Tuesday, October 1st, 2024

Enjoy a nice cup of freshly brewed quantum news ☕️ 

Today’s issue includes:

• IBM has launched its first European Quantum Data Center in Ehningen, Germany.

• Scientists explore whether quantum error mitigation or learning-based techniques can improve the sensitivity of noisy quantum sensors.

• Qibocal facilitates the calibration and characterization of self-hosted superconducting quantum devices.

• The QuaST decision tree provides an automated framework for developing quantum-assisted solutions to industrial optimization problems.

• Plus quantum annealing for AI-driven drug discovery, ceramic as the novel material for quantum devices, integrated optical fibers, and more .

And even more research, news, & events within quantum.

🎉 IBM Opens First European Quantum Data Center in Germany, Supporting Quantum Innovation with Heron-Based Systems

QUICK BYTE: IBM has launched its first European Quantum Data Center in Ehningen, Germany, providing powerful new quantum systems to European enterprises and research institutions for advancing quantum computing applications.

DETAILS

• IBM’s new Quantum Data Center in Germany is part of the company’s strategy to expand its global quantum computing capabilities, featuring the IBM Quantum Heron-based system, which offers a 16-fold increase in performance and 25-fold faster speeds compared to earlier systems.

• The ultimate goal of the center is to support the development of quantum algorithms and practical quantum use cases, with key partners such as Bosch, Volkswagen, and the University of the Basque Country using these quantum systems to advance fields like energy optimization, materials science, and finance.

• This facility is IBM’s second global quantum data center, supporting European regulatory and processing proximity requirements, and providing cloud-based access to utility-scale quantum systems via the IBM Quantum Platform.

📚️ Learning-Based Inference Outperforms Error Mitigation in Enhancing Noisy Quantum Sensor Sensitivity

QUICK BYTE: Scientists from Los Alamos National Laboratory, Vector Institute, and others explore whether quantum error mitigation or learning-based techniques can improve the sensitivity of noisy quantum sensors and concludes that learning-based inference techniques, rather than zero-noise extrapolation, provide the best performance when operating under a limited shot budget.

DETAILS

• The authors present an analysis of quantum sensing under noise, examining strategies such as error mitigation and inference techniques to improve measurement sensitivity. They find that error-mitigation techniques like zero-noise extrapolation often provide diminishing returns compared to learning-based inference approaches.

• Through detailed bias-variance analysis of noisy sensing protocols, the paper concludes that inference-based pre-characterization of the sensor’s response function leads to better performance than direct shot investments in error mitigation techniques.

• The work demonstrates that under realistic noise levels, the stability and pre-characterization of the sensor become essential for optimal performance. The study stresses that zero-noise extrapolation, despite its potential to remove noise, often increases variance and reduces the overall sensing precision.

• The paper’s results are significant for advancing quantum sensing applications, suggesting that learning the sensor’s noisy response function provides a more efficient use of resources and greater precision, positive news for fields requiring high-sensitivity measurements under practical constraints.

👩‍💻 Qibocal: Streamlining Superconducting Quantum Device Calibration with Automated Open-Source Tools

QUICK BYTE: Qibocal, an open-source software framework, was developed by scientists from the Technology Innovation Institute in Abu Dhabi, CERN, and others to facilitate the calibration and characterization of self-hosted superconducting quantum devices, integrating with the Qibo framework to automate and optimize the performance of quantum processors.

DETAILS

• Qibocal is a key extension of the Qibo framework, and serves as a tool for the automatic calibration and monitoring of superconducting quantum devices, relevant for optimizing the parameters required for high-fidelity quantum computation in real-world environments.

• The framework supports single- and two-qubit gate calibration, offering routines such as Rabi experiments, Ramsey spectroscopy, and randomized benchmarking to fine-tune pulse parameters, correct qubit frequencies, and maximize gate fidelities.

• Qibocal introduces flexible tools for recalibration and automatic monitoring, enabling users to recalibrate quantum devices based on dynamic changes such as flux drifts, ensuring consistent performance over time.

• The significance of Qibocal lies in its ability to reduce redundancy in quantum calibration protocols across research institutions, improving the scalability and reliability of quantum hardware platforms and promoting broader adoption of self-hosted quantum devices.

🌲 QuaST Decision Tree: Automating Quantum-Assisted Solutions for Industrial Optimization and Bridging Research with Real-World Applications

QUICK BYTE: Designed by researchers from Fraunhofer Institute for Cognitive Systems, the QuaST decision tree provides an automated framework for developing quantum-assisted solutions to industrial optimization problems, streamlining the process from problem formulation to the selection of hybrid quantum-classical algorithms, making quantum computing more accessible for non-experts.

