arXiv subjects

Dae-Won Kim

Publications and source records attributed to Dae-Won Kim.

36 records · Page 2Linked to original sources

arXiv2018

Exploring the Variability of the Flat Spectrum Radio Source 1633+382. II: Physical Properties

The flat spectrum radio quasar 1633+382 (4C~38.41) showed a significant increase of its radio flux density during the period 2012 March - 2015 August which correlates with gamma-ray flaring activity. Multi-frequency simultaneous VLBI observations were conducted as part of the interferometric monitoring of gamma-ray bright active galactic nuclei (iMOGABA) program and supplemented with additional radio monitoring observations with the OVRO 40m telescope, the Boston University VLBI program, and the Submillimeter Array. The epochs of the maxima for the two largest gamma-ray flares coincide with the ejection of two respective new VLBI components. Analysis of the spectral energy distribution indicates a higher turnover frequency after the flaring events. The evolution of the flare in the turnover frequency - turnover flux density plane probes the adiabatic losses in agreement with the shock-in-jet model. Derived synchrotron self absorption magnetic fields, of the order of 0.1mG, do not seem to dramatically change during the flares, and are much smaller, by a factor $10^4$, than the estimated equipartition magnetic fields, indicating that the source of the flare may be associated with a particle dominated emitting region.

astro-ph.HE↗

arXiv2017

The Power of Simultaneous Multi-frequency Observations for mm-VLBI: Beyond Frequency Phase Transfer

Atmospheric propagation effects at millimeter wavelengths can significantly alter the phases of radio signals and reduce the coherence time, putting tight constraints on high frequency Very Long Baseline Interferometry (VLBI) observations. In previous works, it has been shown that non-dispersive (e.g. tropospheric) effects can be calibrated with the frequency phase transfer (FPT) technique. The coherence time can thus be significantly extended. Ionospheric effects, which can still be significant, remain however uncalibrated after FPT as well as the instrumental effects. In this work, we implement a further phase transfer between two FPT residuals (i.e. so-called FPT-square) to calibrate the ionospheric effects based on their frequency dependence. We show that after FPT-square, the coherence time at 3 mm can be further extended beyond 8~hours, and the residual phase errors can be sufficiently canceled by applying the calibration of another source, which can have a large angular separation from the target (>20 deg) and significant temporal gaps. Calibrations for all-sky distributed sources with a few calibrators are also possible after FPT-square. One of the strengths and uniqueness of this calibration strategy is the suitability for high-frequency all-sky survey observations including very weak sources. We discuss the introduction of a pulse calibration system in the future to calibrate the remaining instrumental effects and allowing the possibility of imaging the source structure at high frequencies with FPT-square, where all phases are fully calibrated without involving any additional sources.

astro-ph.IM↗

arXiv2017

Exploring the Variability of the Flat Spectrum Radio Source 1633+382. I. Phenomenology of the Light Curves

We present multi-frequency simultaneous VLBI radio observations of the flat spectrum radio quasar 1633+382 (4C~38.41) as part of the interferometric monitoring of gamma-ray bright active galactic nuclei (iMOGABA) program combined with additional observations in radio, optical, X-rays and $γ-$rays carried out between the period 2012 March - 2015 August. The monitoring of this source reveals a significant long-lived increase in its activity since approximately two years in the radio bands, which correlates with a similar increase on all other bands from sub-millimeter to $γ-$rays. A significant correlation is also found between radio fluxes and simultaneous spectral indices during this period. The study of the discrete correlation function (DCF) indicates time lags smaller than the $\sim40$ days uncertainties among both radio bands and also high-energy bands, and a time lag of $\sim$70 days, with $γ-$rays leading radio. We interpret that the high-energy and radio fluxes are arising from different emitting regions, located at $1\pm12$ and $40\pm13$ pc from the central engine respectively.

