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''Moreau envelope''
 
''Moreau envelope''
  
Let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m1202301.png" /> be a real [[Hilbert space|Hilbert space]] and let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m1202302.png" /> be a lower semi-continuous extended-real-valued function (cf. also [[Continuous function|Continuous function]]) such that for a certain <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m1202303.png" />,
+
Let $H$ be a real [[Hilbert space|Hilbert space]] and let $f : H \rightarrow ( - \infty , + \infty ]$ be a lower semi-continuous extended-real-valued function (cf. also [[Continuous function|Continuous function]]) such that for a certain $T > 0$,
  
<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/m/m120/m120230/m1202304.png" /></td> </tr></table>
+
\begin{equation*} \operatorname { inf } _ { x \in H } \left( f ( x ) + ( 2 T ) ^ { - 1 } \| x \| ^ { 2 } \right) \end{equation*}
  
is finite. For <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m1202305.png" />, the Moreau envelope function <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m1202306.png" /> is defined by infimal convolution of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m1202307.png" /> with <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m1202308.png" />, i.e.,
+
is finite. For $t > 0$, the Moreau envelope function $f _ { t }$ is defined by infimal convolution of $f$ with $( 2 t ) ^ { - 1 } \| . \| ^ { 2 }$, i.e.,
  
<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/m/m120/m120230/m1202309.png" /></td> <td valign="top" style="width:5%;text-align:right;">(a1)</td></tr></table>
+
\begin{equation} \tag{a1} f _ { t } ( x ) = \operatorname { inf } _ { y \in H } \left( f ( y ) + \frac { 1 } { 2 t } \| x - y \| ^ { 2 } \right) , \quad x \in H. \end{equation}
  
This operation amounts geometrically to performing vector addition of the strict epigraphs of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023010.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023011.png" />. The Moreau envelopes are usually utilized as approximants of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023012.png" />, although regularization was not the purpose of the seminal paper [[#References|[a12]]].
+
This operation amounts geometrically to performing vector addition of the strict epigraphs of $f$ and $( 2 t ) ^ { - 1 } \| . \| ^ { 2 }$. The Moreau envelopes are usually utilized as approximants of $f$, although regularization was not the purpose of the seminal paper [[#References|[a12]]].
  
If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023013.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023014.png" /> is everywhere finite and Lipschitz continuous (cf. also [[Lipschitz condition|Lipschitz condition]]) on bounded sets. Moreover, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023015.png" /> increases pointwise to <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023016.png" /> as <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023017.png" /> decreases to <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023018.png" />; the convergence is in fact uniform on bounded sets (cf. also [[Uniform convergence|Uniform convergence]]) when <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023019.png" /> is uniformly continuous on bounded sets (cf. also [[Uniform continuity|Uniform continuity]]). One might expect that under some additional assumptions on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023020.png" /> the differentiability properties of the square of the norm in <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023021.png" /> should to some extent carry over to <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023022.png" />, thus giving rise to a smooth regularization of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023023.png" />. This is true in the presence of convexity.
+
If $t \in ( 0 , T )$, $f _ { t }$ is everywhere finite and Lipschitz continuous (cf. also [[Lipschitz condition|Lipschitz condition]]) on bounded sets. Moreover, $f _ { t }$ increases pointwise to $f$ as $t$ decreases to $0$; the convergence is in fact uniform on bounded sets (cf. also [[Uniform convergence|Uniform convergence]]) when $f$ is uniformly continuous on bounded sets (cf. also [[Uniform continuity|Uniform continuity]]). One might expect that under some additional assumptions on $f$ the differentiability properties of the square of the norm in $H$ should to some extent carry over to $f _ { t }$, thus giving rise to a smooth regularization of $f$. This is true in the presence of convexity.
  
