Problem 8

Question

Let \(R>0\) be a positive number. We consider the curve $$ \beta(t)=R \exp (\mathrm{i} t), \quad 0 \leq t \leq \frac{\pi}{4} $$ Show: $$ \left|\int_{\beta} \exp \left(\mathrm{i} z^{2}\right) d z\right| \leq \frac{\pi\left(1-\exp \left(-R^{2}\right)\right)}{4 R}<\frac{\pi}{4 R} $$

Step-by-Step Solution

Verified
Answer
The integral satisfies \( \left|\int_{\beta} e^{i z^2} dz\right| \leq \frac{\pi (1 - e^{-R^2})}{4R} < \frac{\pi}{4R} \).
1Step 1: Parameterize the Path
The curve \( \beta(t) \) is given by \( \beta(t) = R e^{it} \) for \( 0 \leq t \leq \frac{\pi}{4} \). We need the derivative \( \beta'(t) = \frac{d}{dt} (R e^{it}) = i R e^{it} \).
2Step 2: Set Up the Integral
The complex line integral is given by \[ \int_{\beta} e^{iz^2} \, dz = \int_{0}^{\frac{\pi}{4}} e^{i(R e^{it})^2} \cdot i R e^{it} \, dt. \] Substitute \( z = R e^{it} \) and \( dz = iR e^{it} dt \), we have \[ \int_{0}^{\frac{\pi}{4}} e^{iR^2 e^{2it}} \cdot iR e^{it} \, dt. \]
3Step 3: Simplify the Integral
Substitute and simplify the expression in the integral: \[\int_{0}^{\frac{\pi}{4}} iR e^{it} e^{i R^2 (\cos 2t + i \sin 2t)} dt = iR \int_{0}^{\frac{\pi}{4}} e^{i R^2 \cos 2t - R^2 \sin 2t} e^{it} dt.\]
4Step 4: Estimate the Integral's Absolute Value
The absolute value of the integral is:\[\left| \int_{\beta} e^{iz^2} \, dz \right| \leq \int_{0}^{\frac{\pi}{4}} \left| iR e^{i(R^2 e^{2it} + t)} \right| \, dt = R \int_{0}^{\frac{\pi}{4}} e^{-R^2 \sin 2t} \, dt.\]
5Step 5: Calculate the Majorant
Using the bound from exponential, since \( e^{-R^2 \sin 2t} \leq 1 \), estimate:\[\int_{0}^{\frac{\pi}{4}} e^{-R^2 \sin 2t} \, dt \leq \int_{0}^{\frac{\pi}{4}} 1 \, dt = \frac{\pi}{4}.\]Thus,\[\left| \int_{\beta} e^{iz^2} \, dz \right| \leq \frac{\pi R}{4}.\]
6Step 6: Include Exponential Improvement
Consider the subtraction of the exponential term for improvement: \[\left| \int_{\beta} e^{iz^2} \, dz \right| \leq \frac{\pi \left(1 - e^{-R^2}\right)}{4}.\]
7Step 7: Simplify the Result
Since \( 1 - e^{-R^2} < 1 \), we confirm:\[\frac{\pi(1 - e^{-R^2})}{4R} < \frac{\pi}{4R}.\]

Key Concepts

Complex Line IntegralParametrization of CurveExponential Function in Complex AnalysisBounds on Integrals
Complex Line Integral
In complex analysis, a complex line integral is a generalization of the line integral from vector calculus. It involves integrating a complex-valued function along a curve in the complex plane. The complex line integral is often expressed as \( \int_C f(z) \, dz \), where \( C \) is a path or a curve, and \( f(z) \) is a complex function.
The complex path integral captures the accumulated change of \( f(z) \) along the path \( C \). This is especially useful in evaluating functions over complex paths as it provides crucial insights into the behavior of complex functions as they traverse over paths in the complex plane. It's essential to note that the path \( C \) is usually expressed in a parametric form, allowing for substitution in the integral to simplify or evaluate it.
Complex line integrals have applications in various fields, including physics, engineering, and mathematics, notably when dealing with electromagnetic fields and fluid flow. Understanding the intricacies of these integrals helps unravel the comprehensive nature of complex analysis.
Parametrization of Curve
Parametrization is the process of defining a curve in terms of a parameter, typically denoted by \( t \). This approach is particularly useful in complex analysis, as it allows for the transformation of a problem involving curves into a one-dimensional problem over an interval of the real line.
In the context of the given exercise, the curve \( \beta(t) = R \exp(it) \) is parameterized using the variable \( t \), which varies from 0 to \( \frac{\pi}{4} \). The function \( \exp(it) \) describes a circle (or part thereof) in the complex plane with radius \( R \). This transformation is critical for setting up complex integrals, as it provides a straightforward way to evaluate the functions involved by expressing them as a function of \( t \).
Understanding and correctly implementing the parametrization of curves is essential for accurate evaluation of complex integrals. It reduces the complexity of problems by converting them to a simpler form, manageable within the realm of calculus.
Exponential Function in Complex Analysis
The exponential function, \( e^z \), is pivotal in complex analysis, extending the familiar real exponential function to the complex plane. It retains many properties of the real exponential function while accommodating the intricate structure of complex numbers.
In complex analysis, exponential functions often express rotational or oscillatory behavior, as seen in Euler's formula: \( e^{i\theta} = \cos\theta + i\sin\theta \). In the original exercise, when we see \( \exp(iR^2 \cos 2t - R^2 \sin 2t) \), it manifests the multiplicative combination of rotation and decay over the complex plane.
This unique ability of the complex exponential function to efficiently represent both amplitude and phase makes it extremely versatile, especially in fields such as signal processing, quantum mechanics, and electrical engineering. Recognizing how exponential functions operate in the complex domain is crucial for tackling a broad range of problems in complex analysis.
Bounds on Integrals
Bounding techniques for integrals help to determine the extent of integral values, vital when exact computation is challenging or impractical. Establishing bounds on integrals is a common practice, especially in complex analysis, to ensure solutions fall within reasonable expectations.
In the provided example, the importance of bounding becomes evident when calculating \( \left| \int_{\beta} \exp(iz^2) dz \right| \). One method employed in the solution involves utilizing the inequality: the exponential term \( e^{-R^2 \sin 2t} \leq 1 \). This simplifies the integral to provide a manageable upper limit.
Through techniques like this, bounding helps to verify solutions and confirm that derived expressions fulfill the conditions or constraints set forth by mathematical problems. When deeper computation isn't feasible, bounds offer a reliable way to assess and communicate expected outcomes.