Collaborative Research: Adiabatic Quantum Computing and Statistics

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For decades computer power has doubled for constant cost roughly once every two years according to the so-called Moore's law. This dream run is realized through technological advances in the fabrication of computer hardware, making electronic devices smaller and smaller. However, as the sizes of the computer electronic devices get close to the atomic scale, quantum effects are starting to interfere in their functioning, and thus conventional computer technology approaches run up against fundamental difficulties of size limit. This research project concerns quantum computing, the development of computer technology dependent on the principles of quantum physics, as opposed to the electronic devices following laws of classical physics used by classical computers. This revolutionary field will enable a range of exotic new devices, and in particular it will likely lead to the creation of powerful quantum computers. The research project is among the frontier research endeavors where quantum technologies are being developed and quantum devices are being built with capabilities exceeding those of classical computational devices. Quantum computation and quantum information science more generally concern the preparation and control of the quantum states of physical systems to manipulate and transmit information. A quantum system usually has complexity exponentially increasing with its size. As a result, it takes an exponential number of bits of memory on a classical computer to store the state of a quantum system, and simulations of quantum systems via classical computers face great computational challenge. On the other hand, since quantum systems are able to store and track an exponential number of complex numbers and perform data manipulations and calculations as the systems evolve, quantum systems hold great promise as computational tools. Quantum information science grapples with understanding how to take advantage of the enormous amount of information hidden in the quantum systems and to harness the immense potential computational power of atoms and photons for the purpose of information processing and computation. This cross-disciplinary research project addresses questions in quantum information science on the interface between quantum computing and machine learning and between quantum tomography and compressed sensing. The collaborative research aims to explore the power of adiabatic quantum computation and its impact on computer science and statistics in general and machine learning and Monte Carlo sampling in particular. The work investigates the use of leading techniques from machine learning in computer science and statistics, compressed sensing in applied mathematics, statistics, and engineering, and quantum tomography in quantum physics for adiabatic quantum computing. The research activities promote collaborations among investigators with different disciplinary backgrounds and stimulate novel ideas for possible breakthrough, transformative research.