+44-1518-081136Algorithmically discovering high temperature superconductors with quantum computers
Joint event on WORLD CONGRESS ON SMART MATERIALS AND STRUCTURES & 3rd International Conference on POLYMER CHEMISTRY AND MATERIALS ENGINEERING
November 21-22, 2019 | Singapore
Deep Prasad
ReactiveQ, Canada
Posters & Accepted Abstracts : Mater Sci Nanotechnol
Abstract:
Superconductors play an integral role in magnetic
resonance imaging (MRI), nuclear magnetic resonance
(NMR) and fusion reactors for magnetic confinement.
When they were first discovered in the early 20th century,
it was unclear what physics went behind making them
work. Since then, we have come a long way in describing
at least one class of superconductors: low temperature,
Type I and Type II superconductors. The mechanism giving
rise to this class of low temperature superconductors is
quantum mechanical in nature. Therefore, it is conceivable
that such processes can be modelled easier and with more
robustness on quantum computers as opposed to classical
computers. This modelling ability can then be exploited to
explore a broader search space of other superconductors
that may have not been discovered yet.
ReactiveQ has created a computational engineering
platform that allows for multi-physics simulations to
be run on classical supercomputers as well as quantum
computers. In lieu of accelerating the discovery of new
materials, namely superconductors, ReactiveQ looked at
the viability of both near-term, Noisy Intermediate Scale
Quantum (NISQ) algorithms as well as long-term Universal
Gate model algorithms that could be used to automate the
discovery of high temperature superconductors.
Biography:
E-mail:
Deep@reactiveq.ioPDF HTML