 
==The convex case.==
 
==The convex case.==
Suppose <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023024.png" /> is convex (cf. also [[Convex function (of a real variable)|Convex function (of a real variable)]]). Then <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023025.png" /> is differentiable and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023026.png" /> is globally Lipschitz continuous of rate <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023027.png" /> when <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023028.png" />. Furthermore, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023029.png" /> is a classical solution of
+
Suppose $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ is convex (cf. also [[Convex function (of a real variable)|Convex function (of a real variable)]]). Then $f _ { t }$ is differentiable and $d f _ { t }$ is globally Lipschitz continuous of rate $\operatorname { max } \{ 1 / t , 1 / ( T - t ) \}$ when $t \in ( 0 , T )$. Furthermore, $u ( t , x ) = f _ { t } ( x )$ is a classical solution of
  
<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/m/m120/m120230/m12023030.png" /></td> </tr></table>
+
\begin{equation*} \frac { \partial u ( t , x ) } { \partial t } + \frac { 1 } { 2 } \| d _ { x } u ( t , x ) \| ^ { 2 } = 0 , \quad ( t , x ) \in ( 0 , T ) \times H. \end{equation*}
  
Let the subdifferential of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023031.png" /> be defined by
+
Let the subdifferential of $f$ be defined by
  
<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/m/m120/m120230/m12023032.png" /></td> </tr></table>
+
\begin{equation*} \partial f ( x ) = \partial _ { c } \left( f + ( 2 T ) ^ { - 1 }  \| \cdot \| ^ { 2 } \right) ( x ) - T ^ { - 1 } x , \quad x \in H, \end{equation*}
  
where the first term at the right-hand side is the subdifferential in the sense of convex analysis of the convex function <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023033.png" /> (<img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023034.png" /> means that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023035.png" /> is finite and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023036.png" /> for all <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023037.png" />). The infimum (a1) is achieved at a unique point <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023038.png" />, which is denoted by <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023039.png" /> and is given by <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023040.png" />. Furthermore,
+
where the first term at the right-hand side is the subdifferential in the sense of convex analysis of the convex function $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ ($\xi \in \partial _ { c } g ( x )$ means that $g ( x )$ is finite and $g ( y ) \geq g ( x ) + \langle y - x , \xi \rangle$ for all $y$). The infimum (a1) is achieved at a unique point $y$, which is denoted by $R _ { t } ( x )$ and is given by $R _ { t } ( x ) = ( I + t \partial f ) ^ { - 1 } ( x )$. Furthermore,
  
<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/m/m120/m120230/m12023041.png" /></td> </tr></table>
+
\begin{equation*} d f _ { t } = t ^ { - 1 } ( I - R _ { t } ) = ( ( \partial f ) ^ { - 1 } + t I ) ^ { - 1 }, \end{equation*}
  
which justifies the alternative term Moreau–Yosida approximation, since <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023042.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023043.png" />, are the Yosida approximants of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023044.png" />. Moreover, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023045.png" /> in the sense of Kuratowski–Painlevé convergence of graphs in <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023046.png" />, while <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023047.png" /> converges to the element of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023048.png" /> of minimal norm unless <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023049.png" /> is empty. Stationary points and values are preserved; as a matter of fact, if <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023050.png" />, then
+
which justifies the alternative term Moreau–Yosida approximation, since $( ( \partial f ) ^ { - 1 } + t l ) ^ { - 1 }$, $t > 0$, are the Yosida approximants of $\partial f$. Moreover, $d f _ { t } \rightarrow \partial f$ in the sense of Kuratowski–Painlevé convergence of graphs in $H \times H$, while $d f _ { t } ( x )$ converges to the element of $\partial f ( x )$ of minimal norm unless $\partial f ( x )$ is empty. Stationary points and values are preserved; as a matter of fact, if $( t , x ) \in ( 0 , T ) \times H$, then
  
<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/m/m120/m120230/m12023051.png" /></td> </tr></table>
+
\begin{equation*} d f _ { t } ( x ) = 0 \Leftrightarrow \partial f ( x ) \ni 0 \Leftrightarrow f _ { t } ( x ) = f ( x ). \end{equation*}
  
 
For various applications and further properties, consult [[#References|[a3]]], [[#References|[a4]]], [[#References|[a1]]], [[#References|[a2]]].
 
