Monday, August 26th, 2024

Enjoy a nice cup of freshly brewed quantum news ☕️ 

Happy Monday, readers!

I've been eagerly awaiting this moment all weekend. The Daily Qubit is officially partnering with The Quantum Insider to bring you even more exclusive, data-driven insights into the quantum industry. There will be no interruption to your daily news and research—only added bonuses to come. Stay tuned for more updates.

In addition, as part of this exciting partnership, I’ll have the distinct honor of joining their team as a Journalist and Data Analyst!

Rest assured, Universum Labs continues to develop behind the scenes. To stay informed with releases, stakeholder updates, and the chance to become a beta user, please join our waitlist here.

Forever and onward,

Cierra

Today’s issue includes:

• Amazon Braket has added the 84-qubit Ankaa-2 superconducting quantum processor from Rigetti Computing to its cloud computing service in the US West region.

• Algorithmiq scientists have developed a tensor network-based method for characterizing noise in near-term quantum computers.

• Researchers from HRL Laboratories, Boeing Research & Technology, and MIT have explored the potential of using quantum computation to stabilize cyclic ozone within fullerene cages.

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

🚀 Amazon Braket Expands with Rigetti's 84-Qubit Ankaa-2

QUICK BYTE: Amazon Braket has added the 84-qubit Ankaa-2 superconducting quantum processor from Rigetti Computing to its cloud computing service in the US West region.

DETAILS: 

• The expansion of AWS cloud computing with the launch of Rigetti's Ankaa-2 on Amazon Braket expands quantum computing accessibility and further reduces barriers to quantum experimentation, a concern that has troubled researchers and industry alike.

• Unlike other devices available through AWS, the new Rigetting QPU will provide continuous availability for running quantum tasks instead of being restricted to a certain timeframe, an issue complicated by different time zones.

• Ankaa-2 is a superconducting quantum processor with 84 qubits, supporting hybrid quantum-classical jobs and parametric compilation. It offers faster gate operations and improved two-qubit gate fidelities as compared to Rigetti's Aspen-M-3 family.

🧮 Algorithmiq Deploys Tensor Networks for Noise Characterization

QUICK BYTE: Algorithmiq scientists have developed a tensor network-based method for characterizing noise in near-term quantum computers, demonstrating its effectiveness on systems with up to 20 qubits.

DETAILS: 

• Accurate noise characterization is of utmost importance in order to maximize the performance of near-term quantum computer. A tensor network method developed by scientists from Algorithmiq, a quantum computing company dedicated to finding quantum solutions for the life sciences, offers a scalable and practical solution in implementing effective quantum error mitigation techniques in real-world applications.

• Traditional quantum process tomography methods quickly lose practicality for systems with tens of qubits due to their exponential resource requirements. The researchers adapted a tensor network-based quantum process tomography method to characterize noise channels on quantum computers. This approach reduced the computational burden, allowing for efficient noise characterization even in larger quantum systems.

• The method was tested on various noise models, including realistic correlated noise, using up to 20 qubits. It accurately characterized noise channels with a modest amount of experimental data, achieving error rates as low as 10^-3 in the reconstruction process. It was also resilient to state preparation and measurement (SPAM) errors, further solidifying its practicality for near-term quantum devices.

🚀 Quantum Computation Fuels Next-Gen Rocket Propellants

QUICK BYTE: Researchers from HRL Laboratories, Boeing Research & Technology, and MIT have explored the potential of using quantum computation to stabilize cyclic ozone within fullerene cages, which could revolutionize rocket fuel efficiency.

DETAILS: 

• Cyclic ozone has a higher energy density than conventional fuels but is highly unstable; stabilizing it within fullerenes could lead to more efficient rocket propellants. Researchers from HRL Laboratories, Boeing Research & Technology, and MIT applied quantum algorithms to predict the feasibility of such material in aerospace technology.

• Previous efforts to stabilize cyclic ozone have been unsuccessful due to its reactivity; quantum computation offers a new approach by simulating and predicting stable configurations within fullerenes. Unlike classical computational methods that are prohibitively expensive and limited in scope, quantum algorithms can handle the complex electronic structures involved in this task.

• Quantum phase estimation was used to calculate the ground state energies of cyclic ozone encapsulated in fullerene cages, determining its stability and potential as a propellant. Various computational frameworks and algorithms, including double-factorized Hamiltonians and dual plane-wave bases, were used to optimize resource efficiency and accuracy.

• Results suggest that cyclic ozone could indeed be stabilized within fullerene cages, making it a viable candidate for next-generation rocket fuels. This could lead to rockets carrying up to 33% more payload, significantly reducing costs and enhancing mission capabilities.

