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{{MSC|03E04}} ''in set theory''
  
{{MSC|26A45}} (Functions of one variable)
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{{MSC|28A}} ''in measure theory''
  
{{MSC|26B30|28A15,26B15,49Q15}} (Functions of severable variables)
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==Set theory==
 
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A minimal non-zero element of a [[Partially ordered set|partially ordered set]] with a zero $0$, i.e. an element $p$ such that $0<x\leq p$ implies $x=p$.
[[Category:Analysis]]
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==Measure algebras==
 
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For the definition and relevance in the theory of measure algebras we refer to [[Measure algebra]].
{{TEX|done}}
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==Classical measure theory==
 
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===Definition===
Also called ''total variation''. A numerical characteristic of functions of one or more real variables which is connected with differentiability properties.
+
Let $\mu$ be a (nonnegative) [[Measure|measure]] on a [[Algebra of sets|$\sigma$-algebra]] $\mathcal{S}$ of subsets of a set $X$. An element $a\in \mathcal{S}$ is called an ''atom'' of $\mu$ if
 
+
*$\mu (A)>0$;
==Functions of one variable==
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*For every $B\in \mathcal{S}$ with $B\subset A$ either $\mu (B)=0$ or $\mu (B)=\mu (A)$
===Classical definition===
+
(cp. with Section IV.9.8 of {{Cite|DS}} or {{Cite|Fe}}).
Let $I\subset \mathbb R$ be an interval. The total variation is defined in the following way.
 
 
 
'''Definition 1'''
 
Consider the collection $\Pi$ of ordered $(N+1)$-ples of points $a_1<a_2 < \ldots <  a_{N+1}\in I$,
 
where $N$ is an arbitrary natural number. The total variation of a function $f: I\to \mathbb R$ is given by
 
\begin{equation}\label{e:TV}
 
TV\, (f) := \sup \left\{ \sum_{i=1}^N |f(a_{i+1})-f(a_i)| : (a_1, \ldots, a_{N+1})\in\Pi\right\}\,
 
\end{equation}
 
(cp. with Section 4.4 of {{cite|Co}} or Section 10.2 of {{Cite|Ro}}).
 
 
 
If the total variation is finite, then $f$ is called a [[Function of bounded variation|function of bounded variation]]. For examples, properties and issues related to the space of functions of bounded variation we refer to [[Function of bounded variation]].
 
 
 
The  definition of total variation of a function of one real variable  can be  easily generalized when the target is a [[Metric space|metric  space]]  $(X,d)$: it suffices to substitute $|f(a_{i+1})-f(a_i)|$ with  $d (f(a_{i+1}),  f(a_i))$ in \ref{e:TV}.
 
 
 
===Modern definition and relation to measure theory===
 
Classically  right-continuous functions of bounded variations can be  mapped  one-to-one to [[Signed measure|signed measures]]. More  precisely,  consider a signed measure $\mu$ on (the [[Borel set|Borel  subsets ]] of$\mathbb R$ with finite total variation (see [[Signed  measure]] for the  definition). We then define the function
 
\begin{equation}\label{e:F_mu}
 
F_\mu (x) := \mu (]-\infty, x])\, .
 
\end{equation}
 
 
 
'''Theorem 2'''
 
*  For every signed measure $\mu$ with finite total variation, $F_\mu$ is  a right-continuous function of bounded variation such that $\lim_{x\to  -\infty} F_\mu (x) = 0$ and $TV (f)$ equals the total variation of $\mu$ (i.e. $|\mu| (\mathbb R))$.
 
* For every right-continuous  function $f:\mathbb R\to  \mathbb R$ of bounded variation with $\lim_{x\to-\infty} f (x) = 0$ there is a unique signed measure $\mu$  such that $f=F_\mu$.
 
Moreover, the total variation of $f$ equals the total variation of the measure $\mu$ (cp. with [[Signed measure]] for the definition).
 
 
 
For  a proof see Section 4 of Chapter 4 in {{Cite|Co}}. Obvious  generalizations hold in the case of  different domains of definition.  
 
