Week 6 - my notes

Table of Contents

Week 6 (qubit by qubit)

Recap

Review: States and Gates

  • X - 180 rotation around the X-axis
  • Z - 180 rotation around the Z-axis
  • H - creates a superposition

Math for Quantum: Qubits

  • With math we can predict the outcomes, without necessarily having to memorize each one of them.
  • Superconducting, Trapped Ions, Diamond NV Centers, Photonics are different kind of qubits, and math is the language common to all of them!
  • Linear Algebra is used in many algorithms, like grover’s algorithm.

Qubits

  • \(|0\rangle\), \(|1\rangle\), \(|+\rangle\), \(|-\rangle\) are ways to represent them.
  • But in an unequal superposition, we need a better way to represent contributions.
  • That is why we will use two numbers in the form of a vector.
  • 0 state is represented as \[\begin{bmatrix}1\\0\end{bmatrix}\]
  • 1 state is represented as \[\begin{bmatrix}0\\1\end{bmatrix}\]
  • It is worth mentioning that the top number represents the component of \(|0\rangle\) and the bottom, the component of \(|1\rangle\).
\begin{bmatrix} |0\rangle\ component\\|1\rangle\ component\end{bmatrix}

Superpostions

  • To represent equal superpositions, we just need to add the two vectors: \[\begin{bmatrix}1\\0\end{bmatrix} + \begin{bmatrix}0\\1\end{bmatrix} = \begin{bmatrix}1\\1\end{bmatrix}\]
  • To get to an unequal superposition, we need to apply some gates to get there and this is the goal of a field called quantum algorithm design

Normalization

  • The vectors representing quantum states must be normalized, which means they have a lenght of 1
  • The radius of the Bloch Sphere is 1, so as all quantum states lie on the Bloch sphere, they must all have a length of 1.
  • [ ] Step 1: Write the state in the vector form \[\begin{bmatrix}a\\b\end{bmatrix}\]
  • [ ] Step 2: Find the length of the state as \[\sqrt{a^2 + b^2}\]
  • [ ] Step 3: If the length is 1, the state is normalized. If not, divide the state by its length to get the normalized state.
    • Normalized form of the state = \[\frac{1}{\sqrt{a^2 + b^2}}\begin{bmatrix}a\\b\end{bmatrix}\]

Examples to help with normalization:

  • Remember that all of this comes from linear algebra
  • The length of the state \[\begin{bmatrix}1\\0\end{bmatrix}\]
    • A: 1
  • Find the normalized state of \[\begin{bmatrix}1\\1\end{bmatrix}\]
    • Finding the length: \[\sqrt{1^2 + 1^2} = \sqrt{2}\]
    • As the length is not 1, we need to divide take the state and divide it by its length, then we get the normalized state:

\[\frac{1}{\sqrt{2}}\begin{bmatrix}1\\1\end{bmatrix}\]

Phase

  • Subtract the following states: \[\frac{1}{\sqrt{2}}\begin{bmatrix}1\\0\end{bmatrix} - \frac{1}{\sqrt{2}}\begin{bmatrix}0\\1\end{bmatrix} = \frac{1}{\sqrt{2}}\begin{bmatrix}1\\-1\end{bmatrix}\]
  • That is the same as \(|-\rangle\)

Normalized form of \(|+\rangle\) and \(|-\rangle\) states

  • \(|+\rangle\) = \[\frac{1}{\sqrt{2}}(|0\rangle+|1\rangle)\] same as \[\frac{1}{\sqrt{2}}\begin{bmatrix}1\\1\end{bmatrix}\]
  • \(|-\rangle\) = \[\\frac{1}{\sqrt{2}}(|0\rangle-|1\rangle)\] same as \[\frac{1}{\sqrt{2}}\begin{bmatrix}1\\-1\end{bmatrix}\]
  • These two states above are both equal superpositions but they differ in phase
  • Therefore, the sign between \(|0\rangle\) and \(|1\rangle\) is called phase. Is it positive or negative?
  • The phase diferences lead to interference (more coming soon)
  • There are more relations in phase that won’t be addressed in this course because they require complex numbers

Lab

  • Qiskit Aer, Qiskit Nature, Qiskit Pulse are what we have inside the mega qiskit library. We are gonna use Qiskit Aer.
    • Qiskit Aer has two simulators: the Statevector simulator and the QASM simulator
  • The Statevector simulator gives us the vector form of the final state. It gives us the ideal result
  • The QASM simulator gives us the performing measurements on quantum circuits (like a hands-on)
  • We can say statevector will give us the theorical result and QASM simulator will give us the experimental result.

Resources

Author: Luís Spengler

Created: 2022-12-19 Mon 09:47