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Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm
[Display omitted] •AGDE is utilized to optimize quantum cloning circuit parameters.•The experimental results reveal that AGDE is outperformed the other well-known metaheuristics algorithms.•AGDE is minimized the parameter values of cloning difference error value down to 10−8.•The qualitative and qua...
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Published in: | Journal of advanced research 2021-03, Vol.29, p.147-157 |
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creator | Houssein, Essam H. Mahdy, Mohamed A. Eldin, Manal. G. Shebl, Doaa Mohamed, Waleed M. Abdel-Aty, Mahmoud |
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•AGDE is utilized to optimize quantum cloning circuit parameters.•The experimental results reveal that AGDE is outperformed the other well-known metaheuristics algorithms.•AGDE is minimized the parameter values of cloning difference error value down to 10−8.•The qualitative and quantitative measurements proved the superiority of AGDE.
Quantum cloning operation, started with no-go theorem which proved that there is no capability to perform a cloning operation on an unknown quantum state, however, a number of trials proved that we can make approximate quantum state cloning that is still with some errors.
To the best of our knowledge, this paper is the first of its kind to attempt using meta-heuristic algorithm such as Adaptive Guided Differential Evolution (AGDE), to tackle the problem of quantum cloning circuit parameters to enhance the cloning fidelity.
To investigate the effectiveness of the AGDE, the extensive experiments have demonstrated that the AGDE can achieve outstanding performance compared to other well-known meta-heuristics including; Enhanced LSHADE-SPACMA Algorithm (ELSHADE-SPACMA), Enhanced Differential Evolution algorithm with novel control parameter adaptation (PaDE), Improved Multi-operator Differential Evolution Algorithm (IMODE), Parameters with adaptive learning mechanism (PALM), QUasi-Affine TRansformation Evolutionary algorithm (QUATRE), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Cuckoo Search (CS), Bat-inspired Algorithm (BA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA).
In the present study, AGDE is applied to improve the fidelity of quantum cloning problem and the obtained parameter values minimize the cloning difference error value down to 10-8.
Accordingly, the qualitative and quantitative measurements including average, standard deviation, convergence curves of the competitive algorithms over 30 independent runs, proved the superiority of AGDE to enhance the cloning fidelity. |
doi_str_mv | 10.1016/j.jare.2020.10.001 |
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fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_f68646a7788b4b70a4deffa8dd8f6f52</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S2090123220302204</els_id><doaj_id>oai_doaj_org_article_f68646a7788b4b70a4deffa8dd8f6f52</doaj_id><sourcerecordid>2511898899</sourcerecordid><originalsourceid>FETCH-LOGICAL-c521t-9aa61668365ee669278466f88bd5cdb6841ecab1c7004040ca26434311bcd0053</originalsourceid><addsrcrecordid>eNp9kc1u3CAUha2qURKleYEsKi-7mSlgjLFUVaqitokUKZtmja7h4mDZZgJ4pObpizvJqNkUFsDh3I-fUxRXlGwpoeLzsB0g4JYRtgpbQui74pyRlmwoY_z9cV6xs-IyxoHkVknZUnpanFWV5IxQdl7097vkJvfs5r58WmBOy1Tq0c_rWrugF5fKHQSYMGGIZQcRTennEgzkwj2W_eJMloyzFgPOycFY4t6PS3Krbex9cOlx-lCcWBgjXr6MF8XDj--_rm82d_c_b6-_3W10zWjatACCCiErUSMK0bJGciGslJ2ptemE5BQ1dFQ3hPDcNTDBK15R2mlDSF1dFLcHrvEwqF1wE4TfyoNTfwUfegUhOT2iskIKLqBpMp13DQFu0FqQxkgrbM0y6-uBtVu6CY3OrwswvoG-3Zndo-r9XskcSlXzDPj0Agj-acGY1OSixnGEGf0SFasplW0Opc1WdrDq4GMMaI_HUKLWwNWg1sDVGviq5cBz0cd_L3gseY03G74cDJi_fO8wqKgdzhqNC6hT_hP3P_4fmpe-mQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2511898899</pqid></control><display><type>article</type><title>Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm</title><source>ScienceDirect Journals</source><source>PubMed Central</source><creator>Houssein, Essam H. ; Mahdy, Mohamed A. ; Eldin, Manal. G. ; Shebl, Doaa ; Mohamed, Waleed M. ; Abdel-Aty, Mahmoud</creator><creatorcontrib>Houssein, Essam H. ; Mahdy, Mohamed A. ; Eldin, Manal. G. ; Shebl, Doaa ; Mohamed, Waleed M. ; Abdel-Aty, Mahmoud</creatorcontrib><description>[Display omitted]
•AGDE is utilized to optimize quantum cloning circuit parameters.•The experimental results reveal that AGDE is outperformed the other well-known metaheuristics algorithms.•AGDE is minimized the parameter values of cloning difference error value down to 10−8.•The qualitative and quantitative measurements proved the superiority of AGDE.
