Thursday, August 22nd, 2024

Enjoy a nice cup of freshly brewed quantum news ☕️ 

Today’s issue includes:

• Phasecraft cautions that the shelving of £1.3 billion in tech and AI funding by the new Labour government could drive UK startups to seek investment abroad.  

• Researchers from Forschungszentrum Jülich in Germany and the IBS Center for Quantum Nanoscience in Korea have developed an atomic-scale quantum sensor capable of detecting electric and magnetic fields.  

• BosonQ Psi and materialsIN collaborated to develop a QML solution that improves the effectiveness of detecting surface cracks in concrete materials.

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

🌍 UK Quantum Startup Warns of Funding Risks Amidst Shift in Government Support

QUICK BYTE: Phasecraft, a leading UK quantum computing startup, has cautioned that the shelving of £1.3 billion in tech and AI funding by the new Labour government could drive UK startups to seek investment abroad.

DETAILS: 

• Phasecraft, a UK quantum computing startup, warns that the UK's decision to halt £1.3bn in tech funding could push startups to move investments overseas. Co-founder Ashley Montanaro emphasized the importance of stable funding for maintaining the UK's leadership in quantum technology, noting that companies are increasingly setting up international offices in response to uncertain support at home.

• Phasecraft has already established a US office with future expansions possibly in Europe or Australia. Phasecraft received significant interest, with over 50 applicants for positions in their US office — a testament to the high demand for specialized quantum computing talent.

• This highlights a significant shift in government policy that could impact the UK's position in the global quantum technology race. The previous Conservative government was a strong supporter of quantum computing, pledging substantial funding over a decade.

🧲 Quantum Sensing Detecting Fields at the Atomic Scale

QUICK BYTE: Researchers from Forschungszentrum Jülich in Germany and the IBS Center for Quantum Nanoscience in Korea have developed an atomic-scale quantum sensor capable of detecting electric and magnetic fields at an unprecedented resolution of 0.1 nm.

DETAILS: 

• Researchers from Forschungszentrum Jülich in Germany and the IBS Center for Quantum Nanoscience in Korea developed a quantum sensor with a spatial resolution of 0.1 nm that can detect electric and magnetic fields at the atomic scale.

• This high-resolution sensor enables the detection of fields from individual atoms, which could lead to further progress in studying complex magnetic orders in quantum materials and developing atomic-scale MRI techniques.

• The sensor was created by attaching a molecule with a molecular spin to the tip of a scanning tunneling microscope, achieving a sensitivity far greater than previous sensors based on NV centers in diamond.

🛠️ Quantum Machine Learning Upgrades Material Informatics in Concrete Crack Detection

QUICK BYTE: BosonQ Psi and materialsIN collaborated to develop a QML solution that improves the accuracy, speed, and cost-effectiveness of detecting surface cracks in concrete materials.

DETAILS: 

• BosonQ Psi and materialsIN, deep-tech ventures based in upstate New York, developed a QML solution for surface crack detection in concrete, yielding higher accuracy and efficiency compared to classical methods that struggle with complex and imbalanced data in material informatics.

• The hybrid quantum-classical neural network model integrates classical feature extraction with quantum processing and improves performance metrics such as accuracy and F1-score, as well as excels in handling imbalanced datasets, which is a common challenge in material informatics.

• The QML model achieved 98% accuracy with only 2137 trainable parameters, outperforming the classical model, which had 14 million parameters and 93.44% accuracy.

• The successful application of QML in this use case demonstrates its potential in solving real-world industrial problems, particularly in reducing costs and time in material defect detection, with broader implications across various industries like aerospace, defense, and manufacturing.

🔦 Sandia National Laboratories and Arizona State University are partnering to integrate quantum technology with large-scale optical systems into chip-sized microsystems for advancing quantum processing capabilities. This collaboration will scale down bulky optical systems in exchange for improved performance and scalability for quantum computing and secure communications. The project has received significant funding, including a $17 million grant for the development of error-corrected photonic qubits.

👩‍💻 IBM has released Qiskit SDK v1.2 with improvements that further add to the performance and functionality of this quantum computing framework. This update moves much of the circuit infrastructure to Rust for faster circuit construction and manipulation, as well as improved synthesis and transpilation. Additionally, this version will be the last to support Python 3.8, with future versions requiring Python 3.9.

🏆️ IonQ and Classiq powered the winning projects at the UK’s National Quantum Computing Centre’s 2024 Hackathon, where students and researchers tackled real-world challenges in areas such as healthcare, energy, and engineering. This is the second consecutive year that IonQ’s QPUs and Classiq’s software have been integral to the event, showcasing their capabilities in optimizing and executing quantum algorithms. The winning teams used these tools to develop scalable quantum solutions to prove the potential impact of quantum computing in practical applications.

🛡️ QuDef, a quantum technology and cybersecurity solutions provider, has launched the early access version of Open Access SQOUT, the first-ever quantum TTP-based Cyber Threat Intelligence platform. This platform helps professionals stay ahead by identifying and sharing tactics, techniques, and countermeasures, offering unclassified insights into quantum and classical vulnerabilities.

📖 Classiq releases its Classiq 101 guide as a starting point to understanding and using Classiq, a platform for developing quantum algorithms. You'll begin with registration and installation, quickly move on to running your first quantum algorithm, and then choose between two learning paths: understanding core Classiq concepts or exploring fundamental quantum algorithm building blocks. Each section is interconnected for flexible learning, and further mastery of Classiq is encouraged through the platform’s community Slack channel and advanced resources.

🧙 Researchers from the University of Sydney, the University of Chicago, and Hon Hai Quantum Computing Research Center investigate the impact of random quantum data on quantum machine learning performance. They identify a phenomenon termed the "curse of random quantum data," where the training efficiency and generalization capabilities of QML are significantly hindered when quantum data is encoded randomly. The study finds that as the number of qubits increases, the performance of QML systems decreases exponentially due to the vast Hilbert space, leading to poor generalization and slower convergence. The researchers emphasize that designing quantum datasets carefully can mitigate these issues and improve the efficiency and effectiveness of QML.

LISTEN

In this episode, Mira and Chris sat down with Markus Müller, a quantum error correction expert, to discuss its critical role in developing large-scale quantum computers. The conversation also explores his contributions to logical qubit experiments and fault-tolerant quantum computing strategies.

PONDER

While not quantum-specific, computationally-interesting — Russell Impagliazzo’s work over the last 40 years has been instrumental in understanding computational complexity. Impagliazzo’s research bridges cryptography and complexity theory, leading to groundbreaking insights such as the five hypothetical worlds that frame the famous P versus NP problem. His fascination with hypothetical worlds extends beyond mathematics into his lifelong passion for role-playing games, where he explores alternative realities with the same curiosity that drives his scientific endeavors.

WATCH

Dr. Trevor Lanting and Murray Thom from D-Wave discuss advancements in coherent annealing quantum computing and D-Wave's fast anneal feature:

• On Saturday, August 24th, Washington DC Quantum Computing Meetup is hosting PiQture - A Quantum Machine Learning Library for Image Processing, a discussion of the open-source Python and Qiskit-based library for QML models —virtual

• On Monday, August 26th, WOMANIUM is hosting Unlocking the Future: Research and Quantum Computing Innovations at Utility—virtual

• On Tuesday, August 27th, qAIntum.ai is hosting another installment in the Quantum Gen AI lecture series, the History of Quantum Computing —in-person (Menlo Park, CA).

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