{"id":"https://openalex.org/W7148255972","doi":"https://doi.org/10.48550/arxiv.2604.01211","title":"Making Every Bit Count for $A$-Optimal State Estimation","display_name":"Making Every Bit Count for $A$-Optimal State Estimation","publication_year":2026,"publication_date":"2026-04-01","ids":{"openalex":"https://openalex.org/W7148255972","doi":"https://doi.org/10.48550/arxiv.2604.01211"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01211","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01211","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":"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.2604.01211","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132805700","display_name":"Cameron Khanpour","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khanpour, Cameron","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057165231","display_name":"Daniel Turizo","orcid":"https://orcid.org/0000-0001-7324-0185"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Turizo, Daniel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5023442914","display_name":"Samuel Talkington","orcid":"https://orcid.org/0000-0001-5768-8115"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Talkington, Samuel","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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.46380001306533813,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.46380001306533813,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.25029999017715454,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10046","display_name":"Stability and Control of Uncertain Systems","score":0.024000000208616257,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/rounding","display_name":"Rounding","score":0.5916000008583069},{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.5598000288009644},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4521999955177307},{"id":"https://openalex.org/keywords/cholesky-decomposition","display_name":"Cholesky decomposition","score":0.40459999442100525},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.39649999141693115},{"id":"https://openalex.org/keywords/lagrange-multiplier","display_name":"Lagrange multiplier","score":0.37310001254081726},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.35659998655319214},{"id":"https://openalex.org/keywords/constrained-optimization","display_name":"Constrained optimization","score":0.3495999872684479},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.3343000113964081},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.31619998812675476}],"concepts":[{"id":"https://openalex.org/C136625980","wikidata":"https://www.wikidata.org/wiki/Q663208","display_name":"Rounding","level":2,"score":0.5916000008583069},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5831000208854675},{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.5598000288009644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49300000071525574},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4684999883174896},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4521999955177307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40779998898506165},{"id":"https://openalex.org/C34727166","wikidata":"https://www.wikidata.org/wiki/Q515375","display_name":"Cholesky decomposition","level":3,"score":0.40459999442100525},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C73684929","wikidata":"https://www.wikidata.org/wiki/Q598870","display_name":"Lagrange multiplier","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C55660270","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization","level":2,"score":0.3495999872684479},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C61005703","wikidata":"https://www.wikidata.org/wiki/Q2145211","display_name":"Round-off error","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C155253501","wikidata":"https://www.wikidata.org/wiki/Q461992","display_name":"Interior point method","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.289000004529953},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C97137487","wikidata":"https://www.wikidata.org/wiki/Q729138","display_name":"Integer (computer science)","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C101901036","wikidata":"https://www.wikidata.org/wiki/Q2269096","display_name":"Semidefinite programming","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01211","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01211","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":"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.2604.01211","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01211","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":"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":{"We":[0,58],"study":[1],"the":[2,23,26,31,67,99,116,119,141,145,153,165],"problem":[3],"of":[4,25,30,66,118],"controlling":[5],"how":[6],"a":[7,49,54,60,70,80,85,113],"limited":[8],"communication":[9],"bandwidth":[10],"budget":[11,51],"is":[12,22,144,157],"allocated":[13],"across":[14],"heterogeneously":[15],"quantized":[16],"sensor":[17],"measurements.":[18],"The":[19],"performance":[20],"criterion":[21,47],"trace":[24],"error":[27,36],"covariance":[28],"matrix":[29],"linear":[32],"minimum":[33],"mean":[34],"square":[35],"(LMMSE)":[37],"state":[38],"estimator,":[39],"i.e.,":[40],"an":[41,90],"$A$-optimal":[42],"design":[43],"criterion.":[44],"Minimizing":[45],"this":[46],"with":[48,94,112,130],"bit":[50,110,155,162],"constraint":[52],"yields":[53],"nonconvex":[55],"optimization":[56,77],"problem.":[57],"derive":[59],"formula":[61],"that":[62,140],"reduces":[63],"each":[64],"evaluation":[65],"gradient":[68,143],"to":[69,132,159],"single":[71],"Cholesky":[72],"factorization.":[73],"This":[74],"enables":[75],"efficient":[76],"by":[78],"both":[79,136,150],"projection-free":[81],"Frank-Wolfe":[82],"method":[83,93],"(with":[84],"computable":[86],"convergence":[87],"certificate)":[88],"and":[89,138],"interior":[91],"point":[92],"L-BFGS":[95],"Hessian":[96],"approximation":[97],"over":[98],"problem's":[100],"continuous":[101],"relaxation.":[102],"A":[103],"largest":[104],"remainder":[105],"rounding":[106],"procedure":[107],"recovers":[108],"integer":[109],"allocations":[111],"bound":[114],"on":[115,164],"quality":[117],"rounded":[120],"solution.":[121],"Numerical":[122],"experiments":[123],"in":[124],"IEEE":[125,168],"power":[126,169],"grid":[127,170],"test":[128,171],"cases":[129],"up":[131],"300":[133],"buses":[134],"compare":[135],"solvers":[137],"demonstrate":[139],"analytic":[142],"key":[146],"computational":[147],"enabler":[148],"for":[149],"methods.":[151],"Additionally,":[152],"heterogeneous":[154],"allocation":[156,163],"compared":[158],"standard":[160],"uniform":[161],"500":[166],"bus":[167],"case.":[172]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-03T00:00:00"}