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{{Short description|Property of some mathematical functions}}
{{Short description|Property of some mathematical functions}}
In [[mathematics]], '''subadditivity''' is a property of a function that states, roughly, that evaluating the function for the sum of two [[element (set)|elements]] of the [[Domain of a function|domain]] always returns something less than or equal to the sum of the function's values at each element. There are numerous examples of subadditive functions in various areas of mathematics, particularly [[norm (mathematics)|norms]] and [[square roots]]. [[Additive map]]s are special cases of subadditive functions.
In [[mathematics]], '''subadditivity''' is a property of a [[Function (mathematics)|function]] that states, roughly, that evaluating the function for the sum of two [[element (set)|elements]] of the [[Domain of a function|domain]] always returns something less than or equal to the sum of the function's values at each element. There are numerous examples of subadditive functions in various areas of mathematics, particularly [[norm (mathematics)|norms]] and [[square roots]]. [[Additive map]]s are special cases of subadditive functions.


==Definitions==
==Definitions==
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With that, all <math>a_{n_k}, a_{n_{k+1}}, ...</math> are forced down as in the previous proof. }}
With that, all <math>a_{n_k}, a_{n_{k+1}}, ...</math> are forced down as in the previous proof. }}


Moreover, the condition <math>a_{n+m}\le a_n + a_m</math> may be weakened as follows: <math>a_{n+m}\le a_n + a_m + \phi(n+m)</math> provided that <math>\phi</math> is an increasing function such that the integral <math display="inline">\int \phi(t) t^{-2} \, dt</math> converges (near the infinity).<ref>{{cite journal |last1=de Bruijn |first1=N.G. |last2=Erdös |first2=P. |title=Some linear and some quadratic recursion formulas. II |journal=Nederl. Akad. Wetensch. Proc. Ser. A |volume=55 |year=1952 |pages=152–163|doi=10.1016/S1385-7258(52)50021-0 }} (The same as ''Indagationes Math.'' '''14'''.) See also Steele 1997, Theorem 1.9.2.</ref>
Moreover, the condition <math>a_{n+m}\le a_n + a_m</math> may be weakened as follows: <math>a_{n+m}\le a_n + a_m + \phi(n+m)</math> provided that <math>\phi</math> is an [[Monotonic function|increasing function]] such that the integral <math display="inline">\int \phi(t) t^{-2} \, dt</math> converges (near the infinity).<ref>{{cite journal |last1=de Bruijn |first1=N.G. |last2=Erdös |first2=P. |title=Some linear and some quadratic recursion formulas. II |journal=Nederl. Akad. Wetensch. Proc. Ser. A |volume=55 |year=1952 |pages=152–163|doi=10.1016/S1385-7258(52)50021-0 }} (The same as ''Indagationes Math.'' '''14'''.) See also Steele 1997, Theorem 1.9.2.</ref>


There are also results that allow one to deduce the [[rate of convergence]] to the limit whose existence is stated in Fekete's lemma if some kind of both [[superadditive|superadditivity]] and subadditivity is present.<ref>Michael J. Steele. "Probability theory and combinatorial optimization". SIAM, Philadelphia (1997). {{isbn|0-89871-380-3}}.</ref><ref>{{cite video|author=Michael J. Steele|title=CBMS Lectures on Probability Theory and Combinatorial Optimization|publisher=University of Cambridge|year=2011|url=http://sms.cam.ac.uk/collection/1189351}}</ref>
There are also results that allow one to deduce the [[rate of convergence]] to the limit whose existence is stated in Fekete's lemma if some kind of both [[superadditive|superadditivity]] and subadditivity is present.<ref>Michael J. Steele. "Probability theory and combinatorial optimization". SIAM, Philadelphia (1997). {{isbn|0-89871-380-3}}.</ref><ref>{{cite video|author=Michael J. Steele|title=CBMS Lectures on Probability Theory and Combinatorial Optimization|publisher=University of Cambridge|year=2011|url=http://sms.cam.ac.uk/collection/1189351}}</ref>


