Implicitly Defined Curve: Tangent Line at (1,1,1) and Parameterized Derivatives

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In summary, to find the equation for the tangent line to the curve at the given point, take d/dx of both equations and differentiate implicitly, then put x=1, y=1 and z=1. This will give two equations in two unknowns for dy/dx and dz/dx. To find the formula for dy/dt and d2y/dt2, consider the geometric interpretation of the curve being contained in a plane and in the other surface, and use the gradient and acceleration vector to find the direction and magnitude of the tangent vector.
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Homework Statement



The curve t(t) passing thru the point (1,1,1) is defined implicitly by:

x2y + y2x + xyz + z2 = 4
and
x + y + z = 3

a) find the equation for the tangent line to this curve at the given point
b) assume you may choose x=t as the parameter. Find the formula for:

dy/dt and d2y/dt2


The Attempt at a Solution



I honestly have no idea where to start! Can anyone give me hints to get me going? Ty.
 
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Any hints?
 
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Ok, take x to be the parameter. So consider y(x) and z(x) to be functions of x. Take d/dx of both equations and differentiate implicitly. Then put x=1, y=1 and z=1. Doesn't that give you two equations in two unknowns for dy/dx and dz/dx? If you solve for them, then the tangent vector is (dx/dx,dy/dx,dz/dx)=(1,dy/dx,dz/dx), correct?
 
  • #4
i'm assuming you don't just want to substitute in, I haven't worked it through totally, but here's some geomteric interpretation I hope helps

the curve is contained in a plane, so its tangent vector will be parallel to the plane, so perpindicular to the normal of the plane

the curve is also contained in the other surface, so its tangent vector will be parallel to its tangent surface, consider a level surface of the function
F(x,y,z) = x^2y + y2x + xyz + z^2 - 4

taking the gradient of will give will give the rate of maximum change, perpindicular to the surface's tangent plane.

you know have two vectors perpindicular to the tangent vector, so you can find the direction of the tangent vector - this will give the relative lengths of dx/dt, dy/dt, dz/dt

now y" = d^2y/dt^2 is a bit trickier, but you know:
- as the curve is contained in a plane you know its acceleration vector must also be parallel to the plane..
- x" is zero,
these 2 should be enough to get the direction, though not too sure on the magnitude... any ideas..? maybe implicit differentiation of the first function?
 

1. What is the definition of a curve defined implicitly?

A curve defined implicitly is a mathematical equation that describes a curve without explicitly stating the relationship between the x and y coordinates. It is typically represented by an equation in the form of F(x,y) = 0.

2. How is a curve defined implicitly different from a curve defined explicitly?

A curve defined implicitly does not explicitly state the relationship between the x and y coordinates, while a curve defined explicitly does. In other words, an implicit curve is described by an equation that does not have y explicitly written in terms of x, while an explicit curve has y written in terms of x.

3. What are the advantages of using an implicit curve?

One advantage of using an implicit curve is that it can represent more complex shapes and curves that may not be easily described by an explicit equation. It also allows for more flexibility and precision in graphing and analyzing curves.

4. How do you graph an implicit curve?

To graph an implicit curve, you can use a graphing calculator or software that has the capability to plot implicit equations. Alternatively, you can plot points by substituting different values of x and solving for y to create a table of values, and then plot those points on a graph.

5. Are there any real-life applications of implicit curves?

Yes, implicit curves have various real-life applications, such as in computer graphics, engineering, and physics. For example, implicit curves can be used to represent the shapes of objects in 3D modeling software, or to model the trajectory of a projectile in physics. They are also commonly used in optimization problems to find the maximum or minimum value of a function.

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