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20242026
most citedRényi entanglement entropy of spin chain with Generative Neural Networks

5 citations · 6 across the 15 of their papers we have counts for

collaborators

17 papers

hep-ph2026

CGC Fit to HERA DIS and Forward Hadron Production in p+p Collisions

Piotr Korcyl, Truong My Hau Le, Farid Salazar +1

Many experiments have provided possible hints of gluon saturation, including geometric scaling in deep inelastic scattering (DIS) at HERA, the suppression of forward particle yield…

hep-ph2026

Scheme Transformations in Non-Linear QCD Evolution: Towards a Stable NLO BK Equation

Renaud Boussarie, Paul Caucal, Piotr Korcyl +1

High-energy QCD evolution at NLO suffers from large collinear logarithms that make the perturbative expansion of the Balitsky-Kovchegov (BK) equation unstable. We develop a systema…

hep-ph2026

Small-x TMD distributions: JIMWLK evolution and the Gaussian truncation

Florian Cougoulic, Piotr Korcyl

We extend the systematic study of small- Transverse Momentum Dependent (TMD) distributions, initiated in [Cougoulic:2026drr], by including the energy evolution. We use the JIMWL…

hep-ph2026

Simultaneous Color Glass Condensate fit to deep inelastic scattering and forward hadron production at HERA, RHIC, and the LHC

Piotr Korcyl, Truong My Hau Le, Farid Salazar +1

We present the first simultaneous fit to deep inelastic scattering (DIS) reduced cross sections from HERA and forward single inclusive hadron production (SIHP) from RHIC and the LH…

cs.LG2026

Variational Autoregressive Networks with probability priors

Piotr Białas, Piotr Korcyl, Tomasz Stebel +1

Monte Carlo methods are essential across diverse scientific fields, yet their efficiency is frequently hampered by critical slowing down-a sharp increase in autocorrelation times n…

cond-mat.dis-nn2026

Sampling two-dimensional spin systems with transformers

Piotr Białas, Piotr Korcyl, Tomasz Stebel +2

Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods,…

hep-ph2026

Small-x TMD distributions initial condition: Nc-dependence and Gaussian approximations

Florian Cougoulic, Piotr Korcyl, Tomasz Stebel

We systematically derive expressions for ten small- Transverse Momentum Dependent (TMD) distributions in the Gaussian approximation, three in the quark-gluon sector and seven in…

hep-lat2026

Probing Instanton Dynamics in the Pion Vector Form Factor with Wilson Flow

Vaibhav Chahar, Piotr Korcyl

Instanton liquid model is believed to capture the main features of vacuum QCD dynamics. Recently, multiple predictions for hadron structure functions have been derived and compared…

hep-ph2025

Probing gluon saturation with forward di-hadron correlations in proton-nucleus collisions

Paul Caucal, Zhong-Bo Kang, Piotr Korcyl +5

We present a detailed numerical investigation of semi-inclusive forward di-hadron production in proton-nucleus collisions employing the Color Glass Condensate effective theory. We…

hep-ph2025

Rotating the Color Glass Condensate

Renaud Boussarie, Paul Caucal, Piotr Korcyl +1

High-energy QCD evolution beyond leading order suffers from instabilities driven by large collinear logarithms. We present a framework, consistent with the standard high-energy ope…

quant-ph2025

Estimation of the reduced density matrix and entanglement entropies using autoregressive networks

Piotr Białas, Piotr Korcyl, Tomasz Stebel +1

We present an application of autoregressive neural networks to Monte Carlo simulations of quantum spin chains using the correspondence with classical two-dimensional spin systems.…

hep-lat2025

NeuMC -- a package for neural sampling for lattice field theories

Piotr Bialas, Piotr Korcyl, Tomasz Stebel +1

We present the \texttt{NeuMC} software package, based on \pytorch, aimed at facilitating the research on neural samplers in lattice field theories. Neural samplers based on normali…

cond-mat.stat-mech2025

Hierarchical autoregressive neural networks in three-dimensional statistical system

Piotr Białas, Vaibhav Chahar, Piotr Korcyl +3

Autoregressive Neural Networks (ANN) have been recently proposed as a mechanism to improve the efficiency of Monte Carlo algorithms for several spin systems. The idea relies on the…

hep-ph2024★ 1 cited

Improving the solver for the Balitsky-Kovchegov evolution equation with Automatic Differentiation

Florian Cougoulic, Piotr Korcyl, Tomasz Stebel

The Balitsky-Kovchegov (BK) evolution equation is an equation derived from perturbative Quantum Chromodynamics that allows one to evolve with collision energy the scattering amplit…

hep-ph2024

Reconciling the kinematical constraint with the JIMWLK evolution equation: correlation functions non-local in rapidity

Piotr Korcyl, Leszek Motyka, Tomasz Stebel

In the high-energy limit of DIS experiments the effective degrees of freedom of QCD are Wilson line operators. Their evolution in the rapidity variable is predicted by the set of B…

cond-mat.stat-mech2024★ 5 cited

Rényi entanglement entropy of spin chain with Generative Neural Networks

Piotr Białas, Piotr Korcyl, Tomasz Stebel +1

We describe a method to estimate Rényi entanglement entropy of a spin system, which is based on the replica trick and generative neural networks with explicit probability estimatio…

hep-ph2024

Progress in implementing the kinematical constraint into the small-x JIMWLK evolution equation

P. Korcyl, L. Motyka, T. Stebel

The most complete high-energy evolution of Wilson line operators is described by the set of equations called Balitsky-JIMWLK evolution equations. It is known from the studies of th…