Perfect thermal contact: Difference between revisions

From formulasearchengine
Jump to navigation Jump to search
en>ChrisGualtieri
m →‎Perfect thermal contact conditions: General fixes / CHECKWIKI fixes using AWB
 
en>Addbot
m Bot: Migrating 2 interwiki links, now provided by Wikidata on d:q4197872
 
Line 1: Line 1:
Her irreverent style makes everyday topics entertaining.<br>In the 1800's, a French Scientist named Peltier discovered that when electric current goes through two different metals, a temperature difference occurs, working like heat pumps, drive heat from one surface to another.<br>http://www.shlgrouptr.com/warm/?p=269 <br /> http://www.shlgrouptr.com/warm/?p=410 <br />  http://www.shlgrouptr.com/warm/?p=104 <br />  http://www. If you treasured this article and also you would like to obtain more info with regards to [http://www.bendtrapclub.com/cheap/ugg.asp Cheap Uggs Boots] nicely visit our own web page. shlgrouptr.com/warm/?p=202 <br />  http://www.shlgrouptr.com/warm/?p=388 <br /> <br>http://necipoglumilas.com/tr/userinfo.php?uid=206876<br>http://www.sebeublizovani.cz/modules.php?name=Your_Account&op=userinfo&username=JIrk
{{Multiple issues|no footnotes = November 2012|orphan = July 2012}}
 
'''System of bilinear equations''' look like the following
<math>y^TA_ix=g_i</math> for <math>i=1,2,\ldots,r</math> for some [[integer]] <math>r</math> where <math>A_i</math> are [[Matrix (mathematics)|matrices]] and <math>g_i</math> are some [[real number]]s. These arise in many subjects like engineering, biology, statistics etc.
 
==Solving in integers==
<!-- "Solving bilinear systems in integers " redirects here -->
We consider here the solution theory for bilinear equations in integers. Let the given system of bilinear equation be
:<math>\begin{alignat}{2}
ax_1x_2+bx_1y_2+cx_2y_1+dy_1y_2&=&\alpha\\
ex_1x_2+fx_1y_2+gx_2y_1+hy_1y_2&=&\beta
\end{alignat}</math>
This system can be written as
:<math>
\begin{bmatrix}a&b&c&d\\e&f&g&h\end{bmatrix}\begin{bmatrix}x_1x_2\\x_1y_2\\y_1x_2\\y_1y_2\end{bmatrix}=\begin{bmatrix}\alpha\\\beta\end{bmatrix}
</math>
Once we solve this linear system of equations then by using [[rank factorization]] below, we can get a solution for the given bilinear system.
:<math>
mat(\begin{bmatrix}x_1x_2\\x_1y_2\\y_1x_2\\y_1y_2\end{bmatrix})=\begin{bmatrix}x_1x_2&x_1y_2\\y_1x_2&y_1y_2\end{bmatrix}=\begin{bmatrix}x_1\\y_1\end{bmatrix}\begin{bmatrix}x_2&y_2\end{bmatrix}
</math>
Now we solve first equation by using smith normal form, given any <math>m\times n</math> matrix <math>A</math>, we can get two matrices <math>U</math> and <math>V</math> in <math>\mbox{SL}_m(\mathbb{Z})</math> and <math>\mbox{SL}_n(\mathbb{Z})</math>, respectively such that <math>UAV=D</math>, where <math>D</math> is as follows:
:<math>
D=\begin{bmatrix}d_1&0&0&\ldots&0\\0&d_2&0&\ldots&0\\\vdots&&&d_s&0&\\0&0&0&\ldots&0\\\vdots&\vdots&\vdots&\vdots&\vdots\end{bmatrix}_{m\times n}
</math>
where <math>d_i>0</math> and <math>d_i|d_{i+1}</math> for <math>i=1,2,\ldots,s-1</math>. It is immediate to note that given a system <math>A\textbf{x}=\textbf{b}</math>, we can rewrite it as <math>D\textbf{y}=\textbf{c}</math>, where <math>V\textbf{y}=\textbf{x}</math> and <math>\textbf{c}=U\textbf{b}</math>. Solving <math>D\textbf{y}=\textbf{c}</math> is easier as the matrix <math>D</math> is somewhat diagonal. Since we are multiplying with some nonsingular matrices we have the two system of equations to be equivalent in the sense that the solutions of one system have one to one correspondence with the solutions of another system. We solve <math>D\textbf{y}=\textbf{c}</math>, and take <math>\textbf{x}=V\textbf{y}</math>.
Let the solution of <math>D\textbf{y}=\textbf{c}</math> is
:<math>
  \textbf{y}=\begin{bmatrix}a_1\\b_1\\s\\t\end{bmatrix}
</math>
where <math>s,t\in\mathbb{Z}</math> are free integers and these are all solutions of <math>D\textbf{y}=\textbf{c}</math>. So, any solution of <math>A\textbf{x}=\textbf{b}</math> is <math>V\textbf{y}</math>. Let <math>V</math> be given by
:<math>
V=\begin{bmatrix}a_{11}&a_{12}&a_{13}&a_{14}\\a_{21}&a_{22}&a_{23}&a_{24}\\a_{31}&a_{32}&a_{33}&a_{34}\\a_{41}&a_{42}&a_{43}&a_{44}\end{bmatrix}=\begin{bmatrix}A_1&B_1\\C_1&D_1\end{bmatrix}
</math>
Then <math>\textbf{x}</math> is
:<math>
  M=mat(\textbf{x})=\begin{bmatrix}a_{11}a_1+a_{12}b_1+a_{13}s+a_{14}t&a_{31}a_1+a_{32}b_1+a_{33}s+a_{34}t\\a_{21}a_1+a_{22}b_1+a_{23}s+a_{24}t&a_{41}a_1+a_{42}b_1+a_{43}s+a_{44}t\end{bmatrix}
</math>
We want matrix <math>M</math> to have rank 1 so that the factorization given in second equation can be done. Solving [[quadratic equation]]s in 2 variables in integers will give us the solutions for a bilinear systems. This method can be extended to any dimension, but at higher dimension solutions become more complicated. This algorithm can be applied in Sage or Matlab to get to the equations at end.
 
