Suppose we have the following equations where $0<p<1$:

\begin{align} a_{i,j}&=pb_{i+1,j} + (1-p)b_{0,j} \\ b_{i,j}&=pa_{i,j+1}+(1-p)a_{i,0} \end{align} with the boundary conditions: \begin{align} b_{3,j}=1 \qquad\text{ where $0\le i< 3$}\\ a_{i,3}=0 \qquad\text{ where $0\le j< 3$} \end{align} We are asked to get $a_{0,0}$

I can solve it by getting a set of equations such as: \begin{align} a_{0,0} & = pb_{1,0} + (1-p) b_{0,0}\\ b_{1,0} & = pa_{1,1} + (1-p) a_{1,0}\\ b_{0,0} & = pa_{0,1} + (1-p) a_{0,0}\\ a_{1,1} & = pb_{2,1} + (1-p) b_{0,1}\\ \vdots \end{align}

however this seems too complicated and very easy to calculate wrong. If we let the number $3$ in the boundary condition to be a much larger number $n$, then this method is impossible to solve by hand.

I want to know if there is a better way or more analytical way to solve this kind of equation?

  • $\begingroup$ these are called linear difference equations-en.m.wikipedia.org/wiki/Linear_difference_equation $\endgroup$ – vidyarthi Nov 29 '16 at 4:56
  • $\begingroup$ Note that you can easily decouple the variables. $\endgroup$ – YoTengoUnLCD Nov 29 '16 at 5:33
  • $\begingroup$ @YoTengoUnLCD decouple varialbes eventually will bring you to $a_{3,3}$ which is not defined. $\endgroup$ – fizis Nov 29 '16 at 6:35
  • $\begingroup$ @vidyarthi not exactly same, here I have two time index... $\endgroup$ – fizis Nov 29 '16 at 6:43
  • $\begingroup$ @fizis not exactly same, but somewhat related. Your equation can be converted to homogenous form, from which you may use characteristic equation, I think $\endgroup$ – vidyarthi Nov 29 '16 at 6:46

One way is to place the values $a_{i,j}$ $b_{i,j}$ (for $0\le i,j<3$) in two matrices $A,B$

Then you get the equivalent system of matrix equations:

$$\begin{array}{rcl} A &=& C B + D \tag{1}\\ B &=& A \, C^T \end{array}$$

where $C=\begin{pmatrix} q & p &0\\ q & 0 &p\\ q & 0 & 0 \end{pmatrix}$ and $D=\begin{pmatrix} 0 & 0 &0\\ 0 & 0 &0\\ p & p & p \end{pmatrix}$

(where $q=1-p$)

Or $$A = C A C^T +D \tag{2}$$

Considering that $A$ is the unknown, this corresponds to $9$ linear equations with $9$ unknowns, so it's in principle solvable. Actually this is known as the discrete Lyapunov equation. Sadly, while it's quite simple to solve it numerically (basically you build a $9 \times 9$ matrix to express it -and solve it- as a basic linear equation $Ax = b$), it does not seem easy to express the solution (in particular, $A_{0,0}$) in general, as a function of $p$ .

An example (in Octave/Matlab) :

>> p = 0.3 ; 
>> q=p-1;
>> C=[ q p 0 ;  q 0 p ; q 0 0]
   0.70000   0.30000   0.00000
   0.70000   0.00000   0.30000
   0.70000   0.00000   0.00000
>> D = [0 0 0; 0 0 0 ; p p p]
D =
  0.00000   0.00000   0.00000
  0.00000   0.00000   0.00000
  0.30000   0.30000   0.30000
>> A=reshape((eye(9)-kron(C,C))\reshape(D,9,1) ,3,3)
A =
  0.50516   0.47077   0.36055
  0.53822   0.50826   0.38327
  0.64639   0.62324   0.54753

  >> C*A*C'+D-A % check
ans =
  0.0000e+000  0.0000e+000  -5.5511e-017
 -1.1102e-016  -1.1102e-016  -5.5511e-017
 -1.1102e-016  1.1102e-016  0.0000e+000   

This agrees with the formula from rajb245's answer : $a_{0,0}(0.3)=0.5051590567552$

  • $\begingroup$ $a_{3,3}$ is undefined, because you never need to reach $a_{3,3}$ to get $a_{0,0}$, how can you write $a$ as a matrix? $\endgroup$ – fizis Dec 8 '16 at 1:45
  • $\begingroup$ @fizis : The matrix dimension is $3\times 3$, it includes from $a_{0,0}$ to $a_{2,2}$ $\endgroup$ – leonbloy Dec 8 '16 at 2:12
  • $\begingroup$ I also can't see how your two matrix equation derives, they are symmetric in the original form, but no longer in your matrix form. $\endgroup$ – fizis Dec 8 '16 at 2:12
  • $\begingroup$ If by "no symmetric" you mean the $D$ term: that comes from the different boundary conditions $\endgroup$ – leonbloy Dec 8 '16 at 2:13
  • $\begingroup$ I have check your two equations with $n=2$, this is really a nice simplification. I wonder how you can see it through and write out the matrix form. $\endgroup$ – fizis Dec 8 '16 at 2:34

A general method that works for any size $n$ and is not prone to errors is to use a computer algebra system (such as Mathematica) to directly solve the system for any size $n$. Given that this is a well-posed finite linear system of equations, I don't see any clever tricks; if you want to solve such a system, you (or the computer) has to do the tedious work of solving it using elimination of variables until you get the result. Whether you call this Gaussian elimination or LU decomposition, you have to substitute the equations into each other and keep track of your operations without error in order to arrive at the correct result. In much more complicated problems (such as solving PDEs such as the wave or heat equation or Maxwell's equations), once you reduce things to a finite system of linear equations, you let the computer solvers take over. The fact that your problem is of this simple class to begin with leads me to believe there really aren't any clever tricks to be played here.

For the approach, I transcribed the two equations you presented into Mathematica, then set it up to explicitly calculate all the equations for $i,j\in\{0,1\ldots n\}$, enforced the boundary conditions for $i=n+1$ and $j=n+1$, then told it to solve the equations. For $n=2$, the solution is: $$ a_{0,0} = -\frac{p^8-2 p^7+p^6-p^4+p^3-1}{p^9-4 p^8+6 p^7-4 p^6+3 p^4-3 p^3+2} $$ A happy consequence is that all the unknowns are solved for simultaneously by Mathematica's algorithms.

Here is a plot of $a_{0,0}$ as a function of $p$:

Plot of a00

And here is the Mathematica code I used:

(*setup the right hand side functions*)
a[i_,j_] := p Subscript[b, i+1,j] + (1-p) Subscript[b, 0,j]
b[i_,j_]:=p Subscript[a, i,j+1] + (1-p) Subscript[a, i,0]
n=2; (*works for any order n*)
(*set the variables equal to the right hand sides, enforce the boundary conditions, and collect into one list*)
aEqs = Table[Subscript[a, i,j]==a[i,j],{i,0,n},{j,0,n}]/.{Subscript[a, i_,n+1]->0,Subscript[b, n+1,j_]->1}//Flatten[#,1]&;
bEqs = Table[Subscript[b, i,j]==b[i,j],{i,0,n},{j,0,n}]/.{Subscript[a, i_,n+1]->0,Subscript[b, n+1,j_]->1}//Flatten[#,1]&;
Eqs = Join[aEqs,bEqs];
(*collect all the variables into one list*)
aVars = Table[Subscript[a, i,j],{i,0,n},{j,0,n}]//Flatten[#,1]&;
bVars = Table[Subscript[b, i,j],{i,0,n},{j,0,n}]//Flatten[#,1]&;
Vars = Join[aVars,bVars];
(*Run the solver*)
Soln = Subscript[a, 0,0]/.Solve[Eqs,Vars][[1]]//Simplify;
  • $\begingroup$ I wonder if mathematica can solve matrix equations directly. The other answer gives the simplified form, it will be a good practice if that match your solution.. $\endgroup$ – fizis Dec 8 '16 at 2:37
  • $\begingroup$ You must be a mathematica pro $\endgroup$ – fizis Dec 8 '16 at 2:51
  • $\begingroup$ The other answer is for one value of $p$, but the approach is similar. I can set $p$ to a numerical value and generate the matrix equations if that would be helpful. $\endgroup$ – rajb245 Dec 8 '16 at 15:25
  • $\begingroup$ what I mean is that the other answer simplifies the equation to only one, which is a big analytical improvement if that simplification really works well $\endgroup$ – fizis Dec 9 '16 at 8:21

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