Matrices Often Used in Quantum Computing

In summary, the conversation discusses a study on quantum computing and the intersection of mathematics, physics, computer science, and electrical engineering. The topic also covers the implementation of a quantum computer simulator and the inclusion of Shor and Grover algorithms, with the intention of adding more in the future. Furthermore, the conversation touches on the use of Phase and pi/8 gates in the simulator. A link to the source code for the simulator is also provided.
  • #1
Ackbach
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I am beginning a study I have long wanted to engage in: quantum computing. This is a field lying at the intersection of mathematics, physics, computer science, and electrical engineering - all topics I studied, to varying levels. From time to time, I plan on posting notes and summaries that might prove useful to others studying the same thing. Without further ado:

$$\begin{array}{|c|c|c|c|c|c|} \hline
\textbf{Name} &\textbf{Matrix} &A^{\dagger}A=I? &A=A^{\dagger}? &\textbf{E-values} &\textbf{Norm. E-vectors} \\
\hline
\text{Hadamard} &H=\dfrac{1}{\sqrt{2}}\begin{bmatrix}1 &1\\1 &-1\end{bmatrix} &\text{Yes} &\text{Yes}
&1,\; -1 &\dfrac{1}{\sqrt{4-2\sqrt{2}}}\begin{bmatrix}1 \\ \sqrt{2}-1\end{bmatrix}, \;
\dfrac{1}{\sqrt{4+2\sqrt{2}}}\begin{bmatrix}1 \\ -\sqrt{2}-1\end{bmatrix} \\ \hline
\text{Pauli }X &X=\begin{bmatrix}0 &1\\1 &0\end{bmatrix} &\text{Yes} &\text{Yes} &1, \; -1
&\dfrac{1}{\sqrt{2}}\begin{bmatrix}1\\1\end{bmatrix}, \; \dfrac{1}{\sqrt{2}}
\begin{bmatrix}1\\-1\end{bmatrix} \\ \hline
\text{Pauli }Y &Y=\begin{bmatrix}0&-i\\i&0\end{bmatrix} &\text{Yes} &\text{Yes}
&1, \; -1 &\dfrac{1}{\sqrt{2}}\begin{bmatrix}1\\i\end{bmatrix}, \; \dfrac{1}{\sqrt{2}}
\begin{bmatrix}1\\-i\end{bmatrix} \\ \hline
\text{Pauli }Z &Z=\begin{bmatrix}1&0\\0&-1\end{bmatrix} &\text{Yes} &\text{Yes}
&1, \; -1 &\begin{bmatrix}1\\0\end{bmatrix}, \; \begin{bmatrix}0\\1\end{bmatrix} \\ \hline
\text{Phase} &S=\begin{bmatrix}1&0\\0&i\end{bmatrix} &\text{Yes} &\text{No} &1,\;i
&\begin{bmatrix}1\\0\end{bmatrix}, \; \begin{bmatrix}0\\1\end{bmatrix} \\ \hline
\pi/8 &T=\begin{bmatrix}1&0\\0&e^{i\pi/4}\end{bmatrix} &\text{Yes} &\text{No} &1, \; e^{i\pi/4}
&\begin{bmatrix}1\\0\end{bmatrix}, \; \begin{bmatrix}0\\1\end{bmatrix} \\ \hline
\end{array}$$
 
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  • #3
Greg Bernhardt said:
Thanks @Ackbach! Think we can move to QM or Comp Sci forum?
Let's put these two in QM. I don't think they're useful enough for stickying.
 
  • #4
A few days ago, I started to implement a quantum computer simulator. It's very basic but the things I tried seem to work ok.
For now only Shor (the quantum part) and Grover algorithms are there but I intend to add more.
Source code here: https://github.com/aromanro/QCSim
Phase and pi/8 gates mentioned above can be used with the more general PhaseShiftGate.
 
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FAQ: Matrices Often Used in Quantum Computing

What are matrices often used for in quantum computing?

Matrices are used to represent quantum states, operations, and measurements in quantum computing. They are an essential tool for studying and manipulating quantum systems.

How are matrices used to represent quantum states?

In quantum computing, matrices are used to represent quantum states by assigning complex numbers to each element. The state of a quantum system is described by a vector of amplitudes, which is represented as a matrix with a single column or row.

What are the basic operations performed on matrices in quantum computing?

The basic operations performed on matrices in quantum computing include addition, multiplication, and tensor product. Addition and multiplication of matrices represent the superposition and entanglement of quantum states, while the tensor product represents the combination of multiple quantum systems.

How are matrices used in quantum algorithms?

Matrices play a crucial role in quantum algorithms as they are used to represent the gates and operations performed on quantum bits (qubits). These matrices are manipulated using quantum gates to perform computations and solve problems that are difficult for classical computers.

Are there any limitations to using matrices in quantum computing?

One limitation of using matrices in quantum computing is that they can become exponentially large as the number of qubits increases. This can make simulations and computations difficult and resource-intensive. Additionally, some quantum algorithms may require specialized matrices that are not easily represented or manipulated using classical computers.

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