{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T17:09:27Z","timestamp":1765040967507,"version":"3.40.5"},"reference-count":12,"publisher":"Walter de Gruyter GmbH","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>One method of computing the electrostatic energy of a\nbiomolecule in a solution uses a continuum representation of the\nsolution via the Poisson\u2013Boltzmann equation.\nThis can be solved in many ways, and we consider a Monte Carlo method of our design that combines the Walk-on-Spheres and Walk-on-Subdomains algorithms.\nIn the course of\nexamining the Monte Carlo implementation of this method, an issue was\ndiscovered in the Walk-on-Subdomains portion of the algorithm which caused the algorithm to sometimes take an abnormally long time to complete. As the\nproblem occurs when a walker repeatedly oscillates between two\nsubdomains, it is something that could cause a large increase in runtime for any method that used a similar algorithm. This issue is described in detail and a\npotential solution is examined.<\/jats:p>","DOI":"10.1515\/mcma-2019-2052","type":"journal-article","created":{"date-parts":[[2019,11,19]],"date-time":"2019-11-19T09:04:06Z","timestamp":1574154246000},"page":"329-340","source":"Crossref","is-referenced-by-count":10,"title":["Geometry entrapment in Walk-on-Subdomains"],"prefix":"10.1515","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5030-2467","authenticated-orcid":false,"given":"Preston","family":"Hamlin","sequence":"first","affiliation":[{"name":"Department of Computer Science , Florida State University , Tallahassee , FL 32306-4530; and National Institute of Standards & Technology, ITL, Gaithersburg, MD 20899-8970 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5487-5545","authenticated-orcid":false,"given":"W. John","family":"Thrasher","sequence":"additional","affiliation":[{"name":"Department of Computer Science , Florida State University , Tallahassee , FL 32306-453 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3807-813X","authenticated-orcid":false,"given":"Walid","family":"Keyrouz","sequence":"additional","affiliation":[{"name":"National Institute of Standards & Technology , ITL , Gaithersburg , MD 20899-8970 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3058-4580","authenticated-orcid":false,"given":"Michael","family":"Mascagni","sequence":"additional","affiliation":[{"name":"Department of Computer Science , Florida State University , Tallahassee , FL 32306-4530; and National Institute of Standards & Technology, ITL, Gaithersburg, MD 20899-8910 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2019,11,19]]},"reference":[{"key":"2023040101440760740_j_mcma-2019-2052_ref_001_w2aab3b7b5b1b6b1ab1b5b1Aa","doi-asserted-by":"crossref","unstructured":"H. M.  Berman, J.  Westbrook, Z.  Feng, G.  Gilliland, T. N.  Bhat, H.  Weissig, I. N.  Shindyalov and P. E.  Bourne,\nThe protein data bank,\nNucleic Acids Res. 28 (2000), 235\u2013242.\n10.1093\/nar\/28.1.235","DOI":"10.1093\/nar\/28.1.235"},{"key":"2023040101440760740_j_mcma-2019-2052_ref_002_w2aab3b7b5b1b6b1ab1b5b2Aa","doi-asserted-by":"crossref","unstructured":"R. N.  Cardinal and M. R. F.  Aitken,\nANOVA for the Behavioral Sciences Researcher,\nPsychology Press, London, 2013.","DOI":"10.4324\/9780203763933"},{"key":"2023040101440760740_j_mcma-2019-2052_ref_003_w2aab3b7b5b1b6b1ab1b5b3Aa","doi-asserted-by":"crossref","unstructured":"M. O.  Fenley, M.  Mascagni, J.  McClain, A. R. J.  Silalahi and N. A.  Simonov,\nUsing correlated Monte Carlo sampling for efficiently solving the linearized Poisson\u2013Boltzmann equation over a broad range of salt concentration,\nJ. Chem. Theory Comput. 6 (2009), 300\u2013314.","DOI":"10.1021\/ct9003806"},{"key":"2023040101440760740_j_mcma-2019-2052_ref_004_w2aab3b7b5b1b6b1ab1b5b4Aa","doi-asserted-by":"crossref","unstructured":"J. A.  Given, J. B.  Hubbard and J. F.  Douglas,\nA first-passage algorithm for the hydrodynamic friction and diffusion-limited reaction rate of macromolecules,\nJ. Chem. Phys. 106 (1997), 3761\u20133771.\n10.1063\/1.473428","DOI":"10.1063\/1.473428"},{"key":"2023040101440760740_j_mcma-2019-2052_ref_005_w2aab3b7b5b1b6b1ab1b5b5Aa","unstructured":"C.-O.  Hwang, M.  Mascagni and N. A.  Simonov,\nMonte Carlo methods for the linearized Poisson\u2013Boltzmann equation,\nAdvances in Numerical Analysis,\nNova Science, Hauppauge (2004)."},{"key":"2023040101440760740_j_mcma-2019-2052_ref_006_w2aab3b7b5b1b6b1ab1b5b6Aa","doi-asserted-by":"crossref","unstructured":"T.  Mackoy, R. C.  Harris, J.  Johnson, M.  Mascagni and M. O.  Fenley,\nNumerical optimization of a walk-on-spheres solver for the linear Poisson\u2013Boltzmann equation,\nCommun. Comput. Phys. 13 (2013), 195\u2013206.\n10.4208\/cicp.220711.041011s","DOI":"10.4208\/cicp.220711.041011s"},{"key":"2023040101440760740_j_mcma-2019-2052_ref_007_w2aab3b7b5b1b6b1ab1b5b7Aa","doi-asserted-by":"crossref","unstructured":"M.  Mascagni and N. A.  Simonov,\nMonte Carlo method for calculating the electrostatic energy of a molecule,\nComputational Science\u2014ICCS 2003. Part I,\nLecture Notes in Comput. Sci. 2657,\nSpringer, Berlin (2003), 63\u201372.","DOI":"10.1007\/3-540-44860-8_7"},{"key":"2023040101440760740_j_mcma-2019-2052_ref_008_w2aab3b7b5b1b6b1ab1b5b8Aa","doi-asserted-by":"crossref","unstructured":"M.  Mascagni and N. A.  Simonov,\nMonte Carlo methods for calculating some physical properties of large molecules,\nSIAM J. Sci. 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Sabelfeld,\nMonte Carlo Methods in Boundary Value Problems,\nSpringer, Berlin, 1991.","DOI":"10.1007\/978-3-642-75977-2"},{"key":"2023040101440760740_j_mcma-2019-2052_ref_012_w2aab3b7b5b1b6b1ab1b5c12Aa","doi-asserted-by":"crossref","unstructured":"K. K.  Sabelfeld and N. A.  Simonov,\nStochastic Methods for Boundary Value Problems. Numerics for High-dimensional PDEs and Applications,\nDe Gruyter, Berlin, 2016.","DOI":"10.1515\/9783110479454"}],"container-title":["Monte Carlo Methods and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/mcma.2019.25.issue-4\/mcma-2019-2052\/mcma-2019-2052.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2019-2052\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2019-2052\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T21:39:04Z","timestamp":1680385144000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2019-2052\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,19]]},"references-count":12,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2019,11,8]]},"published-print":{"date-parts":[[2019,12,1]]}},"alternative-id":["10.1515\/mcma-2019-2052"],"URL":"https:\/\/doi.org\/10.1515\/mcma-2019-2052","relation":{},"ISSN":["1569-3961","0929-9629"],"issn-type":[{"type":"electronic","value":"1569-3961"},{"type":"print","value":"0929-9629"}],"subject":[],"published":{"date-parts":[[2019,11,19]]}}}