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ABSTRACT: The LSST survey will provide multi-epoch, multi-wavelength (u,g,r,i,z,y) mapping of the Southern Hemisphere, with a single-visit depth of r~24.5 and a gain of three magnitudes by the end of the program. This unprecedented spatial coverage will enable detection of young, pre-main sequence stars and stellar clusters down to distances of 5-10 kpc. A crucial and challenging step for spatial analyses of large stellar populations is measuring the extinction Av of individual objects. Multi-color photometry on a (r-i, g-r) or (i-J, r-i) diagram offers a direct solution to this issue for M-type stars: indeed, while the color locus of early-type (< K7) stars on these diagrams is parallel to the reddening vector, the color locus traced by M-type stars is tilted with respect to the reddening vector, which enables a straightforward and empirical measurement of their Av. By investigating the correlation between extinction and spatial properties of M-type stars in a given field, it is therefore possible to reconstruct the structure of the region and probe the nature of its population. In this study, we test the method on the NGC 2264 field. We selected a 2°x2° area centered on the NGC 2264 cluster, and collected the available r,i,J photometry from existing large-scale surveys (notably Pan-STARRS and UKIDSS). Then, assuming no prior knowledge on the nature of stars in the field, we used the (i-J, r-i) diagram to identify and deredden M-type stars in the sample, and the (r-i, r) + (RA, Dec) diagrams to investigate the nature and spatial distribution of stars as a function of their Av. We derived a non-uniform distribution of Av across the region, and could distinguish between a diffuse field population and a clustered stellar population toward the center of the field. An a posteriori comparison between the inferred spatial density map of the clustered population and the literature census of the NGC 2264 cluster enabled us to assess the performance of the method and its predictive capability.

Unveiling the many possible chemical routes through which life might have originated and evolved on early Earth is a task traditionally faced by means of peculiar experiments. However, in the last few years, state-of-the-art computational approaches have been put forward as powerful investigative tools in the wide spectrum of problems connected with the “origins of life” enigma. Advanced supercomputing techniques are nowadays able to simulate systems approaching the experimental complexity of a real sample, which they can model with the unprecedented reliability and precision conferred by Quantum Mechanics. In this way, avant-garde simulation methods such as ab initio molecular dynamics (AIMD), have suggested – with an atomistic detail – new chemical pathways for the synthesis of essential prebiotic species such as, e.g., amino acids [1].

Since ab initio simulations are nowadays capable to efficiently simulate disparate energy sources (i.e., electrical discharges [2], shock-waves mimicking meteoritic or grain impacts [3], high pressure/temperature regimes simulating hydrothermal conditions, UV radiation, etc.) most of the environments where life might have begun – both on Earth and in the outer space – can be reproduced to a high degree of reliability. Furthermore, novel metadynamics approaches [4] allow for the precise evaluation of the “plausibility degree” of each possible chemical pathway leading to the onset of prebiotically relevant molecules. This way, avant-garde computing educated with the laws of Density Functional Theory and Statistical Mechanics is able to reliably discern the most probable chemical route(s) within the a priori complex reaction network identifying a specific chemical transformation.

In this talk, after a brief examination of the basic concepts underlying those computational techniques, I will present disparate recent results gathered via advanced computing and that have offered novel insights not only in prebiotic chemistry but also in the more fundamental chemical physics scenario.