{"id":"https://openalex.org/W7117172744","doi":"https://doi.org/10.1109/tit.2025.3648262","title":"Characterizing Dependence of Samples Along the Langevin Dynamics and Algorithms via Contraction of \u03a6-Mutual Information","display_name":"Characterizing Dependence of Samples Along the Langevin Dynamics and Algorithms via Contraction of \u03a6-Mutual Information","publication_year":2025,"publication_date":"2025-12-24","ids":{"openalex":"https://openalex.org/W7117172744","doi":"https://doi.org/10.1109/tit.2025.3648262"},"language":null,"primary_location":{"id":"doi:10.1109/tit.2025.3648262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2025.3648262","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Theory","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102007299","display_name":"Jiaming Liang","orcid":"https://orcid.org/0000-0001-7439-3845"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]},{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiaming Liang","raw_affiliation_strings":["Goergen Institute for Data Science and Artificial Intelligence and the Department of Computer Science, University of Rochester, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"Goergen Institute for Data Science and Artificial Intelligence and the Department of Computer Science, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228","https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061115074","display_name":"Siddharth Mitra","orcid":"https://orcid.org/0000-0003-3527-6288"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siddharth Mitra","raw_affiliation_strings":["Department of Computer Science, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043389973","display_name":"Andre Wibisono","orcid":null},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andre Wibisono","raw_affiliation_strings":["Department of Computer Science, Yale University, New Haven, CT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102007299"],"corresponding_institution_ids":["https://openalex.org/I155173764","https://openalex.org/I5388228"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78605987,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"72","issue":"2","first_page":"921","last_page":"945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12261","display_name":"Statistical Mechanics and Entropy","score":0.00139999995008111,"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/T10974","display_name":"Advanced Queuing Theory Analysis","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.8669000267982483},{"id":"https://openalex.org/keywords/langevin-dynamics","display_name":"Langevin dynamics","score":0.6287999749183655},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.590399980545044},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5759000182151794},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.5412999987602234},{"id":"https://openalex.org/keywords/stationary-distribution","display_name":"Stationary distribution","score":0.4970000088214874},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.4948999881744385},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.49070000648498535},{"id":"https://openalex.org/keywords/markov-renewal-process","display_name":"Markov renewal process","score":0.44920000433921814}],"concepts":[{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.8669000267982483},{"id":"https://openalex.org/C2780004032","wikidata":"https://www.wikidata.org/wiki/Q6485978","display_name":"Langevin dynamics","level":2,"score":0.6287999749183655},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5982000231742859},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.590399980545044},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5759000182151794},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C98951983","wikidata":"https://www.wikidata.org/wiki/Q7604341","display_name":"Stationary distribution","level":3,"score":0.4970000088214874},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.4948999881744385},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.49070000648498535},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.48010000586509705},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44920000433921814},{"id":"https://openalex.org/C163540672","wikidata":"https://www.wikidata.org/wiki/Q1115431","display_name":"Markov renewal process","level":5,"score":0.44920000433921814},{"id":"https://openalex.org/C106666656","wikidata":"https://www.wikidata.org/wiki/Q6771323","display_name":"Markov kernel","level":5,"score":0.44839999079704285},{"id":"https://openalex.org/C189973286","wikidata":"https://www.wikidata.org/wiki/Q176695","display_name":"Markov property","level":4,"score":0.445499986410141},{"id":"https://openalex.org/C97074811","wikidata":"https://www.wikidata.org/wiki/Q6771322","display_name":"Markov chain mixing time","level":5,"score":0.4205999970436096},{"id":"https://openalex.org/C163415756","wikidata":"https://www.wikidata.org/wiki/Q126473","display_name":"Contraction (grammar)","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C76408418","wikidata":"https://www.wikidata.org/wiki/Q5419314","display_name":"Examples of Markov chains","level":5,"score":0.3149000108242035},{"id":"https://openalex.org/C147080032","wikidata":"https://www.wikidata.org/wiki/Q176720","display_name":"Continuous-time Markov