分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Line intensity mapping (LIM) is a promising probe to study star formation, the large-scale structure of the Universe, and the epoch of reionization (EoR). Since carbon monoxide (CO) is the second most abundant molecule in the Universe except for molecular hydrogen ${\rm H}_2$, it is suitable as a tracer for LIM surveys. However, just like other LIM surveys, CO intensity mapping also suffers strong foreground contamination that needs to be eliminated for extracting valuable astrophysical and cosmological information. In this work, we take $^{12}$CO($\it J$=1-0) emission line as an example to investigate whether deep learning method can effectively recover the signal by removing the foregrounds. The CO(1-0) intensity maps are generated by N-body simulations considering CO luminosity and halo mass relation, and we discuss two cases with median and low CO signals by comparing different relations. We add foregrounds generated from real observations, including thermal dust, spinning dust, free-free, synchrotron emission and CMB anisotropy. The beam with sidelobe effect is also considered. Our deep learning model is built upon ResUNet, which combines image generation algorithm UNet with the state-of-the-art architecture of deep learning, ResNet. The principal component analysis (PCA) method is employed to preprocess data before feeding it to the ResUNet. We find that, in the case of low instrumental noise, our UNet can efficiently reconstruct the CO signal map with correct line power spectrum by removing the foregrounds and recovering PCA signal loss and beam effects. Our method also can be applied to other intensity mappings like neutral hydrogen 21cm surveys.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： A redshifted 21 cm line absorption signature is commonly expected from the cosmic dawn era, when the first stars and galaxies formed. The detailed traits of this signal can provide important insight on the cosmic history. However, high precision measurement of this signal is hampered by the ionosphere refraction and absorption, as well as radio frequency interference (RFI). A space observation can solve the problem of the ionosphere, and the Moon can shield the RFI from the Earth. In this paper, we present simulations of the global spectrum measurement in the 30 -- 120 MHz frequency band on the lunar orbit, from the proposed Discovering the Sky at the Longest wavelength (DSL) project. In particular, we consider how the measured signal varies as the satellite moves along the orbit, take into account the blockage of different parts of the sky by the Moon and the antenna response. We estimate the sensitivity for such a 21 cm global spectrum experiment. An RMS noise level of $\le 0.05$ K is expected at 75 MHz after 10 orbits ($\sim$ 1 day) observation, for a frequency channel width of 0.4 MHz. We also study the influence of a frequency-dependent beam, which may generate complex spectral structures in the spectrum. Estimates of the uncertainties in the foreground and 21 cm model parameters are obtained.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Line intensity mapping (LIM) is a promising probe to study star formation, the large-scale structure of the Universe, and the epoch of reionization (EoR). Since carbon monoxide (CO) is the second most abundant molecule in the Universe except for molecular hydrogen ${\rm H}_2$, it is suitable as a tracer for LIM surveys. However, just like other LIM surveys, CO intensity mapping also suffers strong foreground contamination that needs to be eliminated for extracting valuable astrophysical and cosmological information. In this work, we take $^{12}$CO($\it J$=1-0) emission line as an example to investigate whether deep learning method can effectively recover the signal by removing the foregrounds. The CO(1-0) intensity maps are generated by N-body simulations considering CO luminosity and halo mass relation, and we discuss two cases with median and low CO signals by comparing different relations. We add foregrounds generated from real observations, including thermal dust, spinning dust, free-free, synchrotron emission and CMB anisotropy. The beam with sidelobe effect is also considered. Our deep learning model is built upon ResUNet, which combines image generation algorithm UNet with the state-of-the-art architecture of deep learning, ResNet. The principal component analysis (PCA) method is employed to preprocess data before feeding it to the ResUNet. We find that, in the case of low instrumental noise, our UNet can efficiently reconstruct the CO signal map with correct line power spectrum by removing the foregrounds and recovering PCA signal loss and beam effects. Our method also can be applied to other intensity mappings like neutral hydrogen 21cm surveys.