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Many other fundamental quantities in science are time derivatives of one another: force is the time derivative of momentum; power is the time derivative of energy; electric current is the time derivative of electric charge; and so on. A common occurrence in physics is the time derivative of a vector, such as velocity or displacement. In dealing ...
The higher order derivatives can be applied in physics; for example, while the first derivative of the position of a moving object with respect to time is the object's velocity, how the position changes as time advances, the second derivative is the object's acceleration, how the velocity changes as time advances. Derivatives can be generalized ...
If the fluent is defined as = (where is time) the fluxion (derivative) at = is: ˙ = = (+) (+) = + + + = + Here is an infinitely small amount of time. [6] So, the term is second order infinite small term and according to Newton, we can now ignore because of its second order infinite smallness comparing to first order infinite smallness of . [7]
Snap, [6] or jounce, [2] is the fourth derivative of the position vector with respect to time, or the rate of change of the jerk with respect to time. [4] Equivalently, it is the second derivative of acceleration or the third derivative of velocity, and is defined by any of the following equivalent expressions: = ȷ = = =.
velocity is the derivative (with respect to time) of an object's displacement (distance from the original position) acceleration is the derivative (with respect to time) of an object's velocity, that is, the second derivative (with respect to time) of an object's position. For example, if an object's position on a line is given by
The derivatives in the table above are for when the range of the inverse secant is [,] and when the range of the inverse cosecant is [,]. It is common to additionally define an inverse tangent function with two arguments , arctan ( y , x ) . {\displaystyle \arctan(y,x).}
In mathematics, the total derivative of a function f at a point is the best linear approximation near this point of the function with respect to its arguments. Unlike partial derivatives , the total derivative approximates the function with respect to all of its arguments, not just a single one.
If the input of the function represents time, then the difference quotient represents change with respect to time. For example, if is a function that takes a time as input and gives the position of a ball at that time as output, then the difference quotient of is how the position is changing in time, that is, it is the velocity of the ball.