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{{distinguish|Pfaffian function|Pfaffian system}}
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In [[mathematics]], the [[determinant]] of a [[skew-symmetric matrix]] can always be written as the square of a [[polynomial]] in the matrix entries. This polynomial is called the '''Pfaffian''' of the matrix. The term ''Pfaffian'' was introduced by {{harvs|txt|authorlink=Arthur Cayley|last=Cayley|year=1852}} who named them after [[Johann Friedrich Pfaff]].  The Pfaffian is nonvanishing only for 2''n'' &times; 2''n'' skew-symmetric matrices, in which case it is a polynomial of degree ''n''.
 
Explicitly, for a skew-symmetric matrix '''A''',
:<math> \operatorname{pf(A)}^2=\det(A),</math>
which was first proved by [[Thomas Muir (mathematician)|Thomas Muir]] in 1882 {{harv|Muir|1882}}.
 
The fact that the determinant of any skew symmetric matrix is the square of a polynomial can be shown by writing the matrix as a block matrix,
then using induction and examining the [[Schur complement]], which is skew symmetric as well.
<ref>Ledermann, W. "A note on skew-symmetric determinants"</ref>
 
==Examples==
 
:<math>A=\begin{bmatrix}  0 & a \\ -a & 0  \end{bmatrix}.\qquad\operatorname{pf(A)}=a.</math>
 
:<math>B=\begin{bmatrix}  0    & a & b \\ -a & 0        & c  \\  -b      &  -c      & 0 \end{bmatrix}.\qquad\operatorname{pf(B)}=0.</math>
 
(3 is odd, so Pfaffian of B is 0)
 
:<math>\operatorname{pf}\begin{bmatrix}    0    & a & b & c \\ -a & 0        & d & e  \\  -b      &  -d      & 0& f    \\-c &  -e      & -f & 0 \end{bmatrix}=af-be+dc.</math>
 
The Pfaffian of a 2''n'' &times; 2''n'' skew-symmetric tridiagonal matrix is given as
:<math>\operatorname{pf}\begin{bmatrix}
0 & a_1\\ -a_1 & 0 & b_1\\  0 & -b_1 &0 & a_2 \\ 0 & 0 & -a_2 &\ddots&\ddots\\
&&&\ddots&&b_{n-1}\\
&&&&-b_{n-1}&0&a_n\\
&&&&&-a_n&0
\end{bmatrix} = a_1 a_2\cdots a_n.</math>
which contains the important case of a 2''n'' &times; 2''n'' skew-symmetric matrix with 2 &times; 2 blocks on the
diagonal:
:<math>\operatorname{pf}\begin{bmatrix}
\begin{matrix} 0 & \lambda_1\\ -\lambda_1 & 0\end{matrix} &  0 & \cdots & 0 \\
0 & \begin{matrix}0 & \lambda_2\\ -\lambda_2 & 0\end{matrix} &  & 0 \\
\vdots &  & \ddots & \vdots \\
0 & 0 & \cdots & \begin{matrix}0 & \lambda_n\\ -\lambda_n & 0\end{matrix}
\end{bmatrix} = \lambda_1\lambda_2\cdots\lambda_n.</math>
(Note that any skew-symmetric matrix can be reduced to this form, see [[Skew-symmetric_matrix#Spectral_theory|Spectral theory of a skew-symmetric matrix]])
 
==Formal definition==
 
Let ''A'' = {''a''<sub>''i,j''</sub>} be a 2''n'' × 2''n'' skew-symmetric matrix. The Pfaffian of ''A'' is defined by the equation
 
:<math>\operatorname{pf}(A) = \frac{1}{2^n n!}\sum_{\sigma\in S_{2n}}\operatorname{sgn}(\sigma)\prod_{i=1}^{n}a_{\sigma(2i-1),\sigma(2i)}</math>
 
where ''S''<sub>2''n''</sub> is the [[symmetric group]] and sgn(σ) is the [[signature (permutation)|signature]] of σ.
 
One can make use of the skew-symmetry of ''A'' to avoid summing over all possible [[permutation]]s. Let Π be the set of all [[partition of a set|partition]]s of {1, 2, …, 2''n''} into pairs without regard to order. There are (2''n'' &minus; 1)[[double factorial|!!]] such partitions. An element α ∈ Π can be written as
 
:<math>\alpha=\{(i_1,j_1),(i_2,j_2),\cdots,(i_n,j_n)\}</math>
 
with ''i''<sub>''k''</sub> < ''j''<sub>''k''</sub> and <math>i_1 < i_2 < \cdots < i_n</math>. Let
 
:<math>\pi=\begin{bmatrix} 1 & 2 & 3 & 4 & \cdots & 2n \\ i_1 & j_1 & i_2 & j_2 & \cdots & j_{n} \end{bmatrix}</math>
 
be the corresponding permutation. Given a partition α as above, define
 
:<math> A_\alpha =\operatorname{sgn}(\pi)a_{i_1,j_1}a_{i_2,j_2}\cdots a_{i_n,j_n}.</math>
 
The Pfaffian of ''A'' is then given by
 
:<math>\operatorname{pf}(A)=\sum_{\alpha\in\Pi} A_\alpha.</math>
 
The Pfaffian of a ''n''&times;''n'' skew-symmetric matrix for ''n'' odd is defined to be zero, as the determinant of an odd skew-symmetric matrix is zero, since for a skew-symmetric matrix, <math>\det\,A = \det\,A^\text{T} = \det\left(-A\right) = (-1)^n \det\,A</math>, and for ''n'' odd, this implies <math>\det\,A = 0</math>.
 
===Recursive definition===
 
By convention, the Pfaffian of the 0×0 matrix is equal to one.  The Pfaffian of a skew-symmetric 2''n''×2''n'' matrix ''A'' with ''n''>0 can be computed recursively as
 
:<math>\operatorname{pf}(A)=\sum_{i=2}^{2n}(-1)^{i}a_{1i}\operatorname{pf}(A_{\hat{1}\hat{i}}),</math>
 
where <math>A_{\hat{1}\hat{i}}</math> denotes the matrix ''A'' with both the first and ''i''-th rows and columns removed.
 
===Alternative definitions===
* One can associate to any skew-symmetric 2''n''×2''n'' matrix ''A'' ={''a''<sub>''ij''</sub>} a [[exterior algebra|bivector]]
 
:<math>\omega=\sum_{i<j} a_{ij}\;e^i\wedge e^j.</math>
 
where {''e''<sup>1</sup>, ''e''<sup>2</sup>, …, ''e''<sup>2''n''</sup>} is the standard basis of '''R'''<sup>2n</sup>. The Pfaffian is then defined by the equation
 
:<math>\frac{1}{n!}\omega^n = \operatorname{pf}(A)\;e^1\wedge e^2\wedge\cdots\wedge e^{2n},</math>
here ω<sup>''n''</sup> denotes the [[wedge product]] of ''n'' copies of ω.
 
==Identities==
 
For a 2''n'' &times; 2''n'' skew-symmetric matrix ''A''
:<math>\operatorname{pf}(A^\text{T}) = (-1)^n\operatorname{pf}(A).</math>
:<math>\operatorname{pf}(\lambda A) = \lambda^n \operatorname{pf}(A).</math>
:<math>\operatorname{pf}(A)^2 = \det(A).</math>
For an arbitrary 2''n'' &times; 2''n'' matrix ''B'',
:<math>\operatorname{pf}(BAB^\text{T})= \det(B)\operatorname{pf}(A).</math>
Substituting in this equation ''B = A<sup>m</sup>'', one gets for all integer ''m''
:<math>\operatorname{pf}(A^{2m+1})= (-1)^{nm}\operatorname{pf}(A)^{2m+1}.</math>
For a block-diagonal matrix
::<math>A_1\oplus A_2=\begin{bmatrix}  A_1 & 0 \\ 0 & A_2 \end{bmatrix},</math>
:<math>\operatorname{pf}(A_1\oplus A_2) =\operatorname{pf}(A_1)\operatorname{pf}(A_2).</math>
For an arbitrary ''n'' &times; ''n'' matrix ''M'':
:<math>\operatorname{pf}\begin{bmatrix}  0 & M \\ -M^\text{T} & 0  \end{bmatrix} =
(-1)^{n(n-1)/2}\det M.</math>
If ''A'' depends on some variable ''x''<sub>''i''</sub>, then the gradient of a Pfaffian is given by
:<math>\frac{1}{\operatorname{pf}(A)}\frac{\partial\operatorname{pf}(A)}{\partial x_i}=\frac{1}{2}\operatorname{tr}\left(A^{-1}\frac{\partial A}{\partial x_i}\right),</math>
and the [[Hessian matrix|Hessian]] of a Pfaffian is given by
:<math>\frac{1}{\operatorname{pf}(A)}\frac{\partial^2\operatorname{pf}(A)}{\partial x_i\partial x_j}=\frac{1}{2}\operatorname{tr}\left(A^{-1}\frac{\partial^2 A}{\partial x_i\partial x_j}\right)-\frac{1}{2}\operatorname{tr}\left(A^{-1}\frac{\partial A}{\partial x_i}A^{-1}\frac{\partial A}{\partial x_j}\right)+\frac{1}{4}\operatorname{tr}\left(A^{-1}\frac{\partial A}{\partial x_i}\right)\operatorname{tr}\left(A^{-1}\frac{\partial A}{\partial x_j}\right).</math>
 
