The primary objective of cosmological research in the coming decade is to understand the accelerated expansion of the Universe, attributed to either a dark energy component or a modification to gravity on cosmic scales.  This thesis will focus on evaluating the Euclid galaxy cluster selection function, an essential element of using the mission’s cluster catalog as a probe of dark energy and modified gravity.  
Galaxy cluster abundance is a powerful observational probe because cluster formation is highly sensitive to the presence of either dark energy or the effects of modified gravity. It is one of the central observational probes employed by Euclid, ESA’s mission dedicated to understanding the origin of the accelerated expansion and scheduled for launch in 2023-2024.  Euclid will produce one of the largest and deepest galaxy cluster catalogs ever for probing dark energy and modified gravity, requiring unprecedented control of the selection function. 
The thesis research will use simulations and available data to evaluate the selection function.  Because the selection function depends on intrinsic cluster properties, the student will run cluster finders on the simulations with varying cluster properties to quantify their impact on the selection function and final cosmological constants.  S/he will also evaluate the potential gains of new cluster detection methods, including those using artificial intelligence trained on catalogs of known clusters. The doctoral student will have the exciting opportunity to work with the first data from the Euclid mission and to contribute to the first cosmological constraints from the mission.
In practice, the doctoral student will:

• Extract and work with outputs from large cosmological simulations
• Perform theoretical modeling of galaxy cluster properties, including their galaxy populations and intra-cluster medium to predict detection at other wavelengths
• Use models and modify simulation outputs to produce mock galaxy cluster catalogs 
• Run available galaxy cluster finder codes on mock data and real data from Euclid and public archives
• Develop and apply artificial neural networks to find galaxy clusters in optical and infrared datasets
• Compare catalogs of simulated clusters to those detected by cluster finding algorithms to evaluate the cluster selection function  
• Apply methods to publicly available survey data and to the first data from the Euclid mission (launch 2023-2024).

Our research team has internationally recognized expertise in galaxy cluster science.  We held leadership roles on the Planck mission, including authorship and delivery of key analysis methods that were used to extract the cluster catalog, evaluate its selection function and extract cosmological constraints.
The APC laboratory is heavily invested in the Euclid mission with important responsibilities in both science and ground segment development.  On the ground segment, we lead the work package dedicated to preparing imaging data from the Rubin Observatory for ingestion into the Euclid pipeline, and we maintain the software development platform for the entire ground segment.  On science, we co-lead the Galaxy Cluster Science Working Group for the Euclid Consortium and the Selection Function Key Project (J.G. Bartlett).