Nabla math

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Nabla math

The term "gradient" has several meanings in mathematics. The simplest is as a synonym for slope. The more general gradient, called simply "the" gradient in vector analysis, is a vector operator denoted and sometimes also called del or nabla. It is most often applied to a real function of three variablesand may be denoted. For general curvilinear coordinatesthe gradient is given by.

The direction of is the orientation in which the directional derivative has the largest value and is the value of that directional derivative. Furthermore, ifthen the gradient is perpendicular to the level curve through if and perpendicular to the level surface through if.

For a matrix. For expressions giving the gradient in particular coordinate systems, see curvilinear coordinates. Arfken, G. Orlando, FL: Academic Press, pp. Kaplan, W. Reading, MA: Addison-Wesley, pp. Morse, P. New York: McGraw-Hill, pp.

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nabla math

The best answers are voted up and rise to the top. Laplace's Equation Symbol [closed] Ask Question. Asked 5 years, 6 months ago. Active 1 year, 4 months ago. Viewed k times. MasterScrat 3 3 bronze badges. Load amsmath package. Can you show an example of non working code? This question appears to be off-topic because it is about MathJax. Active Oldest Votes. Daniel Daniel 5 5 silver badges 8 8 bronze badges. This is nice, but the question itself is 'off-topic', since it is concerned with a a typo on Physics.

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Hot Network Questions.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It only takes a minute to sign up. First up, this question differs from the other ones on this site as I would like to know the isolated meaning of nabla if that makes sense.

Meanwhile, other questions might ask what it means in relation to something else. This might be a very stupid question; it's hard to tell when I struggle to understand what it indicates, and thus this might seem very idiotic for a person fully knowledgeable about its meaning. Currently I interpret the nabla symbol as a way of turning something into a vector. Is my understanding correct? Anyway, what is the meaning of it, and why is it used? Please try and describe it as simple as possible.

In case there should exist multiple meanings of this symbol, this is the context: I stumbled upon this symbol when researching neural networks C denotes the cost function :.

Nabla is a vector whose components are operators. How you've described it, it's used as the gradient of a function in multivariable calculus. By itself, the nabla can be thought of as a vector of partial derivative operators, and when applied to a multivariable function, it represents the vector of partial derivatives of each component dot product and the direction of steepest ascent for some input:.

The nabla can be applied to a number of different areas in multivariable calculus, such as divergence or curl.

In all these cases, the nabla can be treated like a vector which you can dot or cross with another vector, such as a multivariable function. That said, it is an operator. Well, instead of defining these terms directly, let me give the motivation for how they relate to the nabla. Let's consider the 1D case first, i.

Your function itself may have some whacky wavy course that makes it hard to do much with it, but locally i. This approximation is a truncated Taylor expansion. Its slope is the derivative of the function. Now the dot and cross operations are also short-hand and are labelled as such because they act on vectors in a similar fashion that the respective products do.

In simple terms, it is a function that takes in many inputs or vectors and spits out just a real number. So now we answer the question, "In order to move downhill from my current location, which direction should I move to? Which is the recursive formula for gradient descent that you have probably seen already but the gradient term was scaled by a very small value referred to as the "learning rate".

Div and Curl of Vector Fields in Calculus

What this does is make the process take smaller steps in the given direction in order to minimise the chances that it runs past the minimum converging better and not oscillate around the minimum. Now keep in mind that when working with such algorithms, it is very common to see the implementation of heuristic techniques in order to lessen the processing power requirement.

For example:. Since this will eventually get scaled down by the learning rate anyway, the factor of 2 or any other constant scalar is usually omitted since it does not contain any information about the direction downhill.The fountain of wisdom. Publisher of books and software in mathematics and computer science. Home Preface Report Register About us. Let's set up the missing cornerstone!

Let's reveal all three methods. Inversely, by plugging the coordinates of translations into the source polynomial function, i. Note that the complete source polynomial has n - 1 terms, missing second and the absolute term. About us. Quench your thirst for knowledge! A revealing insight into the polynomial function.

Every polynomial function has its initial position at the origin of the coordinate system. There are three methods to transform an n -th degree polynomial written in the general form. Each method is based on the fact that a polynomial written in general form represents translation of its source original function in the direction of the coordinate axes, where the coordinates of translations are. First method. Second method.

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The coefficients aof the source polynomial function are related to corresponding value of the derivative of the given polynomial at x 0like coefficients of the Taylor polynomial in Taylor's or Maclaurin's formula, thus. Observe that coefficients of the source polynomial function define the value and the direction of the vertical translation of successive derivatives of given polynomial that is. Trigonometry 1 Applications of Trigonometry :.