Quantum cloning operation, started with no-go theorem which proved that there is no capability to perform a cloning operation on an unknown quantum state, however, a number of trials proved that we can make approximate quantum state cloning that is still with some errors.
To the best of our knowledge, this paper is the first of its kind to attempt using meta-heuristic algorithm such as Adaptive Guided Differential Evolution (AGDE), to tackle the problem of quantum cloning circuit parameters to enhance the cloning fidelity.
To investigate the effectiveness of the AGDE, the extensive experiments have demonstrated that the AGDE can achieve outstanding performance compared to other well-known meta-heuristics including; Enhanced LSHADE-SPACMA Algorithm (ELSHADE-SPACMA), Enhanced Differential Evolution algorithm with novel control parameter adaptation (PaDE), Improved Multi-operator Differential Evolution Algorithm (IMODE), Parameters with adaptive learning mechanism (PALM), QUasi-Affine TRansformation Evolutionary algorithm (QUATRE), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Cuckoo Search (CS), Bat-inspired Algorithm (BA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA).
In the present study, AGDE is applied to improve the fidelity of quantum cloning problem and the obtained parameter values minimize the cloning difference error value down to 10-8.
Accordingly, the qualitative and quantitative measurements including average, standard deviation, convergence curves of the competitive algorithms over 30 independent runs, proved the superiority of AGDE to enhance the cloning fidelity.</description><identifier>ISSN: 2090-1232</identifier><identifier>EISSN: 2090-1224</identifier><identifier>DOI: 10.1016/j.jare.2020.10.001</identifier><identifier>PMID: 33842012</identifier><language>eng</language><publisher>Egypt: Elsevier B.V</publisher><subject>Adaptive guided differential evolution ; AGDE ; Cloned qubits ; Cloning fidelity ; Mathematics, Engineering, and Computer Science ; Meta-heuristics ; Quantum cloning</subject><ispartof>Journal of advanced research, 2021-03, Vol.29, p.147-157</ispartof><rights>2021</rights><rights>2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University.</rights><rights>2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c521t-9aa61668365ee669278466f88bd5cdb6841ecab1c7004040ca26434311bcd0053</citedby><cites>FETCH-LOGICAL-c521t-9aa61668365ee669278466f88bd5cdb6841ecab1c7004040ca26434311bcd0053</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020354/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S2090123220302204$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,3549,27924,27925,45780,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33842012$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Houssein, Essam H.</creatorcontrib><creatorcontrib>Mahdy, Mohamed A.</creatorcontrib><creatorcontrib>Eldin, Manal. G.</creatorcontrib><creatorcontrib>Shebl, Doaa</creatorcontrib><creatorcontrib>Mohamed, Waleed M.</creatorcontrib><creatorcontrib>Abdel-Aty, Mahmoud</creatorcontrib><title>Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm</title><title>Journal of advanced research</title><addtitle>J Adv Res</addtitle><description>[Display omitted]
•AGDE is utilized to optimize quantum cloning circuit parameters.•The experimental results reveal that AGDE is outperformed the other well-known metaheuristics algorithms.•AGDE is minimized the parameter values of cloning difference error value down to 10−8.•The qualitative and quantitative measurements proved the superiority of AGDE.
Quantum cloning operation, started with no-go theorem which proved that there is no capability to perform a cloning operation on an unknown quantum state, however, a number of trials proved that we can make approximate quantum state cloning that is still with some errors.
To the best of our knowledge, this paper is the first of its kind to attempt using meta-heuristic algorithm such as Adaptive Guided Differential Evolution (AGDE), to tackle the problem of quantum cloning circuit parameters to enhance the cloning fidelity.
To investigate the effectiveness of the AGDE, the extensive experiments have demonstrated that the AGDE can achieve outstanding performance compared to other well-known meta-heuristics including; Enhanced LSHADE-SPACMA Algorithm (ELSHADE-SPACMA), Enhanced Differential Evolution algorithm with novel control parameter adaptation (PaDE), Improved Multi-operator Differential Evolution Algorithm (IMODE), Parameters with adaptive learning mechanism (PALM), QUasi-Affine TRansformation Evolutionary algorithm (QUATRE), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Cuckoo Search (CS), Bat-inspired Algorithm (BA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA).
In the present study, AGDE is applied to improve the fidelity of quantum cloning problem and the obtained parameter values minimize the cloning difference error value down to 10-8.
