{"title":"面向高能衍射的深度学习增强蒙特卡罗事件发生器","authors":"Mikael Mieskolainen","doi":"10.5506/aphyspolbsupp.16.5-a6","DOIUrl":null,"url":null,"abstract":"We introduce GRANIITTI, a new Monte Carlo event generator designed especially to solve the enigma of glueballs at the LHC. We discuss the available physics processes, compare the simulations against STAR data from RHIC and span ambitious future directions towards the first diffractive event generator with a deep learning-enhanced computational engine.","PeriodicalId":39158,"journal":{"name":"Acta Physica Polonica B, Proceedings Supplement","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Graniitti: Towards a Deep Learning-enhanced Monte Carlo Event Generator for High-energy Diffraction\",\"authors\":\"Mikael Mieskolainen\",\"doi\":\"10.5506/aphyspolbsupp.16.5-a6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce GRANIITTI, a new Monte Carlo event generator designed especially to solve the enigma of glueballs at the LHC. We discuss the available physics processes, compare the simulations against STAR data from RHIC and span ambitious future directions towards the first diffractive event generator with a deep learning-enhanced computational engine.\",\"PeriodicalId\":39158,\"journal\":{\"name\":\"Acta Physica Polonica B, Proceedings Supplement\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Physica Polonica B, Proceedings Supplement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5506/aphyspolbsupp.16.5-a6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Physics and Astronomy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Physica Polonica B, Proceedings Supplement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5506/aphyspolbsupp.16.5-a6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Physics and Astronomy","Score":null,"Total":0}
Graniitti: Towards a Deep Learning-enhanced Monte Carlo Event Generator for High-energy Diffraction
We introduce GRANIITTI, a new Monte Carlo event generator designed especially to solve the enigma of glueballs at the LHC. We discuss the available physics processes, compare the simulations against STAR data from RHIC and span ambitious future directions towards the first diffractive event generator with a deep learning-enhanced computational engine.
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