Besides, analogues of Fekete's lemma have been proved for subadditive real maps (with additional assumptions) from finite subsets of an amenable group <ref>{{Cite journal| doi = 10.1007/BF02810577 | doi-access=free | issn = 0021-2172| volume = 115| issue = 1| pages = 1–24| last1 = Lindenstrauss| first1 = Elon| authorlink1=Elon Lindenstrauss | last2 = Weiss| first2 = Benjamin| authorlink2=Benjamin Weiss| title = Mean topological dimension| journal = [[Israel Journal of Mathematics]]| year = 2000| citeseerx = 10.1.1.30.3552}} Theorem 6.1</ref>
Additionally, analogues of Fekete's lemma have been proven for subadditive real maps (with additional assumptions) from finite subsets of an [[amenable group]],<ref>{{Cite journal| doi = 10.1007/BF02810577 | doi-access=free | issn = 0021-2172| volume = 115| issue = 1| pages = 1–24| last1 = Lindenstrauss| first1 = Elon| authorlink1=Elon Lindenstrauss | last2 = Weiss| first2 = Benjamin| authorlink2=Benjamin Weiss| title = Mean topological dimension| journal = [[Israel Journal of Mathematics]]| year = 2000| citeseerx = 10.1.1.30.3552}} Theorem 6.1</ref><ref>{{Cite journal| doi = 10.1007/BF02790325| doi-access=free | issn = 0021-7670| volume = 48| issue = 1| pages = 1–141| last1 = Ornstein| first1 = Donald S.|authorlink1=Donald Samuel Ornstein| last2 = Weiss| first2 = Benjamin| authorlink2=Benjamin Weiss| title = Entropy and isomorphism theorems for actions of amenable groups| journal = [[Journal d'Analyse Mathématique]]| year = 1987}}</ref><ref>{{Cite journal| doi = 10.1023/A:1009841100168| issn = 1385-0172| volume = 2| issue = 4| pages = 323–415| last = Gromov| first = Misha| title = Topological Invariants of Dynamical Systems and Spaces of Holomorphic Maps: I| journal = Mathematical Physics, Analysis and Geometry| year = 1999| bibcode = 1999MPAG....2..323G| s2cid = 117100302}}</ref> and further, of a cancellative left-amenable [[semigroup]].<ref>{{Cite journal | arxiv = 1209.6179| last1 = Ceccherini-Silberstein| first1 = Tullio| title = An analogue of Fekete's lemma for subadditive functions on cancellative amenable semigroups| journal = [[Journal d'Analyse Mathématique]]| volume = 124| pages = 59–81| last2 = Krieger| first2 = Fabrice| last3 = Coornaert| first3 = Michel| year = 2014| doi = 10.1007/s11854-014-0027-4 | doi-access=free}} Theorem 1.1</ref>
<ref>{{Cite journal| doi = 10.1007/BF02790325| doi-access=free | issn = 0021-7670| volume = 48| issue = 1| pages = 1–141| last1 = Ornstein| first1 = Donald S.|authorlink1=Donald Samuel Ornstein| last2 = Weiss| first2 = Benjamin| authorlink2=Benjamin Weiss| title = Entropy and isomorphism theorems for actions of amenable groups| journal = [[Journal d'Analyse Mathématique]]| year = 1987}}</ref>
,<ref>{{Cite journal| doi = 10.1023/A:1009841100168| issn = 1385-0172| volume = 2| issue = 4| pages = 323–415| last = Gromov| first = Misha| title = Topological Invariants of Dynamical Systems and Spaces of Holomorphic Maps: I| journal = Mathematical Physics, Analysis and Geometry| year = 1999| bibcode = 1999MPAG....2..323G| s2cid = 117100302}}</ref>
and further, of a cancellative left-amenable semigroup.<ref>{{Cite journal | arxiv = 1209.6179| last1 = Ceccherini-Silberstein| first1 = Tullio| title = An analogue of Fekete's lemma for subadditive functions on cancellative amenable semigroups| journal = [[Journal d'Analyse Mathématique]]| volume = 124| pages = 59–81| last2 = Krieger| first2 = Fabrice| last3 = Coornaert| first3 = Michel| year = 2014| doi = 10.1007/s11854-014-0027-4 | doi-access=free}} Theorem 1.1</ref>


