Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems
This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sabelfeld, Karl K. [verfasserIn] Popov, Nikita [verfasserIn] |
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E-Artikel |
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| Erschienen: |
De Gruyter ; 2020 |
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15 |
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| Reproduktion: |
Walter de Gruyter Online Zeitschriften |
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| Übergeordnetes Werk: |
Enthalten in: Monte Carlo methods and applications - Berlin [u.a.] : de Gruyter, 1995, 26(2020), 3 vom: 06. Aug., Seite 177-191 |
| Übergeordnetes Werk: |
volume:26 ; year:2020 ; number:3 ; day:06 ; month:08 ; pages:177-191 ; extent:15 |
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| DOI / URN: |
10.1515/mcma-2020-2073 |
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| 520 | |a This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. | ||
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10.1515/mcma-2020-2073 doi articles2015-2020.pp (DE-627)NLEJ248119907 DE-627 ger DE-627 rakwb Sabelfeld, Karl K. verfasserin aut Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems De Gruyter 2020 15 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. Walter de Gruyter Online Zeitschriften Narrow escape problem drift-diffusion trajectory first passage time random walk on spheres 65C05 65C20 65Z05 Popov, Nikita verfasserin aut Enthalten in Monte Carlo methods and applications Berlin [u.a.] : de Gruyter, 1995 26(2020), 3 vom: 06. Aug., Seite 177-191 (DE-627)NLEJ248236458 (DE-600)2043509-5 1569-3961 nnns volume:26 year:2020 number:3 day:06 month:08 pages:177-191 extent:15 https://doi.org/10.1515/mcma-2020-2073 Deutschlandweit zugänglich GBV_USEFLAG_U ZDB-1-DGR GBV_NL_ARTICLE AR 26 2020 3 06 08 177-191 15 |
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10.1515/mcma-2020-2073 doi articles2015-2020.pp (DE-627)NLEJ248119907 DE-627 ger DE-627 rakwb Sabelfeld, Karl K. verfasserin aut Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems De Gruyter 2020 15 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. Walter de Gruyter Online Zeitschriften Narrow escape problem drift-diffusion trajectory first passage time random walk on spheres 65C05 65C20 65Z05 Popov, Nikita verfasserin aut Enthalten in Monte Carlo methods and applications Berlin [u.a.] : de Gruyter, 1995 26(2020), 3 vom: 06. Aug., Seite 177-191 (DE-627)NLEJ248236458 (DE-600)2043509-5 1569-3961 nnns volume:26 year:2020 number:3 day:06 month:08 pages:177-191 extent:15 https://doi.org/10.1515/mcma-2020-2073 Deutschlandweit zugänglich GBV_USEFLAG_U ZDB-1-DGR GBV_NL_ARTICLE AR 26 2020 3 06 08 177-191 15 |
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10.1515/mcma-2020-2073 doi articles2015-2020.pp (DE-627)NLEJ248119907 DE-627 ger DE-627 rakwb Sabelfeld, Karl K. verfasserin aut Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems De Gruyter 2020 15 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. Walter de Gruyter Online Zeitschriften Narrow escape problem drift-diffusion trajectory first passage time random walk on spheres 65C05 65C20 65Z05 Popov, Nikita verfasserin aut Enthalten in Monte Carlo methods and applications Berlin [u.a.] : de Gruyter, 1995 26(2020), 3 vom: 06. Aug., Seite 177-191 (DE-627)NLEJ248236458 (DE-600)2043509-5 1569-3961 nnns volume:26 year:2020 number:3 day:06 month:08 pages:177-191 extent:15 https://doi.org/10.1515/mcma-2020-2073 Deutschlandweit zugänglich GBV_USEFLAG_U ZDB-1-DGR GBV_NL_ARTICLE AR 26 2020 3 06 08 177-191 15 |
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10.1515/mcma-2020-2073 doi articles2015-2020.pp (DE-627)NLEJ248119907 DE-627 ger DE-627 rakwb Sabelfeld, Karl K. verfasserin aut Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems De Gruyter 2020 15 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. Walter de Gruyter Online Zeitschriften Narrow escape problem drift-diffusion trajectory first passage time random walk on spheres 65C05 65C20 65Z05 Popov, Nikita verfasserin aut Enthalten in Monte Carlo methods and applications Berlin [u.a.] : de Gruyter, 1995 26(2020), 3 vom: 06. Aug., Seite 177-191 (DE-627)NLEJ248236458 (DE-600)2043509-5 1569-3961 nnns volume:26 year:2020 number:3 day:06 month:08 pages:177-191 extent:15 https://doi.org/10.1515/mcma-2020-2073 Deutschlandweit zugänglich GBV_USEFLAG_U ZDB-1-DGR GBV_NL_ARTICLE AR 26 2020 3 06 08 177-191 15 |
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10.1515/mcma-2020-2073 doi articles2015-2020.pp (DE-627)NLEJ248119907 DE-627 ger DE-627 rakwb Sabelfeld, Karl K. verfasserin aut Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems De Gruyter 2020 15 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. Walter de Gruyter Online Zeitschriften Narrow escape problem drift-diffusion trajectory first passage time random walk on spheres 65C05 65C20 65Z05 Popov, Nikita verfasserin aut Enthalten in Monte Carlo methods and applications Berlin [u.a.] : de Gruyter, 1995 26(2020), 3 vom: 06. Aug., Seite 177-191 (DE-627)NLEJ248236458 (DE-600)2043509-5 1569-3961 nnns volume:26 year:2020 number:3 day:06 month:08 pages:177-191 extent:15 https://doi.org/10.1515/mcma-2020-2073 Deutschlandweit zugänglich GBV_USEFLAG_U ZDB-1-DGR GBV_NL_ARTICLE AR 26 2020 3 06 08 177-191 15 |
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This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. |
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This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. |
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This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">NLEJ248119907</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220820035855.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220814s2020 xx |||||o 00| ||und c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1515/mcma-2020-2073</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">articles2015-2020.pp</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ248119907</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Sabelfeld, Karl K.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="b">De Gruyter</subfield><subfield code="c">2020</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">15</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particleto reach a small part of a boundary far away from the starting position of the particle.A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a differentapproach whichdrastically improves the efficiency of the diffusion trajectory tracking algorithm byintroducing an artificial drift velocitydirected to the target position.The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry.The algorithm is meshless both in space and time,and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled.</subfield></datafield><datafield tag="533" ind1=" " ind2=" "><subfield code="f">Walter de Gruyter Online Zeitschriften</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Narrow escape problem</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">drift-diffusion trajectory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">first passage time</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">random walk on spheres</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">65C05</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">65C20</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">65Z05</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Popov, Nikita</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Monte Carlo methods and applications</subfield><subfield code="d">Berlin [u.a.] : de Gruyter, 1995</subfield><subfield code="g">26(2020), 3 vom: 06. 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