activity
20062024
most citedPaving the Way Towards Precision Physics in Saturation Studies Through Exclusive Diffractive Light Neutral Vector Meson Production

83 citations · 481 across the 28 of their papers we have counts for

collaborators

27 papers

hep-ph2024

Gluon tomography through diffractive processes in a saturation framework

Renaud Boussarie, Michael Fucilla, Andrey V. Grabovsky +3

We discuss a series of results aimed at bringing saturation physics and gluon tomography into an era of precision. In particular, the NLO treatment of diffractive: 1) exclusive dij…

hep-ph2023

Diffractive single and di-hadron production at the NLO in a saturation framework

Michael Fucilla, Andrey Grabovsky, Emilie Li +2

Motivated by the need to increase the precision of theoretical predictions to test saturation physics at both the LHC and the EIC, we compute the cross-sections for the diffractive…

hep-ph2023★ 17 cited

Diffractive single hadron production in a saturation framework at the NLO

Michael Fucilla, Andrey Grabovsky, Emilie Li +2

We calculate the cross-sections of diffractive single hadron photo- or electroproduction with large , on a nucleon or a nucleus in the shockwave formalism. We use the hybrid f…

hep-ph2022★ 27 cited

NLO computation of diffractive di-hadron production in a saturation framework

Michael Fucilla, Andrey V. Grabovsky, Emilie Li +2

The cross-sections of diffractive double hadron photo- or electroproduction with large , on a nucleon or a nucleus, are calculated to NLO accuracy. A hybrid formalism mixing c…

hep-ph2022

Diffractive di-hadron production at NLO within the shockwave formalism

Michael Fucilla, Andrey V. Grabovsky, Lech Szymanowski +2

We compute the next-leading-order cross-sections for diffractive electro- or photoproduction of a pair of hadrons with large , out of a nucleus or a nucleon. A hybrid factoriz…

cs.NE2022★ 1 cited

Bio-inspired Machine Learning: programmed death and replication

Andrey Grabovsky, Vitaly Vanchurin

We analyze algorithmic and computational aspects of biological phenomena, such as replication and programmed death, in the context of machine learning. We use two different measure…