Question

Improving classical processors with simulation or optimization on a quantum computer?

Answer 1

Two classes of applications for quantum computers are (1) solving constrained optimization problems [example ] and (2) ab initio simulation of quantum systems [review ]. Have there been any concrete proposals for using either technique to improve the design (and hence performance) of classical computational hardware devices such as traditional microprocessors?
Using a quantum annealer to optimize datapaths would be an example of (1). Deploying new insights in material science, derived from a quantum simulation, to improve flash memory fabrication would be an example of (2).

Answer 2

Concept:

A traditional bit can only be a $0$ or a $1.$ A superposition of $0$ and $1$ is known as a quantum bit, or qubit. Therefore, a single qubit can simultaneously assume two classical values. Each qubit action is performed simultaneously on both values. Because of this, we frequently hear that a qubit contains more information than a conventional bit.

Given:

Here it is given that the question is improving classical processors with simulation or optimization on a quantum computer.

Find:

We have to find the answer of the question that is improving classical processors with simulation or optimization on a quantum computer.

Solution:

According to the question,

Calculations that are impossible for classical computers to complete are one of quantum computing's ultimate objectives. Therefore, it is essential that practical quantum computers be extremely challenging to model traditionally, else the applications envisioned for quantum computers might be implemented using classical computers.

Hence, the answer is The applications envisioned for quantum computers might be implemented using classical computers, so they must be extremely challenging to model traditionally.

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