===Functions===
===Functions===
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[[Entropy]] plays a fundamental role in [[information theory]] and [[statistical physics]], as well as in [[quantum mechanics]] in a generalized formulation due to [[von Neumann entropy|von Neumann]].
[[Entropy]] plays a fundamental role in [[information theory]] and [[statistical physics]], as well as in [[quantum mechanics]] in a generalized formulation due to [[von Neumann entropy|von Neumann]].
Entropy appears always as a subadditive quantity in all of its formulations, meaning the entropy of a supersystem or a set union of random variables is always less or equal than the sum of the entropies of its individual components.
Entropy appears always as a subadditive quantity in all of its formulations, meaning the entropy of a supersystem or a [[set union]] of random variables is always less or equal than the sum of the entropies of its individual components.
Additionally, entropy in physics satisfies several more strict inequalities such as the Strong Subadditivity of Entropy in classical statistical mechanics and its [[Strong subadditivity of quantum entropy|quantum analog]].
Additionally, entropy in physics satisfies several more strict inequalities such as the Strong Subadditivity of Entropy in classical statistical mechanics and its [[Strong subadditivity of quantum entropy|quantum analog]].


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===Finance===
===Finance===
Subadditivity is one of the desirable properties of [[coherent risk measure]]s in [[risk management]].<ref name="Rau-Bredow">{{Cite journal | doi = 10.3390/risks7030091| title = Bigger Is Not Always Safer: A Critical Analysis of the Subadditivity Assumption for Coherent Risk Measures| year = 2019| last1 = Rau-Bredow | first1 = H. | journal = Risks| volume = 7| issue = 3|pages = 91| doi-access = free| hdl = 10419/257929| hdl-access = free}}</ref> The economic intuition behind risk measure subadditivity is that a portfolio risk exposure should, at worst, simply equal the sum of the risk exposures of the individual positions that compose the portfolio. The lack of subadditivity is one of the main critiques of [[Value at risk|VaR]] models which do not rely on the assumption of [[Normal distribution|normality]] of risk factors. The Gaussian VaR ensures subadditivity: for example, the Gaussian VaR of a two unitary long positions portfolio <math> V </math> at the confidence level <math> 1-p </math> is, assuming that the mean portfolio value variation is zero and the VaR is defined as a negative loss,
Subadditivity is one of the desirable properties of [[coherent risk measure]]s in [[risk management]].<ref name="Rau-Bredow">{{Cite journal | doi = 10.3390/risks7030091| title = Bigger Is Not Always Safer: A Critical Analysis of the Subadditivity Assumption for Coherent Risk Measures| year = 2019| last1 = Rau-Bredow | first1 = H. | journal = Risks| volume = 7| issue = 3|pages = 91| doi-access = free| hdl = 10419/257929| hdl-access = free}}</ref> The economic intuition behind risk measure subadditivity is that a [[Portfolio (finance)|portfolio]] risk exposure should, at worst, simply equal the sum of the risk exposures of the individual positions that compose the portfolio. The lack of subadditivity is one of the main critiques of [[Value at risk|VaR]] models which do not rely on the assumption of [[Normal distribution|normality]] of risk factors. The Gaussian VaR ensures subadditivity: for example, the Gaussian VaR of a two unitary long positions portfolio <math> V </math> at the confidence level <math> 1-p </math> is, assuming that the mean portfolio value variation is zero and the VaR is defined as a negative loss,
<math display="block"> \text{VaR}_p \equiv z_{p}\sigma_{\Delta V} =  z_{p}\sqrt{\sigma_x^2+\sigma_y^2+2\rho_{xy}\sigma_x \sigma_y} </math>
<math display="block"> \text{VaR}_p \equiv z_{p}\sigma_{\Delta V} =  z_{p}\sqrt{\sigma_x^2+\sigma_y^2+2\rho_{xy}\sigma_x \sigma_y} </math>
where <math> z_p </math> is the inverse of the normal [[cumulative distribution function]] at probability level <math> p </math>, <math> \sigma_x^2,\sigma_y^2 </math> are the individual positions returns variances and <math> \rho_{xy} </math> is the [[Pearson correlation coefficient|linear correlation measure]] between the two individual positions returns. Since [[variance]] is always positive,
where <math> z_p </math> is the inverse of the normal [[cumulative distribution function]] at probability level <math> p </math>, <math> \sigma_x^2,\sigma_y^2 </math> are the individual positions returns variances and <math> \rho_{xy} </math> is the [[Pearson correlation coefficient|linear correlation measure]] between the two individual positions returns. Since [[variance]] is always positive,
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===Thermodynamics===
===Thermodynamics===
Subadditivity occurs in the thermodynamic properties of non-[[ideal solution]]s and mixtures like the excess [[molar volume]] and [[heat of mixing]] or excess enthalpy.
Subadditivity occurs in the thermodynamic properties of non-[[ideal solution]]s and mixtures like the excess [[molar volume]] and [[heat of mixing]] or excess [[enthalpy]].


