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Two curves which intersect at right angles, ( the angle between the two tangents to the curve) curves at the point of intersection are called orthogonal trajectories. The product of the slopes of the two tangents is -1.

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Can the difference of 2 vectors be orthogonal?

The answer will depend on orthogonal to WHAT!


If you is orthogonal to v and w then is u orthogonal to v plus w?

yes. not sure of the proof though.


What is a vector which is orthogonal to the other vectors and is coplanar with the other vectors called?

In a plane, each vector has only one orthogonal vector (well, two, if you count the negative of one of them). Are you sure you don't mean the normal vector which is orthogonal but outside the plane (in fact, orthogonal to the plane itself)?


Show some details about the set of all orthogonal matrices?

The set of all orthogonal matrices consists of square matrices ( Q ) that satisfy the condition ( Q^T Q = I ), where ( Q^T ) is the transpose of ( Q ) and ( I ) is the identity matrix. This means that the columns (and rows) of an orthogonal matrix are orthonormal vectors. Orthogonal matrices preserve the Euclidean norm of vectors and the inner product, making them crucial in various applications such as rotations and reflections in geometry. The determinant of an orthogonal matrix is either ( +1 ) or ( -1 ), corresponding to special orthogonal matrices (rotations) and improper orthogonal matrices (reflections), respectively.


What is the difference between orthogonal and orthonormal vectors?

All vectors that are perpendicular (their dot product is zero) are orthogonal vectors.Orthonormal vectors are orthogonal unit vectors. Vectors are only orthonormal if they are both perpendicular have have a length of 1.

Related Questions

Self orthogonal trajectories?

a family of curves whose family of orthogonal trajectories is the same as the given family, is called self orthogonal trajectories.


What is self orthogonal?

Self orthogonal trajectories are a family of curves whose family of orthogonal trajectories is the same as the given family. This is a term that is not very widely used.


Why use orthogonal trajectories?

we dont ever


What are the Applications of orthogonal trajectory?

orthogonal trajectories represent the curves in which the magnitude of the velocity or the force is the same at each point on that curve. In the case of the flow field the orthognal trajectories are called the velocity potential and in the case of Force Fileds the orthogonal trajectories are called equipotential curves--curves in which the magnitude of the Force is the same.


What is the definition of orthogonal signal space?

Orthogonal signal space is defined as the set of orthogonal functions, which are complete. In orthogonal vector space any vector can be represented by orthogonal vectors provided they are complete.Thus, in similar manner any signal can be represented by a set of orthogonal functions which are complete.


Can the difference of 2 vectors be orthogonal?

The answer will depend on orthogonal to WHAT!


What is orthogonal planning in ancient Greece?

it is planning of orthogonal planning


When was Orthogonal - novel - created?

Orthogonal - novel - was created in 2011.


What is the orthogonal planning in ancient Greece?

it is planning of orthogonal planning


How do you use Orthogonal in a sentence?

Orthogonal is a term referring to something containing right angles. An example sentence would be: That big rectangle is orthogonal.


What has the author Richard Askey written?

Richard Askey has written: 'Three notes on orthogonal polynomials' -- subject(s): Orthogonal polynomials 'Recurrence relations, continued fractions, and orthogonal polynomials' -- subject(s): Continued fractions, Distribution (Probability theory), Orthogonal polynomials 'Orthogonal polynomials and special functions' -- subject(s): Orthogonal polynomials, Special Functions


What is an orthogonal matrix?

A matrix A is orthogonal if itstranspose is equal to it inverse. So AT is the transpose of A and A-1 is the inverse. We have AT=A-1 So we have : AAT= I, the identity matrix Since it is MUCH easier to find a transpose than an inverse, these matrices are easy to compute with. Furthermore, rotation matrices are orthogonal. The inverse of an orthogonal matrix is also orthogonal which can be easily proved directly from the definition.