arXiv subjects

Kyungsik Kim

Publications and source records attributed to Kyungsik Kim.

At least 37 records · Page 2Linked to original sources

arXiv2022

Inclusive electron scattering in the quasielastic region with Korea-IBS-Daegu-SKKU density functional

With the framework of KIDS (Korea-IBS-Daegu-SKKU) density functional model, the isoscalar and isovector effective masses of nucleon and the effect of symmetry energy in nuclear medium are investigated in inclusive $(e,e')$ reaction in quasielastic region. The effective masses are varied in the range $(0.7 \sim 1.0)M$ with free nucleon mass $M$, and the symmetry energy is varied within the uncertainty allowed by nuclear data and neutron star observation. The wave functions of nucleons inside target nucleus are generated by solving Hartree-Fock equation with adjusting equation of state, binding energy and radius of various stable nuclei, and effective mass of nucleon in the KIDS model. With the obtained wave functions, we calculate the differential cross section for the inclusive $(e,e')$ reaction and compare the theoretical results with Bates, Saclay, and SLAC experimental data. Our model describes experimental data better at SLAC-type high incident electron energy than those measured from Bates and Saclay. The influence of the effective mass and symmetry energy appears to be precise on the longitudinal cross section.

nucl-th↗

arXiv2021

Quasi-elastic electron scattering with KIDS nuclear energy density functional

Isoscalar and isovector effective masses of the nucleon in nuclear medium are explored in the quasi-elastic electron scattering of nuclei with KIDS (Korea-IBS-Daegu-SKKU) density functional model. Effective masses are varied in the range (0.7 ~ 1.0)$M$ where $M$ is the mass of the nucleon in free space. Parameters in the KIDS functional are adjusted to nuclear matter equation of state, energy and radius of selected nuclei, and effective mass of nucleons. Hartree-Fock equation is solved to obtain the wave functions of the nucleon in target nuclei, and they are plugged in the calculation of electron-nucleus scattering cross sections at the energies of incident electrons 300 MeV ~ 2.5 GeV. Theoretical prediction agrees well with measurement. Dependence on the effective mass is evident: cross section tends to increase with small isoscalar effective masses. However, effect of isovector effective mass is negligible. Spectroscopic factors are estimated for the protons in the outermost shells of $^{16}$O, $^{40}$Ca, and $^{208}$Pb. Results are consistent with the values in the literature.

nucl-th↗

arXiv2021

Dynamical prediction of two meteorological factors using the deep neural network and the long short-term memory $(2)$

This paper presents the predictive accuracy using two-variate meteorological factors, average temperature and average humidity, in neural network algorithms. We analyze result in five learning architectures such as the traditional artificial neural network, deep neural network, and extreme learning machine, long short-term memory, and long-short-term memory with peephole connections, after manipulating the computer-simulation. Our neural network modes are trained on the daily time-series dataset during seven years (from 2014 to 2020). From the trained results for 2500, 5000, and 7500 epochs, we obtain the predicted accuracies of the meteorological factors produced from outputs in ten metropolitan cities (Seoul, Daejeon, Daegu, Busan, Incheon, Gwangju, Pohang, Mokpo, Tongyeong, and Jeonju). The error statistics is found from the result of outputs, and we compare these values to each other after the manipulation of five neural networks. As using the long-short-term memory model in testing 1 (the average temperature predicted from the input layer with six input nodes), Tonyeong has the lowest root mean squared error (RMSE) value of 0.866 $(%)$ in summer from the computer-simulation in order to predict the temperature. To predict the humidity, the RMSE is shown the lowest value of 5.732 $(%)$, when using the long short-term memory model in summer in Mokpo in testing 2 (the average humidity predicted from the input layer with six input nodes). Particularly, the long short-term memory model is is found to be more accurate in forecasting daily levels than other neural network models in temperature and humidity forecastings. Our result may provide a computer-simuation basis for the necessity of exploring and develping a novel neural network evaluation method in the future.

cs.LG↗

arXiv2021

Dynamical prediction of two meteorological factors using the deep neural network and the long short term memory $(1)$

