arXiv subjects

Junhan Kim

Publications and source records attributed to Junhan Kim.

At least 37 records · Page 2Linked to original sources

arXiv2022

COMAP Early Science: IV. Power Spectrum Methodology and Results

We present the power spectrum methodology used for the first-season COMAP analysis, and assess the quality of the current data set. The main results are derived through the Feed-feed Pseudo-Cross-Spectrum (FPXS) method, which is a robust estimator with respect to both noise modeling errors and experimental systematics. We use effective transfer functions to take into account the effects of instrumental beam smoothing and various filter operations applied during the low-level data processing. The power spectra estimated in this way have allowed us to identify a systematic error associated with one of our two scanning strategies, believed to be due to residual ground or atmospheric contamination. We omit these data from our analysis and no longer use this scanning technique for observations. We present the power spectra from our first season of observing and demonstrate that the uncertainties are integrating as expected for uncorrelated noise, with any residual systematics suppressed to a level below the noise. Using the FPXS method, and combining data on scales $k=0.051-0.62 \,\mathrm{Mpc}^{-1}$ we estimate $P_\mathrm{CO}(k) = -2.7 \pm 1.7 \times 10^4μ\textrm{K}^2\mathrm{Mpc}^3$, the first direct 3D constraint on the clustering component of the CO(1-0) power spectrum in the literature.

astro-ph.CO↗

arXiv2022

COMAP Early Science: V. Constraints and Forecasts at $z \sim 3$

We present the current state of models for the $z\sim3$ carbon monoxide (CO) line-intensity signal targeted by the CO Mapping Array Project (COMAP) Pathfinder in the context of its early science results. Our fiducial model, relating dark matter halo properties to CO luminosities, informs parameter priors with empirical models of the galaxy-halo connection and previous CO(1-0) observations. The Pathfinder early science data spanning wavenumbers $k=0.051$-$0.62\,$Mpc$^{-1}$ represent the first direct 3D constraint on the clustering component of the CO(1-0) power spectrum. Our 95% upper limit on the redshift-space clustering amplitude $A_{\rm clust}\lesssim70\,μ$K$^2$ greatly improves on the indirect upper limit of $420\,μ$K$^2$ reported from the CO Power Spectrum Survey (COPSS) measurement at $k\sim1\,$Mpc$^{-1}$. The COMAP limit excludes a subset of models from previous literature, and constrains interpretation of the COPSS results, demonstrating the complementary nature of COMAP and interferometric CO surveys. Using line bias expectations from our priors, we also constrain the squared mean line intensity-bias product, $\langle{Tb}\rangle^2\lesssim50\,μ$K$^2$, and the cosmic molecular gas density, $ρ_\text{H2}<2.5\times10^8\,M_\odot\,$Mpc$^{-3}$ (95% upper limits). Based on early instrument performance and our current CO signal estimates, we forecast that the five-year Pathfinder campaign will detect the CO power spectrum with overall signal-to-noise of 9-17. Between then and now, we also expect to detect the CO-galaxy cross-spectrum using overlapping galaxy survey data, enabling enhanced inferences of cosmic star-formation and galaxy-evolution history.

astro-ph.CO↗

arXiv2021

Semantic Feature Extraction for Generalized Zero-shot Learning

Generalized zero-shot learning (GZSL) is a technique to train a deep learning model to identify unseen classes using the attribute. In this paper, we put forth a new GZSL technique that improves the GZSL classification performance greatly. Key idea of the proposed approach, henceforth referred to as semantic feature extraction-based GZSL (SE-GZSL), is to use the semantic feature containing only attribute-related information in learning the relationship between the image and the attribute. In doing so, we can remove the interference, if any, caused by the attribute-irrelevant information contained in the image feature. To train a network extracting the semantic feature, we present two novel loss functions, 1) mutual information-based loss to capture all the attribute-related information in the image feature and 2) similarity-based loss to remove unwanted attribute-irrelevant information. From extensive experiments using various datasets, we show that the proposed SE-GZSL technique outperforms conventional GZSL approaches by a large margin.

cs.CV↗

arXiv2021

COMAP Early Science: III. CO Data Processing

We describe the first season COMAP analysis pipeline that converts raw detector readouts to calibrated sky maps. This pipeline implements four main steps: gain calibration, filtering, data selection, and map-making. Absolute gain calibration relies on a combination of instrumental and astrophysical sources, while relative gain calibration exploits real-time total-power variations. High efficiency filtering is achieved through spectroscopic common-mode rejection within and across receivers, resulting in nearly uncorrelated white noise within single-frequency channels. Consequently, near-optimal but biased maps are produced by binning the filtered time stream into pixelized maps; the corresponding signal bias transfer function is estimated through simulations. Data selection is performed automatically through a series of goodness-of-fit statistics, including $χ^2$ and multi-scale correlation tests. Applying this pipeline to the first-season COMAP data, we produce a dataset with very low levels of correlated noise. We find that one of our two scanning strategies (the Lissajous type) is sensitive to residual instrumental systematics. As a result, we no longer use this type of scan and exclude data taken this way from our Season 1 power spectrum estimates. We perform a careful analysis of our data processing and observing efficiencies and take account of planned improvements to estimate our future performance. Power spectrum results derived from the first-season COMAP maps are presented and discussed in companion papers.

astro-ph.IM↗

arXiv2021

COMAP Early Science: II. Pathfinder Instrument

Line intensity mapping (LIM) is a new technique for tracing the global properties of galaxies over cosmic time. Detection of the very faint signals from redshifted carbon monoxide (CO), a tracer of star formation, pushes the limits of what is feasible with a total-power instrument. The CO Mapping Project (COMAP) Pathfinder is a first-generation instrument aiming to prove the concept and develop the technology for future experiments, as well as delivering early science products. With 19 receiver channels in a hexagonal focal plane arrangement on a 10.4 m antenna, and an instantaneous 26-34 GHz frequency range with 2 MHz resolution, it is ideally suited to measuring CO($J$=1-0) from $z\sim3$. In this paper we discuss strategies for designing and building the Pathfinder and the challenges that were encountered. The design of the instrument prioritized LIM requirements over those of ancillary science. After a couple of years of operation, the instrument is well understood, and the first year of data is already yielding useful science results. Experience with this Pathfinder will drive the design of the next generations of experiments.

astro-ph.IM↗

arXiv2021

COMAP Early Science: I. Overview

The CO Mapping Array Project (COMAP) aims to use line intensity mapping of carbon monoxide (CO) to trace the distribution and global properties of galaxies over cosmic time, back to the Epoch of Reionization (EoR). To validate the technologies and techniques needed for this goal, a Pathfinder instrument has been constructed and fielded. Sensitive to CO(1-0) emission from $z=2.4$-$3.4$ and a fainter contribution from CO(2-1) at $z=6$-8, the Pathfinder is surveying $12$ deg$^2$ in a 5-year observing campaign to detect the CO signal from $z\sim3$. Using data from the first 13 months of observing, we estimate $P_\mathrm{CO}(k) = -2.7 \pm 1.7 \times 10^4μ\mathrm{K}^2 \mathrm{Mpc}^3$ on scales $k=0.051-0.62 \mathrm{Mpc}^{-1}$ - the first direct 3D constraint on the clustering component of the CO(1-0) power spectrum. Based on these observations alone, we obtain a constraint on the amplitude of the clustering component (the squared mean CO line temperature-bias product) of $\langle Tb\rangle^2<49$ $μ$K$^2$ - nearly an order-of-magnitude improvement on the previous best measurement. These constraints allow us to rule out two models from the literature. We forecast a detection of the power spectrum after 5 years with signal-to-noise ratio (S/N) 9-17. Cross-correlation with an overlapping galaxy survey will yield a detection of the CO-galaxy power spectrum with S/N of 19. We are also conducting a 30 GHz survey of the Galactic plane and present a preliminary map. Looking to the future of COMAP, we examine the prospects for future phases of the experiment to detect and characterize the CO signal from the EoR.

