Welcome to the Quantum Realm.

Enjoy today’s breakdown of news, research, & events within quantum.

🦗Relatively quiet day on the quantum front — but there is quantum excitement to be had in Berkeley Lab’s process for identifying and fabricating quantum materials. Plus, if there were QIS standards for secondary schooling, these would be it.

🗓️UPCOMING

Sunday, July 21 | QTM-X Quantum Education Series 6 of 10: Quantum Hardware

📰QUANTUM QUICK BYTES

🧫Researchers at Berkeley Lab have developed a rapid computational approach for quantum materials: Researchers at Berkeley Lab, in collaboration with multiple institutions, have successfully demonstrated a new method to accelerate the discovery of quantum materials by combining rapid computational predictions with precise fabrication techniques. This approach screens hundreds of materials to identify promising candidates, which are then fabricated and evaluated for quantum properties. The team focused on two-dimensional materials, such as tungsten disulfide, and identified defects that could be beneficial for quantum applications. One significant finding was a cobalt defect in WS2, which had previously unknown quantum properties. The results of their research are shared in a publicly available database called the Quantum Defect Genome.

⚛️IBM has joined Fermilab's SQMS Center in the name of superconducting quantum systems: IBM has been approved as a new partner in the Superconducting Quantum Materials and Systems Center at Fermilab that will bring together IBM's superconducting quantum computing technology and SQMS's expertise to overcome challenges in quantum computing, communication, and large-scale deployment. The collaboration will focus on large-scale cryogenics, quantum interconnects, noise reduction in qubits, and developing scientific applications for quantum systems. Additionally, IBM and SQMS will work towards establishing quantum workforce development programs to attract and train the next generation of quantum professionals.

🔗Quandela and Welinq have partnered to advance photonic quantum computing by integrating quantum interconnects: Quandela has partnered with Welinq to combine expertise in quantum processors and interconnect technology. This collaboration will work towards creating custom quantum links for photonic quantum computers, enabling interconnected and error-corrected quantum computer clusters. The real highlight is the capability of the technology itself: photonic QPUs offer modularity and high-speed data transmission (ideal for complex computations), and efficient quantum interconnects (necessary for linking multiple QPUs) maintain the integrity of quantum information during transmission.

🧊attocube supports the scaling and commercialization of quantum tech with nanotechnology: The quantum technology supply chain is evolving as companies like Google, Microsoft, IBM, and start-ups transition from research to commercial opportunities in quantum computing, communications, and metrology. attocube, a German nanotechnology manufacturer, is providing essential R&D and manufacturing tools, such as low-vibration cryostats and precision-motion components. attocube emphasizes a collaborative R&D approach with clients — a key example being their attoCMC cryostat, which improves energy efficiency and supports the deployment of quantum technologies like Quandela’s single-photon source, Prometheus, for scalable quantum computing and networking applications.

☕️FRESHLY BREWED RESEARCH

TEACHING QUANTUM INFORMATICS AT SCHOOL: COMPUTER SCIENCE PRINCIPLES AND STANDARDS

QUICK BYTE: The case for integrating quantum informatics into secondary school curricula is made through positioning it within traditional computer science education, aligning it with the Great Principles of Computing, and establishing standards for expected student outcomes.

PRE-REQS:

• The Great Principles of Computing make up a framework defined by Peter Dunning that identifies seven fundamental categories of computing: computation, communication, coordination, automation, recollection, design, and evaluation.

• The CSTA K-12 Computer Science Standards were developed by the Computer Science Teachers Association and outline the essential concepts and practices that students should be exposed to a each grade level. Key areas include computational thinking, collaboration, computing practice and programming, computing systems, data and analysis, and the impacts of computing.

SIGNIFICANCE: As quantum technologies advance, the importance of integrating quantum informatics into the secondary school curriculum becomes more and more relevant. Quantum informatics is the application of quantum physics to computer science to provide a new paradigm of problem-solving. The authors argue that early education in quantum informatics can prepare students for future technological developments as well as the benefit that comes from studying quantum science in general: that it challenges you to rethink the lens through which you view your reality due to the abstract nature of the concepts that are not visible to us regularly to encourage a more natural and deeper understanding of the complex topics.

While there have been efforts to create and provide interactive and engaging resources for young adults and children, through games, DIY experiments, community initiatives, etc., we have yet to demonstrate how this can be naturally implemented into existing curriculums. The paper has two main objectives: positioning quantum informatics within the traditional computer science curriculum and defining the expected outcomes for students.

Key to determining the curriculum was integrating it with the Great Principles of traditional computer science and reviewed by an external computer science expert before final adoption. The CSTA K-12 Computer Science Standards were reviewed according to the overall learning goals and how to integrate the previously mentioned categorization.

The authors also highlight that certain topics, such as quantum error correction and cryptography, are more suitable for secondary education compared to less developed areas like quantum networks. Various teaching methods are explored, including interactive/gamified, visual, and language-based, as potentially widely-adopted practicies to make quantum informatics accessible and engaging for students.

RESULTS:

• Presents a curriculum designed to blend quantum informatics with traditional computer science education, reviewed by experts to ensure coherence and relevance

• Proposed standards align with the Great Principles of Computing, ensuring students understand key quantum concepts like error correction and cryptography

• Suggested methods include interactive, visual, and language-based approaches, utilizing games, experiments, and tools to make learning engaging and accessible

HONORABLE RESEARCH MENTIONS:

A polynomial-time classical algorithm for simulating noisy quantum circuits computes the expectation value of any observable for circuits affected by noise by leveraging the damping effects of noise on non-local correlations. The approach highlights that any quantum circuit for which error mitigation is efficient must be classically simulable, providing a fundamental limit on noise mitigation strategies. Additionally, the algorithm enables sampling from the output distribution of a circuit in quasi-polynomial time. —> link to A polynomial-time classical algorithm for noisy quantum circuits

A cryogenic on-chip microwave pulse generator has been designed in an effort to advance large-scale superconducting quantum computing. This device generates coherent microwave pulses at millikelvin temperatures, featuring well-controlled phase, intensity, and frequency. By integrating these pulse generators with superconducting quantum circuits, the heat load is minimized and scalability maximized. Successful implementation shows high-fidelity qubit readouts. —> link to A cryogenic on-chip microwave pulse generator for large-scale superconducting quantum computing

A data-agnostic method for predicting properties of quantum states is proposed by using parametrized quantum circuits. It’s tested numerically for tasks like predicting the parameter of a quantum channel, the entanglement of two-qubit states, and the ground state parameter of a Hamiltonian. Results show high accuracy in predictions, sometimes reaching the Cramer-Rao bound. —> link to Predicting properties of quantum systems by regression on a quantum computer

Pulse-Based Variational Quantum Optimization is designed as a hardware-level framework for solving optimization problems using analog quantum computing, specifically targeting superconducting circuits. PBVQO optimizes control pulses to drive quantum states towards target states, as demonstrated through numerical experiments solving the MAX-CUT problem. The method's performance is further improved by meta-learning techniques for parameter initialization and shows advantages over conventional gate-based variational quantum algorithms. —> link to Pulse-based variational quantum optimization and meta-learning in superconducting circuit

UNTIL TOMORROW.