Extremal geometry of a Brownian porous medium
The path W [ 0 , t ] of a Brownian motion on a d -dimensional torus T d run for time t is a random compact subset of T d . We study the geometric properties of the complement T d \ W [ 0 , t ] as t → ∞ for d ≥ 3 . In particular, we show that the largest regions in T d \ W [ 0 , t ] have a linear sca...
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creator | Goodman, Jesse den Hollander, Frank |
description | The path
W
[
0
,
t
]
of a Brownian motion on a
d
-dimensional torus
T
d
run for time
t
is a random compact subset of
T
d
. We study the geometric properties of the complement
T
d
\
W
[
0
,
t
]
as
t
→
∞
for
d
≥
3
. In particular, we show that the largest regions in
T
d
\
W
[
0
,
t
]
have a linear scale
φ
d
(
t
)
=
[
(
d
log
t
)
/
(
d
-
2
)
κ
d
t
]
1
/
(
d
-
2
)
, where
κ
d
is the capacity of the unit ball. More specifically, we identify the sets
E
for which
T
d
\
W
[
0
,
t
]
contains a translate of
φ
d
(
t
)
E
, and we count the number of disjoint such translates. Furthermore, we derive large deviation principles for the largest inradius of
T
d
\
W
[
0
,
t
]
as
t
→
∞
and the
ε
-cover time of
T
d
as
ε
↓
0
. Our results, which generalise laws of large numbers proved by Dembo et al. (Electron J Probab 8(15):1–14,
2003
), are based on a large deviation estimate for the shape of the component with largest capacity in
T
d
\
W
ρ
(
t
)
[
0
,
t
]
, where
W
ρ
(
t
)
[
0
,
t
]
is the Wiener sausage of radius
ρ
(
t
)
, with
ρ
(
t
)
chosen much smaller than
φ
d
(
t
)
but not too small. The idea behind this choice is that
T
d
\
W
[
0
,
t
]
consists of “lakes”, whose linear size is of order
φ
d
(
t
)
, connected by narrow “channels”. We also derive large deviation principles for the principal Dirichlet eigenvalue and for the maximal volume of the components of
T
d
\
W
ρ
(
t
)
[
0
,
t
]
as
t
→
∞
. Our results give a complete picture of the extremal geometry of
T
d
\
W
[
0
,
t
]
and of the optimal strategy for
W
[
0
,
t
]
to realise extreme events. |
doi_str_mv | 10.1007/s00440-013-0525-9 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1620091160</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1620091160</sourcerecordid><originalsourceid>FETCH-LOGICAL-c420t-9b4bf15622fd40a1e94468105b87e2d472f4b45df7abb01137a160ad405d498e3</originalsourceid><addsrcrecordid>eNp9kE9LxDAQR4MouK5-AG8FL16iM-k0aY-6rH9gwYueQ7pNly5tsyYtut_eLPUggp7m8t7w4zF2iXCDAOo2ABABB0w5ZCLjxRGbIaWCC5B0zGaAKuc5ZHjKzkLYAoBIScwYX34O3namTTbWdXbw-8TViUnuvfvoG9MnO-fdGJLOVs3YnbOT2rTBXnzfOXt7WL4unvjq5fF5cbfiaxIw8KKkssZMClFXBAZtQSRzhKzMlRUVKVFTSVlVK1OWgJgqgxJMZLOKitymc3Y9_d159z7aMOiuCWvbtqa3cY1GKQAKjFJEr36hWzf6Pq7TQkoUsgDC_6i4E1SqKJWRwolaexeCt7Xe-aYzfq8R9CGznjLrmFkfMusiOmJyQmT7jfU_Pv8pfQHuAXvw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1560737436</pqid></control><display><type>article</type><title>Extremal geometry of a Brownian porous medium</title><source>Business Source® Complete</source><source>SpringerLink Journals - AutoHoldings</source><creator>Goodman, Jesse ; den Hollander, Frank</creator><creatorcontrib>Goodman, Jesse ; den Hollander, Frank</creatorcontrib><description>The path
W
[
0
,
t
]
of a Brownian motion on a
d
-dimensional torus
T
d
run for time
t
is a random compact subset of
T
d
. We study the geometric properties of the complement
T
d
\
W
[
0
,
t
]
as
t
→
∞
for
d
≥
3
. In particular, we show that the largest regions in
T
d
\
W
[
0
,
t
]
have a linear scale
φ
d
(
t
)
=
[
(
d
log
t
)
/
(
d
-
2
)
κ
d
t
]
1
/
(
d
-
2
)
, where
κ
d
