Comparing Gradient: Highest & Lowest, Vector/Scalar?

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In summary, the conversation discusses the equations of three lines and the concept of gradient or slope. It is mentioned that the gradient can be considered as a vector or scalar quantity, and that line 1 has the highest gradient while line 3 has the steepest gradient. There is also a question about the difference between "highest gradient" and "steepest gradient," and the suggestion to give both answers if unsure of the intended meaning. The conversation ends with the need to understand gradient for drawing purposes.
  • #1
songoku
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If, let say, I have 3 equation of lines:
Line 1: y = 3x + 10
Line 2: y = 0
Line 3: y = -4x

which line has the highest and lowest gradient?

Is gradient in equation of line vector quantity or scalar quantity?

Do we say gradient = 0 is higher than gradient = -4 or is gradient = -4 is higher than 0 because the gradient is only "directed" downwards?

Thanks
 
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  • #2
Usually it would be regarded as a vector quantity, so that Line 1 has the highest gradient.
A term that is sometimes used for gradient as a scalar is 'steep'. We would say the Line 3 has the steepest gradient.

If it is an assignment question and you are not sure what the lecturer intended, I suggest you give both answers and explain why they are different.
 
  • #3
The three equations are those of lines. The terminology we use in the US is "slope," as "gradient" is usually reserved to the discussion multivariate functions.
For example, if ##w = f(x, y, z)## is a function of three variables, the gradient of f, denoted ##\nabla f## can be written as ##\nabla f = \frac{\partial f}{\partial x} \textbf i + \frac{\partial f}{\partial y}\textbf j + \frac{\partial f}{\partial z} \textbf k##.

The slopes of the three lines are 3, 0, and -4, respectively. Although -4 < 0 < 3, the third line is the steepest.
 
  • #4
andrewkirk said:
Usually it would be regarded as a vector quantity, so that Line 1 has the highest gradient.
A term that is sometimes used for gradient as a scalar is 'steep'. We would say the Line 3 has the steepest gradient.
Is there difference between "highest gradient" and "steepest gradient"?
If I want to find highest gradient, it is line 1 but if I want to find steepest gradient, it is line 3?

If it is an assignment question and you are not sure what the lecturer intended, I suggest you give both answers and explain why they are different.
I need to draw something related to gradient (slope) so I have to understand about this

Thanks
 

1. What is the difference between a gradient with the highest and lowest values?

The gradient is a vector that represents the change in a scalar quantity (such as temperature or pressure) over a distance. The highest value of the gradient indicates the steepest increase in the scalar quantity, while the lowest value indicates the shallowest increase.

2. Can you explain the concept of vector and scalar in the context of gradients?

A vector quantity has both magnitude and direction, while a scalar quantity only has magnitude. In the context of gradients, the vector represents the change in the scalar quantity over a distance, while the scalar quantity itself is the magnitude of the change.

3. How do you compare gradients with different orientations?

To compare gradients with different orientations, you can use the dot product. The dot product of two vectors gives a scalar value that represents the amount of alignment between the two vectors. A higher dot product indicates a stronger alignment and a lower dot product indicates a weaker alignment.

4. What are some real-world applications of comparing gradients?

Comparing gradients is useful in many fields, such as meteorology, geology, and physics. For example, meteorologists use gradients to study changes in wind speed and direction, while geologists use gradients to analyze changes in elevation. In physics, gradients are used to understand changes in electric or magnetic fields.

5. How can I visualize and interpret gradients?

Gradients can be visualized using vector fields, where each vector represents the gradient at a specific point. The length and direction of the vector indicate the magnitude and direction of the gradient. Interpreting gradients involves understanding the relationship between the scalar quantity and the changes in that quantity over a distance, which can be helpful in understanding patterns and trends in data.

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