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Péter Kovács

Publications and source records attributed to Péter Kovács.

36 records · Page 2Linked to original sources

The fate of the critical endpoint at large $N_c$

The phase diagram of QCD is investigated by varying number of colors $N_c$ within a Polyakov loop quark-meson chiral model. In particular, our attention is focused on the critical point(s): the critical point present for $N_c=3$ moves toward the $μ_q$-axis and disappears as soon as the number of color is increased. Yet, a distinct critical point emerges along the temperature axis for $N_c = 53$ and moves toward finite density when increasing $N_c$ further. Thus, the phase diagram at large $N_c$ looks specular w.r.t. the $N_c = 3$ results, with the first order transition in the upper-left and crossover in the down-right regions of the the $(μ_q,T)$-plane. The pressure is also evaluated in dependence of $N_c$, showing a scaling with $N_c^0$ in the confined and chirally broken phase and with $N_c^2$ in the deconfined one. Moreover, the presence of a chirally symmetric but confined `quarkyonic phase' at large density and moderate temperature with a pressure proportional to $N_c$ is confirmed.

hep-ph↗

Abnormal Road Surface Detection Using Wheel Sensor Data

Intelligent tires can be used for a wide array of applications ranging from tire pressure monitoring to analyzing tire/road interactions, wheel loading, and tread wear monitoring. In this article, we develop a measurement system for intelligent tires equipped with a 3-D piezoresistive force sensor. The output of the sensor is segmented into tire revolution cycles, which are then represented by a transformation relying on adaptive Hermite functions. The underlying idea behind this step is to extract relevant features which capture tire dynamics. Then we evaluate the proposed measurement system in a potential vehicle application, that is, abnormal road surface detection. We deal with the corresponding binary classification problem by developing both low-complexity analytical and data-driven machine learning algorithms, which are tested on real-world measurement data. Our experiments showed that the proposed methods are able to detect abnormalities on the road surface with a mean accuracy of over 97%.

eess.SY↗

Neutron star properties with careful parameterization in the (axial)vector meson extended linear sigma model

The existence of quark matter inside the cores of heavy neutron stars is a possibility which can be probed with modern astrophysical observations. We use an (axial)vector meson extended quark-meson model to describe quark matter in the core of neutron stars. We discover that an additional parameter constraint is necessary in the quark model to ensure chiral restoration at high densities. By investigating hybrid star sequences with various parameter sets we show that low sigma meson masses are needed to fulfill the upper radius constraints, and that the maximum mass of stable hybrid stars is only slightly dependent on the parameters of the crossover-type phase transition. Using this observation and results from recent astrophysical measurements a constraint of 2.6 < g_V < 4.3 is set for the constituent quark - vector meson coupling. The effect of a nonzero bag constant is also investigated and we observe that its effect is small for values adopted in previous works.

nucl-th↗

VPNet: Variable Projection Networks

We introduce VPNet, a novel model-driven neural network architecture based on variable projection (VP). Applying VP operators to neural networks results in learnable features, interpretable parameters, and compact network structures. This paper discusses the motivation and mathematical background of VPNet and presents experiments. The VPNet approach was evaluated in the context of signal processing, where we classified a synthetic dataset and real electrocardiogram (ECG) signals. Compared to fully connected and one-dimensional convolutional networks, VPNet offers fast learning ability and good accuracy at a low computational cost of both training and inference. Based on these advantages and the promising results obtained, we anticipate a profound impact on the broader field of signal processing, in particular on classification, regression and clustering problems.

cs.LG↗

Machine learning aided noise filtration and signal classification for CREDO experiment

The wealth of smartphone data collected by the Cosmic Ray Extremely Distributed Observatory(CREDO) greatly surpasses the capabilities of manual analysis. So, efficient means of rejectingthe non-cosmic-ray noise and identification of signals attributable to extensive air showers arenecessary. To address these problems we discuss a Convolutional Neural Network-based method ofartefact rejection and complementary method of particle identification based on common statisticalclassifiers as well as their ensemble extensions. These approaches are based on supervised learning,so we need to provide a representative subset of the CREDO dataset for training and validation.According to this approach over 2300 images were chosen and manually labeled by 5 judges.The images were split into spot, track, worm (collectively named signals) and artefact classes.Then the preprocessing consisting of luminance summation of RGB channels (grayscaling) andbackground removal by adaptive thresholding was performed. For purposes of artefact rejectionthe binary CNN-based classifier was proposed which is able to distinguish between artefacts andsignals. The classifier was fed with input data in the form of Daubechies wavelet transformedimages. In the case of cosmic ray signal classification, the well-known feature-based classifierswere considered. As feature descriptors, we used Zernike moments with additional feature relatedto total image luminance. For the problem of artefact rejection, we obtained an accuracy of 99%. For the 4-class signal classification, the best performing classifiers achieved a recognition rate of 88%.

