BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Information and Statistics in Nuclear Experiment and Theory (ISNET
8)
DTSTART;VALUE=DATE-TIME:20211213T133000Z
DTEND;VALUE=DATE-TIME:20211216T231500Z
DTSTAMP;VALUE=DATE-TIME:20230202T202445Z
UID:indico-event-47@indico.frib.msu.edu
DESCRIPTION:The (hybrid) Information and Statistics in Nuclear Experimen
t and Theory (ISNET 8) conference will be held at the Facility for Rare
Isotope Beams (FRIB) on the campus of Michigan State University (MSU) in E
ast Lansing\, MI USA in Dec.\n\nData is expensive to obtain and comes with
uncertainty. What is the best way to use experimental data in the formula
tion of theoretical models that attempt to explain the results? This works
hop will discuss the use of information theory in the analysis of experime
nts\, and the use of applied mathematics and statistics within the context
of theoretical models dealing with current and future data.\n\n———
————————————————————————
—————————\n\nTopics\n\n• Information theory\n\n• Bay
esian approaches\n\n• Uncertainty quantification\n\n• Statistical corr
elations\n\n• Computational techniques\n\n——————————
————————————————————————
——\n\nKey Questions\n\n• How can we estimate statistical and systema
tic errors on calculated quantities?\n\n• How can the uniqueness and use
fulness of an observable be assessed\, i.e.\, its information content with
respect to current theoretical models?\n\n• How can model-based extrapo
lations be validated and verified?\n\n• What experimental data are cruci
al for better constraining current nuclear models?\n\n• How can statisti
cal tools of nuclear theory help planning future experiments and experimen
tal programs?\n\n———————————————————
—————————————————\n\nBackground\n\nThe s
cientific method uses experimentation to assess theoretical predictions. B
ased on experimental data\, the theory is modified and can be used to guid
e future measurements. The process is then repeated until the theory is ab
le to explain observations\, and the experiment is consistent with theoret
ical predictions. The positive feedback in the loop "experiment-theory-exp
eriment-" can be enhanced if statistical methods and scientific computing
are applied to determine the independence of model parameters\, parameter
uncertainties\, and the errors of calculated observables.\n\nNuclei commun
icate with us through a great variety of observables. Some are easy to mea
sure\; some take a considerable effort and experimental ingenuity. But not
every observable has a potential to impact theoretical developments: some
are more important than the others. Nuclear theory is developing tools to
deliver uncertainty quantification and error analysis for theoretical stu
dies as well as for the assessment of new experimental data. Statistical t
ools can also be used to assess the information content of an observable w
ith respect to current theoretical models\, and evaluate the degree of cor
relation between different observables. Such technologies are essential fo
r providing predictive capability\, estimate uncertainties\, and assess mo
del-based extrapolations - as theoretical models are often applied to enti
rely new nuclear systems and conditions that are not accessible to experim
ent.\n\nhttps://indico.frib.msu.edu/event/47/
LOCATION:NSCL/FRIB 1300 Auditorium or via ZOOM https://msu.zoom.us/j/95027
389061
URL:https://indico.frib.msu.edu/event/47/
END:VEVENT
END:VCALENDAR