Solving the logistic differential equation part 1 | Khan Academy

Khan Academy
24 Jul 201413:38
EducationalLearning
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TLDRIn the video script, the presenter delves into solving the logistic differential equation, a model for population growth that accounts for limited resources. They begin by reviewing constant solutions, such as the scenario where the population is zero or at the maximum sustainable level, where the rate of change is zero. The presenter then explores the possibility of a non-constant solution where the population starts below the maximum sustainable level. They introduce the concept of the separable differential equation and proceed to solve it using partial fraction expansion. The process involves taking the anti-derivative of both sides with respect to time, which leads to the natural logarithm of the population size and its relation to the carrying capacity. The presenter successfully simplifies the equation, bringing the audience closer to finding the analytic expression for the population over time. The video concludes with the promise of continuing the solution in the next installment, leaving viewers intrigued and eager for more.

Takeaways
  • ๐Ÿ“ The logistic differential equation models population growth with a carrying capacity K, where the growth rate decreases as the population size N approaches K.
  • โน At N=0, the rate of population change is zero, as there are no individuals to reproduce, which is consistent with real-world scenarios.
  • ๐Ÿ”„ When the population N equals the carrying capacity K, the growth rate is also zero, leading to a constant solution where the population remains at its maximum sustainable level.
  • ๐Ÿ“ˆ For initial conditions where N is between 0 and K, the rate of change of the population is proportional to N, leading to growth that approaches the carrying capacity asymptotically.
  • ๐Ÿงฉ The logistic equation is separable, allowing for an analytical solution by separating variables and integrating both sides with respect to time t.
  • โœ… The partial fraction expansion technique is used to simplify the equation into two fractions, which can be more easily integrated.
  • ๐Ÿ“‰ The anti-derivatives of 1/N and ln|N| are used to find the integral of the separated equation, with the latter being a natural logarithm whose derivative is 1/N.
  • ๐Ÿ”€่ฟ็”จ้“พๅผๆณ•ๅˆ™(Chain Rule)ๆฅๆ‰พๅˆฐๅคๅˆๅ‡ฝๆ•ฐ็š„ๅฏผๆ•ฐ๏ผŒ่ฟ™ๅฏนไบŽ่งฃๅ†ณๆถ‰ๅŠNๅ’Œๆ—ถ้—ดt็š„่กจ่พพๅผๆ˜ฏ่‡ณๅ…ณ้‡่ฆ็š„ใ€‚
  • ๐Ÿšซ Assumption is made that N(t) is always between 0 and K, ensuring that terms involving N remain positive and valid within the logistic model's context.
  • ๐Ÿ”ข The integration with respect to t results in an equation involving natural logarithms of N and (1 - N/K), leading to a general form of the solution for N(t).
  • ๐Ÿ”„ The process involves finding constants A and B through partial fraction decomposition, where A/N + B/(1 - N/K) equals 1/N * (1 - N/K).
  • โฉ The final solution for N(t) is approached but will be completed in a subsequent video, highlighting the iterative and stepwise nature of solving differential equations.
Q & A
  • What is the logistic differential equation?

    -The logistic differential equation is a mathematical model used to describe population growth when the growth rate is not constant but depends on the size of the population. It is often used to model growth where there is a limited carrying capacity, such as in an environment that can only sustain a certain maximum population size.

  • What are the two constant solutions for the logistic differential equation mentioned in the script?

    -The two constant solutions mentioned are: 1) N(t) = 0, which represents a scenario where the population remains at zero, as there are no individuals to reproduce. 2) N(t) = K, which represents a scenario where the population remains at the maximum sustainable size K, as the growth rate becomes zero once the population reaches this size.

  • What is the significance of the constant r in the logistic differential equation?

    -The constant r in the logistic differential equation represents the intrinsic growth rate of the population. It is a positive constant that, when multiplied by the population size N, gives the number of individuals able to reproduce at any given time.

  • How does the logistic differential equation account for environmental carrying capacity?

    -The logistic differential equation accounts for environmental carrying capacity through the term '1 - N/K'. As the population size N approaches the carrying capacity K, the term '1 - N/K' approaches zero, which in turn reduces the growth rate of the population, preventing it from exceeding the environment's carrying capacity.

  • What is a Malthusian mindset in the context of population growth?