astro-ph.CO↗

arXiv2021

Synergies between the COMAP CO Line Intensity Mapping mission and a Lyα galaxy survey: How to probe the early universe with voxel based analysis of observational data

Line Intensity Mapping (LIM) offers a novel avenue to observe and characterize our universe. LIM data of CO spectral lines are becoming available, such as those obtained by the CO Mapping Array Project (COMAP). COMAP data can be used to probe the molecular gas content of the universe from the last stages of the Epoch of Reionization (EoR) ($z < 8.0$) to $z \sim 2.5$. In this work, we examine the prospects for deriving voxel-level statistical constraints on high-redshift galaxies from COMAP data by considering the additional information available from observations of LAEs galaxies using the Visible Integral-Field Replicable Unit Spectrograph (VIRUS) on the Hobby-Eberly Telescope (HET). We post-process the IllustrisTNG300 galaxy-formation simulation with a set of prescriptions to consistently determine CO and Ly$α$ line luminosities. The different line prescriptions span the uncertainty in the CO line luminosity according to current observations by the VLA high-z CO surveys and set the Ly$α$ emission to be compatible with observational LAE luminosity functions. We produce mock observations for the two surveys over a $(300\, {\rm Mpc})^3$ volume. These are then used to formulate and test methodologies for data analysis and to predict COMAP constraints on CO emission. We use combinations of masking, stacking, voxel intensity distribution (VID), and other statistics. We find that in combination with VIRUS/HET, a voxel-level analysis of the COMAP Pathfinder survey can detect and characterize the CO signal from $z\sim3$ and improve current constraints on the $z\sim6$ signal, identify individual voxels with bright CO(1-0) emission at $z\sim3$ and probe the redshift evolution of the CO emission. This study illustrates the potential of synergies between LIM and galaxy surveys both to improve the significance of a detection and to aid the interpretation of noisy LIM data.

astro-ph.GA↗

arXiv2021

Event Horizon Telescope observations of the jet launching and collimation in Centaurus A

Very-long-baseline interferometry (VLBI) observations of active galactic nuclei at millimeter wavelengths have the power to reveal the launching and initial collimation region of extragalactic radio jets, down to $10-100$ gravitational radii ($r_g=GM/c^2$) scales in nearby sources. Centaurus A is the closest radio-loud source to Earth. It bridges the gap in mass and accretion rate between the supermassive black holes (SMBHs) in Messier 87 and our galactic center. A large southern declination of $-43^{\circ}$ has however prevented VLBI imaging of Centaurus A below $λ1$cm thus far. Here, we show the millimeter VLBI image of the source, which we obtained with the Event Horizon Telescope at $228$GHz. Compared to previous observations, we image Centaurus A's jet at a tenfold higher frequency and sixteen times sharper resolution and thereby probe sub-lightday structures. We reveal a highly-collimated, asymmetrically edge-brightened jet as well as the fainter counterjet. We find that Centaurus A's source structure resembles the jet in Messier 87 on ${\sim}500r_g$ scales remarkably well. Furthermore, we identify the location of Centaurus A's SMBH with respect to its resolved jet core at $λ1.3$mm and conclude that the source's event horizon shadow should be visible at THz frequencies. This location further supports the universal scale invariance of black holes over a wide range of masses.

astro-ph.GA↗

arXiv2021

Probing Hot Gas Components of Circumgalactic Medium in Cosmological Simulations with the Thermal Sunyaev-Zel'dovich Effect