For various applications and further properties, consult [[#References|[a3]]], [[#References|[a4]]], [[#References|[a1]]], [[#References|[a2]]].
  
 
==Regularization in the non-convex case.==
 
==Regularization in the non-convex case.==
If one insists on a smooth regularization, the Moreau envelopes cannot be used for arbitrary functions. This is however not a serious drawback. It is easy to see that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023052.png" /> is always a convex function, so that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023053.png" /> is smooth when <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023054.png" />; in fact, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023055.png" /> is globally Lipschitz continuous of rate <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023056.png" />. Explicitly,
+
If one insists on a smooth regularization, the Moreau envelopes cannot be used for arbitrary functions. This is however not a serious drawback. It is easy to see that $- f _ { t } + ( 2 t ) ^ { - 1 } \| . \| ^ { 2 }$ is always a convex function, so that $f _ { t , s } : = - ( - f _ { t } ) _ { s }$ is smooth when $0 < s < t < T$; in fact, $d f _ { t ,\, s }$ is globally Lipschitz continuous of rate $\operatorname { max } \{ 1 / s , 1 / ( t - s ) \}$. Explicitly,
  
<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/m/m120/m120230/m12023057.png" /></td> </tr></table>
+
\begin{equation*} f _ { t , s } ( x ) = \operatorname { sup } _ { z \in H } \operatorname { inf } _ { y \in H } \left( f ( y ) + \frac { 1 } { 2 t } \| z - y \| ^ { 2 } - \frac { 1 } { 2 s } \| x - z \| ^ { 2 } \right) \end{equation*}
  
for all <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023058.png" />.
+
for all $x \in H$.
  
Moreover, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023059.png" /> and hence <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023060.png" /> pointwise as <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023061.png" />. The double envelopes <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023062.png" />, frequently called the Lasry–Lions approximants of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023063.png" />, were introduced and investigated by J.-M. Lasry and P.-L. Lions in [[#References|[a10]]]; see also [[#References|[a4]]], [[#References|[a13]]]. One can prove that the equation <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023064.png" /> is true for all <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023065.png" /> exactly when <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023066.png" /> is a convex function [[#References|[a13]]], in which case therefore the approximation method reduces to the previous one.
+
Moreover, $f _ { t - s } \leq f _ { t , s } \leq f$ and hence $f _ { t , s } \rightarrow f$ pointwise as $0 < s < t \rightarrow 0$. The double envelopes $f _ { t , s }$, frequently called the Lasry–Lions approximants of $f$, were introduced and investigated by J.-M. Lasry and P.-L. Lions in [[#References|[a10]]]; see also [[#References|[a4]]], [[#References|[a13]]]. One can prove that the equation $f _ { t , s } = f _ { t - s }$ is true for all $0 < s < t < T$ exactly when $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ is a convex function [[#References|[a13]]], in which case therefore the approximation method reduces to the previous one.
  
 
==Connections with the Hamilton–Jacobi equation.==
 
==Connections with the Hamilton–Jacobi equation.==
As stated above, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023067.png" /> furnishes a classical solution of the initial-value problem
+
As stated above, $u ( t , x ) = f _ { t } ( x )$ furnishes a classical solution of the initial-value problem
  
<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/m/m120/m120230/m12023068.png" /></td> </tr></table>
+
\begin{equation*} \frac { \partial u ( t , x ) } { \partial t } + \frac { 1 } { 2 } \| d _ { x } u ( t , x ) \| ^ { 2 } = 0 , \quad ( t , x ) \in ( 0 , T ) \times H, \end{equation*}
  
