{"id":"https://openalex.org/W7155055284","doi":"https://doi.org/10.48550/arxiv.2604.18357","title":"Momentum Stability and Adaptive Control in Stochastic Reconfiguration","display_name":"Momentum Stability and Adaptive Control in Stochastic Reconfiguration","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155055284","doi":"https://doi.org/10.48550/arxiv.2604.18357"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.18357","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18357","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"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.2604.18357","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134177493","display_name":"Yuyang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5060086206","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0003-2186-0635"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xin","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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.3400999903678894,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.3400999903678894,"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":0.10599999874830246,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.09960000216960907,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6686999797821045},{"id":"https://openalex.org/keywords/momentum","display_name":"Momentum (technical analysis)","score":0.4625000059604645},{"id":"https://openalex.org/keywords/control-reconfiguration","display_name":"Control reconfiguration","score":0.44749999046325684},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4368000030517578},{"id":"https://openalex.org/keywords/counterexample","display_name":"Counterexample","score":0.42649999260902405},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4262000024318695},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4156999886035919},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.3950999975204468},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.38769999146461487},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.3628000020980835}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6686999797821045},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.48429998755455017},{"id":"https://openalex.org/C60718061","wikidata":"https://www.wikidata.org/wiki/Q1414747","display_name":"Momentum (technical analysis)","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C119701452","wikidata":"https://www.wikidata.org/wiki/Q5165881","display_name":"Control reconfiguration","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4415000081062317},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4368000030517578},{"id":"https://openalex.org/C162838799","wikidata":"https://www.wikidata.org/wiki/Q596077","display_name":"Counterexample","level":2,"score":0.42649999260902405},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4262000024318695},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4156999886035919},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4059000015258789},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39719998836517334},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.3950999975204468},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.38769999146461487},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.3598000109195709},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.3596000075340271},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.33709999918937683},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2890999913215637},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C147060835","wikidata":"https://www.wikidata.org/wiki/Q1757151","display_name":"Krylov subspace","level":3,"score":0.272599995136261},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C113603373","wikidata":"https://www.wikidata.org/wiki/Q2362761","display_name":"Wave function","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.2635999917984009},{"id":"https://openalex.org/C16171025","wikidata":"https://www.wikidata.org/wiki/Q863349","display_name":"Singularity","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C207821765","wikidata":"https://www.wikidata.org/wiki/Q405372","display_name":"Instability","level":2,"score":0.2581999897956848}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.18357","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18357","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.18357","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18357","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Variational":[0],"Monte":[1],"Carlo":[2],"(VMC)":[3],"combined":[4],"with":[5],"expressive":[6],"neural":[7],"network":[8],"wavefunctions":[9],"has":[10],"become":[11],"a":[12,35,67,146],"powerful":[13],"route":[14],"to":[15,63,163],"high-accuracy":[16],"ground-state":[17],"calculations,":[18],"yet":[19],"its":[20,42],"practical":[21],"success":[22],"hinges":[23],"on":[24,152],"efficient":[25],"and":[26,76,97,108,134,156],"stable":[27],"wavefunction":[28],"optimization.":[29,173],"While":[30],"stochastic":[31],"reconfiguration":[32],"(SR)":[33],"provides":[34],"geometry-aware":[36],"preconditioner":[37],"motivated":[38],"by":[39,130],"imaginary-time":[40],"evolution,":[41],"Kaczmarz-inspired":[43],"variant,":[44],"subsampled":[45],"projected-increment":[46],"natural":[47],"gradient":[48],"descent":[49],"(SPRING),":[50],"achieves":[51,160],"state-of-the-art":[52],"empirical":[53],"performance.":[54],"However,":[55],"the":[56,64,77,90,94,124],"effectiveness":[57],"of":[58,66,74],"SPRING":[59,166],"is":[60,126],"highly":[61],"sensitive":[62],"choice":[65],"momentum-like":[68],"parameter":[69],"$\u03bc$.":[70],"The":[71],"original":[72],"sensitivity":[73],"$\u03bc$":[75],"instability":[78],"observed":[79],"at":[80],"$\u03bc=1$,":[81],"have":[82],"remained":[83],"unclear.":[84],"In":[85],"this":[86],"work,":[87],"we":[88,137],"clarify":[89],"distinct":[91],"mechanisms":[92],"governing":[93],"regimes":[95],"$\u03bc&lt;1$":[96],"$\u03bc=1$.":[98],"We":[99],"establish":[100],"convergence":[101],"guarantees":[102],"for":[103],"$0\\le\u03bc&lt;1$":[104],"under":[105],"mild":[106],"assumptions,":[107],"construct":[109],"counterexamples":[110],"showing":[111],"that":[112],"$\u03bc=1$":[113],"can":[114],"induce":[115],"divergence":[116],"via":[117],"uncontrolled":[118],"growth":[119],"along":[120],"kernel-related":[121],"directions":[122],"when":[123],"step-size":[125],"not":[127],"summable.":[128],"Motivated":[129],"these":[131],"theoretical":[132],"insights":[133],"numerical":[135],"observations,":[136],"further":[138],"propose":[139],"\\textit{Principal":[140],"Range":[141],"Informed":[142],"MomEntum":[143],"SR}":[144],"(PRIME-SR),":[145],"tuning-free":[147],"momentum-adaptive":[148],"SR":[149],"method":[150],"based":[151],"effective":[153],"spectral":[154],"dimension":[155],"subspace":[157],"overlap.":[158],"PRIME-SR":[159],"performance":[161],"comparable":[162],"optimally":[164],"tuned":[165],"while":[167],"significantly":[168],"improving":[169],"robustness":[170],"in":[171],"VMC":[172]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-22T00:00:00"}