• Even more notable, the success of this study indicates that quantum computation could become a critical tool in designing advanced materials for aerospace and other industries. While further development and optimization of these quantum methods is necessitated, they could enable broader applications in molecular engineering, beyond just rocket propellants.

💻️ Petros Wallden's team at the University of Edinburgh developed quantum machine learning methods using NVIDIA's CUDA-Q platform to reduce the qubit count required for large data set analysis. Using coresets and quantum clustering algorithms, they created a scalable solution that bypasses the need for quantum random access memory (QRAM). This allows for accelerated simulations and the handling of larger problem sizes — important in order to demonstrate competitive performance compared to classical methods.

🔬 Researchers from the University of Chicago and the University of Trento in Italy have developed an exact Ansatz for solving the eigenstate problem in mixed fermion-boson systems, providing a precise and implementable solution on quantum devices. This overcomes previous limitations of traditional methods such as density functional theory and coupled cluster algorithms by avoiding approximations. Tested on the Tavis-Cummings model, the Ansatz demonstrated improved accuracy in predicting ground states and energy levels, particularly in strong coupling regimes, making it highly applicable for research in quantum materials and other complex many-body systems.

🤝 Quantum Machines and Bluefors announced an extended OEM agreement to integrate the QCage sample holder with Bluefors' cryogenic measurement systems. This partnership provides a turnkey solution that reduces hardware setup time, allowing researchers to reinvest saved time back into quantum computing research. By combining Quantum Machines' expertise in quantum control with Bluefors' cryogenic technology, the pre-tested and pre-installed QCage system improves performance through reduced losses and decoherence.

📳 Tony Low and his team at the University of Minnesota Twin Cities have uncovered key insights into how light, electrons, and crystal vibrations interact in materials, focusing on "planar hyperbolic polaritons." This study explores how these hybrid particles can be manipulated to improve on-chip architectures for quantum information processing, potentially reducing fabrication constraints and enhancing thermal management. The research offers promising applications in quantum computing and electronics, supported by funding from the U.S. Office of Naval Research for further development.

❌ As quantum technologies become increasingly critical for national security, Australia has added them to its Defence and Strategic Goods List, imposing export restrictions. Amid global competition and investment in quantum computing, communication, and sensing, experts suggest that Australia would benefit from a national quantum tech accord to unify government, industry, and academia in a coordinated and ethical development strategy. The accord could address the fragmented implementation of previous investments, align short-term and long-term interests, and ensure that Australia remains competitive while safeguarding national security and promoting responsible innovation.

💡 Researchers from the National Research Council of Canada and University of Ottawa have developed a new platform for programmable photonic quantum circuits using ultrafast time-bin encoding, offering phase stability and scalability in quantum information processing. This addresses challenges in quantum photonics by enabling compact, resilient circuits that maintain coherence over extended periods. The platform was validated through high-fidelity experiments, demonstrated scalability with circuits involving up to 36 optical modes, and achieved stable, high-fidelity quantum processing without active stabilization.

🤖 The International Conference on Machine Learning and Applications Special Session on Quantum Machine Learning Algorithms and Applications will focus on the latest advancements in quantum computing, particularly the use of variational quantum circuits and their applications in machine learning and artificial intelligence. The session invites submissions on topics such as trustworthy and privacy-preserving QML, quantum cybersecurity, and QML applications in various fields. Submissions are due by September 5th, 2024 and the conference will take place December 18-20, 2024. Register here.

LISTEN

On the most recent edition of The New Quantum Era podcase, hosts Sebastian Hassinger and Kevin Rowe, interview Jessica Pointing, a PhD candidate at the University of Oxford. They discuss the challenges of applying classical machine learning concepts, such as simplicity bias, to quantum systems, and the potential limitations and opportunities of quantum neural networks.

ENJOY

In a recent interview, Ferdinand Tomassini, CEO and cofounder of Moth Quantum, shared how his company is bridging the gap between quantum computing and the creative industries. Tomassini explained that Moth Quantum is on a mission to revolutionize music, gaming, and digital art by making quantum technology accessible to artists. The company was born from a convergence of passionate communities eager to explore quantum's potential in creative fields, and they are now rolling out innovative products like the Quantum Synthesizer and Generative Music System. Tomassini envisions a future where quantum computing becomes a key tool for creativity, unlocking new possibilities that were once unimaginable.

WATCH

This Qiskit Global Summer School lecture on quantum machine learning covers near-term algorithms, focusing on variational quantum circuits as classifiers, quantum kernels, support vector machines, and quantum neural networks:

• 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).

• On Thursday, September 5th, paper submissions are due for the 23rd International Conference on Machine Learning and Applications.