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# Falling in Love with Quantum Variational Algorithms

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## What are Quantum Variational Algorithms?

Quantum Variational Algorithms are algorithms inspired by the Variational Principle in Quantum Mechanics. They are algorithms with the purpose of approximating solutions to a given problem.

Of course each algorithm has it’s nuances but the basic principle behind all of them is the same:

1. Prepare a parameterized circuit: This means a circuit where some of the gates have parameters that allow us to fine-tune their effect (i.e. the angle of a CX rotation).
2. Do some measurements: This might include of course multiple measurements in different basis and all sort of other combinations as well.

These algorithms are most of the time (and I say “most” because my knowledge in the field is not too extensive) used in optimization problems. This means you usually encounter 2 other common steps:

1. Calculate the cost of the solution given by your last run of the algorithm
2. Classically optimize the parameters of your circuit so that you minimize / maximize your cost function. This second point is also the reason why very often this algorithms are also called “hybrid”. The optimization part happens outside of the quantum world.

## Why are they Famous?

These algorithms are very famous because they usually exhibit a small number of gates and qubits (shallow circuits) which in turn means that are quite resistant to noise.

These algorithms also have shown to be applicable to a bunch of real world problems and are also present in a lot of the theory behind Quantum Machine Learning.

## Some Examples

I am sure I am missing a lot of good examples but the list below shows what seems to be the 3 most well-known algorithms around the internet nowadays.

## A Teenager in Love?

The problem that I personally have with these algorithms is that as I study them it really feels like teenager love from an adult’s perspective. You feel the excitement but it doesn’t feel genuine enough. Something tells me I still need to grow up to fully understand and appreciate the magic behind them. It’s a bit like trial and error on computational steroids. But this is what most the current Machine Learning techniques do as well-

I am looking forward to grow up and learn what true variational love means.

The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

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#### Araceli Venegas

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