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''for random covering''
 
''for random covering''
  
The Billard method was originally used to obtain a necessary condition for almost surely covering the circle <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105201.png" /> by random intervals of given lengths <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105202.png" /> (see [[Dvoretzky problem|Dvoretzky problem]]). Surprisingly, this necessary condition also turned out to be sufficient, not only in this case, but also in many extensions of the Dvoretzky problem. Unaware of this fact, P. Billard chose to give a weaker and more manageable condition, namely [[#References|[a1]]]:
+
The Billard method was originally used to obtain a necessary condition for almost surely covering the circle $  T $
 +
by random intervals of given lengths $  l _ {1} ,l _ {2} , \dots $(
 +
see [[Dvoretzky problem|Dvoretzky problem]]). Surprisingly, this necessary condition also turned out to be sufficient, not only in this case, but also in many extensions of the Dvoretzky problem. Unaware of this fact, P. Billard chose to give a weaker and more manageable condition, namely [[#References|[a1]]]:
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105203.png" /></td> <td valign="top" style="width:5%;text-align:right;">(a1)</td></tr></table>
+
$$ \tag{a1 }
 +
\sum _ {n = 1 } ^  \infty  l _ {n}  ^ {2} { \mathop{\rm exp} } ( l _ {1} + \dots + l _ {n} ) = \infty,
 +
$$
  
 
while the necessary and sufficient condition, stated by L. Shepp in 1972 is [[#References|[a3]]]:
 
while the necessary and sufficient condition, stated by L. Shepp in 1972 is [[#References|[a3]]]:
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105204.png" /></td> <td valign="top" style="width:5%;text-align:right;">(a2)</td></tr></table>
+
$$ \tag{a2 }
 +
\sum _ {n = 1 } ^  \infty  {
 +
\frac{1}{n  ^ {2} }
 +
} { \mathop{\rm exp} } ( l _ {1} + \dots + l _ {n} ) = \infty
 +
$$
  
when <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105205.png" /> (see [[Dvoretzky problem|Dvoretzky problem]]). Conditions (a1) and (a2) are quite close, but different; (a2) implies (a1), but (a1) does not imply (a2). Both are of interest when trying to cover the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105206.png" />-dimensional torus <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105207.png" /> almost surely by random translates of given convex sets <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105208.png" /> with volumes <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b1105209.png" /> (<img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052010.png" />). In that case, whatever <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052011.png" /> may be, (a1) is necessary and (a2) is sufficient. The necessary and sufficient condition lies in between; it is (a2) when <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052012.png" /> and changes, tending to (a1), as <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052013.png" /> increases to infinity, at least if one restricts to homothetic simplices [[#References|[a2]]].
+
when $  1 > l _ {1} \geq  l _ {2} \geq  \dots > 0 $(
 +
see [[Dvoretzky problem|Dvoretzky problem]]). Conditions (a1) and (a2) are quite close, but different; (a2) implies (a1), but (a1) does not imply (a2). Both are of interest when trying to cover the $  d $-
 +
dimensional torus $  T  ^ {d} $
 +
almost surely by random translates of given convex sets $  g _ {n} $
 +
with volumes $  v _ {n} = l _ {n} $(
 +
$  n = 1,2, \dots $).  
 +
In that case, whatever $  d $
 +
may be, (a1) is necessary and (a2) is sufficient. The necessary and sufficient condition lies in between; it is (a2) when $  d = 1 $
 +
and changes, tending to (a1), as $  d $
 +
increases to infinity, at least if one restricts to homothetic simplices [[#References|[a2]]].
  
