Number Partitioning with Grover's Algorithm in Central Spin Systems

TL;DR

This paper introduces a quantum algorithm using Grover's search to solve subset sum and number partitioning problems by encoding solutions in qubit couplings, demonstrating potential quantum speedup and scalable implementation schemes.

Contribution

It proposes a novel quantum approach to NP-complete problems using central spin systems, including scalable algorithms and experimental implementation strategies.

Findings

Quantum speedup across phase transition in partition problem

Recursive algorithm enables scalability for NP-complete problems

Implementation schemes proposed for cold atom platforms

Abstract

Numerous conceptually important quantum algorithms rely on a black-box device known as an oracle, which is typically difficult to construct without knowing the answer to the problem that the algorithm is intended to solve. A notable example is Grover's search algorithm. Here we propose a Grover search for solutions to a class of NP-complete decision problems known as subset sum problems, including the special case of number partitioning. Each problem instance is encoded in the couplings of a set of qubits to a central spin or boson, which enables a realization of the oracle without knowledge of the solution. The algorithm provides a quantum speedup across a known phase transition in the computational complexity of the partition problem, and we identify signatures of the phase transition in the simulated performance. Whereas the naive implementation of our algorithm requires a spectral resolution that scales exponentially with system size for NP-complete problems, we also present a recursive algorithm that enables scalability. We propose and analyze implementation schemes with cold atoms, including Rydberg-atom and cavity-QED platforms.