For many years, INFN has developed its own infrastructure dedicated to scientific computing. Both analysing data produced by the big experiments and theoretical simulations actually need computing power, large storage quantities, and ultra-fast networks. In general, the synergy between computing capacity and network speed is essential for creating scalable and efficient IT infrastructure. Modern computing environments require high-speed networks to enable efficient communication between distributed systems and the sharing of computational resources. INFN proposed the National Centre for Supercomputing (ICSC) that aims to develop a distributed scientific computing infrastructure, of the Data Lake kind. This will be accessible to the whole national research community, integrating and strengthening existing computing resources with funds made available by the PNRR and extending the networks able to exchange data at the speed of a terabit per second throughout the nation.
Quantum computers have always been considered a kind of “holy grail” of technological innovation, capable of revolutionising the IT world and all of society thanks to their applications.
Today, computers and supercomputers are essential tools for physics research, with the purpose of analysing experimental data and implementing theoretical models useful for studying often very complex phenomena, impossible to investigate with conventional analytical tools.
The increase in the sensitivity and efficiency of physics experiments, combined with the use of more and more technologically advanced electronics, has led to an explosion in the quantity of data collected during experiments in recent decades.
The integration of automatic learning or machine learning – i.e. the capacity of a machineto learn and improve its performance with experience – in modelling physical systems and analysing experimental data is offering very interesting opportunities (in some cases, revolutionary ones) for the scientific community.
Since the dawn of the scientific investigation of natural phenomena, the construction ofsimplified models of physical reality has been an essential tool for studying more or less complex systems.