Complex variable - Maximum Modulus Principle

In summary, the function f is continuous on a closed bounded region R, and it is analytic and not constant in the interior of R. The maximum value of |f(z)| in R, which is always reached, occurs smoewhere on the boundary of R and never in the interior.
  • #1
hsong9
80
1

Homework Statement



Let a function f be continuous on a closed bounded region R, and let it be analytic and not constant throughout the interior of R. Assuming that f(z) != 0 anywhere in R, prove that |f(z)| has a minimum value m in R which occurs on the boundary of R and never in the interior. Do this by applying the corresponding result for maximum values to the function g(z) = 1/f(z).

Homework Equations


Corollary. Suppose that a function f is continuous on a closed bounded region R and that it is analytic and not constant in the interior of R. Then the maximum value of |f(z)| in R, which is always reached, occurs smoewhere on the boundary of R and never in the interior.

The Attempt at a Solution


Suppose that g = 1/f is continuous on a closed bounded region R and that it is analytic and not constant in the interior of R. By Corollary, |g(z)| has a maximum value, and
when |g(z)| has the maximum value, |1/g(z)|=|f(z)| has the minimum value. Complete.

Is it right approach?
 
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  • #2
Basically. But you are skimming over an issue. You can't assume g=1/f is analytic. You are only given that f is analytic. You have to prove g is analytic. What might this have to do with the assumption that f(z)!=0 in R?
 
  • #3
Thanks,
I think
since f(z) is not equal to zero, 1/f(z) is entire functino and also anlytic.
Thus I can assume g is analytic...
How about this idea?
 
  • #4
f(z) is only assumed to be nonzero in R. That doesn't make it 'entire', but yes, that's the missing ingredient. g is analytic in R.
 
  • #5
Thanks!
So..
Since f(z) is nonzero in R, g = 1/f is analytic in R.
Is it enough for proving g is analytic?
 
  • #6
You've probably already proved that, haven't you? If a(z)=b(z)/c(z) and c(z0) is not zero, then a(z) is analytic at z=z0. Right?
 

What is the maximum modulus principle in complex variables?

The maximum modulus principle is a fundamental theorem in complex analysis that states that the maximum value of a complex-valued analytic function on a closed and bounded subset of its domain is achieved on the boundary of the subset. In other words, the maximum modulus of a complex function occurs either at a singularity or on the boundary of the domain.

How is the maximum modulus principle used in complex variable analysis?

The maximum modulus principle is used to solve a variety of problems in complex analysis, such as finding the maximum value of a function, determining the location of singularities, and proving the existence of certain types of functions. It is also used to prove other important theorems, such as Liouville's theorem and the fundamental theorem of algebra.

What is the relation between the maximum modulus principle and the Cauchy integral formula?

The maximum modulus principle is closely related to the Cauchy integral formula, which states that the value of an analytic function at any point inside a closed contour can be calculated by integrating the function over the contour. The maximum modulus principle can be used to prove the Cauchy integral formula, and the two principles are often used together to solve problems in complex analysis.

Can the maximum modulus principle be applied to functions with multiple variables?

Yes, the maximum modulus principle can be extended to functions with multiple variables, known as holomorphic functions. The principle states that the maximum value of a holomorphic function on a closed and bounded subset of its domain is achieved on the boundary of the subset, just like in the case of single-variable functions.

Are there any real-world applications of the maximum modulus principle?

Yes, the maximum modulus principle has numerous real-world applications in fields such as physics, engineering, and economics. For example, it can be used to model the flow of fluids around objects, analyze electromagnetic fields, and optimize the production of goods. It is also used in image processing and data compression algorithms.

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