arXiv subjects

Junhua Gu

Publications and source records attributed to Junhua Gu.

At least 37 records · Page 2Linked to original sources

arXiv2022

Global CD/EoR Signal Detection with a Dense Digital Beamforming Array and Beyond

The global neutral hydrogen 21 cm signal extracted from the all-sky averaged radio spectra is one of the signatures of the Cosmic Dawn and Epoch of Reionization (CD/EoR). The frequency-dependency of antenna beam patterns coupled with the strong foreground emission could introduce artificial spectral structures and cause false detection. A digital beamforming array could be potentially employed to form achromatic station beam patterns to overcome this problem. In this work, we discuss the method of forming achromatic beam patterns with a dense regular beamforming array to detect the global CD/EoR signal, covering topics including the array configuration, antenna weight optimization, and error estimation. We also show that based on the equivalence between a beamforming array and an interferometer, most antennas in the array can be removed by canceling redundant baselines. We present an example array design, optimize the antenna weights, and show the final array configuration by canceling redundant baselines. The performance of the example array is evaluated based on a simulation, which provides a positive indication towards the feasibility of detecting the CD/EoR signal using a dense digital beamforming array.

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arXiv2022

Impact of the turnover in the high-z galaxy luminosity function on the 21-cm signal during Cosmic Dawn and Epoch of Reionization

The shape of the faint-end of the high-z galaxy luminosity function (LF) informs early star formation and reionization physics during the Cosmic Dawn and Epoch of Reionization. Until recently, based on the strong gravitational lensing cluster deep surveys, the Hubble Frontier Fields (HFF) has found a potential turnover in the ultraviolet (UV) LF at z$\sim$6. In this paper, we analyze the contribution of extremely faint galaxies with the magnitude larger than the turnover magnitude in LF to cosmic reionization. We apply the measurement from HFF to our suppressed star formation efficiency model, including three free parameters: halo mass threshold $M_t$, curvature parameter $β$ and a UV conversion factor $l_{\rm UV}$. According to our fit of 68\% confidence level, the high-redshift star formation in haloes smaller than $ M_t=1.82^{+2.86}_{-1.08}\times10^{10} \rm M_{\odot}$ is found to be dampened. The turnover magnitude $\rm \gtrsim -13.99-2.45$, correspondingly the halo mass $\lesssim(4.57+20.03)\times10^{9} \rm M_{\odot}$. We find that the absorption trough in the global 21-cm signal is sensitive to our SFE model parameters. Together with ($β$, $l_{\rm UV}$) = ($2.17^{+2.42}_{-1.72}$, $9.33^{+0.43}_{-0.42} \rm ~erg~yr ~s^{-1}M_{\odot}^{-1})$, the trough locates at $\sim$ $134^{+10}_{-17}$ $\rm MHz$ with an amplitude of $\sim$ $-237^{-6}_{+7}$ $\rm mK$, compared to (106\rm MHz, -212\rm mK) in the absence of turnover. Besides, we find that the star formation of faint galaxies has also an impact on the 21-cm power spectra. The best fitting peak power decreases by $\sim4\%$ and shifts towards smaller scales from $0.88 h \rm Mpc^{-1}$ to $0.91 h \rm Mpc^{-1}$. According to our calculation, such impact is distinguishable with the forthcoming Square Kilometre Array.

astro-ph.GA↗

arXiv2021

A systematic evaluation of methods for cell phenotype classification using single-cell RNA sequencing data

Background: Single-cell RNA sequencing (scRNA-seq) yields valuable insights about gene expression and gives critical information about complex tissue cellular composition. In the analysis of single-cell RNA sequencing, the annotations of cell subtypes are often done manually, which is time-consuming and irreproducible. Garnett is a cell-type annotation software based the on elastic net method. Besides cell-type annotation, supervised machine learning methods can also be applied to predict other cell phenotypes from genomic data. Despite the popularity of such applications, there is no existing study to systematically investigate the performance of those supervised algorithms in various sizes of scRNA-seq data sets. Methods and Results: This study evaluates 13 popular supervised machine learning algorithms to classify cell phenotypes, using published real and simulated data sets with diverse cell sizes. The benchmark contained two parts. In the first part, we used real data sets to assess the popular supervised algorithms' computing speed and cell phenotype classification performance. The classification performances were evaluated using AUC statistics, F1-score, precision, recall, and false-positive rate. In the second part, we evaluated gene selection performance using published simulated data sets with a known list of real genes. Conclusion: The study outcomes showed that ElasticNet with interactions performed best in small and medium data sets. NB was another appropriate method for medium data sets. In large data sets, XGB works excellent. Ensemble algorithms were not significantly superior to individual machine learning methods. Adding interactions to ElasticNet can help, and the improvement was significant in small data sets.