    -A Malthusian mindset refers to the idea that population growth can outstrip the means of subsistence, leading to a crisis. It is named after Thomas Malthus, who argued that population growth tends to increase geometrically (exponentially), while the food supply tends to increase arithmetically, which could lead to a shortage of resources.

  • What is the process of partial fraction expansion and why is it used in the script?

    -Partial fraction expansion is a technique used in mathematics to break down a complex fraction into simpler fractions, typically when dealing with rational functions. In the script, it is used to simplify the expression for further integration and to make it easier to find the anti-derivative required to solve the logistic differential equation.

  • What is the significance of the natural logarithm in solving the logistic differential equation?

    -The natural logarithm is used to find the anti-derivatives of the terms '1/N' and '1/(1 - N/K)'. Knowing the anti-derivatives allows the integration of these terms with respect to time, which is a crucial step in solving the logistic differential equation and finding the function N(t).

  • What is the role of the constant C in the general solution of the logistic differential equation?

    -The constant C in the general solution represents an arbitrary constant of integration, which arises when integrating differential equations. It accounts for the initial conditions or the specific path the solution takes, and different values of C will yield different particular solutions to the logistic differential equation.

  • What is the assumption made about N(t) in the script?

    -The assumption made about N(t) in the script is that it is always less than K and greater than zero (N(t) < K and N(t) > 0). This assumption ensures that the population size remains within the bounds of the environment's carrying capacity and above zero.

  • How does the logistic differential equation model population growth that is more consistent with a Malthusian mindset?

    -The logistic differential equation models population growth that accounts for limited resources, which is more consistent with a Malthusian mindset. It incorporates a carrying capacity K, which represents the maximum population size that the environment can sustain, thus preventing unlimited exponential growth.

  • What is the next step after finding the anti-derivatives in the logistic differential equation?

    -The next step after finding the anti-derivatives is to solve for N(t) by integrating both sides of the equation with respect to time and applying any given initial conditions to find the particular solution that fits the specific population scenario being modeled.

Outlines
00:00
๐Ÿ“ Introduction to the Logistic Differential Equation

The video begins with an attempt to solve the logistic differential equation, which models population growth with a carrying capacity. The presenter reviews constant solutions, such as N(t) = 0 (no growth) and N(t) = K (maximum sustainable population). The focus then shifts to the possibility of a dynamic solution where the initial population is between these two constants. The logistic equation is identified as a separable differential equation, and the presenter starts to manipulate it to find an analytic expression for N(t), which would represent a more realistic growth model.

05:01
๐Ÿ” Partial Fraction Expansion and Integration

The presenter continues by separating the logistic differential equation and performing a partial fraction expansion to simplify the equation. This step involves finding constants A and B such that A/N + B/(1 - N/K) equals the right side of the equation. Through algebraic manipulation, A is determined to be 1 and B is found to be 1/K. The equation is then rewritten in a more integrable form. The presenter highlights the importance of recognizing the integral of 1/N and using the chain rule to find the derivative of the natural logarithm of (1 - N/K) with respect to N, which is crucial for the next steps in solving the differential equation.

10:02
๐Ÿงฎ Integration and Solution Assumptions

The video script outlines the process of taking the anti-derivative of both sides of the equation with respect to time, t. The presenter assumes N(t) is always positive and less than the carrying capacity K, which simplifies the natural logarithms involved. By integrating, the presenter arrives at an equation involving the natural logarithm of the absolute value of N and (1 - N/K), equal to a constant plus r times t. The presenter then subtracts a constant (C1) from both sides to isolate the natural logarithm terms, leading to a general form of the solution. The video concludes with a teaser for the next video, where the presenter is eager to finalize the solution for N(t).