==References==
* Charles R. Johnson, Joshua A. Link 'Solution theory for complete bilinear systems of equations' - http://onlinelibrary.wiley.com/doi/10.1002/nla.676/abstract
* Vinh, Le Anh 'On the solvability of systems of bilinear equations in finite fields' - http://arxiv.org/abs/0903.1156
* Yang Dian 'Solution theory for system of bilinear equations' - https://digitalarchive.wm.edu/handle/10288/13726
*  Scott Cohen and Carlo Tomasi. 'Systems of bilinear equations'. Technical report, Stanford, CA, USA, 1997.- ftp://reports.stanford.edu/public_html/cstr/reports/cs/tr/97/1588/CS-TR-97-1588.pdf
 
[[Category:Equations]]

Latest revision as of 22:01, 22 March 2013

Template:Multiple issues

System of bilinear equations look like the following for for some integer where are matrices and are some real numbers. These arise in many subjects like engineering, biology, statistics etc.

Solving in integers

We consider here the solution theory for bilinear equations in integers. Let the given system of bilinear equation be

This system can be written as

Once we solve this linear system of equations then by using rank factorization below, we can get a solution for the given bilinear system.

Now we solve first equation by using smith normal form, given any matrix , we can get two matrices and in and , respectively such that , where is as follows:

where and for . It is immediate to note that given a system , we can rewrite it as , where and . Solving is easier as the matrix is somewhat diagonal. Since we are multiplying with some nonsingular matrices we have the two system of equations to be equivalent in the sense that the solutions of one system have one to one correspondence with the solutions of another system. We solve , and take . Let the solution of is

where are free integers and these are all solutions of . So, any solution of is . Let be given by

Then is

We want matrix to have rank 1 so that the factorization given in second equation can be done. Solving quadratic equations in 2 variables in integers will give us the solutions for a bilinear systems. This method can be extended to any dimension, but at higher dimension solutions become more complicated. This algorithm can be applied in Sage or Matlab to get to the equations at end.

References