Related papers: CGC/saturation approach: an impact-parameter depen…
We introduce Diffusion Active Learning, a novel approach that combines generative diffusion modeling with data-driven sequential experimental design to adaptively acquire data for inverse problems. Although broadly applicable, we focus on…
We study for the first time the transverse momentum transfer distributions $d\sigma/dt$ in coherent production of charmonia in nuclear ultra-peripheral and electron-ion collisions within the QCD color dipole approach based on a rigorous…
Coherent diffraction imaging (CDI) of single molecules at atomic resolution is a major goal for the x-ray free electron lasers (XFELs). However, during an imaging pulse, the fast laser-induced ionization may strongly affect the recorded…
We introduce a saturation model for photon-photon interactions, based on a QCD dipole picture of high energy scattering. The two-dipole cross-section is assumed to satisfy the saturation property. This pomeron-like contribution is…
In this paper we study the double $J/\psi$ production in central diffractive processes considering the Resolved Pomeron model. Based on the nonrelativistic QCD (NRQCD) factorization formalism for the quarkonium production mechanism we…
We present a combined QCD analysis of recent data produced by the H1 and ZEUS collaborations on the diffractive and leading-proton deep inelastic positron--proton scattering structure functions, $F_2^{D(3)}$ and $F_2^{LP(3)}$, respectively.…
We derive the semiclassical (instanton-induced) contribution to the inelastic cross section of two color dipoles at large $\sqrt{s}$. We study its dependence on the dipole sizes, orientations and, most importantly, the impact parameter. The…
In our contemporary academic inquiry, we present "Diffusion-C," a foundational methodology to analyze the generative restrictions of Diffusion Models, particularly those akin to GANs, DDPM, and DDIM. By employing input visual data that has…
Trajectory generation for mobile robots in unstructured environments faces a critical dilemma: balancing kinematic smoothness for safe execution with terminal precision for fine-grained tasks. Existing generative planners often struggle…
Diffusion models, a powerful and universal generative AI technology, have achieved tremendous success in computer vision, audio, reinforcement learning, and computational biology. In these applications, diffusion models provide flexible…
Saturation in deep inelastic scattering (DIS) and deeply virtual Compton scattering (DVCS) is associated with a phase transition between the partonic gas, typical of moderate $x$ and $Q^2$, and partonic fluid appearing at increasing $Q^2$…
We review QCD based descriptions of diffractive deep inelastic scattering emphasising the role of models with parton saturation. These models provide natural explanation of such experimentally observed facts as the constant ratio of the…
Diffractive events are studied by means of identification of one or more rapidity gaps and/or a leading antiproton. Measurements of soft and hard diffractive processes have been performed at the Tevatron $p\bar p$ collider and presented. We…
We compute the rate for diffractive $\phi$ electro-production using the Color Glass Condensate dipole model. The model parameters are obtained from fits to the most recent combined HERA data on inclusive deep inelastic scattering. As for…
We study exclusive charmonium production in diffractive deep inelastic scattering and ultra-peripheral heavy-ion collisions within the dipole picture. The mass spectrum and light-front wavefunctions of charmonium are obtained from the basis…
ZEUS inclusive diffractive cross-section measurements have been used in a next-to-leading-order QCD analysis to extract the diffractive parton distribution functions. Data on diffractive dijet production in deep inelastic scattering have…
Two-dimensional materials constitute an exciting platform for nonlinear optics with large nonlinearities that are tunable by gating. Hence, gate-tunable harmonic generation and intensity-dependent refraction have been observed in e.g.…
Diffusion models have become popular for policy learning in robotics due to their ability to capture high-dimensional and multimodal distributions. However, diffusion policies are stochastic and typically trained offline, limiting their…
Classifier-Free Guidance (CFG) is a cornerstone of modern conditional diffusion models, yet its reliance on the fixed or heuristic dynamic guidance weight is predominantly empirical and overlooks the inherent dynamics of the diffusion…
In this paper we review and update the Amaral-Gay Ducati-Betemps-Soyez saturation model, by testing it against the recent H1-ZEUS combined data on deep inelastic scattering, including heavy quarks in the dipole amplitude. We obtain that…