{"id":"https://openalex.org/W2511758788","doi":"https://doi.org/10.1109/jsac.2016.2603619","title":"MCMC Methods for Drawing Random Samples From the Discrete-Grains Model of a Magnetic Medium","display_name":"MCMC Methods for Drawing Random Samples From the Discrete-Grains Model of a Magnetic Medium","publication_year":2016,"publication_date":"2016-08-26","ids":{"openalex":"https://openalex.org/W2511758788","doi":"https://doi.org/10.1109/jsac.2016.2603619","mag":"2511758788"},"language":"en","primary_location":{"id":"doi:10.1109/jsac.2016.2603619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsac.2016.2603619","pdf_url":null,"source":{"id":"https://openalex.org/S90422530","display_name":"IEEE Journal on Selected Areas in Communications","issn_l":"0733-8716","issn":["0733-8716","1558-0008"],"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 Journal on Selected Areas in Communications","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/A5042130437","display_name":"Nikhil Das","orcid":"https://orcid.org/0000-0002-5049-5422"},"institutions":[{"id":"https://openalex.org/I114602248","display_name":"Bharat Electronics (India)","ror":"https://ror.org/00edfym28","country_code":"IN","type":"company","lineage":["https://openalex.org/I114602248"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"N. V. Abhinav Das","raw_affiliation_strings":["Bharat Electronics Ltd., Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"Bharat Electronics Ltd., Bengaluru, India","institution_ids":["https://openalex.org/I114602248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059452861","display_name":"Navin Kashyap","orcid":null},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Navin Kashyap","raw_affiliation_strings":["Department of Electrical Communication Engineering, Indian Institute of Science, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Communication Engineering, Indian Institute of Science, Bengaluru, India","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042130437"],"corresponding_institution_ids":["https://openalex.org/I114602248"],"apc_list":null,"apc_paid":null,"fwci":0.7097,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.75708541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"34","issue":"9","first_page":"2430","last_page":"2438"},"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":0.9987999796867371,"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":0.9987999796867371,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9909999966621399,"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/T10591","display_name":"Theoretical and Computational Physics","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/3104","display_name":"Condensed Matter Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.8289660811424255},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6857803463935852},{"id":"https://openalex.org/keywords/metropolis\u2013hastings-algorithm","display_name":"Metropolis\u2013Hastings algorithm","score":0.5653957724571228},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.5431960225105286},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.5205158591270447},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5127871632575989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49772194027900696},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4615018963813782},{"id":"https://openalex.org/keywords/square","display_name":"Square (algebra)","score":0.4229829013347626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38566386699676514},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.38113725185394287},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.37251657247543335},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.35946470499038696},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24440336227416992},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10583722591400146},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.10313498973846436}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.8289660811424255},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6857803463935852},{"id":"https://openalex.org/C204693719","wikidata":"https://www.wikidata.org/wiki/Q910810","display_name":"Metropolis\u2013Hastings algorithm","level":4,"score":0.5653957724571228},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.5431960225105286},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.5205158591270447},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5127871632575989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49772194027900696},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4615018963813782},{"id":"https://openalex.org/C135692309","wikidata":"https://www.wikidata.org/wiki/Q111124","display_name":"Square (algebra)","level":2,"score":0.4229829013347626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38566386699676514},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.38113725185394287},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.37251657247543335},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.35946470499038696},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24440336227416992},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10583722591400146},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.10313498973846436},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jsac.2016.2603619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsac.2016.2603619","pdf_url":null,"source":{"id":"https://openalex.org/S90422530","display_name":"IEEE Journal on Selected Areas in Communications","issn_l":"0733-8716","issn":["0733-8716","1558-0008"],"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 Journal on Selected Areas in Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W621546036","https://openalex.org/W1600293573","https://openalex.org/W1653035750","https://openalex.org/W1819325491","https://openalex.org/W1840847274","https://openalex.org/W1975911596","https://openalex.org/W1985908422","https://openalex.org/W2033281046","https://openalex.org/W2041562692","https://openalex.org/W2056760934","https://openalex.org/W2058953255","https://openalex.org/W2104248547","https://openalex.org/W2111340923","https://openalex.org/W2114644198","https://openalex.org/W2120857236","https://openalex.org/W2129726722","https://openalex.org/W2138309709","https://openalex.org/W2152042087","https://openalex.org/W2152646636","https://openalex.org/W2158477630","https://openalex.org/W2471517265","https://openalex.org/W3103229293","https://openalex.org/W6638689888"],"related_works":["https://openalex.org/W2956835927","https://openalex.org/W2392396032","https://openalex.org/W2071668645","https://openalex.org/W4250051631","https://openalex.org/W160986626","https://openalex.org/W2073412813","https://openalex.org/W4362705882","https://openalex.org/W4390532044","https://openalex.org/W217235565","https://openalex.org/W3037960898"],"abstract_inverted_index":{"The":[0,46],"discrete-grains":[1],"model":[2,6],"is":[3,49],"a":[4,13,96,132,177,213],"simple":[5],"for":[7,75,129],"the":[8,21,88,101,105,121,142,190,194,202,208,218],"distribution":[9,134],"of":[10,28,79,87,112,120,159,168,174,180,193,201,204],"\u201cgrains\u201d":[11],"on":[12,20,104,156,189],"magnetic":[14,47],"medium.":[15],"In":[16,64],"this":[17,65,148],"model,":[18],"grains":[19],"medium":[22,48],"are":[23],"taken":[24,206],"to":[25,124,141,150,211],"be":[26,93],"one":[27],"four":[29,61,89],"basic":[30,62,90],"rectangular":[31],"shapes":[32],"(\u201ctiles\u201d)-1":[33],"\u00d7":[34,37,40,44,55,82],"1,":[35,41],"1":[36],"2,":[38],"2":[39,43],"and":[42,187],"2.":[45],"then":[50],"modeled":[51],"as":[52],"an":[53,80,126],"N":[54,56,81,83],"square":[57,84],"tiled":[58],"by":[59,207],"these":[60],"tiles.":[63,91],"paper,":[66],"we":[67,117],"present":[68,184],"Markov":[69,196],"chain":[70],"Monte":[71],"Carlo":[72],"(MCMC)":[73],"methods":[74,210],"generating":[76],"random":[77,214],"tilings":[78],"consisting":[85,167],"only":[86],"To":[92],"precise,":[94],"given":[95],"target":[97,143,219],"probability":[98,133,154,220],"distribution,":[99,103],"e.g.,":[100],"uniform":[102],"space,":[106],"S":[107,160],"<sub":[108,161],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[109,162],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">N</sub>":[110,163],",":[111,164],"all":[113],"possible":[114],"such":[115],"tilings,":[116,169],"make":[118],"use":[119],"Metropolis-Hastings":[122],"algorithm":[123],"design":[125],"MCMC":[127,209],"method":[128],"sampling":[130,152],"from":[131,153,217],"arbitrarily":[135],"close,":[136],"in":[137,170],"total":[138],"variation":[139],"distance,":[140],"distribution.":[144,221],"We":[145,182],"further":[146],"extend":[147],"approach":[149],"enable":[151],"distributions":[155],"certain":[157],"subsets":[158],"namely,":[165],"those":[166],"which":[171,198],"each":[172],"kind":[173],"tile":[175],"occurs":[176],"fixed":[178],"number":[179],"times.":[181],"finally":[183],"some":[185],"bounds":[186],"conjectures":[188],"mixing":[191],"times":[192],"underlying":[195],"chains,":[197],"provide":[199],"estimates":[200],"amount":[203],"time":[205],"generate":[212],"tiling":[215],"sampled":[216]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}