Quantum-enhanced pulsar detection
Problem
Pulsar detection is a complex task in radio astronomy, involving the processing of vast amounts of data to locate these distant cosmic beacons. Together with ASTRON, we aim to refine the detection and analysis of pulsars, thereby enriching our cosmic knowledge. This is a massive task, partly due to undetectable cosmic phenomena.
Solution
This project leverages quantum computing to accelerate and improve the analysis of astronomical data. Two methods are central: a variational one-qubit classifier and a Variational Quantum Linear Solver (VQLS). The one-qubit classifier simplifies data categorisation, aiding in the rapid identification of potential pulsars. The VQLS, available on QAL's GitHub, offers a new approach to solving linear systems of equations for image reconstruction, a common challenge in pulsar data analysis, with improved efficiency and scalability through quantum computing.
Benefit
The application of quantum computing in pulsar detection can significantly reduce data analysis times and potentially reveal previously undetectable cosmic phenomena. The signal processing pipeline consists of many computationally intensive steps. The introduction of variational classifiers and VQLS in various parts of this pipeline lays the foundation for profound discoveries in the field.
