Galaxy-galaxy strong lensing in galaxy clusters is a unique tool for studying the subhalo mass distribution, as well as for testing predictions from cosmological simulations. We describe a novel method that simulates realistic lensed features embedded inside the complexity of observed data by exploiting high-precision cluster lens models. Such methodology is used to build a large dataset with which Convolutional Neural Networks have been trained to identify strong lensing events in galaxy clusters. In particular, we inject lensed sources around cluster members using the images acquired by the Hubble Space Telescope. The resulting simulated mock data preserve the complexity of observation by taking into account all the physical components that could affect the morphology and the luminosity of the lensing events. The trained networks achieve a purity-completeness level of ∼ 91% in detecting such events. The methodology presented can be extended to other data-intensive surveys carried out with the next-generation facilities.

We present high-precision strong lensing models for the galaxy clusters MACS J0416.1–0403 at z=0.396 and Abell 2744 at z=0.307. The models are constrained by two of the largest data-sets of secure multiple images ever used in lensing. These are identified from the photometric images observed by the Hubble space telescope and JWST in combination with spectroscopic data obtained by the Multi-Unit Spectroscopic Explorer at the Very Large Telescope. The same spectro-photometric data are used to create pure and complete samples of cluster member galaxies. Our models allow an extremely precise estimation of the cluster total mass distribution and produce accurate magnification maps that are fundamental to study the physical properties (mass, size, luminosity, etc.) of the lensed high-redshift galaxies.

The identification of young massive star clusters (YMCs) at high redshift is becoming a real fact. We present recent results from Hubble deep imaging and VLT/ MUSE - X-Shooter observations boosted by strong gravitational lensing. We report on two parsec-scale star-forming systems at z = 6.145 and 2.37 (>10 Gyrs of look back time) currently representing the best candidate high-z YMCs. All of this also implies that the search for globular cluster precursors has already begun.

Euclid is the next ESA mission devoted to cosmology. It aims at observing most of the extragalactic sky, studying both gravitational lensing and clustering over ~15,000 square degrees. The mission is expected to be launched in year 2020 and to last six years. The sheer amount of data of different kinds, the variety of (un)known systematic effects and the complexity of measures require efforts both in sophisticated simulations and techniques of data analysis. We review the mission main characteristics, some aspects of the the survey and highlight some of the areas of interest to this meeting.

The Euclid space mission proposes to survey 15000 square degrees of the extragalactic sky during 6 years, with a step-and-stare technique. The scheduling of observation sequences is driven by the primary scientific objectives, spacecraft constraints, calibration requirements and physical properties of the sky. We present the current reference implementation of the Euclid survey and on-going work on survey optimization.

Comparisons between observed and predicted strong lensing properties of galaxy clusters have been used to claim either tension or consistency with ΛCDM cosmology. However, standard approaches to such tests are unable to quantify the preference for one cosmology over another. We advocate a Bayesian approach whereby the parameters defining the scaling relation between Einstein radii and cluster mass are treated as the observables. We demonstrate a method of estimating the likelihood for observing these parameters under the ΛCDM framework, using the X-ray selected z > 0.5 MACS clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We account for cluster lens triaxiality within the modelling of the likelihood function. Cluster selection criteria is found to play as important a role as the uncertainty related to the description of star formation and feedback.

An experiment to study the physics of merging and of focusing ion beams is under development at the Lawrence Berkeley Laboratory. In this design, parallel beams of ions (C+, Al+, or Al++) are accelerated to several MV and merged transversely. The merged beams are then further accelerated and the growth in transverse and longitudinal emittance is determined for comparison with theory. The completed apparatus will be used to study problems associated with focusing ion beams to a small spot as required for heavy ion fusion. Details of the accelerator design and considerations of the physics of combining beams are presented.

Background and purpose. Depressive symptoms are frequently associated with heart failure (HF), but the brain mechanisms underlying such association are unclear. We hypothesized that the presence of major depressive disorder (MDD) emerging after the onset of HF would be associated with regional cerebral blood flow (rCBF) abnormalities in medial temporal regions previously implicated in primary MDD, namely the hippocampus and parahippocampal gyrus.

Method. Using 99mTc-SPECT, we measured rCBF in 17 elderly MDD-HF patients, 17 non-depressed HF patients, and 18 healthy controls, matched for demographic variables. Group differences were investigated with Statistical Parametric Mapping.

Results. Significant rCBF reductions in MDD-HF patients relative to both non-depressed HF patients and healthy controls were detected in the left anterior parahippocampal gyrus and hippocampus (ANOVA, p=0·008 corrected for multiple comparisons) and the right posterior hippocampus and parahippocampal gyrus (p=0·005 corrected). In the overall HF group, there was a negative correlation between the severity of depressive symptoms and rCBF in the right posterior hippocampal/parahippocampal region (p=0·045 corrected).

Conclusions. These findings are consistent with the notion that the medial temporal region is vulnerable to brain perfusion deficits associated with HF, and provide evidence that such functional deficits may be specifically implicated in the pathophysiology of MDD associated with HF.