The general setting for Billard's method is as follows: <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052014.png" /> is a space, e.g., <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052015.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052016.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052017.png" />, or <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052018.png" />; <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052019.png" /> is a [[Probability space|probability space]]; the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052020.png" /> (<img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052021.png" />; <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052022.png" />) are random independent subsets of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052023.png" />; and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052024.png" /> is a fixed subset of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052025.png" />. One writes <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052026.png" /> if <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052027.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052028.png" /> otherwise. The problem of covering <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052029.png" /> almost surely in such a way that each point belongs to infinitely many <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052030.png" /> reduces to verifying that the series
+
The general setting for Billard's method is as follows: $  X $
 +
is a space, e.g., $  T $,  
 +
$  T  ^ {d} $,  
 +
$  \mathbf R $,  
 +
or $  \mathbf R  ^ {d} $;  
 +
$  ( \Omega, {\mathcal A}, {\mathsf P} ) $
 +
is a [[Probability space|probability space]]; the $  G _ {n} = G _ {n} ( \omega ) $(
 +
$  n = 1,2, \dots $;  
 +
$  \omega \in \Omega $)  
 +
are random independent subsets of $  X $;  
 +
and $  K $
 +
is a fixed subset of $  X $.  
 +
One writes $  G _ {n} ( \omega,x ) = 1 $
 +
if $  x \in G _ {n} $
 +
and $  G _ {n} ( \omega,x ) = 0 $
 +
otherwise. The problem of covering $  K $
 +
almost surely in such a way that each point belongs to infinitely many $  G _ {n} $
 +
reduces to verifying that the series
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052031.png" /></td> </tr></table>
+
$$
 +
\sum _ {n = 1 } ^  \infty  G _ {n} ( \omega,x )
 +
$$
  
diverges almost surely on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052032.png" />. Billard's method is to consider the infinite product
+
diverges almost surely on $  K $.  
 +
Billard's method is to consider the infinite product
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052033.png" /></td> </tr></table>
+
$$
 +
\prod _ {n = 1 } ^  \infty  {
 +
\frac{1 - G _ {n} ( \omega,x ) }{1 - {\mathsf E} G _ {n} ( \omega,x ) }
 +
} ,
 +
$$
  
where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052034.png" /> denotes [[Mathematical expectation|mathematical expectation]]. If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052035.png" /> carries a probability measure <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052036.png" /> such that the [[Martingale|martingale]]
+
where $  {\mathsf E} ( \cdot ) $
 +
denotes [[Mathematical expectation|mathematical expectation]]. If $  K $
 +
carries a probability measure $  \sigma $
 +
such that the [[Martingale|martingale]]
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052037.png" /></td> </tr></table>
+
$$
 +
S _ {N} = \int\limits {\prod _ {n = 1 } ^ { N }  {
 +
\frac{1 - G _ {n} ( \omega,x ) }{1 - {\mathsf E} G _ {n} ( \omega,x ) }
 +
} }  {\sigma ( dx ) }
 +
$$
  
converges in <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052038.png" />, then the infinite product cannot vanish on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052039.png" /> almost surely, and then finite covering cannot take place. This happens whenever <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052040.png" />, that is, when
+
converges in $  L _ {2} ( \Omega ) $,  
 +
then the infinite product cannot vanish on $  K $
 +
almost surely, and then finite covering cannot take place. This happens whenever $  {\mathsf E} ( S _ {N}  ^ {2} ) = O ( 1 ) $,  
 +
that is, when
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052041.png" /></td> </tr></table>
+
$$
 +
{\int\limits \int\limits } {k _ {N} ( x,y ) }  {\sigma ( dx )  \sigma ( dy ) } < \infty,
 +
$$
  
 
where
 
where
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052042.png" /></td> </tr></table>
+
$$
 +
k _ {N} ( x,y ) =
 +
$$
  
<table class="eq" style="width:100%;"> <tr><td valign="top" style="width:94%;text-align:center;"><img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052043.png" /></td> </tr></table>
+
$$
 +
=  
 +
\prod _ {n = 1 } ^ { N }  {
 +
\frac{1 - {\mathsf E} G _ {n} ( \omega,x ) - {\mathsf E} G _ {n} ( \omega,y ) + {\mathsf E} G _ {n} ( \omega,x ) {\mathsf E} G _ {n} ( \omega,y ) }{( 1 - {\mathsf E} G _ {n} ( \omega,x ) ) ( 1 - {\mathsf E} G _ {n} ( \omega,y ) ) }
 +
} .
 +
$$
  
Therefore, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052044.png" /> is not covered by infinitely many <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052045.png" /> whenever <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052046.png" /> carries a [[Probability measure|probability measure]] of bounded energy with respect to the kernels <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052047.png" />.
+
Therefore, $  K $
 +
is not covered by infinitely many $  G _ {n} $
 +
whenever $  K $
 +
carries a [[Probability measure|probability measure]] of bounded energy with respect to the kernels $  k _ {N} ( x,y ) $.
  
