Related papers: TopicFlow: Disentangling quark and gluon jets with…
Recently, there has been a surge of interest in incorporating neural networks into particle filters, e.g. differentiable particle filters, to perform joint sequential state estimation and model learning for non-linear non-Gaussian…
The state of art in studying thermodynamic properties of hot and dense nuclear matter is reviewed with the special emphasis on the confinement-deconfinement transition between hadron matter and quark-gluon plasma. The most popular models…
Normalizing flows, a category of probabilistic models famed for their capabilities in modeling complex data distributions, have exhibited remarkable efficacy in unsupervised anomaly detection. This paper explores the potential of…
The different modifications of quark- and gluon-initiated jets in the quark-gluon plasma (QGP) produced in heavy-ion collisions is a long-standing question that has not yet received a definitive answer from experiments. In particular, the…
Normalizing Flows provide a principled framework for high-dimensional density estimation and generative modeling by constructing invertible transformations with tractable Jacobian determinants. We propose Fractal Flow, a novel normalizing…
In the past, normalizing generative flows have emerged as a promising class of generative models for natural images. This type of model has many modeling advantages: the ability to efficiently compute log-likelihood of the input data, fast…
Given the growth in the variety and precision of astronomical datasets of interest for cosmology, the best cosmological constraints are invariably obtained by combining data from different experiments. At the likelihood level, one…
Gluon jets are identified in e+e- hadronic annihilation events by tagging two quark jets in the same hemisphere of an event. The gluon jet is defined inclusively as all the particles in the opposite hemisphere. Gluon jets defined in this…
The purpose of the present article is to call attention to some realistic quasiparticle-based description of the quark/gluon matter and its consistent implementation in thermodynamics. A simple and transparent representation of the…
To measure the characteristics of quark and gluon jets in hadron-hadron collisions, two samples of jets are used. Given the large statistics of jets at the LHC, the two-sample method requires taking into account the following corrections:…
We apply advanced machine learning techniques to two challenging jet classification problems at the LHC. The first is strange-quark tagging, in particular distinguishing strange-quark jets from down-quark jets. The second, which we term…
In the first talk I discuss the usefulness of jet grooming for testing jet quenching mechanisms, and I present a calculation of soft-drop jet mass distribution in proton-proton and heavy ion collisions. In the second talk I discuss the…
A flow decomposition method based on canonical correlation analysis is proposed in this paper to optimally dissect complex flows into mutually orthogonal modes that are ranked by their cross-correlation with an observable. It is…
Since the machine learning techniques are improving rapidly, it has been shown that the image recognition techniques in deep neural networks can be used to detect jet substructure. And it turns out that deep neural networks can match or…
Experimental data, theoretical ideas and models concerning jet fragmentation and the hadronization process are reviewed, concentrating on the following topics: factorization and small-x resummation of fragmentation functions, hadronization…
We review the formalism of quark recombination applied to the hadronization of a quark gluon plasma. Evidence in favor of the quark recombination model is outlined. Recent work on parton correlations, leading to detectable correlations…
We propose a new strategy to obtain a high-purity sample of gluon-initiated jets at the LHC. Our approach, inspired by the Lund jet plane picture, is to perform a dijet selection where the two jets are collinear to each other and their…
Identifying jets in heavy ion collisions is of significant interest since the properties of jets are expected to get modified because of the formation of quark gluon plasma. The detection of jets is, however, difficult because of large…
In many scientific applications, the target probability distribution cannot be evaluated in closed form or sampled from directly. Instead, it can often be decomposed into multiple components, some of which are accessible only through…
We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing…