Skip to main content

Bernstein–Vazirani Algorithm

 

Quantum computers currently available are not sufficient to solve every existing classical problem due to their own characteristics. This does not mean that they are inferior to classical computers, or that, on the contrary, quantum computers should give all kinds of advantages over classical computers.

Popular quantum algorithms solved in quantum computers are algorithms created by taking advantage of the superposition and entanglement properties of particles. So, they are algorithms created to show the prominent features of quantum properties.

Today I will talk about an enjoyable algorithm that demonstrates the efficiency and speed of these quantum features. Known as the Bernstein - Vazirani algorithm is a quantum algorithm invented by Ethan Bernstein and Umesh Vazirani in 1992.

The purpose of this algorithm, which is a game, is to find a desired number. To put it more clearly, let's keep in mind a string of binary numbers, for example, 1011001. Next, let's write an algorithm and ask our computer to predict this number.

Our classical computers have to take 7 tries to find this 7-bit number. That is, it will be able to reach this number in a loop using the "AND" logic gate for each bit.

The ambitious aspect of the Bernstein–Vazirani algorithm is that it can find it in one shot.
Bernstein–Vazirani algorithm circuit representation

It is an important algorithm for demonstrating the speed of quantum computers. In the following years, it is certain that there will be a great leap forward in terms of technology by applying this superiority to classical problems.




Reference

https://learn.qiskit.org/course/ch-algorithms/bernstein-vazirani-algorithm

Labels:

Comments

Post a Comment

Popular posts from this blog

Statement of Bell's Inequality

 One of the most important applications of quantum mechanics is Bell's inequality. In 1965, John Stewart Bell actually thought that Einstein might be right and tried to prove it, but proved that quantum logic violated classical logic. It was a revolutionary discovery. Let's look at its mathematically simple explanation. To create the analogy, let's first write a classical inequality.   This inequality above is a classic expression. The quantum analogy of this expression represents the Bell inequality. With just one difference. Bell's inequality shows that the above equation is violated. Expressing Bell's inequality by skipping some complicated mathematical intermediates; While there is no such situation in the classical world that will violate the inequality we mentioned at the beginning, it is difficult to find a situation that does not violate this inequality in the quantum world. Reference https://www.youtube.com/watch?v=lMyWl6Pq904 https://slideplay...
1 comment
Read more

Bloch Sphere – Geometric Representation of Quantum State

    It is very difficult to visualize quantum states before our eyes. The Bloch sphere represents quantum state functions quite well. The Bloch sphere is named after physicist Felix Bloch. As you can see in the Bloch sphere figure below, it geometrically shows the pure states of two-level quantum mechanical systems. The poles of the Bloch sphere consist of bits |0⟩ and |1⟩. Classically, the point on the sphere indicates either 0 or 1. However, from a quantum mechanics point of view, quantum bits contain possibilities to be found on the entire surface of the sphere. Traditionally, the z-axis represents the |0⟩ qubit, and the z-axis the |1⟩ qubit. When the wave function in superposition is measured, the state function collapses to one of the two poles no matter where it is on the sphere. The probability of collapsing into either pole depends on which pole the vector representing the qubit is closest to. The angle θ that the vector makes with the z-axis determines this probabilit...
1 comment
Read more

Let's Define Quantum Programming

    Along with the strange discoveries of quantum physics, one of these ideas for how we could use it is quantum computers. Work on quantum computers, which is a pretty good idea, started small and became what it is today. Now we had to take one more step and do quantum programming. The first studies on this process were made in the early 2000s. However, these studies were more theoretical. This was because quantum computers were not yet technologically ready. Finally, with the serious development of quantum computers (of course, we are still not at the desired point) we started to create our quantum algorithms. Today, we can do these algorithms on IBM Quantum Experience, Microsoft Azure Quantum, DWave Leap Cloud, or with quantum development kits. With these platforms, most of which are open source, we can create our quantum algorithms with the Python language, which we use classically and which is the most common programming language. The fact that such platforms are open sou...
2 comments
Read more