Q TALKS ABOUT FLAT EARTH...TRUTH IS COMING 💯

Hugh Everett's birthday! Pioneer of the Many-Worlds Interpretation of quantum mechanics. Let us celebrate by thinking about ontological extravagance. I will do so by way of analogy, because I have found that everyone loves analogies and nobody ever willfully misconstrues them.

The physicist Hugh Everett III was born #OTD in 1930. His \u201crelative state\u201d formulation of quantum mechanics, which we now call the \u201cMany Worlds Interpretation,\u201d was published in 1957. pic.twitter.com/ZqMsZcPJDG
— Robert McNees, the bastegod (@mcnees) November 11, 2020

We look at the night sky and see photons arriving to us, emitted by distant stars. Let's contrast two different theories about how stars emit photons.

One theory says, we know how stars shine, and our equations predict that they emit photons roughly uniformly in all directions. Call this the "Many-Photons Interpretation" (MPI).

But! Others object. That is *so many photons*. Most of which we don't observe, and can't observe, since they're moving away at the speed of light. It's too ontologically extravagant to posit a huge number of unobservable things!

So they suggest a "Photon Collapse Interpretation." According to this theory, the photons emitted toward us actually exist. But photons that would be emitted in directions we will never observe simply collapse into utter non-existence.

Matthew Salganik
@msalganik

Announcing the 2021 Summer Institutes in Computational Social Science. #SICSS is for grad students, post-docs & beginning faculty. Free for participants. @chris_bail and I are happy to tell you about all 20 locations. https://t.co/wolhtZIMc5 [thread]

SICSS brings together social scientists & data scientists interested in computational social science for 1-2 week events with intensive study & collaborative research.

Topics covered include automated text analysis, web scraping, non-probability sampling, digital experiments, ethics & much more.

All education materials created for SICSS are available open-source so that people who are unable to participate can still learn. You can also use them in your teaching. Here are materials from previous years:

Because of COVID, all SICSS locations will be online only in 2021.

Carlos E. Perez
@IntuitMachine

In physics, energy is that which is causally invariant or symmetric with respect to time. Said differently, energy is never created or destroyed, it is conserved in the universe.

Now there is a question about information. Is information causally invariant? Does information remain the same with respect to time? To understand this, let's first understand what energy is, then attempt to understand what information is.

The strange thing about energy is that it is this universal currency that seems to be interchangeable between the different forces in nature (i.e. electromagnetic, strong, weak and gravity). It is that thing that makes change possible.

Now let's assume that the universe is computational in nature. That is, anything we see in nature is a consequence of computation. That is, there is computation underneath the physics that is driving the universe to change.

What does it mean then that information is conserved in this computational universe? Also, how is energy conservation related to information conservation?

10-K Diver
@10kdiver

1/

Get a cup of coffee.

In this thread, I'll help you understand the basics of Binomial Thinking.

The future is always uncertain. There are many different ways it can unfold -- some more likely than others. Binomial thinking helps us embrace this view.

2/

The S&P 500 index is at ~3768 today.

Suppose we want to predict where it will be 10 years from now.

Historically, we know that this index has returned ~10% per year.

If we simply extrapolate this, we get an estimate of ~9773 for the index 10 years from now:

3/

What we just did is called a "point estimate" -- a prediction about the future that's a single number (9773).

But of course, we know the future is uncertain. It's impossible to predict it so precisely.

So, there's a sense of *false precision* in point estimates like this.

4/

To emphasize the uncertainty inherent in such predictions, a better approach is to predict a *range* of values rather than a single number.

For example, we may say the index will return somewhere in the *range* of 8% to 12% (instead of a fixed 10%) per year.

5/

10 years from now, this implies an index value in the *range* [8135, 11703]:

Bert Hubert
@PowerDNS_Bert

Recently I learned something about DNA that blew my mind, and in this thread, I'll attempt to blow your mind as well. Behold: Chargaff's 2nd Parity Rule for DNA N-Grams.
If you are into cryptography or reverse engineering, you should love this.
Thread:

DNA consists of four different 'bases', A, C, G and T. These bases have specific meaning within our biology. Specifically, within the 'coding part' of a gene, a triplet of bases encodes for an amino acid

Most DNA is stored redundantly, in two connected strands. Wherever there is an A on one strand, you'll find a T on the other one. And similarly for C and G:

T G T C A G T
A C A G T C A

(note how the other strand is upside down - this matters!)

If you take all the DNA of an organism (both strands), you will find equal numbers of A's and T's, as well as equal numbers of C's and G's. This is true by definition.
This is called Chargaff's 1st parity rule.
https://t.co/jD4cMt0PJ0

Strangely enough, this rule also holds per strand! So even if you take away the redundancy, there are 99% equal numbers of A/T and C/G * on each strand *. And we don't really know why.
This is called Chargaff's 2nd parity rule.

Q TALKS ABOUT FLAT EARTH...TRUTH IS COMING 💯

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