{"id":"https://openalex.org/W7128507006","doi":"https://doi.org/10.48550/arxiv.2602.08012","title":"A Unified Density Operator View of Flow Control and Merging","display_name":"A Unified Density Operator View of Flow Control and Merging","publication_year":2026,"publication_date":"2026-02-08","ids":{"openalex":"https://openalex.org/W7128507006","doi":"https://doi.org/10.48550/arxiv.2602.08012"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.08012","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08012","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.08012","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052185248","display_name":"Riccardo De Santi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"De Santi, Riccardo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125505153","display_name":"Malte Franke","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Franke, Malte","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125584995","display_name":"Ya-Ping Hsieh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsieh, Ya-Ping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125547371","display_name":"Andreas Krause","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krause, Andreas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.4781999886035919,"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":0.4781999886035919,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.12680000066757202,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.09070000052452087,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.6378999948501587},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.6287000179290771},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.5555999875068665},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5473999977111816},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.5202999711036682},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.490200012922287},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.40549999475479126},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3472000062465668}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.6378999948501587},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.6287000179290771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5983999967575073},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5555999875068665},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5473999977111816},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.5202999711036682},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.490200012922287},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.46230000257492065},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4596000015735626},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.40549999475479126},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3314000070095062},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3303000032901764},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3303000032901764},{"id":"https://openalex.org/C160191386","wikidata":"https://www.wikidata.org/wiki/Q868299","display_name":"Control flow","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26930001378059387},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.08012","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08012","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.08012","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08012","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"progress":[1],"in":[2],"large-scale":[3],"flow":[4,27,50,123,142],"and":[5,20,47,140,162,171],"diffusion":[6],"models":[7,80],"raised":[8],"two":[9],"fundamental":[10],"algorithmic":[11],"challenges:":[12],"(i)":[13],"control-based":[14],"reward":[15],"adaptation":[16],"of":[17,23,56,76,128,151],"pre-trained":[18,58],"flows,":[19],"(ii)":[21],"integration":[22],"multiple":[24,57],"models,":[25],"i.e.,":[26],"merging.":[28],"While":[29],"current":[30],"approaches":[31],"address":[32],"them":[33],"separately,":[34],"we":[35,111,133,147],"introduce":[36,112],"a":[37,73,117,126],"unifying":[38],"probability-space":[39],"framework":[40],"that":[41,120],"subsumes":[42],"both":[43],"as":[44,101,103],"limit":[45],"cases,":[46],"enables":[48],"reward-guided":[49,99,122,139],"merging,":[51],"allowing":[52],"principled,":[53],"task-aware":[54],"combination":[55],"flows":[59],"(e.g.,":[60,84,89,95],"merging":[61,124,143],"priors":[62],"while":[63],"maximizing":[64],"drug-discovery":[65],"utilities).":[66],"Our":[67],"formulation":[68],"renders":[69],"possible":[70],"to":[71,85,90,125,166],"express":[72],"rich":[74],"family":[75],"operators":[77],"over":[78],"generative":[79,108],"densities,":[81],"including":[82],"intersection":[83],"enforce":[86],"safety),":[87],"union":[88],"compose":[91],"diverse":[92],"models),":[93],"interpolation":[94],"for":[96,138],"discovery),":[97],"their":[98],"counterparts,":[100],"well":[102],"complex":[104],"logical":[105],"expressions":[106],"via":[107,144],"circuits.":[109],"Next,":[110],"Reward-Guided":[113],"Flow":[114],"Merging":[115],"(RFM),":[116],"mirror-descent":[118],"scheme":[119],"reduces":[121],"sequence":[127],"standard":[129],"fine-tuning":[130],"problems.":[131],"Then,":[132],"provide":[134],"first-of-their-kind":[135],"theoretical":[136],"guarantees":[137],"pure":[141],"RFM.":[145],"Ultimately,":[146],"showcase":[148],"the":[149,152],"capabilities":[150],"proposed":[153],"method":[154,165],"on":[155],"illustrative":[156],"settings":[157],"providing":[158],"visually":[159],"interpretable":[160],"insights,":[161],"apply":[163],"our":[164],"high-dimensional":[167],"de-novo":[168],"molecular":[169],"design":[170],"low-energy":[172],"conformer":[173],"generation.":[174]},"counts_by_year":[],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2026-02-11T00:00:00"}