Accordingly, the qualitative and quantitative measurements including average, standard deviation, convergence curves of the competitive algorithms over 30 independent runs, proved the superiority of AGDE to enhance the cloning fidelity.</description><subject>Adaptive guided differential evolution</subject><subject>AGDE</subject><subject>Cloned qubits</subject><subject>Cloning fidelity</subject><subject>Mathematics, Engineering, and Computer Science</subject><subject>Meta-heuristics</subject><subject>Quantum cloning</subject><issn>2090-1232</issn><issn>2090-1224</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9kc1u3CAUha2qURKleYEsKi-7mSlgjLFUVaqitokUKZtmja7h4mDZZgJ4pObpizvJqNkUFsDh3I-fUxRXlGwpoeLzsB0g4JYRtgpbQui74pyRlmwoY_z9cV6xs-IyxoHkVknZUnpanFWV5IxQdl7097vkJvfs5r58WmBOy1Tq0c_rWrugF5fKHQSYMGGIZQcRTennEgzkwj2W_eJMloyzFgPOycFY4t6PS3Krbex9cOlx-lCcWBgjXr6MF8XDj--_rm82d_c_b6-_3W10zWjatACCCiErUSMK0bJGciGslJ2ptemE5BQ1dFQ3hPDcNTDBK15R2mlDSF1dFLcHrvEwqF1wE4TfyoNTfwUfegUhOT2iskIKLqBpMp13DQFu0FqQxkgrbM0y6-uBtVu6CY3OrwswvoG-3Zndo-r9XskcSlXzDPj0Agj-acGY1OSixnGEGf0SFasplW0Opc1WdrDq4GMMaI_HUKLWwNWg1sDVGviq5cBz0cd_L3gseY03G74cDJi_fO8wqKgdzhqNC6hT_hP3P_4fmpe-mQ</recordid><startdate>20210301</startdate><enddate>20210301</enddate><creator>Houssein, Essam H.</creator><creator>Mahdy, Mohamed A.</creator><creator>Eldin, Manal. G.</creator><creator>Shebl, Doaa</creator><creator>Mohamed, Waleed M.</creator><creator>Abdel-Aty, Mahmoud</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20210301</creationdate><title>Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm</title><author>Houssein, Essam H. ; Mahdy, Mohamed A. ; Eldin, Manal. G. ; Shebl, Doaa ; Mohamed, Waleed M. ; Abdel-Aty, Mahmoud</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c521t-9aa61668365ee669278466f88bd5cdb6841ecab1c7004040ca26434311bcd0053</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptive guided differential evolution</topic><topic>AGDE</topic><topic>Cloned qubits</topic><topic>Cloning fidelity</topic><topic>Mathematics, Engineering, and Computer Science</topic><topic>Meta-heuristics</topic><topic>Quantum cloning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Houssein, Essam H.</creatorcontrib><creatorcontrib>Mahdy, Mohamed A.</creatorcontrib><creatorcontrib>Eldin, Manal. G.</creatorcontrib><creatorcontrib>Shebl, Doaa</creatorcontrib><creatorcontrib>Mohamed, Waleed M.</creatorcontrib><creatorcontrib>Abdel-Aty, Mahmoud</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of advanced research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Houssein, Essam H.</au><au>Mahdy, Mohamed A.</au><au>Eldin, Manal. G.</au><au>Shebl, Doaa</au><au>Mohamed, Waleed M.</au><au>Abdel-Aty, Mahmoud</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm</atitle><jtitle>Journal of advanced research</jtitle><addtitle>J Adv Res</addtitle><date>2021-03-01</date><risdate>2021</risdate><volume>29</volume><spage>147</spage><epage>157</epage><pages>147-157</pages><issn>2090-1232</issn><eissn>2090-1224</eissn><abstract>[Display omitted]
•AGDE is utilized to optimize quantum cloning circuit parameters.•The experimental results reveal that AGDE is outperformed the other well-known metaheuristics algorithms.•AGDE is minimized the parameter values of cloning difference error value down to 10−8.•The qualitative and quantitative measurements proved the superiority of AGDE.
Quantum cloning operation, started with no-go theorem which proved that there is no capability to perform a cloning operation on an unknown quantum state, however, a number of trials proved that we can make approximate quantum state cloning that is still with some errors.
To the best of our knowledge, this paper is the first of its kind to attempt using meta-heuristic algorithm such as Adaptive Guided Differential Evolution (AGDE), to tackle the problem of quantum cloning circuit parameters to enhance the cloning fidelity.
To investigate the effectiveness of the AGDE, the extensive experiments have demonstrated that the AGDE can achieve outstanding performance compared to other well-known meta-heuristics including; Enhanced LSHADE-SPACMA Algorithm (ELSHADE-SPACMA), Enhanced Differential Evolution algorithm with novel control parameter adaptation (PaDE), Improved Multi-operator Differential Evolution Algorithm (IMODE), Parameters with adaptive learning mechanism (PALM), QUasi-Affine TRansformation Evolutionary algorithm (QUATRE), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Cuckoo Search (CS), Bat-inspired Algorithm (BA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA).
In the present study, AGDE is applied to improve the fidelity of quantum cloning problem and the obtained parameter values minimize the cloning difference error value down to 10-8.
Accordingly, the qualitative and quantitative measurements including average, standard deviation, convergence curves of the competitive algorithms over 30 independent runs, proved the superiority of AGDE to enhance the cloning fidelity.</abstract><cop>Egypt</cop><pub>Elsevier B.V</pub><pmid>33842012</pmid><doi>10.1016/j.jare.2020.10.001</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adaptive guided differential evolution AGDE Cloned qubits Cloning fidelity Mathematics, Engineering, and Computer Science Meta-heuristics Quantum cloning |
title | Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm |
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