View source for ApCoCoA-1:CharP.MNLASolve

{{Version|1}}
<command>
    <title>CharP.MNLASolve</title>
    <short_description>Computes the unique <tt>F_2-</tt>rational zero of a given polynomial system over <tt>F_2</tt>.</short_description>
<syntax>
CharP.MNLASolve(F:LIST):LIST
</syntax>
    <description>
<em>Please note:</em> The function(s) explained on this page is/are using the <em>ApCoCoAServer</em>. You will have to start the ApCoCoAServer in order to use it/them.

<par/>
This function computes the unique zero in <tt>F_2^n</tt> of a polynomial system over <tt>F_2 </tt>. It uses Mutant NLA-Algorithm to find the unique zero. The Mutant NLA-Algorithm generates a sequence of linear systems to solve the given system. The Mutant NLA-Algorithm can find the unique zero only. If the given polynomial system has more than one zeros in <tt>F_2^n </tt> then this function does not find any zero. In this case a massage for non-uniqueness will be displayed to the screen after reaching the maximum degree bound. In fact Mutant NLA-Algorithm is the NLA-Algorithm with mutant strategy. It uses <ref>ApCoCoA-1:LinAlg.EF|LinAlg.EF</ref> for gaussian elimination.



<itemize>
<item>@param <em>F:</em> List of polynomials of given system.</item>
<item>@return The unique solution of the given system in <tt>F_2^n</tt>. </item>
</itemize>

<example>
Use Z/(2)[x[1..4]];
F:=[
    x[1]x[2] + x[2]x[3] + x[2]x[4] + x[3]x[4] + x[1] + x[3] + 1, 
    x[1]x[2] + x[1]x[3] + x[1]x[4] + x[3]x[4] + x[2] + x[3] + 1, 
    x[1]x[2] + x[1]x[3] + x[2]x[3] + x[3]x[4] + x[1] + x[4] + 1, 
    x[1]x[3] + x[2]x[3] + x[1]x[4] + x[2]x[4] + 1
    ];


-- Then we compute the solution with
CharP.MNLASolve(F);

-- And we achieve the following information on the screen together with the solution at the end.
----------------------------------------
    
The size of Matrix is:
     No. of Rows=4
     No. of Columns=11
Applying Gaussian Elimination finding Muatants...
Gaussian Elimination Compeleted
Finding Variable: x[4]
    The size of Matrix is:
    	No. of Rows=11
    	No. of Columns=5
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=11
    	No. of Columns=5
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=4
    	No. of Columns=11
Applying Gaussian Elimination finding Muatants...
Gaussian Elimination Compeleted
    The No. of Mutants found = 0
    The size of Matrix is:
   	No. of Rows=11
    	No. of Columns=9
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
    The size of Matrix is:
  	No. of Rows=11
   	No. of Columns=9
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=8
    	No. of Columns=11
Applying Gaussian Elimination finding Muatants...
Gaussian Elimination Compeleted
    The No. of Mutants found = 1
    The size of Matrix is:
    	No. of Rows=11
    	No. of Columns=12
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=11
    	No. of Columns=12
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
x[4] = 1
Finding Variable: x[3]
   The size of Matrix is:
    	No. of Rows=7
    	No. of Columns=10
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
x[3] = 0
Finding Variable: x[2]
    The size of Matrix is:
    	No. of Rows=4
    	No. of Columns=5
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
    The size of Matrix is:
	No. of Rows=4
    	No. of Columns=5
Applying Gaussian Elimination to check solution coordinate...
Gaussian Elimination Completed.
x[2] = 1

[0, 1, 0, 1]
</example>


<example>
Use Z/(2)[x[1..4]];
F:=[ 
    x[2]x[3] + x[1]x[4] + x[2]x[4] + x[3]x[4] + x[1] + x[2] + x[3] + x[4], 
    x[2]x[3] + x[2]x[4] + x[3]x[4] + x[2] + x[3] + x[4],  
    x[1]x[2] + x[2]x[3] + x[2]x[4] + x[3]x[4] + x[1] + x[2],  
    x[1]x[2] + x[2]x[3] + x[2]x[4] + x[3]x[4] + x[1] + x[2]
   ];

-- Solution is not unique i.e. [0, 1, 1, 1], [0, 0, 0, 0], and [1, 1, 1, 1] are solutions 

-- Then we compute the solution with
CharP.MNLASolve(F);

-- And we achieve the following information on the screen.
----------------------------------------
    
     The size of Matrix is:
    	No. of Rows=4
    	No. of Columns=9
    Applying Gaussian Elimination finding Muatants...
    Gaussian Elimination Compeleted
    Finding Variable: x[4]
    The size of Matrix is:
    	No. of Rows=9
    	No. of Columns=4
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=9
    	No. of Columns=4
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=3
    	No. of Columns=9
    Applying Gaussian Elimination finding Muatants...
    Gaussian Elimination Compeleted
    The No. of Mutants found = 0
    The size of Matrix is:
    	No. of Rows=14
    	No. of Columns=16
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=14
    	No. of Columns=16
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=15
    	No. of Columns=14
    Applying Gaussian Elimination finding Muatants...
    Gaussian Elimination Compeleted
    The No. of Mutants found = 4
    The size of Matrix is:
    	No. of Rows=14
    	No. of Columns=28
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=14
    	No. of Columns=28
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=27
    	No. of Columns=14
    Applying Gaussian Elimination finding Muatants...
    Gaussian Elimination Compeleted
    The No. of Mutants found = 0
    The size of Matrix is:
    	No. of Rows=14
    	No. of Columns=13
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=14
    	No. of Columns=13
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=12
    	No. of Columns=14
    Applying Gaussian Elimination finding Muatants...
    Gaussian Elimination Compeleted
    The No. of Mutants found = 0
    The size of Matrix is:
    	No. of Rows=15
    	No. of Columns=20
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    The size of Matrix is:
    	No. of Rows=15
    	No. of Columns=20
    Applying Gaussian Elimination to check solution coordinate...
    Gaussian Elimination Completed.
    x[4] = NA
	Please Check the uniqueness of solution.
	The Given system of polynomials does not
	seem to have a unique solution or it has
	no solution over the finite field F2.

</example>


    </description>
    <seealso>
      <see>ApCoCoA-1:CharP.MXLSolve|CharP.MXLSolve</see>
     <see>ApCoCoA-1:Introduction to CoCoAServer|Introduction to CoCoAServer</see>
     <see>ApCoCoA-1:Introduction to Groebner Basis in CoCoA|Introduction to Groebner Basis in CoCoA</see>
     <see>ApCoCoA-1:CharP.GBasisF2|CharP.GBasisF2</see>
     <see>ApCoCoA-1:CharP.XLSolve|CharP.XLSolve</see>
     <see>ApCoCoA-1:CharP.IMXLSolve|CharP.IMXLSolve</see>
     <see>ApCoCoA-1:CharP.IMNLASolve|CharP.IMNLASolve</see>
   </seealso>

    <types>
      <type>apcocoaserver</type>
      <type>poly_system</type>
    </types>

    <key>charP.mnlasolve</key>
    <key>mnlasolve</key>
    <key>finite field</key>
    <wiki-category>ApCoCoA-1:Package_charP</wiki-category>
  </command>