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salim-barzani

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0 years, 192 days
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These are questions asked by salim-barzani

what is pronlem why i can't get solution...

salim-barzani 200 Maple 2024
syntax 2dmath
December 23 2024
1 9

i already use this method for a lot of equation but this time something not normal hapening what is problem?

``

> 

restart
> 

with(PDEtools)
> 

with(LinearAlgebra)
> 

with(Physics)
> 

with(SolveTools)
> 

``
> 

eq0 := -4*alpha*k^2*m^2*n^2*A[0]^2+4*beta*k*m*n^2*A[0]^3-4*gamma*k*m*n^2*A[0]^3+4*delta^2*m*n^2*A[0]^2-4*n^2*sigma*A[0]^4-4*m*n^2*w*A[0]^2 = 0
> 

eq1 := -8*alpha*k^2*m^2*n^2*A[0]*A[1]+12*beta*k*m*n^2*A[0]^2*A[1]-12*gamma*k*m*n^2*A[0]^2*A[1]+8*delta^2*m*n^2*A[0]*A[1]-16*n^2*sigma*A[0]^3*A[1]+2*a*alpha*m*n*A[0]*A[1]-8*m*n^2*w*A[0]*A[1] = 0
> 

eq2 := -4*alpha*k^2*m^2*n^2*A[1]^2+12*beta*k*m*n^2*A[0]*A[1]^2-12*gamma*k*m*n^2*A[0]*A[1]^2+4*delta^2*m*n^2*A[1]^2-24*n^2*sigma*A[0]^2*A[1]^2+a*alpha*m^2*A[1]^2+3*alpha*b*m*n*A[0]*A[1]-4*m*n^2*w*A[1]^2 = 0
> 

eq3 := 4*beta*k*m*n^2*A[1]^3-4*gamma*k*m*n^2*A[1]^3-16*n^2*sigma*A[0]*A[1]^3+alpha*b*m^2*A[1]^2+alpha*b*m*n*A[1]^2+4*alpha*c*m*n*A[0]*A[1] = 0
> 

eq4 := -4*n^2*sigma*A[1]^4+alpha*c*m^2*A[1]^2+2*alpha*c*m*n*A[1]^2 = 0
> 

C := solve({eq0, eq1, eq2, eq3, eq4}, {a, b, c, `__ `*A[0]})

Warning, solving for expressions other than names or functions is not recommended.

  

(1)
 

NULL

Download problem.mw

How remove error when changing delta par...

salim-barzani 200 Maple 2024
finance spam numeric
December 17 2024
0 14

This is my first time working with plotting data from a matrix. However, with the help of a friends on MaplePrimes, I learned how to plot the data in both Maple and MATLAB. Despite this, I am having trouble with visualization. When I change the delta value, my function experiences vibrations or noise, which is clearly visible in the plot. But when I change delta, I encounter errors with my matrix data. How can I fix this problem? and there is any way for get better visualization by Explore ? also How show this vibration or noise in 2D?

> 

restart;
> 

randomize():
> 

local gamma;

gamma

 (1)
> 

currentdir(kernelopts(':-homedir'))
> 

NULL
> 

T3 := (B[1]*(tanh(2*n^2*(delta^2-w)*k*t/((k*n-1)*(k*n+1))+x)-1))^(1/(2*n))*exp(I*(-k*x+w*t+delta*W(t)-delta^2*t))

(B[1]*(tanh(2*n^2*(delta^2-w)*k*t/((k*n-1)*(k*n+1))+x)-1))^((1/2)/n)*exp(I*(-k*x+w*t+delta*W(t)-delta^2*t))

 (2)
> 

NULL
> 

params := {B[1]=1,n=2,delta=1,w=1,k=3 };

{delta = 1, k = 3, n = 2, w = 1, B[1] = 1}

 (3)
> 

NULL

insert numerical values

> 

solnum :=subs(params, T3);

(tanh(x)-1)^(1/4)*exp(I*(-3*x+W(t)))

 (4)
> 

CodeGeneration['Matlab']('(tanh(x)-1)^(1/4)*exp(I*(-3*x+W(t)))')

Warning, the function names {W} are not recognized in the target language

  

cg = ((tanh(x) - 0.1e1) ^ (0.1e1 / 0.4e1)) * exp(i * (-0.3e1 * x + W(t)));

  
> 

N := 100:

use Finance in:
  Wiener := WienerProcess():
  P := PathPlot(Wiener(t), t = 0..10, timesteps = N, replications = 1):
end use:
> 

W__points := plottools:-getdata(P)[1, -1]:
t_grid := convert(W__points[..,1], list):
x_grid := [seq(-2..2, 4/N)]:
> 

T, X := map(mul, [selectremove(has, [op(expand(solnum))], t)])[]:

ST := unapply(eval(T, W(t)=w), w)~(W__points[.., 2]):
SX := evalf(unapply(X, x)~(x_grid)):

STX := Matrix(N$2, (it, ix) -> ST[it]*SX[ix]);

_rtable[36893490640185799852]

 (5)
> 

opts := axis[1]=[tickmarks=[seq(k=nprintf("%1.1f", t_grid[k]), k=1..N, 40)]],
        axis[2]=[tickmarks=[seq(k=nprintf("%1.1f", x_grid[k]), k=1..N, 40)]],
        style=surface:

DocumentTools:-Tabulate(
  [
    plots:-matrixplot(Re~(STX), opts),
    plots:-matrixplot(Im~(STX), opts),
plots:-matrixplot(abs~(STX), opts)
  ]
  , width=60
)

"Tabulate"

 (6)
> 

MatlabFile := cat(currentdir(), "/ST2.txt"); ExportMatrix(MatlabFile, STX, target = MATLAB, format = rectangular, mode = ascii, format = entries)

421796

 (7)

NULL

Download data-analysis.mw

Transform data in maple to Matlab or mak...

salim-barzani 200 Maple 2024
matlab excel export
December 16 2024
1 7

I have a matrix for data analysis that I want to plot. Ideally, I would like to use Maple, but I’m struggling to create a well-designed plot suitable for submission to journals. Because of this, I’m considering transferring the data to Excel or constructing a 3D graph using MATLAB.

My question is: how can I transfer this data to Excel? The data is currently saved as a Notepad file, but I’m unsure how to convert it into an Excel format. I will upload a figure to show the data structure.

also in last runig program give me error which is (Error, (in ExportMatrix) permission denied

Thank you in advance for any help!

> 

restart;
> 

randomize():
> 

local gamma;

gamma

 (1)
 
> 

T3 := (B[1]*(tanh(2*n^2*(delta^2-w)*k*t/((k*n-1)*(k*n+1))+x)-1))^(1/(2*n))*exp(I*(-k*x+w*t+delta*W(t)-delta^2*t))

(B[1]*(tanh(2*n^2*(delta^2-w)*k*t/((k*n-1)*(k*n+1))+x)-1))^((1/2)/n)*exp(I*(-k*x+w*t+delta*W(t)-delta^2*t))

 (2)
> 

``
> 

params := {B[1]=1,n=2,delta=1,w=1,k=3 };

{delta = 1, k = 3, n = 2, w = 1, B[1] = 1}

 (3)
> 

``

insert numerical values

> 

solnum :=subs(params, T3);

(tanh(x)-1)^(1/4)*exp(I*(-3*x+W(t)))

 (4)
> 

CodeGeneration['Matlab']('(tanh(x)-1)^(1/4)*exp(I*(-3*x+W(t)))')

Warning, the function names {W} are not recognized in the target language

  

cg = ((tanh(x) - 0.1e1) ^ (0.1e1 / 0.4e1)) * exp(i * (-0.3e1 * x + W(t)));

  
> 

N := 100:

use Finance in:
  Wiener := WienerProcess():
  P := PathPlot(Wiener(t), t = 0..10, timesteps = N, replications = 1):
end use:
> 

W__points := plottools:-getdata(P)[1, -1]:
t_grid := convert(W__points[..,1], list):
x_grid := [seq(-2..2, 4/N)]:
> 

T, X := map(mul, [selectremove(has, [op(expand(solnum))], t)])[]:

ST := unapply(eval(T, W(t)=w), w)~(W__points[.., 2]):
SX := evalf(unapply(X, x)~(x_grid)):

STX := Matrix(N$2, (it, ix) -> ST[it]*SX[ix]);

_rtable[36893489786521178348]

 (5)
> 

opts := axis[1]=[tickmarks=[seq(k=nprintf("%1.1f", t_grid[k]), k=1..N, 40)]],
        axis[2]=[tickmarks=[seq(k=nprintf("%1.1f", x_grid[k]), k=1..N, 40)]],
        style=surface:

DocumentTools:-Tabulate(
  [
    plots:-matrixplot(Re~(STX), opts),
    plots:-matrixplot(Im~(STX), opts),
plots:-matrixplot(abs~(STX), opts)
  ]
  , width=60
)

"Tabulate"

 (6)
> 

MatlabFile := cat(currentdir(), "/ST2.txt"); ExportMatrix(MatlabFile, STX, target = MATLAB, format = rectangular, mode = ascii, format = entries)

Error, (in ExportMatrix) permission denied

  
 

 

Download data-analysis.mw

Find parameters for two independent vari...

salim-barzani 200 Maple
parameters
December 14 2024
0 7

What systematic methods can be used to determine the optimal parameters in a long equation involving two independent variables, and how do techniques like separation of variables, balancing principles, or dimensional analysis aid in simplifying and solving such equations?

parameters_x_t.mw

Better simplification and latex export...

salim-barzani 200 Maple 2024
collect simplification latex
December 13 2024
2 10

I was rejected because the editor said my equation is too long. My question is: Is there a way to rewrite the equation in a more concise form? Additionally, is there a package in Maple that allows for automatic simplification or collection of terms without using specific commands? Any suggestions for addressing this issue would be appreciated.

> 

restart
> 

``
> 

eq3 := -6*lambda*beta[0]^2*alpha[1]^2*a[3]-2*lambda*beta[0]^2*a[5]*alpha[0]+6*mu*beta[0]*alpha[1]^2*a[2]+3*mu*beta[0]*a[5]*alpha[0]^2+(10*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*alpha[1]^2*alpha[0]^3*a[4]+(6*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*alpha[1]^2*alpha[0]^2*a[3]+(4*(-(2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*lambda+4*mu^2))*alpha[1]^2*a[5]*alpha[0]-12*mu^2*alpha[1]^2*a[5]*alpha[0]+(3*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*alpha[1]^2*alpha[0]*a[2]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*k^2*a[1]*alpha[1]^2+(1/2)*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[1]+(5*(-(2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*lambda+4*mu^2))*alpha[1]^4*alpha[0]*a[4]+(4*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*alpha[1]^2*lambda*a[5]*alpha[0]-k^2*a[1]*beta[0]^2+10*beta[0]^2*alpha[0]^3*a[4]+6*beta[0]^2*alpha[0]^2*a[3]+3*beta[0]^2*alpha[0]*a[2]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*w*alpha[1]^2-(1/4)*lambda*beta[0]^2*a[1]-9*mu^2*alpha[1]^2*a[1]*(1/4)+3*mu*a[1]*alpha[0]*beta[0]*(1/2)+(1/4)*(3*(-(2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*lambda+4*mu^2))*alpha[1]^2*a[1]+(-(2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda))*lambda+4*mu^2)*alpha[1]^4*a[3]-w*beta[0]^2-30*lambda*beta[0]^2*alpha[1]^2*alpha[0]*a[4]-20*mu*beta[0]*lambda*alpha[1]^4*a[4]-7*mu*beta[0]*lambda*a[5]*alpha[1]^2+24*mu*beta[0]*alpha[1]^2*alpha[0]*a[3]+60*mu*beta[0]*alpha[1]^2*alpha[0]^2*a[4] = 0

-k^2*a[1]*beta[0]^2+4*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[5]*alpha[0]-30*lambda*beta[0]^2*alpha[1]^2*alpha[0]*a[4]-20*mu*beta[0]*lambda*alpha[1]^4*a[4]+60*mu*beta[0]*alpha[1]^2*alpha[0]^2*a[4]-7*mu*beta[0]*lambda*a[5]*alpha[1]^2+24*mu*beta[0]*alpha[1]^2*alpha[0]*a[3]-w*beta[0]^2-(9/4)*mu^2*alpha[1]^2*a[1]+6*beta[0]^2*alpha[0]^2*a[3]-(1/4)*lambda*beta[0]^2*a[1]+3*beta[0]^2*alpha[0]*a[2]+(3/4)*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[1]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*w*alpha[1]^2+10*beta[0]^2*alpha[0]^3*a[4]+(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*a[3]+6*mu*beta[0]*alpha[1]^2*a[2]+3*mu*beta[0]*a[5]*alpha[0]^2+(3/2)*mu*a[1]*alpha[0]*beta[0]-6*lambda*beta[0]^2*alpha[1]^2*a[3]-2*lambda*beta[0]^2*a[5]*alpha[0]-12*mu^2*alpha[1]^2*a[5]*alpha[0]+3*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]*a[2]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*k^2*a[1]*alpha[1]^2+(1/2)*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[1]+5*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*alpha[0]*a[4]+10*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^3*a[4]+6*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^2*a[3]+4*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[5]*alpha[0] = 0

 (1)
> 

numer(lhs(3*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]*a[2]+5*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*alpha[0]*a[4]+10*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^3*a[4]+6*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^2*a[3]+4*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[5]*alpha[0]-6*lambda*beta[0]^2*alpha[1]^2*a[3]-2*lambda*beta[0]^2*a[5]*alpha[0]+6*mu*beta[0]*alpha[1]^2*a[2]+3*mu*beta[0]*a[5]*alpha[0]^2+(3/2)*mu*a[1]*alpha[0]*beta[0]-12*mu^2*alpha[1]^2*a[5]*alpha[0]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*k^2*a[1]*alpha[1]^2+(1/2)*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[1]-w*beta[0]^2+4*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[5]*alpha[0]-30*lambda*beta[0]^2*alpha[1]^2*alpha[0]*a[4]-20*mu*beta[0]*lambda*alpha[1]^4*a[4]-7*mu*beta[0]*lambda*a[5]*alpha[1]^2+24*mu*beta[0]*alpha[1]^2*alpha[0]*a[3]+60*mu*beta[0]*alpha[1]^2*alpha[0]^2*a[4]+(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*a[3]+(3/4)*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[1]-k^2*a[1]*beta[0]^2+10*beta[0]^2*alpha[0]^3*a[4]+6*beta[0]^2*alpha[0]^2*a[3]+3*beta[0]^2*alpha[0]*a[2]-(9/4)*mu^2*alpha[1]^2*a[1]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*w*alpha[1]^2-(1/4)*lambda*beta[0]^2*a[1] = 0))*denom(rhs(3*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]*a[2]+5*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*alpha[0]*a[4]+10*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^3*a[4]+6*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^2*a[3]+4*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[5]*alpha[0]-6*lambda*beta[0]^2*alpha[1]^2*a[3]-2*lambda*beta[0]^2*a[5]*alpha[0]+6*mu*beta[0]*alpha[1]^2*a[2]+3*mu*beta[0]*a[5]*alpha[0]^2+(3/2)*mu*a[1]*alpha[0]*beta[0]-12*mu^2*alpha[1]^2*a[5]*alpha[0]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*k^2*a[1]*alpha[1]^2+(1/2)*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[1]-w*beta[0]^2+4*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[5]*alpha[0]-30*lambda*beta[0]^2*alpha[1]^2*alpha[0]*a[4]-20*mu*beta[0]*lambda*alpha[1]^4*a[4]-7*mu*beta[0]*lambda*a[5]*alpha[1]^2+24*mu*beta[0]*alpha[1]^2*alpha[0]*a[3]+60*mu*beta[0]*alpha[1]^2*alpha[0]^2*a[4]+(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*a[3]+(3/4)*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[1]-k^2*a[1]*beta[0]^2+10*beta[0]^2*alpha[0]^3*a[4]+6*beta[0]^2*alpha[0]^2*a[3]+3*beta[0]^2*alpha[0]*a[2]-(9/4)*mu^2*alpha[1]^2*a[1]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*w*alpha[1]^2-(1/4)*lambda*beta[0]^2*a[1] = 0)) = numer(rhs(3*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]*a[2]+5*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*alpha[0]*a[4]+10*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^3*a[4]+6*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^2*a[3]+4*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[5]*alpha[0]-6*lambda*beta[0]^2*alpha[1]^2*a[3]-2*lambda*beta[0]^2*a[5]*alpha[0]+6*mu*beta[0]*alpha[1]^2*a[2]+3*mu*beta[0]*a[5]*alpha[0]^2+(3/2)*mu*a[1]*alpha[0]*beta[0]-12*mu^2*alpha[1]^2*a[5]*alpha[0]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*k^2*a[1]*alpha[1]^2+(1/2)*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[1]-w*beta[0]^2+4*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[5]*alpha[0]-30*lambda*beta[0]^2*alpha[1]^2*alpha[0]*a[4]-20*mu*beta[0]*lambda*alpha[1]^4*a[4]-7*mu*beta[0]*lambda*a[5]*alpha[1]^2+24*mu*beta[0]*alpha[1]^2*alpha[0]*a[3]+60*mu*beta[0]*alpha[1]^2*alpha[0]^2*a[4]+(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*a[3]+(3/4)*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[1]-k^2*a[1]*beta[0]^2+10*beta[0]^2*alpha[0]^3*a[4]+6*beta[0]^2*alpha[0]^2*a[3]+3*beta[0]^2*alpha[0]*a[2]-(9/4)*mu^2*alpha[1]^2*a[1]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*w*alpha[1]^2-(1/4)*lambda*beta[0]^2*a[1] = 0))*denom(lhs(3*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]*a[2]+5*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*alpha[0]*a[4]+10*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^3*a[4]+6*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*alpha[0]^2*a[3]+4*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[5]*alpha[0]-6*lambda*beta[0]^2*alpha[1]^2*a[3]-2*lambda*beta[0]^2*a[5]*alpha[0]+6*mu*beta[0]*alpha[1]^2*a[2]+3*mu*beta[0]*a[5]*alpha[0]^2+(3/2)*mu*a[1]*alpha[0]*beta[0]-12*mu^2*alpha[1]^2*a[5]*alpha[0]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*k^2*a[1]*alpha[1]^2+(1/2)*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[1]-w*beta[0]^2+4*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*alpha[1]^2*lambda*a[5]*alpha[0]-30*lambda*beta[0]^2*alpha[1]^2*alpha[0]*a[4]-20*mu*beta[0]*lambda*alpha[1]^4*a[4]-7*mu*beta[0]*lambda*a[5]*alpha[1]^2+24*mu*beta[0]*alpha[1]^2*alpha[0]*a[3]+60*mu*beta[0]*alpha[1]^2*alpha[0]^2*a[4]+(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^4*a[3]+(3/4)*(-2*(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*lambda+4*mu^2)*alpha[1]^2*a[1]-k^2*a[1]*beta[0]^2+10*beta[0]^2*alpha[0]^3*a[4]+6*beta[0]^2*alpha[0]^2*a[3]+3*beta[0]^2*alpha[0]*a[2]-(9/4)*mu^2*alpha[1]^2*a[1]-(lambda*B[1]^2-lambda*B[2]^2-mu^2/lambda)*w*alpha[1]^2-(1/4)*lambda*beta[0]^2*a[1] = 0))

-40*lambda^3*B[1]^2*a[4]*alpha[0]*alpha[1]^4+40*lambda^3*B[2]^2*a[4]*alpha[0]*alpha[1]^4-8*lambda^3*B[1]^2*a[3]*alpha[1]^4+8*lambda^3*B[2]^2*a[3]*alpha[1]^4+40*lambda^2*B[1]^2*a[4]*alpha[0]^3*alpha[1]^2-40*lambda^2*B[2]^2*a[4]*alpha[0]^3*alpha[1]^2-4*k^2*lambda^2*B[1]^2*a[1]*alpha[1]^2+4*k^2*lambda^2*B[2]^2*a[1]*alpha[1]^2-16*lambda^3*B[1]^2*a[5]*alpha[0]*alpha[1]^2+16*lambda^3*B[2]^2*a[5]*alpha[0]*alpha[1]^2-80*lambda^2*mu*a[4]*alpha[1]^4*beta[0]+24*lambda^2*B[1]^2*a[3]*alpha[0]^2*alpha[1]^2-24*lambda^2*B[2]^2*a[3]*alpha[0]^2*alpha[1]^2+120*lambda*mu^2*a[4]*alpha[0]*alpha[1]^4-4*lambda^3*B[1]^2*a[1]*alpha[1]^2+4*lambda^3*B[2]^2*a[1]*alpha[1]^2+12*lambda^2*B[1]^2*a[2]*alpha[0]*alpha[1]^2-12*lambda^2*B[2]^2*a[2]*alpha[0]*alpha[1]^2-120*lambda^2*a[4]*alpha[0]*alpha[1]^2*beta[0]^2+24*lambda*mu^2*a[3]*alpha[1]^4+240*lambda*mu*a[4]*alpha[0]^2*alpha[1]^2*beta[0]-40*mu^2*a[4]*alpha[0]^3*alpha[1]^2+4*k^2*mu^2*a[1]*alpha[1]^2-28*lambda^2*mu*a[5]*alpha[1]^2*beta[0]-4*lambda^2*w*B[1]^2*alpha[1]^2+4*lambda^2*w*B[2]^2*alpha[1]^2-24*lambda^2*a[3]*alpha[1]^2*beta[0]^2+32*lambda*mu^2*a[5]*alpha[0]*alpha[1]^2+96*lambda*mu*a[3]*alpha[0]*alpha[1]^2*beta[0]+40*lambda*a[4]*alpha[0]^3*beta[0]^2-24*mu^2*a[3]*alpha[0]^2*alpha[1]^2-4*k^2*lambda*a[1]*beta[0]^2-8*lambda^2*a[5]*alpha[0]*beta[0]^2+7*lambda*mu^2*a[1]*alpha[1]^2+24*lambda*mu*a[2]*alpha[1]^2*beta[0]+12*lambda*mu*a[5]*alpha[0]^2*beta[0]+24*lambda*a[3]*alpha[0]^2*beta[0]^2-12*mu^2*a[2]*alpha[0]*alpha[1]^2-lambda^2*a[1]*beta[0]^2+6*lambda*mu*a[1]*alpha[0]*beta[0]+12*lambda*a[2]*alpha[0]*beta[0]^2+4*mu^2*w*alpha[1]^2-4*lambda*w*beta[0]^2 = 0

 (2)
> 

simplify(-40*lambda^3*B[1]^2*a[4]*alpha[0]*alpha[1]^4+40*lambda^3*B[2]^2*a[4]*alpha[0]*alpha[1]^4-8*lambda^3*B[1]^2*a[3]*alpha[1]^4+8*lambda^3*B[2]^2*a[3]*alpha[1]^4+40*lambda^2*B[1]^2*a[4]*alpha[0]^3*alpha[1]^2-40*lambda^2*B[2]^2*a[4]*alpha[0]^3*alpha[1]^2-4*k^2*lambda^2*B[1]^2*a[1]*alpha[1]^2+4*k^2*lambda^2*B[2]^2*a[1]*alpha[1]^2-16*lambda^3*B[1]^2*a[5]*alpha[0]*alpha[1]^2+16*lambda^3*B[2]^2*a[5]*alpha[0]*alpha[1]^2-80*lambda^2*mu*a[4]*alpha[1]^4*beta[0]+24*lambda^2*B[1]^2*a[3]*alpha[0]^2*alpha[1]^2-24*lambda^2*B[2]^2*a[3]*alpha[0]^2*alpha[1]^2+120*lambda*mu^2*a[4]*alpha[0]*alpha[1]^4-4*lambda^3*B[1]^2*a[1]*alpha[1]^2+4*lambda^3*B[2]^2*a[1]*alpha[1]^2+12*lambda^2*B[1]^2*a[2]*alpha[0]*alpha[1]^2-12*lambda^2*B[2]^2*a[2]*alpha[0]*alpha[1]^2-120*lambda^2*a[4]*alpha[0]*alpha[1]^2*beta[0]^2+24*lambda*mu^2*a[3]*alpha[1]^4+240*lambda*mu*a[4]*alpha[0]^2*alpha[1]^2*beta[0]-40*mu^2*a[4]*alpha[0]^3*alpha[1]^2+4*k^2*mu^2*a[1]*alpha[1]^2-28*lambda^2*mu*a[5]*alpha[1]^2*beta[0]-4*lambda^2*w*B[1]^2*alpha[1]^2+4*lambda^2*w*B[2]^2*alpha[1]^2-24*lambda^2*a[3]*alpha[1]^2*beta[0]^2+32*lambda*mu^2*a[5]*alpha[0]*alpha[1]^2+96*lambda*mu*a[3]*alpha[0]*alpha[1]^2*beta[0]+40*lambda*a[4]*alpha[0]^3*beta[0]^2-24*mu^2*a[3]*alpha[0]^2*alpha[1]^2-4*k^2*lambda*a[1]*beta[0]^2-8*lambda^2*a[5]*alpha[0]*beta[0]^2+7*lambda*mu^2*a[1]*alpha[1]^2+24*lambda*mu*a[2]*alpha[1]^2*beta[0]+12*lambda*mu*a[5]*alpha[0]^2*beta[0]+24*lambda*a[3]*alpha[0]^2*beta[0]^2-12*mu^2*a[2]*alpha[0]*alpha[1]^2-lambda^2*a[1]*beta[0]^2+6*lambda*mu*a[1]*alpha[0]*beta[0]+12*lambda*a[2]*alpha[0]*beta[0]^2+4*mu^2*w*alpha[1]^2-4*lambda*w*beta[0]^2 = 0, 'symbolic')

-40*(B[1]-B[2])*((a[4]*alpha[0]+(1/5)*a[3])*alpha[1]^2+(2/5)*a[5]*alpha[0]+(1/10)*a[1])*alpha[1]^2*(B[1]+B[2])*lambda^3+4*(-20*a[4]*beta[0]*alpha[1]^4*mu+(10*(B[1]^2-B[2]^2)*a[4]*alpha[0]^3+6*a[3]*(B[1]^2-B[2]^2)*alpha[0]^2+3*(B[1]^2*a[2]-B[2]^2*a[2]-10*a[4]*beta[0]^2)*alpha[0]-6*beta[0]^2*a[3]-7*a[5]*beta[0]*mu-(B[1]-B[2])*(B[1]+B[2])*(k^2*a[1]+w))*alpha[1]^2-2*(a[5]*alpha[0]+(1/8)*a[1])*beta[0]^2)*lambda^2+(120*(a[4]*alpha[0]+(1/5)*a[3])*mu^2*alpha[1]^4+(240*a[4]*beta[0]*alpha[0]^2*mu+32*(mu^2*a[5]+3*mu*a[3]*beta[0])*alpha[0]+24*beta[0]*mu*a[2]+7*mu^2*a[1])*alpha[1]^2-4*(-10*a[4]*beta[0]*alpha[0]^3+3*(-mu*a[5]-2*a[3]*beta[0])*alpha[0]^2+3*(-beta[0]*a[2]-(1/2)*mu*a[1])*alpha[0]+beta[0]*(k^2*a[1]+w))*beta[0])*lambda+4*alpha[1]^2*mu^2*(-10*a[4]*alpha[0]^3+k^2*a[1]-6*a[3]*alpha[0]^2-3*a[2]*alpha[0]+w) = 0

  

 

 

Error, (in collect) invalid input: collect uses a 2nd argument, x, which is missing

  
> 

Q1 := collect(%, {B__1, B__2})

