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Speakers and poster presenters must submit abstracts of their presentations. You must register before submitting an abstract and/or presenting a poster.

Abstract Submission Information

SPEAKERS:

Speakers are encouraged to submit abstracts of their presentations.

All speakers must register before submitting an abstract.

POSTER PARTICIPANTS:

Poster participants must submit an abstract in order to receive a poster display spot. 

All poster participants must register for the event before submitting an abstract.

REGISTRATIONS AND ABSTRACT SUBMISSIONS MUST BE COMPLETE BY WEDNESDAY, SEPTEMBER 20.

Participating with a poster presentation is a great way to share your latest research advances and find out what's new from other users. 

Check back later for a list of 2017 Abstracts!

DIRECTIONS - Please read these directions before submitting an abstract:

  1. Abstracts must be submitted in .PDF format (Maximum File Size: 4 MB).
  2. Please save your file title as "LastName,FirstName,AbstractType." The four different abstract types are: Plenary, Invited, Oral, Poster.
  3. Abstracts are limited to 1 page and should be formatted based on the SSRL/LCLS Users' Meeting Abstract Template.
  4. Visit the Abstract Submission Form to submit your abstract.
       
WorkshopDateTimeLocationNameTitleAbstract
Accelerator Performance DevelopmentsSeptember 271:30 PMSUSB 053-2002 BerryessaAxel BrachmannLCLS Accelerator PerformanceThis talk will review the current LCLS Accelerator performance. We will discuss general KPI’s such as electron and x-ray pulse energy, photon energy reach, beam stability and beam availability. In addition we will summarize the currently available beam delivery modes beyond the standard parameter set, such as dual bunch/dual energy beams and polarization control. Also, an overview of new developments will be given and their timeline for routine availability for user experiments. This includes new capabilities, diagnostics systems and accelerator control applications.Through the ongoing Mission Readiness program, many LCLS Accelerator systems will be upgraded and modernized. We will review the scope of this program and its impact on LCLS beam delivery.The current normal conducting copper accelerator will remain an important part of the future LCLS-I/II facility. We will present our vision how the copper linac will be integrated into the overall facility to provide high energy pulse energy beams in the hard x-ray energy range.
Accelerator Performance DevelopmentsSeptember 272:10 PMSUSB 053-2002 BerryessaAlberto LutmanX-ray multi-pulses at the LCLSX-ray free-electron lasers (XFEL) are the brightest source of x-rays, with a peak brightness ten orders of magnitude higher than conventional synchrotron radiation sources. Several FEL schemes have been developed to enable double (or multiple) X-ray pulses, covering different ranges of delays, color separation and pulse durations. Fresh-slice split undulator schemes use distinct undulator sections to produce high-power short pulses with delays up to 1 ps, providing independent customizability of each pulse in terms of polarization, pointing. However, each pulse must reach saturation within a subsection of the entire undulator line, making this scheme particularly suitable for Soft X-rays. Split undulator schemes will enable arbitrary color separation with variable gap undulators. Alternatively, two distinct electron bunches can be extracted from the cathode and lase using the full undulator line. The Twin-bunch scheme produces high-power double pulses at any available wavelength with delays up to 125 fs from two electron bunches accelerated in the same radiofrequency bucket and wavelength separation up to 3% at soft X-rays and 1% at hard X-rays. The Two-bucket scheme provides long delays from 350 ps to several hundreds of nanoseconds in 350 ps steps by accelerating two electron bunches in distinct radiofrequency buckets. Performance, advantages and drawbacks of each scheme will be discussed.
Accelerator Performance DevelopmentsSeptember 273:20 PMSUSB 053-2002 BerryessaAgostino MarinelliThe XLEAP Project (X-Ray Laser-Enhanced Attosecond Pulse generation)Time-resolved experiments at the attosecond scale hold great promise for understanding ultrafast electron dynamics in molecules, as well as the role of electron coherence in chemistry. In the recent past, much progress has been made in using X-ray free-electron lasers (X-FELs) to visualize atomic motion at the tens of femtosecond scale. At the same time, table-top lasers have been operated at the attosecond scale and successfully employed in scientific experiments. However, the femtosecond barrier has not yet been broken at X-ray free-electron lasers, hindering our ability to understand the fundamental motion of electrons.In my talk I will describe the XLEAP project, aimed at generating attosecond pulses in the soft-X-ray region at LCLS. I will discuss the physics of laser-enhanced FELs and the effect of bandwidth broadening and self-compression in this FEL mode. Finally I will describe our plans for the transition from FEL R&D to science and discuss the roadmap to attosecond science with LCLS-II.
