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Unveiling the formation and evolution of galaxy clusters through the intracluster light and multidisciplinar techniques of image processing and big data analysis

Periodic Reporting for period 1 - CICLE (Unveiling the formation and evolution of galaxy clusters through the intracluster light and multidisciplinar techniques of image processing and big data analysis)

Okres sprawozdawczy: 2020-04-01 do 2022-03-31

Clusters of galaxies are the largest and most massive structures gravitationally bound in the Universe. They are composed of different components, such as galaxies, hot gas, and dark matter. This project focuses on a fourth and barely studied component, the intracluster light (ICL), formed by stars bound gravitationally by the cluster but not hosted by any galaxy. Different cluster galaxies initially hosted these stars but different mechanisms, more or less violent, stripped them out and threw them into the intracluster space. Therefore, the ICL and its properties depend directly on the assembling history of the cluster and its current state. Knowledge about the properties of the ICL, its formation pathways, and its evolution give us insights into the dynamics of clusters and, consequently, into the mechanisms that reign the Universe. The main objectives of this project are: 1) characterizing the physical properties of the ICL, 2) identifying the main channels that create and feed the ICL, 3) linking the properties of the ICL and the total clusters, and 4) understanding the evolution of the ICL across cosmic time.
With this project I conclude that the ICL is intimately linked to the dynamical stage of the cluster, at all redshifts. The ICL is a record of the cluster's history and a tale of the formation and evolution of the cluster that we can read, with different colors, shapes, and properties depending on the merger history of the system. Also, the ICL is crucial to analyze clusters observed by the recently launched James Webb telescope.
The ICL is a very faint and diffuse light enveloping the cluster galaxies. Its detection requires deep and high-quality images, and its study is challenging because it is very complex to disentangle the ICL from the light that galaxies emit. In this project, I applied an algorithm of my design to analyze the ICL, called CHEFs Intracluster Light Estimator (CICLE). Using a sample of 41 clusters observed by the Hubble Space Telescope (HST) within the frame of the Reionization Lensing Cluster Survey (RELICS) and other programs, such as the Frontier Fields initiative, simulations, and fossil groups (FGs), I studied the ICL in systems with different masses: from the massive clusters of the RELICS sample to the lower-mass groups. Additionally, FGs are a particular type of galaxy association, where the brightest cluster galaxy is much more luminous than the other close galaxy members. It is believed that these systems must be ancient to reach this particular configuration and have remained isolated for an extended period of time.

The main result of my project is that the ICL can be used as a highly reliable indicator of the dynamical state of the systems. I observed that the ICL in merging clusters (active) is more abundant than in relaxed (passive) systems. Its color is also different: the ICL in passive clusters is similar to that of the massive galaxy members. In merging systems, it is a mixture of redder and bluer stellar populations. I also measured a parameter called ICL fraction, which compares the light emitted by the ICL with the light emitted by the whole cluster; this is, ICL plus galaxies. I found that active clusters show an excess in the ICL fraction measured at specific wavelengths. In contrast, relaxed clusters have approximately the same ICL fraction at all wavelengths. Moreover, this behavior does not depend on the cluster's distance from us (redshift), but this excess seems ubiquitous. Only the location of this excess (or wavelength where it appears) differs depending on the cluster's redshift, indicating that the stars thrown into the ICL by the violent merger come from galaxies with different properties.

I also discovered that this excess is non-existent for FGs, indicating that these systems are indeed ancient and relaxed, which supports the hypothesis that they have remained undisturbed and isolated for an extended period of time. Additionally, I found that the ICL fractions and the system's mass (calculated from its hot gas distribution, visible in X-rays) can estimate the time elapsed since their last external interaction. All the evidence confirms that FGs are relics from the past. However, not all the systems that satisfy the definition are real fossils since their ICL shows they must have recently undergone a merger. Thus, I can use the ICL fractions to identify bona fide FGs from regular clusters that transitory reached the typical FG configuration.

I also used the ICL for other purposes, such as the discovery of Earendel, the most distant star known so far. Analyzing the cluster WHL0137-08, which is a powerful gravitational lens, we found a highly magnified galaxy forming an arc, dubbed the Sunrise Arc, at redshift 6.2. We observed a star (or a binary system) called Earendel in a region of maximum magnification. The star emitted light 900 million years after the Big Bang taking 12.9 billion years to reach us. I estimated the mass of the ICL in the region surrounding Earendel to predict if the flux of the star should vary in the following years. Although it was a rare possibility, my ICL measurements and microlensing simulations predicted that Earendel's flux should not change. Now, we have HST and JWST observations that confirmed that the flux of the star, surprisingly, has remained almost constant for the last eight years, making this the most successful and astonishing application of the ICL to date.

All the work done during these two years of project have been presented in 12 articles published in peer-reviewed, top-ranked scientifical journals (one in Nature), plus one accepted and another submitted,five international conferences and meetings, four outreach talks (two in the European Researcher's Night), a press release, several interviews for TV, radio, and newspapers, and an article for the bulletin of the Spanish Astronomical Society.
The algorithms I developed to study the ICL are the only ones that do not assume any a priori hypothesis about the properties of the ICL or the cluster galaxies. As a consequence, our results are unbiased. Our study is homogeneous and robust since it relies on superb-quality data from spatial telescopes: Hubble and James Webb. Thus, combining our precise tools and deep images opens a window to a part of our Universe that has remained understudied so far: the low-surface-brightness Universe, the faintest stellar light we can detect and measure.

Our results show that the ICL gives insights into how the most massive structures of our Universe formed, with a history full of violent encounters, associations, mergers, and material interchanges. Moreover, the ICL has revealed itself as a powerful tool to understand the accretion of matter across cosmic time and to know the stellar composition of galaxies and clusters of galaxies at different ages of the Universe.
Finally, secondary applications such as ICL-based forecasts have helped in unprecedented discoveries such as that of Earendel, the most distant known star to date, a witness of the cosmic down. This opens a window to a part of our Universe which remains completely unexplored: the first generations of stars created after the Big Bang.

The societal implications of my study are huge: it not only unveils our cosmic origins, adding a new link to the chain of our History, but also validates the great investment (economical and technical) made to build superb telescopes as Webb.
Color image of the ICL in cluster WHL0137
ICL fractions found for merging (red) and passive clusters (blue),and 2 fossil candidates.
Color image of the Sunrise Arc and Earendel, the most distant star known
Original image (right) and ICL map (left) of the fossil group RXJ1007+3800 in the F606W filter
Color image of cluster WHL0137
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