physics.ins-det↗

ECG Beat Representation and Delineation by means of Variable Projection

The electrocardiogram (ECG) follows a characteristic shape, which has led to the development of several mathematical models for extracting clinically important information. Our main objective is to resolve limitations of previous approaches, that means to simultaneously cope with various noise sources, perform exact beat segmentation, and to retain diagnostically important morphological information. Methods: We therefore propose a model that is based on Hermite and sigmoid functions combined with piecewise polynomial interpolation for exact segmentation and low-dimensional representation of individual ECG beat segments. Hermite and sigmoidal functions enable reliable extraction of important ECG waveform information while the piecewise polynomial interpolation captures noisy signal features like the BLW. For that we use variable projection, which allows the separation of linear and nonlinear morphological variations of the according ECG waveforms. The resulting ECG model simultaneously performs BLW cancellation, beat segmentation, and low-dimensional waveform representation. Results: We demonstrate its BLW denoising and segmentation performance in two experiments, using synthetic and real data (Physionet QT database). Compared to state-of-the-art algorithms, the experiments showed less diagnostic distortion in case of denoising and a more robust delineation for the P and T wave. Conclusion: This work suggests a novel concept for ECG beat representation, easily adaptable to other biomedical signals with similar shape characteristics, such as blood pressure and evoked potentials. Significance: Our method is able to capture linear and nonlinear wave shape changes. Therefore, it provides a novel methodology to understand the origin of morphological variations caused, for instance, by respiration, medication, and abnormalities.

eess.SP↗

One-loop constituent quark contributions to the vector and axial-vector meson curvature mass

The renormalized contribution of fermions to the curvature masses of vector and axial-vector mesons is derived with two different methods at leading order in the loop expansion applied to the (2+1)-flavor constituent quark-meson model. The corresponding contribution to the curvature masses of the scalar and pseudoscalar mesons, already known in the literature, is rederived in a transparent way. The temperature dependence of the curvature mass of various (axial-)vector modes obtained by decomposing the curvature mass tensor is investigated along with the (axial-)vector--(pseudo)scalar mixing. All fermionic corrections are expressed as simple integrals that involve at finite temperature only the Fermi-Dirac distribution function modified by the Polyakov-loop degrees of freedom. The renormalization of the (axial-)vector curvature mass allows us to lift a redundancy in the original Lagrangian of the globally symmetric extended linear sigma model, in which terms already generated by the covariant derivative were reincluded with different coupling constants.

hep-ph↗

Hybrid star properties from an extended linear sigma model

The equation of state provided by effective models of strongly interacting matter should comply with the restrictions imposed by current astrophysical observations on compact stars. Using the equation of state given by the (axial-)vector meson extended linear sigma model, we determine the mass-radius relation and study whether these restrictions are satisfied under the assumption that most of the star is filled with quark matter. We study the dependence of the mass-radius relation on the parameters of the model.

nucl-th↗

Comment on "Tidal Love numbers of neutron and self-bound quark stars"

We comment on the paper of S. Postnikov et al. in Phys. Rev. D 82, 024016 (2010) and give a modified formula that needs to be taken into account when calculating the tidal Love number of neutron stars in case a first order phase-transition occurs at non-zero pressure. We show that the error made when using the original formula tends to zero as $p \rightarrow 0$ and we estimate the maximum relative error to be $\sim 5\%$ if the density discontinuity is at larger densities.

astro-ph.HE↗

Hybrid star construction with the extended linear sigma model: preliminary results

The interior of compact stars is usually divided into two major parts, the outer part called crust and the inner part called core. There are several possibilities for the composition of these parts. One is a hybrid star, in which the crust contains nuclear matter, while the inner core contains quark matter. Since at large baryon densities one can work with effective models, and nuclear and quark matter are usually described by different models, some unification of the two parts is needed. We show two different approaches for a composite model and some recent developments in hybrid star constructions using the extended linear sigma model for modeling the quark matter at the core.

hep-ph↗

Nonlinear least-squares spline fitting with variable knots

In this paper, we present a nonlinear least-squares fitting algorithm using B-splines with free knots. Since its performance strongly depends on the initial estimation of the free parameters (i.e. the knots), we also propose a fast and efficient knot-prediction algorithm that utilizes numerical properties of first-order B-splines. Using $\ell_p\;(p=1,2,\infty)$ norm solutions, we also provide three different strategies for properly selecting the free knots. Our initial predictions are then iteratively refined by means of a gradient-based variable projection optimization. Our method is general in nature and can be used to estimate the optimal number of knots in cases in which no a-priori information is available. To evaluate the performance of our method, we approximated a one-dimensional discrete time series and conducted an extensive comparative study using both synthetic and real-world data. We chose the problem of electrocardiogram (ECG) signal compression as a real-world case study. Our experiments on the well-known PhysioNet MIT-BIH Arrhythmia database show that the proposed method outperforms other knot-prediction techniques in terms of accuracy while requiring much lower computational complexity.