Computational Workflows for X-Ray ScienceSeptember 298:00 AMSUSB 053-1350 TrinityAlexander HexemerTowards Real-Time Analysis of X-ray DataThe advent of high brightness sources, fast detectors and the increasing need of time-resolved experiments at X-ray facilities has created an unprecedented data deluge, and has triggered the need to combine X-ray research, mathematics and computer science. The eventual dream must be near real-time data analysis and feedback to scientists during experiments. To achieve such a goal, it is necessary to implement a complete data curation pipeline, starting with data reduction and simple analysis as close as possible to the detector. This process is followed by a fast pipeline to move the resulting data and metadata into a database at a large computing cluster for further and more detailed analysis. A combination of fast hardware and the fastest algorithms is crucial to reach near real-time. I will present a variety of our latest math algorithms developed under CAMERA to highlight the potential speed-up that can be achieved with new developments. A user facility faces the additional challenge of presenting the analysis framework in a user-friendly environment to allow the scientist to focus on their experiments and maximize the science output. To step closer to that goal we have developed a plug-in based toolkit, XI-CAM, under CAMERA that connects algorithms and allows execution on fast clusters and supercomputers. We have developed a variety of high performance plug-ins and analysis tools in collaboration with scientists from around the country such as SSRL, APS and NSLS II to support DOE user facility sciences.
Computational Workflows for X-Ray ScienceSeptember 298:50 AMSUSB 053-1350 TrinityAmedeo PerazzoData Analytics at the Exascale for Free Electron LasersDetector data rates at light sources are advancing exponentially: LCLS will increase its data throughput by three orders of magnitude by 2025. In the ExaFEL project we identify a grand challenge: enabling new photon science from the LCLS requiring burst computational intensities in the exascale range. As an end-to-end challenge problem, XFEL applications require significant orchestration of compute, network, and storage resources and present a model use case for ESnet R&D into network operating systems. Leveraging a successful existing collaboration between LCLS and NERSC we present a plan for broadening the impact of exascale in related data analysis workflows.
Computational Workflows for X-Ray ScienceSeptember 299:20 AMSUSB 053-1350 TrinityBenedikt DaurerNanosurveyor: A Framework for Real-time Data ProcessingRecent developments on both development of accelerator-based sources and new computational capabilities have made it possible to study the three-dimensional structure of material at high-resolution using coherent diffractive imaging methods such as ptychography. However, the processing pipeline for such methods typically involve multiple steps including data collection, data reduction, writing to file, pre-processing and image reconstruction that are usually carried out individually. Here we present "Nanosurveyor", a real-time framework data processing that automates all necessary processing steps involved and makes high-resolution imaging with immediate feedback available. We describe the streamlined processing pipeline of ptychography data analysis.
Computational Workflows for X-Ray ScienceSeptember 299:50 AMSUSB 053-1350 TrinityApurva MehtaMore Science through Less Data: Towards Automated, Unsupervised and Machine Learned Work-flowsOver the last three decades, there has been an explosive rise in the amount of data collected at the National User Facilities. This exponential rise has transformed materials and chemical sciences by enabling a move away from investigations of simple single-phase materials towards a deeper understanding of hierarchically complex materials and devices under “real-world” operation.However, assessment of data quality as well extraction of scientific information from it, currently, relies heavily on active human interaction; but humans cannot keep up with the accelerating pace of data collection. Isolation of data collection from data assessment has resulted in poorer and scientifically less relevant data; and in extreme cases forced recollection of data. Isolation of data acquisition from analysis, curation and visualization, in essence absence of integration of data centric tools with data acquisition, has significantly hampered the rate of new discoveries. This major shortcoming