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arXiv2020

Direct Parameter Inference from Global EoR Signal with Bayesian Statistics

In the observation of sky-averaged HI signal from Epoch of Reionization, model parameter inference can be a computation-intensive work, which makes it hard to perform a direct one-stage model parameter inference by using MCMC sampling method in Bayesian framework. Instead, a two-stage inference is usually used, i.e., the parameters of some characteristic points on the EoR spectrum model are first estimated, which are then used as the input to estimate physical model parameters further. However, some previous works had noticed that this kind of method could bias results, and it could be meaningful to answer the question of whether it is feasible to perform direct one-stage MCMC sampling and obtain unbiased physical model parameter estimations. In this work, we studied this problem and confirmed the feasibility. We find that unbiased estimations to physical model parameters can be obtained with a one-stage direct MCMC sampling method. We also study the influence of some factors that should be considered in practical observations to model parameter inference. We find that a very tiny amplifier gain calibration error ($10^{-5}$ relative error) with complex spectral structures can significantly bias the parameter estimation; the frequency-dependent antenna beam and geographical position can also influence the results, so that should be carefully handled.

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arXiv2019

The Giant Radio Array for Neutrino Detection (GRAND): Science and Design

The Giant Radio Array for Neutrino Detection (GRAND) is a planned large-scale observatory of ultra-high-energy (UHE) cosmic particles, with energies exceeding 10^8 GeV. Its goal is to solve the long-standing mystery of the origin of UHE cosmic rays. To do this, GRAND will detect an unprecedented number of UHE cosmic rays and search for the undiscovered UHE neutrinos and gamma rays associated to them with unmatched sensitivity. GRAND will use large arrays of antennas to detect the radio emission coming from extensive air showers initiated by UHE particles in the atmosphere. Its design is modular: 20 separate, independent sub-arrays, each of 10 000 radio antennas deployed over 10 000 km^2. A staged construction plan will validate key detection techniques while achieving important science goals early. Here we present the science goals, detection strategy, preliminary design, performance goals, and construction plans for GRAND.

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arXiv2019

Contribution of Radio Halos to the Foreground for SKA EoR Experiments

The overwhelming foreground contamination is one of the primary impediments to probing the Epoch of Reionization (EoR) through measuring the redshifted 21 cm signal. Among various foreground components, radio halos are less studied and their impacts on the EoR observations are still poorly understood. In this work, we employ the Press-Schechter formalism, merger-induced turbulent re-acceleration model, and the latest SKA1-Low layout configuration to simulate the SKA "observed" images of radio halos. We calculate the one-dimensional power spectra from simulated images and find that radio halos can be about $10^4$, $10^3$ and $10^{2.5}$ times more luminous than the EoR signal on scales of $0.1\,\text{Mpc}^{-1} < k < 2\,\text{Mpc}^{-1}$ in the 120-128, 154-162, and 192-200 MHz bands, respectively. By examining the two-dimensional power spectra inside properly defined EoR windows, we find that the power leaked by radio halos can still be significant, as the power ratios of radio halos to the EoR signal on scales of $0.5\,\text{Mpc}^{-1} \lesssim k \lesssim 1\,\text{Mpc}^{-1}$ can be up to about 230-800%, 18-95%, and 7-40% in the three bands, when the 68% uncertainties caused by the variation of the number density of bright radio halos are considered. Furthermore, we find that radio halos located inside the far side-lobes of the station beam can also impose strong contamination within the EoR window. In conclusion, we argue that radio halos are severe foreground sources and need serious treatments in future EoR experiments.