astro-ph.HE↗

arXiv2017

The Millimeter-Radio Emission of BL Lacertae During Two gamma-ray Outbursts

We present a study of the inexplicit connection between radio jet activity and gamma-ray emission of BL Lacertae (BL Lac; 2200+420). We analyze the long-term millimeter activity of BL Lac via interferometric observations with the Korean VLBI Network (KVN) obtained at 22, 43, 86, and 129 GHz simultaneously over three years (from January 2013 to March 2016); during this time, two gamma-ray outbursts (in November 2013 and March 2015) can be seen in gamma-ray light curves obtained from Fermi observations. The KVN radio core is optically thick at least up to 86 GHz; there is indication that it might be optically thin at higher frequencies. To first order, the radio light curves decay exponentially over the time span covered by our observations, with decay timescales of 411+/-85 days, 352+/-79 days, 310+/-57 days, and 283+/-55 days at 22, 43, 86, and 129 GHz, respectively. Assuming synchrotron cooling, a cooling time of around one year is consistent with magnetic field strengths B~2microT and electron Lorentz factors gamma~10,000. Taking into account that our formal measurement errors include intrinsic variability and thus over-estimate the statistical uncertainties, we find that the decay timescale tau scales with frequency nu like tau~nu^{-0.2}. This relation is much shallower than the one expected from opacity effects (core shift), but in agreement with the (sub-)mm radio core being a standing recollimation shock. We do not find convincing radio flux counterparts to the gamma$ray outbursts. The spectral evolution is consistent with the `generalized shock model' of Valtaoja et al. (1992). A temporary increase in the core opacity and the emergence of a knot around the time of the second gamma-ray event indicate that this gamma-ray outburst might be an `orphan' flare powered by the `ring of fire' mechanism.

astro-ph.GA↗

arXiv2017

Interferometric Monitoring of Gamma-ray Bright AGNs: S5 0716+714

We present the results of very long baseline interferometry (VLBI) observations of gamma-ray bright blazar S5 0716+714 using the Korean VLBI Network (KVN) at the 22, 43, 86, and 129 GHz bands, as part of the Interferometric Monitoring of Gamma-ray Bright AGNs (iMOGABA) KVN key science program. Observations were conducted in 29 sessions from January 16, 2013 to March 1, 2016, with the source being detected and imaged at all available frequencies. In all epochs, the source was compact on the milliarcsecond (mas) scale, yielding a compact VLBI core dominating the synchrotron emission on these scales. Based on the multi-wavelength data between 15 GHz (Owens Valley Radio Observatory) and 230 GHz (Submillimeter Array), we found that the source shows multiple prominent enhancements of the flux density at the centimeter (cm) and millimeter (mm) wavelengths, with mm enhancements leading cm enhancements by -16$\pm$8 days. The turnover frequency was found to vary between 21 to 69GHz during our observations. By assuming a synchrotron self-absorption model for the relativistic jet emission in S5 0716+714, we found the magnetic field strength in the mas emission region to be $\le$5 mG during the observing period, yielding a weighted mean of 1.0$\pm$0.6 mG for higher turnover frequencies (e.g., >45 GHz).

astro-ph.GA↗

arXiv2016

Interferometric Monitoring of Gamma-ray Bright AGNs I: Results of Single-epoch Multifrequency Observations

We present results of single-epoch very long baseline interferometry (VLBI) observations of gamma-ray bright active galactic nuclei (AGNs) using the Korean VLBI Network (KVN) at 22, 43, 86, and 129~GHz bands, which are part of a KVN key science program, Interferometric Monitoring of Gamma-ray Bright AGNs (iMOGABA). We selected a total of 34 radio-loud AGNs of which 30 sources are gamma-ray bright AGNs with flux densities of $>6\times10^{-10}$~ph~cm$^{-2}$~s$^{-1}$. Single-epoch multi-frequency VLBI observations of the target sources were conducted during a 24-hr session on 2013 November 19 and 20. All observed sources were detected and imaged at all frequency bands with or without a frequency phase transfer technique which enabled the imaging of 12 faint sources at 129~GHz, except for one source. Many of the target sources are resolved on milliarcsecond scales, yielding a core-jet structure with the VLBI core dominating the synchrotron emission on the milliarcsecond scale. CLEAN flux densities of the target sources are 0.43-28~Jy, 0.32-21~Jy, 0.18-11~Jy, and 0.35-8.0~Jy in the 22, 43, 86, and 129~GHz bands, respectively.

astro-ph.GA↗

arXiv2016

Repetitive Patterns in Rapid Optical Variations in the Nearby Black-hole Binary V404 Cygni

