Advancing Quantum State Detection Techniques

I'm excited to share our latest work, Demonstration of robust and efficient quantum property learning with shallow shadows, published in Nature Communications! 🎉 📝 Authors: Hong-Ye Hu, Andi Gu, Swarnadeep Majumder, Hang Ren, Yipei Zhang, Derek S. Wang, Yi-Zhuang You, Zlatko Minev, Susanne F. Yelin, Alireza Seif 🔍 Context: Extracting information efficiently from quantum systems is crucial for advancing quantum information processing. Classical shadow tomography offers a powerful technique, but it struggles with noisy, high-dimensional quantum states and complex observables. 🤔 Key Question: Can we overcome noise limitations and improve sample efficiency in quantum state learning, especially for high-weight and non-local observables, using shallow quantum circuits? 💡 Our Findings: We introduce robust shallow shadows—a protocol designed to mitigate noise using Bayesian inference, enabling highly efficient learning of quantum state properties, even in the presence of noise. Our experiments on a 127-qubit superconducting quantum processor confirm the protocol’s practical use, showing up to 5x reduction in sample complexity compared to traditional methods. ✨ Key Takeaways: 1. Noise-resilience: Accurate predictions across diverse quantum state properties. 2. Sample Efficiency: Substantial reduction in sample complexity for high-weight and non-local observables. 3. Scalability: The protocol is well-suited for near-term quantum devices, even with noise. Paper: https://lnkd.in/dW4NJ23Q

China unveils drone-mounted quantum device for submarine detection in South China Sea - Chinese scientists’ breakthrough in magnetic detection technology could give China the edge in submarine warfare amid Sino-US tension - As US-China tensions simmer over submarine operations in the South China Sea, Chinese space scientists have unveiled a breakthrough in magnetic detection technology that could tip the balance in underwater warfare. - A drone-mounted quantum sensor system, tested successfully in offshore trials, achieved picotesla precision to track magnetic anomaly and map seabed resources while overcoming some severe practical limitations of existing devices, researchers disclosed in a peer-reviewed paper. - With such sensitivity, People’s Liberation Army’s (PLA) anti-submarine forces cannot only pinpoint a submarine but also catch the tail waves it generates, according to some previous studies. - the Coherent Population Trapping (CPT) atomic magnetometer. Leveraging quantum interference effects in rubidium atoms, the device exploits Zeeman splitting – energy level shifts caused by magnetic fields – to generate seven microwave resonance signals. - These frequencies correlate linearly with magnetic field strength, enabling omnidirectional detection regardless of orientation, according to the researchers. - With a sensitivity of 8pT by design – on par with Canada’s MAD-XR system used by Nato allies – the Chinese system eliminates blind zones while cutting costs and complexity. - The towed system developed by Wang and his colleagues, described in a paper published in the Chinese Journal of Scientific Instrument on April 16, pairs the CPT sensor with a rotor drone via a 20-metre (65.6ft) cable to minimise electromagnetic interference from the aircraft. - A fluxgate magnetometer corrects heading errors, while GPS and ground stations process data using algorithms that suppress noise, compensate for diurnal geomagnetic shifts, and generate high-resolution anomaly maps. - During trials off Weihai, Shandong province, the drone surveyed a 400 by 300-metre grid with 34 crossover points. Raw data showed 2.517 nanotesla (nT) accuracy, refined to 0.849 nT after error correction – a threefold improvement. - Crucially, two independent surveys achieved a 99.8 per cent correlation in magnetic anomaly maps, with a root mean square error (RMSE) of just 1.149 nT, “demonstrating outstanding stability in real life tests”, Wang’s team added. - This is not just about submarines, according to the researchers. At picotesla-level sensitivity, it can map oil reservoirs, archaeological wrecks, and tectonic shifts. - https://lnkd.in/eYdDkCit

Qunnect's team has demonstrated polarization entanglement between telecom photons and a room-temperature quantum memory. #Quantum memories are critical elements of entanglement-based quantum networks, enabling the storage and retrieval of quantum states. Our breakthroughs tackle major limitations of existing quantum platforms, which usually rely on cryogenic setups and vacuum apparatus. Room-temperature quantum memories and #entanglement sources, like those based on atoms of rubidium, offer practical solutions for quantum networking, repeaters, and distributed #quantumcomputing or #quantumsensing. As we continue advancing these technologies, we anticipate many further improvements: extending coherence times into the millisecond regime through specialized vapor cells, enhancing fidelity with optimized photon sources, and increasing efficiency via noise filtering techniques... All towards increasing the performances of our existing commercial units, including the #quantummemory we launched in 2021, and which remains, for now, the only commercially available quantum memory. Ultimately, our solutions pave the way for scalable, affordable, and reliable quantum infrastructure suited to real-world applications. > For all the details, check out our team's pre-print paper by Yang Wang, here: https://lnkd.in/eQn6_xUv > Or explore a deep-dive blog post from Qunnect’s CSO Mehdi Namazi, here: https://lnkd.in/eunnfKpf