{"title":"研究虫洞可行性的深度学习和量子算法方法:综述","authors":"Wahyu Rahmaniar , B. Ramzan , Alfian Ma'arif","doi":"10.1016/j.ascom.2024.100802","DOIUrl":null,"url":null,"abstract":"<div><p>Wormholes, hypothetical structures connecting distant regions of spacetime, have long captured the imagination of scientists and science fiction fans alike. Wormholes are a complex phenomenon with challenges that require innovative approaches and interdisciplinary investigations. In this review, we investigate the potential of deep learning and quantum algorithms to explain the implications of wormholes as an alternative to traditional analytical methods of this phenomenon. A comprehensive analysis of the current understanding of wormholes is elaborated to discuss its theoretical foundations and limitations further. Next, deep learning techniques and quantum algorithms are examined for their application in the context of wormhole research. Previous approaches and findings were discussed to evaluate the effectiveness of these computational techniques in unraveling the mysteries surrounding wormholes. Our review is expected to provide new perspectives for future research. Emphasizes the synergistic potential of deep learning and quantum algorithms in advancing our understanding of wormholes and their existence as interesting shortcuts in spacetime.</p></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"47 ","pages":"Article 100802"},"PeriodicalIF":1.9000,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep learning and quantum algorithms approach to investigating the feasibility of wormholes: A review\",\"authors\":\"Wahyu Rahmaniar , B. Ramzan , Alfian Ma'arif\",\"doi\":\"10.1016/j.ascom.2024.100802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Wormholes, hypothetical structures connecting distant regions of spacetime, have long captured the imagination of scientists and science fiction fans alike. Wormholes are a complex phenomenon with challenges that require innovative approaches and interdisciplinary investigations. In this review, we investigate the potential of deep learning and quantum algorithms to explain the implications of wormholes as an alternative to traditional analytical methods of this phenomenon. A comprehensive analysis of the current understanding of wormholes is elaborated to discuss its theoretical foundations and limitations further. Next, deep learning techniques and quantum algorithms are examined for their application in the context of wormhole research. Previous approaches and findings were discussed to evaluate the effectiveness of these computational techniques in unraveling the mysteries surrounding wormholes. Our review is expected to provide new perspectives for future research. Emphasizes the synergistic potential of deep learning and quantum algorithms in advancing our understanding of wormholes and their existence as interesting shortcuts in spacetime.</p></div>\",\"PeriodicalId\":48757,\"journal\":{\"name\":\"Astronomy and Computing\",\"volume\":\"47 \",\"pages\":\"Article 100802\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-02-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Astronomy and Computing\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2213133724000179\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ASTRONOMY & ASTROPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Astronomy and Computing","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213133724000179","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
Deep learning and quantum algorithms approach to investigating the feasibility of wormholes: A review
Wormholes, hypothetical structures connecting distant regions of spacetime, have long captured the imagination of scientists and science fiction fans alike. Wormholes are a complex phenomenon with challenges that require innovative approaches and interdisciplinary investigations. In this review, we investigate the potential of deep learning and quantum algorithms to explain the implications of wormholes as an alternative to traditional analytical methods of this phenomenon. A comprehensive analysis of the current understanding of wormholes is elaborated to discuss its theoretical foundations and limitations further. Next, deep learning techniques and quantum algorithms are examined for their application in the context of wormhole research. Previous approaches and findings were discussed to evaluate the effectiveness of these computational techniques in unraveling the mysteries surrounding wormholes. Our review is expected to provide new perspectives for future research. Emphasizes the synergistic potential of deep learning and quantum algorithms in advancing our understanding of wormholes and their existence as interesting shortcuts in spacetime.
Astronomy and ComputingASTRONOMY & ASTROPHYSICSCOMPUTER SCIENCE,-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.10
自引率
8.00%
发文量
67
期刊介绍:
Astronomy and Computing is a peer-reviewed journal that focuses on the broad area between astronomy, computer science and information technology. The journal aims to publish the work of scientists and (software) engineers in all aspects of astronomical computing, including the collection, analysis, reduction, visualisation, preservation and dissemination of data, and the development of astronomical software and simulations. The journal covers applications for academic computer science techniques to astronomy, as well as novel applications of information technologies within astronomy.