<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/m/m120/m120230/m12023069.png" /></td> </tr></table>
+
\begin{equation*} \operatorname { lim } _ { t \downarrow 0 } u ( t , x ) = f ( x ) \quad \text { for all } x \in H, \end{equation*}
  
if <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023070.png" /> is a convex function. Let, now, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023071.png" /> and drop the convexity hypothesis on <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023072.png" />. While being non-differentiable in general, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023073.png" /> is nonetheless locally Lipschitz continuous in <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023074.png" /> and is known to be the unique viscosity solution of the above initial-value problem [[#References|[a11]]], [[#References|[a14]]]. (This notion of a generalized solution allows merely continuous functions to be solutions, [[#References|[a6]]]; cf. [[Viscosity solutions|Viscosity solutions]]). In this context, (a1) is referred to as the Lax formula; the Lax formula is intimately related to the Hopf formula for conservation laws, see [[#References|[a9]]], [[#References|[a7]]], [[#References|[a8]]], [[#References|[a11]]].
+
if $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ is a convex function. Let, now, $H = {\bf R} ^ { n }$ and drop the convexity hypothesis on $f$. While being non-differentiable in general, $u ( t , x ) = f _ { t } ( x )$ is nonetheless locally Lipschitz continuous in $( 0 , T ) \times \mathbf{R} ^ { n }$ and is known to be the unique viscosity solution of the above initial-value problem [[#References|[a11]]], [[#References|[a14]]]. (This notion of a generalized solution allows merely continuous functions to be solutions, [[#References|[a6]]]; cf. [[Viscosity solutions|Viscosity solutions]]). In this context, (a1) is referred to as the Lax formula; the Lax formula is intimately related to the Hopf formula for conservation laws, see [[#References|[a9]]], [[#References|[a7]]], [[#References|[a8]]], [[#References|[a11]]].
  
 
==Extensions to Banach spaces.==
 
==Extensions to Banach spaces.==
The Lasry–Lions regularization scheme has been extended to certain classes of Banach spaces <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023075.png" />. For the case where <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023076.png" /> and the dual norm <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023077.png" /> are simultaneously locally uniformly rotund, an approach by means of the Legendre–Fenchel transformation has been taken in [[#References|[a13]]]. Another extension appears in [[#References|[a5]]], under the hypothesis that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023078.png" /> be super-reflexive (cf. also [[Reflexive space|Reflexive space]]).
+
The Lasry–Lions regularization scheme has been extended to certain classes of Banach spaces $( X , \| \, .\,  \| )$. For the case where $\| .\|$ and the dual norm $\| . \|_{*}$ are simultaneously locally uniformly rotund, an approach by means of the Legendre–Fenchel transformation has been taken in [[#References|[a13]]]. Another extension appears in [[#References|[a5]]], under the hypothesis that $X$ be super-reflexive (cf. also [[Reflexive space|Reflexive space]]).
  
 
For more on the theme of regularization, see (the editorial comments to) [[Regularization|Regularization]] and [[Regularization method|Regularization method]].
 
For more on the theme of regularization, see (the editorial comments to) [[Regularization|Regularization]] and [[Regularization method|Regularization method]].
  