===Combinatorics on words===
===Combinatorics on words===
A factorial [[Formal language|language]] <math>L</math> is one where if a [[String (computer science)|word]] is in <math>L</math>, then all [[Substring|factors]] of that word are also in <math>L</math>.  In [[combinatorics on words]], a common problem is to determine the number <math>A(n)</math> of length-<math>n</math> words in a factorial language.  Clearly <math>A(m+n) \leq A(m)A(n)</math>, so <math>\log A(n)</math> is subadditive, and hence Fekete's lemma can be used to estimate the growth of <math>A(n)</math>.<ref name=shur>{{cite journal|last=Shur|first=Arseny|title=Growth properties of power-free languages|journal=Computer Science Review|date=2012|volume=6|issue=5–6|pages=187–208|doi=10.1016/j.cosrev.2012.09.001}}</ref>
A factorial [[Formal language|language]] <math>L</math> is one where if a [[String (computer science)|word]] is in <math>L</math>, then all [[Substring|factors]] of that word are also in <math>L</math>.  In [[combinatorics on words]], a common problem is to determine the number <math>A(n)</math> of length-<math>n</math> words in a factorial language.  Clearly <math>A(m+n) \leq A(m)A(n)</math>, so <math>\log A(n)</math> is subadditive, and hence Fekete's lemma can be used to estimate the growth of <math>A(n)</math>.<ref name=shur>{{cite journal|last=Shur|first=Arseny|title=Growth properties of power-free languages|journal=Computer Science Review|date=2012|volume=6|issue=5–6|pages=187–208|doi=10.1016/j.cosrev.2012.09.001}}</ref>