How black holes accrete surrounding matter is a fundamental, yet unsolved question in astrophysics. It is generally believed that matter is absorbed into black holes via accretion disks, the state of which depends primarily on the mass-accretion rate. When this rate approaches the critical rate (the Eddington limit), thermal instability is supposed to occur in the inner disc, causing repetitive patterns of large-amplitude X-ray variability (oscillations) on timescales of minutes to hours. In fact, such oscillations have been observed only in sources with a high mass accretion rate, such as GRS 1915+105. These large-amplitude, relatively slow timescale, phenomena are thought to have physical origins distinct from X-ray or optical variations with small amplitudes and fast ($\lesssim$10 sec) timescales often observed in other black hole binaries (e.g., XTE J1118+480 and GX 339-4). Here we report an extensive multi-colour optical photometric data set of V404 Cygni, an X-ray transient source containing a black hole of nine solar masses (and a conpanion star) at a distance of 2.4 kiloparsecs. Our data show that optical oscillations on timescales of 100 seconds to 2.5 hours can occur at mass-accretion rates more than ten times lower than previously thought. This suggests that the accretion rate is not the critical parameter for inducing inner-disc instabilities. Instead, we propose that a long orbital period is a key condition for these large-amplitude oscillations, because the outer part of the large disc in binaries with long orbital periods will have surface densities too low to maintain sustained mass accretion to the inner part of the disc. The lack of sustained accretion -- not the actual rate -- would then be the critical factor causing large-amplitude oscillations in long-period systems.

astro-ph.HE↗

arXiv2015

A Package for the Automated Classification of Periodic Variable Stars

We present a machine learning package for the classification of periodic variable stars. Our package is intended to be general: it can classify any single band optical light curve comprising at least a few tens of observations covering durations from weeks to years, with arbitrary time sampling. We use light curves of periodic variable stars taken from OGLE and EROS-2 to train the model. To make our classifier relatively survey-independent, it is trained on 16 features extracted from the light curves (e.g. period, skewness, Fourier amplitude ratio). The model classifies light curves into one of seven superclasses - Delta Scuti, RR Lyrae, Cepheid, Type II Cepheid, eclipsing binary, long-period variable, non-variable - as well as subclasses of these, such as ab, c, d, and e types for RR Lyraes. When trained to give only superclasses, our model achieves 0.98 for both recall and precision as measured on an independent validation dataset (on a scale of 0 to 1). When trained to give subclasses, it achieves 0.81 for both recall and precision. In order to assess classification performance of the subclass model, we applied it to the MACHO, LINEAR, and ASAS periodic variables, which gave recall/precision of 0.92/0.98, 0.89/0.96, and 0.84/0.88, respectively. We also applied the subclass model to Hipparcos periodic variable stars of many other variability types that do not exist in our training set, in order to examine how much those types degrade the classification performance of our target classes. In addition, we investigate how the performance varies with the number of data points and duration of observations. We find that recall and precision do not vary significantly if the number of data points is larger than 80 and the duration is more than a few weeks. The classifier software of the subclass model is available from the GitHub repository (https://goo.gl/xmFO6Q).

astro-ph.IM↗

arXiv2015

Interferometric Monitoring of Gamma-ray Bright Active Galactic Nuclei II: Frequency Phase Transfer

The Interferometric Monitoring of Gamma-ray Bright Active galactic nuclei (iMOGABA) program provides not only simultaneous multifrequency observations of bright gamma-ray detected active galactic nuclei (AGN), but also covers the highest Very Large Baseline Interferometry (VLBI) frequencies ever being systematically monitored, up to 129 GHz. However, observation and imaging of weak sources at the highest observed frequencies is very challenging. In the second paper in this series, we evaluate the viability of the frequency phase transfer technique to iMOGABA in order to obtain larger coherence time at the higher frequencies of this program (86 and 129 GHz) and image additional sources that were not detected using standard techniques. We find that this method is applicable to the iMOGABA program even under non-optimal weather conditions.

astro-ph.IM↗

arXiv2015

Supervised detection of anomalous light-curves in massive astronomical catalogs

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. To process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new method to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all the information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. Our method is suitable for exploring massive datasets given that the training process is performed offline. We tested our algorithm on 20 millions light-curves from the MACHO catalog and generated a list of anomalous candidates. We divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post analysis stage by perfoming a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables and X-ray sources. For some outliers there were no additional information. Among them we identified three unknown variability types and few individual outliers that will be followed up for a deeper analysis.