==Properties==
Pfaffians have the following properties, which are similar to those of determinants.
* Multiplication of a row and a column by a constant is equivalent to multiplication of Pfaffian by the same constant.
* Simultaneous interchange of two different rows and corresponding columns changes the sign of Pfaffian.
* A multiple of a row and corresponding column added to another row and corresponding column does not change the value of Pfaffian.
These properties can be derived from the identity <math>\operatorname{pf}(BAB^\text{T})=\det(B)\operatorname{pf}(A)</math>.
 
==Applications==
*There exist programs for the numerical computation of the Pfaffian on various platforms (Python, Matlab, Mathematica) {{harv|Wimmer|2012}}.
 
*The Pfaffian is an [[invariant polynomial]] of a skew-symmetric matrix under a proper [[orthogonal group|orthogonal]] change of basis. As such, it is important in the theory of [[characteristic class]]es. In particular, it can be used to define the [[Euler class]] of a [[Riemannian manifold]] which is used in the [[generalized Gauss–Bonnet theorem]].
 
*The number of [[perfect matching]]s in a [[planar graph]] is given by a Pfaffian, hence is polynomial time computable via the [[FKT algorithm]]. This is surprising given that for general graphs, the problem is very difficult (so called [[Sharp-P-complete|#P-complete]]). This result is used to calculate  the number of  [[domino tiling]]s of a rectangle, the [[partition function (statistical mechanics)|partition function]] of [[Ising model]]s in physics, or of [[Markov random fields]] in [[machine learning]] ({{harvnb|Globerson|Jaakkola|2007}}; {{harvnb|Schraudolph|Kamenetsky|2009}}), where the underlying graph is planar. It is also used to derive efficient algorithms for some otherwise seemingly intractable problems, including the efficient simulation of certain types of [[restricted quantum computation]]. Read [[Holographic algorithm]] for more information.
 
==See also==
 
*[[Determinant]]
*[[Dimer model]]
*[[Polyomino]]
*[[Statistical mechanics]]
 
