[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119754-en":3,"doc-seo-119754-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119754,549758146520,"Patrick","https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470",8,"Research & Report","Quantum State Tomography using Quantum Machine Learning","Quantum State Tomography (QST) reconstructs unknown quantum states, but conventional approaches demand many measurements, limiting practicality for large-scale quantum systems. This work integrates Quantum Machine Learning (QML) methods to improve QST efficiency through a comprehensive review of classical and quantum techniques. Implemented QML-based strategies are validated on simulated and experimental multi-qubit systems, achieving up to 98% fidelity with far fewer measurements than conventional protocols, supporting scalable applications in Quantum Information Processing.","arXiv :2308 . 10327v1 [ quant-ph] 20 Aug 2023  \nQuantum State Tomography using Quantum Machine Learning  \nNouhaila Innan1 ,2‡, Owais Ishtiaq Siddiqui3 , Shivang Arora4 , Tamojit Ghosh5 , Yasemin Poyraz Ko¸cak6 , Dominic Paragas7 , Abdullah Al Omar Galib8 , Muhammad Al-Zafar Khan2 ,9 § and Mohamed Bennai 1  \n1 Quantum Physics and Magnetism Team, LPMC, Faculty of Sciences Ben M’sick, Hassan II University of Casablanca, Morocco  \n2 Quantum Formalism Fellow, Zaiku Group Ltd, Liverpool, United Kingdom  \n3 Department of Physics, COMSATS University Islamabad, 45550, Pakistan.  \n4 Technical University of Munich, Munich, Germany  \n5 Department of Physics, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India  \n6 Istanbul University-Cerrahpa¸sa, Computer Technology Department, Istanbul, Turkey  \n7 University of California Berkeley, California, USA  \n8 Independent Researcher  \n9 Robotics, Autonomous Intelligence, and Learning Laboratory (RAIL), School of Computer Science and Applied Mathematics, University of the Witwatersrand, 1 Jan Smuts Ave, Braamfontein, Johannesburg 2000, Gauteng, South Africa  \nAbstract. Quantum State Tomography (QST) is a fundamental technique in Quantum Information Processing (QIP) for reconstructing unknown quantum states. However, the conventional QST methods are limited by the number of measurements required, which makes them impractical for large-scale quantum systems. To overcome this challenge, we propose the integration of Quantum Machine Learning (QML) techniques to enhance the efficiency of QST. In this paper, we conduct a comprehensive investigation into various approaches for QST, encompassing both classical and quantum methodologies; We also implement different QML approaches for QST and demonstrate their effectiveness on various simulated and experimental quantum systems, including multi-qubit networks. Our results show that our QML-based QST approach can achieve high fidelity (98%) with significantly fewer measurements than conventional methods, making it a promising tool for practical QIP applications.  \nKeywords: Quantum State Tomography, Quantum Machine Learning, Quantum Variational Circuit, Quantum Information Processing  \n‡ [nouhaila.innan-etu@etu.univh2c.ma](nouhaila.innan-etu@etu.univh2c.ma)  \n§ [muhammadalzafark@gmail.com](muhammadalzafark@gmail.com)  \nQuantum State Tomography using Quantum Machine Learning 2  \n1. Introduction  \nQuantum Information Processing (QIP) involves the storage, transmission, and computation of information using the principles of Quantum Mechanics as a driver for effectively carrying out these tasks. For QIP to be effective, quantum systems must be prepared, controlled, and characterised. As a result of the act of measurement on a quantum system, the system will inevitably disintegrate from its current state to one of its eigenstates via wavefunction collapse. Subsequently, the usage of a single copy of the collapsed state to access the system’s initial state is impossible. Additionally, the no-cloning theorem [1] prohibits making multiple copies of the unknown state in order to reconstruct it further. Quantum State Tomography (QST) is an experimental procedure where the ensemble of unknown, but identically prepared quantum states, is characterised by a sequence of measurements in different bases, enabling the reconstruction of its density matrix. Analogous to medical tomographic reconstructions, in QST, several measurements in the various bases are taken and combined to give a reconstruction of the complete (initial) quantum state.  \nMeasurement on a quantum system generally gives a probabilistic result, and the measurement outcome only provides limited information about the state of the system, even when an ideal measurement device is used. QST consists of only finite measurements and the use of appropriate estimation algorithms. Hence, choosing optimal measurement sets, and designing efficient state reconstruction algorithms, are two critical is","cbCaibk3Yrys2kZV","https://ap.wps.com/l/cbCaibk3Yrys2kZV","pdf",1452335,1,18,"English","en",105,"# Abstract\n# Introduction\n## Quantum state preparation, measurement, and reconstruction\n## Algorithmic workflow for QST\n## Applications and motivation for QML-accelerated QST","[{\"question\":\"What is Quantum State Tomography (QST) used for?\",\"answer\":\"QST is used to reconstruct unknown quantum states by combining measurements performed in different bases to form the density matrix.\"},{\"question\":\"Why do conventional QST methods become impractical for large systems?\",\"answer\":\"They require a large number of measurements, making them inefficient and difficult to scale to large quantum systems.\"},{\"question\":\"How does Quantum Machine Learning improve QST efficiency?\",\"answer\":\"The paper proposes QML-based reconstruction approaches that achieve high fidelity while using significantly fewer measurements than conventional QST methods.\"}]","Quantum State Tomography using Quantum Machine Learning | PDF",1785726126,45,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"quantum-state-tomography-using-quantum-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/quantum-state-tomography-using-quantum-machine-learning/119754/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is Quantum State Tomography (QST) used for?","Question",{"text":75,"@type":76},"QST is used to reconstruct unknown quantum states by combining measurements performed in different bases to form the density matrix.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Why do conventional QST methods become impractical for large systems?",{"text":80,"@type":76},"They require a large number of measurements, making them inefficient and difficult to scale to large quantum systems.",{"name":82,"@type":73,"acceptedAnswer":83},"How does Quantum Machine Learning improve QST efficiency?",{"text":84,"@type":76},"The paper proposes QML-based reconstruction approaches that achieve high fidelity while using significantly fewer measurements than conventional QST methods.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]