Macroscopic entanglement in Quantum Computation

TL;DR

This paper explores how macroscopic entanglement in quantum states correlates with the difficulty of problems solved by quantum algorithms like Grover's and Shor's, suggesting such entanglement is key to quantum speedup.

Contribution

It demonstrates that macroscopically entangled states are used in quantum algorithms for hard problems, supporting the idea that such entanglement underpins quantum computational advantage.

Findings

Macroscopically entangled states are used in Grover's algorithm for hard problems.

Almost always used in Shor's algorithm for hard problems.

Supports the conjecture that macroscopic entanglement enables quantum speedup.

Abstract

We investigate macroscopic entanglement of quantum states in quantum computers, where we say a quantum state is entangled macroscopically if the state has superposition of macroscopically distinct states. The index $p$ of the macroscopic entanglement is calculated as a function of the step of the computation, for Grover's quantum search algorithm and Shor's factoring algorithm. It is found that whether macroscopically entangled states are used or not depends on the numbers and properties of the solutions to the problem to be solved. When the solutions are such that the problem becomes hard in the sense that classical algorithms take more than polynomial steps to find a solution, macroscopically entangled states are always used in Grover's algorithm and almost always used in Shor's algorithm. Since they are representative algorithms for unstructured and structured problems, respectively, our results support strongly the conjecture that quantum computers utilize macroscopically entangled states when they solve hard problems much faster than any classical algorithms.