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SUMMARY:Constraining DVCS Compton Form Factors Using Lattice QCD informed 
 Neural Network
DTSTART;VALUE=DATE-TIME:20261011T084000Z
DTEND;VALUE=DATE-TIME:20261011T085500Z
DTSTAMP;VALUE=DATE-TIME:20261005T035320Z
UID:indico-contribution-2862@indico.itp.ac.cn
DESCRIPTION:Speakers: 源源 黄 (南京师范大学)\nThe lattice QCD cal
 culation of generalized form factors are exploited to determine the subtra
 ction\nconstants through all order dispersion relations of Deeply Virtual 
 Compton Scattering (DVCS). The\nleading order relation is found to constra
 in significantly the real part of the Compton Form Factors\n(CFFs)\, and t
 he higher order one reduces considerably both the real and imaginary part 
 of CFFs\nin a global analysis of proton data. This is realized by a synthe
 sis of the DVCS data and LQCD\ncalculations within a neural network framew
 ork\, whose architecture is specifically designed for a\nreliable extrapol
 ation to unmeasured kinematic regime. By leveraging dispersion relations b
 eyond\nleading order\, our framework allows for adding higher moments of g
 eneralized parton distributions\nfrom LQCD into the extraction of CFFs fro
 m DVCS data.\n\nhttps://indico.itp.ac.cn/event/437/contributions/2862/
LOCATION:会议楼2 CXII103
URL:https://indico.itp.ac.cn/event/437/contributions/2862/
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