Maximizing Potential: Solving for a in a Function with Two Particle Charges

In summary, the conversation discusses a function for calculating potential in a classical over-barrier model, with variables qp and qt representing particle charges. The question is posed about finding dV/da, and the group discusses using the chain rule and sketching the function to find the maximum. It is noted that the function has two variables and the process for finding dV/da is similar to finding it with just one variable. The conversation concludes with a note about using the discriminant to determine the type of critical point.
  • #1
the-rocketman
3
0
I have this function (to calculate potential for classical over-barrier model if you're wondering) where qp and qt are both (different) particle charges:

V(a,R) = -(qp /R) - [qt / (R-a)]

What is dV/da?

The maximum of the function occurs when dV/da = 0, and I need to solve for a. So does solving for a yield R[1 + sqrt(qt/qp)]^-1?

Thanks
 
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  • #2
the-rocketman said:
I have this function (to calculate potential for classical over-barrier model if you're wondering) where qp and qt are both (different) particle charges:

V(a,R) = -(qp /R) - [qt / (R-a)]

What is dV/da?

use the chain rule.
 
  • #3
Hm... but it has 2 variables. I haven't had any multivariable calc.
 
  • #4
what?
try to sketch the function. obviously, the function doesn't have a maximum for any constant R.
what is the question from the beginning?
 
  • #5
R and a are not constants, they are the variables. the constants are the q values
 
  • #6
the-rocketman said:
The maximum of the function occurs when dV/da = 0...
That isn't necessarily true for multivariable functions. Instead, you need to see when the gradient vector [dV/da, dV/dR] = 0 and use the discriminant to tell what type of critical point it is.
 
  • #7
the-rocketman said:
Hm... but it has 2 variables. I haven't had any multivariable calc.

the process is the same. just imagine that R isn't a variable, so long as you want to find dV/da.

(the "d's" should be curly, like so: [tex]\partial[/tex])
 

1. What is a Derivative Particle Problem?

A Derivative Particle Problem is a concept in physics that involves finding the position, velocity, and acceleration of a particle based on its position, velocity, and acceleration at previous points in time. It is essentially the reverse process of finding the derivative of a function in calculus.

2. How is a Derivative Particle Problem solved?

A Derivative Particle Problem is typically solved using a set of equations known as the kinematic equations. These equations involve the particle's initial position, final position, initial velocity, final velocity, and acceleration. By manipulating these equations, the unknown variables can be solved for.

3. What is the importance of understanding Derivative Particle Problems?

Understanding Derivative Particle Problems is important in many areas of science, such as physics, engineering, and astronomy. It allows us to track the motion of objects and predict their future positions, which is crucial in fields like space exploration and transportation.

4. What are some common real-world applications of Derivative Particle Problems?

Derivative Particle Problems can be applied to a variety of real-world scenarios, such as calculating the trajectory of a projectile, predicting the movement of celestial bodies, and determining the speed and acceleration of vehicles in motion. They are also used in robotics and computer animation to simulate realistic movement.

5. Can Derivative Particle Problems be solved using numerical methods?

Yes, Derivative Particle Problems can be solved using numerical methods such as Euler's method or the Runge-Kutta method. These methods involve breaking down the problem into smaller steps and using calculations to approximate the values of the unknown variables at each step, resulting in a numerical solution.

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