Related papers: Deconfusing intensity maps with neural networks
Line intensity mapping (LIM) is a promising observational method to probe large-scale fluctuations of line emission from distant galaxies. Data from wide-field LIM observations allow us to study the large-scale structure of the universe as…
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…
Line intensity mapping (LIM) is an emerging observational method to study the large-scale structure of the Universe and its evolution. LIM does not resolve individual sources but probes the fluctuations of integrated line emissions. A…
Line intensity mapping (LIM) proposes to efficiently observe distant faint galaxies and map the matter density field at high redshift. Building upon the formalism in the companion paper, we first highlight the degeneracies between cosmology…
We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. $z=2$). We extract…
Line-intensity mapping (LIM) traces the large-scale distribution of matter by measuring fluctuations in aggregate line emission from unresolved galaxies and the intergalactic medium, providing a powerful probe of both astrophysics and…
Line intensity mapping (LIM) is a rapidly emerging technique for constraining cosmology and galaxy formation using multi-frequency, low angular resolution maps. Many LIM applications crucially rely on cross-correlations of two line…
Line-intensity mapping (LIM or IM) is an emerging field of observational work, with strong potential to fit into a larger effort to probe large-scale structure and small-scale astrophysical phenomena using multiple complementary tracers.…
This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and…
Spectral line intensity mapping has been proposed as a promising tool to efficiently probe the cosmic reionization and the large-scale structure. Without detecting individual sources, line intensity mapping makes use of all available…
Line intensity mapping (LIM) is emerging as a powerful technique to map the cosmic large-scale structure and to probe cosmology over a wide range of redshifts and spatial scales. We perform Fisher forecasts to determine the optimal design…
We seek to remove foreground contaminants from 21cm intensity mapping observations. We demonstrate that a deep convolutional neural network (CNN) with a UNet architecture and three-dimensional convolutions, trained on simulated…
The XENON1T experiment uses a time projection chamber (TPC) with liquid Xenon to search for Weakly Interacting Massive Particles (WIMPs), a proposed Dark Matter particle, via direct detection. As this experiment relies on capturing rare…
We explore the possible application of linear covariance-based (LCB) filtering to line-intensity mapping (LIM) signal reconstructions. Originally introduced for reconstruction of the integrated Sachs-Wolfe effect in the cosmic microwave…
Convolutional Neural Networks (CNN) have recently been demonstrated on synthetic data to improve upon the precision of cosmological inference. In particular they have the potential to yield more precise cosmological constraints from weak…
Line intensity mapping (LIM) serves as a potent probe in astrophysics, relying on the statistical analysis of integrated spectral line emissions originating from distant star-forming galaxies. While LIM observations hold the promise of…
We address the problem of line confusion in intensity mapping surveys and explore the possibility to mitigate line foreground contamination by progressively masking the brightest pixels in the observed map. We consider experiments targeting…
Line intensity mapping (LIM) promises to probe previously inaccessible corners of the faint and high-redshift universe. However, confusion with bright foregrounds is a major challenge for current-era pathfinder LIM experiments.…
Line intensity mapping is emerging as a novel method that can measure the collective intensity fluctuations of atomic/molecular line emission from distant galaxies. Several observational programs with various wavelengths are ongoing and…
Intensity mapping experiments survey the spectrum of diffuse line radiation rather than detect individual objects at high signal-to-noise. Spectral maps of unresolved atomic and molecular line radiation contain three-dimensional information…