For every <math>k \geq 1</math>, sample two strings of length <math>n</math> uniformly at random on the alphabet <math>1, 2, ..., k</math>. The expected length of the [[longest common subsequence]] is a ''super''-additive function of <math>n</math>, and thus there exists a number <math>\gamma_k \geq 0</math>, such that the expected length grows as <math>\sim \gamma_k n</math>. By checking the case with <math>n=1</math>, we easily have <math>\frac 1k < \gamma_k \leq 1</math>. The exact value of even <math>\gamma_2</math>, however, is only known to be between 0.788 and 0.827.<ref>{{Cite journal |last=Lueker |first=George S. |date=May 2009 |title=Improved bounds on the average length of longest common subsequences |url=https://dl.acm.org/doi/10.1145/1516512.1516519 |journal=Journal of the ACM |language=en |volume=56 |issue=3 |pages=1–38 |doi=10.1145/1516512.1516519 |s2cid=7232681 |issn=0004-5411|url-access=subscription }}</ref>
For every <math>k \geq 1</math>, sample two strings of length <math>n</math> uniformly at random on the alphabet <math>1, 2, ..., k</math>. The expected length of the [[longest common subsequence]] is a ''super''-additive function of <math>n</math>, and thus there exists a number <math>\gamma_k \geq 0</math>, such that the expected length grows as <math>\sim \gamma_k n</math>. By checking the case with <math>n=1</math>, we have <math>\frac 1k < \gamma_k \leq 1</math>. The exact value of even <math>\gamma_2</math>, however, is only known to be between 0.788 and 0.827.<ref>{{Cite journal |last=Lueker |first=George S. |date=May 2009 |title=Improved bounds on the average length of longest common subsequences |url=https://dl.acm.org/doi/10.1145/1516512.1516519 |journal=Journal of the ACM |language=en |volume=56 |issue=3 |pages=1–38 |doi=10.1145/1516512.1516519 |s2cid=7232681 |issn=0004-5411|url-access=subscription }}</ref>


== See also ==
== See also ==

Latest revision as of 03:33, 1 July 2025

Template:Short description In mathematics, subadditivity is a property of a function that states, roughly, that evaluating the function for the sum of two elements of the domain always returns something less than or equal to the sum of the function's values at each element. There are numerous examples of subadditive functions in various areas of mathematics, particularly norms and square roots. Additive maps are special cases of subadditive functions.

Definitions

A subadditive function is a function f:AB, having a domain A and an ordered codomain B that are both closed under addition, with the following property: x,yA,f(x+y)f(x)+f(y).

An example is the square root function, having the non-negative real numbers as domain and codomain: since x,y0 we have: x+yx+y.

A sequence {an}n1 is called subadditive if it satisfies the inequality an+man+am for all m and n. This is a special case of subadditive function, if a sequence is interpreted as a function on the set of natural numbers.

Note that while a concave sequence is subadditive, the converse is false. For example, arbitrarily assign a1,a2,... with values in [0.5,1]; then the sequence is subadditive but not concave.

Properties

Sequences

Script error: No such module "anchor".A useful result pertaining to subadditive sequences is the following lemma due to Michael Fekete.[1]

Template:Math theorem

Template:Math proof

The analogue of Fekete's lemma holds for superadditive sequences as well, that is: an+man+am. (The limit then may be positive infinity: consider the sequence an=logn!.)

There are extensions of Fekete's lemma that do not require the inequality an+man+am to hold for all m and n, but only for m and n such that 12mn2.

Template:Math proof

Moreover, the condition an+man+am may be weakened as follows: an+man+am+ϕ(n+m) provided that ϕ is an increasing function such that the integral ϕ(t)t2dt converges (near the infinity).[2]

There are also results that allow one to deduce the rate of convergence to the limit whose existence is stated in Fekete's lemma if some kind of both superadditivity and subadditivity is present.[3][4]

Additionally, analogues of Fekete's lemma have been proven for subadditive real maps (with additional assumptions) from finite subsets of an amenable group,[5][6][7] and further, of a cancellative left-amenable semigroup.[8]

Functions

Template:Math theorem

If f is a subadditive function, and if 0 is in its domain, then f(0) ≥ 0. To see this, take the inequality at the top. f(x)f(x+y)f(y). Hence f(0)f(0+y)f(y)=0

A concave function f:[0,) with f(0)0 is also subadditive. To see this, one first observes that f(x)yx+yf(0)+xx+yf(x+y). Then looking at the sum of this bound for f(x) and f(y), will finally verify that f is subadditive.[9]

The negative of a subadditive function is superadditive.


Examples in various domains

Entropy

Entropy plays a fundamental role in information theory and statistical physics, as well as in quantum mechanics in a generalized formulation due to von Neumann. Entropy appears always as a subadditive quantity in all of its formulations, meaning the entropy of a supersystem or a set union of random variables is always less or equal than the sum of the entropies of its individual components. Additionally, entropy in physics satisfies several more strict inequalities such as the Strong Subadditivity of Entropy in classical statistical mechanics and its quantum analog.

