Old stuff: my first IEEE paper on Computational Intelligence

Before I finished my college, I managed to publish a paper on evolutionary computation (EC). The paper is on the encoding part. My next task is to use quantum to rewrite my algorithm. Well, there is a quantum genetic algorithm (QGA) there. However, I think with the latest decision on Q# and quantum algorithms. The paper link is here.

Microsoft Q# Day 1: Qubit Collapsed

After going through the quantum linear algebra, I am going to see some quantum concept by using Q#.

The first one I want to prove is measurement will collapse the qubit. I will use the AssertProb to verify the value with probability. The pseudo code is listed below:

1. use H gate to set the qubit to superposition
2. check the probability to 1 equals 0.5 (50%)
3. measure the qubit
4. check the qubit equals the measured value equals to 1 (100%). The qubit collapsed. 

the code listed below:

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namespace Quantum.QSharpApplication2 { open Microsoft.Quantum.Primitive; open Microsoft.Quantum.Canon; open Microsoft.Quantum.Extensions.Convert; operation Operation1 () : Unit { body(...) { using (ancilla = Qubit()) { H(ancilla); AssertProb([PauliZ], [ancilla], Zero, 0.5, "error", 1e-5); AssertProb([PauliZ], [ancilla], One, 0.5, "error", 1e-5); mutable gate = PauliZ; let mX = Measure([gate], [ancilla]); AssertProb([gate], [ancilla], mX, 1.0, "error", 1e-5); Message(ToStringD(mX == Zero ? 0. | 1.)); Reset(ancilla); } } } }

Microsoft Q# is my choice

Today I am thinking to dig into the real quantum programming after learning the foundation part. There are three big players I was looking at on quantum programming framework/language. I hate to waste my time learning the framework or language itself. I want to focus on so I can focus on solving the problem. I have three choices:

• IBM, IBM Q
• Google Cirq
• Microsoft Q#

It seems IBM Q and Cirq are reusing the Python to provide a framework while Q# is a brand new language. It makes sense IBM and Google use Python as base as it has a good math library. However, I doubt this choice is the best choice. Like the GPU, quantum is special hardware. Cuda is a like C language but it has its own features. For quantum computing, it has a totally different way to compute. Therefore, I think the best way to use a new language, maybe it is just a DSL. C++ can be used to write a functional program, but the best way is still to use a functional programming language. 

Also, the examples from those three companies show a huge difference. Q# provides the best sample pack so far. It has a quantum foundation, matrix computation, and programming language. It will help me a lot to adopt this new stuff. 

The setup and debugging is the last thought. I had tried to step away from Microsoft stack; however, the debugging and the setup needs more time I expected. I was spoiled by double click and just working. 

Anyway, the current Q# shows good progress and the watch, star, and pull request number is bigger than other players. I will continue to focus on the quantum basics, like matrix and math part, anyway. 

SelfNotes: Quantum Algorithms

I believe the quantum computing is the key to enable real AI. No matter how complicated the AI algorithm can be, the fundamental computing power will make a real difference.

The huge difference between a classical computer and a quantum computer is so intriguing! It is the first time that math can come back to computer science and guide its evolution. Also, the quantum algorithm is the first time it introduces the internal parallelism. Those existing algorithms barely considered parallelism when it is designed. Now the quantum can change this situation!

The following are some notes about quantum algorithms. They are not related to any language implementation, it is just pure math. The only tool I want to use is "that piece of meat between my ears". :)