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July 2020
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  1. CFN Colloquium (Virtual)

    4 pm, BlueJeans Event - see "more information"

    Hosted by: Deyu Lu

    Autonomous experimentation holds the promise of revolutionizing scientific studies and accelerating materials discovery, through instruments that can explore scientific problems without human intervention. This talk will introduce basic machine-learning concepts, and describe our ongoing development of autonomous experimentation at synchrotron x-ray scattering beamlines. Deep learning (convolutional neural networks) are used to classify x-ray detector images, with performance improving when "physics awareness" is included. To close the autonomous loop, we deploy a general-purpose algorithm that selects high-value experiments to conduct, attempting to minimize both uncertainty and experimental cost. Examples from recent autonomous experiments will be presented, including measuring nanoparticle ordering, combinatorial libraries of block copolymer materials, and realtime photo-thermal processing. *** 1) Web Browser a)https://primetime.bluejeans.com/a2m/live-event/hxuzwcjf *** 2) Laptop paired with room system (Best Experience) a) Dial: bjn.vc or 199.48.152.152 in the room system. b) Go to https://primetime.bluejeans.com/a2m/live-event/hxuzwcjf/room-system/ c) Enter the pairing code displayed on your room system screen into your browser. *** 3) Room System a) Dial: bjn.vc or 199.48.152.152 in the room system. b) Enter Meeting ID: 712959100 and Passcode: 5736 *** 4)Joining via a mobile device? a) Open this link: https://primetime.bluejeans.com/a2m/live-event/hxuzwcjf b) Download the app if you don't have it already. c) Enter event ID : hxuzwcjf *** 5) Phone a) Dial one of the following numbers: +1 (415) 466-7000 (US) b) Enter the participant PIN: 4639035 followed by # to confirm. Joining from outside the US? https://www.bluejeans.com/numbers/primetime-attendees/event?id=hxuzwcjf

  2. CFNS seminar

    4 pm, https://bluejeans.com/494177937

    Hosted by: Jinlong Zhang

    We will present a detailed study of diffractive dijet photoproduction at the recently approved electron-ion collider (EIC) at BNL. Apart from establishing the kinematic reaches for various energies and kinematic cuts, we make precise predictions at next-to-leading order (NLO) of QCD in the most important kinematic variables. We show that the EIC will provide new and more precise information on the diffractive parton density functions (PDFs) in the pomeron than previously obtained at HERA, illuminate the still disputed mechanism of global vs. only resolved-photon factorization breaking, and provide access to diffractive PDFs.

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