Related papers: A Gaussian Process Generative Model for QCD Equati…
Gaussian Process Regression (GPR) is widely used for inferring functions from noisy data. GPR crucially relies on the choice of a kernel, which might be specified in terms of a collection of hyperparameters that must be chosen or learned.…
Quantum denoising diffusion models have recently emerged as a powerful framework for generative quantum machine learning. In this work, we extend these models by introducing a conditioning mechanism that enables the generation of quantum…
The only first principle knowledge of the QCD equation of state at finite baryonic density is given from Lattice QCD as a Taylor expansion around $\mu_B = 0$. The coefficients of such an expansion are currently available up to order ${\cal…
For finite chemical potential effective models of QCD predict a first order phase transition. In favour for the search of such a phase transition in nature, we construct an equation of state for strange quark matter based on the MIT bag…
We study the phase structure and phase transition of cold dense QCD matter via the Dyson-Schwinger equation approach. We take the rainbow approximation and the Gaussian-type gluon model. In order to guarantee that the quark number density…
QCD gives rise to a rich spectrum of excited baryon states. Understanding their internal structure is important for many areas of nuclear physics, such as nuclear forces, dense matter, and neutrino-nucleus interactions. Generalized parton…
This paper is devoted to the study of QCD equation of state in external magnetic field and nonzero baryon density. Our study is carried out by means of lattice simulation with 2+1 dynamical staggered quarks at the physical masses. The…
The equation of state of dense matter determines the structure of neutron stars, their typical radii, and maximum masses. Recent improvements in theoretical modeling of nuclear forces from the low-energy effective field theory of QCD has…
Accurate phase diagram calculation from molecular dynamics requires systematic treatment and convergence of statistical averages. In this work we propose a Gaussian process regression based framework for reconstructing the free energy…
We investigate how large baryon densities (and possibly high temperatures) may induce spontaneous parity violation in the composite meson sector of vector-like gauge theory (presumably QCD or techni-QCD) . The analysis at intermediate…
The discovery of the coalescence of binary neutron star GW170817 was a watershed moment in the field of gravitational wave astronomy. Among the rich variety of information that we were able to uncover from this discovery was the first…
Location of critical point and mapping the QCD phase boundary still exists as one of the most interesting and studied problems of heavy-ion physics. A new equation of state (EOS) for a gas of extended baryons and pointlike mesons is…
In this work, we propose a novel generative model for mapping inputs to structured, high-dimensional outputs using structured conditional normalizing flows and Gaussian process regression. The model is motivated by the need to characterize…
A method to reconstruct fields, source strengths and physical parameters based on Gaussian process regression is presented for the case where data are known to fulfill a given linear differential equation with localized sources. The…
We incorporate the empirical low-density properties of isospin symmetric nuclear matter into the excluded-volume model for quarkyonic matter by including attractive mean field in the nucleonic sector and considering variations on the…
Nucleon matters are studied based on QCD. We extract nucleon-nucleon interaction from lattice QCD simulations in a recently developed approach, and then derive the equations of state of the symmetric nuclear matter and the pure neutron…
The paper investigated a set of non-Gaussian states generated by measuring the number of particles in one of the modes of a two-mode entangled Gaussian state. It was demonstrated that all generated states depend on two types of parameters:…
We present a novel framework for the equation of state of dense and hot Quantum Chromodynamics (QCD), which focuses on the region of the phase diagram relevant for neutron star mergers and core-collapse supernovae. The model combines…
In this paper, a quantum algorithm based on gaussian process regression model is proposed. The proposed quantum algorithm consists of three sub-algorithms. One is the first quantum subalgorithm to efficiently generate mean predictor. The…
We discuss the Taylor expansion approach to non-zero baryon chemical potential ($\mu_B$) and present results on expanion coefficients of the pressure and energy density up to the 6-th order in $\mu_B$. Calculations have been performed with…