Math Problem Statement
Solution
To solve the problem, we need to find the absolute maximum and minimum of the function subject to the constraint .
Steps to Solve:
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Set up the constraint: The constraint is .
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Use the method of Lagrange multipliers: Introduce a multiplier and solve the equations: where and .
This gives:
Simplify: \lambda = \frac{1}{2x^2} \quad \text{(if x \neq 0)}, \quad \lambda = \frac{1}{2y^2} \quad \text{(if y \neq 0)}.
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Critical points: From symmetry and the constraint, we test or , and also cases when . Substitute into the constraint to find possible critical points.
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Compute at all critical points to find the maximum and minimum values.
Let me calculate these steps and provide the solution.from sympy import symbols, solve, Eq
Define variables
x, y, lambd = symbols('x y lambd')
Function and constraint
f = x2 + y2 # The function g = x4 + y4 - 16 # The constraint
Gradients for Lagrange multipliers
fx = 2 * x fy = 2 * y gx = 4 * x3 gy = 4 * y3
Solve using Lagrange multipliers
eq1 = Eq(fx, lambd * gx) eq2 = Eq(fy, lambd * gy) eq3 = Eq(x4 + y4, 16)
Solve for critical points
critical_points = solve([eq1, eq2, eq3], (x, y, lambd), dict=True)
Evaluate f(x, y) at critical points
results = [] for point in critical_points: x_val = point[x] y_val = point[y] results.append({'x': x_val, 'y': y_val, 'f(x,y)': f.subs({x: x_val, y: y_val})})
Find maximum and minimum values
results_sorted = sorted(results, key=lambda r: r['f(x,y)']) # Sort by f(x, y) results_sorted[{'x': -2**(3/4)I, 'y': -2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': -2**(3/4)I, 'y': 2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': 2**(3/4)I, 'y': -2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': 2**(3/4)I, 'y': 2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': 0, 'y': -2I, 'f(x,y)': -4}, {'x': 0, 'y': 2I, 'f(x,y)': -4}, {'x': -2I, 'y': 0, 'f(x,y)': -4}, {'x': 2I, 'y': 0, 'f(x,y)': -4}, {'x': -2, 'y': 0, 'f(x,y)': 4}, {'x': 0, 'y': -2, 'f(x,y)': 4}, {'x': 0, 'y': 2, 'f(x,y)': 4}, {'x': 2, 'y': 0, 'f(x,y)': 4}, {'x': -2**(3/4), 'y': -2**(3/4), 'f(x,y)': 4sqrt(2)}, {'x': -2**(3/4), 'y': 2**(3/4), 'f(x,y)': 4sqrt(2)}, {'x': 2**(3/4), 'y': -2**(3/4), 'f(x,y)': 4sqrt(2)}, {'x': 2**(3/4), 'y': 2**(3/4), 'f(x,y)': 4sqrt(2)}][{'x': -2**(3/4)I, 'y': -2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': -2**(3/4)I, 'y': 2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': 2**(3/4)I, 'y': -2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': 2**(3/4)I, 'y': 2*(3/4)I, 'f(x,y)': -4sqrt(2)}, {'x': 0, 'y': -2I, 'f(x,y)': -4}, {'x': 0, 'y': 2I, 'f(x,y)': -4}, {'x': -2I, 'y': 0, 'f(x,y)': -4}, {'x': 2I, 'y': 0, 'f(x,y)': -4}, {'x': -2, 'y': 0, 'f(x,y)': 4}, {'x': 0, 'y': -2, 'f(x,y)': 4}, {'x': 0, 'y': 2, 'f(x,y)': 4}, {'x': 2, 'y': 0, 'f(x,y)': 4}, {'x': -2**(3/4), 'y': -2**(3/4), 'f(x,y)': 4sqrt(2)}, {'x': -2**(3/4), 'y': 2**(3/4), 'f(x,y)': 4sqrt(2)}, {'x': 2**(3/4), 'y': -2**(3/4), 'f(x,y)': 4sqrt(2)}, {'x': 2**(3/4), 'y': 2**(3/4), 'f(x,y)': 4sqrt(2)}]success
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Math Problem Analysis
Mathematical Concepts
Multivariable Calculus
Lagrange Multipliers
Optimization
Algebra
Formulas
f(x, y) = x^2 + y^2
Constraint: x^4 + y^4 = 16
Lagrange Multipliers: ∇f = λ∇g
Theorems
Lagrange Multipliers
Symmetry in Optimization
Suitable Grade Level
College Level (Calculus III or Advanced Calculus)
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