It is important to calculate and analyze temperature and humidity prediction accuracies among quantitative meteorological forecasting. This study manipulates the extant neural network methods to foster the predictive accuracy. To achieve such tasks, we analyze and explore the predictive accuracy and performance in the neural networks using two combined meteorological factors (temperature and humidity). Simulated studies are performed by applying the artificial neural network (ANN), deep neural network (DNN), extreme learning machine (ELM), long short-term memory (LSTM), and long short-term memory with peephole connections (LSTM-PC) machine learning methods, and the accurate prediction value are compared to that obtained from each other methods. Data are extracted from low frequency time-series of ten metropolitan cities of South Korea from March 2014 to February 2020 to validate our observations. To test the robustness of methods, the error of LSTM is found to outperform that of the other four methods in predictive accuracy. Particularly, as testing results, the temperature prediction of LSTM in summer in Tongyeong has a root mean squared error (RMSE) value of 0.866 lower than that of other neural network methods, while the mean absolute percentage error (MAPE) value of LSTM for humidity prediction is 5.525 in summer in Mokpo, significantly better than other metropolitan cities.

physics.ao-ph↗

arXiv2017

Effects of pairing correlations on the neutron skin thickness and the symmetry energy

We investigated effects of pairing correlations on the neutron skin thickness and the symmetry energy of finite nuclei. In this calculation we used Hartree-Fock-Bogoliubov (HFB) method with Skyrme forces and effective pairing interactions. The results have been compared with available experimental data, Hartree-Fock (HF) results as well as the predictions by droplet model (DM). Finally, our discussion was extended to study of the pairing interaction in nuclear matter. Roles of isospin T = 0 pairing in the nuclear matter were also discussed.

nucl-th↗

arXiv2006

The art of fitting financial time series with Levy stable distributions

This paper illustrates a procedure for fitting financial data with $α$-stable distributions. After using all the available methods to evaluate the distribution parameters, one can qualitatively select the best estimate and run some goodness-of-fit tests on this estimate, in order to quantitatively assess its quality. It turns out that, for the two investigated data sets (MIB30 and DJIA from 2000 to present), an $α$-stable fit of log-returns is reasonably good.

physics.data-an↗

arXiv2006

Collective Political Opinion Formation in Nonlinear Social Interaction

We have presented a numerical model of a collective opinion formation procedure to explain political phenomena such as two-party and multi-party systems in politics, political unrest, military coup d'etats and netizen revolutions. Nonlinear interaction with binary and independent decision making processes can yield various collective behaviors or collective political opinions. Statistical physics and nonlinear dynamics may provide useful tools to study various socio-political dynamics.

physics.soc-ph↗

arXiv2005

Dynamical Structures of High-Frequency Financial Data

We study the dynamical behavior of high-frequency data from the Korean Stock Price Index (KOSPI) using the movement of returns in Korean financial markets. The dynamical behavior for a binarized series of our models is not completely random. The conditional probability is numerically estimated from a return series of KOSPI tick data. Non-trivial probability structures can be constituted from binary time series of autoregressive (AR), logit, and probit models, for which the Akaike Information Criterion shows a minimum value at the 15th order. From our results, we find that the value of the correct match ratio for the AR model is slightly larger than the findings of other models.

physics.soc-ph↗

arXiv2005

Dynamical Stochastic Processes of Returns in Financial Markets

We study the evolution of probability distribution functions of returns, from the tick data of the Korean treasury bond (KTB) futures and the S$&$P 500 stock index, which can be described by means of the Fokker-Planck equation. We show that the Fokker-Planck equation and the Langevin equation from the estimated Kramers-Moyal coefficients are estimated directly from the empirical data. By analyzing the statistics of the returns, we present quantitatively the deterministic and random influences on financial time series for both markets, for which we can give a simple physical interpretation. We particularly focus on the diffusion coefficient that may be significantly important for the creation of a portfolio.

physics.soc-ph↗

arXiv2005

Reaction-diffusion processes of three species on small-world networks

We study the decay process for the reaction-diffusion process of three species on the small-world network. The decay process is manipulated from the deterministic rate equation of three species in the reaction-diffusion system. The particle density and the global reaction rate on a two dimensional small-world network adding new random links is discussed numerically, and the global reaction rate before and after the crossover is also found by means of the Monte Carlo simulation. The time-dependent global reaction rate scales as a power law with the scaling exponent 0.66 at early time regime while it scales with -0.50 at long time regime, in all four cases of the added probability $p=0.2-0.8$. Especially, our result presented is compared with the numerical calculation of regular networks.

cond-mat.stat-mech↗

arXiv2005

Dynamical Minority Games in Futures Exchange Markets

We introduce the minority game theory for two kinds of the Korean treasury bond (KTB) in Korean futures exchange markets. Since we discuss numerically the standard deviation and the global efficiency for an arbitrary strategy, our case is found to be approximate to the majority game. Our result presented will be compared with numerical findings for the well-known minority and majority game models.