-40*(B[1]-B[2])*((a[4]*alpha[0]+(1/5)*a[3])*alpha[1]^2+(2/5)*a[5]*alpha[0]+(1/10)*a[1])*alpha[1]^2*(B[1]+B[2])*lambda^3+4*(-20*a[4]*beta[0]*alpha[1]^4*mu+(10*(B[1]^2-B[2]^2)*a[4]*alpha[0]^3+6*a[3]*(B[1]^2-B[2]^2)*alpha[0]^2+3*(B[1]^2*a[2]-B[2]^2*a[2]-10*a[4]*beta[0]^2)*alpha[0]-6*beta[0]^2*a[3]-7*a[5]*beta[0]*mu-(B[1]-B[2])*(B[1]+B[2])*(k^2*a[1]+w))*alpha[1]^2-2*(a[5]*alpha[0]+(1/8)*a[1])*beta[0]^2)*lambda^2+(120*(a[4]*alpha[0]+(1/5)*a[3])*mu^2*alpha[1]^4+(240*a[4]*beta[0]*alpha[0]^2*mu+32*(mu^2*a[5]+3*mu*a[3]*beta[0])*alpha[0]+24*beta[0]*mu*a[2]+7*mu^2*a[1])*alpha[1]^2-4*(-10*a[4]*beta[0]*alpha[0]^3+3*(-mu*a[5]-2*a[3]*beta[0])*alpha[0]^2+3*(-beta[0]*a[2]-(1/2)*mu*a[1])*alpha[0]+beta[0]*(k^2*a[1]+w))*beta[0])*lambda+4*alpha[1]^2*mu^2*(-10*a[4]*alpha[0]^3+k^2*a[1]-6*a[3]*alpha[0]^2-3*a[2]*alpha[0]+w) = 0

 (3)
> 

latex(Q1)

-40 \left(B_{1}-B_{2}\right) \left(\left(a_{4} \alpha_{0}+\frac{a_{3}}{5}\right) \alpha_{1}^{2}+\frac{2 a_{5} \alpha_{0}}{5}+\frac{a_{1}}{10}\right) \alpha_{1}^{2} \left(B_{1}+B_{2}\right) \lambda^{3}+4 \left(-20 a_{4} \beta_{0} \alpha_{1}^{4} \mu +\left(10 \left(B_{1}^{2}-B_{2}^{2}\right) a_{4} \alpha_{0}^{3}+6 a_{3} \left(B_{1}^{2}-B_{2}^{2}\right) \alpha_{0}^{2}+3 \left(B_{1}^{2} a_{2}-B_{2}^{2} a_{2}-10 a_{4} \beta_{0}^{2}\right) \alpha_{0}-6 \beta_{0}^{2} a_{3}-7 a_{5} \beta_{0} \mu -\left(B_{1}-B_{2}\right) \left(B_{1}+B_{2}\right) \left(k^{2} a_{1}+w \right)\right) \alpha_{1}^{2}-2 \left(a_{5} \alpha_{0}+\frac{a_{1}}{8}\right) \beta_{0}^{2}\right) \lambda^{2}+\left(120 \left(a_{4} \alpha_{0}+\frac{a_{3}}{5}\right) \mu^{2} \alpha_{1}^{4}+\left(240 a_{4} \beta_{0} \alpha_{0}^{2} \mu +32 \left(\mu^{2} a_{5}+3 \mu  a_{3} \beta_{0}\right) \alpha_{0}+24 \beta_{0} \mu  a_{2}+7 \mu^{2} a_{1}\right) \alpha_{1}^{2}-4 \left(-10 a_{4} \beta_{0} \alpha_{0}^{3}+3 \left(-\mu  a_{5}-2 a_{3} \beta_{0}\right) \alpha_{0}^{2}+3 \left(-\beta_{0} a_{2}-\frac{\mu  a_{1}}{2}\right) \alpha_{0}+\beta_{0} \left(k^{2} a_{1}+w \right)\right) \beta_{0}\right) \lambda +4 \alpha_{1}^{2} \mu^{2} \left(-10 a_{4} \alpha_{0}^{3}+k^{2} a_{1}-6 a_{3} \alpha_{0}^{2}-3 a_{2} \alpha_{0}+w \right)
 = 0

  
 

NULL

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