eess.SP↗

Generalized Rational Variable Projection With Application in ECG Compression

In this paper we develop an adaptive transform-domain technique based on rational function systems. It is of general importance in several areas of signal theory, including filter design, transfer function approximation, system identification, control theory etc. The construction of the proposed method is discussed in the framework of a general mathematical model called variable projection. First we generalize this method by adding dimension type free parameters. Then we deal with the optimization problem of the free parameters. To this order, based on the well-known particle swarm optimization (PSO) algorithm, we develop the multi-dimensional hyperbolic PSO algorithm. It is designed especially for the rational transforms in question. As a result, the system along with its dimension is dynamically optimized during the process. The main motivation was to increase the adaptivity while keeping the computational complexity manageable. We note that the proposed method is of general nature. As a case study the problem of electrocardiogram (ECG) signal compression is discussed. By means of comparison tests performed on the PhysioNet MIT-BIH Arrhythmia database we demonstrate that our method outperforms other transformation techniques.

eess.SP↗

Compact star properties from an extended linear sigma model

The equation of state provided by effective models of strongly interacting matter should comply with the restrictions imposed by current astrophysical observations of compact stars. Using the equation of state given by the (axial-)vector meson extended linear sigma model, we determine the mass-radius relation and study whether these restrictions are satisfied under the assumption that most of the star is filled with quark matter. We also compare the mass-radius sequence with those given by the equations of state of somewhat simpler models.

hep-ph↗

Orbital-free approximations to the kinetic-energy density in exchange-correlation MGGA functionals: tests on solids

A recent study of Mejia-Rodriguez and Trickey [Phys. Rev. A 96, 052512 (2017)] showed that the deorbitalization procedure (replacing the exact Kohn-Sham kinetic-energy density by an approximate orbital-free expression) applied to exchange-correlation functionals of the meta-generalized gradient approximation (MGGA) can lead to important changes in the results for molecular properties. For the present work, the deorbitalization of MGGA functionals is further investigated by considering various properties of solids. It is shown that depending on the MGGA, common orbital-free approximations to the kinetic-energy density can be sufficiently accurate for the lattice constant, bulk modulus, and cohesive energy. For the band gap, calculated with the modified Becke-Johnson MGGA potential, the deorbitalization has a larger impact on the results.

cond-mat.mtrl-sci↗

A statistical method to estimate low-energy hadronic cross sections

In this article we propose a model based on the Statistical Bootstrap approach to estimate the cross sections of different hadronic reactions up to a few GeV in c.m.s energy. The method is based on the idea, when two particles collide a so called fireball is formed, which after a short time period decays statistically into a specific final state. To calculate the probabilities we use a phase space description extended with quark combinatorial factors and the possibility of more than one fireball formation. In a few simple cases the probability of a specific final state can be calculated analytically, where we show that the model is able to reproduce the ratios of the considered cross sections. We also show that the model is able to describe proton\,-\,antiproton annihilation at rest. In the latter case we used a numerical method to calculate the more complicated final state probabilities. Additionally, we examined the formation of strange and charmed mesons as well, where we used existing data to fit the relevant model parameters.

nucl-th↗

Phase diagram and isentropic curves from the vector meson extended Polyakov quark meson model

In the framework of the $N_f = 2+1$ flavor (axial)vector meson extended Polyakov quark meson model we investigate the QCD phase diagram at finite temperature and density. We use a $χ^2$ minimization procedure to parameterize the model based on tree\,-\,level decay widths and vacuum scalar and pseudoscalar curvature masses which incorporate the contribution of the constituent quarks. Using a hybrid approximation (mesons at tree level, fermions at one\,-\,loop level) for the grand potential we determine the phase boundary both on the $μ_B-T$ and $ρ-T$ planes. We also determine the location of the critical end point of the phase diagram. Moreover by calculating the pressure and other thermodynamical quantities derived from it, we determine a set of isentropic curves in the crossover region. We show that the curves behave very similarly as their counterparts obtained from the lattice in the crossover regime.

hep-ph↗

Chiral phase transition scenarios from the vector meson extended Polyakov quark meson model

Chiral phase transition is investigated in an $SU(3)_L \times SU(3)_R$ symmetric vector meson extended linear sigma model with additional constituent quarks and Polyakov loops (extended Polyakov quark meson model). The parameterization of the Lagrangian is done at zero temperature in a hybrid approach, where the mesons are treated at tree-level, while the constituent quarks at 1-loop level. The temperature and baryochemical potential dependence of the two assumed scalar condensates are calculated from the hybrid 1-loop level equations of states. The order of the phase transition along the $T=0$ and $μ_B=0$ axes are determined for various parameterization scenarios. We find that in order to have a first order phase transition at $T=0$ as a function of $μ_B$ a light isoscalar particle is needed.

hep-ph↗

Chiral phase transition in the vector meson extended linear sigma model

In the framework of an SU(3) (axial)vector meson extended linear sigma model with additional constituent quarks and Polyakov loops, we investigate the effects of (axial)vector mesons on the chiral phase transition. The parameters of the Lagrangian are set at zero temperature and we use a hybrid approach where in the effective potential the constituent quarks are treated at one-loop level and all the mesons at tree-level. We have four order parameters, two scalar condensates and two Polyakov loop variables and their temperature and baryochemical potential dependence are determined from the corresponding field equations. We also investigate the changes of the tree-level scalar meson masses in the hot and dense medium.

hep-ph↗