 
====References====
 
====References====
<table><TR><TD valign="top">[a1]</TD> <TD valign="top">  I. Ekeland,  J.M. Lasry,  "On the number of periodic trajectories for a Hamiltonian flow on a convex energy surface"  ''Ann. of Math.'' , '''112'''  (1980)  pp. 283–319</TD></TR><TR><TD valign="top">[a2]</TD> <TD valign="top">  R.T. Rockafellar,  R.J.-B. Wets,  "Variational analysis" , Springer  (1998)</TD></TR><TR><TD valign="top">[a3]</TD> <TD valign="top">  H. Attouch,  "Variational convergence for functions and operators" , ''Applicable Math.'' , Pitman  (1984)</TD></TR><TR><TD valign="top">[a4]</TD> <TD valign="top">  H. Attouch,  D. Azé,  "Approximation and regularization of arbitrary functions in Hilbert spaces by the Lasry–Lions method"  ''Ann. Inst. H. Poincaré Anal. Non Lin.'' , '''10'''  (1993)  pp. 289–312</TD></TR><TR><TD valign="top">[a5]</TD> <TD valign="top">  M. Cepedello–Boiso,  "On regularization in superreflexive Banach spaces by infimal convolution formulas"  ''Studia Math.'' , '''129'''  (1998)  pp. 265–284</TD></TR><TR><TD valign="top">[a6]</TD> <TD valign="top">  M.G. Crandall,  P.-L. Lions,  "Viscosity solutions of Hamilton–Jacobi equations"  ''Trans. Amer. Math. Soc.'' , '''277'''  (1983)  pp. 1–42</TD></TR><TR><TD valign="top">[a7]</TD> <TD valign="top">  E. Hopf,  "The partial differential equation <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m120/m120230/m12023079.png" />"  ''Commun. Pure Appl. Math.'' , '''3'''  (1950)  pp. 201–230</TD></TR><TR><TD valign="top">[a8]</TD> <TD valign="top">  E. Hopf,  "Generalized solutions of non-linear equations of first order"  ''J. Math. Mech.'' , '''14'''  (1965)  pp. 951–973</TD></TR><TR><TD valign="top">[a9]</TD> <TD valign="top">  P.D. Lax,  "Hyperbolic systems of conservation laws II"  ''Commun. Pure Appl. Math.'' , '''10'''  (1957)  pp. 537–566</TD></TR><TR><TD valign="top">[a10]</TD> <TD valign="top">  J.-M. Lasry,  P.-L. Lions,  "A remark on regularization in Hilbert spaces"  ''Israel J. Math.'' , '''55'''  (1986)  pp. 257–266</TD></TR><TR><TD valign="top">[a11]</TD> <TD valign="top">  P.-L. Lions,  "Generalized solutions of Hamilton–Jacobi equations" , ''Res. Notes Math.'' , '''69''' , Pitman  (1982)</TD></TR><TR><TD valign="top">[a12]</TD> <TD valign="top">  J-J. Moreau,  "Proximité et dualité dans un espace hilbertien"  ''Bull. Soc. Math. France'' , '''93'''  (1965)  pp. 273–299</TD></TR><TR><TD valign="top">[a13]</TD> <TD valign="top">  T. Strömberg,  "On regularization in Banach spaces"  ''Ark. Mat.'' , '''34'''  (1996)  pp. 383–406</TD></TR><TR><TD valign="top">[a14]</TD> <TD valign="top">  T. Strömberg,  "Hopf's formula gives the unique viscosity solution"  ''Math. Scand.''  (submitted)</TD></TR></table>
+
<table>
 +
<tr><td valign="top">[a1]</td> <td valign="top">  I. Ekeland,  J.M. Lasry,  "On the number of periodic trajectories for a Hamiltonian flow on a convex energy surface"  ''Ann. of Math.'' , '''112'''  (1980)  pp. 283–319</td></tr><tr><td valign="top">[a2]</td> <td valign="top">  R.T. Rockafellar,  R.J.-B. Wets,  "Variational analysis" , Springer  (1998)</td></tr><tr><td valign="top">[a3]</td> <td valign="top">  H. Attouch,  "Variational convergence for functions and operators" , ''Applicable Math.'' , Pitman  (1984)</td></tr><tr><td valign="top">[a4]</td> <td valign="top">  H. Attouch,  D. Azé,  "Approximation and regularization of arbitrary functions in Hilbert spaces by the Lasry–Lions method"  ''Ann. Inst. H. Poincaré Anal. Non Lin.'' , '''10'''  (1993)  pp. 289–312</td></tr><tr><td valign="top">[a5]</td> <td valign="top">  M. Cepedello–Boiso,  "On regularization in superreflexive Banach spaces by infimal convolution formulas"  ''Studia Math.'' , '''129'''  (1998)  pp. 265–284</td></tr><tr><td valign="top">[a6]</td> <td valign="top">  M.G. Crandall,  P.-L. Lions,  "Viscosity solutions of Hamilton–Jacobi equations"  ''Trans. Amer. Math. Soc.'' , '''277'''  (1983)  pp. 1–42</td></tr><tr><td valign="top">[a7]</td> <td valign="top">  E. Hopf,  "The partial differential equation $u _ { t } + u u _ { x } = \mu u _ { xx }$"  ''Commun. Pure Appl. Math.'' , '''3'''  (1950)  pp. 201–230</td></tr><tr><td valign="top">[a8]</td> <td valign="top">  E. Hopf,  "Generalized solutions of non-linear equations of first order"  ''J. Math. Mech.'' , '''14'''  (1965)  pp. 951–973</td></tr><tr><td valign="top">[a9]</td> <td valign="top">  P.D. Lax,  "Hyperbolic systems of conservation laws II"  ''Commun. Pure Appl. Math.'' , '''10'''  (1957)  pp. 537–566</td></tr><tr><td valign="top">[a10]</td> <td valign="top">  J.-M. Lasry,  P.-L. Lions,  "A remark on regularization in Hilbert spaces"  ''Israel J. Math.'' , '''55'''  (1986)  pp. 257–266</td></tr><tr><td valign="top">[a11]</td> <td valign="top">  P.-L. Lions,  "Generalized solutions of Hamilton–Jacobi equations" , ''Res. Notes Math.'' , '''69''' , Pitman  (1982)</td></tr><tr><td valign="top">[a12]</td> <td valign="top">  J-J. Moreau,  "Proximité et dualité dans un espace hilbertien"  ''Bull. Soc. Math. France'' , '''93'''  (1965)  pp. 273–299</td></tr><tr><td valign="top">[a13]</td> <td valign="top">  T. Strömberg,  "On regularization in Banach spaces"  ''Ark. Mat.'' , '''34'''  (1996)  pp. 383–406</td></tr><tr><td valign="top">[a14]</td> <td valign="top">  T. Strömberg,  "Hopf's formula gives the unique viscosity solution"  ''Math. Scand.''  (submitted)</td></tr>
 +
</table>

