NQN Seminar Series: Algorithms for near-term quantum computers

In this talk, Alán will discuss an overview of some example applications for near-term
quantum computers. He will start by an overview of the different families of algorithms that
have been developed so far and then delve in the variational quantum eigensolver and the
quantum computer-aided design algorithms. He will finish with some discussion about the
path forward.

Alán Aspuru-Guzik’s research lies at the interface of computer science with chemistry and
physics. He works in the integration of robotics, machine learning and high-throughput
quantum chemistry for the development of materials acceleration platforms. These “selfdriving laboratories¨ promise to accelerate the rate of scientific discovery, with applications to
clean energy and optoelectronic materials. Alán also develops quantum computer algorithms
for quantum machine learning and has pioneered quantum algorithms for the simulation of

Hosted by the Northwest Quantum Nexus (NQN), a coalition led by the U.S. Department of
Energy’s Pacific Northwest National Laboratory, Microsoft Quantum, and the University of
. These web-based seminars feature experts on quantum computing and its
applications, and support NQN’s goal of creating a vibrant industry that will contribute to the
economic vitality of the region. For questions, contact diane.stephens@pnnl.gov
Wednesday, June 9 | 3:00pm

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