{"id":"https://openalex.org/W3111467040","doi":"https://doi.org/10.1088/2632-2153/abd486","title":"A hybrid quantum regression model for the prediction of molecular atomization energies","display_name":"A hybrid quantum regression model for the prediction of molecular atomization energies","publication_year":2020,"publication_date":"2020-12-17","ids":{"openalex":"https://openalex.org/W3111467040","doi":"https://doi.org/10.1088/2632-2153/abd486","mag":"3111467040"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/abd486","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/abd486","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/abd486/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://iopscience.iop.org/article/10.1088/2632-2153/abd486/pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110708133","display_name":"Pranath Reddy","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101034","display_name":"Birla Institute of Technology and Science - Hyderabad Campus","ror":"https://ror.org/014ctt859","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210101034","https://openalex.org/I74796645"]},{"id":"https://openalex.org/I74796645","display_name":"Birla Institute of Technology and Science, Pilani","ror":"https://ror.org/001p3jz28","country_code":"IN","type":"education","lineage":["https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pranath Reddy","raw_affiliation_strings":["Department of Physics, Birla Institute of Technology & Science, Pilani\u2014Hyderabad Campus, Telangana, India"],"raw_orcid":"https://orcid.org/0000-0002-6609-3495","affiliations":[{"raw_affiliation_string":"Department of Physics, Birla Institute of Technology & Science, Pilani\u2014Hyderabad Campus, Telangana, India","institution_ids":["https://openalex.org/I4210101034","https://openalex.org/I74796645"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053466012","display_name":"Aranya B. Bhattacherjee","orcid":"https://orcid.org/0000-0002-7713-8927"},"institutions":[{"id":"https://openalex.org/I4210101034","display_name":"Birla Institute of Technology and Science - Hyderabad Campus","ror":"https://ror.org/014ctt859","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210101034","https://openalex.org/I74796645"]},{"id":"https://openalex.org/I74796645","display_name":"Birla Institute of Technology and Science, Pilani","ror":"https://ror.org/001p3jz28","country_code":"IN","type":"education","lineage":["https://openalex.org/I74796645"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Aranya B Bhattacherjee","raw_affiliation_strings":["Department of Physics, Birla Institute of Technology & Science, Pilani\u2014Hyderabad Campus, Telangana, India"],"raw_orcid":"https://orcid.org/0000-0002-7713-8927","affiliations":[{"raw_affiliation_string":"Department of Physics, Birla Institute of Technology & Science, Pilani\u2014Hyderabad Campus, Telangana, India","institution_ids":["https://openalex.org/I4210101034","https://openalex.org/I74796645"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053466012"],"corresponding_institution_ids":["https://openalex.org/I4210101034","https://openalex.org/I74796645"],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":0.6516,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.6425964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"2","issue":"2","first_page":"025019","last_page":"025019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11177","display_name":"Spectroscopy and Quantum Chemical Studies","score":0.9646000266075134,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quantum-machine-learning","display_name":"Quantum machine learning","score":0.6283160448074341},{"id":"https://openalex.org/keywords/quantum-algorithm","display_name":"Quantum algorithm","score":0.6256304383277893},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5969612002372742},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.504104733467102},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5011355876922607},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49869418144226074},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.47762221097946167},{"id":"https://openalex.org/keywords/quantum-phase-estimation-algorithm","display_name":"Quantum phase estimation algorithm","score":0.46116986870765686},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45769792795181274},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.4422128200531006},{"id":"https://openalex.org/keywords/quantum-computer","display_name":"Quantum computer","score":0.4327964782714844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.427171528339386},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.42246416211128235},{"id":"https://openalex.org/keywords/quantum-error-correction","display_name":"Quantum error correction","score":0.24447888135910034},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.24186497926712036},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2415175437927246},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.10452744364738464}],"concepts":[{"id":"https://openalex.org/C2779094486","wikidata":"https://www.wikidata.org/wiki/Q18811578","display_name":"Quantum machine learning","level":4,"score":0.6283160448074341},{"id":"https://openalex.org/C137019171","wikidata":"https://www.wikidata.org/wiki/Q2623817","display_name":"Quantum algorithm","level":3,"score":0.6256304383277893},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5969612002372742},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.504104733467102},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5011355876922607},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49869418144226074},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.47762221097946167},{"id":"https://openalex.org/C192122513","wikidata":"https://www.wikidata.org/wiki/Q2835770","display_name":"Quantum phase estimation algorithm","level":5,"score":0.46116986870765686},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45769792795181274},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.4422128200531006},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.4327964782714844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.427171528339386},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.42246416211128235},{"id":"https://openalex.org/C51003876","wikidata":"https://www.wikidata.org/wiki/Q1536431","display_name":"Quantum error