flowchart TD
A["dy/dx + P(x)y = F(x)yⁿ"] --> B["If n ≥ 2"]
A --> C["If n = 0 or 1"]
B --> D["Substitute u = y¹⁻ⁿ"]
D --> E["Then use integrating factor method"]
C --> F["Integrating factor method"]
Differential Equations
Differential Equations
Equations in which rates and derivatives are mentioned. We use the operator \(L\) in such equations.
Reference Function
A reference function is one not directly involved in the differentiability of an equation.
Classifications of Differential Equations
1. By Type
- Ordinary Differential Equation (ODE): involves derivatives with respect to a single independent variable.
- Partial Differential Equation (PDE): involves partial derivatives (i.e., with respect to multiple independent variables).
2. By Order
- Refers to the highest derivative in the equation.
- Note: This is not the same as the degree (which refers to the power of the highest derivative term).
3. By Linearity
A differential equation is linear if it is of the form:
\[ a_n(x)\frac{d^n y}{dx^n} + a_{n-1}(x)\frac{d^{n-1} y}{dx^{n-1}} + \cdots + a_1(x)\frac{dy}{dx} + a_0(x)y = g(x) \]
Linearity conditions:
- The dependent variable \(y\) and all its derivatives \(y', y'', \ldots, y^{(n)}\) are of first degree (i.e., raised to the power of 1).
- The coefficients \(a_0(x), a_1(x), \ldots, a_n(x)\) depend only on the independent variable \(x\) (or are constants).
- The term \(g(x)\) depends only on the independent variable \(x\) (or is a constant).
- No products of \(y\) or its derivatives (e.g., \(y \cdot y'\) or \((y'')^2\)).
Notation
Leibniz Notation: \[ \frac{dy}{dx} \]
Newton Notation: \[ y' \]
Solutions of Differential Equations
General Solutions
- A general solution contains arbitrary constants (e.g., \(C_1, C_2\)).
- Particular solutions are derived from the general solution by assigning specific values to these constants, usually determined by initial or boundary conditions. Hence, there are infinitely many particular solutions.
Initial Value Problem (IVP)
- A differential equation where the conditions are specified at a single point (i.e., a specific value of the independent variable). For an \(n\)-th order ODE, \(n\) conditions are given at the same point \(x_0\).
Boundary Value Problem (BVP)
- A differential equation where the conditions are specified at two or more different points (boundaries) of the independent variable. For example, conditions might be given at \(x=a\) and \(x=b\).
Normal Form
The general form of an \(n\)-th order differential equation, solved for the highest derivative:
\[ \frac{d^n y}{dx^n} = f(x, y, y', \dots, y^{(n-1)}) \]
Family of Curves
- The solution curves for a general solution form a family, with each curve corresponding to a different combination of the arbitrary constants.
First Order Differential Equations
Given a first-order differential equation:
\[ \frac{dy}{dx} = f(x, y) \]
This represents the slope of the tangent line to the solution curve at each point \((x, y)\).
Slope Conditions:
- \((\frac{dy}{dx} > 0)\): The function \(y(x)\) is increasing.
- \((\frac{dy}{dx} < 0)\): The function \(y(x)\) is decreasing.
- \((\frac{dy}{dx} = 0)\): The function \(y(x)\) has a local extremum or a horizontal tangent; these points are often called equilibrium points or critical points.
At an equilibrium point: \[ \frac{dy}{dx} = 0 \Rightarrow y = \text{constant} \] (if \(f\) depends only on \(y\))
Autonomous First-Order Equations
An autonomous first-order differential equation is of the form:
\[ \frac{dy}{dx} = f(y) \]
- The derivative depends only on the dependent variable \(y\), not directly on the independent variable \(x\).
- By finding the zeros of the function \(f(y)\) (i.e., \(f(y)=0\)), we can determine:
- Equilibrium points (constant solutions)
- Intervals where \(y(x)\) is increasing (\(f(y)>0\))
- Intervals where \(y(x)\) is decreasing (\(f(y)<0\))
Solution Methods for First-Order Differential Equations
1. Solution by Direct Integration (Separable Equations)
A first-order ODE is separable if it can be written in the form \(dy/dx = G(x)H(y)\), or equivalently: \[ M(x)dx + N(y)dy = 0 \] where the variables can be separated.
Fundamental Theorem of Calculus (as applied to solutions): If \(\frac{dy}{dx} = g(x)\), then the solution is given by: \[ y(x) = y_0 + \int_{x_0}^{x} g(t)\,dt \]
2. Solution by Integrating Factor Method (Linear First-Order ODEs)
Applicable to all linear first-order differential equations (FODE).
Given the general linear first-order ODE: \[ a_1(x)\frac{dy}{dx} + a_0(x)y = g(x) \]
Step 1: Convert to Standard Form Divide by \(a_1(x)\) (assuming \(a_1(x) \ne 0\)): \[ \frac{dy}{dx} + \frac{a_0(x)}{a_1(x)}y = \frac{g(x)}{a_1(x)} \] This is the standard form: \[ \frac{dy}{dx} + P(x)y = f(x) \] where \(P(x) = \frac{a_0(x)}{a_1(x)}\) and \(f(x) = \frac{g(x)}{a_1(x)}\).