  
 +
'''Remark'''
 +
If we denote by $\mathcal{N}$ the null sets and consider the standard quotient measure algebra $(\mathcal{S}/\mathcal{N}, \mu)$, then any atom of such quotient measure algebra corresponds to an equivalence class of atoms of $\mu$.
 +
===Atomic measures===
 +
A measure $\mu$ is called ''atomic'' if there is a partition of $X$ into countably many elements of $\mathcal{A}$ which are either atoms or null sets. An atomic probability neasure is often called ''atomic distribution''. Examples of atomic distributions are the [[Discrete distribution|discrete distributions]].
 +
===Nonatomic measures===
 +
A measure $\mu$ is called ''nonatomic'' it has no atoms.
 
===Jordan decomposition===
 
===Jordan decomposition===
{{Anchor|Jordan decomposition}}
+
If $\mu$ is $\sigma$-finite, it is possible to decompose $\mu$ as $\mu_a+\mu_{na}$, where $\mu_a$ is an atomic measure and $\mu_{na}$ is a nonatomic measure. In case $\mu$ is a probability measure, this means that $\mu$ can be written as $p \mu_a + (1-p) \mu_{na}$, where $p\in [0,1]$, $\mu_a$ is an atomic probability measure and $\mu_{na}$ a nonatomic probability measure (see {{Cite|Fe}}), which is sometimes called a [[Continuous distribution|continuous distribution]]. This decomposition is sometimes called ''Jordan decomposition'', although several authors use this name in other contexts, see [[Jordan decomposition]].
A fundamental characterization of functions of bounded variation of one variable is due to Jordan.
+
===Measures in the euclidean space===
 
+
If $\mu$ is a $\sigma$-finite measure on the [[Borel set|Borel $\sigma$-algebra]] of $\mathbb R^n$, then it is easy to show that, for any atom $B$ of $\mu$ there is a point $x\in B$ with the property that $\mu (B) = \mu (\{x\})$. Thus such a measure is atomic if and only if it is the countable sum of [[Delta-function|Dirac deltas]], i.e. if there is an (at most) countable set $\{x_i\}\subset \mathbb R^n$ and an (at most) countable set $\{\alpha_i\}\subset ]0, \infty[$ with the property that
'''Theorem 3'''
 
Let  $I\subset \mathbb R$ be an interval. A function $f: I\to\mathbb R$ has  bounded variation if and only if it can be written as the difference  of  two bounded nondecreasing functions.
 
 
 
(Cp. with  Theorem 4  of Section 5.2 in {{Cite|Ro}}). Indeed it is possible to find  a  canonical representation of any function of bounded variation as  difference of nondecreasing functions.
 
 
 
'''Theorem 4'''
 
If  $f:[a,b] \to\mathbb R$ is a function of bounded variation then there  is  a pair of nondecreasing functions $f^+$ and $f^-$ such that $f= f^+-  f^-$ and $TV (f) = f^+ (b)-f^+ (a) + f^- (b)- f^- (a)$. The pair is  unique up to addition of a constant, i.e. if $g^+$ and $g^-$ is a second  pair with the same property, then $g^+-g^-=f^+-f^-\equiv {\rm const}$.
 
 
 
(Cp.  with Theorem 3 of Section 5.2 in {{Cite|Ro}}). The latter  representation of a function of bounded variation is also called  [[Jordan decomposition]].
 
====Negative and positive variations====
 
It is possible to define the negative and positive variations of $f$ in the following way.
 
 
 
'''Definition 5'''
 
Let $I\subset \mathbb R$ be an interval and $\Pi$ be as in '''Definition 1'''. The negative and positive variations of $f:I\to\mathbb R$ are then defined as
 
\[
 
TV^+ (f):= \sup \left\{ \sum_{i=1}^N \max \{(f(a_{i+1})-f(a_i)), 0\} : (a_1, \ldots, a_{N+1})\in\Pi\right\}\,
 
\]
 
\[
 
TV^- (f) := \sup \left\{ \sum_{i=1}^N \max \{-(f(a_{i+1})-f(a_i)), 0\} : (a_1, \ldots, a_{N+1})\in\Pi\right\}\, .
 
\]
 
 
 
If $f$ is a function of bounded variation on $[a,b]$ we can define $f^+ (x) = TV^+ (f|_{[a,x]})$ and $f^- (x) = TV^- (f|_{[a,x]})$. Then it turns out that, up to constants, these two functions give the Jordan decomposition of '''Theorem 4''', cp. with Lemma 3 in Section 2, Chapter 5 of {{Cite|Ro}}.
 
===Historical remark===
 
The variation of a function of one real variable was considered for the first time by C. Jordan in  {{Cite|Jo}} to study the  pointwise convergence of [[Fourier  series]], cp. with  [[Jordan  criterion]] and [[Function of bounded variation]].
 
==Wiener's and Young's generalizations==
 
One sometimes also considers classes $BV_\Phi ([a,b])$  defined as follows. Let $\Phi: [0, \infty[\to [0, \infty[$ be a continuous function with $\Phi (0)=0$ which increases monotonically. If $f:[a,b]\to \mathbb R$, we let $TV_{\phi} (f)$ be the least  upper bound of sums of the type
 
\[
 
\sum_{i=1}^N \Phi (|f (x_{i+1}- f(x_i)|)
 
\]
 
where  $a\leq x_1 < \ldots < x_{N+1}<b$ is an arbitrary family of points. The quantity $TV_\Phi (f)$ is called the $\Phi$-variation of $f$ on $[a,b]$. If $TV_\Phi (f)<\infty$ one says that $f$ has bounded $\Phi$-variation on  $[a,b]$, while the class  of such functions is denoted by $BV_\Phi ([a,b])$ (see {{Cite|Bar}}). If $\Phi (u)=u$, one obtains  Jordan's class $BV ([a,b])$, while if $\Phi (u)=u^p$, one obtains  Wiener's classes $BV_p ([a,b])$ (see {{Cite|Wi}}). The definition of the class $BV_\Phi ([a,b])$ was proposed by  L.C. Young in {{Cite|Yo}}.
 
 
 
If
 
\[
 
\limsup_{u\to 0^+} \frac{\Phi_1 (u)}{\Phi_2 (u)} < \infty
 
\]
 
then
 
\[
 
BV_{\Phi_2} ([a,b])\subset BV_{\Phi_1} ([a,b)]\, .
 
\]
 
In particular, on any interval $[a,b]$,
 
\[
 
BV_p ([a,b])\subset BV_q ([a,b]) \subset BV_{\exp (-u^{-\alpha})} ([a,b]) \subset
 
BV_{\exp (-u^{-\beta})} ([a,b])\, .
 
\]
 
for $1\leq p < q$ and $0<\alpha<\beta<\infty$, these being  proper inclusions.
 
 
 
==Functions of several variables==
 
===Historical remarks===
 
After  the introduction by Jordan of functions of bounded variations  of one  real variable, several authors attempted to generalize the  concept to  functions of more than one variable. The first attempt was  made by  Arzelà and Hardy in 1905, see [[Arzelà variation]] and [[Hardy  variation]], followed by Vitali, Fréchet, Tonelli and Pierpont, cp.  with  [[Vitali variation]], [[Fréchet variation]], [[Tonelli plane  variation]] and [[Pierpont variation]] (moreover, the definition of  Vitali variation was also considered independently by Lebesgue and De la  Vallée-Poussin). However, the point of view which became popular and  it  is nowadays accepted in the literature as most efficient  generalization  of the $1$-dimensional theory is due to De Giorgi and  Fichera (see  {{Cite|DG}} and {{Cite|Fi}}). Though with different  definitions, the  approaches by De Giorgi and Fichera are  equivalent  (and very close in spirit) to the ''distributional theory''  described  below. A promiment role in the further developing of the  theory was  also played by Fleming, Federer and Volpert. Moreover, Krickeberg and  Fleming showed, independently, that the current definition of functions  of bounded variation is indeed equivalent to a slight modification of  Tonelli's one {{Cite|To}}, proposed by Cesari {{Cite|Ce}}, cp. with the  section '''Tonelli-Cesari variation''' of [[Function of bounded variation]]. We refer to Section 3.12  of {{Cite|AFP}} for a thorough discussion of the topic.  
 