is the capacity of the unit ball. More specifically, we identify the sets
E
for which
T
d
\
W
[
0
,
t
]
contains a translate of
φ
d
(
t
)
E
, and we count the number of disjoint such translates. Furthermore, we derive large deviation principles for the largest inradius of
T
d
\
W
[
0
,
t
]
as
t
→
∞
and the
ε
-cover time of
T
d
as
ε
↓
0
. Our results, which generalise laws of large numbers proved by Dembo et al. (Electron J Probab 8(15):1–14,
2003
), are based on a large deviation estimate for the shape of the component with largest capacity in
T
d
\
W
ρ
(
t
)
[
0
,
t
]
, where
W
ρ
(
t
)
[
0
,
t
]
is the Wiener sausage of radius
ρ
(
t
)
, with
ρ
(
t
)
chosen much smaller than
φ
d
(
t
)
but not too small. The idea behind this choice is that
T
d
\
W
[
0
,
t
]
consists of “lakes”, whose linear size is of order
φ
d
(
t
)
, connected by narrow “channels”. We also derive large deviation principles for the principal Dirichlet eigenvalue and for the maximal volume of the components of
T
d
\
W
ρ
(
t
)
[
0
,
t
]
as
t
→
∞
. Our results give a complete picture of the extremal geometry of
T
d
\
W
[
0
,
t
]
and of the optimal strategy for
W
[
0
,
t
]
to realise extreme events.</description><identifier>ISSN: 0178-8051</identifier><identifier>EISSN: 1432-2064</identifier><identifier>DOI: 10.1007/s00440-013-0525-9</identifier><identifier>CODEN: PTRFEU</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Brownian motion ; Channels ; Deviation ; Dirichlet problem ; Economics ; Eigenvalues ; Euclidean space ; Finance ; Geometry ; Insurance ; Lakes ; Management ; Mathematical and Computational Biology ; Mathematical and Computational Physics ; Mathematics ; Mathematics and Statistics ; Operations Research/Decision Theory ; Porous media ; Principles ; Probability ; Probability Theory and Stochastic Processes ; Quantitative Finance ; Statistics for Business ; Strategy ; Texts ; Theoretical ; Time & motion studies ; Toruses</subject><ispartof>Probability theory and related fields, 2014-10, Vol.160 (1-2), p.127-174</ispartof><rights>Springer-Verlag Berlin Heidelberg 2013</rights><rights>Springer-Verlag Berlin Heidelberg 2014</rights><rights>Springer-Verlag Berlin Heidelberg 2013.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c420t-9b4bf15622fd40a1e94468105b87e2d472f4b45df7abb01137a160ad405d498e3</citedby><cites>FETCH-LOGICAL-c420t-9b4bf15622fd40a1e94468105b87e2d472f4b45df7abb01137a160ad405d498e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00440-013-0525-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00440-013-0525-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids></links><search><creatorcontrib>Goodman, Jesse</creatorcontrib><creatorcontrib>den Hollander, Frank</creatorcontrib><title>Extremal geometry of a Brownian porous medium</title><title>Probability theory and related fields</title><addtitle>Probab. Theory Relat. Fields</addtitle><description>The path
W
[
0
,
t
]
of a Brownian motion on a
d
-dimensional torus
T
d
run for time
t
is a random compact subset of
T
d
. We study the geometric properties of the complement
T
d
\
W
[
0
,
t
]
as
t
→
∞
for
d
≥
3
. In particular, we show that the largest regions in
T
d
\
W
[
0
,
t
]
have a linear scale
φ
d
(
t
)
=
[
(
d
log
t
)
/
(
d
-
2
)
κ
d
t
]
1
/
(
d
-
2
)
, where
κ
d
is the capacity of the unit ball. More specifically, we identify the sets
E
for which
T
d
\
W
[
0
,
t
]
contains a translate of
φ
d
(
t
)
E
, and we count the number of disjoint such translates. Furthermore, we derive large deviation principles for the largest inradius of
T
d
\
W
[
0
,
t
]
as
t