Step 2: Find the Integrating Factor \(\mu(x)\) The integrating factor \(\mu(x)\) is defined as: \[ \mu(x) = e^{\int P(x)\,dx} \] (Note: we typically choose the constant of integration to be zero for simplicity, as any constant factor will cancel out).
Step 3: Multiply by Integrating Factor Multiply both sides of the standard form equation by \(\mu(x)\): \[ \mu(x) \frac{dy}{dx} + \mu(x) P(x)y = \mu(x) f(x) \] The left-hand side is now the derivative of a product: \[ \frac{d}{dx}[\mu(x) y] = \mu(x) f(x) \]
Step 4: Integrate Both Sides Integrate with respect to \(x\): \[ \int \frac{d}{dx}[\mu(x) y]\,dx = \int \mu(x) f(x)\,dx \] \[ \mu(x) y = \int \mu(x) f(x)\,dx + C \]
Step 5: Solve for \(y(x)\) \[ y(x) = \frac{1}{\mu(x)} \left[\int \mu(x) f(x)\,dx + C \right] \]
3. Exact Differential Equations
General Form: \[ M(x, y)\,dx + N(x, y)\,dy = 0 \]
A differential equation of this form is exact if there exists a function \(F(x, y)\) such that its total differential \(dF\) is equal to \(M(x, y)\,dx + N(x, y)\,dy\). This means: \[ dF = \frac{\partial F}{\partial x}dx + \frac{\partial F}{\partial y}dy \] So, \(M(x, y) = \frac{\partial F}{\partial x}\) and \(N(x, y) = \frac{\partial F}{\partial y}\).
Test for exactness: For an equation to be exact, the mixed partial derivatives must be equal: \[ \frac{\partial M}{\partial y} = \frac{\partial N}{\partial x} \]
Steps to Solve an Exact Equation: 1. Verify exactness using the test condition. 2. Integrate \(M(x, y)\) with respect to \(x\) (treating \(y\) as a constant) to find \(F(x, y)\): \(F(x, y) = \int M(x, y)\,dx + h(y)\) (where \(h(y)\) is an arbitrary function of \(y\)) 3. Alternatively, integrate \(N(x, y)\) with respect to \(y\) (treating \(x\) as a constant) to find \(F(x, y)\): \(F(x, y) = \int N(x, y)\,dy + k(x)\) (where \(k(x)\) is an arbitrary function of \(x\)) 4. Differentiate the obtained \(F(x, y)\) (from step 2) with respect to \(y\) and set it equal to \(N(x, y)\) to find \(h'(y)\). Integrate \(h'(y)\) to find \(h(y)\). (If using step 3, differentiate with respect to \(x\) and set equal to \(M(x,y)\) to find \(k'(x)\), then integrate for \(k(x)\).) 5. Substitute the found \(h(y)\) (or \(k(x)\)) back into \(F(x, y)\). 6. The general solution is implicitly given by \(F(x, y) = C\), where \(C\) is an arbitrary constant.
4. Integrating Factor for Non-Exact Equations (Special Cases)
If \(M(x, y)\,dx + N(x, y)\,dy = 0\) is not exact, we might be able to find an integrating factor \(\mu(x, y)\) such that \(\mu M\,dx + \mu N\,dy = 0\) is exact.
If \(\mu\) depends only on \(x\): This is possible if \(\frac{\frac{\partial M}{\partial y} - \frac{\partial N}{\partial x}}{N}\) is a function of \(x\) only. Then the integrating factor is: \[ \mu(x) = \exp\left(\int \frac{\frac{\partial M}{\partial y} - \frac{\partial N}{\partial x}}{N} \; dx\right) \]
If \(\mu\) depends only on \(y\): This is possible if \(\frac{\frac{\partial N}{\partial x} - \frac{\partial M}{\partial y}}{M}\) is a function of \(y\) only. Then the integrating factor is: \[ \mu(y) = \exp\left(\int \frac{\frac{\partial N}{\partial x} - \frac{\partial M}{\partial y}}{M} \; dy\right) \]
Other cases for finding \(\mu\) (More advanced/specific): Sometimes an integrating factor can be found in forms like \(\mu(x+y)\), \(\mu(xy)\), or by inspection, but the formulas above are the most common general approaches for non-exact equations. The expressions \(\frac{1}{M_x + N_y}\) or \(\frac{1}{M_y - N_x}\) are not general integrating factors; they might appear in specific contexts or derivations for certain types of non-exact equations, but they are not universal formulas for \(\mu\).
