Quantum Brain
← Back to papers

Collective neutrino oscillations on a quantum computer

Kubra Yeter-Aydeniz, Shikha Bangar, G. Siopsis, Raphael C. Pooser·April 7, 2021·DOI: 10.1007/s11128-021-03348-x
PhysicsComputer Science

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

We calculate the energy levels of a system of neutrinos undergoing collective oscillations as functions of an effective coupling strength and radial distance from the neutrino source using the quantum Lanczos (QLanczos) algorithm implemented on IBM Q quantum computer hardware. Our calculations are based on the many-body neutrino interaction Hamiltonian introduced in Patwardhan et al. (Phys Rev D 99, https://doi.org/10.1103/PhysRevD.99.123013, 2019). We show that the system Hamiltonian can be separated into smaller blocks, which can be represented using fewer qubits than those needed to represent the entire system as one unit, thus reducing the noise in the implementation on quantum hardware. We also calculate transition probabilities of collective neutrino oscillations using a Trotterization method which is simplified before subsequent implementation on hardware. These calculations demonstrate that energy eigenvalues of a collective neutrino system and collective neutrino oscillations can both be computed on quantum hardware with certain simplification to within good agreement with exact results.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.