Abstract
Present-day computers work on the principles of classical mechanics. Imagine a coin in the classical regime. When we toss the coin, it can take up either of these two states: “head” (H) or “tail” (T). However, in a quantum world, a coin, or rather a quantum one, can exist in both the states “head” and “tail” simultaneously. This property of quantum mechanical objects—existing in multiple states simultaneously—is known as superposition. Similarly, quantum mechanical objects can exhibit a much stronger correlation than their classical counterparts through the phenomenon of entanglement. Using entanglement, two or more quantum particles can be linked in perfect unison, even when they are placed at opposite ends of the universe. Quantum computing harnesses and exploits the laws of quantum mechanics, especially superposition, entanglement, and interference, to process information. An important idea in quantum computing is to collapse a probability distribution toward specific measurement states. Quantum interference is a by-product of quantum superposition, and it helps bias quantum measurement toward specific quantum states.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Santanu Pattanayak
About this chapter
Cite this chapter
Pattanayak, S. (2021). Introduction to Quantum Computing. In: Quantum Machine Learning with Python. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-6522-2_1
Download citation
DOI: https://doi.org/10.1007/978-1-4842-6522-2_1
Published:
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-6521-5
Online ISBN: 978-1-4842-6522-2
eBook Packages: Professional and Applied ComputingProfessional and Applied Computing (R0)Apress Access Books