== References ==
{{Reflist}}
 
*{{Cite journal | last1=Cayley | first1=Arthur | author1-link=Arthur Cayley | title=On the theory of permutants | url=http://www.archive.org/stream/collectedmathema02cayluoft#page/16/mode/2up | year=1852 | journal=Cambridge and Dublin Mathematical Journal  | volume=VII | pages=40–51 | ref=harv | postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}} Reprinted in Collected mathematical papers, volume 2.
* {{cite journal | ref=harv
| title = The statistics of dimers on a lattice. I. The number of dimer arrangements on a quadratic lattice
| journal = Physica
| volume = 27 | issue = 12 | year = 1961 | pages = 1209–1225
| first = P. W. | last = Kasteleyn
| authorlink = Pieter_Kasteleyn
| doi = 10.1016/0031-8914(61)90063-5}}
* {{cite arXiv | first=James | last=Propp | year = 2004 | title="Lambda-determinants and domino-tilings" | eprint=math/0406301 | eprint=math.CO/0406301 | ref=harv | postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite arxiv to end in a ".", as necessary. -->{{inconsistent cite arxivs}}}}.
* {{Cite journal | first=Amir | last=Globerson | first2=Tommi | last2=Jaakkola | year = 2007 | contribution= ''Approximate inference using planar graph decomposition'' | contribution-url= http://books.nips.cc/papers/files/nips19/NIPS2006_0703.pdf | title=''Advances in Neural Information Processing Systems 19''  | url=http://books.nips.cc/ | publisher=MIT Press | ref=harv | postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}.
* {{Cite journal | first=Nicol | last=Schraudolph | first2=Dmitry | last2=Kamenetsky | year = 2009 | contribution= ''Efficient exact inference in planar Ising models'' | contribution-url= http://books.nips.cc/papers/files/nips21/NIPS2008_0401.pdf | title=''Advances in Neural Information Processing Systems 21'' | url=http://books.nips.cc/ | publisher=MIT Press | ref=harv | postscript=<!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}.
* {{cite journal | ref=harv | journal=The Games and Puzzles Journal | volume=2 | year=1996 | pages=204–5 | first1=G.P. |last=Jeliss | first2=Robin J. | last2=Chapman | title=Dominizing the Chessboard | issue=14}}
* {{cite journal | ref=harv | title=Domino Tilings and Products of Fibonacci and Pell numbers| journal=Journal of Integer Sequences | volume=5 | year=2002 | first=James A. | last=Sellers | issue=1 |page=02.1.2 | url=http://www.cs.uwaterloo.ca/journals/JIS/VOL5/Sellers/sellers4.html }}
* {{cite book | ref=harv | title=[[The Penguin Dictionary of Curious and Interesting Numbers]] | edition=revised | year=1997 | isbn=0-14-026149-4 |  first=David | last=Wells | page=182 }}
* {{cite book | ref=harv | title=A Treatise on the Theory of Determinants | year=1882 | publisher=Macmillan and Co. | first=Thomas | last=Muir}} [http://books.google.com/books?id=pk4DAAAAQAAJ&dq=thomas+muir+treatise+on+the+theory+of+determinant&psp=1 ''Online'']
* {{cite journal | ref=harv | title=Skew-Symmetric Determinants | journal=The American Mathematical Monthly | volume=61 | year=1954 | page=116 | first=S. | last=Parameswaran | jstor=2307800 | issue=2}}
* {{cite journal| ref=harv |title=Efficient numerical computation of the Pfaffian for dense and banded skew-symmetric matrices|journal=[[ACM Trans. Math. Software]]|volume=38|page=30|year=2012 | first=M. | last=Wimmer | arxiv=1102.3440}}
 
==External links==
* [http://planetmath.org/encyclopedia/Pfaffian.html Pfaffian at PlanetMath.org]
* T. Jones, [http://www.physics.drexel.edu/~tim/open/pfaff/pfaff.pdf  ''The Pfaffian and the Wedge Product'' (a demonstration of the proof of the Pfaffian/determinant relationship)]
* R. Kenyon and [[Andrei Okounkov|A. Okounkov]], [http://www.ams.org/notices/200503/what-is.pdf ''What is ... a dimer?'']
* {{OEIS|id=A004003}}
* W. Ledermann "A note on skew-symmetric determinants" http://www.researchgate.net/publication/231827602_A_note_on_skew-symmetric_determinants
 
[[Category:Determinants]]
[[Category:Multilinear algebra]]

Latest revision as of 03:41, 10 October 2014

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Boots came into existence all through Earth War I as pilots wore these fleece - lined traveling these boots popularly recognized as FUG boots. Also in nineteen thirties boots have been worn by Australian shepherds to retain their ft heat and comfortable from chilly weather conditions and tough of approaches which they experienced to journey. Later on, 1960's surfers in Australia put on these products and solutions immediately after coming in from riding icy waves as they assist them to make their toes warm. Whichever you get in touch with them, "sheepskin boots" or "Ugg boots", they are amazingly warm and delicate. They have also develop into a important hit among pattern-setters and lots of celebs in earlier few of years.
These products are designed out of quite superior in quality sheepskin acknowledged as 'twin faced' which indicates acted on from both of those sides internal as nicely as outer. These tactics created the boots to do the job and wick resulting in dry feet. In reality, sheepskin is nothing at all but water resistant by nature. Thats why sturdy stitching and and hardy sole guide the boots very strong and sturdy. This boot is very mild in body weight nevertheless it looks really hefty. Genuinely if we wander in these boots we really feel we are going for walks bare ft. And these boots don"t allow for climate with muddy and moist issue, so we have to prevent these weather with these boot.
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