Critical points are the points where the gradient is undefined or the gradient is zero (see https://en.wikipedia.org/wiki/Critical_point_(mathematics)). In our case
"\\dfrac{\\partial f}{\\partial x} = 4x^3-4y = 0; \\; \\dfrac{\\partial f}{\\partial y} = 4y^3-4x = 0;"
therefore, "x^3=y \\; \\text{and} \\; y^3=x" , so "(x^3)^3 = x" , "x^9-x = 0" . Therefore, "x(x^8-1) = 0." So the critical points are the following:
"x=0, y=0^3=0, f(x,y) = 1; \\\\\nx =1, y=1^3=1, f(x,y) = -1; \\\\\nx=-1, y=(-1)^3=-1, f(x,y)=-1."
To determine whether the point is critical or not, we should calculate determinant of matrix comprised of partial derivatives of 2nd order.
Let "A = \\dfrac{\\partial^2 f}{\\partial x^2}\\,, \\; C = \\dfrac{\\partial^2 f}{\\partial y^2}\\,, \\; B = \\dfrac{\\partial^2 f}{\\partial x\\partial y}." In our case "A=12x^2\\, \\; C = 12y^2, \\; B = -4."
We should calculate "\\Delta = \\begin{vmatrix}\n A & B \\\\\n B & C\n\\end{vmatrix}= AC-B^2."
1) "x = 0,\\; y=0."
"A=12\\cdot0^2 = 0,\\; C = 12\\cdot0^2 = 0, \\; B = -4."
"\\Delta = AC-B^2 = 0\\cdot0-(-4)^2 = -16 < 0," so there is no extremum, it is a saddle point.
2) "x = 1,\\; y=1."
"A=12\\cdot1^2 = 12,\\; C = 12\\cdot1^2 = 12, \\; B = -4."
"\\Delta = AC-B^2 = 12\\cdot12-(-4)^2 = 128 > 0," so there is an extremum. "A>0," therefore it is local minimum. The matrix is indefinite, so this is a saddle point.
3) "x = -1,\\; y=-1."
"A=12\\cdot(-1)^2 = 12,\\; C = 12\\cdot(-1)^2 = 12, \\; B = -4."
"\\Delta = AC-B^2 = 12\\cdot12-(-4)^2 = 128 > 0," so there is an extremum. "A>0," therefore it is local minimum.
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