Economics

Subadditivity is an essential property of some particular cost functions. It is, generally, a necessary and sufficient condition for the verification of a natural monopoly. It implies that production from only one firm is socially less expensive (in terms of average costs) than production of a fraction of the original quantity by an equal number of firms.

Economies of scale are represented by subadditive average cost functions.

Except in the case of complementary goods, the price of goods (as a function of quantity) must be subadditive. Otherwise, if the sum of the cost of two items is cheaper than the cost of the bundle of two of them together, then nobody would ever buy the bundle, effectively causing the price of the bundle to "become" the sum of the prices of the two separate items. Thus proving that it is not a sufficient condition for a natural monopoly; since the unit of exchange may not be the actual cost of an item. This situation is familiar to everyone in the political arena where some minority asserts that the loss of some particular freedom at some particular level of government means that many governments are better; whereas the majority assert that there is some other correct unit of cost.Script error: No such module "Unsubst".

Finance

Subadditivity is one of the desirable properties of coherent risk measures in risk management.[10] The economic intuition behind risk measure subadditivity is that a portfolio risk exposure should, at worst, simply equal the sum of the risk exposures of the individual positions that compose the portfolio. The lack of subadditivity is one of the main critiques of VaR models which do not rely on the assumption of normality of risk factors. The Gaussian VaR ensures subadditivity: for example, the Gaussian VaR of a two unitary long positions portfolio V at the confidence level 1p is, assuming that the mean portfolio value variation is zero and the VaR is defined as a negative loss, VaRpzpσΔV=zpσx2+σy2+2ρxyσxσy where zp is the inverse of the normal cumulative distribution function at probability level p, σx2,σy2 are the individual positions returns variances and ρxy is the linear correlation measure between the two individual positions returns. Since variance is always positive, σx2+σy2+2ρxyσxσyσx+σy Thus the Gaussian VaR is subadditive for any value of ρxy[1,1] and, in particular, it equals the sum of the individual risk exposures when ρxy=1 which is the case of no diversification effects on portfolio risk.

Thermodynamics

Subadditivity occurs in the thermodynamic properties of non-ideal solutions and mixtures like the excess molar volume and heat of mixing or excess enthalpy.

Combinatorics on words

A factorial language L is one where if a word is in L, then all factors of that word are also in L. In combinatorics on words, a common problem is to determine the number A(n) of length-n words in a factorial language. Clearly A(m+n)A(m)A(n), so logA(n) is subadditive, and hence Fekete's lemma can be used to estimate the growth of A(n).[11]

For every k1, sample two strings of length n uniformly at random on the alphabet 1,2,...,k. The expected length of the longest common subsequence is a super-additive function of n, and thus there exists a number γk0, such that the expected length grows as γkn. By checking the case with n=1, we have 1k<γk1. The exact value of even γ2, however, is only known to be between 0.788 and 0.827.[12]

See also

Notes

  1. Script error: No such module "Citation/CS1".
  2. Script error: No such module "Citation/CS1". (The same as Indagationes Math. 14.) See also Steele 1997, Theorem 1.9.2.
  3. Michael J. Steele. "Probability theory and combinatorial optimization". SIAM, Philadelphia (1997). Template:Isbn.
  4. Template:Cite video
  5. Script error: No such module "Citation/CS1". Theorem 6.1
  6. Script error: No such module "Citation/CS1".
  7. Script error: No such module "Citation/CS1".
  8. Script error: No such module "Citation/CS1". Theorem 1.1
  9. Script error: No such module "citation/CS1"., p.314,12.25
  10. Script error: No such module "Citation/CS1".
  11. Script error: No such module "Citation/CS1".
  12. Script error: No such module "Citation/CS1".

References

External links

This article incorporates material from subadditivity on PlanetMath, which is licensed under the Creative Commons Attribution/Share-Alike License.