The thermal Sunyaev-Zel'dovich (tSZ) effect is a powerful tool with the potential for constraining directly the properties of the hot gas that dominates dark matter halos because it measures pressure and thus thermal energy density. Studying this hot component of the circumgalactic medium (CGM) is important because it is strongly impacted by star-formation and active galactic nuclei (AGN) activity in galaxies, participating in the feedback loop that regulates star and black hole mass growth in galaxies. We study the tSZ effect across a wide halo mass range using three cosmological hydrodynamical simulations: Illustris-TNG, EAGLE, and FIRE-2. Specifically, we present the scaling relation between tSZ signal and halo mass and radial profiles of gas density, temperature, and pressure for all three simulations. The analysis includes comparisons to Planck tSZ observations and to the thermal pressure profile inferred from the Atacama Cosmology Telescope (ACT) measurements. We compare these tSZ data to the simulations to interpret the measurements in terms of feedback and accretion processes in the CGM. We also identify as-yet unobserved potential signatures of these processes that may be visible in future measurements, which will have the capability of measuring tSZ signals to even lower masses. We also perform internal comparisons between runs with different physical assumptions. We conclude: (1) there is strong evidence for the impact of feedback at $R_{500}$ but that this impact decreases by $5R_{500}$, and (2) the thermodynamic profiles of the CGM are highly dependent on the implemented model, such as cosmic-ray or AGN feedback prescriptions.

astro-ph.GA↗

arXiv2021

Gradual Federated Learning with Simulated Annealing

Federated averaging (FedAvg) is a popular federated learning (FL) technique that updates the global model by averaging local models and then transmits the updated global model to devices for their local model update. One main limitation of FedAvg is that the average-based global model is not necessarily better than local models in the early stage of the training process so that FedAvg might diverge in realistic scenarios, especially when the data is non-identically distributed across devices and the number of data samples varies significantly from device to device. In this paper, we propose a new FL technique based on simulated annealing. The key idea of the proposed technique, henceforth referred to as \textit{simulated annealing-based FL} (SAFL), is to allow a device to choose its local model when the global model is immature. Specifically, by exploiting the simulated annealing strategy, we make each device choose its local model with high probability in early iterations when the global model is immature. From extensive numerical experiments using various benchmark datasets, we demonstrate that SAFL outperforms the conventional FedAvg technique in terms of the convergence speed and the classification accuracy.

cs.LG↗

arXiv2020

Gravitational Test Beyond the First Post-Newtonian Order with the Shadow of the M87 Black Hole

The 2017 Event Horizon Telescope (EHT) observations of the central source in M87 have led to the first measurement of the size of a black-hole shadow. This observation offers a new and clean gravitational test of the black-hole metric in the strong-field regime. We show analytically that spacetimes that deviate from the Kerr metric but satisfy weak-field tests can lead to large deviations in the predicted black-hole shadows that are inconsistent with even the current EHT measurements. We use numerical calculations of regular, parametric, non-Kerr metrics to identify the common characteristic among these different parametrizations that control the predicted shadow size. We show that the shadow-size measurements place significant constraints on deviation parameters that control the second post-Newtonian and higher orders of each metric and are, therefore, inaccessible to weak-field tests. The new constraints are complementary to those imposed by observations of gravitational waves from stellar-mass sources.

gr-qc↗

arXiv2020

On the Fundamental Recovery Limit of Orthogonal Least Squares

Orthogonal least squares (OLS) is a classic algorithm for sparse recovery, function approximation, and subset selection. In this paper, we analyze the performance guarantee of the OLS algorithm. Specifically, we show that OLS guarantees the exact reconstruction of any $K$-sparse vector in $K$ iterations, provided that a sensing matrix has unit $\ell_{2}$-norm columns and satisfies the restricted isometry property (RIP) of order $K+1$ with \begin{align*} δ_{K+1} &<C_{K} = \begin{cases} \frac{1}{\sqrt{K}}, & K=1, \\ \frac{1}{\sqrt{K+\frac{1}{4}}}, & K=2, \\ \frac{1}{\sqrt{K+\frac{1}{16}}}, & K=3, \\ \frac{1}{\sqrt{K}}, & K \ge 4. \end{cases} \end{align*} Furthermore, we show that the proposed guarantee is optimal in the sense that if $δ_{K+1} \ge C_{K}$, then there exists a counterexample for which OLS fails the recovery.

