Crystal diffraction prediction and partiality estimation using Gaussian basis functions

被引:0
|
作者
Brehm, Wolfgang [1 ,2 ]
White, Thomas [1 ]
Chapman, Henry N. [1 ,2 ,3 ]
机构
[1] Deutsch Elektronen Synchrotron DESY, Ctr Free Electron Laser Sci CFEL, Notkestr 85, D-22607 Hamburg, Germany
[2] Univ Hamburg, Dept Phys, Luruper Chaussee 149, D-22761 Hamburg, Germany
[3] Hamburg Ctr Ultrafast Imaging, Luruper Chaussee 149, D-22761 Hamburg, Germany
关键词
partiality estimation; diffraction prediction; merging; serial snapshot crystallography; SYNCHROTRON X-RADIATION; SERIAL FEMTOSECOND CRYSTALLOGRAPHY; REFLECTING RANGE; POST-REFINEMENT; PROFILE;
D O I
10.1107/S2053273323000682
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The recent diversification of macromolecular crystallographic experiments including the use of pink beams, convergent electron diffraction and serial snapshot crystallography has shown the limitations of using the Laue equations for diffraction prediction. This article gives a computationally efficient way of calculating approximate crystal diffraction patterns given varying distributions of the incoming beam, crystal shapes and other potentially hidden parameters. This approach models each pixel of a diffraction pattern and improves data processing of integrated peak intensities by enabling the correction of partially recorded reflections. The fundamental idea is to express the distributions as weighted sums of Gaussian functions. The approach is demonstrated on serial femtosecond crystallography data sets, showing a significant decrease in the required number of patterns to refine a structure to a given error.
引用
收藏
页码:145 / 162
页数:18
相关论文
共 50 条
  • [21] Prediction of the optical properties in photonic crystal fiber using support vector machine based on radial basis functions
    Li, Hongwei
    Chen, Hailiang
    Li, Yuxin
    Chen, Qiang
    Fan, Xiaoya
    Li, Shuguang
    Ma, Mingjian
    OPTIK, 2023, 275
  • [22] PROBABILITY DENSITY-ESTIMATION USING ELLIPTIC BASIS FUNCTIONS
    JOHNSTON, LPM
    KRAMER, MA
    AICHE JOURNAL, 1994, 40 (10) : 1639 - 1649
  • [23] Prediction of sound transmission through plates using spectral Gaussian basis functions and application to plates with periodic acoustic black holes
    Yang, Yi
    Kingan, Michael
    Mace, Brian
    JOURNAL OF SOUND AND VIBRATION, 2025, 605
  • [24] Molecular integrals over gaussian basis functions
    Gill, PMW
    ADVANCES IN QUANTUM CHEMISTRY, VOL 25, 1994, 25 : 141 - 205
  • [25] Modal-based phase retrieval using Gaussian radial basis functions
    Piscaer, P. J.
    Gupta, A.
    Soloviev, O.
    Verhaegen, M.
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2018, 35 (07) : 1233 - 1242
  • [26] APPROXIMATION OF BACKWARD HEAT CONDUCTION PROBLEM USING GAUSSIAN RADIAL BASIS FUNCTIONS
    Abbasbandy, S.
    Azarnavid, B.
    Hashim, I.
    Alsaedi, A.
    UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN-SERIES A-APPLIED MATHEMATICS AND PHYSICS, 2014, 76 (04): : 67 - 76
  • [27] STABLE COMPUTATIONS WITH GAUSSIAN RADIAL BASIS FUNCTIONS
    Fornberg, Bengt
    Larsson, Elisabeth
    Flyer, Natasha
    SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2011, 33 (02): : 869 - 892
  • [28] Bayesian smoothing with Gaussian processes using Fourier basis functions in the spectralGP package
    Paciorek, Christopher J.
    JOURNAL OF STATISTICAL SOFTWARE, 2007, 19 (02): : 1 - 38
  • [29] Gaussian radial basis functions for simulation metamodeling
    Shin, MY
    Sargent, RG
    Goel, AL
    PROCEEDINGS OF THE 2002 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2002, : 483 - 488
  • [30] Approximation of input-output maps using Gaussian radial basis functions
    Sandberg, IW
    STABILITY AND CONTROL OF DYNAMICAL SYSTEMS WITH APPLICATIONS: A TRIBUTE TO ANTHONY N. MICHEL, 2003, : 155 - 166