====Link to the theory of currents====
 
Functions  of bounded variation in $\mathbb R^n$ can be identified with  $n$-dimensional normal [[Current|currents]] in $\mathbb R^n$. This is the point  of view of Federer, {{Cite|Fe}}, which thus derives most of  the  conclusions of the theory of $BV$ functions as special cases of more  general theorems for normal currents,
 
 
 
===Definition===
 
Following {{Cite|EG}}:
 
 
 
'''Definition 6'''
 
Let $\Omega\subset \mathbb R^n$ be open. The total variation of $u\in L^1_{loc} (\Omega)$ is given by
 
\begin{equation}\label{e:diverg}
 
(u, \Omega) := \sup \left\{ \int_\Omega u\, {\rm div}\, \psi : \psi\in  C^\infty_c (\Omega, \mathbb R^n), \, \|\psi\|_{C^0}\leq 1\right\}\, .
 
\end{equation}
 
If $V(u, \Omega)< \infty$ then we say that $u$ has '''bounded variation'''. The space of functions $u\in L^1 (\Omega)$ which have bounded variation are denoted by $BV (\Omega)$.
 
 
 
As a consequence of the [[Radon-Nikodym theorem]] we then have
 
 
 
'''Prposition 7'''
 
A  function $u\in L^1_{loc} (\Omega)$, then $V(u, \Omega)<\infty$ if and only the [[Generalized derivative|distributional derivative]] of $f$ is a Radon measure $Du$. Moreover $V (u,\Omega) = |Du|  (\Omega)$, where $|Du|$ is the total variation measure of $Du$.
 
 
 
When $n=1$ and $\Omega=[a,b]$, then $V (u, [a,b])<\infty$ if and only if there exists a function $\tilde{u}$ such that
 
$u=\tilde{u}$ a.e. and $TV (\tilde{u})<\infty$. Moreover,
 
 
\[
 
\[
V (u, [a,b]) = \inf \{TV (\tilde{u}): \tilde{u}= t \quad\mbox{a.e.}\}\, .
+
\mu (A) = \sum_{x_i\in A} \alpha_i \qquad \mbox{for every Borel set $A$}.
 
\]
 
\]
(Cp. with [[Function of bounded variation]]).
+
===Sierpinski's theorem===
 
+
A nonatomic measure takes a continuum of values. This is a corollary of the following Theorem due to Sierpinski (see {{Cite|Si}}):
===Caccioppoli sets===
 
A special class of $BV_{loc}$ functions which play a fundamental role in  the  theory (and had also a pivotal role in its historical development)  is  the set of those $f\in BV$ which takes only the values $0$ and $1$  and  are, therefore, the indicator functions of a set.
 
 
 
'''Definition 8'''
 
Let  $\Omega\subset \mathbb R^n$ be an open set and $E\subset \Omega$ a  measurable set such that $ V({\bf 1}_E, \Omega)<\infty$. The $E$ is called a  ''Caccioppoli set'' or a ''set of finite perimeter'' and its  perimeter  in $\Omega$ is defined to be
 
\[
 
{\rm Per}\, (E, \Omega) = V ({\bf 1}_E, \Omega)\, .
 
\]
 
 
 
 
 
==Coarea formula==
 
An  important tool which allows often to reduce problems for $BV$  functions  to problems for Caccioppoli sets is the following generalization of the  [[Coarea formula]], first proved by Fleming and  Rishel in {{Cite|FR}}.
 
 
 
'''Theorem 29'''
 
For  any  open set $\Omega\subset \mathbb R^n$ and any $u\in L^1 (\Omega)$,  the  map $t\mapsto {\rm Per}\, (\{u>t\}, \Omega)$ is Lebesgue  measurable  and one has
 
\[
 
V (u,\Omega) = \int_{-\infty}^\infty {\rm Per}\, (\{u>t\}, \Omega)\, dt\,
 
\]
 
In    particular, if $u\in BV (\Omega)$, then $U_t:=\{u>t\}$ is a  Caccioppoli  set for a.e. $t$ and, for any Borel set  $B\subset \Omega$,
 
\[
 
|Du| (B) = \int_{-\infty}^\infty |D{\bf 1}_{U_t}| (B)\, dt \qquad\mbox{and}\qquad
 
Du (B) = \int_{-\infty}^\infty D{\bf 1}_{U_t} (B)\, dt\,
 
\]
 
(where the maps $t\mapsto |D{\bf 1}_{U_t}| (B)$ and $t\mapsto D{\bf 1}_{U_t} (B)$ are both Lebesgue measurable).
 