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arXiv2019

Autonomous radiodetection of air showers with the TREND50 antenna array

TREND50 is a radio detection setup of 50 self-triggered antennas working in the 50-100MHz frequency range and deployed in a radio-quiet valley of the Tianshan mountains (China). TREND50 achieved its goal: the autonomous radiodetection and identification of air showers. Thanks to a dedicated offine selection algorithm, 564 air shower candidates were indeed selected out of $7\cdot10^8$ transient radio signals recorded during the 314 live days of data taken during the first two years of operation of this setup (2011 and 2012). This event rate, as well as the distribution of the candidate directions of arrival, is consistent with what is expected from cosmic-ray-induced air showers according to simulations, assuming an additional $\sim$20% contamination of the final sample by background events. This result is obtained at the cost of a reduced air shower detection efficiency, estimated to be $\sim$3%. This low efficiency is mostly due to the large amount of dead time of the setup. This result paves the way for the GRANDProto35 experiment, the first stage of the GRAND project.

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arXiv2019

Separating the EoR Signal with a Convolutional Denoising Autoencoder: A Deep-learning-based Method

When applying the foreground removal methods to uncover the faint cosmological signal from the epoch of reionization (EoR), the foreground spectra are assumed to be smooth. However, this assumption can be seriously violated in practice since the unresolved or mis-subtracted foreground sources, which are further complicated by the frequency-dependent beam effects of interferometers, will generate significant fluctuations along the frequency dimension. To address this issue, we propose a novel deep-learning-based method that uses a 9-layer convolutional denoising autoencoder (CDAE) to separate the EoR signal. After being trained on the SKA images simulated with realistic beam effects, the CDAE achieves excellent performance as the mean correlation coefficient ($\barρ$) between the reconstructed and input EoR signals reaches $0.929 \pm 0.045$. In comparison, the two representative traditional methods, namely the polynomial fitting method and the continuous wavelet transform method, both have difficulties in modelling and removing the foreground emission complicated with the beam effects, yielding only $\barρ_{\text{poly}} = 0.296 \pm 0.121$ and $\barρ_{\text{cwt}} = 0.198 \pm 0.160$, respectively. We conclude that, by hierarchically learning sophisticated features through multiple convolutional layers, the CDAE is a powerful tool that can be used to overcome the complicated beam effects and accurately separate the EoR signal. Our results also exhibit the great potential of deep-learning-based methods in future EoR experiments.

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arXiv2017

The Giant Radio Array for Neutrino Detection (GRAND): Present and Perspectives

The Giant Radio Array for Neutrino Detection (GRAND) aims at detecting ultra-high energy extraterrestrial neutrinos via the extensive air showers induced by the decay of tau leptons created in the interaction of neutrinos under the Earth's surface. Consisting of an array of $\sim10^5$ radio antennas deployed over $\sim 2\times10^5\,\rm {km}^2$, GRAND plans to reach, for the first time, an all-flavor sensitivity of $\sim1.5\times10^{-10} \,\rm GeV\, cm^{-2} \,s^{-1}\, sr^{-1}$ above $5\times10^{17}$ eV and a sub-degree angular resolution, beyond the reach of other planned detectors. We describe here preliminary designs and simulation results, plans for the ongoing, staged approach to the construction of GRAND, and the rich research program made possible by GRAND's design sensitivity and angular resolution.

astro-ph.IM↗

arXiv2017

The Giant Radio Array for Neutrino Detection

The Giant Radio Array for Neutrino Detection (GRAND) is a planned array of ~200 000 radio antennas deployed over ~200 000 km2 in a mountainous site. It aims primarly at detecting high-energy neutrinos via the observation of extensive air showers induced by the decay in the atmosphere of taus produced by the interaction of cosmic neutrinos under the Earth surface. GRAND aims at reaching a neutrino sensitivity of 5.10$^{11}$ E$^{-2}$ GeV$^{-1}$cm$^{-2}$s$^{-1}$sr$^{-1}$ above 3.10$^{16}$ eV. This ensures the detection of cosmogenic neutrinos in the most pessimistic source models, and ~50 events per year are expected for the standard models. The instrument will also detect UHECRs and possibly FRBs. Here we show how our preliminary design should enable us to reach our sensitivity goals, and discuss the steps to be taken to achieve GRAND.

astro-ph.IM↗

arXiv2016

A Chandra Study of the Image Power Spectra of 41 Cool Core and Non-Cool Core Galaxy Clusters

