{"id":"https://openalex.org/W4415813254","doi":"https://doi.org/10.3390/sym17111841","title":"DdONN-PINNs: Complex Optical Wavefield Reconstruction by Domain Decomposition of Optical Neural Networks and Physics-Informed Information","display_name":"DdONN-PINNs: Complex Optical Wavefield Reconstruction by Domain Decomposition of Optical Neural Networks and Physics-Informed Information","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4415813254","doi":"https://doi.org/10.3390/sym17111841"},"language":"en","primary_location":{"id":"doi:10.3390/sym17111841","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17111841","pdf_url":"https://www.mdpi.com/2073-8994/17/11/1841/pdf?version=1762134597","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/17/11/1841/pdf?version=1762134597","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016029538","display_name":"Miao Xiao-yu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141176","display_name":"Communication University of Zhejiang","ror":"https://ror.org/04t7gxr16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210141176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Miao","raw_affiliation_strings":["College of Media Engineering, Communication University of Zhejiang, Hangzhou 310018, China","Key Lab of Film and TV Media Technology of Zhejiang Province, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"College of Media Engineering, Communication University of Zhejiang, Hangzhou 310018, China","institution_ids":["https://openalex.org/I4210141176"]},{"raw_affiliation_string":"Key Lab of Film and TV Media Technology of Zhejiang Province, Hangzhou 310018, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021550676","display_name":"Xun Zhuang","orcid":"https://orcid.org/0000-0002-3974-8193"},"institutions":[{"id":"https://openalex.org/I4210141176","display_name":"Communication University of Zhejiang","ror":"https://ror.org/04t7gxr16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210141176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyue Zhuang","raw_affiliation_strings":["College of Media Engineering, Communication University of Zhejiang, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"College of Media Engineering, Communication University of Zhejiang, Hangzhou 310018, China","institution_ids":["https://openalex.org/I4210141176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048679582","display_name":"Lipu Zhang","orcid":"https://orcid.org/0000-0002-2186-3716"},"institutions":[{"id":"https://openalex.org/I4210141176","display_name":"Communication University of Zhejiang","ror":"https://ror.org/04t7gxr16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210141176"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lipu Zhang","raw_affiliation_strings":["College of Media Engineering, Communication University of Zhejiang, Hangzhou 310018, China","Key Lab of Film and TV Media Technology of Zhejiang Province, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"College of Media Engineering, Communication University of Zhejiang, Hangzhou 310018, China","institution_ids":["https://openalex.org/I4210141176"]},{"raw_affiliation_string":"Key Lab of Film and TV Media Technology of Zhejiang Province, Hangzhou 310018, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048679582"],"corresponding_institution_ids":["https://openalex.org/I4210141176"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17696379,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"11","first_page":"1841","last_page":"1841"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9023000001907349,"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"}},"topics":[{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9023000001907349,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.023499999195337296,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10232","display_name":"Optical Network Technologies","score":0.014800000004470348,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5504000186920166},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4936999976634979},{"id":"https://openalex.org/keywords/coupling","display_name":"Coupling (piping)","score":0.49149999022483826},{"id":"https://openalex.org/keywords/amplitude","display_name":"Amplitude","score":0.4715000092983246},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4523000121116638},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.4212999939918518},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3716999888420105},{"id":"https://openalex.org/keywords/artificial-noise","display_name":"Artificial noise","score":0.3646000027656555},{"id":"https://openalex.org/keywords/attenuation","display_name":"Attenuation","score":0.3555999994277954}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6251000165939331},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5533000230789185},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5504000186920166},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4936999976634979},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.49149999022483826},{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.4212999939918518},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3716999888420105},{"id":"https://openalex.org/C2780909371","wikidata":"https://www.wikidata.org/wiki/Q4801092","display_name":"Artificial