In all cases of interest, this means that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052048.png" /> has a strictly positive [[Capacity|capacity]] with respect to a kernel <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052049.png" /> (<img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052050.png" />). In the general setting, this is not a necessary and sufficient condition. However, it proves necessary and sufficient in the following cases:
+
In all cases of interest, this means that $  K $
 +
has a strictly positive [[Capacity|capacity]] with respect to a kernel $  k ( x,y ) $(
 +
= k _  \infty  ( x,y ) $).  
 +
In the general setting, this is not a necessary and sufficient condition. However, it proves necessary and sufficient in the following cases:
  
1) <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052051.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052052.png" />, with <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052053.png" /> independent and Lebesgue-distributed on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052054.png" /> (the original [[Dvoretzky problem|Dvoretzky problem]]; here <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052055.png" /> and the condition reads <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052056.png" />);
+
1) $  X = K = T $
 +
and $  G _ {n} = ( 0,l _ {n} ) + \omega _ {n} $,
 +
with $  \omega _ {n} $
 +
independent and Lebesgue-distributed on $  T $(
 +
the original [[Dvoretzky problem|Dvoretzky problem]]; here $  k ( x,y ) = k _ {0} ( x,y ) $
 +
and the condition reads $  k _ {0} \notin L _ {1} ( T ) $);
  
2) <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052057.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052058.png" /> is a compact subset of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052059.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052060.png" /> as above;
+
2) $  X = T $,  
 +
$  K $
 +
is a compact subset of $  X $
 +
and $  G _ {n} $
 +
as above;
  
3) <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052061.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052062.png" />, where the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052063.png" /> are homothetic simplices and the <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052064.png" /> are independent and Lebesgue-distributed on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/b/b110/b110520/b11052065.png" />.
+
3) $  X = K = T  ^ {d} $
 +
and $  G _ {n} = g _ {n} + \omega _ {n} $,  
 +
where the $  g _ {n} $
 +
are homothetic simplices and the $  \omega _ {n} $
 +
are independent and Lebesgue-distributed on $  T  ^ {d} $.
  
 
The Billard method gives a rough idea of the relation between random coverings and [[Potential theory|potential theory]]. To go further, more powerful methods are needed [[#References|[a2]]] (see [[Fitzsimmons–Fristedt–Shepp theorem|Fitzsimmons–Fristedt–Shepp theorem]]).
 
The Billard method gives a rough idea of the relation between random coverings and [[Potential theory|potential theory]]. To go further, more powerful methods are needed [[#References|[a2]]] (see [[Fitzsimmons–Fristedt–Shepp theorem|Fitzsimmons–Fristedt–Shepp theorem]]).

Latest revision as of 10:59, 29 May 2020


for random covering

The Billard method was originally used to obtain a necessary condition for almost surely covering the circle $ T $ by random intervals of given lengths $ l _ {1} ,l _ {2} , \dots $( see Dvoretzky problem). Surprisingly, this necessary condition also turned out to be sufficient, not only in this case, but also in many extensions of the Dvoretzky problem. Unaware of this fact, P. Billard chose to give a weaker and more manageable condition, namely [a1]:

$$ \tag{a1 } \sum _ {n = 1 } ^ \infty l _ {n} ^ {2} { \mathop{\rm exp} } ( l _ {1} + \dots + l _ {n} ) = \infty, $$

while the necessary and sufficient condition, stated by L. Shepp in 1972 is [a3]:

$$ \tag{a2 } \sum _ {n = 1 } ^ \infty { \frac{1}{n ^ {2} } } { \mathop{\rm exp} } ( l _ {1} + \dots + l _ {n} ) = \infty $$

when $ 1 > l _ {1} \geq l _ {2} \geq \dots > 0 $( see Dvoretzky problem). Conditions (a1) and (a2) are quite close, but different; (a2) implies (a1), but (a1) does not imply (a2). Both are of interest when trying to cover the $ d $- dimensional torus $ T ^ {d} $ almost surely by random translates of given convex sets $ g _ {n} $ with volumes $ v _ {n} = l _ {n} $( $ n = 1,2, \dots $). In that case, whatever $ d $ may be, (a1) is necessary and (a2) is sufficient. The necessary and sufficient condition lies in between; it is (a2) when $ d = 1 $ and changes, tending to (a1), as $ d $ increases to infinity, at least if one restricts to homothetic simplices [a2].

