Investigating the use of quantum computing and quantum machine learning to reduce carbon emissions in aviation

Quantum Base Alpha与爱丁堡大学合作，并从NQCC获得专业建议，将研究量子计算（QC）和量子机器学习（QML）的潜力，以帮助解决一个重要但目前棘手的问题。该项目的主要重点是通过优化飞行路线来最大限度地减少航空造成的碳排放。气候变化委员会是一个为英国政府提供建议的独立机构，据报告，航空目前产生了英国8%的温室气体排放。到2050年，具有法律约束力的净零碳目标，预计将成为剩余排放量巨大的关键部门。鉴于他们认为，由于开发和认证的准备时间长，而且机队周转缓慢，航空领域的重大技术突破不太可能产生重大影响，因此他们得出结论，届时航空将成为最大的排放部门。需要改善空域的使用，包括在空中交通管制中部署先进的工具。这包括需要研究和开发使用不断发展的量子计算技术与人工智能和机器学习一起。

Quantum Base Alpha in collaboration with the University of Edinburgh and specialised advice form the NQCC will investigate the potential of Quantum Computing (QC) together with Quantum Machine Learning ( QML)to help solve a vital but currently intractable problem. The project's main focus is to minimise the carbon emissions caused by aviation by optimising flight paths.The Climate Change Committee, an independent body advising the UK Government ,has reported that Aviation currently produces 8% of UK Greenhouse Gas Emissions . By 2050,the legally binding target for Net Zero Carbon , it is predicted to be the key sector with significant remaining emissions . Given their view that major technological breakthroughs in aviation are unlikely to make significant differences given long development and certification lead times and the slow turnover of fleets , they conclude that aviation will be the largest emitting sector then.Hence , the need to improve the use of Airspace including the deployment of cutting edge tools in Air Traffic Control.This includes the need to research and develop the use of evolving Quantum Computing techniques alongside AI and Machine Learning.