Bra-ket notation and other linear algebra stuff

In summary, the conversation is discussing notes taken in a class about matrices and vectors. The first part addresses a confusion about the row vector being complex conjugates. In the second part, there is a question about the presence of a second unit matrix in the expression. The expert summarizer clarifies that it is added to convert the vector b into a transposed vector b. Towards the bottom of the page, there is a question about the expression "ab" becoming <a|b>, and the expert explains that the 'a' in 'ab' should be hermitian for it to become <a|b>.
  • #1
iScience
466
5
forgive the messiness; i take bad notes in class.

http://i.imgur.com/VmW8Ubg.jpg

towards the middle of the page where it says "this is equivalent to..." and then my professor wrote what follows but i thought the row vector should be complex conjugates? ie, the red writings are not actually part of the notes, i just wrote them because i was confused as to why they weren't there.
http://i.imgur.com/5zGGBe3.jpg

towards the bottom right, where it has a(hermitian)IbI, which are all matrices by the way, i don't understand where the second 'I' (unit matrix) came from (where i stated my confusion in the notes).btw, does anyone know how to shrink an image when i do ['img']link['/img']? sometimes these images are too large
 
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  • #2
Your first remark is correct. They should be complex conjugates.

For the second part if you have numbers like [tex]a\cdot u^{-1} \cdot u \cdot b[/tex].
Than you get [tex]a\cdot 1\cdot b[/tex]. you can freely multiply this entire expression with 1.

I believe the second unit matrix is added to convert the vector b in the transposed vector b since otherwise you have the product of 2 column vectors.
 
  • #3
towards the bottom of the page where i wrote "where'd this one come from?", to the RHS of that, i have 'ab'.

but if this is to become < a | b > , then shouldn't the 'a' in 'ab' be hermitian?
 

1. What is bra-ket notation and how is it used in linear algebra?

Bra-ket notation is a mathematical notation used to represent and manipulate vectors and linear operators in quantum mechanics and other applications of linear algebra. It consists of two parts, the bra \langle\psi| and the ket |\phi\rangle, with the bra representing a row vector and the ket representing a column vector. This notation is used to perform operations such as inner products, outer products, and matrix multiplication.

2. What is the difference between a vector and a matrix in linear algebra?

A vector is a one-dimensional array of numbers, while a matrix is a two-dimensional array of numbers. Vectors are used to represent a single variable or quantity, while matrices are used to represent a system of equations or multiple variables. In linear algebra, vectors are often used to represent points or directions in space, while matrices are used to represent transformations or operations on those vectors.

3. How does linear algebra relate to other branches of mathematics?

Linear algebra is a foundational branch of mathematics that plays a crucial role in many other areas, including calculus, physics, computer science, and statistics. It provides tools and techniques for solving systems of equations, analyzing data sets, and understanding geometric and spatial relationships. Many concepts and methods from linear algebra are also used in more advanced areas of mathematics, such as abstract algebra and differential equations.

4. What are eigenvectors and eigenvalues in linear algebra?

Eigenvectors and eigenvalues are important concepts in linear algebra that are used to study the behavior of linear transformations and matrices. An eigenvector of a linear transformation is a vector that, when multiplied by the transformation, is only scaled by a constant factor. This constant factor is known as the eigenvalue. Eigenvectors and eigenvalues are useful for understanding how a system changes under repeated transformations and for finding special solutions to systems of equations.

5. Can you give an example of a real-world application of linear algebra?

Linear algebra has many practical applications in fields such as engineering, physics, and computer science. One example is using linear algebra to solve systems of equations in electrical circuits. By representing the currents and voltages in a circuit as vectors and using techniques such as Gaussian elimination, engineers can analyze and design complex circuits. Linear algebra is also used in machine learning and data analysis to perform operations on large datasets and make predictions based on patterns and relationships in the data.

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