cs.CE↗

arXiv2014

The EPOCH Project: I. Periodic variable stars in the EROS-2 LMC database

The EPOCH (EROS-2 periodic variable star classification using machine learning) project aims to detect periodic variable stars in the EROS-2 light curve database. In this paper, we present the first result of the classification of periodic variable stars in the EROS-2 LMC database. To classify these variables, we first built a training set by compiling known variables in the Large Magellanic Cloud area from the OGLE and MACHO surveys. We crossmatched these variables with the EROS-2 sources and extracted 22 variability features from 28 392 light curves of the corresponding EROS-2 sources. We then used the random forest method to classify the EROS-2 sources in the training set. We designed the model to separate not only $δ$ Scuti stars, RR Lyraes, Cepheids, eclipsing binaries, and long-period variables, the superclasses, but also their subclasses, such as RRab, RRc, RRd, and RRe for RR Lyraes, and similarly for the other variable types. The model trained using only the superclasses shows 99% recall and precision, while the model trained on all subclasses shows 87% recall and precision. We applied the trained model to the entire EROS-2 LMC database, which contains about 29 million sources, and found 117 234 periodic variable candidates. Out of these 117 234 periodic variables, 55 285 have not been discovered by either OGLE or MACHO variability studies. This set comprises 1 906 $δ$ Scuti stars, 6 607 RR Lyraes, 638 Cepheids, 178 Type II Cepheids, 34 562 eclipsing binaries, and 11 394 long-period variables. A catalog of these EROS-2 LMC periodic variable stars will be available online at http://stardb.yonsei.ac.kr and at the CDS website (http://vizier.u-strasbg.fr/viz-bin/VizieR).

astro-ph.IM↗

arXiv2013

Assessment of stochastic and deterministic models of 6304 quasar lightcurves from SDSS Stripe 82

The optical light curves of many quasars show variations of tenths of a magnitude or more on time scales of months to years. This variation often cannot be described well by a simple deterministic model. We perform a Bayesian comparison of over 20 deterministic and stochastic models on 6304 QSO light curves in SDSS Stripe 82. We include the damped random walk (or Ornstein-Uhlenbeck [OU] process), a particular type of stochastic model which recent studies have focused on. Further models we consider are single and double sinusoids, multiple OU processes, higher order continuous autoregressive processes, and composite models. We find that only 29 out of 6304 QSO lightcurves are described significantly better by a deterministic model than a stochastic one. The OU process is an adequate description of the vast majority of cases (6023). Indeed, the OU process is the best single model for 3462 light curves, with the composite OU process/sinusoid model being the best in 1706 cases. The latter model is the dominant one for brighter/bluer QSOs. Furthermore, a non-negligible fraction of QSO lightcurves show evidence that not only the mean is stochastic but the variance is stochastic, too. Our results confirm earlier work that QSO light curves can be described with a stochastic model, but place this on a firmer footing, and further show that the OU process is preferred over several other stochastic and deterministic models. Of course, there may well exist yet better (deterministic or stochastic) models which have not been considered here.

astro-ph.CO↗

arXiv2013

An improved quasar detection method in EROS-2 and MACHO LMC datasets

We present a new classification method for quasar identification in the EROS-2 and MACHO datasets based on a boosted version of Random Forest classifier. We use a set of variability features including parameters of a continuous auto regressive model. We prove that continuous auto regressive parameters are very important discriminators in the classification process. We create two training sets (one for EROS-2 and one for MACHO datasets) using known quasars found in the LMC. Our model's accuracy in both EROS-2 and MACHO training sets is about 90% precision and 86% recall, improving the state of the art models accuracy in quasar detection. We apply the model on the complete, including 28 million objects, EROS-2 and MACHO LMC datasets, finding 1160 and 2551 candidates respectively. To further validate our list of candidates, we crossmatched our list with a previous 663 known strong candidates, getting 74% of matches for MACHO and 40% in EROS-2. The main difference on matching level is because EROS-2 is a slightly shallower survey which translates to significantly lower signal-to-noise ratio lightcurves.

astro-ph.IM↗

arXiv2013

Statistical Properties of Galactic δ Scuti Stars: Revisited

We present statistical characteristics of 1,578 δ Scuti stars including nearby field stars and cluster member stars within the Milky Way. We obtained 46% of these stars (718 stars) from the works done by Rodríguez and collected the remaining 54% stars (860 stars) from other literatures. We updated the entries with the latest information of sky coordinate, color, rotational velocity, spectral type, period, amplitude and binarity. The majority of our sample are well characterized in terms of typical period range (0.02-0.25 days), pulsation amplitudes (<0.5 mag) and spectral types (A-F type). Given this list of δ Scuti stars, we examined relations between their physical properties (i.e., periods, amplitudes, spectral types and rotational velocities) for field stars and cluster members, and confirmed that the correlations of properties are not significantly different from those reported in the Rodríguez's works. All the δ Scuti stars are cross-matched with several X-ray and UV catalogs, resulting in 27 X-ray and 41 UV-only counterparts. These counterparts are interesting targets for further study because of their rarity and uniqueness in showing δ Scuti-type variability and X-ray/UV emission at the same time. The compiled catalog can be accessed through the web interface http://stardb.yonsei.ac.kr/DeltaScuti

astro-ph.SR↗

arXiv2012

Detecting Variability in Massive Astronomical Time-Series Data II: Variable Candidates in the Northern Sky Variability Survey

