Trapped-Ion Quantum Simulation of Collective Neutrino Oscillations

TL;DR

This paper demonstrates how to simulate collective neutrino oscillations using quantum computers, analyzing error sources, optimizing circuit complexity, and successfully running experiments on a trapped-ion quantum device.

Contribution

It introduces a quantum simulation method for collective neutrino oscillations, optimizing circuit design and demonstrating practical implementation on a trapped-ion quantum computer.

Findings

Polynomial scaling of complexity with neutrino number

Error reduction through circuit optimization and connectivity

Successful experimental demonstration on a trapped-ion quantum device

Abstract

It is well known that the neutrino flavor in extreme astrophysical environments changes under the effect of three contributions: the vacuum oscillation, the interaction with the surrounding matter, and the collective oscillations due to interactions between different neutrinos. The latter adds a non-linear contribution to the equations of motion, making the description of their dynamics complex. In this work we study various strategies to simulate the coherent collective oscillations of a system of N neutrinos in the two-flavor approximation using quantum computation. This was achieved by using a pair-neutrino decomposition designed to account for the fact that the flavor Hamiltonian, in the presence of the neutrino-neutrino term, presents an all-to-all interaction that makes the implementation of the evolution dependent on the qubit topology. We analyze the Trotter error caused by the decomposition demonstrating that the complexity of the implementation of time evolution scales polynomially with the number of neutrinos and that the noisy from near-term quantum device simulation can be reduced by optimizing the quantum circuit decomposition and exploiting a full-qubit connectivity. We find that the gate complexity using second order Trotter-Suzuki formulae scales better with system size than with other decomposition methods such as Quantum Signal Processing. We finally present the application and the results of our algorithm on a real quantum device based on trapped-ions qubits.