correction","level":4,"score":0.24447888135910034},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.24186497926712036},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2415175437927246},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.10452744364738464}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1088/2632-2153/abd486","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/abd486","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/abd486/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/abd486","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/abd486","pdf_url":"https://iopscience.iop.org/article/10.1088/2632-2153/abd486/pdf","source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3111467040.pdf"},"referenced_works_count":77,"referenced_works":["https://openalex.org/W199424061","https://openalex.org/W430219513","https://openalex.org/W638560767","https://openalex.org/W654652841","https://openalex.org/W1499864241","https://openalex.org/W1522301498","https://openalex.org/W1631356911","https://openalex.org/W1998260904","https://openalex.org/W2015811642","https://openalex.org/W2051446825","https://openalex.org/W2064675550","https://openalex.org/W2069563009","https://openalex.org/W2091085232","https://openalex.org/W2101403221","https://openalex.org/W2104489082","https://openalex.org/W2107436902","https://openalex.org/W2131774270","https://openalex.org/W2153693853","https://openalex.org/W2154196599","https://openalex.org/W2177870565","https://openalex.org/W2243462087","https://openalex.org/W2295598076","https://openalex.org/W2489886790","https://openalex.org/W2523246573","https://openalex.org/W2557283755","https://openalex.org/W2559394418","https://openalex.org/W2560386163","https://openalex.org/W2592484110","https://openalex.org/W2594183968","https://openalex.org/W2594860211","https://openalex.org/W2666784499","https://openalex.org/W2772412867","https://openalex.org/W2792946961","https://openalex.org/W2795534239","https://openalex.org/W2798309714","https://openalex.org/W2896712926","https://openalex.org/W2898913178","https://openalex.org/W2916370975","https://openalex.org/W2919115771","https://openalex.org/W2936573766","https://openalex.org/W2937307539","https://openalex.org/W2941783269","https://openalex.org/W2947849003","https://openalex.org/W2949858440","https://openalex.org/W2970821532","https://openalex.org/W2972345006","https://openalex.org/W2985302520","https://openalex.org/W2997421965","https://openalex.org/W3004965358","https://openalex.org/W3006388831","https://openalex.org/W3010895642","https://openalex.org/W3084121144","https://openalex.org/W3098400458","https://openalex.org/W3098832331","https://openalex.org/W3099734242","https://openalex.org/W3101135395","https://openalex.org/W3102476541","https://openalex.org/W3104599990","https://openalex.org/W3207342693","https://openalex.org/W4297958736","https://openalex.org/W6608201162","https://openalex.org/W6629930100","https://openalex.org/W6631190155","https://openalex.org/W6663326937","https://openalex.org/W6676177546","https://openalex.org/W6727249380","https://openalex.org/W6734026524","https://openalex.org/W6734557874","https://openalex.org/W6734561206","https://openalex.org/W6749684677","https://openalex.org/W6749702402","https://openalex.org/W6755322515","https://openalex.org/W6761712014","https://openalex.org/W6763449645","https://openalex.org/W6764708164","https://openalex.org/W6767400126","https://openalex.org/W6775199687"],"related_works":["https://openalex.org/W4289534122","https://openalex.org/W2906136444","https://openalex.org/W2995485305","https://openalex.org/W2204682854","https://openalex.org/W2765183970","https://openalex.org/W3012076960","https://openalex.org/W3113887578","https://openalex.org/W4286585841","https://openalex.org/W2102181336","https://openalex.org/W2994642008"],"abstract_inverted_index":{"Abstract":[0],"Quantum":[1],"machine":[2,26,47,93,220],"learning":[3,27,48,94,221,224],"is":[4,42],"a":[5,90,120,166,182,210,236],"relatively":[6],"new":[7],"research":[8],"field":[9],"that":[10],"aims":[11],"to":[12,29,61,200,241],"combine":[13],"the":[14,23,43,51,58,67,98,105,112,126,133,139,148,188,243,246],"dramatic":[15],"performance":[16],"advantage":[17],"offered":[18],"by":[19],"quantum":[20,52,62,77,81,92,167,172,175,183,193,211],"computing":[21],"and":[22,55,80,108,135,147,160,222,235,249],"ability":[24],"of":[25,33,39,45,57,69,101,111,129,138,152,253],"algorithms":[28,49],"learn":[30],"complex":[31],"distributions":[32],"high-dimensional":[34],"data.":[35],"The":[36,191],"primary":[37],"focus":[38],"this":[40,86],"domain":[41,54],"implementation":[44],"classical":[46,206,219],"in":[50],"mechanical":[53],"study":[56,242],"speedup":[59,203],"due":[60],"parallelism,":[63],"which":[64],"could":[65],"enable":[66],"development":[68],"novel":[70],"techniques":[71],"for":[72,96,125,186],"solving":[73],"problems":[74],"such":[75,170,226],"as":[76,171,227],"phase":[78],"recognition":[79],"error":[82],"correction":[83],"optimization.":[84],"In":[85],"paper,":[87],"we":[88,116,161,213],"propose":[89],"hybrid":[91,192],"pipeline":[95],"predicting":[97],"atomization":[99,189,251],"energies":[100,252],"various":[102],"molecules":[103],"using":[104,119,165,217],"nuclear":[106,158],"charges":[107],"atomic":[109,145],"positions":[110,146],"constituent":[113],"atoms.":[114],"Firstly,":[115],"will":[117,162,214],"be":[118,164,216],"deep":[121,223,231],"convolutional":[122,232],"auto-encoder":[123],"model":[124],"feature":[127],"extraction":[128],"data":[130],"constructed":[131],"from":[132,144,157],"eigenvalues":[134],"eigenvector":[136],"centralities":[137],"pairwise":[140],"distance":[141],"matrix":[142,155],"calculated":[143,156],"unrolled":[149],"upper":[150],"triangle":[151],"each":[153],"Coulomb":[154],"charges,":[159],"then":[163],"regression":[168],"algorithm":[169],"linear":[173],"regression,":[174],"radial":[176],"basis":[177],"function":[178],"neural":[179,184,194,233],"network":[180,185,195,240],"and,":[181],"estimating":[187],"energy.":[190],"models":[196,225],"do":[197],"not":[198],"seem":[199],"provide":[201],"any":[202],"over":[204],"their":[205],"counterparts.":[207],"Before":[208],"implementing":[209],"algorithm,":[212],"also":[215],"state-of-the-art":[218],"XGBoost,":[228],"multilayer":[229],"perceptron,":[230],"network,":[234],"long":[237],"short-term":[238],"memory":[239],"correlation":[244],"between":[245],"extracted":[247],"features":[248],"corresponding":[250],"molecules.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}