相关论文: A statistical framework for recovering intensity m…

This article discusses a generalization of the 1-dimensional multi-reference alignment problem. The goal is to recover a hidden signal from many noisy observations, where each noisy observation includes a random translation and random…

Compressed sensing deals with the reconstruction of sparse signals using a small number of linear measurements. One of the main challenges in compressed sensing is to find the support of a sparse signal. In the literature, several bounds on…

Cross-correlations between 21cm observations and galaxy surveys provide a powerful probe of reionization by reducing foreground sensitivity while linking ionization morphology to galaxies. We quantify the constraining power of 21cm-Galaxy…

We present a method for extracting the expected cosmological 21-cm signal from the epoch of reionization, taking into account contaminating radiations and random instrumental noise. The method is based on the maximum a-posteriori…

Random sampling in compressive sensing (CS) enables the compression of large amounts of input signals in an efficient manner, which is useful for many applications. CS reconstructs the compressed signals exactly with overwhelming…

We investigate the cross-correlation between the spatial distribution of Lyman Break Galaxies (LBGs) and the 21cm intensity mapping signal at $z\sim[3-5]$. At these redshifts, galactic feedback is supposed to only marginally affect the…

We present a new estimator for the cross-correlation signal between line intensity maps to probe the Epoch of Reionization. The proposed estimator is the hitherto neglected antisymmetric component of the cross-correlation, under the…

Sparsity is a ubiquitous feature of many real world signals such as natural images and neural spiking activities. Conventional compressed sensing utilizes sparsity to recover low dimensional signal structures in high ambient dimensions…

Compressive sampling has great potential for making wideband spectrum sensing possible at sub-Nyquist sampling rates. As a result, there have recently been research efforts that leverage compressive sampling to enable efficient wideband…

Analyzing and visualizing scientific ensemble datasets with high dimensionality and complexity poses significant challenges. Dimensionality reduction techniques and autoencoders are powerful tools for extracting features, but they often…

We have developed a fast, accurate and generally applicable method for inferring the power spectrum and its uncertainties from maps of the cosmic microwave background (CMB) in the presence of inhomogeneous and correlated noise. For maps…

In the recent years, the internal-linear-combination (ILC) method was investigated extensively in the context of reconstruction of Cosmic Microwave Background (CMB) temperature anisotropy signal using observations obtained by WMAP and…

21 cm intensity mapping has arisen as a powerful probe of the high-redshift universe, but its potential is limited by extremely bright foregrounds and high source confusion. In this Letter, we propose a new analysis which can help solve…

Compressive Sensing (CS) exploits the surprising fact that the information contained in a sparse signal can be preserved in a small number of compressive, often random linear measurements of that signal. Strong theoretical guarantees have…

We consider the scenario in which multiple sensors send spatially correlated data to a fusion center (FC) via independent Rayleigh-fading channels with additive noise. Assuming that the sensor data is sparse in some basis, we show that the…

Compressed sensing has a wide range of applications that include error correction, imaging, radar and many more. Given a sparse signal in a high dimensional space, one wishes to reconstruct that signal accurately and efficiently from a…

Contamination of interloper galaxies due to misidentified emission lines can be a big issue in the spectroscopic galaxy clustering surveys, especially in future high-precision observations. We propose a statistical method based on the…

The 21 cm intensity mapping (IM) technique provides us with an efficient way to observe the cosmic large-scale structure (LSS). From the LSS data, one can use the baryon acoustic oscillation and redshift space distortion to trace the…

Line intensity mapping using atomic hydrogen (HI) has the potential to efficiently map large volumes of the universe if the signal can be successfully separated from overwhelmingly bright radio foreground emission. This motivates…

We present a new method that deals with the uncertainty in matter-clustering in cosmic shear power spectrum analysis that arises mainly due to poorly understood nonlinear baryonic processes on small-scales. We show that the majority of…