Related papers: Deep Learning for Line Intensity Mapping Observati…
Intensity mapping (IM) is sensitive to the cumulative line emission of galaxies. As such it represents a promising technique for statistical studies of galaxies fainter than the limiting magnitude of traditional galaxy surveys. The strong…
Line Intensity Mapping (LIM) has garnered attention as a powerful cosmological probe, with next-generation instruments such as SPHEREx preparing to map the evolution of large-scale structure during the Epoch of Reionization (EoR).…
The nature of dark matter is a longstanding mystery in cosmology, which can be studied with laboratory or collider experiments, as well as astrophysical and cosmological observations. In this work, we propose realistic and efficient…
Line intensity mapping (LIM) is an emerging technique with a unique potential to probe a wide range of scales and redshifts. Realizing the full potential of LIM, however, relies on accurate modeling of the signal. We introduce an extended…
The intensity mapping of the [CII] 157.7 $\rm \mu$m fine-structure emission line represents an ideal experiment to probe star formation activity in galaxies, especially in those that are too faint to be individually detected. Here, we…
Line-intensity mapping (LIM) experiments coming online now will survey fluctuations in aggregate emission in the [C II] ionized carbon line from galaxies at the end of reionization. Experimental progress must be matched by theoretical…
Recent advances in deep learning have relied on large, labelled datasets to train high-capacity models. However, collecting large datasets in a time- and cost-efficient manner often results in label noise. We present a method for learning…
Line Intensity Mapping (LIM) offers a novel avenue to observe and characterize our universe. LIM data of CO spectral lines are becoming available, such as those obtained by the CO Mapping Array Project (COMAP). COMAP data can be used to…
Visbal & Loeb (2010) have shown that it is possible to measure the clustering of galaxies by cross correlating the cumulative emission from two different spectral lines which originate at the same redshift. Through this cross correlation,…
We present LIMFAST, a semi-numerical code for simulating high-redshift galaxy formation and cosmic reionization as revealed by multi-tracer line intensity mapping (LIM) signals. LIMFAST builds upon and extends the 21cmFAST code widely used…
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.…
Line-intensity mapping (LIM) is emerging as a powerful probe of the high-redshift Universe, with a growing number of LIM experiments targeting various spectral lines deep into the epochs of reionization and cosmic dawn. A key remaining…
Intensity mapping (IM) of spectral lines has the potential to revolutionize cosmology by increasing the total number of observed modes by several orders of magnitude compared to the cosmic microwave background (CMB) anisotropies. In this…
Line-intensity mapping (LIM) offers an approach to obtain three-dimensional maps of the large-scale structure by collecting the aggregate emission from all emitters along the line of sight. The procedure hinges on reconstructing the radial…
Infrared fine-structure emission lines from trace metals are powerful diagnostics of the interstellar medium in galaxies. We explore the possibility of studying the redshifted far-IR fine-structure line emission using the three-dimensional…
Intensity mapping has attracted significant interest as an approach to measure the properties of the interstellar medium in typical galaxies at high redshift. Intensity mapping measures the statistics of surface brightness as a function of…
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…
Following the first two annual intensity mapping workshops at Stanford in March 2016 and Johns Hopkins in June 2017, we report on the recent advances in theory, instrumentation and observation that were presented in these meetings and some…
Removing noise from images, a.k.a image denoising, can be a very challenging task since the type and amount of noise can greatly vary for each image due to many factors including a camera model and capturing environments. While there have…
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…