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Cross-correlating the data of neutral hydrogen (HI) 21cm intensity mapping with galaxy surveys is an effective method to extract astrophysical and cosmological information. In this work, we investigate the cross-correlation of MeerKAT single-dish mode HI intensity mapping and China Space Station Telescope (CSST) spectroscopic galaxy surveys. We simulate a survey area of $\sim 300$ $\mathrm{deg}^2$ of MeerKAT and CSST surveys at $z=0.5$ using Multi-Dark N-body simulation. The PCA algorithm is applied to remove the foregrounds of HI intensity mapping, and signal compensation is considered to solve the signal loss problem in the HI-galaxy cross power spectrum caused by the foreground removal process. We find that from CSST galaxy auto and MeerKAT-CSST cross power spectra, the constraint accuracy of the parameter product $\Omega_{\rm HI}b_{\rm HI}r_{{\rm HI},g}$ can reach to $\sim1\%$, which is about one order of magnitude higher than the current results. After performing the full MeerKAT HI intensity mapping survey with 5000 deg$^2$ survey area, the accuracy can be enhanced to $<0.3\%$. This implies that the MeerKAT-CSST cross-correlation can be a powerful tool to probe the cosmic HI property and the evolution of galaxies and the Universe.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Cross-correlating the data of neutral hydrogen (HI) 21cm intensity mapping with galaxy surveys is an effective method to extract astrophysical and cosmological information. In this work, we investigate the cross-correlation of MeerKAT single-dish mode HI intensity mapping and China Space Station Telescope (CSST) spectroscopic galaxy surveys. We simulate a survey area of $\sim 300$ $\mathrm{deg}^2$ of MeerKAT and CSST surveys at $z=0.5$ using Multi-Dark N-body simulation. The PCA algorithm is applied to remove the foregrounds of HI intensity mapping, and signal compensation is considered to solve the signal loss problem in the HI-galaxy cross power spectrum caused by the foreground removal process. We find that from CSST galaxy auto and MeerKAT-CSST cross power spectra, the constraint accuracy of the parameter product $\Omega_{\rm HI}b_{\rm HI}r_{{\rm HI},g}$ can reach to $\sim1\%$, which is about one order of magnitude higher than the current results. After performing the full MeerKAT HI intensity mapping survey with 5000 deg$^2$ survey area, the accuracy can be enhanced to $<0.3\%$. This implies that the MeerKAT-CSST cross-correlation can be a powerful tool to probe the cosmic HI property and the evolution of galaxies and the Universe.
分类： 物理学 >> 地球物理学、天文学和天体物理学 提交时间： 2023-12-15 合作期刊: 《Research in Astronomy and Astrophysics》
摘要： In the neutral hydrogen (H i) galaxy survey, a significant challenge is to identify and extract the H igalaxy signal from the observational data contaminated by radio frequency interference (RFI). For a drift-scan survey, or more generally a survey of a spatially continuous region, in the time-ordered spectral data, the H i galaxies and RFI all appear as regions that extend an area in the time-frequency waterfall plot, so the extraction of the H i galaxies and RFI from such data can be regarded as an image segmentation problem, and machine-learning methods can be applied to solve such problems. In this study, we develop a method to effectively detect and extract signals of H i galaxies based on a Mask R-CNN network combined with the PointRend method. By simulating FAST-observed galaxy signals and potential RFI impact, we created a realistic data set for the training and testing of our neural network. We compared five different architectures and selected the best-performing one. This architecture successfully performs instance segmentation of H igalaxy signals in the RFI-contaminated time-ordered data, achieving a precision of 98.64% and a recall of 93.59%.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Zijie Yu
Furen Deng
Shijie Sun
Chenhui Niu
Jixia Li
Fengquan Wu
Wei-Yang Wang
Yougang Wang
Hui Feng
Lin Shu
Jie Hao
Reza Ansari
Albert Stebbins
Xuelei Chen
摘要： The Tianlai Dish Pathfinder array is a radio interferometer array consisting of 16 six meter dish antennas. The original digital backend integration time is at the seconds level, designed for HI intensity mapping experiment. A new digital backend with millisecond response is added to enable it to search for fast radio burst (FRB) during its observations. The design and calibration of this backend, and the real time search pipeline for it are described in this paper. It is capable of forming 16 digital beams for each linear polarisation, covering an area of 19.6 square degrees. The search pipeline is capable of searching for, recording and classifying FRBs automatically in real time. In commissioning, we succeeded in capturing the signal pulses from the pulsars PSR B0329+54 and B2021+51.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Zijie Yu
Furen Deng
Shijie Sun
Chenhui Niu
Jixia Li
Fengquan Wu
Wei-Yang Wang
Yougang Wang
Hui Feng
Lin Shu
Jie Hao
Reza Ansari
Albert Stebbins
Xuelei Chen
摘要： The Tianlai Dish Pathfinder array is a radio interferometer array consisting of 16 six meter dish antennas. The original digital backend integration time is at the seconds level, designed for HI intensity mapping experiment. A new digital backend with millisecond response is added to enable it to search for fast radio burst (FRB) during its observations. The design and calibration of this backend, and the real time search pipeline for it are described in this paper. It is capable of forming 16 digital beams for each linear polarisation, covering an area of 19.6 square degrees. The search pipeline is capable of searching for, recording and classifying FRBs automatically in real time. In commissioning, we succeeded in capturing the signal pulses from the pulsars PSR B0329+54 and B2021+51.
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