Latest revision as of 20:56, 8 February 2024

Moreau envelope

Let $H$ be a real Hilbert space and let $f : H \rightarrow ( - \infty , + \infty ]$ be a lower semi-continuous extended-real-valued function (cf. also Continuous function) such that for a certain $T > 0$,

\begin{equation*} \operatorname { inf } _ { x \in H } \left( f ( x ) + ( 2 T ) ^ { - 1 } \| x \| ^ { 2 } \right) \end{equation*}

is finite. For $t > 0$, the Moreau envelope function $f _ { t }$ is defined by infimal convolution of $f$ with $( 2 t ) ^ { - 1 } \| . \| ^ { 2 }$, i.e.,

\begin{equation} \tag{a1} f _ { t } ( x ) = \operatorname { inf } _ { y \in H } \left( f ( y ) + \frac { 1 } { 2 t } \| x - y \| ^ { 2 } \right) , \quad x \in H. \end{equation}

This operation amounts geometrically to performing vector addition of the strict epigraphs of $f$ and $( 2 t ) ^ { - 1 } \| . \| ^ { 2 }$. The Moreau envelopes are usually utilized as approximants of $f$, although regularization was not the purpose of the seminal paper [a12].

If $t \in ( 0 , T )$, $f _ { t }$ is everywhere finite and Lipschitz continuous (cf. also Lipschitz condition) on bounded sets. Moreover, $f _ { t }$ increases pointwise to $f$ as $t$ decreases to $0$; the convergence is in fact uniform on bounded sets (cf. also Uniform convergence) when $f$ is uniformly continuous on bounded sets (cf. also Uniform continuity). One might expect that under some additional assumptions on $f$ the differentiability properties of the square of the norm in $H$ should to some extent carry over to $f _ { t }$, thus giving rise to a smooth regularization of $f$. This is true in the presence of convexity.

The convex case.

