Do you struggle with understanding quantum circuits because of all the math?

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

In previous posts, I claimed that you don’t need to be a mathematician or a physicist to understand quantum computing.

Yet, if you’re neither a mathematician nor a physicist, studying quantum algorithms can be hard sometimes. It is challenging for it uses symbols extensively. The problem with symbols is that you can’t google them easily. Consider the following circuit, for instance.

It represents a structure you’ll frequently encounter when studying quantum algorithms. …


Concluding a series of posts on the famous Deutsch and Jozsa quantum algorithm

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

In the previous post, we developed a probabilistic version of Deutsch and Jozsa’s quantum algorithm.

Deutsch and Jozsa’s original algorithm tells you whether a given function produces constant output (always the same) or balanced output (equal number of zeros and ones). But it assumes the balanced function to be balanced within a specific boundary. …


Making use of the probabilistic nature of a qubit

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

In a series of previous posts (“An Illustrative Case Of Quantum Advantage” and “Improving The Deutsch And Jozsa Quantum Algorithm”), we looked at one of the first quantum algorithms proving to be exponentially faster than its classical counterpart. David Deutsch’s developed this algorithm and generalized it later together with Richard Jozsa.

These algorithms are all about determining whether an input function is constant or balanced. The first analogy coming to mind is a coin.

The coin could be tricked, thus…


A practical guide about a famous quantum algorithm

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

In a previous post, we got to know the algorithm developed by David Deutsch and Richard Jozsa. One of the first algorithms to prove how a quantum algorithm can be exponentially faster than a classical algorithm.

This algorithm evaluates in a single run whether the input we provide is constant or balanced. As an example, we looked at a coin. To say whether a coin is fair, you have to toss and evaluate it multiple times. …


The Deutsch-Jozsa quantum algorithm in practice

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

Posts on quantum computing usually start with anecdotal stories of how it will change the world. It is said to perform tasks in a few seconds that classical computers need thousands of years for.

Then, we start looking into it. First, we learn how quantum bits (qubits) are different from classical bits. They are in a state of superposition. Superposition is a complex (as in complex numbers) linear combination of the states 0 and 1. Many like the notion that…


How to implement “and” and “or” in Qiskit

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

Quantum computing is fundamentally different from classical computing. In classical computing, we use boolean logic. We evaluate the truth value of a variable to decide whether to perform one action or another.

It is best illustrated by the standard if then else structure.

The if-clause of this structure usually contains pure boolean logic. There, we extensively use boolean operators such as and, or, and not.

But boolean logic does not work in quantum computing. In quantum computing, all transformations…


You don’t need to be a mathematician to understand quantum computing, but when things become tricky, math is your ally.

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

In classical computing, we are used to thinking in boolean states. A term is true or false. A bit is off (0) or on (1). That’s it. It is the basis for all our algorithms.

With boolean logic and with only very few operators, such as not, and, and or, we can develop quite complex programs. If a term is true, do this, else do that. For this term is true, repeat doing a certain thing.

As a programmer, you…


A new profession is about to rise

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

Quantum computing has the potential to be the most disruptive technology of the 21st century. It is a different form of computation that builds upon quantum mechanics, and it promises to solve problems we can’t solve with classical computers, such as the factorization of large numbers.

Quantum computing is moving from tech labs to mainstream commercial use

Quantum computing has evolved over the years. So have the career opportunities that this exciting technology offers. Quantum computing has long been a…


The Qiskit Quantum Simulators-How to use them and What they are used for

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

In quantum computing, we use the fundamental properties of quantum physics to perform a computation: superposition and entanglement.

Superposition refers to the quantum phenomenon where a quantum system exists in a complex linear combination of the quantum states |0⟩ and |1⟩. Entanglement is an extremely strong correlation between quantum particles. Entangled particles remain perfectly correlated even if separated by great distances.

The mere fact that we’re able to use these phenomena to perform a computation is astonishing. But the fact…


There are other ways to use quantum computers

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

Quantum computers are no science fiction anymore. They are reality.

Google already claimed quantum supremacy in 2019 — their quantum computer solved a task in 200 seconds a classical computer would need 10,000 years for. Even though IBM countered one of their (classical) supercomputers could solve the same problem in less than three days, it is still an impressive speedup.

But if two tech giants battle for whose devices prove quantum supremacy first, chances are poor to find a quantum…

Frank Zickert

I have been working as an IT professional for 17 years. I studied Information Systems Development and earned my PhD in 2012 at Goethe University of Frankfurt.

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