 
 
Cp.  with Theorem 3.40 in {{Cite|AFP}}.
 
===Banach indicatrix===
 
Let $f:[a,b]\to \mathbb R$. The [[Banach indicatrix]] $N (y,f)$ is then the cardinality of the set $\{f=y\}$. A special
 
case of the coarea formula, first proved by Banach in {{Cite|Ba}}, is the identity
 
\[
 
TV (f) = \int_{-\infty}^\infty N (f,y)\, dy
 
\]
 
which holds for every '''continuous''' function $f:[a,b]\to\mathbb R$.
 
 
 
===Vitushkin variation===
 
In {{Cite|Vi}} Vitushkin proposed a notion of variation for functions of several variables based on the [[Banach indicatrix|Banach indicatrix]]. Let $f: [0,1]^n\to \mathbb R$ be a Lebesgue measurable function and $k\in \{1, \ldots, n\}$. The variation $V_k (f)$ of order $k$ of $f$ on $[0,1]^n$ is the number
 
\[
 
\int_{-\infty}^\infty v_{k-1} (\{f=t\})\, dt
 
\]
 
where $v_{k-1} (E)$ denotes the [[Variation  of a set|Variation of the set]] $E$ of order $k-1$. The Vitushkin variation
 
enjoys the following properties:
 
 
 
a) $V_n (f+g)\leq V_n (f) + V_n (g)$.
 
 
 
b) If a  sequence of functions $f_j$ converges  uniformly to $f$ in $[0,1]^n$, then
 
\[
 
V_k (f) \leq \liminf_{j\to\infty}\; V_k (f_j)\, .
 
\]
 
 
 
c) If the  function $f$ is continuous and all its  variations are finite, then $f$ has a total  differential almost-everywhere.
 
 
 
d) If the function  $f$ is absolutely  continuous then
 
\[
 
V_n (f) = \int_{[0,1]^n} |\nabla f (x)|\, dx
 
\]
 
and hence coincides with the variation $V (f, [0,1]^n)$. However, the two quantities differ in general.
 
 
 
e) If the  function $f$ is continuous, it has bounded variations of all orders and can be extended periodically with period $1$ in all variables, then its Fourier series converges uniformly to it (Pringsheim's  theorem).
 
 
 
If the function $f$ has continuous  derivatives of all orders up to and including $n-k+1$, then its  variation of order $k$ is finite. The smoothness conditions  cannot be improved for any $k$.
 
 
 
 
 
 
 
  
 +
'''Theorem'''
 +
If $\mu$ is a nonatomic measure on a $\sigma$-algebra $\mathcal{A}$ and $A\in \mathcal{A}$ an element such that $\mu (A)>0$, then for every $b\in [0, \mu (B)]$ there is an element $B\in \mathcal{A}$ with $B\subset A$ and $\mu (B) = b$.
  
 +
==Comment==
 +
By a natural extension of meaning, the term atom is also used for an object of a category having no subobjects other than itself and the null subobject (cf. [[Null object of a category|Null object of a category]]).
  
 
==References==
 
==References==
 
{|
 
{|
 
|-
 
|-
|valign="top"|{{Ref|AFP}}||      L. Ambrosio, N. Fusco, D.  Pallara, "Functions of bounded  variations  and  free  discontinuity  problems". Oxford Mathematical  Monographs. The    Clarendon Press,  Oxford University Press, New York,  2000.      {{MR|1857292}}{{ZBL|0957.49001}}
+
|valign="top"|{{Ref|DS}}||      N. Dunford, J.T. Schwartz,  "Linear operators. General theory",    '''1''', Interscience (1958).  {{MR|0117523}} {{ZBL|0635.47001}}
|-
 
|valign="top"|{{Ref|Ba}}|| S. Banach,  "Sur les lignes rectifiables et les surfaces dont l'aire est finie"  ''Fund. Math.'' , '''7'''  (1925)  pp. 225–236.
 