In this work we propose a new diagnostic to segregate cool core (CC) clusters from non-cool core (NCC) clusters by studying the two-dimensional power spectra of the X-ray images observed with the Chandra X-ray observatory. Our sample contains 41 members ($z=0.01\sim 0.54$), which are selected from the Chandra archive when a high photon count, an adequate angular resolution, a relatively complete detector coverage, and coincident CC-NCC classifications derived with three traditional diagnostics are simultaneously guaranteed. We find that in the log-log space the derived image power spectra can be well represented by a constant model component at large wavenumbers, while at small wavenumbers a power excess beyond the constant component appears in all clusters, with a clear tendency that the excess is stronger in CC clusters. By introducing a new CC diagnostic parameter, i.e., the power excess index (PEI), we classify the clusters in our sample and compare the results with those obtained with three traditional CC diagnostics. We find that the results agree with each other very well. By calculating the PEI values of the simulated clusters, we find that the new diagnostic works well at redshifts up to 0.5 for intermediately sized and massive clusters with a typical Chandra or XMM pointing observation. The new CC diagnostic has several advantages over its counterparts, e.g., it is free of the effects of the commonly seen centroid shift of the X-ray halo caused by merger event, and the corresponding calculation is straightforward, almost irrelevant to the complicated spectral analysis.

astro-ph.CO↗

arXiv2015

A Chandra Study of Radial Temperature Profiles of the Intra-Cluster Medium in 50 Galaxy Clusters

In order to investigate the spatial distribution of the ICM temperature in galaxy clusters in a quantitative way and probe the physics behind, we analyze the X-ray spectra of a sample of 50 galaxy clusters, which were observed with the Chandra ACIS instrument in the past 15 years, and measure the radial temperature profiles out to $0.45r_{500}$. We construct a physical model that takes into account the effects of gravitational heating, thermal history (such as radiative cooling, AGN feedback, and thermal conduction) and work done via gas compression, and use it to fit the observed temperature profiles by running Bayesian regressions. The results show that in all cases our model provides an acceptable fit at the 68% confidence level. To further validate this model we select nine clusters that have been observed with both Chandra (out to $\gtrsim 0.3r_{500}$) and Suzaku (out to $\gtrsim 1.5r_{500}$), fit their Chandra spectra with our model, and compare the extrapolation of the best-fits with the Suzaku measurements. We find that the model profiles agree with the Suzaku results very well in seven clusters. In the rest two clusters the difference between the model and observation is possibly caused by local thermal substructures. Our study also implies that for most of the clusters the assumption of hydrostatic equilibrium is safe out to at least $0.5r_{500}$, and the non-gravitational interactions between dark matter and its luminous counterpart is consistent with zero.

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arXiv2015

The Giant Radio Array for Neutrino Detection

High-energy neutrino astronomy will probe the working of the most violent phenomena in the Universe. The Giant Radio Array for Neutrino Detection (GRAND) project consists of an array of $\sim10^5$ radio antennas deployed over $\sim$200000km$^2$ in a mountainous site. It aims at detecting high-energy neutrinos via the measurement of air showers induced by the decay in the atmosphere of $τ$ leptons produced by the interaction of the cosmic neutrinos under the Earth surface. Our objective with GRAND is to reach a neutrino sensitivity of $3\times10^{-11}E^{-2}$GeV$^{-1}$cm$^{-2}$s$^{-1}$sr$^{-1}$ above $3 \times10^{16}$eV. This sensitivity ensures the detection of cosmogenic neutrinos in the most pessimistic source models, and about 100 events per year are expected for the standard models. GRAND would also probe the neutrino signals produced at the potential sources of UHECRs. We show how our preliminary design should enable us to reach our sensitivity goals, and present the experimental characteristics. We assess the possibility to adapt GRAND to other astrophysical radio measurements. We discuss in this token the technological options for the detector and the steps to be taken to achieve the GRAND project.

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arXiv2013

The Application of Continuous Wavelet Transform Based Foreground Subtraction Method in 21 cm Sky Surveys

We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.

astro-ph.CO↗

arXiv2013

Chandra Study of the Massive and Distant Galaxy Cluster SDSS J0150-1005

In this work, we present a high spatial resolution study of a fossil cluster, SDSS J0150-1005 ($z \simeq 0.364$), based on the imaging spectroscopic analysis of \chandra\ observation. The \chandra\ X-ray image shows a relax and symmetric morphology, which indicates SDSS J0150-1005 is a well-developed galaxy cluster with no sign of recent merger. Its global gas temperature is 5.73 $\pm$ 0.80 keV, and the virial mass is 6.23 $\pm$ 1.34 $\times 10^{14} $ M$_{\odot}$ according to the isothermal model. Compared with polytropic temperature model, the mass calculated based on isothermal model overestimates 49 $\pm$ 11%. The central gas entropy, $S_{0.1r_{200}} = 143.9 \pm 18.3$ keV cm$^2$, is significantly lower than average value of the normal galaxy clusters with similar temperatures. Our results indicate the early formation epoch of SDSS J0150-1005.

