This paper provides an overview of the potential applications and limitations of quantum computing in the field of civil engineering.
The authors first introduce the fundamental principles of quantum computing, highlighting its key differences from traditional binary computing. They then discuss the current challenges associated with scaling quantum computing, focusing on algorithms and problem classes that can be studied with current, noisy quantum computers.
The authors then review the areas where quantum computing has the potential to outperform traditional computing, including:
Simulations: Quantum computing holds the potential to enhance performance in solving differential equations, which are commonly used in finite element analysis (FEA) and computational fluid dynamics (CFD) problems in civil engineering.
Machine Learning: Quantum computing shows promise in the speed-up that may be achieved through quantum kernel methods for a variety of classification tasks, as well as advancements in algorithmic steps that may perform better on a quantum computer. However, the necessity of these quantum variants is debatable for some civil engineering applications, such as time series problems and deep learning models.
Optimization: Quantum computing has been explored for a number of optimization problems, such as resource allocation, scheduling, and network design, which are common in civil engineering. There is ongoing research to identify relevant problem-mappings to solutions like Max-Cut or QUBO.
The authors conclude that while quantum computing has the potential to catalyze a revolutionary paradigm shift in civil engineering, similar to the transformative impact of GPU computing, the innovations are expected to derive from the ability to address an entirely new set of challenges using specialized software, rather than simply accelerating existing code.
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by Joern Ploenn... klokken arxiv.org 03-29-2024
https://arxiv.org/pdf/2402.14556.pdfDypere Spørsmål