|-
 
|valign="top"|{{Ref|Bar}}|| N.K. Bary,  "A treatise on trigonometric series" , Pergamon (1964).
 
|-
 
|valign="top"|{{Ref|Ca}}||  R. Caccioppoli, "Misura e integrazione sugli insiemei dimensionalmente  orientati I, II", Rend. Acc. Naz. Lincei (8), {\bf 12} (1952) pp. 3-11  and 137-146.
 
|-
 
|valign="top"|{{Ref|Co}}|| D. L. Cohn, "Measure theory". Birkhäuser, Boston 1993.
 
|-
 
|valign="top"|{{Ref|DG}}||  E. De Giorgi, "Su una teoria generale della misura $n-1$-dimensionale  in uno spazio a $r$ dimensioni", Ann. Mat. Pura Appl. (4), '''36'''  (1954) pp. 191-213.
 
|-
 
|valign="top"|{{Ref|EG}}||    L.C. Evans, R.F. Gariepy, "Measure theory and fine properties of    functions" Studies in Advanced Mathematics. CRC Press, Boca Raton, FL,    1992. {{MR|1158660}} {{ZBL|0804.2800}}
 
|-
 
|valign="top"|{{Ref|Fe}}||    H. Federer, "Geometric measure  theory". Volume 153 of Die  Grundlehren  der mathematischen  Wissenschaften. Springer-Verlag New  York Inc., New  York, 1969.  {{MR|0257325}} {{ZBL|0874.49001}}
 
|-
 
|valign="top"|{{Ref|Fi}}||  G. Fichera, "Lezioni sulle trasformazioni lineari", Istituto  matematico  dell'Università di Trieste, vol. I, 1954.
 
|-
 
|valign="top"|{{Ref|FR}}||  W. H. Fleming, R. Rishel, "An integral formula for total gradient  variation", Arch. Math., '''11''' (1960) pp. 218-222.
 
|-
 
|valign="top"|{{Ref|Jo}}|| C. Jordan,   "Sur la série de Fourier"  ''C.R. Acad. Sci. Paris'' , '''92'''  (1881) pp. 228–230
 
|-
 
|valign="top"|{{Ref|Ro}}|| H.L. Royden,  "Real analysis" , Macmillan (1969). {{MR|0151555}} {{ZBL|0197.03501}}
 
|-
 
|valign="top"|{{Ref|To}}||  L. Tonelli, "Sulle funzioni di due variabili generalmente a variazione  limitata", Ann. Scuola Norm. Sup. Pisa Cl. Sci. (2), '''5''' (1936)  pp.  315-320.
 
 
|-
 
|-
|valign="top"|{{Ref|Vi}}|| A.G. Vitushkin,   "On higher-dimensional variations", Moscow  (1955).
+
|valign="top"|{{Ref|Fe}}|| W. Feller, "An introduction to  probability theory and its  applications"|"An introduction to  probability theory and its  applications", '''2''', Wiley (1971).
 
|-
 
|-
|valign="top"|{{Ref|Wi}}|| N. Wiener,   "The quadratic variation of a function and its Fourier coefficients" ''J. Math. and Phys.'' , '''3'''  (1924) pp. 72–94.
+
|valign="top"|{{Ref|Lo}}|| M. Loève, "Probability theory", Princeton Univ. Press (1963). {{MR|0203748}} {{ZBL|0108.14202}}
 
|-
 
|-
|valign="top"|{{Ref|Yo}}|| L.C. Young,   "Sur une généralisation de la notion de variation de  puissance $p$ borneé au sens de  M. Wiener, et sur la convergence des series de Fourier" ''C.R. Acad.  Sci. Paris Sér. I Math.'' , '''204''' (1937) pp. 470–472
+
|valign="top"|{{Ref|Si}}|| W. Sierpinski, "Sur le fonctions d'enseble additives et continuoes", '''3''', Fund. Math. (1922) pp. 240-246.
 
|-
 
|-
 
|}
 
|}

Revision as of 10:29, 17 September 2012

2020 Mathematics Subject Classification: Primary: 03E04 [MSN][ZBL] in set theory

2020 Mathematics Subject Classification: Primary: 28A [MSN][ZBL] in measure theory

Set theory

A minimal non-zero element of a partially ordered set with a zero $0$, i.e. an element $p$ such that $0<x\leq p$ implies $x=p$.

