Where in STEM can I expect to use dual basis, dual map, annihilator?

In summary, dual basis, dual map, and annihilator concepts are essential in various fields of STEM, particularly in linear algebra, functional analysis, and theoretical physics. They are used in optimizing and solving systems of equations, understanding vector spaces, and working with dual spaces in mathematical frameworks. These concepts also find applications in computer science, specifically in algorithms and data structures, as well as in engineering disciplines for modeling and control systems. Understanding these tools enhances problem-solving capabilities and provides deeper insights into the structure of mathematical and physical systems.
  • #1
zenterix
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I find the topics of dual space, dual basis, dual map, and annihilator quite abstract.

I understand the proofs in the book I am reading (Linear Algebra Done Right), and I can solve problems. But after a few weeks without doing any linear algebra I forget what these concepts are and the reason is that I haven't seen them in other subjects in the past and I don't see them in any other subject that I am currently studying (thermodynamics, special relativity, differential equations, electromagnetism).

Where in STEM can I expect to see these linear algebra topics used?
 
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  • #2
Dual spaces and dual bases are used in differential forms, tensors, QM, GR.
 
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  • #3
In general: differential geometry, tensor algebra, i.e. everywhere in physics. You are right, the concept is mathematically a bit boring if you only consider finite-dimensional vector spaces with an inner product. This changes if you look at the correspondence of tangent vectors and derivations on ##C^\infty (\mathbb{R}^n)##,
$$
v\longleftrightarrow \left(v(f)=\left. \dfrac{d}{dt}\right|_{t=0}f(p+tv)\right)
$$
or investigate the computational complexity of bilinear multiplications,
$$
(x,y) \longmapsto \operatorname{min}\left\{r\, \left| \,x\cdot y =\sum_{\rho=1}^r u_\rho(x)v_\rho(y)W_\rho \right.\right\}
$$
or simply try to understand what a ##(2,1)##-tensor is.
 

FAQ: Where in STEM can I expect to use dual basis, dual map, annihilator?

Where in STEM can I expect to use dual basis, dual map, annihilator in Physics?

In Physics, particularly in areas like Quantum Mechanics and General Relativity, dual basis and dual maps are often used. For instance, in Quantum Mechanics, dual vectors (bra vectors) are essential in the formulation of quantum states. In General Relativity, tensors and their duals are crucial for describing the curvature of spacetime.

How are dual basis and dual maps relevant in Computer Science?

In Computer Science, dual basis and dual maps are relevant in fields such as cryptography and coding theory. They are used in the design and analysis of algorithms, especially those involving linear transformations and vector spaces. Additionally, they play a role in machine learning, particularly in the context of kernel methods and support vector machines.

Can dual basis and annihilators be applied in Engineering?

Yes, in Engineering, particularly in Control Theory and Signal Processing, dual basis and annihilators are used. They are important for understanding system behaviors, designing controllers, and analyzing signals. Dual spaces help in formulating state-space representations and transforming signals in various domains.

Are dual basis and dual maps used in Mathematics?

Absolutely, dual basis and dual maps are fundamental concepts in Mathematics, especially in Linear Algebra, Functional Analysis, and Differential Geometry. They are used to study vector spaces, linear transformations, and to understand the properties of functions and spaces. Annihilators are particularly useful in module theory and ring theory.

How do dual basis and dual maps apply in Economics?

In Economics, dual basis and dual maps are used in optimization problems and game theory. They help in understanding duality in linear programming and in analyzing economic models. Annihilators can be useful in understanding constraints and optimal solutions in various economic scenarios.

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