Quantum GPS, Teleportation, and X-Rays

The Australian startup Q-CTRL is working on quantum sensor technology. They have developed a navigation system using quantum sensors that can work when satellite GPS is unavailable. The sensor uses the quantum physics of atoms to detect motion and any small changes in Earth’s gravity. This technology could guide military equipment with minimal directional error.

Countries are racing to develop quantum technologies, with the US considering stricter export controls to stay ahead of competitors. However, there are concerns that heavy restrictions on quantum technology could make overall progress slower. For the US, clear guidelines for export are essential to maintain a competitive advantage against countries like China.

D-Wave has partnered with the Institute for Quantum Computing (IQC) for hardware research. Canada's National Quantum Strategy is funding them through the NSERC Quantum Alliance program. The research improves device design and material quality to enhance the coherence in superconducting quantum processors. The collaboration will explore the physics of new superconducting qubits, paving the way for future quantum computing architectures. This collaboration is also expected to help build Canada's quantum-ready workforce, providing experience in their growing quantum computing field.

Researchers from the University of Electronic Science and Technology of China (UESTC) used a low-Earth orbit Micius satellite and achieved quantum teleportation over 1200 km. Quantum teleportation transfers information to different locations through quantum entanglement and classical communication.

The main experiment for a teleportation system is performing the Bell state measurement (BSM). The researchers developed a feedback system to enhance the efficiency and accuracy of their model. They used sensitive superconducting nanowire single-photon detectors for the analysis. UETC’s high-speed teleportation achieved extremely accurate results, surpassing the previous maximum level possible in classical systems (66.7%).

Cornell researchers have developed an advanced imaging technique using X-rays, algorithms, and machine learning to reveal nanotextures in thin-film materials. These nanotextures give the material unique properties, making them valuable for quantum computing.

The new imaging technique uses phase retrieval and machine learning to convert X-ray diffraction data into a physical visualization of the material. X-ray diffraction makes the technique more accessible and allows a larger portion of the sample to be photographed, providing a better representation of the material's true state. This technique has potential applications in studying future terahertz technologies, like quantum sensors and computing.