Julien Gaboriaud

Auditorium (LAPTh)

 https://indico.in2p3.fr/event/29995/

Locality and symmetry for T-Tbar and gravity

Auditorium (LAPTh)

Speakers: Ruben Monten (Cern)Holography appears to be a fundamental property of gravity. However, even in well-established models like AdS/CFT, the compatibility of this principle with the locality properties of the […]

[Journal Club] Leonard pair

Petit Amphi

Speakers: Nicolas CrampéI will give the definition of the Leonard pair and itsconnection with the Askey-Wilson algebra.The use of these objects is explained in the context of different areas:integrable systems, […]

Ben Heidenreich — UMass Amherst

Speakers: Cristofero Fraser-Taliente (Oxford U.)Abstract: Link: ZoomAnLy: https://sites.google.com/view/anlystringsandfields  https://indico.in2p3.fr/event/32490/

$b->smu^+mu^-$ anomalies: New Physics or QCD effects?

Petit Amphi (LAPTh)

Speakers: Nico Gubernari (Cambridge U., DAMTP)Rare $B$ meson decays are powerful probes for testing the Standard Model (SM). Recent measurements of several observables in $bto s mumu$ transitions have revealed […]

AnLy Meeting in honor of Anamaria Font

Auditorium (LAPTh)

Prof. Anamaria Font (Central University of Venezuela) is a renowned string theorist whose career has recently been recognised thanks to the L’Oréal-UNESCO International Award "For Women in Science" (see here […]

Gilberto Tetlalmatzi-Xolocotzi

Auditorium Vivargent (LAPTh)

Speakers: Gilberto Tetlalmatzi-Xolocotzi (Universität Siegen)https://indico.in2p3.fr/event/32169/

RAQIS 24

LAPTh

Recent Advances in Quantum Integrable Systemshttps://indico.in2p3.fr/event/32579/

Maxim Chernodub

Auditorium Vivargent (LAPTh)

Speakers: Maxim Chernodub (Institut Denis Poisson (Tours, France))https://indico.in2p3.fr/event/32564/

Scattering Transforms in astrophysics, application to components separation

Salle des Sommets (LAPTh)

Speakers: Erwan Allys (LPENS Paris) New statistical descriptions related to the so-called Scattering Transform recently obtained attractive results for several astrophysical applications. These statistics share ideas with convolutional neural networks, but do not require to be learned, allowing for very efficient characterization of non-Gaussian processes from a very small amount of data. In this talk, […]