This is the order in which you would want to transverse to read the chapters of a book.
Like breadth-first search, this also has the property of visiting parents before any children.
This is the order in which a binary search tree should be traversed for ordered output, i.e.:
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.
Has the property of visiting all descendants before the parent.
When viewed as matrices, it is the group of all matrices that preserve the dot product, i.e.:
This implies that it also preserves important geometric notions such as norm (intuitively: distance between two points) and angles.
This is perhaps the best "default definition".
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.
Conversely, if:
is true, then
These matricese are called the orthogonal matrices.
TODO is there any more intuitive way to think about this?
The Taylor series expansion is the most direct definition of the expontial as it obviously satisfies the exponential function differential equation:
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.:
To do that, let's multiply by itself once:
and multiplying a third time:
TODO conclude.
The dot product is a positive definite matrix, and so we see that those will have an important link to familiar geometry.
One of the Holiest age old debugging techniques!
The cool thing about bisection is that it is a brainless process: unlike when using a debugger, you don't have to understand anything about the system, and it incredibly narrows down the problem cause for you. Not having to think is great!
Using de novo DNA synthesis to synthesize a genes to later insert somewhere.
Note that this is a specific application of de novo DNA synthesis, e.g. polymerase chain reaction primers is another major application that does not imply creating genes.
Synthesizing the DNA itself is not the only problem however.
You then have to get that DNA into a working living form state so that normal cell processes can continue:

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