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Quantum-Inspired Optimization for Enterprises

Quantum-Inspired Optimization for Enterprises

R. Thilagavathy (Department of Computing Technologies, SRM Institute of Science and Technology, India), M. Gayathri (Department of Computing Technologies, SRM Institute of Science and Technology, India), G. K. Sandhia (Department of Computing Technologies, SRM Institute of Science and Technology, India), and M. Pushpalatha (Department of Computing Technologies, SRM Institute of Science and Technology, India)
Copyright: © 2024 |Pages: 11
DOI: 10.4018/979-8-3693-1168-4.ch018
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Abstract

Optimization involves finding the best solution from a set of possible options. Traditional computers employ classical algorithms like gradient descent and simulated annealing to solve these problems. However, as the complexity of problems increases, classical computers encounter limitations in terms of time and resources. Quantum optimization stands as a revolutionary paradigm that harnesses the unique properties of quantum mechanics to tackle complex optimization problems that are beyond the capabilities of classical computers. Quantum computers utilize qubits, the fundamental units of quantum information, which can exist in superpositions of states, enabling them to process a vast number of possibilities simultaneously. Additionally, the phenomenon of entanglement enables qubits to be correlated in ways that classical bits cannot, further enhancing their computational power. In this chapter, the authors will delve into the principles, applications, and current developments in the realm of quantum optimization.
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2. Quantum Mechanics Primer

Before we dive into quantum-inspired optimization, it's essential to have a basic understanding of quantum mechanics. At its core, quantum mechanics describes the behavior of particles at the atomic and subatomic levels. Several fundamental principles of quantum mechanics underpin quantum-inspired optimization (Gill, 2022):

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    Superposition: In quantum mechanics, particles can exist in multiple states simultaneously, a phenomenon known as superposition. Quantum-inspired optimization algorithms leverage this principle to explore multiple solutions to a problem simultaneously.

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    Entanglement: Entanglement is a quantum phenomenon where the properties of two or more particles become correlated, even when separated by vast distances. This concept is used to enhance the exploration of solution spaces in quantum-inspired optimization.

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    Quantum Bits (Qubits): Qubits are the quantum analogs of classical bits. Unlike classical bits, which can be either 0 or 1, qubits can exist in a superposition of states, representing both 0 and 1 simultaneously. This property enables quantum-inspired algorithms to process information in new and powerful ways.

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3. The Quantum-Inspired Advantage

Quantum-inspired optimization algorithms leverage the principles of quantum mechanics to tackle complex optimization problems efficiently. While true quantum computers are still in their infancy, quantum-inspired algorithms are readily available for enterprises to harness the power of quantum principles on classical hardware (Li, Y., 2020). Here's why enterprises should take notice:

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