Fluctuations and Criticality in Heavy-Ion Collisions

Quantum Chromodynamics (QCD) predicts various extraordinary phases of matter whose underlying physics is described by the strong interaction. Identifying the QCD phase diagram, of which a critical point serves as the landmark, is one of the fundamental open subjects in modern physics. The properties of the QCD phase transitions and criticality can be studied by the relativistic heavy-ion collision experiments at various laboratory accelerator facilities, where a strongly interacting primordial matter is expected to form in extreme conditions on an event-by-event basis. Fluctuations are therefore indispensable for describing such stochastic process and become rather crucial for understanding the universal behavior when the system approaches the critical point. In this thesis, we will discuss the current methodology and challenge of discovering the QCD critical point, with an emphasis on the recent progress in quantifying the fluctuation-driven phenomena both in and out of equilibrium. The state-of-the-art formalism we developed constitutes an integral part of the theoretical framework for interpreting the experimental results from the ongoing RHIC Beam Energy Scan Program

Fig 5 -

The performance of our active learning approach with support vector machine (a), logistic regression (b), and random forest (c) as the respective base classifiers in terms of the F1 score.</p

Research framework for screening articles about the origins of SARS-CoV-2.

Research framework for screening articles about the origins of SARS-CoV-2.</p

An illustrative example with a partial list of backward citations in [57].

An illustrative example with a partial list of backward citations in [57].</p

The number of articles in the top 10 journals.

The number of articles in the top 10 journals.</p

The procedure of an active learning approach.

The procedure of an active learning approach.</p

The trends of the number of relevant and nonrelevant publications with publishing time in our seed dataset.

The trends of the number of relevant and nonrelevant publications with publishing time in our seed dataset.</p

The performance of the top screened articles about the origins of SARS-CoV-2 from the CORD-19 dataset.

The performance of the top screened articles about the origins of SARS-CoV-2 from the CORD-19 dataset.</p

F1 score and numbers of queries when each model reached the maximum F1 score.

F1 score and numbers of queries when each model reached the maximum F1 score.</p

The overlapping shares of relevant articles screened by three base classifiers.

The overlapping shares of relevant articles screened by three base classifiers.</p