Dirac Lagrangian Updated 2025-07-16
where:
Remember that is a 4-vetor, gamma matrices are 4x4 matrices, so the whole thing comes down to a dot product of two 4-vectors, with a modified by matrix multiplication/derivatives, and the result is a scalar, as expected for a Lagrangian.
Like any other Lagrangian, you can then recover the Dirac equation, which is the corresponding equations of motion, by applying the Euler-Lagrange equation to the Lagrangian.
Cryogen-free dilution refrigerator Updated 2025-07-16
Dilution refrigerator manufacturer Updated 2025-07-16
Frequency divider Updated 2025-07-16
Huygens-Fresnel principle Updated 2025-07-16
Developmental genetics Updated 2025-07-16
How genes form bodies.
Developmental Genetics 1 by Joseph Ross (2020)
Source. Talks about homeobox genes. Heavy water Updated 2025-07-16
Cody'sLab had a nice 5 video series on making it at home! But the United States Government asked him to take it down as suggested at Video "What's Been Going On With Cody'sLab? by Cody'sLab (2019)" at youtu.be/x1mv0vwb08Y?t=84.
Pre-order depth-first search Updated 2025-07-16
Like breadth-first search, this also has the property of visiting parents before any children.
In-order depth-first search Updated 2025-07-16
This is the order in which a binary search tree should be traversed for ordered output, i.e.:
- everything to the left is smaller than parent
- everything to the right is larger than parent
This ordering makes sense for binary trees and not k-ary trees in general because if there are more than two nodes it is not clear what the top node should go in the middle of.
This is unlike pre-order depth-first search and post-order depth-first search which generalize obviously to general trees.
Post-order depth-first search Updated 2025-07-16
Has the property of visiting all descendants before the parent.
The orthogonal group is the group of all invertible matrices where the inverse is equal to the transpose Updated 2025-07-16
Let's show that this definition is equivalent to the orthogonal group is the group of all matrices that preserve the dot product.
Note that:and for that to be true for all possible and then we must have:i.e. the matrix inverse is equal to the transpose.
These matricese are called the orthogonal matrices.
TODO is there any more intuitive way to think about this?
The orthogonal group is the group of all matrices with orthonormal rows and orthonormal columns Updated 2025-07-16
Or equivalently, the set of rows is orthonormal, and so is the set of columns. TODO proof that it is equivalent to the orthogonal group is the group of all matrices that preserve the dot product.
Taylor expansion definition of the exponential function Updated 2025-07-16
The Taylor series expansion is the most direct definition of the expontial as it obviously satisfies the exponential function differential equation:
Product definition of the exponential function Updated 2025-07-16
The basic intuition for this is to start from the origin and make small changes to the function based on its known derivative at the origin.
More precisely, we know that for any base b, exponentiation satisfies:And we also know that for in particular that we satisfy the exponential function differential equation and so:One interesting fact is that the only thing we use from the exponential function differential equation is the value around , which is quite little information! This idea is basically what is behind the importance of the ralationship between Lie group-Lie algebra correspondence via the exponential map. In the more general settings of groups and manifolds, restricting ourselves to be near the origin is a huge advantage.
- .
- .
Now suppose that we want to calculate . The idea is to start from and then then to use the first order of the Taylor series to extend the known value of to .
E.g., if we split into 2 parts, we know that:or in three parts:so we can just use arbitrarily many parts that are arbitrarily close to :and more generally for any we have:
Let's see what happens with the Taylor series. We have near in little-o notation:Therefore, for , which is near for any fixed :and therefore:which is basically the formula tha we wanted. We just have to convince ourselves that at , the disappears, i.e.:
Positive definite matrix Updated 2025-07-16
The dot product is a positive definite matrix, and so we see that those will have an important link to familiar geometry.
Halting problem Updated 2025-07-16
The canonical undecidable problem.
Bisection (software engineering) Updated 2025-07-16
One of the Holiest age old debugging techniques!
Git has some helpers to help you achieve bisection Nirvana: stackoverflow.com/questions/4713088/how-to-use-git-bisect/22592593#22592593
Obviously not restricted to software engineering alone, and used in all areas of engineering, e.g. Video "Air-tight vs. Vacuum-tight by AlphaPhoenix (2020)" uses it in vacuum engineering.
Debugger Updated 2025-07-16
De novo DNA synthesis company Updated 2025-07-16
There are unlisted articles, also show them or only show them.