noise","level":4,"score":0.3646000027656555},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.3555999994277954},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C169744125","wikidata":"https://www.wikidata.org/wiki/Q510375","display_name":"Seismogram","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C207114421","wikidata":"https://www.wikidata.org/wiki/Q133900","display_name":"Diffraction","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C44886760","wikidata":"https://www.wikidata.org/wiki/Q1758425","display_name":"Wave propagation","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C154236941","wikidata":"https://www.wikidata.org/wiki/Q942347","display_name":"Physical optics","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C198880260","wikidata":"https://www.wikidata.org/wiki/Q5289813","display_name":"Domain decomposition methods","level":3,"score":0.27709999680519104},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/sym17111841","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17111841","pdf_url":"https://www.mdpi.com/2073-8994/17/11/1841/pdf?version=1762134597","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/sym17111841","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym17111841","pdf_url":"https://www.mdpi.com/2073-8994/17/11/1841/pdf?version=1762134597","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415813254.pdf","grobid_xml":"https://content.openalex.org/works/W4415813254.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2798701005","https://openalex.org/W2899283552","https://openalex.org/W3087326580","https://openalex.org/W3098546160","https://openalex.org/W3107308400","https://openalex.org/W3209909540","https://openalex.org/W4367852984","https://openalex.org/W4388043357","https://openalex.org/W4391970400","https://openalex.org/W4399840403","https://openalex.org/W4400810358","https://openalex.org/W4401389039","https://openalex.org/W4402694963","https://openalex.org/W4406034683","https://openalex.org/W4407449287","https://openalex.org/W4409540413","https://openalex.org/W4414036579"],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,28,35,41,64,73,97,122],"challenges":[3],"of":[4,12,38,46,57,68,76,102,139,145,165],"poor":[5],"adaptability":[6],"to":[7,71,84,94,106],"spatial":[8,74,107],"heterogeneity,":[9],"easy":[10],"breakage":[11],"amplitude\u2013phase":[13],"coupling":[14,113],"relationships,":[15],"and":[16,50,89,99,141,150,181,189],"insufficient":[17],"physical":[18,86,179],"consistency":[19],"in":[20,114,186],"complex":[21,103],"optical":[22,47],"wavefield":[23,77,174],"reconstruction,":[24],"this":[25],"paper":[26],"proposes":[27],"DdONN-PINNs":[29,131],"hybrid":[30],"framework.":[31],"Focused":[32],"on":[33,54,117],"preserving":[34,111],"intrinsic":[36],"symmetries":[37],"wave":[39],"physics,":[40],"framework":[42,168],"achieves":[43],"deep":[44],"integration":[45],"neural":[48],"networks":[49],"physics-informed":[51],"information.":[52],"Centered":[53],"an":[55,133],"architecture":[56],"\u201cSIREN":[58],"shared":[59],"encoding\u2013domain-specific":[60],"output\u201d,":[61],"it":[62],"utilizes":[63],"periodic":[65],"activation":[66],"property":[67],"SIREN":[69],"encoders":[70],"maintain":[72],"symmetry":[75],"distribution,":[78],"incorporates":[79],"learnable":[80],"Fourier":[81],"diffraction":[82],"layers":[83],"model":[85],"propagation":[87],"processes,":[88],"adopts":[90],"native":[91],"complex-domain":[92],"modeling":[93],"avoid":[95],"splitting":[96],"real":[98],"imaginary":[100],"parts":[101],"amplitudes\u2014effectively":[104],"adapting":[105],"heterogeneity":[108],"while":[109],"fully":[110],"amplitude-phase":[112],"wavefields.":[115],"Validated":[116],"rogue":[118],"wavefields":[119],"governed":[120],"by":[121],"Nonlinear":[123],"Schr\u00f6dinger":[124],"Equation":[125],"(NLSE),":[126],"experimental":[127],"results":[128],"demonstrate":[129],"that":[130,176],"achieve":[132],"amplitude":[134],"Mean":[135],"Squared":[136],"Error":[137],"(MSE)":[138],"2.94\u00d710\u22123":[140],"a":[142,162,170],"phase":[143],"MSE":[144],"5.86\u00d710\u22124,":[146],"outperforming":[147],"non-domain-decomposed":[148],"models":[149],"ReLU-activated":[151],"variants":[152],"significantly.":[153],"Robustness":[154],"analysis":[155],"shows":[156],"stable":[157],"reconstruction":[158,175],"performance":[159],"even":[160],"at":[161],"noise":[163],"level":[164],"\u03c3=0.1.":[166],"This":[167],"provides":[169],"balanced":[171],"solution":[172],"for":[173],"integrates":[177],"precision,":[178],"interpretability,":[180],"robustness,":[182],"with":[183],"potential":[184],"applications":[185],"fiber-optic":[187],"communication":[188],"ocean":[190],"optics.":[191]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-11-03T00:00:00"}