Los Alamos and CAMERA scientists:

Toward Rapid Ptychographic Reconstruction:


The BlackBEAR (Beamline Experiment Analysis and Reconstruction)  project at Los Alamos National Laboratory is aimed at developing a capability for rapid ptychographic reconstruction and beam characterization of coherent light source experiments at the Linac Coherent Light Source (LCLS) at SLAC National Accelerator Laboratory.  Working together, LANL and CAMERA (The Center for Advanced Mathematics for Energy Research Applications) scientists have ported and customized the CAMERA SHARP ptychography software for fast reconstruction of Los Alamos experiment data and have also been experimenting with beam blocks, beam attenuators and various test samples. The goal of the project is to understand how LANL can utilize both cutting edge software and beamline supports, assess the current state-of the art in these areas, and determine where we need to make advances for future experiments of interest to LANL.




       In the near future, LANL scientists plan to incorporate position refinement into the SHARP code to handle beam jitter, as well make modifications that will allow pixels to “float” to cope with the spaces between detector pads and beam blocks and incorporate a center parameter to align data.


The Team: 

   On the LANL side, the current BlackBEAR team consists of PIs Richard Sandberg from the Center for Integrated Nanotechnologies (MPA-CINT) and James Hunter Applied Engineering Technology (AET).  Additional team members on the project are:  Ben Pound and Dennis Trujillo from MPA-CINT,  Bill Ward from AET, Nina Weiss Bernstein from Intelligence and Space Research (ISR), Christine Sweeney and Chris Sewell from Computer, Computational and Statistical Sciences (CCS),  and Kevin Mertes from Chemistry (C) division. SLAC team members include Mark Hunter and Matt Seaberg of the LCLS.

    CAMERA scientists tasked to work with LANL include Hari Krishnan, Stefano Marchesini, David Shapiro, and Talita Perciano.

A successful first step occurred during a recent LANL-LCLS experiment. LANL preprocessing (included summing the images at each position, normalizing to the beam energy (FEEGasDetEnergy), including noise reduction, and customizing for geometry) and efficient use of SHARP led to reconstructions at the LCLS.  The current workflow consists of copying over data translated into CXI format to the  LANL cluster and doing preprocessing at LANL, then running SHARP at LANL.