arXiv subjects

L. Y. Gao

Publications and source records attributed to L. Y. Gao.

3 recordsLinked to original sources

arXiv2025

Mitigating incoherent excess variance in high-redshift 21 cm observations with multi-output cross-Gaussian process regression

Systematic effects that limit the achievable sensitivity of current low-frequency radio telescopes to the 21 cm signal are among the foremost challenges in observational 21 cm cosmology. The standard approach to retrieving the 21 cm signal from radio interferometric data separates it from bright astrophysical foregrounds by exploiting their spectrally smooth nature, in contrast to the finer spectral structure of the 21 cm signal. Contaminants exhibiting rapid frequency fluctuations, on the other hand, are difficult to separate from the 21 cm signal using standard techniques, and the power from these contaminants contributes to low-level systematics that can limit our ability to detect the 21 cm signal. Many of these low-level systematics are incoherent across multiple nights of observation, resulting in an incoherent excess variance above the thermal noise sensitivity of the instrument. In this paper, we develop a method called cross-GPR (cross covariance Gaussian process regression) that exploits the incoherence of these systematics to separate them from the 21 cm signal, which remains coherent across multiple nights of observation. We first develop and demonstrate the technique on synthetic signals in a general setting, and then apply it to gridded interferometric visibility cubes. We perform realistic simulations of visibility cubes containing foregrounds, 21 cm signal, noise, and incoherent systematics. The simulations show that the method can successfully separate and subtract incoherent contributions to the excess variance, and its advantages over standard techniques become more evident when the spectral behavior of the contaminants resembles that of the 21 cm signal. Simulations performed on a variety of 21 cm signal shapes also reveal that the cross-GPR approach can subtract incoherent contributions to the excess variance, without suppressing the 21 cm signal.

astro-ph.CO↗

arXiv2025

The impact of lunar topography on the 21-cm power spectrum for grid-based arrays : Insights for the Dark-ages EXplorer (DEX)

The Dark Ages (DA) provides a crucial window into the physics of the infant Universe, with the 21-cm signal offering the only direct probe for mapping out the three-dimensional distribution of matter at this epoch. To measure this cosmological signal, the Dark-ages EXplorer (DEX) has been proposed as a compact, grid-based radio array on the lunar farside. The minimal design consists of a 32 $\times$ 32 array of 3-m dipole antennas, operating in the $7 - 50$ MHz band. A practical challenge on the lunar surface is that the antennas may get displaced from their intended positions due to deployment imprecisions and non-coplanarity arising from local surface undulations. We present, for the first time, an end-to-end simulation pipeline, called SPADE-21cm, that integrates a sky model with a DA 21-cm signal model simulated in the lunar frame and incorporating lunar topography data. We study the effects of both lateral (xy) and vertical (z) offsets on the two-dimensional power spectra across the $7 - 12$ MHz and $30 - 35$ MHz spectral windows, with tolerance thresholds derived only for the latter. Our results show that positional offsets bias the power spectrum by $10 - 30$ per cent relative to the expected 21-cm power spectrum during DA. Lateral offsets within $σ_{xy}/λ\lesssim 0.027$ (at 32.5 MHz) keep the fraction of Fourier modes with strong contamination (> 50 per cent of the signal) to less than 1 per cent, whereas vertical height offsets affect a larger fraction. This conclusion holds for the 21-cm window with $k_\parallel > 0.5$ $h$ cMpc$^{-1}$ over the range of $k_\perp = 0.003 - 0.009$ $h$ cMpc$^{-1}$.

astro-ph.IM↗

arXiv2025

Near-field imaging of local interference in radio interferometric data: Impact on the redshifted 21 cm power spectrum

Radio-frequency interference (RFI) is a major systematic limitation in radio astronomy, particularly for science cases requiring high sensitivity, such as 21 cm cosmology. Traditionally, RFI is dealt with by identifying its signature in the dynamic spectra of visibility data and flagging strongly affected regions. However, for RFI sources that do not occupy narrow regions in the time-frequency space, such as persistent local RFI, modeling these sources could be essential to mitigating their impact. This paper introduces two methods for detecting and characterizing local RFI sources from radio interferometric visibilities: matched filtering and maximum a posteriori (MAP) imaging. These algorithms use the spherical wave equation to construct three-dimensional near-field image cubes of RFI intensity from the visibilities. The matched filter algorithm can generate normalized maps by cross-correlating the expected contributions from RFI sources with the observed visibilities, while the MAP method performs a regularized inversion of the visibility equation in the near field. We developed a full polarization simulation framework for RFI and demonstrated the methods on simulated observations of local RFI sources. The stability, speed, and errors introduced by these algorithms were investigated, and, as a demonstration, the algorithms were applied to a subset of NenuFAR observations to perform spatial, spectral, and temporal characterization of two local RFI sources. We used simulations to assess the impact of local RFI on images, the uv plane, and cylindrical power spectra, and to quantify the level of bias introduced by the algorithms in order to understand their implications for the estimated 21 cm power spectrum with radio interferometers. The near-field imaging and simulation codes are publicly available in the Python library nfis.

astro-ph.IM↗