Mindmap
Keywords
๐Ÿ’กLogistic Differential Equation
The logistic differential equation is a mathematical model used to describe population growth in an environment with limited resources. It is a modification of the exponential growth model that incorporates a carrying capacity, which is the maximum population size that the environment can sustain. In the video, the logistic differential equation is the central theme, as the speaker attempts to find a solution for it.
๐Ÿ’กConstant Solutions
Constant solutions refer to the scenarios where the population size does not change over time. In the context of the logistic differential equation, two constant solutions are identified: N(t) = 0, where the population size is zero and thus remains unchanged, and N(t) = K, where K is the carrying capacity and the population size remains at its maximum sustainable level. These solutions are important as they represent boundary conditions of the model.
๐Ÿ’กPartial Fraction Expansion
Partial fraction expansion is a technique used in mathematics to decompose a complex fraction into simpler parts. In the video, the speaker uses this technique to simplify the expression obtained from the logistic differential equation. By finding suitable constants A and B, the fraction is broken down to help find the anti-derivative, which is crucial for solving the differential equation.
๐Ÿ’กAnti-Derivative
An anti-derivative, also known as an integral, represents the reverse operation to differentiation. It is used to find the original function when given its derivative. In the video, the speaker takes the anti-derivative of expressions involving the population size N with respect to time t, which is a step towards solving the logistic differential equation and finding the function N(t).
๐Ÿ’กNatural Logarithm
The natural logarithm is the logarithm to the base e (approximately equal to 2.71828). It is used in mathematics and physics for a variety of applications, including solving differential equations. In the video, the natural logarithm appears when taking the anti-derivative of certain expressions related to the population size N, which helps in integrating the logistic differential equation.
๐Ÿ’กSeparable Differential Equation
A separable differential equation is a type of ordinary differential equation that can be written in a form that allows the variables to be separated on different sides of the equation, often simplifying the process of solving the equation. The logistic differential equation is noted as separable in the video, which means it can be solved by separating the variables N and t and then integrating.
๐Ÿ’กRate of Change
The rate of change, in the context of the logistic differential equation, refers to how the population size N changes over time t. It is represented by the derivative dN/dt. Understanding the rate of change is essential for modeling population dynamics, as it shows how the population grows or declines in response to its current size and the carrying capacity K.
๐Ÿ’กCarrying Capacity (K)
The carrying capacity, denoted as K in the logistic differential equation, is the maximum population size that the environment can sustain indefinitely. It is a key parameter in the model that determines the upper limit of population growth. In the video, K is used to describe the scenario where the population size reaches its maximum sustainable level and stops growing.
๐Ÿ’กAsymptote
An asymptote is a line that a curve approaches but never actually intersects. In the context of the logistic differential equation, the term is used to describe the behavior of the population size N(t) as it approaches the carrying capacity K. The speaker suggests that the population growth will asymptotically approach K, meaning it will get closer and closer to K without ever exceeding it.
๐Ÿ’กInitial Condition
An initial condition is a fixed value or condition that applies at the starting point of a problem, in this case, the starting population size N(0) when time t equals zero. The initial condition is crucial for solving differential equations as it provides the necessary information to determine the unique solution that fits the model's behavior over time.
๐Ÿ’กMalthusian Mindset
The Malthusian mindset refers to the idea that population growth tends to increase geometrically, while the means of subsistence, such as food production, only increase arithmetically. This concept, named after Thomas Malthus, suggests that population growth can outstrip the ability of the environment to support it. In the video, the speaker mentions this mindset as a contrasting view to the logistic growth model, which incorporates environmental constraints.
Highlights

The logistic differential equation is being explored for solutions.

Constant solutions for N(t) = 0 and N(t) = K are identified, representing no population growth and maximum sustainable population, respectively.

The scenario where the initial condition is between zero and the environmental carrying capacity is considered.

The rate of change of the population is found to be proportional to N and approaches zero as N approaches the carrying capacity K.

A potential solution is hypothesized where the population asymptotically approaches the carrying capacity K.

The differential equation is recognized as separable, simplifying the process of finding N(t).

Partial fraction expansion is used to simplify the equation and find an expression for the anti-derivative.

The integration of 1/N and 1/(1 - N/K) with respect to N is performed to find the anti-derivatives.

The natural logarithm of the absolute value of N and (1 - N/K) are identified as the anti-derivatives.

Integration with respect to time t is carried out to progress towards finding N(t).

The assumption is made that N(t) is always between zero and K, ensuring the natural logarithm arguments are positive.

An arbitrary constant C is introduced to account for the integration constant.

The process of solving for N(t) is continued in the next video due to the complexity and length of the explanation.

The approach to solving the logistic differential equation is a blend of differential calculus, algebra, and partial fraction decomposition.

The potential application of the logistic differential equation in modeling population growth with environmental constraints is discussed.

The solution process is detailed, emphasizing the step-by-step mathematical operations and assumptions made.

The video concludes with a teaser for the next part of the solution, maintaining viewer engagement and interest.

Transcripts
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