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Symposia
cases, such as for rotational systems, the excitation itself can provide providing substantial computational capability. The true power of quantum
passive tuning of the resonance to match the environmental conditions. In computing comes from the complexity of entanglement between many
other cases, alternative solutions are required. For linearly-excited energy qubits. When entanglement is realized, quantum algorithms for problems
harvesters, we have created multi degree of freedom systems in which the such as factoring numbers and solving linear algebra problems show
degrees of freedom interact with each other in multiple different ways, exponential speed-up relative to any known classical algorithm. Linear
further broadening the system’s operational range and enabling efficient algebra problems are of particular interest in engineering application for
harvesting from low frequency motions. The creation, analysis, and solving finite element and finite difference models. In this presentation,
demonstration of this family of systems will be presented, including the we explore quantum linear algebra problems where we design and
recent demonstration of a compact, passively-switched resonant implement a quantum circuit that can be tested on IBM’s quantum
harvester that reduces the hardware size by a factor of six as compared computing hardware. A set of quantum gates are assimilated into a circuit
with prior passively-switched harvesters while maintaining a comparable and implemented on the IBM Q system to demonstrate its algorithm
center frequency of 7 Hz, a comparable normalized power density, and a capabilities and its measurement methodology. The comparison of
frequency bandwidth of 6 Hz. numerical simulations and implementation results provide insight into the
quantum machine and performance attributes using certain quantum
Biography circuit operations. We explore different measurement methods to extract
quantum information that is expected to be beneficial to engineering
Carol Livermore is an Associate Professor in the Department of materials and structure problems. From this presentation, we will
Mechanical and Industrial Engineering at Northeastern University. demonstrate the capability of quantum computers with limited amount of
She received her B.S. in Physics from the University of Massachusetts, qubits and emphasize differences in quantum simulation results versus
Amherst in 1993, and her A.M. and Ph.D. in physics from Harvard IBM quantum hardware computations.
University in 1995 and 1998, respectively. She then joined the
Massachusetts Institute of Technology, first as a postdoc and research Biography
scientist and then as a member of the faculty in the Department of
Mechanical Engineering. She joined Northeastern University in 2011, Guanglei Xu is currently a postdoctoral researcher in the Florida Center for
where her current research focuses on micro technologies to address key Advanced Aero Propulsion (FCAAP) of Department of Mechanical
challenges in energy harvesting, tissue engineering, and microscale Engineering at Florida A&M-Florida State University College of
vacuum systems. She has published thirty-plus journal articles in journals Engineering. He earned his PhD degree in Physics from University of
such as Nano Letters, Lab on a Chip, Applied Physics Letters, and Science. Strathclyde, Scotland in 2018, performed research on adiabatic quantum
She has also received the NSF CAREER Award, multiple teaching awards, computing and classical noise in optical lattices. He has contributed to the
and both best paper and best poster awards at international conferences. field of computation fluid dynamics with quantum algorithm to provide
quantum speed up. His research interests include quantum computing
SYMPOSIUM 8 with digital and analog quantum computers and quantum simulators.
Guanglei joined FCAAP in May of 2018, mainly working on developing
CAN QUANTUM COMPUTERS SOLVE LINEAR ALGEBRA quantum algorithm and applications of quantum computers on
PROBLEMS TO ADVANCE ENGINEERING APPLICATIONS? material sciences.
Guanglei Xu
Post Doctorate Researcher
Florida Center for Advanced Aero-Propulsion (FCAAP)
Department of Mechanical Engineering
Florida State University
Abstract 23
Since its inception by Richard Feynman in 1982, quantum computing has
provided an intriguing opportunity to advance computational capabilities
over classical computing. Classical computers use bits that process
information in terms of zeros and ones. Quantum computers use the
complex world of quantum mechanics to carry out calculations using what
is known as a qubit (quantum analog of a classical bit). Quantum
computers are designed to solve certain problems that are intractable by
conventional computers. The dimension of corresponding Hilbert space
grows exponentially with the size of a quantum computer and thus