cs.IT↗

arXiv2020

Markov Chains for Horizons (MARCH). I. Identifying Biases in Fitting Theoretical Models to Event Horizon Telescope Observations

We introduce a new Markov Chain Monte Carlo (MCMC) algorithm with parallel tempering for fitting theoretical models of horizon-scale images of black holes to the interferometric data from the Event Horizon Telescope (EHT). The algorithm implements forms of the noise distribution in the data that are accurate for all signal-to-noise ratios. In addition to being trivially parallelizable, the algorithm is optimized for high performance, achieving 1 million MCMC chain steps in under 20 seconds on a single processor. We use synthetic data for the 2017 EHT coverage of M87 that are generated based on analytic as well as General Relativistic Magnetohydrodynamic (GRMHD) model images to explore several potential sources of biases in fitting models to sparse interferometric data. We demonstrate that a very small number of data points that lie near salient features of the interferometric data exert disproportionate influence on the inferred model parameters. We also show that the preferred orientations of the EHT baselines introduce significant biases in the inference of the orientation of the model images. Finally, we discuss strategies that help identify the presence and severity of such biases in realistic applications.

astro-ph.IM↗

arXiv2020

Joint Sparse Recovery Using Signal Space Matching Pursuit

In this paper, we put forth a new joint sparse recovery algorithm called signal space matching pursuit (SSMP). The key idea of the proposed SSMP algorithm is to sequentially investigate the support of jointly sparse vectors to minimize the subspace distance to the residual space. Our performance guarantee analysis indicates that SSMP accurately reconstructs any row $K$-sparse matrix of rank $r$ in the full row rank scenario if the sampling matrix $\mathbf{A}$ satisfies $\text{krank}(\mathbf{A}) \ge K+1$, which meets the fundamental minimum requirement on $\mathbf{A}$ to ensure exact recovery. We also show that SSMP guarantees exact reconstruction in at most $K-r+\lceil \frac{r}{L} \rceil$ iterations, provided that $\mathbf{A}$ satisfies the restricted isometry property (RIP) of order $L(K-r)+r+1$ with $$δ_{L(K-r)+r+1} < \max \left \{ \frac{\sqrt{r}}{\sqrt{K+\frac{r}{4}}+\sqrt{\frac{r}{4}}}, \frac{\sqrt{L}}{\sqrt{K}+1.15 \sqrt{L}} \right \},$$ where $L$ is the number of indices chosen in each iteration. This implies that the requirement on the RIP constant becomes less restrictive when $r$ increases. Such behavior seems to be natural but has not been reported for most of conventional methods. We further show that if $r=1$, then by running more than $K$ iterations, the performance guarantee of SSMP can be improved to $δ_{\lfloor 7.8K \rfloor} \le 0.155$. In addition, we show that under a suitable RIP condition, the reconstruction error of SSMP is upper bounded by a constant multiple of the noise power, which demonstrates the stability of SSMP under measurement noise. Finally, from extensive numerical experiments, we show that SSMP outperforms conventional joint sparse recovery algorithms both in noiseless and noisy scenarios.

