{"created":"2023-06-20T16:46:53.526997+00:00","id":18486,"links":{},"metadata":{"_buckets":{"deposit":"ca4a7269-d206-4f59-a43e-0945ecd95286"},"_deposit":{"created_by":29,"id":"18486","owners":[29],"pid":{"revision_id":0,"type":"depid","value":"18486"},"status":"published"},"_oai":{"id":"oai:kindai.repo.nii.ac.jp:00018486","sets":["14:923:2091:4344"]},"author_link":["31161","31163","31162"],"item_2_biblio_info_21":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2017-02-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"29","bibliographicPageEnd":"9","bibliographicPageStart":"1","bibliographic_titles":[{"bibliographic_title":"理工学総合研究所研究報告"},{"bibliographic_title":"Annual reports by Research Institute for Science and Technology","bibliographic_titleLang":"en"}]}]},"item_2_description_33":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"巡回セールスマン問題とは，N 都市と各都市の間の距離が与えられたとき，セールスマンがN都市すべてを1 回づつ訪問し，かつその全距離を最小にする経路を探す問題である．古典的にはすべての可能性を列挙して，その中で最小距離の経路を求めればよいが，それにはN! 程度のステップが必要となる．これはNP 困難とよばれるクラスに属する問題で，N が大きくなると実用的ではない．最近，量子コンピュータを用いて，この問題を解く方法が提案され，注目されている．これは断熱的量子コンピューティングと言われる手法であり，実用的な量子コンピュータが存在すれば，N に関して多項式時間で問題が解けると期待される．実際には古典コンピュータを用いて，シミュレーティッド・アニーリングや量子アニーリングとよばれる手法で問題を解くのであるが，本論文では，教育面に重点を置いて，4 都市の問題を表現するシュレーディンガー方程式を直接解き，解法の原理的デモンストレーションを行う．","subitem_description_type":"Abstract"}]},"item_2_description_41":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_2_publisher_14":{"attribute_name":"出版者 名前","attribute_value_mlt":[{"subitem_publisher":"近畿大学理工学総合研究所"}]},"item_2_source_id_22":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"09162054","subitem_source_identifier_type":"ISSN"}]},"item_2_text_8":{"attribute_name":"著者 所属","attribute_value_mlt":[{"subitem_text_value":"近畿大学"},{"subitem_text_value":"近畿大学工業高等専門学校"},{"subitem_text_value":"早稲田大学高等研究所: 国立研究開発法人科学技術振興機構さきがけ"}]},"item_2_text_9":{"attribute_name":"著者所属(翻訳)","attribute_value_mlt":[{"subitem_text_value":"Kindai University"},{"subitem_text_value":"Kindai University"}]},"item_2_version_type_12":{"attribute_name":"版","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_be7fb7dd8ff6fe43","subitem_version_type":"NA"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"中原, 幹夫"}],"nameIdentifiers":[{"nameIdentifier":"31161","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"坂東, 将光"}],"nameIdentifiers":[{"nameIdentifier":"31162","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"田中, 宗"}],"nameIdentifiers":[{"nameIdentifier":"31163","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-06-20"}],"displaytype":"detail","filename":"AN10074306-20170228-0001.pdf","filesize":[{"value":"1.1 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"AN10074306-20170228-0001.pdf","url":"https://kindai.repo.nii.ac.jp/record/18486/files/AN10074306-20170228-0001.pdf"},"version_id":"7dc75a42-f4bc-41fb-bd29-d4d23d35d962"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"断熱量子コンピューティングによる巡回セールスマン問題の解法","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"断熱量子コンピューティングによる巡回セールスマン問題の解法"}]},"item_type_id":"2","owner":"29","path":["4344"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-06-20"},"publish_date":"2017-06-20","publish_status":"0","recid":"18486","relation_version_is_last":true,"title":["断熱量子コンピューティングによる巡回セールスマン問題の解法"],"weko_creator_id":"29","weko_shared_id":-1},"updated":"2023-06-20T21:58:01.059536+00:00"}