Summary
An important challenge in building a quantum computer is quantifying the level of control obtained in the preparation of a quantum state. The state of a quantum device is characterized from experimental measurements, using a procedure known as tomography. Exact tomography requires a vast amount of computer resources, making it prohibitive for quantum devices larger than a few qubits. In this project we develop a practical, approximate tomography method using modern machine learning techniques. Our work is based on training artificial neural networks using measurement data obtained from a system of qubits. After training, the neural network is sampled to determine properties of the underlying quantum state. As part of a collaborative effort, we will demonstrate our machine learning algorithms on both synthetic and experimental measurement data. Our ultimate goal is to deliver practical machine learning technology to design and characterize near-term quantum devices.
Figure 1. A visualization of the phases of a quantum wavefunction of 100 qubits. At left, the exact value of the phases, obtained from a large-scale computer simulation. At right, the phases reconstructed with state tomography using artificial neural networks.
Related Content
Using Interactive Digital Storytelling to Represent Transformative Quantum Technologies in Augmented/Extended Reality Environments
Summary A major roadblock to the broader adoption of quantum technologies is the long learning curve associated with their seemingly abstract concepts. This often renders quantum technologies inaccessible to most audiences, especially through explanations using conventional scientific language. In this project, we develop novel methods of interactive digital storytelling – augmented and extended reality (AR/XR) […]
February 24, 2021
Line-Scanning optical coherence tomography system for in-vivo, non-invasive imaging of the cellular structure and blood perfusion of biological tissue
Summary Optical coherence tomography (OCT) is an optical imaging method that allows for in-vivo, non-invasive imaging of the structure and vasculature of biological tissue. Commercially available, clinical OCT systems utilize point-scanning method to acquire volumetric images over a large surface with typical frame rates of ~ 30 frames/ second. Since living biological tissue is constantly […]
August 27, 2019
Coherent magnon generation, magnon condensation, and quantum spin liquids via spin pumping in 2D magnets
Summary Developing hybrid quantum systems is essential to harnessing the complementary advantages of different quantum technology platforms. This necessitates the successful transfer of quantum information between platforms, which can be achieved, e.g., by harnessing magnons, or spin wave excitations, in magnetic materials. Decoherence due to uncontrolled coupling of qubits to the environment remains a fundamental […]
February 1, 2023
Applications of Neutron Interferometry and Structured Neutron Beams
Summary Neutrons are a powerful probe of matter and physics due to their Angstrom size wavelengths, electric neutrality and relatively large mass. In this project, we develop quantum sensors that exploit these attributes to increases the precision of measurements of fundamental forces and materials structure. With David Cory, Alexander Cronin of the University of Arizona, […]
July 31, 2018