5. Solution by Substitution
a. Homogeneous Equations
A first-order differential equation \(M(x, y) dx + N(x, y) dy = 0\) (or \(dy/dx = f(x,y)\)) is homogeneous if \(M(x,y)\) and \(N(x,y)\) are homogeneous functions of the same degree. A function \(F(x,y)\) is homogeneous of degree \(k\) if \(F(tx, ty) = t^k F(x, y)\) for some constant \(k\).
Substitutions for Homogeneous Equations: - If \(N(x,y)\) is simpler or \(dy/dx = f(x,y)\) is easier to express as \(f(y/x)\): Let \(y = ux \Rightarrow dy = u\,dx + x\,du\). - If \(M(x,y)\) is simpler or \(dx/dy = g(x,y)\) is easier to express as \(g(x/y)\): Let \(x = vy \Rightarrow dx = v\,dy + y\,dv\).
These substitutions transform the homogeneous equation into a separable equation in terms of \(u\) (or \(v\)) and \(x\) (or \(y\)).
b. Bernoulli’s Equation
General form: \[ \frac{dy}{dx} + P(x)y = F(x)y^n \] This is a non-linear first-order ODE.
- If \(n=0\): The equation becomes \(\frac{dy}{dx} + P(x)y = F(x)\), which is a linear first-order ODE solvable by the integrating factor method.
- If \(n=1\): The equation becomes \(\frac{dy}{dx} + P(x)y = F(x)y \Rightarrow \frac{dy}{dx} = (F(x)-P(x))y\), which is a separable equation.
- If \(n \neq 0\) and \(n \neq 1\): Substitution: Let \(u = y^{1-n}\). Then \(\frac{du}{dx} = (1-n)y^{-n}\frac{dy}{dx}\). From the original equation, \(\frac{dy}{dx} = F(x)y^n - P(x)y\). Substitute \(\frac{dy}{dx}\) and \(y = u^{1/(1-n)}\) into the expression for \(\frac{du}{dx}\). This substitution transforms Bernoulli’s equation into a linear first-order ODE in terms of \(u\), which can then be solved using the integrating factor method.
c. Reduction to Separation of Variables (for \(dy/dx = F(Ax + By + C)\))
Given an equation of the form: \[ \frac{dy}{dx} = F(Ax + By + C) \]
- If \(B \neq 0\): Substitution: Let \(u = Ax + By + C\). Then \(\frac{du}{dx} = A + B\frac{dy}{dx}\). So, \(\frac{dy}{dx} = \frac{1}{B}\left(\frac{du}{dx} - A\right)\). Substitute these into the original equation: \(\frac{1}{B}\left(\frac{du}{dx} - A\right) = F(u)\) \(\frac{du}{dx} = B F(u) + A\) This is a separable equation in terms of \(u\) and \(x\).
General Strategy for First-Order ODEs:
- When given \(M(x,y) dx + N(x,y) dy = 0\):
- Check for Exactness: Is \(\frac{\partial M}{\partial y} = \frac{\partial N}{\partial x}\)?
- If Yes: Solve as an exact equation.
- If No: Proceed.
- Check for Homogeneity: Are \(M(x,y)\) and \(N(x,y)\) homogeneous functions of the same degree?
- If Yes: Use substitution (\(y=ux\) or \(x=vy\)) to convert to a separable equation.
- If No: Proceed.
- Check if Linear: Can it be written as \(\frac{dy}{dx} + P(x)y = f(x)\)?
- If Yes: Use the integrating factor method.
- If No: Proceed.
- Check if Bernoulli: Can it be written as \(\frac{dy}{dx} + P(x)y = F(x)y^n\)?
- If Yes: Use the substitution \(u = y^{1-n}\) to convert to a linear equation.
- If No: Proceed.
- Check for \(F(Ax+By+C)\) form: Can it be written as \(\frac{dy}{dx} = F(Ax+By+C)\)?
- If Yes: Use the substitution \(u = Ax+By+C\) to convert to a separable equation.
- If No: Look for an appropriate integrating factor to make it exact (special cases) or it might be a more advanced type of equation.
- Check for Exactness: Is \(\frac{\partial M}{\partial y} = \frac{\partial N}{\partial x}\)?
Error Function
The error function is a special function often encountered in solutions of differential equations related to diffusion or probability. It is defined as: \[ \text{erf}(x) = \frac{2}{\sqrt{\pi}} \int_0^x e^{-t^2} dt \] Its complementary form is: \[ \text{erfc}(x) = 1 - \text{erf}(x) = \frac{2}{\sqrt{\pi}} \int_x^{\infty} e^{-t^2} dt \] - The denominator usually includes \(\sqrt{\pi}\).
Flowcharts for Solution Strategies
Flowchart 1: Solving Bernoulli’s Equation
flowchart TD
A["M(x,y)dx + N(x,y)dy"] --> B["If it is not Homogeneous"]
A --> C["Check if it is Homogeneous"]
B --> D["Then it must be exact"]
D --> E["Otherwise make exact"]
C --> F["If so substitute y=vx then solve as seperable equations"]