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Near term Algorithms | hybrids
The current landscape of quantum computers is hard to navigate. There is little information about the subject just cause it is so new and we as a species are learning about it as we go. The current use cases of these noisy quantum computers are a hybrid of classical algorithms controlling the parameters of the quantum algorithm. Since most quantum computers right now have a lot of errors or noise. It is important that we continue to find a use for the quantum computers we have now so that investors and researchers get to further develop and grow this field.
Taking into consideration the limits of our NISQ quantum computers. Hybrid algorithms are the best use case right now. I’ve seen different terms floating around this space for these types of algorithms. Near terms, quantum artificial intelligence hybrids, quantum machine learning hybrids.
In this article, I will cover one type of these near-term algorithms. There are certain types of problems that are considered unsolvable. You still can get to a close enough solution. One of the common problems is the backpack problem.
Let’s say you have a backpack. It only holds a certain weight of 9 Kilograms. You can fill the backpack with the items you want to sell. The weight and value of the items are different. Let's just put the items in boxes with their weights. item 1 has a $4 value and is 3…