DETAILS

• The QuaST decision tree is a modular and flexible software framework designed to automate the process of solving industrial optimization problems using quantum-assisted methods like the quantum approximate optimization algorithm and the variational quantum eigensolver.

• It integrates with quantum computing frameworks such as Qiskit and provides a guided decision-making process for non-experts, reducing the complexity of algorithm selection, problem formulation, and hardware backend choices through an interactive and automated interface.

• By automating complex tasks, such as selecting the appropriate algorithm and configuring it for specific optimization problems, the QuaST decision tree enhances accessibility and scalability of quantum computing solutions, allowing researchers and industry practitioners to test quantum methods on real-world use cases more easily.

• The paper highlights the potential of the QuaST framework to foster collaboration between quantum computing researchers and industry, bridging the gap between theoretical research and practical quantum computing applications in fields like logistics, finance, and production planning​.

D-Wave Quantum and Japan Tobacco's pharmaceutical division announced a joint proof-of-concept project using D-Wave's annealing quantum computing to explore AI-driven drug discovery. The goal of the collaboration is to accelerate the speed and quality of AI systems in identifying 'first-in-class' pharmaceutical compounds by leveraging quantum technology. Following the initial project, JT plans to further develop these quantum AI systems for production use in drug design.

India’s National Quantum Mission has announced the establishment of four Thematic Hubs (T-Hubs) at premier institutions, including IISc Bengaluru and IITs, to lead advancements in quantum computing, communication, sensing, and materials. These T-Hubs, selected from 384 proposals, will drive research, human resource development, and collaboration, with a focus on scalable quantum technologies. The overall goal of the initiative is to elevate India as a leader in quantum technologies by encouraging partnerships between academia, startups, and industry.

Researchers have proposed a hybrid quantum-classical algorithm called the photonic counterdiabatic quantum optimization, designed for continuous-variable optimization on photonic quantum computing systems. The algorithm uses counterdiabatic protocols to reduce the number of required quantum operations and outperforms existing quantum optimization methods like CV-QAOA in convergence and implementability. A proof-of-principle demonstration on Xanadu’s eight-mode photonic chip validated the algorithm’s potential for practical quantum applications.

Researchers at the Ferdinand-Braun-Institut demonstrated the use of 3D-printed ceramics to improve the resilience and portability of quantum devices, which traditionally suffer from instability due to the use of metal components. By 3D printing ceramic housings for quantum sensors, the team reduced device size while maintaining performance and stability. Their work presents a miniaturized optical frequency reference that could be integrated into various quantum systems, demonstrating the potential for ceramics to improve the scalability and practicality of quantum technologies.

QuantumDiamonds has introduced the QD m.0, the first commercial quantum device specifically designed for semiconductor chip failure analysis, utilizing diamond-based quantum microscopy for precise fault detection in integrated circuits. The device addresses challenges in 2.5D/3D packaging and chiplet-based architectures, enabling manufacturers to localize faults and improve production yields. By integrating advanced software with optimized quantum sensing technology, the QD m.0 offers a solution to the growing complexity of modern semiconductor designs, with the first units shipping by Q4 2024.

Infleqtion and Thorlabs have partnered to accelerate the commercialization of quantum technologies by releasing Infleqtion’s integrated optical fiber collimation package, a crucial component for quantum applications. This compact, robust package offers a linearly polarized beam with integrated power monitoring, improving reliability and performance in quantum devices. Developed as part of the QT Assemble project, the partnership intends to bring quantum solutions to market faster by making high-quality, cost-effective components accessible to researchers and product developers worldwide.

LISTEN

On the most recent episode of the Superposition Guy’s podcast, Yuval Boger, CMO of QuEra, sits down with Rob Schoelkopf, co-founder and chief scientist at Quantum Circuits Inc., and Ray Smets, CEO. Rob shares insights on Quantum Circuits’ unique dual-rail qubit approach, which focuses on reducing error rates through error detection and correction at the hardware level. Ray emphasizes the company’s shift from scientific research to commercial implementation, highlighting its cost-efficiency and full-stack quantum computing solution. They discuss the scaling potential of superconducting qubits, the importance of error correction, the next steps for Quantum Circuits’ technology, and much more.

ENJOY

Dr. Sana Amairi-Pyka, Lead Scientist for Quantum Communications at the Technology Innovation Institute, is leading the Abu Dhabi Quantum Optical Ground Station project to make the UAE a leader in space-based quantum communication. With a Ph.D. in Quantum Optical Metrology and a history of contributing to space missions, Amairi-Pyka now focuses on quantum key distribution for secure data transmission. In a recent interview, she explains the growing need for QKD, especially as quantum computers threaten traditional encryption, and highlights industries such as finance, defense, and critical infrastructure as early adopters.

WATCH

Dr. Shohini Ghose, physicist and CTO at the Quantum Algorithms Institute, discusses her quantum science journey: