Maple Questions and Posts

These are Posts and Questions associated with the product, Maple

[Edit: a general procedure based on these ideas is given below.]

Maple's isolve can solve some but not all of the quadratic equations in two variables describing the conic sections. Here I show that by transforming the equations, Maple can then solve these missing cases.

restart

with(plots)

I was recently surprised that isolve cannot solve the following simple Diophantine equation

isolve(2*x^2+4*x*y+y^2 = 7)

which has the obvious (to a human) solution {x = 1, y = 1}. This led me to think about the case of conic sections, which have the following general equation (= 0 implied), where I assume a, () .. (), f are integers.

P := a*x^2+b*x*y+c*y^2+d*x+e*y+f

a*x^2+b*x*y+c*y^2+d*x+e*y+f

The above equation has discriminant -4*a*c+b^2 positive, indicating that is is a hyperbola.

h_params := {a = 2, b = 4, c = 1, d = 0, e = 0, f = -7}; P__h := eval(P, h_params); disc := -4*a*c+b^2; eval(disc, h_params); plot__h := implicitplot(P__h, x = -10 .. 10, y = -10 .. 10, colour = red)

{a = 2, b = 4, c = 1, d = 0, e = 0, f = -7}

2*x^2+4*x*y+y^2-7

-4*a*c+b^2

8

Here's a parabola case (discriminant = 0) that isolve also has trouble with

p_params := {a = 2, b = 4, c = 2, d = 1, e = 2, f = 7}; eval(disc, p_params); P__p := eval(P, p_params); {isolve(P__p)}; plot__h := implicitplot(P__p, x = -10 .. 10, y = -10 .. 10, colour = red)

{a = 2, b = 4, c = 2, d = 1, e = 2, f = 7}

0

2*x^2+4*x*y+2*y^2+x+2*y+7

{}

But this has at least one solution

eval(P__p, {x = 7, y = -7})

0

Maple seems to do better in the elliptic case (discriminant negative) and finds two solutions. Examination of the plot suggests there are no other solutions.

e_params := {a = 2, b = 4, c = 3, d = 1, e = 2, f = -7}; eval(disc, e_params); P__e := eval(P, e_params); {isolve(P__e)}; plot__e := implicitplot(P__e, x = -10 .. 10, y = -10 .. 10, colour = red)

{a = 2, b = 4, c = 3, d = 1, e = 2, f = -7}

-8

2*x^2+4*x*y+3*y^2+x+2*y-7

{{x = -3, y = 2}, {x = 2, y = -3}}

I show that transformation of the general equation to the form -D*Y^2+X^2 = m, where D is the discriminant, allows Maple to solve the hyperbolic case, as well as the elliptic case it already knows how to solve; another transformation works for the parabolic case. Maple appears to be able to solve all (solvable) cases of the transformed equations, though this is not clear from the help page. The transformation is discussed in Bogdan Grechuk, Polynomial Diophantine Equations: A Systematic Approach, Springer, 2024, Sec. 3.1.7. doi: 10.1007/978-3-031-62949-5

 

A complete classification of the conics, including degenerate cases, is given in https://en.wikipedia.org/wiki/Matrix_representation_of_conic_sections. If the determinant, delta, of the following matrix is zero, we have a degenerate case.

A__Q := Matrix(3, 3, [a, (1/2)*b, (1/2)*d, (1/2)*b, c, (1/2)*e, (1/2)*d, (1/2)*e, f]); delta := LinearAlgebra:-Determinant(A__Q)

Matrix(%id = 36893489963432522084)

a*c*f-(1/4)*a*e^2-(1/4)*b^2*f+(1/4)*b*d*e-(1/4)*c*d^2

The case of a = b and b = c and c = 0 is just the linear case, which Maple can solve, and is one case where D = delta and delta = 0. Other degenerate parabola cases are two coincident lines or two parallel lines. Degenerate hyperbolas are two intersecting lines, and degenerate ellipses are a single point. Maple can solve all these cases, e.g.,NULL

expand((2*x+3*y+1)*(2*x+3*y)); {isolve(%)}; expand((2*x+3*y)*(2*x+3*y)); {isolve(%)}; expand((x-2)*(y-3)); {isolve(%)}; x^2+y^2 = 0; {isolve(%)}

4*x^2+12*x*y+9*y^2+2*x+3*y

{{x = -3*_Z1, y = 2*_Z1}, {x = -2-3*_Z1, y = 1+2*_Z1}}

4*x^2+12*x*y+9*y^2

{{x = -3*_Z1, y = 2*_Z1}}

x*y-3*x-2*y+6

{{x = _Z1, y = 3}}

x^2+y^2 = 0

{{x = 0, y = 0}}

(The intersecting lines case above only finds one of the lines.) The transformation will consider only the case where at least one of a or c is non-zero. This misses hyperbolas with a = c and c = 0; Maple seems to handle these bilinear equations, e.g.,

bl_params := {a = 0, b = 2, c = 0, d = 1, e = 1, f = 2}; P__bl := eval(P, bl_params); {isolve(P__bl)}

{a = 0, b = 2, c = 0, d = 1, e = 1, f = 2}

2*x*y+x+y+2

{{x = -2, y = 0}, {x = -1, y = 1}, {x = 0, y = -2}, {x = 1, y = -1}}

Transformation for non-zero discriminant
At least one of a or c must be non-zero; if necessary exchange x and y to ensure a is non-zero.

We multiply P by -4*a*(-4*a*c+b^2) and change to new variables X and Y.

itr := {X = (-4*a*c+b^2)*y+b*d-2*a*e, Y = 2*a*x+b*y+d}; tr := solve(itr, {x, y})

{X = (-4*a*c+b^2)*y+b*d-2*a*e, Y = 2*a*x+b*y+d}

{x = (1/2)*(4*Y*a*c-Y*b^2+2*a*b*e-4*a*c*d+X*b)/((4*a*c-b^2)*a), y = -(2*a*e-b*d+X)/(4*a*c-b^2)}

The transformed equation has the form -D*Y^2+X^2-m = 0 or -D*Y^2+X^2 = m, where D is the discriminant.

Q := collect(normal(eval(-4*P*a*(-4*a*c+b^2), tr)), {X, Y}); m := -coeff(coeff(Q, X, 0), Y, 0)

X^2+(4*a*c-b^2)*Y^2+16*a^2*c*f-4*a^2*e^2-4*a*b^2*f+4*a*b*d*e-4*a*c*d^2

-16*a^2*c*f+4*a^2*e^2+4*a*b^2*f-4*a*b*d*e+4*a*c*d^2

For positive discriminant D, this is a general Pell's equation, -D*Y^2+X^2 = m, which Maple knows how to solve. (The definition of Pell's equation requires that D is not a square, but Maple can also solve the simpler case where D is a square.) For the hyperbola above, we have an infinite number of solutions, parameterized by an arbitrary integer _Z1.

Q__h := eval(Q, h_params); solXY__h := {isolve(Q__h)}

X^2-8*Y^2+448

{{X = -12*(1+2^(1/2))^(1+2*_Z1)-12*(1-2^(1/2))^(1+2*_Z1)-4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = -3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))-2*(1+2^(1/2))^(1+2*_Z1)-2*(1-2^(1/2))^(1+2*_Z1)}, {X = -12*(1+2^(1/2))^(1+2*_Z1)-12*(1-2^(1/2))^(1+2*_Z1)-4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = 3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))+2*(1+2^(1/2))^(1+2*_Z1)+2*(1-2^(1/2))^(1+2*_Z1)}, {X = -12*(1+2^(1/2))^(1+2*_Z1)-12*(1-2^(1/2))^(1+2*_Z1)+4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = -3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))+2*(1+2^(1/2))^(1+2*_Z1)+2*(1-2^(1/2))^(1+2*_Z1)}, {X = -12*(1+2^(1/2))^(1+2*_Z1)-12*(1-2^(1/2))^(1+2*_Z1)+4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = 3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))-2*(1+2^(1/2))^(1+2*_Z1)-2*(1-2^(1/2))^(1+2*_Z1)}, {X = 12*(1+2^(1/2))^(1+2*_Z1)+12*(1-2^(1/2))^(1+2*_Z1)-4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = -3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))+2*(1+2^(1/2))^(1+2*_Z1)+2*(1-2^(1/2))^(1+2*_Z1)}, {X = 12*(1+2^(1/2))^(1+2*_Z1)+12*(1-2^(1/2))^(1+2*_Z1)-4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = 3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))-2*(1+2^(1/2))^(1+2*_Z1)-2*(1-2^(1/2))^(1+2*_Z1)}, {X = 12*(1+2^(1/2))^(1+2*_Z1)+12*(1-2^(1/2))^(1+2*_Z1)+4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = -3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))-2*(1+2^(1/2))^(1+2*_Z1)-2*(1-2^(1/2))^(1+2*_Z1)}, {X = 12*(1+2^(1/2))^(1+2*_Z1)+12*(1-2^(1/2))^(1+2*_Z1)+4*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), Y = 3*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))+2*(1+2^(1/2))^(1+2*_Z1)+2*(1-2^(1/2))^(1+2*_Z1)}}

Transforming back to the original coordinates

sol__h := {seq(eval(eval(tr, h_params), solXY), `in`(solXY, solXY__h))}

{{x = -2*(1+2^(1/2))^(1+2*_Z1)-2*(1-2^(1/2))^(1+2*_Z1)-(5/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = (3/2)*(1+2^(1/2))^(1+2*_Z1)+(3/2)*(1-2^(1/2))^(1+2*_Z1)+(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}, {x = -2*(1+2^(1/2))^(1+2*_Z1)-2*(1-2^(1/2))^(1+2*_Z1)+(5/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = (3/2)*(1+2^(1/2))^(1+2*_Z1)+(3/2)*(1-2^(1/2))^(1+2*_Z1)-(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}, {x = -(1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)-(1/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = (3/2)*(1+2^(1/2))^(1+2*_Z1)+(3/2)*(1-2^(1/2))^(1+2*_Z1)-(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}, {x = -(1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)+(1/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = (3/2)*(1+2^(1/2))^(1+2*_Z1)+(3/2)*(1-2^(1/2))^(1+2*_Z1)+(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}, {x = (1+2^(1/2))^(1+2*_Z1)+(1-2^(1/2))^(1+2*_Z1)-(1/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = -(3/2)*(1+2^(1/2))^(1+2*_Z1)-(3/2)*(1-2^(1/2))^(1+2*_Z1)-(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}, {x = (1+2^(1/2))^(1+2*_Z1)+(1-2^(1/2))^(1+2*_Z1)+(1/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = -(3/2)*(1+2^(1/2))^(1+2*_Z1)-(3/2)*(1-2^(1/2))^(1+2*_Z1)+(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}, {x = 2*(1+2^(1/2))^(1+2*_Z1)+2*(1-2^(1/2))^(1+2*_Z1)-(5/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = -(3/2)*(1+2^(1/2))^(1+2*_Z1)-(3/2)*(1-2^(1/2))^(1+2*_Z1)+(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}, {x = 2*(1+2^(1/2))^(1+2*_Z1)+2*(1-2^(1/2))^(1+2*_Z1)+(5/4)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1)), y = -(3/2)*(1+2^(1/2))^(1+2*_Z1)-(3/2)*(1-2^(1/2))^(1+2*_Z1)-(1/2)*2^(1/2)*((1+2^(1/2))^(1+2*_Z1)-(1-2^(1/2))^(1+2*_Z1))}}

Evaluate for some _Z1 values, say _Z1=0 and _Z1=5.
It is evident from tr above that integer solutions in X, Y may transform to non-integer solutions in x, y but that doesn't occur for these two cases

sol__h0 := evala(eval(sol__h, _Z1 = 0)); sol__h5 := evala(eval(sol__h, _Z1 = 5))

{{x = -9, y = 5}, {x = -3, y = 1}, {x = -1, y = -1}, {x = -1, y = 5}, {x = 1, y = -5}, {x = 1, y = 1}, {x = 3, y = -1}, {x = 9, y = -5}}

{{x = -61181, y = 35839}, {x = -21979, y = 12875}, {x = -10497, y = 35839}, {x = -3771, y = 12875}, {x = 3771, y = -12875}, {x = 10497, y = -35839}, {x = 21979, y = -12875}, {x = 61181, y = -35839}}

Check they are solutions to P__h

map2(eval, P__h, `union`(sol__h0, sol__h5))

{0}

For negative discriminant and negative m, the equation -D*Y^2+X^2 = m has no solutions. In the classification scheme for the conics, the "imaginary ellipse" case (no real solutions) occurs when (a+c)*delta > 0. For negative discriminant, we must have a and c the same sign, and this is the case of negative m.

factor(expand((16*(a+c))*delta)); factor(-m)

4*(a+c)*(4*a*c*f-a*e^2-b^2*f+b*d*e-c*d^2)

4*a*(4*a*c*f-a*e^2-b^2*f+b*d*e-c*d^2)

. In this case Maple returns NULL for both the untransformed and transformed case, which can mean no solutions or just that isolve couldn't find any.

ie_params := {a = 3, b = 0, c = 5, d = 0, e = 0, f = 8}; P__ie := eval(P, ie_params); {isolve(P__ie)}; Q__ie := eval(Q, ie_params); {isolve(Q__ie)}

{a = 3, b = 0, c = 5, d = 0, e = 0, f = 8}

3*x^2+5*y^2+8

{}

X^2+60*Y^2+5760

{}

For negative discriminant and positive m or (a+c)*delta < 0, the ellipse is real, and there are a finite number of solutions. Maple solves the untransformed and transformed equations.
Here we need to filter out non-integer solutions

P__e; {isolve(P__e)}; Q__e := eval(Q, e_params); solXY__e := {isolve(Q__e)}; {seq(eval(eval(tr, e_params), solXY), `in`(solXY, solXY__e))}; sol__e := select(proc (q) options operator, arrow; eval(x::integer, q) and eval(y::integer, q) end proc, %)

2*x^2+4*x*y+3*y^2+x+2*y-7

{{x = -3, y = 2}, {x = 2, y = -3}}

X^2+8*Y^2-472

{{X = -20, Y = -3}, {X = -20, Y = 3}, {X = 20, Y = -3}, {X = 20, Y = 3}}

{{x = -3, y = 2}, {x = 2, y = -3}, {x = -3/2, y = 2}, {x = 7/2, y = -3}}

{{x = -3, y = 2}, {x = 2, y = -3}}

Transformation for zero discriminant
For the case of zero discriminant (parabola), we need a different transformation.

itr0 := {X = 2*a*x+b*y+d, Y = y}; tr0 := solve(itr0, {x, y})

{X = 2*a*x+b*y+d, Y = y}

{x = (1/2)*(-Y*b+X-d)/a, y = Y}

The transformed equation is of the form A*Y+X^2+B = 0

Q0 := collect(normal(eval(4*a*P, tr0)), {X, Y})

X^2+(4*a*c-b^2)*Y^2+(4*a*e-2*b*d)*Y+4*f*a-d^2

We consider the parabolic example above, for which Maple finds no solutions without transformation.

P__p; {isolve(P__p)}

2*x^2+4*x*y+2*y^2+x+2*y+7

{}

For the transformed problem, Maple finds an infinite number of solutions

Q__p := eval(Q0, p_params); solXY__p := {isolve(Q__p)}; sol__p := {seq(eval(eval(tr0, p_params), solXY), `in`(solXY, solXY__p))}

X^2+8*Y+55

{{X = 1+8*_Z1, Y = -8*_Z1^2-2*_Z1-7}, {X = 3+8*_Z1, Y = -8*_Z1^2-6*_Z1-8}, {X = 5+8*_Z1, Y = -8*_Z1^2-10*_Z1-10}, {X = 7+8*_Z1, Y = -8*_Z1^2-14*_Z1-13}}

{{x = 17/2+8*_Z1+8*_Z1^2, y = -8*_Z1^2-6*_Z1-8}, {x = 29/2+16*_Z1+8*_Z1^2, y = -8*_Z1^2-14*_Z1-13}, {x = 8*_Z1^2+4*_Z1+7, y = -8*_Z1^2-2*_Z1-7}, {x = 8*_Z1^2+12*_Z1+11, y = -8*_Z1^2-10*_Z1-10}}

Two of the general solutions will not give integer solutions, so could be filtered out, but it is easier to filter after choosing some specific _Z1 values.

eval(sol__p, _Z1 = 0); sol__p0 := select(proc (q) options operator, arrow; eval(x::integer, q) and eval(y::integer, q) end proc, %); eval(sol__p, _Z1 = 5); sol__p5 := select(proc (q) options operator, arrow; eval(x::integer, q) and eval(y::integer, q) end proc, %)

{{x = 7, y = -7}, {x = 11, y = -10}, {x = 17/2, y = -8}, {x = 29/2, y = -13}}

{{x = 7, y = -7}, {x = 11, y = -10}}

{{x = 227, y = -217}, {x = 271, y = -260}, {x = 497/2, y = -238}, {x = 589/2, y = -283}}

{{x = 227, y = -217}, {x = 271, y = -260}}

Check they are solutions to P__p

map2(eval, P__p, `union`(sol__p0, sol__p5))

{0}

NULL

Download DiophantineConics2.mw

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How can I use an if statement inside a do - loop in maple and then plot a figure based on the conditional results? I need help with the correct syntax for combining the do-loop, `if` condition, and plotting command.

Sheet attached below:
Algorithmm.mw

Hi,
I want to have a colorbar aside the curve, but I can't. (My Maple version is 2018).

restart:
with(plots):

# --- constants ---
qc := 0.4:
qh := 0.64:
alpha := 0.8:

# --- parameter ranges ---
deltac_min := 0.01: deltac_max := 0.99:
Tch_min := 0.1:     Tch_max := 1.1:

# --- numerical safety ---
epsDen := 1e-12:
Mcap := 3.0: # cap to avoid infinity

# --- denominator ---
Den := (deltac, Tch) ->
       -2*Tch*deltac*qh - 2*Tch*deltac + 2*Tch*qh
       + 2*deltac*qc + 2*Tch + 2*deltac:

# --- safe functions ---
M1safe := (deltac, Tch) ->
    piecewise(Den(deltac,Tch) > epsDen,
              min(2/sqrt(Den(deltac,Tch)), Mcap),
              Mcap):

M0safe := (deltac, Tch) ->
    piecewise(Den(deltac,Tch) > epsDen,
              min(2*alpha/sqrt(Den(deltac,Tch)), Mcap),
              Mcap):

# --- density plots ---
p1 := densityplot(
       M1safe(deltac,Tch),
       deltac = deltac_min .. deltac_max,
       Tch   = Tch_min .. Tch_max,
       grid  = [200,200],
       style = patchnogrid,
       colorstyle = HUE,
       axes = boxed,
       labels = ["δ_c", "T_ch"],
       title = sprintf("M1(δ_c, T_ch)  (capped at %.2f)", Mcap)
     ):

p2 := densityplot(
       M0safe(deltac,Tch),
       deltac = deltac_min .. deltac_max,
       Tch   = Tch_min .. Tch_max,
       grid  = [200,200],
       style = patchnogrid,
       colorstyle = HUE,
       axes = boxed,
       labels = ["δ_c", "T_ch"],
       title = sprintf("M0(δ_c, T_ch)  (capped at %.2f)", Mcap)
     ):

# --- Contour Den = 0 (to mark physical boundary) ---
cont := contourplot(
          Den(deltac,Tch),
          deltac = deltac_min .. deltac_max,
          Tch   = Tch_min .. Tch_max,
          contours = [0],
          color = black,
          thickness = 2
        ):

# --- Overlay contour ---
p1_final := display(p1, cont):
p2_final := display(p2, cont):

# --- Display side by side ---
display(array([p1_final, p2_final]), scaling = constrained);

@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@

restart;
with(plots):

# === Constants ===
qc := 0.4:
qh := 0.64:
alpha := 0.8:

# === Denominator ===
Den := (deltac, Tch) ->
     -2*Tch*deltac*qh - 2*Tch*deltac + 2*Tch*qh
     + 2*deltac*qc + 2*Tch + 2*deltac:

# === M1 and M0 ===
M1 := (deltac, Tch) -> piecewise(Den(deltac,Tch)>0, 2/sqrt(Den(deltac,Tch)), undefined):
M0 := (deltac, Tch) -> piecewise(Den(deltac,Tch)>0, 2*alpha/sqrt(Den(deltac,Tch)), undefined):

# === Domain ===
deltac_min := 0.05:  deltac_max := 0.95:
Tch_min := 0.01:     Tch_max := 1.10:   # Physically realistic range

# === 3D Plots ===
p1 := plot3d(M1(deltac,Tch),
             deltac=deltac_min..deltac_max,
             Tch=Tch_min..Tch_max,
             grid=[80,80],
             axes=boxed,
             orientation=[-130,45],
             scaling=constrained,
             style=surfacecontour,
             color=green,
             labels=["δ_c", "T_ch", "M1"],
             labelfont=[TIMES,12],
             title="M1(δ_c, T_ch) for qc=0.4, qh=0.64"):

p2 := plot3d(M0(deltac,Tch),
             deltac=deltac_min..deltac_max,
             Tch=Tch_min..Tch_max,
             grid=[80,80],
             axes=boxed,
             orientation=[-130,45],
             scaling=constrained,
             style=surfacecontour,
             color=blue,
             labels=["δ_c", "T_ch", "M0"],
             labelfont=[TIMES,12],
             title="M0(δ_c, T_ch) for α=0.8, qc=0.4, qh=0.64"):

# === Display vertically (M1 above M0) ===
display(Array(1..2, [p1, p2]), insequence=true, scaling=constrained);
display(Array([[p1], [p2]]));

I am using S := sort([sqrt(x2), sqrt(y2), sqrt(z2)]);

restart;
n := 0:
L := []:

for a from 3 to 100 do
    for b from 3 to a do
        c2 := a^2 - a*b + b^2;
        c := isqrt(c2);
        if c^2 = c2 then
            if c < a + b and a < b + c and b < c + a then
                if igcd(a, b, c) = 1 then
                    x2 := (-a^2 + b^2 + c^2)/2;
                    y2 := (a^2 - b^2 + c^2)/2;
                    z2 := (a^2 + b^2 - c^2)/2;
                    if 0 < x2 and 0 < y2 and 0 < z2 then
                        S := sort([sqrt(x2), sqrt(y2), sqrt(z2)]);
                        x := S[1]; 
                        y := S[2]; 
                        z := S[3];
                        n := n + 1;
                        L := [op(L), [x, y, z, sqrt(x^2 + y^2), sqrt(y^2 + z^2), sqrt(x^2 + z^2)]];
                    end if;
                end if;
            end if;
        end if;
    end do;
end do;

n;
L;
 

But I get the result. How can I get the correct result of sort? 