We present variability analysis of data from the Northern Sky Variability Survey (NSVS). Using the clustering method which defines variable candidates as outliers from large clusters, we cluster 16,189,040 light curves, having data points at more than 15 epochs, as variable and non-variable candidates in 638 NSVS fields. Variable candidates are selected depending on how strongly they are separated from the largest cluster and how rarely they are grouped together in eight dimensional space spanned by variability indices. All NSVS light curves are also cross-correlated to the Infrared Astronomical Satellite, AKARI, Two Micron All Sky Survey, Sloan Digital Sky Survey (SDSS), and Galaxy Evolution Explorer objects as well as known objects in the SIMBAD database. The variability analysis and cross-correlation results are provided in a public online database which can be used to select interesting objects for further investigation. Adopting conservative selection criteria for variable candidates, we find about 1.8 million light curves as possible variable candidates in the NSVS data, corresponding to about 10% of our entire NSVS samples. Multi-wavelength colors help us find specific types of variability among the variable candidates. Moreover, we also use morphological classification from other surveys such as SDSS to suppress spurious cases caused by blending objects or extended sources due to the low angular resolution of the NSVS.

astro-ph.SR↗

arXiv2011

A Refined QSO Selection Method Using Diagnostics Tests: 663 QSO Candidates in the LMC

We present 663 QSO candidates in the Large Magellanic Cloud (LMC) selected using multiple diagnostics. We started with a set of 2,566 QSO candidates from our previous work selected using time variability of the MACHO LMC lightcurves. We then obtained additional information for the candidates by crossmatching them with the Spitzer SAGE, the MACHO UBVI, the 2MASS, the Chandra and the XMM catalogs. Using this information, we specified six diagnostic features based on mid-IR colors, photometric redshifts using SED template fitting, and X-ray luminosities in order to further discriminate high confidence QSO candidates in the absence of spectra information. We then trained a one-class SVM (Support Vector Machine) model using the diagnostics features of the confirmed 58 MACHO QSOs. We applied the trained model to the original candidates and finally selected 663 high confidence QSO candidates. Furthermore, we crossmatched these 663 QSO candidates with the newly confirmed 144 QSOs and 275 non-QSOs in the LMC fields. On the basis of the counterpart analysis, we found that the false positive rate is less than 1%.

astro-ph.CO↗

arXiv2011

QSO Selection Algorithm Using Time Variability and Machine Learning: Selection of 1,620 QSO Candidates from MACHO LMC Database

We present a new QSO selection algorithm using a Support Vector Machine (SVM), a supervised classification method, on a set of extracted times series features including period, amplitude, color, and autocorrelation value. We train a model that separates QSOs from variable stars, non-variable stars and microlensing events using 58 known QSOs, 1,629 variable stars and 4,288 non-variables using the MAssive Compact Halo Object (MACHO) database as a training set. To estimate the efficiency and the accuracy of the model, we perform a cross-validation test using the training set. The test shows that the model correctly identifies ~80% of known QSOs with a 25% false positive rate. The majority of the false positives are Be stars. We applied the trained model to the MACHO Large Magellanic Cloud (LMC) dataset, which consists of 40 million lightcurves, and found 1,620 QSO candidates. During the selection none of the 33,242 known MACHO variables were misclassified as QSO candidates. In order to estimate the true false positive rate, we crossmatched the candidates with astronomical catalogs including the Spitzer Surveying the Agents of a Galaxy's Evolution (SAGE) LMC catalog and a few X-ray catalogs. The results further suggest that the majority of the candidates, more than 70%, are QSOs.

astro-ph.IM↗

arXiv2009

De-Trending Time Series for Astronomical Variability Surveys

We present a de-trending algorithm for the removal of trends in time series. Trends in time series could be caused by various systematic and random noise sources such as cloud passages, changes of airmass, telescope vibration or CCD noise. Those trends undermine the intrinsic signals of stars and should be removed. We determine the trends from subsets of stars that are highly correlated among themselves. These subsets are selected based on a hierarchical tree clustering algorithm. A bottom-up merging algorithm based on the departure from normal distribution in the correlation is developed to identify subsets, which we call clusters. After identification of clusters, we determine a trend per cluster by weighted sum of normalized light-curves. We then use quadratic programming to de-trend all individual light-curves based on these determined trends. Experimental results with synthetic light-curves containing artificial trends and events are presented. Results from other de-trending methods are also compared. The developed algorithm can be applied to time series for trend removal in both narrow and wide field astronomy.

astro-ph↗