of current data management paradigm was extensively explored in a 2015 DOE workshop and the findings highlighted in a report titled, “Management, Visualization, and Analysis of Experimental and Observational Data (EOD) - The Convergence of Data and Computing”.Herein, I will describe the work that a team of us has been doing over the last year to address this challenge through development of an approach that makes routine data analysis automatic and instantaneous and allows real time visualization that highlights not only data quality but also high-level scientific information contained in it. We anticipate our approach to become a starting point for a sophisticated decision-tree that automatically optimizes data quality, extracts scientific information contained in it in real time, and suggests the highest impact follow-up measurement, and thereby frees researchers to focus their expertise where they are truly needed.
Computational Workflows for X-Ray ScienceSeptember 2910:50 AMSUSB 053-1350 TrinityRichard SandbergTools for Real-time Adaptive Acceleration of Dynamic Compression Science at Light SourcesAnalyzing and extracting scientific knowledge from modern light source experiments has become the rate-limiting step in the scientific process. We propose to accelerate knowledge-discovery from experimental scientific facilities by combining computer and statistical science to produce an adaptive methodology and toolset that will analyze data and augment a scientist's decision-making so that the scientist can optimize experiments in real time. We will develop this capability in the context of dynamic compression experiments from X-ray light sources (MEC-LCLS, DCS), an area that is currently in the midst of substantial increases in the rate of data generation. We will describe our development of a data science focused information science and technology (IS&T) toolset that is optimized for and will revolutionize dynamic compression science experiments using X-ray user facilities. Furthermore, this work will produce many reusable components that can be applied to multiple scientific domains. When achieved, our approach will allow scientists to elevate their focus above the mundane tasks required for experiment completion to that of making strategic scientific decisions.
Computational Workflows for X-Ray ScienceSeptember 2911:20 AMSUSB 053-1350 TrinityThomas CaswellHow I learned to stop worrying about formats and love interfacesAt NSLS-II we have developed the bluesky suite of tools for data acquisition, management, and access. One of the core abstractions is a light-weight schema for describing experimental and derived data. The schema clearly encodes the underlying data, metadata about hardware configuration, and metadata about user-intent in a machine-readable way.This talk will briefly cover the motivation behind the schema, the tools we have developed at NSLS-II, and how it can be used to provide a uniform interface to diverse experimental data.
Plenary SpeakerSeptember 281:15 PMSUSB 053-Panofsky AuditoriumKathryn HastieStructural basis for antibody-mediated neutralization of Lassa virusDownload Abstract
    Wenxin TangDeveloping Time Resolved Spin-Polarized LEEMDownload Abstract
Advanced X-ray Spectroscopy at SLAC: From Theory to Experimental ConceptsSeptember 294:30 PMSUSB 053-Panofsky AuditoriumYu ZhangNonlinear X-ray Spectroscopy of Molecules---Simulation Methods, Applications and ChallengesDownload Abstract
Plenary SpeakerSeptember 281:45 PMSUSB 053-Panofsky AuditoriumSuhas KumarUsing a Synchrotron to Understand Nanoelectronics and Design Futuristic ComputersDownload Abstract
Detectors for Photon ScienceSeptember 298:30 AM051 Kavli AuditoriumEliane LessnerAccelerator and Detector Research program updates 
Detectors for Photon ScienceSeptember 298:50 AM051 Kavli AuditoriumPeter DenesVFCCD – a soft spot for X-rays at LCLS-II 
Detectors for Photon ScienceSeptember 299:20 AM051 Kavli AuditoriumFarah FahimFLORA: a large dynamic range and continuous fast readout rate detector 
Detectors for Photon ScienceSeptember 299:50 AM051 Kavli AuditoriumAngelo DragoneePix detectors for LCLS-II 
Detectors for Photon ScienceSeptember 2910:45 AM051 Kavli AuditoriumKelsey MorganTES: a high efficiency, high resolution, energy-dispersive area detector 
Detectors for Photon ScienceSeptember 2911:15 AM051 Kavli AuditoriumDale LiBuilding a TES Spectrometer for LCLS-II 
Feature Extraction for LCLS-IISeptember 271:00 PM051 Kavli AuditoriumChristopher O’GradyLCLS-II Data Reduction: Motivation and DirectionsLCLS-II is projected to have data volumes of 200GB/s in 2020, making storage of the full data too costly. This talk gives an overview of approaches being taken to reduce this data volume, with the goal being a factor of 10 reduction.
