30 MK. Such improvement is a key step in understanding the nature of individual X-ray sources, and particularly important for studies of flare initiation

Tomographic reconstruction with a generative adversarial network

This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The algorithm uses a generative adversarial network (GAN) to solve the inverse of the Radon transform directly. It works for independent sinograms without additional training steps. The GAN has been developed to fit the input sinogram with the model sinogram generated from the predicted reconstruction. Good quality reconstructions can be obtained during the minimization of the fitting errors. The reconstruction is a self-training procedure based on the physics model, instead of on training data. The algorithm showed significant improvements in the reconstruction accuracy, especially for missing-wedge tomography acquired at less than 180° rotational range. It was also validated by reconstructing a missing-wedge X-ray ptychographic tomography (PXCT) data set of a macroporous zeolite particle, for which only 51 projections over 70° could be collected. The GANrec recovered the 3D pore structure with reasonable quality for further analysis. This reconstruction concept can work universally for most of the ill-posed inverse problems if the forward model is well defined, such as phase retrieval of in-line phase-contrast imaging

XML-VM: An XML-Based Grid Computing Middleware

This paper describes a novel distributing computing middleware named XML-VM. Its architecture is inspired by the \u2018Grid Computing\u2019 paradigm. The proposed system improves many characteristics of previous Grid systems, in particular the description of the distributed computation, the distribution of the code and the execution times. XML is a markup language commonly used to interchange arbitrary data over the Internet. The idea behind this work is to use XML to describe algorithms; XML documents are distributed by means of XML-RPC, interpreted and executed using virtual machines. XML-VM is an assembly-like language, coded in XML. Parsing of XML-VM programs is performed with a fast SAX parser for JAVA. XML-VM interpreter is coded in JAVA. Several algorithms are written in XML-VM and executed in a distributed environment. Representative experimental results are reported

Uncorrelated Volatile Behavior during the 2011 Apparition of Comet C/2009 P1 Garradd

The High Resolution Instrument Infrared Spectrometer (HRI-IR) on board the Deep Impact Flyby spacecraft detected H2O, CO2, and CO in the coma of the dynamically young Oort Cloud comet C/2009 P1 (Garradd) post-perihelion at a heliocentric distance of 2 AU. Production rates were derived for the parent volatiles, Q_(H2O) = 4.6 ± 0.8 × 10^(28), Q_(CO2) = 3.9 ± 0.7 × 10^(27), and Q_(CO) = 2.9 ± 0.8 × 10^(28) molecules s^(–1), and are consistent with the trends seen by other observers and within the error bars of measurements acquired during a similar time period. When compiled with other observations of Garradd's dominant volatiles, unexpected behavior was seen in the release of CO. Garradd's H_2O outgassing, increasing and peaking pre-perihelion and then steadily decreasing, is more typical than that of CO, which monotonically increased throughout the entire apparition. Due to the temporal asymmetry in volatile release, Garradd exhibited the highest CO to H_2O abundance ratio ever observed for any comet inside the water snow line at ~60% during the HRI-IR observations. Also, the HRI-IR made the only direct measurement of CO_2, giving a typical cometary abundance ratio of CO_2 to H_2O of 8% but, with only one measurement, no sense of how it varied with orbital position