Quantum computing using continuous-time evolution
- URL: http://arxiv.org/abs/2004.00704v1
- Date: Wed, 1 Apr 2020 20:58:15 GMT
- Title: Quantum computing using continuous-time evolution
- Authors: Viv Kendon
- Abstract summary: Digital silicon computers have reached their limits in terms of speed.
Quantum computing exploits the coherence and superposition of quantum systems.
Early quantum computers will be small, reminiscent of the early days of digital silicon computing.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Computational methods are the most effective tools we have besides scientific
experiments to explore the properties of complex biological systems. Progress
is slowing because digital silicon computers have reached their limits in terms
of speed. Other types of computation using radically different architectures,
including neuromorphic and quantum, promise breakthroughs in both speed and
efficiency. Quantum computing exploits the coherence and superposition
properties of quantum systems to explore many possible computational paths in
parallel. This provides a fundamentally more efficient route to solving some
types of computational problems, including several of relevance to biological
simulations. In particular, optimisation problems, both convex and non-convex,
feature in many biological models, including protein folding and molecular
dynamics. Early quantum computers will be small, reminiscent of the early days
of digital silicon computing. Understanding how to exploit the first generation
of quantum hardware is crucial for making progress in both biological
simulation and the development of the next generations of quantum computers.
This review outlines the current state-of-the-art and future prospects for
quantum computing, and provides some indications of how and where to apply it
to speed up bottlenecks in biological simulation.
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