{"id":"https://openalex.org/W7155170669","doi":"https://doi.org/10.48550/arxiv.2604.18801","title":"Preserving Clusters in Error-Bounded Lossy Compression of Particle Data","display_name":"Preserving Clusters in Error-Bounded Lossy Compression of Particle Data","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155170669","doi":"https://doi.org/10.48550/arxiv.2604.18801"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.18801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18801","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.2604.18801","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112997189","display_name":"Congrong Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Congrong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134319673","display_name":"Sheng Di","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di, Sheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043238619","display_name":"Katrin Heitmann","orcid":"https://orcid.org/0000-0003-1468-8232"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heitmann, Katrin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134336631","display_name":"Franck Cappello","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cappello, Franck","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134225334","display_name":"Hanqi Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Hanqi","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/T11181","display_name":"Advanced Data Storage Technologies","score":0.6103000044822693,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.6103000044822693,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.05869999900460243,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.05719999969005585,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/lossy-compression","display_name":"Lossy compression","score":0.8240000009536743},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7926999926567078},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.6757000088691711},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.44609999656677246},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.44530001282691956},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.43709999322891235},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.4016999900341034},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.396699994802475},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.38499999046325684}],"concepts":[{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.8240000009536743},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7926999926567078},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.6757000088691711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5921000242233276},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5385000109672546},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46389999985694885},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.44609999656677246},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.44530001282691956},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.43709999322891235},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.4016999900341034},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.38499999046325684},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.37599998712539673},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.3621000051498413},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.3601999878883362},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C2778517922","wikidata":"https://www.wikidata.org/wiki/Q7140482","display_name":"Particle (ecology)","level":2,"score":0.3449999988079071},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.322299987077713},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.31850001215934753},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.30809998512268066},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.3019999861717224},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2858000099658966},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26980000734329224},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.25279998779296875},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.18801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18801","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.2604.18801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.18801","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Lossy":[0],"compression":[1,165],"is":[2],"widely":[3],"used":[4],"to":[5,75],"reduce":[6],"storage":[7],"and":[8,23,50,58,66,92,112,136,141,150,173],"I/O":[9],"costs":[10],"for":[11,35,144],"large-scale":[12,145],"particle":[13,48,107],"datasets":[14,153],"in":[15],"scientific":[16,68],"applications":[17],"such":[18,89],"as":[19,90],"cosmology,":[20],"molecular":[21,151],"dynamics,":[22,25],"fluid":[24],"where":[26],"clustering":[27,56,78,122,160],"structures":[28],"(e.g.,":[29],"single-linkage":[30,77],"or":[31],"Friends-of-Friends)":[32],"are":[33,97],"critical":[34],"downstream":[36],"analysis;":[37],"however,":[38],"existing":[39],"compressors":[40,88],"typically":[41],"provide":[42],"only":[43],"pointwise":[44],"error":[45],"bounds":[46],"on":[47,54,83,148],"positions":[49],"offer":[51],"no":[52],"guarantees":[53],"preserving":[55],"outcomes,":[57],"even":[59],"small":[60],"perturbations":[61],"can":[62],"alter":[63],"cluster":[64],"connectivity":[65],"compromise":[67],"validity.":[69],"We":[70],"propose":[71],"a":[72,100,129,138],"correction-based":[73],"technique":[74],"preserve":[76],"under":[79],"lossy":[80],"compression,":[81],"operating":[82],"decompressed":[84],"data":[85],"from":[86],"off-the-shelf":[87],"SZ3":[91],"Draco.":[93],"Our":[94],"key":[95],"contributions":[96],"threefold:":[98],"(1)":[99],"clustering-aware":[101],"correction":[102],"algorithm":[103],"that":[104,120,131,155],"identifies":[105],"vulnerable":[106],"pairs":[108],"via":[109],"spatial":[110],"partitioning":[111],"local":[113],"neighborhood":[114],"search;":[115],"(2)":[116],"an":[117],"optimization-based":[118],"formulation":[119],"enforces":[121],"consistency":[123],"using":[124],"projected":[125],"gradient":[126],"descent":[127],"with":[128,168],"loss":[130],"encodes":[132],"pairwise":[133],"distance":[134],"violations;":[135],"(3)":[137],"scalable":[139],"GPU-accelerated":[140],"distributed":[142],"implementation":[143],"datasets.":[146],"Experiments":[147],"cosmology":[149],"dynamics":[152],"show":[154],"our":[156],"method":[157],"effectively":[158],"preserves":[159],"results":[161],"while":[162],"maintaining":[163],"competitive":[164],"performance":[166],"compared":[167],"SZ3,":[169],"ZFP,":[170],"Draco,":[171],"LCP,":[172],"space-filling-curve-based":[174],"schemes.":[175]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-23T00:00:00"}