chain","level":5,"score":0.31470000743865967},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.2985000014305115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.29089999198913574},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C158917313","wikidata":"https://www.wikidata.org/wiki/Q4849964","display_name":"Balance equation","level":4,"score":0.2833000123500824},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.27469998598098755},{"id":"https://openalex.org/C98735484","wikidata":"https://www.wikidata.org/wiki/Q186971","display_name":"Time reversibility","level":5,"score":0.26829999685287476},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.2653000056743622}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2025.3648262","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2025.3648262","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4331797957420349,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W74953171","https://openalex.org/W423603040","https://openalex.org/W1479763159","https://openalex.org/W1481224392","https://openalex.org/W1509845160","https://openalex.org/W1520471750","https://openalex.org/W1585160083","https://openalex.org/W1954227087","https://openalex.org/W1980451075","https://openalex.org/W1983452151","https://openalex.org/W1996977322","https://openalex.org/W2029164135","https://openalex.org/W2035306297","https://openalex.org/W2042864197","https://openalex.org/W2043371182","https://openalex.org/W2060960121","https://openalex.org/W2071048859","https://openalex.org/W2097636360","https://openalex.org/W2099111195","https://openalex.org/W2100967164","https://openalex.org/W2111616148","https://openalex.org/W2130416410","https://openalex.org/W2135177479","https://openalex.org/W2140291117","https://openalex.org/W2155549573","https://openalex.org/W2161269121","https://openalex.org/W2166524562","https://openalex.org/W2171750587","https://openalex.org/W2222154095","https://openalex.org/W2290247654","https://openalex.org/W2518143623","https://openalex.org/W2593511049","https://openalex.org/W2804635973","https://openalex.org/W2885549115","https://openalex.org/W2888706989","https://openalex.org/W2962883731","https://openalex.org/W2963423396","https://openalex.org/W2963657839","https://openalex.org/W2963763760","https://openalex.org/W3019950912","https://openalex.org/W3157879672","https://openalex.org/W3190285696","https://openalex.org/W3198855841","https://openalex.org/W4205463258","https://openalex.org/W4233762729","https://openalex.org/W4244481070","https://openalex.org/W4247690662","https://openalex.org/W4249256225","https://openalex.org/W4317815220","https://openalex.org/W4393002334","https://openalex.org/W4401057266","https://openalex.org/W4401180887","https://openalex.org/W4403183092","https://openalex.org/W4408181569","https://openalex.org/W4411320045","https://openalex.org/W4412112838","https://openalex.org/W4415368150","https://openalex.org/W4415368758","https://openalex.org/W4415795901"],"related_works":[],"abstract_inverted_index":{"The":[0],"mixing":[1,163],"time":[2],"of":[3,12,41,88,164,186,200,226],"a":[4,85],"Markov":[5,14,32,51,112,158,166,202,212],"chain":[6,15],"determines":[7],"how":[8,42],"fast":[9,43,130,162],"the":[10,13,18,26,31,39,44,56,63,68,76,89,103,114,118,121,136,149,157,165,173,177,184,193,197,201,208,211,215,223,227],"iterates":[11,209],"converge":[16],"to":[17,97,127,171,182,191],"stationary":[19,178],"distribution;":[20],"however,":[21],"it":[22],"does":[23],"not":[24],"control":[25],"dependencies":[27],"between":[28,78,117],"samples":[29,45,79,104],"along":[30,49,110,156,196,210],"chain.":[33],"In":[34,180],"this":[35,206],"paper,":[36],"we":[37,168,189,204],"study":[38],"question":[40],"become":[46],"approximately":[47],"independent":[48],"popular":[50],"chains":[52,213],"for":[53,176],"continuous-space":[54],"sampling:":[55],"Langevin":[57,65],"dynamics":[58],"in":[59,71,131],"continuous":[60],"time,":[61],"and":[62,67,93,100,120],"Unadjusted":[64],"Algorithm":[66],"Proximal":[69],"Sampler":[70],"discrete":[72],"time.":[73],"We":[74,107],"measure":[75],"dependence":[77],"via":[80],"\u03a6-mutual":[81,115,187],"information,":[82,92,188],"which":[83,94,219],"is":[84,95,139,145,220],"broad":[86],"generalization":[87],"standard":[90],"mutual":[91],"equal":[96],"0":[98,128],"if":[99,102],"only":[101,169],"are":[105],"independent.":[106],"show":[108,172,192],"that":[109],"these":[111],"chains,":[113,167],"information":[116],"first":[119],"<italic":[122,132],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[123,133],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</i>-th":[124],"iterate":[125],"decreases":[126],"exponentially":[129],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</i>":[134],"when":[135,207],"target":[137,228],"distribution":[138],"strongly":[140],"log-concave.":[141],"Our":[142],"proof":[143],"technique":[144],"based":[146],"on":[147],"showing":[148],"Strong":[150],"Data":[151],"Processing":[152],"Inequalities":[153],"(SDPIs)":[154],"hold":[155,175,195],"chains.":[159],"To":[160],"prove":[161,183,205],"need":[170,190],"SDPIs":[174,194],"distribution.":[179,229],"contrast,":[181],"contraction":[185],"entire":[198],"trajectories":[199],"chains;":[203],"satisfy":[214],"corresponding":[216],"\u03a6-Sobolev":[217],"inequality,":[218],"implied":[221],"by":[222],"strong":[224],"log-concavity":[225]},"counts_by_year":[],"updated_date":"2026-02-23T20:09:44.859080","created_date":"2025-12-24T00:00:00"}