The general setting for Billard's method is as follows: $ X $ is a space, e.g., $ T $, $ T ^ {d} $, $ \mathbf R $, or $ \mathbf R ^ {d} $; $ ( \Omega, {\mathcal A}, {\mathsf P} ) $ is a probability space; the $ G _ {n} = G _ {n} ( \omega ) $( $ n = 1,2, \dots $; $ \omega \in \Omega $) are random independent subsets of $ X $; and $ K $ is a fixed subset of $ X $. One writes $ G _ {n} ( \omega,x ) = 1 $ if $ x \in G _ {n} $ and $ G _ {n} ( \omega,x ) = 0 $ otherwise. The problem of covering $ K $ almost surely in such a way that each point belongs to infinitely many $ G _ {n} $ reduces to verifying that the series

$$ \sum _ {n = 1 } ^ \infty G _ {n} ( \omega,x ) $$

diverges almost surely on $ K $. Billard's method is to consider the infinite product

$$ \prod _ {n = 1 } ^ \infty { \frac{1 - G _ {n} ( \omega,x ) }{1 - {\mathsf E} G _ {n} ( \omega,x ) } } , $$

where $ {\mathsf E} ( \cdot ) $ denotes mathematical expectation. If $ K $ carries a probability measure $ \sigma $ such that the martingale

$$ S _ {N} = \int\limits {\prod _ {n = 1 } ^ { N } { \frac{1 - G _ {n} ( \omega,x ) }{1 - {\mathsf E} G _ {n} ( \omega,x ) } } } {\sigma ( dx ) } $$

converges in $ L _ {2} ( \Omega ) $, then the infinite product cannot vanish on $ K $ almost surely, and then finite covering cannot take place. This happens whenever $ {\mathsf E} ( S _ {N} ^ {2} ) = O ( 1 ) $, that is, when

$$ {\int\limits \int\limits } {k _ {N} ( x,y ) } {\sigma ( dx ) \sigma ( dy ) } < \infty, $$

where

$$ k _ {N} ( x,y ) = $$

$$ = \prod _ {n = 1 } ^ { N } { \frac{1 - {\mathsf E} G _ {n} ( \omega,x ) - {\mathsf E} G _ {n} ( \omega,y ) + {\mathsf E} G _ {n} ( \omega,x ) {\mathsf E} G _ {n} ( \omega,y ) }{( 1 - {\mathsf E} G _ {n} ( \omega,x ) ) ( 1 - {\mathsf E} G _ {n} ( \omega,y ) ) } } . $$

Therefore, $ K $ is not covered by infinitely many $ G _ {n} $ whenever $ K $ carries a probability measure of bounded energy with respect to the kernels $ k _ {N} ( x,y ) $.

In all cases of interest, this means that $ K $ has a strictly positive capacity with respect to a kernel $ k ( x,y ) $( $ = k _ \infty ( x,y ) $). In the general setting, this is not a necessary and sufficient condition. However, it proves necessary and sufficient in the following cases:

1) $ X = K = T $ and $ G _ {n} = ( 0,l _ {n} ) + \omega _ {n} $, with $ \omega _ {n} $ independent and Lebesgue-distributed on $ T $( the original Dvoretzky problem; here $ k ( x,y ) = k _ {0} ( x,y ) $ and the condition reads $ k _ {0} \notin L _ {1} ( T ) $);

2) $ X = T $, $ K $ is a compact subset of $ X $ and $ G _ {n} $ as above;

3) $ X = K = T ^ {d} $ and $ G _ {n} = g _ {n} + \omega _ {n} $, where the $ g _ {n} $ are homothetic simplices and the $ \omega _ {n} $ are independent and Lebesgue-distributed on $ T ^ {d} $.

The Billard method gives a rough idea of the relation between random coverings and potential theory. To go further, more powerful methods are needed [a2] (see Fitzsimmons–Fristedt–Shepp theorem).

For additional references, see Dvoretzky problem.

References

[a1] P. Billard, "Séries de Fourier aléatoirement bornées, continues, uniformément convergentes" Ann. Sci. Ecole Norm. Sup. , 82 (1965) pp. 131–179
[a2] J.-P. Kahane, "Recouvrements aléatoires et théorie du potentiel" Coll. Math. , 60/1 (1990) pp. 387–411
[a3] L.A. Shepp, "Covering the circle with random arcs" Israel J. Math. , 11 (1972) pp. 328–345
How to Cite This Entry:
Billard method. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Billard_method&oldid=14956
This article was adapted from an original article by J.-P. Kahane (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article