{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/42127"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/42127","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Binning for efficient stochastic particle simulations","abstract":"Restriction data tranferred 2014-07-01T11:11:50-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2015-02-03 13:18:53 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","abstract_html":"Restriction data tranferred 2014-07-01T11:11:50-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2015-02-03 13:18:53 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","abstract_has_math":false,"creators":["Michelotti, Matthew"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Heath, Michael T.","West, Matthew"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-02-03T19:16:34Z","date_published":"2013-02-03T19:16:34Z","updated_at":"2026-07-22T22:25:31Z","subjects":["stochastic","Markov process","coalescence","atmospheric aerosol","stochastic simulation algorithm","tau leaping","particle resolved"],"languages":["en"],"rights":["Copyright 2012 Matthew D. Michelotti"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/42127","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Heath, Michael T.","West, Matthew"]},{"key":"dc:creator","label":"Author","values":["Michelotti, Matthew"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2013-02-03T19:16:34Z","2015-02-03T11:00:27Z","2012-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["stochastic","Markov process","coalescence","atmospheric aerosol","stochastic simulation algorithm","tau leaping","particle resolved"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2012 Matthew D. Michelotti"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/42127"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Restriction data tranferred 2014-07-01T11:11:50-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2015-02-03 13:18:53 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","U of I Only Restriction Lifted for Item 42074 on 2015-02-03T11:00:27Z.","Gillespie's Stochastic Simulation Algorithm (SSA) is an exact procedure for simulating the evolution of a collection of discrete, interacting entities, such as coalescing aerosol particles or reacting chemical species. The high computational cost of SSA has motivated the development of more efficient variants, such as Tau-Leaping, which sacrifices the exactness of SSA. For models whose interacting entities can be characterized by a continuous parameter, such as a measure of size for aerosol particles, we analyze strategies for accelerating these algorithms by aggregating particles of similar size into bins. We show that for such models an appropriate binning strategy can dramatically enhance efficiency, and in particular can make SSA computationally competitive without sacrificing exactness. We formulate binned versions of both the SSA and Tau-Leaping algorithms and analyze and demonstrate their performance.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-11-26T16:09:07Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Michelotti_Matthew.pdf: 546732 bytes, checksum: 20faf33d2551d1448d21dcfaa6e94d1c (MD5)","Made available in DSpace on 2013-02-03T19:16:34Z (GMT). No. of bitstreams: 2 Matthew_Michelotti.pdf: 546732 bytes, checksum: 20faf33d2551d1448d21dcfaa6e94d1c (MD5) license.txt: 4068 bytes, checksum: 18445f7021c0768ea3cd41b6664be7bd (MD5)","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Seth Robbins (srobbins@illinois.edu) on 2013-02-03T19:18:56Z Item is restricted until 2015-02-03T19:18:53Z"]},{"key":"dc:title","label":"Title","values":["Binning for efficient stochastic particle simulations"]}]}],"canonical_facts":{"dc:contributor":["Heath, Michael T.","West, Matthew"],"dc:creator":["Michelotti, Matthew"],"dc:date":["2013-02-03T19:16:34Z","2015-02-03T11:00:27Z","2012-12"],"dc:description":["Restriction data tranferred 2014-07-01T11:11:50-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2015-02-03 13:18:53 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system","U of I Only Restriction Lifted for Item 42074 on 2015-02-03T11:00:27Z.","Gillespie's Stochastic Simulation Algorithm (SSA) is an exact procedure for simulating the evolution of a collection of discrete, interacting entities, such as coalescing aerosol particles or reacting chemical species. The high computational cost of SSA has motivated the development of more efficient variants, such as Tau-Leaping, which sacrifices the exactness of SSA. For models whose interacting entities can be characterized by a continuous parameter, such as a measure of size for aerosol particles, we analyze strategies for accelerating these algorithms by aggregating particles of similar size into bins. We show that for such models an appropriate binning strategy can dramatically enhance efficiency, and in particular can make SSA computationally competitive without sacrificing exactness. We formulate binned versions of both the SSA and Tau-Leaping algorithms and analyze and demonstrate their performance.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-11-26T16:09:07Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Michelotti_Matthew.pdf: 546732 bytes, checksum: 20faf33d2551d1448d21dcfaa6e94d1c (MD5)","Made available in DSpace on 2013-02-03T19:16:34Z (GMT). No. of bitstreams: 2 Matthew_Michelotti.pdf: 546732 bytes, checksum: 20faf33d2551d1448d21dcfaa6e94d1c (MD5) license.txt: 4068 bytes, checksum: 18445f7021c0768ea3cd41b6664be7bd (MD5)","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Seth Robbins (srobbins@illinois.edu) on 2013-02-03T19:18:56Z Item is restricted until 2015-02-03T19:18:53Z"],"dc:identifier":["http://hdl.handle.net/2142/42127"],"dc:language":["en"],"dc:rights":["Copyright 2012 Matthew D. Michelotti"],"dc:subject":["stochastic","Markov process","coalescence","atmospheric aerosol","stochastic simulation algorithm","tau leaping","particle resolved"],"dc:title":["Binning for efficient stochastic particle simulations"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:31Z"}