Measure algebras

For the definition and relevance in the theory of measure algebras we refer to Measure algebra.

Classical measure theory

Definition

Let $\mu$ be a (nonnegative) measure on a $\sigma$-algebra $\mathcal{S}$ of subsets of a set $X$. An element $a\in \mathcal{S}$ is called an atom of $\mu$ if

  • $\mu (A)>0$;
  • For every $B\in \mathcal{S}$ with $B\subset A$ either $\mu (B)=0$ or $\mu (B)=\mu (A)$

(cp. with Section IV.9.8 of [DS] or [Fe]).

Remark If we denote by $\mathcal{N}$ the null sets and consider the standard quotient measure algebra $(\mathcal{S}/\mathcal{N}, \mu)$, then any atom of such quotient measure algebra corresponds to an equivalence class of atoms of $\mu$.

Atomic measures

A measure $\mu$ is called atomic if there is a partition of $X$ into countably many elements of $\mathcal{A}$ which are either atoms or null sets. An atomic probability neasure is often called atomic distribution. Examples of atomic distributions are the discrete distributions.

Nonatomic measures

A measure $\mu$ is called nonatomic it has no atoms.

Jordan decomposition

If $\mu$ is $\sigma$-finite, it is possible to decompose $\mu$ as $\mu_a+\mu_{na}$, where $\mu_a$ is an atomic measure and $\mu_{na}$ is a nonatomic measure. In case $\mu$ is a probability measure, this means that $\mu$ can be written as $p \mu_a + (1-p) \mu_{na}$, where $p\in [0,1]$, $\mu_a$ is an atomic probability measure and $\mu_{na}$ a nonatomic probability measure (see [Fe]), which is sometimes called a continuous distribution. This decomposition is sometimes called Jordan decomposition, although several authors use this name in other contexts, see Jordan decomposition.

Measures in the euclidean space

If $\mu$ is a $\sigma$-finite measure on the Borel $\sigma$-algebra of $\mathbb R^n$, then it is easy to show that, for any atom $B$ of $\mu$ there is a point $x\in B$ with the property that $\mu (B) = \mu (\{x\})$. Thus such a measure is atomic if and only if it is the countable sum of Dirac deltas, i.e. if there is an (at most) countable set $\{x_i\}\subset \mathbb R^n$ and an (at most) countable set $\{\alpha_i\}\subset ]0, \infty[$ with the property that \[ \mu (A) = \sum_{x_i\in A} \alpha_i \qquad \mbox{for every Borel set '"`UNIQ-MathJax45-QINU`"'}. \]

Sierpinski's theorem

A nonatomic measure takes a continuum of values. This is a corollary of the following Theorem due to Sierpinski (see [Si]):

Theorem If $\mu$ is a nonatomic measure on a $\sigma$-algebra $\mathcal{A}$ and $A\in \mathcal{A}$ an element such that $\mu (A)>0$, then for every $b\in [0, \mu (B)]$ there is an element $B\in \mathcal{A}$ with $B\subset A$ and $\mu (B) = b$.

Comment

By a natural extension of meaning, the term atom is also used for an object of a category having no subobjects other than itself and the null subobject (cf. Null object of a category).

References

[DS] N. Dunford, J.T. Schwartz, "Linear operators. General theory", 1, Interscience (1958). MR0117523 Zbl 0635.47001
[Fe] "An introduction to probability theory and its applications", 2, Wiley (1971).
[Lo] M. Loève, "Probability theory", Princeton Univ. Press (1963). MR0203748 Zbl 0108.14202
[Si] W. Sierpinski, "Sur le fonctions d'enseble additives et continuoes", 3, Fund. Math. (1922) pp. 240-246.
How to Cite This Entry:
Camillo.delellis/sandbox. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Camillo.delellis/sandbox&oldid=27940