During the last two decades, new high-precision cosmological observations have revolutionized our understanding of the early universe, to the point at which we are today able to pin-point the age and the composition of the universe to percent accuracy. However, as the precision of each experiment increases, there is one source of uncertainty that eventually will affect all new measurements, namely contaminating radiation emitted from our own Milky Way. To remove these contaminants from the data, one has to perform a process called astrophysical component separation, which is a major branch of contemporary computational cosmology. Furthermore, it is a field in which the University of Oslo (UiO) currently plays an internationally leading role.
The original goal of the INTPART funded Global Component Separation Network (GCSN) was to bring together international scientists from four forward-looking experiments (COMAP, LiteBIRD, PASIPHAE and SPIDER) to exchange experience and knowledge and teach component separation to the next generation of cosmologists. The advantage of joint analysis of complementary datasets is that they break each other's degeneracies, and we get a best possible characterization of the different instruments, the astrophysics of our own galaxy, and the fundamental cosmological parameters we are after.
The significance of this approach is getting more and more clear within the cosmological and astrophysical scientific environment, and in 2019 the European Research Council (ERC) funded the Cosmoglobe research project, lead by the GCSN PI. Since then, Cosmoglobe and GCSN have developed into an integrated research project with a goal of joint analysis of as many datasets as possible into a common sky model, where Cosmoglobe covers fundamental research and GCSN covers network building and training of the next generation scientists. The first major Cosmoglobe data release took place in March 2023, and included the first joint raw data analysis of two leading Cosmic Microwave Background (CMB) satellites, NASA's WMAP and ESA's Planck. This analysis has revolutionized the way this type of data will be analyzed in the future, and experiments, collaborations and scientistst all over the globe are now joining forces in Cosmoglobe to create a joint model of the Universe.
Global Componet Separation Network originally spanned eight internationally leading education and research institutions (Caltech, IUCAA, KwaZulu-Natal, Kavli IPMU/Tokyo, Oslo, Princeton, South African Astronomical Observatory, and Toronto), but have during the project period expanded to include 15 institutions in 6 countries. Together with Cosmoglobe the number of dedicated experiments have grown from 4 to 9, while at least 18 experiments and several hundred scientists have attended our meetings. We have developed a permanent intensive course in cosmological component separation and Bayesian data analysis at University of Oslo - with more international participants than we can accommodate - and we have facilitated student and researcher visits and not least arranged more than ten international meetings - some of them digital due to the pandemic.
We have built up an intensive course in cosmological component separation and Bayesian data analysis at University of Oslo (UiO). This is an integrated part of UiO's course portfolio with course code AST5240 for master students and AST9240 for phd students, and with a mechanism for giving official ECTS from UiO to external students. Here students get an introduction to the cosmic microwave background (CMB), cosmological experiments, instrumentation and data analysis, and the astrophysics of the Milky Way, as well as hands-on tutorials to component separation and Bayesian data analysis in general. More importantly, students with very diverse backgrounds (geographic, scientific, and experiment-wise) come together to work on a common project. We have during the project period continuously developed the course based on feedback, current research and new ideas, and the overarching theme of each installment of the course is now a joint large project work that leads to a joint publication. Anonymous course evaluations show that students find the course useful and fun.
The collaborative cutting-edge nature of the course naturally leads to continued collaborations, and the course has become the most important recruitment channel for scientific collaborators. Together with community-wide meetings, experiment-related smaller meetings and intermediate workshops, the yearly intensive course is a cornerstone of the global community that Cosmoglobe and the Global Component Separation Network (GCSN) have built to jointly tackle joint global analysis. This initiative now has around 50 core collaborators whereof more than half are international, while several hundred have attended some of our activities.
Moving from per-experiment analysis to joint global analysis can be viewed as a paradigm shift in the community and the GCSN was one of the main forerunners for this to happen. The latest and most visible example of this is the joint data analysis of the two last CMB satellite missions, Planck and WMAP, being submitted in March 2023; for the first time the maps from these two satellite experiments are consistent at large scales, a problem that has puzzled the community since the first Planck release in 2013. Joint analysis of two or more experiments break each others degeneracies, and for Planck and WMAP this means that the excess signal from unconstrained instrumental systematics is gone and we get a clearer view of the underlying cosmology like when the first stars were born.
The INTPART-funded Global Component Separation Network has already contributed positively to the funding of Cosmoglobe from the ERC, and the results and collective expertise of GCSN and Cosmoglobe will hopefully lead to even more EU funding and ideally a Center of Excellence in the future. These may then be utilized to complete the vision of truly global analysis of all cosmological datasets, and serve as a training ground and opportunity network for the next generation of cosmologists.
During the last two decades, new high-precision cosmological
observations have revolutionized our understanding of the early
universe, to the point at which we are today able to pin-point the age
and the composition of the universe to percent accuracy. However, as
the precision of each experiment increases, there is one source of
uncertainty that eventually will affect all new measurements, namely
contaminating radiation emitted from our own Milky Way. To remove
these contaminants from the data, one has to perform a process called
astrophysical component separation, which is a major branch of
contemporary computational cosmology. Furthermore, it is a field in
which the University of Oslo (UiO) currently plays an internationally
In this proposal we propose to establish a network of eight
internationally leading education and research institutions (Caltech,
IUCAA, KwaZulu-Natal, Kavli IPMU/Tokyo, Oslo, Princeton, South African
Astronomical Observatory, and Toronto) and four state-of-the-art
cosmology experiments (COMAP, LiteBIRD, PASIPHAE, and SPIDER), and
employ this network to enhance both teaching and research in each
individual member institution. The main focus of this network lies on
education and teaching, and is thus complementary to and will enhance
on-going efforts dedicated to the scientific aspects of each
experiment. Specifically, we will 1) host a bi-annual summer school
for partner students; 2) create a new course in astrophysical
component separation at the University of Oslo; 3) facilitate student
exchange between parter institutions; and 4) organize work meetings,
cross-experiment meetings, and an international conference targeting
young scientists, PhD and master students.
The long-term goal of the project is to establish this network as an
internationally recognized hub for astrophysical component separation
effort and computational cosmology. As such, it will consolidate
Norway's leading position in the field in the coming decade.