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Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It only takes a minute to sign up. Sign up to join this community. The best answers are voted up and rise to the top. Home Questions Tags Users Unanswered. Definition of Nabla Operator Ask Question. Asked 4 years, 4 months ago. Active 1 year, 9 months ago. Viewed times.

Scientifica 8, 4 4 gold badges 14 14 silver badges 37 37 bronze badges. Active Oldest Votes. Christian Blatter Christian Blatter k 12 12 gold badges silver badges bronze badges. I have a hard time following your argumentation to be honest.

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Hot Network Questions. Question feed. Mathematics Stack Exchange works best with JavaScript enabled.The gradient vector can be interpreted as the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point pthe direction of the gradient is the direction in which the function increases most quickly from pand the magnitude of the gradient is the rate of increase in that direction.

The gradient thus plays a fundamental role in optimization theorywhere it is used to maximize a function by gradient ascent. Consider a room where the temperature is given by a scalar fieldTso at each point xyz the temperature is T xyzindependent of time. At each point in the room, the gradient of T at that point will show the direction in which the temperature rises most quickly, moving away from xyz.

The magnitude of the gradient will determine how fast the temperature rises in that direction. Consider a surface whose height above sea level at point xy is H xy. The gradient of H at a point is a plane vector pointing in the direction of the steepest slope or grade at that point. The steepness of the slope at that point is given by the magnitude of the gradient vector.

The gradient can also be used to measure how a scalar field changes in other directions, rather than just the direction of greatest change, by taking a dot product. More generally, if the hill height function H is differentiablethen the gradient of H dotted with a unit vector gives the slope of the hill in the direction of the vector, the directional derivative of H along the unit vector. The gradient or gradient vector field of a scalar function f x 1x 2x 3The notation grad f is also commonly used to represent the gradient.

The gradient of f is defined as the unique vector field whose dot product with any vector v at each point x is the directional derivative of f along v. That is. Formally, the gradient is dual to the derivative; see relationship with derivative.

When a function also depends on a parameter such as time, the gradient often refers simply to the vector of its spatial derivatives only see Spatial gradient. The magnitude and direction of the gradient vector are independent of the particular coordinate representation. In the three-dimensional Cartesian coordinate system with a Euclidean metricthe gradient, if it exists, is given by:.

For example, the gradient of the function. In some applications it is customary to represent the gradient as a row vector or column vector of its components in a rectangular coordinate system; this article follows the convention of the gradient being a column vector, while the derivative is a row vector.

In cylindrical coordinates with a Euclidean metric, the gradient is given by: [19]. In spherical coordinatesthe gradient is given by: [19]. For the gradient in other orthogonal coordinate systemssee Orthogonal coordinates Differential operators in three dimensions. We consider general coordinateswhich we write as x 1Here, the upper index refers to the position in the list of the coordinate or component, so x 2 refers to the second component—not the quantity x squared. The index variable i refers to an arbitrary element x i.

Using Einstein notationthe gradient can then be written as:. The latter expression evaluates to the expressions given above for cylindrical and spherical coordinates. While these both have the same components, they differ in what kind of mathematical object they represent: at each point, the derivative is a cotangent vectora linear form covector which expresses how much the scalar output changes for a given infinitesimal change in vector input, while at each point, the gradient is a tangent vectorwhich represents an infinitesimal change in vector input.

Computationally, given a tangent vector, the vector can be multiplied by the derivative as matriceswhich is equal to taking the dot product with the gradient:. The function dfwhich maps x to df xis called the total differential or exterior derivative of f and is an example of a differential 1-form.

Much as the derivative of a function of a single variable represents the slope of the tangent to the graph of the function, [20] the directional derivative of a function in several variables represents the slope of the tangent hyperplane in the direction of the vector.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

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nabla math

It only takes a minute to sign up. But the Nabla-Operator is applied in multiple ways; therefore, one cannot define it as a function. The keyword is Operator Calculus or alternatively Operational Calculus. Here is an introductory PDF document. Other references are easily found on the internet, such as Fractional Calculus WikipediaWhat is operator calculus? I find this an interesting question, because it appeared to me also when I studied multivariable calculus.

First of all, "an equation needs to have two evaluatable terms on both sides, but an operator is not a value" is meaningless and also false, no matter what meaning you give to "evaluatable terms". What does this even mean?

nabla math

Your only objection can be to the meaning of the right hand sie. It is a perfectly ok definition. Sign up to join this community. The best answers are voted up and rise to the top. Home Questions Tags Users Unanswered. How to define the Nabla-Operator Ask Question. Asked 6 years, 8 months ago. Active 5 years, 6 months ago.

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