Suppose $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ is convex (cf. also Convex function (of a real variable)). Then $f _ { t }$ is differentiable and $d f _ { t }$ is globally Lipschitz continuous of rate $\operatorname { max } \{ 1 / t , 1 / ( T - t ) \}$ when $t \in ( 0 , T )$. Furthermore, $u ( t , x ) = f _ { t } ( x )$ is a classical solution of

\begin{equation*} \frac { \partial u ( t , x ) } { \partial t } + \frac { 1 } { 2 } \| d _ { x } u ( t , x ) \| ^ { 2 } = 0 , \quad ( t , x ) \in ( 0 , T ) \times H. \end{equation*}

Let the subdifferential of $f$ be defined by

\begin{equation*} \partial f ( x ) = \partial _ { c } \left( f + ( 2 T ) ^ { - 1 } \| \cdot \| ^ { 2 } \right) ( x ) - T ^ { - 1 } x , \quad x \in H, \end{equation*}

where the first term at the right-hand side is the subdifferential in the sense of convex analysis of the convex function $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ ($\xi \in \partial _ { c } g ( x )$ means that $g ( x )$ is finite and $g ( y ) \geq g ( x ) + \langle y - x , \xi \rangle$ for all $y$). The infimum (a1) is achieved at a unique point $y$, which is denoted by $R _ { t } ( x )$ and is given by $R _ { t } ( x ) = ( I + t \partial f ) ^ { - 1 } ( x )$. Furthermore,

\begin{equation*} d f _ { t } = t ^ { - 1 } ( I - R _ { t } ) = ( ( \partial f ) ^ { - 1 } + t I ) ^ { - 1 }, \end{equation*}

which justifies the alternative term Moreau–Yosida approximation, since $( ( \partial f ) ^ { - 1 } + t l ) ^ { - 1 }$, $t > 0$, are the Yosida approximants of $\partial f$. Moreover, $d f _ { t } \rightarrow \partial f$ in the sense of Kuratowski–Painlevé convergence of graphs in $H \times H$, while $d f _ { t } ( x )$ converges to the element of $\partial f ( x )$ of minimal norm unless $\partial f ( x )$ is empty. Stationary points and values are preserved; as a matter of fact, if $( t , x ) \in ( 0 , T ) \times H$, then

\begin{equation*} d f _ { t } ( x ) = 0 \Leftrightarrow \partial f ( x ) \ni 0 \Leftrightarrow f _ { t } ( x ) = f ( x ). \end{equation*}

For various applications and further properties, consult [a3], [a4], [a1], [a2].

Regularization in the non-convex case.

If one insists on a smooth regularization, the Moreau envelopes cannot be used for arbitrary functions. This is however not a serious drawback. It is easy to see that $- f _ { t } + ( 2 t ) ^ { - 1 } \| . \| ^ { 2 }$ is always a convex function, so that $f _ { t , s } : = - ( - f _ { t } ) _ { s }$ is smooth when $0 < s < t < T$; in fact, $d f _ { t ,\, s }$ is globally Lipschitz continuous of rate $\operatorname { max } \{ 1 / s , 1 / ( t - s ) \}$. Explicitly,

\begin{equation*} f _ { t , s } ( x ) = \operatorname { sup } _ { z \in H } \operatorname { inf } _ { y \in H } \left( f ( y ) + \frac { 1 } { 2 t } \| z - y \| ^ { 2 } - \frac { 1 } { 2 s } \| x - z \| ^ { 2 } \right) \end{equation*}

for all $x \in H$.

Moreover, $f _ { t - s } \leq f _ { t , s } \leq f$ and hence $f _ { t , s } \rightarrow f$ pointwise as $0 < s < t \rightarrow 0$. The double envelopes $f _ { t , s }$, frequently called the Lasry–Lions approximants of $f$, were introduced and investigated by J.-M. Lasry and P.-L. Lions in [a10]; see also [a4], [a13]. One can prove that the equation $f _ { t , s } = f _ { t - s }$ is true for all $0 < s < t < T$ exactly when $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ is a convex function [a13], in which case therefore the approximation method reduces to the previous one.

Connections with the Hamilton–Jacobi equation.