physics.soc-ph↗

arXiv2005

Financial Networks in the Korean Stock Exchange Market

We investigate the financial network in the Korean stock exchange (KSE) market, using both numerical simulations and scaling arguments. We estimate the cross-correlation on the stock price exchanges of all companies listed on the the Korean stock exchange market, where all companies are fully connected via weighted links, by introducing a weighted random graph. The degree distribution and the edge density are discussed numerically from the market graph, and the statistical analysis for the degree distribution of vertices is particularly found to approximately follow the power law.

physics.soc-ph↗

arXiv2004

Power Law Distributions for Stock Prices in Financial Markets

We study the rank distribution, the cumulative probability, and the probability density of returns of stock prices of listed firms traded in four stock markets. We find that the rank distribution and the cumulative probability of stock prices traded in are consistent approximately with the Zipf's law or a power law. It is also obtained that the probability density of normalized returns for listed stocks almost has the form of the exponential function. Our results are compared with those of other numerical calculations.

cond-mat.other↗

arXiv2004

Dynamical Volatilities for Yen-Dollar Exchange Rates

We study the continuous time random walk theory from financial tick data of the yen-dollar exchange rate transacted at the Japanese financial market. The dynamical behavior of returns and volatilities in this case is particularly treated at the long-time limit. We find that the volatility for prices shows a power-law with anomalous scaling exponent k = 0.96 (one minute) and 0.86 (ten minutes), and that our behavior occurs in the subdiffusive process. Our result presented will be compared with that of recent numerical calculations.

cond-mat.other↗

arXiv2004

Phase Transition of Dynamical Herd Behaviors in Financial Markets

We study the phase transition of dynamical herd behaviors for the yen-dollar exchange rate in the Japanese financial market. It is obtained that the probability distribution of returns satisfies the power-law behavior with three different values of the scaling exponent 3.11 (one time lag $τ$ = 1 minute), 2.81 (30 minutes), and 2.29 (1 hour). The crash regime in which the probabilty density increases with the increasing return appears in the case of $τ$ < 30 minutes, while it occurs no financial crash at $τ$ > 30 minutes. it is especially obtained that our dynamical herd behavior exhibits the phase transition at one time lag $τ$ = 30 minutes.

cond-mat.stat-mech↗

arXiv2004

Zipf's Law Distributions for Korean Stock Prices

This paper investigates the rank distribution, cumulative probability, and probability density of price returns for the stocks traded in the KSE and the KOSDAQ market. This research demonstrates that the rank distribution is consistent approximately with the Zipf's law with exponent $α= -1.00$ (KSE) and -1.31 (KOSDAQ), similar that of stock prices traded on the TSE. In addition, the cumulative probability distribution follows a power law with scaling exponent $β= -1.23$ (KSE) and -1.45 (KOSDAQ). In particular, the evidence displays that the probability density of normalized price returns for two kinds of assets almost has the form of an exponential function, similar to the result in the TSE and the NYSE.

cond-mat.stat-mech↗

arXiv2004

Multifractal Measures for the Yen-Dollar Exchange Rate

We study the tick dynamical behavior of the yen-dollar exchange rate using the rescaled range analysis in financial market. It is found that the multifractal Hurst exponents with the short and long-run memory effects can be obtained from the yen-dollar exchange rate. This exists one crossover for the Hurst exponents at charateristic time scales, while the bond futures exists no crossover. Particularly, it is shown that the probability distribution of the yen-dollar exchange rate has one form of the Lorentz distribution rather than fat-tailed properties, which is similar to that of for the won-dollar exchange rate.

cond-mat.stat-mech↗

arXiv2004

Herd Behaviors in Financial Markets

We investigate the herd behavior of returns for the yen-dollar exchange rate in the Japanese financial market. It is obtained that the probability distribution $P(R)$ of returns $R$ satisfies the power-law behavior $P(R) \simeq R^{-β}$ with the exponents $ β=3.11$(the time interval $τ=$ one minute) and 3.36($τ=$ one day). The informational cascade regime appears in the herding parameter $H\ge 2.33$ at $τ=$ one minute, while it occurs no herding at $τ=$ one day. Especially, we find that the distribution of normalized returns shows a crossover to a Gaussian distribution at one time step $Δt=1$ day.

cond-mat.stat-mech↗