Hyung Joo Park, N. Duane Loh, Raymond G. Sierra, Christina Y. Hampton, Dmitri Starodub, Andrew V. Martin, Anton Barty, Andrew Aquila, Joachim Schulz, Jan Steinbrener, Robert L. Shoeman, Lukas Lomb, Stephan Kassemeyer, Christoph Bostedt, John Bozek, Sascha W. Epp, Benjamin Erk, Robert Hartmann, Daniel Rolles, Artem Rudenko, Benedikt Rudek, Lutz Foucar, Nils Kimmel, Georg Weidenspointner, Guenter Hauser, Peter Holl, Emanuele Pedersoli, Mengning Liang, Mark S. Hunter, Lars Gumprecht, Nicola Coppola, Cornelia Wunderer, Heinz Graafsma, Filipe R.N.C. Maia, Tomas Ekeberg, Max Hantke, Holger Fleckenstein, Helmut Hirsemann, Karol Nass, Herbert J. Tobias, George R. Farquar, W. Henry Benner, Stefan Hau-Riege, Christian Reich, Andreas Hartmann, Heike Soltau, Stefano Marchesini, Sasa Bajt, Miriam Barthelmess, Lothar Strueder, Joachim Ullrich, Philip Bucksbaum, Matthias Frank, Ilme Schlichting, Henry N. Chapman, Michael J. Bogan, and Veit Elser

DOI: 10.1364/OE.21.028729

Single shot diffraction imaging experiments via X-ray free-electron lasers can generate as many as hundreds of thousands of diffraction patterns of scattering objects. Recovering the real space contrast of a scattering object from these patterns currently requires a reconstruction process with user guidance in a number of steps, introducing severe bottlenecks in data processing. We present a series of measures that replace user guidance with algorithms that reconstruct contrasts in an unsupervised fashion. We demonstrate the feasibility of automating the reconstruction process by generating hundreds of contrasts obtained from soot particle diffraction experiments. Show Partial Abstract