cs.IT↗

arXiv2019

Low-Rank Matrix Completion: A Contemporary Survey

As a paradigm to recover unknown entries of a matrix from partial observations, low-rank matrix completion (LRMC) has generated a great deal of interest. Over the years, there have been lots of works on this topic but it might not be easy to grasp the essential knowledge from these studies. This is mainly because many of these works are highly theoretical or a proposal of new LRMC technique. In this paper, we give a contemporary survey on LRMC. In order to provide better view, insight, and understanding of potentials and limitations of LRMC, we present early scattered results in a structured and accessible way. Specifically, we classify the state-of-the-art LRMC techniques into two main categories and then explain each category in detail. We next discuss issues to be considered when one considers using LRMC techniques. These include intrinsic properties required for the matrix recovery and how to exploit a special structure in LRMC design. We also discuss the convolutional neural network (CNN) based LRMC algorithms exploiting the graph structure of a low-rank matrix. Further, we present the recovery performance and the computational complexity of the state-of-the-art LRMC techniques. Our hope is that this survey article will serve as a useful guide for practitioners and non-experts to catch the gist of LRMC.

cs.DS↗

arXiv2019

Matrix Completion Based Localization in the Internet of Things Network

In order to make a proper reaction to the collected information from internet of things (IoT) devices, location information of things should be available at the data center. One challenge for the massive IoT networks is to identify the location map of whole sensor nodes from partially observed distance information. In this paper, we propose a matrix completion based localization algorithm to reconstruct the location map of sensors using partially observed distance information. From the numerical experiments, we show that the proposed method based on the modified conjugate gradient is effective in recovering the Euclidean distance matrix.

cs.IT↗

arXiv2018

Tilted Beam Measurement of VLBI Receiver for the South Pole Telescope

We have developed a 230 and 345 GHz very-long-baseline interferometry (VLBI) receiver for the South Pole Telescope (SPT). With the receiver installed, the SPT has joined the global Event Horizon Telescope (EHT) array. The receiver optics select the 230 or 345 GHz mixers by rotating the tertiary mirror around the optical axis, directing the chief ray from the secondary mirror to the feed horn of the selected frequency band. The tertiary is installed on top of the receiver cryostat, which contains both mixer assemblies. The feed horns are placed symmetrically across the centerline of the telescope optics and tilted inward by 5.7 degrees from the vertical plane so that their beams intersect at the chief ray intersection on the tertiary mirror. We have performed vector beam measurements of the SPT VLBI receiver in both frequency bands. The measurements preserved the relative location of the beams, to establish the relative locations of the phase centers of the two horns. Measurements in two parallel reference planes above the cryostat were used to suppress reflected light. To model the beam, we derive a general expression of the electric field vector on the measurement plane for a tilted beam and infer the feed horn position parameters for both frequency bands by fitting models to data with a Markov chain Monte Carlo (MCMC) method. The inferred parameters such as the tilt angle of the feed horn are in good agreement with the design. We present the measurement setup, amplitude and phase pattern of the beam, and the fitting result here.

astro-ph.IM↗

arXiv2018

GRMHD simulations of visibility amplitude variability for Event Horizon Telescope images of Sgr A*

Synthesis imaging of the black hole in the center of the Milky Way, Sgr A*, with the Event Horizon Telescope (EHT) rests on the assumption of a stationary image. We explore the limitations of this assumption using high-cadence GRMHD simulations of Sgr A*. We employ analytic models that capture the basic characteristics of the images to understand the origin of the variability in the simulated visibility amplitudes. We find that, in all simulations, the visibility amplitudes for baselines oriented perpendicular to the spin axis of the black hole typically decrease smoothly over baseline lengths that are comparable to those of the EHT. On the other hand, the visibility amplitudes for baselines oriented parallel to the spin axis show significant structure with one or more minima. This suggests that fitting EHT observations with geometric models will lead to reasonably accurate determination of the orientation of the black-hole on the plane of the sky. However, in the disk-dominated models, the locations and depths of the minima in the visibility amplitudes depend primarily on the width and asymmetry of the crescent-like images and are highly variable. In the jet-dominated models, the locations of the minima are determined by the separation of the two image components but their depths depend primarily on the relative brightness of the two components and are also variable. This suggests that using time-independent models to infer additional black-hole parameters, such as the shadow size or the spin magnitude, will be severely affected by the variability of the accretion flow.

astro-ph.HE↗