→
∞
and the
ε
-cover time of
T
d
as
ε
↓
0
. Our results, which generalise laws of large numbers proved by Dembo et al. (Electron J Probab 8(15):1–14,
2003
), are based on a large deviation estimate for the shape of the component with largest capacity in
T
d
\
W
ρ
(
t
)
[
0
,
t
]
, where
W
ρ
(
t
)
[
0
,
t
]
is the Wiener sausage of radius
ρ
(
t
)
, with
ρ
(
t
)
chosen much smaller than
φ
d
(
t
)
but not too small. The idea behind this choice is that
T
d
\
W
[
0
,
t
]
consists of “lakes”, whose linear size is of order
φ
d
(
t
)
, connected by narrow “channels”. We also derive large deviation principles for the principal Dirichlet eigenvalue and for the maximal volume of the components of
T
d
\
W
ρ
(
t
)
[
0
,
t
]
as
t
→
∞
. Our results give a complete picture of the extremal geometry of
T
d
\
W
[
0
,
t
]
and of the optimal strategy for
W
[
0
,
t
]
to realise extreme events.</description><subject>Brownian motion</subject><subject>Channels</subject><subject>Deviation</subject><subject>Dirichlet problem</subject><subject>Economics</subject><subject>Eigenvalues</subject><subject>Euclidean space</subject><subject>Finance</subject><subject>Geometry</subject><subject>Insurance</subject><subject>Lakes</subject><subject>Management</subject><subject>Mathematical and Computational Biology</subject><subject>Mathematical and Computational Physics</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Operations Research/Decision Theory</subject><subject>Porous media</subject><subject>Principles</subject><subject>Probability</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Quantitative Finance</subject><subject>Statistics for Business</subject><subject>Strategy</subject><subject>Texts</subject><subject>Theoretical</subject><subject>Time & motion studies</subject><subject>Toruses</subject><issn>0178-8051</issn><issn>1432-2064</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kE9LxDAQR4MouK5-AG8FL16iM-k0aY-6rH9gwYueQ7pNly5tsyYtut_eLPUggp7m8t7w4zF2iXCDAOo2ABABB0w5ZCLjxRGbIaWCC5B0zGaAKuc5ZHjKzkLYAoBIScwYX34O3namTTbWdXbw-8TViUnuvfvoG9MnO-fdGJLOVs3YnbOT2rTBXnzfOXt7WL4unvjq5fF5cbfiaxIw8KKkssZMClFXBAZtQSRzhKzMlRUVKVFTSVlVK1OWgJgqgxJMZLOKitymc3Y9_d159z7aMOiuCWvbtqa3cY1GKQAKjFJEr36hWzf6Pq7TQkoUsgDC_6i4E1SqKJWRwolaexeCt7Xe-aYzfq8R9CGznjLrmFkfMusiOmJyQmT7jfU_Pv8pfQHuAXvw</recordid><startdate>20141001</startdate><enddate>20141001</enddate><creator>Goodman, Jesse</creator><creator>den Hollander, Frank</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>20141001</creationdate><title>Extremal geometry of a Brownian porous medium</title><author>Goodman, Jesse ; den Hollander, Frank</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c420t-9b4bf15622fd40a1e94468105b87e2d472f4b45df7abb01137a160ad405d498e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Brownian motion</topic><topic>Channels</topic><topic>Deviation</topic><topic>Dirichlet problem</topic><topic>Economics</topic><topic>Eigenvalues</topic><topic>Euclidean space</topic><topic>Finance</topic><topic>Geometry</topic><topic>Insurance</topic><topic>Lakes</topic><topic>Management</topic><topic>Mathematical and Computational Biology</topic><topic>Mathematical and Computational Physics</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Operations Research/Decision Theory</topic><topic>Porous media</topic><topic>Principles</topic><topic>Probability</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Quantitative Finance</topic><topic>Statistics for Business</topic><topic>Strategy</topic><topic>Texts</topic><topic>Theoretical</topic><topic>Time & motion studies</topic><topic>Toruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Goodman, Jesse</creatorcontrib><creatorcontrib>den Hollander, Frank</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global (ProQuest)</collection><collection>Computing Database</collection><collection>ProQuest Research Library</collection><collection>ProQuest Science Journals</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Probability theory and related fields</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Goodman, Jesse</au><au>den Hollander, Frank</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Extremal geometry of a Brownian porous medium</atitle><jtitle>Probability theory and related fields</jtitle><stitle>Probab. Theory Relat. Fields</stitle><date>2014-10-01</date><risdate>2014</risdate><volume>160</volume><issue>1-2</issue><spage>127</spage><epage>174</epage><pages>127-174</pages><issn>0178-8051</issn><eissn>1432-2064</eissn><coden>PTRFEU</coden><abstract>The path
W
[
0
,
t
]
of a Brownian motion on a
d
-dimensional torus
T
d
run for time
t
is a random compact subset of
T
d
. We study the geometric properties of the complement
T
d
\
W
[
0
,
t
]
as
t
→
∞
for
d
≥
3
. In particular, we show that the largest regions in
T
d
\
W
[
0
,
t
]
have a linear scale
φ
d
(
t
)
=
[
(
d
log
t
)
/
(
d
-
2
)
κ
d
t
]
1
/
(
d
-
2
)
, where
κ
d
is the capacity of the unit ball. More specifically, we identify the sets
E
for which
T
d
\
W
[
0
,
t
]
contains a translate of
φ
d
(
t
)
E
, and we count the number of disjoint such translates. Furthermore, we derive large deviation principles for the largest inradius of
T
d
\
W
[
0
,
t
]
as
t
→
∞
and the
ε
-cover time of
T
d
as
ε
↓
0
. Our results, which generalise laws of large numbers proved by Dembo et al. (Electron J Probab 8(15):1–14,
2003
), are based on a large deviation estimate for the shape of the component with largest capacity in
T
d
\
W
ρ
(
t
)
[
0
,
t
]
, where
W
ρ
(
t
)
[
0
,
t
]
is the Wiener sausage of radius
ρ
(
t
)
, with
ρ
(
t
)
chosen much smaller than
φ
d
(
t
)
but not too small. The idea behind this choice is that
T
d
\
W
[
0
,
t
]
consists of “lakes”, whose linear size is of order
φ
d
(
t
)
, connected by narrow “channels”. We also derive large deviation principles for the principal Dirichlet eigenvalue and for the maximal volume of the components of
T
d
\
W
ρ
(
t
)
[
0
,
t
]
as
t
→
∞
. Our results give a complete picture of the extremal geometry of
T
d
\
W
[
0
,
t
]
and of the optimal strategy for
W
[
0
,
t
]
to realise extreme events.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00440-013-0525-9</doi><tpages>48</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0178-8051 |
ispartof | Probability theory and related fields, 2014-10, Vol.160 (1-2), p.127-174 |
issn | 0178-8051 1432-2064 |
language | eng |
recordid | cdi_proquest_miscellaneous_1620091160 |
source | Business Source® Complete; SpringerLink Journals - AutoHoldings |
subjects | Brownian motion Channels Deviation Dirichlet problem Economics Eigenvalues Euclidean space Finance Geometry Insurance Lakes Management Mathematical and Computational Biology Mathematical and Computational Physics Mathematics Mathematics and Statistics Operations Research/Decision Theory Porous media Principles Probability Probability Theory and Stochastic Processes Quantitative Finance Statistics for Business Strategy Texts Theoretical Time & motion studies Toruses |
title | Extremal geometry of a Brownian porous medium |
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