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Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware
The ambitious HL-LHC program will require enormous computing resources in the next two decades. A burning question is whether quantum computer can solve the ever growing demand of computing resources in High Energy Physics in general and physics at LHC in particular.Using IBM Quantum Computer Simula...
| Autores principales: | , , , , , , , , |
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| Lenguaje: | eng |
| Publicado: |
SISSA
2019
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.22323/1.367.0049 http://cds.cern.ch/record/2712232 |
| _version_ | 1780965289398108160 |
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| author | Chan, Jay Guan, Wen Sun, Shaojun Wang, Alex Zeng Wu, Sau Lan Zhou, Chen Livny, Miron Carminati, Federico Meglio, Alberto Di |
| author_facet | Chan, Jay Guan, Wen Sun, Shaojun Wang, Alex Zeng Wu, Sau Lan Zhou, Chen Livny, Miron Carminati, Federico Meglio, Alberto Di |
| author_sort | Chan, Jay |
| collection | CERN |
| description | The ambitious HL-LHC program will require enormous computing resources in the next two decades. A burning question is whether quantum computer can solve the ever growing demand of computing resources in High Energy Physics in general and physics at LHC in particular.Using IBM Quantum Computer Simulators and Quantum Computer Hardware, we have successfully employed the Quantum Support Vector Machine Method (QSVM) for a ttH (H to two photons), Higgs coupling to top quarks analysis at LHC. |
| id | oai-inspirehep.net-1774966 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2019 |
| publisher | SISSA |
| record_format | invenio |
| spelling | oai-inspirehep.net-17749662022-08-17T12:59:29Zdoi:10.22323/1.367.0049http://cds.cern.ch/record/2712232engChan, JayGuan, WenSun, ShaojunWang, Alex ZengWu, Sau LanZhou, ChenLivny, MironCarminati, FedericoMeglio, Alberto DiApplication of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer HardwareParticle Physics - ExperimentComputing and ComputersThe ambitious HL-LHC program will require enormous computing resources in the next two decades. A burning question is whether quantum computer can solve the ever growing demand of computing resources in High Energy Physics in general and physics at LHC in particular.Using IBM Quantum Computer Simulators and Quantum Computer Hardware, we have successfully employed the Quantum Support Vector Machine Method (QSVM) for a ttH (H to two photons), Higgs coupling to top quarks analysis at LHC.SISSAoai:inspirehep.net:17749662019 |
| spellingShingle | Particle Physics - Experiment Computing and Computers Chan, Jay Guan, Wen Sun, Shaojun Wang, Alex Zeng Wu, Sau Lan Zhou, Chen Livny, Miron Carminati, Federico Meglio, Alberto Di Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware |
| title | Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware |
| title_full | Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware |
| title_fullStr | Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware |
| title_full_unstemmed | Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware |
| title_short | Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware |
| title_sort | application of quantum machine learning to high energy physics analysis at lhc using ibm quantum computer simulators and ibm quantum computer hardware |
| topic | Particle Physics - Experiment Computing and Computers |
| url | https://dx.doi.org/10.22323/1.367.0049 http://cds.cern.ch/record/2712232 |
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