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Mathematical optimization studies extrema under constraints.

Completing the square in the optimization constraint givesThe left side is nonnegative, so every feasible point has $x_1^2\ge 4$. Equality is feasible precisely when $x_2=3x_1/2$ and $x_1=\pm 2$. Thus the global minimum isThere is no maximum: for every $|x_1|\ge 2$, the values $x_2=3x_1/2\pm \sqrt{x_1^2/4-1}$ satisfy the optimization constraint, allowing $x_1^2$ to be arbitrarily large. This direct argument also establishes that the two stationary points are the only local minima on the two branches of the constraint curve.