Related papers: Diffusion-Based Point-Cloud Generation of Heavy-Io…
Hexahedral meshes are widely used in simulation pipelines, yet automatic generation remains challenging for complex CAD geometries. Polycube-based hexahedral meshing is a representative approach due to its regular, parameterization-friendly…
In the particle-flow approach information from all available sub-detector systems is combined to reconstruct all stable particles. The global event reconstruction has been shown to improve, in particular, the resolution of jet energy and…
Defects in laser powder bed fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. For instance, the melt pool can directly contribute to the formation of undesirable…
Machine learning has demonstrated remarkable promise for solving the trajectory generation problem and in paving the way for online use of trajectory optimization for resource-constrained spacecraft. However, a key shortcoming in current…
Diffusion-based image generators can now produce high-quality and diverse samples, but their success has yet to fully translate to 3D generation: existing diffusion methods can either generate low-resolution but 3D consistent outputs, or…
In very high energy collisions, many particles are produced and distributed in the available phase space volume in various ways. With advent of new accelerator facilities (especially, for nucleus-nucleus collisions), the problem of pattern…
We present a new 3D resolved model for the initial state of ultrarelativistic heavy-ion collisions, based on the $k_\perp$-factorized Color Glass Condensate hybrid approach. The McDIPPER framework responds to the need for a…
The production of jets, and high momentum hadrons from jets, produced in deuteron ($d$)-$Au$ collisions at the relativistic heavy-ion collider (RHIC) and proton ($p$)-$Pb$ collisions at the large hadron collider (LHC) are studied as a…
We model the disassembly of an excited nuclear system formed as a result of a heavy ion collision. We find that, as the beam energy in central collisions in varied, the dissociating system crosses a liquid-gas coexistence curve, resulting…
Deep learning techniques have the power to identify the degree of modification of high energy jets traversing deconfined QCD matter on a jet-by-jet basis. Such knowledge allows us to study jets based on their initial, rather than final…
The heavy ion event generator HYDJET++ is presented. HYDJET++ simulates relativistic heavy ion AA collisions as a superposition of the soft, hydro-type state and the hard state resulting from multi-parton fragmentation. This model is the…
Stably placing an object in a multi-object scene is a fundamental challenge in robotic manipulation, as placements must be penetration-free, establish precise surface contact, and result in a force equilibrium. To assess stability, existing…
For the successful generation of ion-beam-driven high energy density matter and heavy ion fusion energy, intense ion beams must be transported and focused onto a target with small spot size. One of the successful approaches to achieve this…
We study the diffractive jet production in electron-ion collisions in the kinematical region where the mass $M_X$ of the diffractive final state is larger than $Q^2$. Based on parton saturation framework predictions are done for the…
At the Large Hadron Collider (LHC), the most abundant processes which take place in proton-proton collisions are the generation of multijet events. These final states rely heavily on phenomenological models and perturbative corrections…
We present an event-by-event analysis of the cluster structure of final multihadron states resulting from heavy ion collisions. A comparison of experimental data with the states obtained from Monte Carlo generators is shown. The analysis of…
We present a simple description of the energy density profile created in a nucleus-nucleus collision, motivated by high-energy QCD. The energy density is modeled as the sum of contributions coming from elementary collisions between…
Modern diffusion-based image generative models have made significant progress and become promising to enrich training data for the object detection task. However, the generation quality and the controllability for complex scenes containing…
Adversarial attack methods for 3D point cloud classification reveal the vulnerabilities of point cloud recognition models. This vulnerability could lead to safety risks in critical applications that use deep learning models, such as…
We introduce a framework for joint grounded scene graph - image generation, a challenging task involving high-dimensional, multi-modal structured data. To effectively model this complex joint distribution, we adopt a factorized approach:…