Abstract
We report the first statistical detection of X-ray emission from cosmic web filaments in ROSAT data. We selected 15 165 filaments at 0.2 < z < 0.6 ranging from 30 Mpc to 100 Mpc in length, identified in the Sloan Digital Sky Survey survey. We stacked the X-ray count-rate maps from ROSAT around the filaments, excluding resolved galaxy groups and clusters above the mass of ∼3 × 1013 M⊙as well as the detected X-ray point sources from the ROSAT,Chandra, andXMM-Newtonobservations. The stacked signal results in the detection of the X-ray emission from the cosmic filaments at a significance of 4.2σin the energy band of 0.56−1.21 keV. The signal is interpreted, assuming the Astrophysical Plasma Emission Code model, as an emission from the hot gas in the filament-core regions with an average gas temperature of 0.9−0.6+1.0keV and a gas overdensity ofδ ∼ 30 at the center of the filaments. Furthermore, we show that stacking the SRG/eROSITA data for ∼2000 filaments only would lead to a ≳5σdetection of their X-ray signal, even with an average gas temperature as low as ∼0.3 keV.
Highlights
The cosmic structure is organized in a complex web-like pattern called cosmic web (Bond et al 1996) made of nodes, filaments, sheets, and voids (i.e., Aragón-Calvo et al 2010; Cautun et al 2013)
We show that stacking the SRG/eROSITA data for ∼2000 filaments only would lead to a 5σ detection of their X-ray signal, even with an average gas temperature as low as ∼0.3 keV
By stacking ROSAT maps at the positions of ∼15 000 large cosmic filaments identified with the Sloan Digital Sky Survey (SDSS) galaxies, we detect for the first time their X-ray emission at a significance of 4.2σ in the energy band of 0.56–1.21 keV
Summary
The cosmic structure is organized in a complex web-like pattern called cosmic web (Bond et al 1996) made of nodes, filaments, sheets, and voids (i.e., Aragón-Calvo et al 2010; Cautun et al 2013). Some detections of gas in filaments have been reported with X-ray and tSZ observations. In this Letter, we study the filaments with the ROSAT maps, which can be used to break the degeneracy and estimate the gas density and temperature. Following T20, we studied the filaments identified in Malavasi et al (2020) using the Discrete Persistent Structure Extractor (DisPerSE) algorithm (Sousbie 2011). This method computes the gradient of a density field and, where the gradient is zero, identifies critical points (maxima, minima, saddles, and bifurcations). This includes 135 118 point-like sources in the Second ROSAT All-Sky Survey Point Source Catalog (2RXS) (Boller et al 2016), 317 167 X-ray sources in the Chandra Source Catalog (CSC 2.0) (Evans et al 2010), and 775 153 sources in the third generation catalog of X-ray sources from XMM-Newton observatory (3XMM-DR8) (Rosen et al 2016)
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