Projective linear group Updated 2025-07-16
TODO motivation. Motivation. Motivation. Motivation. The definitin with quotient group is easy to understand.
Talmud Updated 2025-07-16
Benchmark Updated 2025-08-08
Allen Mouse Brain Updated 2025-07-16
Grouping their mouse brain projcts here.
Video 1.
Tutorial: Allen Developing Mouse Brain by Allen Institute (2014)
Source.
Dojo Updated 2025-07-16
"Dojo" is the japanese version of the word that unfortunately came to dominate in the West, the original is of course Chinese Dao4 chang3 (道場) which means:
  • dao4 (道): Taoism, the Enlightned Path to something
  • chang3 (場): suffix indicating "a place where you do something"
Peptide Updated 2025-07-16
Quantum compilation Updated 2025-07-16
Software that maps higher level languages like Qiskit into actual quantum circuits.
Qubit Updated 2025-07-16
Received Pronunciation Updated 2025-07-16
Video 1.
Hard Attack: How English is getting more "choppy" by Dr Geoff Lindsey (2023)
Source. Goodness this dude is a master of it.
Tunnel magnetoresistance Updated 2025-07-16
Video 1.
What is spintronics and how is it useful? by SciToons (2019)
Source. Gives a good 1 minute explanation of tunnel magnetoresistance.
IBM Quantum Computing Updated 2025-07-16
The term "IBM Q" has been used in some promotional material as of 2020, e.g.: www.ibm.com/mysupport/s/topic/0TO50000000227pGAA/ibm-q-quantum-computing?language=en_US though the fuller form "IBM Quantum Computing" is somewhat more widely used.
Meditation Updated 2025-07-16
Psalm 46:10 from the bible:
Be still, and know that I am God;
I will be exalted among the nations,
I will be exalted in the earth.
Oxford Quantum Circuits Updated 2025-07-16
Their main innovation seems to be their 3D design which they call "Coaxmon".
Video 1.
The Coaxmon by Oxford Quantum Circuits (2022)
Source.
One key insight, is that the matrix of a non-trivial quantum circuit is going to be huge, and won't fit into any amount classical memory that can be present in this universe.
This is because the matrix is exponential in the number qubits, and is more than the number of atoms in the universe!
Therefore, off the bat we know that we cannot possibly describe those matrices in an explicit form, but rather must use some kind of shorthand.
But it gets worse.
Even if we had enough memory, the act of explicitly computing the matrix is not generally possible.
This is because knowing the matrix, basically means knowing the probability result for all possible outputs for each of the possible inputs.
But if we had those probabilities, our algorithmic problem would already be solved in the first place! We would "just" go over each of those output probabilities (OK, there are of those, which is also an insurmountable problem in itself), and the largest probability would be the answer.
So if we could calculate those probabilities on a classical machine, we would also be able to simulate the quantum computer on the classical machine, and quantum computing would not be able to give exponential speedups, which we know it does.
To see this, consider that for a given input, say 000 on a 3 qubit machine, the corresponding 8-sized quantum state looks like:
000 -> 1000 0000 == (1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
and therefore when you multiply it by the unitary matrix of the quantum circuit, what you get is the first column of the unitary matrix of the quantum circuit. And 001, gives the second column and so on.
As a result, to prove that a quantum algorithm is correct, we need to be a bit smarter than "just calculate the full matrix".
Which is why you should now go and read: Section "Quantum algorithm".
This type of thinking links back to how physical experiments relate to quantum computing: a quantum computer realizes a physical experiment to which we cannot calculate the probabilities of outcomes without exponential time.
So for example in the case of a photonic quantum computer, you are not able to calculate from theory the probability that photons will show up on certain wires or not.

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