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arXiv2012

Exploring the Cosmic Reionization Epoch in Frequency Space: An Improved Approach to Remove the Foreground in 21 cm Tomography

Aiming to correctly restore the redshifted 21 cm signals emitted by the neutral hydrogen during the cosmic reionization processes, we re-examine the separation approaches based on the quadratic polynomial fitting technique in frequency space to investigate whether they works satisfactorily with complex foreground, by quantitatively evaluate the quality of restored 21 cm signals in terms of sample statistics. We construct the foreground model to characterize both spatial and spectral substructures of the real sky, and use it to simulate the observed radio spectra. By comparing between different separation approaches through statistical analysis of restored 21 cm spectra and corresponding power spectra, as well as their constraints on the mean halo bias $b$ and average ionization fraction $x_e$ of the reionization processes, at $z=8$ and the noise level of 60 mK we find that, although the complex foreground can be well approximated with quadratic polynomial expansion, a significant part of Mpc-scale components of the 21 cm signals (75% for $\gtrsim 6h^{-1}$ Mpc scales and 34% for $\gtrsim 1h^{-1}$ Mpc scales) is lost because it tends to be mis-identified as part of the foreground when single-narrow-segment separation approach is applied. The best restoration of the 21 cm signals and the tightest determination of $b$ and $x_e$ can be obtained with the three-narrow-segment fitting technique as proposed in this paper. Similar results can be obtained at other redshifts.

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arXiv2012

Chandra Observation of a Weak Shock in the Galaxy Cluster A2556

Based on a 21.5 ks \chandra\ observation of A2556, we identify an edge on the surface brightness profile (SBP) at about 160$h_{71}^{-1}$ kpc northeast of the cluster center, and it corresponds to a shock front whose Mach number $\mathcal{M}$ is calculated to be $1.25_{-0.03}^{+0.02}$. No prominent substructure, such as sub-cluster, is found in either optical or X-ray band that can be associated with the edge, suggesting that the conventional super-sonic motion mechanism may not work in this case. As an alternative solution, we propose that the nonlinear steepening of acoustic wave, which is induced by the turbulence of the ICM at the core of the cluster, can be used to explain the origin of the shock front. Although nonlinear steepening weak shock is expected to occur frequently in clusters, why it is rarely observed still remains a question that requires further investigation, including both deeper X-ray observation and extensive theoretical studies.

astro-ph.HE↗

arXiv2012

Two-Phase ICM in the Central Region of the Rich Cluster of Galaxies Abell 1795: A Joint Chandra, XMM-Newton, and Suzaku View

Based on a detailed analysis of the high-quality Chandra, XMM-Newton, and Suzaku data of the X-ray bright cluster of galaxies Abell 1795, we report clear evidence for a two-phase intracluster medium (ICM) structure, which consists of a cool (with a temperature T = 2.0-2.2 keV) and a hot (T = 5.0-5.7 keV) component that coexist and dominate the X-ray emission at least in the central 80 kpc. A third weak emission component (T = 0.8 keV) is also detected within the innermost 144 kpc and is ascribed to a portion of inter-stellar medium (ISM) of the cD galaxy. Deprojected spectral analysis reveals flat radial temperature distributions for both the hot phase and cool phase components. These results are consistent with the ASCA measurements reported in Xu et al. (1998), and resemble the previous findings for the Centaurus cluster (e.g., Takahashi et al. 2009). By analyzing the emission measure ratio and gas metal abundance maps created from the Chandra data, we find that the cool phase component is more metal-enriched than the hot phase one in 50-100 kpc region, which agrees with that found in M87 (Simionescu et al. 2008). The coexistence of the cool phase and hot phase ICM cannot be realized by bubble uplifting from active galactic nuclei (AGN) alone. Instead, the two-phase ICM properties are better reconciled with a cD corona model (Makishima et al. 2001). (Abridged)

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