Multivariable Calculus, Hubbard and Hubbard and Lang's

In summary, the individual is seeking advice on which books to study in order to gain a strong understanding of multivariable calculus. They are considering Hubbard and Hubbard's 'Vector Calculus, Linear Algebra, and Differential Forms' and Serge Lang's 'Calculus of Several Variables' after studying Serge Lang's 'Linear Algebra'. However, they have already decided to go through Baby Rudin and Spivak's 'Calculus on Manifolds' and are wondering if it is necessary to also study Hubbard and Hubbard or Lang's 'Calculus of Several Variables'. They express a desire to apply their knowledge to physics but clarify that they are a math major. The responder recommends studying both Hubbard/Hubbard and Spivak's books for a
  • #1
unintuit
10
0
I do not know multivariable calculus. I have studied out of Apostol Vol.1.

I do not want to learn the material from Apostol Vol. II.

Therefore I want to know If it would be worthwhile to go through Hubbard and Hubbard's 'Vector Calculus, Linear Algebra, and Differential Forms' after going through Serge Lang's 'Linear Algebra' or would it be better to go through Serge Lang's 'Calculus of Several Variables' and then Baby Rudin followed by Spivak's 'Calculus on Manifolds'?

Regardless, I am going to go through Baby Rudin and Spivak's 'Calculus on Manifolds' book, I really just want to know if it is worth the time to go through Hubbard and Hubbard or Lang's 'Calculus of Several Variables' or can I skip these and do Rudin and Spivak's book?

Thank you for your helpful responses.
 
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  • #2
I want to apply the knowledge of Spivak's 'Calculus on Manifolds' to physics. However, I am still a math major. Physics is just an interesting aside.
 
  • #3
That depends on your emphasis. I always recommend Hubbard/Hubbard as a companion to Spivak's Calculus on Manifolds due to the latter's extreme emphasis on purely theoretical applications. Hubbard/Hubbard includes practical considerations, such as finite precision techniques for computers, and applied examples of the theory of calculus on manifolds to physical and mechanical scenarios. Spivak, on the other hand, presents calculus on manifolds in an extremely elegant and concise way, so that every part of the general theory is well motivated and internally connected using very simple notation and definitions. So exposure to both can keep your ability to work with the abstract machinery in both theoretical and practical situations well rounded.
 

FAQ: Multivariable Calculus, Hubbard and Hubbard and Lang's

What is Multivariable Calculus?

Multivariable calculus is a branch of mathematics that studies functions of multiple variables, as opposed to just one variable like in single variable calculus. It involves the study of limits, derivatives, integrals, and series in multiple dimensions.

Who are Hubbard and Hubbard and Lang?

Hubbard and Hubbard are mathematicians who co-authored the textbook "Vector Calculus, Linear Algebra, and Differential Forms: A Unified Approach" which is commonly used for teaching Multivariable Calculus. Lang is also a mathematician who has written a similar textbook titled "Multivariable Calculus".

What is the difference between Multivariable Calculus and Single Variable Calculus?

The main difference between the two is that Multivariable Calculus deals with functions of multiple variables, while Single Variable Calculus deals with functions of only one variable. Multivariable Calculus also involves studying vectors, surfaces, and volumes, which are not typically covered in Single Variable Calculus.

Why is Multivariable Calculus important?

Multivariable Calculus is important in many fields, including physics, engineering, economics, and computer science. It provides a framework for understanding and solving problems involving multiple variables and is essential for advanced mathematical and scientific studies.

What are some real-world applications of Multivariable Calculus?

Multivariable Calculus has many real-world applications, such as in computer graphics, where it is used to model and render three-dimensional objects. It is also used in economics to study optimization problems and in physics to describe the motion of objects in three-dimensional space. Other applications include machine learning, fluid dynamics, and statistical analysis.

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