After Maple 2025 start-up (with disabled start-up page) and closing the blank worksheet (note the dark grey workspace) there is still one mserver running (highlighted in yellow).

I have not seen a difference when I kill this process and open a new worksheet which starts a new mserver.exe task (and run Maple code).

The task seems to be inactive (no processor load and memory allocation visible).

Is it a task only used by the interface task (javaw.exe)?
What might be the purpose of this mserver.exe? 

 

Update: The task is inactive in a sense that it does not show immetiate activity when annother mserver.exe task runs (i.e. exceuting a worksheet). However, after a day memory allocation shows changes. When exactly these changes happend is unclear.

Has anyone had any success in turning off the scrollable matrix feature on Mac? I found the post

 https://www.mapleprimes.com/questions/238061-How-To-Disable-The-New-Scrollable-Matrices

and tried to follow the steps outlined by Acer, but I cannot get it to work. Specifically, I greated a preference file at the location:

 //Users/$USER/Library/Preferences/Maple/<version>/Maple preferences which has the statement 

ScrollableMathTableOutput=false

Any success stories, or tips, will be greatly appreciated. 

Thanks. 

I want to ask a question, but I cannot submit it using the link below. I tried several times, but it didn’t work. I wrote it like this, but I didn’t get the desired answer.

http://www.mapleprimes.com/questions/231499-Changing-The-Variables-

NULL

restart:
with(PDEtools):
tr1:={x=xi- lambda*t - delta,u(x,t)=Theta(xi) };


PDE := diff(u(x,t),t) + diff(u(x,t),x) + alpha*u(x,t)^2*diff(u(x,t),x)
      + beta*diff(u(x,t), t, x$2);

ode := dchange(tr1,PDE,[xi,Theta(xi)]);

{x = -lambda*t-delta+xi, u(x, t) = Theta(xi)}

 

diff(u(x, t), t)+diff(u(x, t), x)+alpha*u(x, t)^2*(diff(u(x, t), x))+beta*(diff(diff(diff(u(x, t), t), x), x))

 

diff(Theta(xi), xi)+alpha*Theta(xi)^2*(diff(Theta(xi), xi))

(1)

NULL NULL

Download 963.mw

Hi,

I want to solve the equation shown in the image, along with its given conditions, using Maple and obtain the same results as in the image, but it does not work. Could you please help me?

NULL

restart:
interface(showassumed = 0):


df := diff(w(xi), xi) = rho + eta*w(xi)^2:

 

# Condition (1): rho * eta>0,
assume(rho * eta>0);

w1 := dsolve([df, w(0)=0]);

w(xi) = tan(xi*(rho*eta)^(1/2))*(rho*eta)^(1/2)/eta

(1)
 

 

Download 852.mw

Although several similar problems were asked many years ago (see, e.g., the section “Formal linear algebra” here), there appears to be no new progress so far. It is said that such functionalities exists in the Physics package, but I cannot find any corresponding examples. 
In short, can Maple at present calculate these examples in terms of symbolic array constructs completely automatically?

residue(z^3*cos(1/(z - 2)), z = 2);

                  3       1
         residue(z  cos(-----), z = 2)
                        z - 2

l notice the help document  asks me to increse the n,but the n of essential singularity is infinity

I wrote a simple expand command in Maple - expand(cos((u - 2*k)*x))

only to get the result

2*cos(x*u)*cos(x*k)^2 + 2*sin(x*u)*sin(x*k)*cos(x*k) - cos(x*u)

The presence of a squared term seems to indicate a bug??

I need to compute complicated numerical integral, and my Maple integration does not produce very stable results. Is the a way to do that on line? 

In the below I had to add the assumption x>=0 to get simplifications. Am I wrong with my interpretation that the other assumptions should have been sufficient?

We are looking for the smallest natural number n with the property that both the digit sum Q(n) of the number n and the digit sum Q(n + 1) of the successor of n are divisible by 5.

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