As stated above, $u ( t , x ) = f _ { t } ( x )$ furnishes a classical solution of the initial-value problem

\begin{equation*} \frac { \partial u ( t , x ) } { \partial t } + \frac { 1 } { 2 } \| d _ { x } u ( t , x ) \| ^ { 2 } = 0 , \quad ( t , x ) \in ( 0 , T ) \times H, \end{equation*}

\begin{equation*} \operatorname { lim } _ { t \downarrow 0 } u ( t , x ) = f ( x ) \quad \text { for all } x \in H, \end{equation*}

if $f + ( 2 T ) ^ { - 1 } \| . \| ^ { 2 }$ is a convex function. Let, now, $H = {\bf R} ^ { n }$ and drop the convexity hypothesis on $f$. While being non-differentiable in general, $u ( t , x ) = f _ { t } ( x )$ is nonetheless locally Lipschitz continuous in $( 0 , T ) \times \mathbf{R} ^ { n }$ and is known to be the unique viscosity solution of the above initial-value problem [a11], [a14]. (This notion of a generalized solution allows merely continuous functions to be solutions, [a6]; cf. Viscosity solutions). In this context, (a1) is referred to as the Lax formula; the Lax formula is intimately related to the Hopf formula for conservation laws, see [a9], [a7], [a8], [a11].

Extensions to Banach spaces.

The Lasry–Lions regularization scheme has been extended to certain classes of Banach spaces $( X , \| \, .\, \| )$. For the case where $\| .\|$ and the dual norm $\| . \|_{*}$ are simultaneously locally uniformly rotund, an approach by means of the Legendre–Fenchel transformation has been taken in [a13]. Another extension appears in [a5], under the hypothesis that $X$ be super-reflexive (cf. also Reflexive space).

For more on the theme of regularization, see (the editorial comments to) Regularization and Regularization method.

References

[a1] I. Ekeland, J.M. Lasry, "On the number of periodic trajectories for a Hamiltonian flow on a convex energy surface" Ann. of Math. , 112 (1980) pp. 283–319
[a2] R.T. Rockafellar, R.J.-B. Wets, "Variational analysis" , Springer (1998)
[a3] H. Attouch, "Variational convergence for functions and operators" , Applicable Math. , Pitman (1984)
[a4] H. Attouch, D. Azé, "Approximation and regularization of arbitrary functions in Hilbert spaces by the Lasry–Lions method" Ann. Inst. H. Poincaré Anal. Non Lin. , 10 (1993) pp. 289–312
[a5] M. Cepedello–Boiso, "On regularization in superreflexive Banach spaces by infimal convolution formulas" Studia Math. , 129 (1998) pp. 265–284
[a6] M.G. Crandall, P.-L. Lions, "Viscosity solutions of Hamilton–Jacobi equations" Trans. Amer. Math. Soc. , 277 (1983) pp. 1–42
[a7] E. Hopf, "The partial differential equation $u _ { t } + u u _ { x } = \mu u _ { xx }$" Commun. Pure Appl. Math. , 3 (1950) pp. 201–230
[a8] E. Hopf, "Generalized solutions of non-linear equations of first order" J. Math. Mech. , 14 (1965) pp. 951–973
[a9] P.D. Lax, "Hyperbolic systems of conservation laws II" Commun. Pure Appl. Math. , 10 (1957) pp. 537–566
[a10] J.-M. Lasry, P.-L. Lions, "A remark on regularization in Hilbert spaces" Israel J. Math. , 55 (1986) pp. 257–266
[a11] P.-L. Lions, "Generalized solutions of Hamilton–Jacobi equations" , Res. Notes Math. , 69 , Pitman (1982)
[a12] J-J. Moreau, "Proximité et dualité dans un espace hilbertien" Bull. Soc. Math. France , 93 (1965) pp. 273–299
[a13] T. Strömberg, "On regularization in Banach spaces" Ark. Mat. , 34 (1996) pp. 383–406
[a14] T. Strömberg, "Hopf's formula gives the unique viscosity solution" Math. Scand. (submitted)
How to Cite This Entry:
Moreau envelope function. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Moreau_envelope_function&oldid=14680
This article was adapted from an original article by Thomas Strömberg (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article