AF: Small: Is the Simulation of Quantum Many-Body Systems Feasible on the Cloud?

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Simulating quantum mechanics with its unique effects such as superposition, interference, and entanglement is a hard problem for classical computing systems including supercomputers and computer clouds with a very large number of servers. To efficiently simulate large quantum-mechanical systems using a computer cloud one has to overcome major obstacles. This research investigates optimal algorithms for contracting tensor networks which arising in the study of condensed matter physics. These algorithms minimize the required communication between the nodes of the computer cloud and exploit its hierarchical organization. The broader research objective in this effort is to optimally exploit the architecture of hierarchically organized systems for big data applications that exhibit fine-grained parallelism.This research project aims to find new efficient methods for simulating large quantum systems that are important for quantum information processing, condensed matter physics, materials science, and chemistry. Its goals are to design and implement novel parallel and distributed simulation algorithms optimized for cloud computing environments such as Amazon Web Services and the National Science Foundation?s future cloud for scientific computing. The ultimate motivation of this project is to enable researchers world-wide to significantly push the boundary in terms of the size of quantum systems that they can simulate reliably and within a reasonable time and with a reasonable budget. While the research mainly concentrates on efficient algorithms and their implementation for the study of properties of condensed matter systems, it also attempts to derive generic strategies to other classes of applications, for instance, in artificial intelligence and in machine learning.