Feature Extraction for LCLS-IISeptember 271:25 PM051 Kavli AuditoriumTim Van DrielRedundant data reduction for X-ray diffuse scatteringFull data reduction of Time-resolved diffuse scattering relies on a number of experiment-specific parameters. Optimal data reduction often requires tweaking parameters and doing multiple passes at the data reduction. In order to accommodate single pass data reduction for high data-rate experiments, we propose to reduce the data with two independent schemes. By reducing the data following two distinct redundant schemes, the single pass reduction will be less likely to render the measured data useless.
Feature Extraction for LCLS-IISeptember 271:50 PM051 Kavli AuditoriumNick SauterSerial Crystallography Data Reduction with Convolutional Neural NetworksSupervised machine learning, in the form of convolutional neural networks, may be one approach to the filtering of high data-rate crystallographic diffraction images, wherein only those events with noticeable Bragg spots are retained for data analysis. Initial attempts were successful at classifying images from CSPAD and Rayonix detectors, especially so for those trials where the training and test data were collected from the same instrument type. Sources of variance between different data sets will be qualitatively examined.
Feature Extraction for LCLS-IISeptember 272:10 PM051 Kavli AuditoriumAnton BartyOpportunities and Challenges of High Data Rate Serial Crystallography 
Feature Extraction for LCLS-IISeptember 272:35 PM051 Kavli AuditoriumChuck YoonSFX/SPI feature extractionWith the massive amount of data that will be generated with LCLS2 repetition rates, feature extraction is needed to keep the disk storage and data analysis down to a manageable level on large computing clusters. This talk will report on some of the on-going work in strategies to make the most use of the limited disk storage space we will have for LCLS2 including vetoing, feature extraction and compression for SFX/SPI experiments. Users interested in SFX/SPI are encouraged to attend to voice their ideas.
Feature Extraction for LCLS-IISeptember 273:15 PM051 Kavli AuditoriumClemens WeningerTechnology Choices for the LCLS II Data Reduction Pipeline and Data FormatsWe are evaluating different technology choices for fast realtime data processing at very high data rates to reduce the data volume by extracting the import features. It will also briefly touch upon the data format for LCLS II and the challenge or storing large amounts of complex data.
Feature Extraction for LCLS-IISeptember 273:40 PM051 Kavli AuditoriumMikhail DubrovinLossless compression of LCLS dataLossless compression of LCLS detector data is discussed. We considered a few standard and home-made compression algorithms against CSPAD raw and calibrated data in order to achieve maximal compression factor. We also calculated our data entropy and estimated theoretical limit on compression factor. In summary, the most optimistic compression factor for LCLS detector data is estimated in the range 2.2-2.5, that is not sufficient to beat a few orders of LCLS-II data flow increase.
Feature Extraction for LCLS-IISeptember 274:00 PM051 Kavli AuditoriumSilke NelsonAutomatic Beam Center Finding (and Beyond)For various types of data reduction it is important to know the beam center on the area detector. Artifacts resulting from the experiment setup or detector readout can make that hard. We will present a multi step approach to find the beam center in various experimental conditions that can run user input free in many circumstances. Next steps on the path to determine data reduction parameters in a manageable, but reliable way will be pointed out.
Feature Extraction for LCLS-IISeptember 274:25 PM051 Kavli AuditoriumSioan ZoharFirmware Processing of LCLS-II Timetool DataEvent building and time stamping of x-ray pulses has proven invaluable in resolving femtosecond dynamics by providing the ability to temporally re-bin events in post processing. In LCLS-I, femtosecond time-stamps for rebinning are calculated using computer based matched finite impulse response filters to images of overlapping laser/x-ray beams reflected from a non-linear material. Here, we show how the demand for increased data processing bandwidth accompanying the rep-rate increase from 120 Hz in LCLS-I to 100 KHz in LCLS-II can be achieved by implementing a number of hardware accelerated algorithms.
First Experiments for LCLS-IISeptember 2711:30 AM051 Kavli AuditoriumRobert SchoenleinEarly Science ApproachSlides
First Experiments for LCLS-IISeptember 279:15 AM051 Kavli AuditoriumMike MinittiNEH 1.1 - Scope, design status, delivery date, componentsSlides
First Experiments for LCLS-IISeptember 2711:00 AM051 Kavli AuditoriumGeorgi DakovskiNEH 2.2 - Scope, design status, delivery date, componentsSlides
Coherent Diffractive Imaging at LCLSSeptember 293:30 PM051 Kavli AuditoriumRuslan KurtaA fluctuation x-ray scattering approach to single particle imaging with XFELsSlides