Welcome to the Quantum Realm.

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

🌊 Higher-order quantum reservoir computing for forecasting complex dynamical systems is more effective than several classical ML models as demonstrated on sea surface temperatures — essential for fields such as meteorology, oceanography, and finance. Plus, QuEra is bringing together global expertise to accelerate the deployment of neurtral-atom computers their the QuEra Alliance Partner Program.

🗓️UPCOMING

Saturday, August 3rd | Optimizing Complex Processes using AI and QC

Tuesday, August 6th | Yale Ventures Startup Speaker Series: Mark Jackson, Quantinuum

Tuesday, August 6th | QED-C Summer Lecture Series: Inertial Sensors

📰QUANTUM QUICK BYTES

🌏️ The QuEra Quantum Alliance Partner Program will accelerate the development and deployment of neutral-atom quantum computers: QuEra Computing announces the QuEra Quantum Alliance Partner Program to accelerate the development, deployment, and use of neutral-atom quantum computers. With the assistance of leading technology and solutions companies, such as BIP, BlueQubit, Classiq, and others, the alliance will use the expertise of the global community to tackle complex computational problems globally. Benefits of the program include exclusive events, early access to QuEra technology, and direct support from QuEra’s scientific team.

🧲 Researchers at UCLA have developed a new superconductor material that maintains superconductivity under higher magnetic fields: Researchers at UCLA designed a material based on a conventional superconductor that retains its superconducting properties under much higher magnetic fields than typically expected. This new material exhibits the superconducting diode effect, allowing higher electrical current in one direction. The team created a lattice with alternating layers of tantalum disulfide and a chiral compound to test these properties. Since it acts as a chiral superconductor, where entangled electrons spin in the same direction, it may provide improved stability in quantum computers. Additionally, it could minimize the energy consumption of electronics in general.

🤝 MIT and the University of Copenhagen establish identical quantum lab: MIT and the University of Copenhagen sign a four-year collaboration agreement to accelerate quantum computing hardware research, specifically in developing fault-tolerant quantum computing hardware and algorithms for life-science applications. The program is funded by the Novo Nordisk Foundation Quantum Computing Programme and is built on the idea that identical quantum laboratories in Copenhagen and Cambridge will encourage collaboration and seamless student exchanges.

🧩 Kyoto University researchers measure quantum coherence time of moiré excitons to advance next-generation nano-semiconductors: Quantum coherence time maintains the quantum state of qubits — no easy feat. Although scientists have proposed using moiré excitons as potential qubits for their expected stability, optical interference challenges their measurement due to diffraction limits. Kyoto University researchers developed a method to obtain the measurement of their quantum coherence time by using electron beam microfabrication and Michelson interferometry. They observed that the quantum coherence of a single moiré exciton remains stable at -269°C for over 12 picoseconds, much longer than in the parent material. This has implications for the future of nano-semiconductors as important components in quantum computers and other quantum technologies.

🚀 The Duality quantum accelerator has accepted its fourth cohort of startups: The Chicago-based Duality quantum accelerator has welcomed its fourth cohort of startups, focusing on quantum computing, sensing, and communication in industries such as biomedicine and aerospace. Duality, led by the Polsky Center for Entrepreneurship and Innovation at the University of Chicago and the Chicago Quantum Exchange, has helped previous startups raise over $20 million since its launch in April 2021. The program offers a 12-month business and entrepreneurship training in collaboration with partner institutions. The new cohort startups include SynthBits, Photon Queue, Artificial Brain, QuantumAstra, and Quantum Rings, each receiving $50,000 in funding and mentorship.

💡 The DOE Quantum Leadership Act would authorize over $2.5 billion for quantum research: U.S. Senators Dick Durbin and Steve Daines introduced the DOE Quantum Leadership Act to authorize $2.5 billion for quantum research at the Department of Energy over the next five years. This act would support the DOE's five National Research Centers, including Fermilab and Argonne National Labs in Illinois. The primary goal of the act would be to solve quantum supply chain challenges, encourage interagency and industry coordination, and establish new workforce support programs. The act is endorsed by multiple organizations as a chance to solidify U.S. leadership in quantum technology, benefiting national security and economic growth.

🔐 BTQ Technologies and ID Quantique to develop a next-generation authentication system: BTQ Technologies Corp. and ID Quantique signed an MoU to develop an authentication system that integrates quantum random number generators with post-quantum cryptography to address imminent security challenges. Using their combined expertise, they will create a new market for authentication systems to advance cybersecurity and secure mission-critical networks as quantum technology advances.

☕️FRESHLY BREWED RESEARCH

HIGHER ORDER QUANTUM RESERVOIR COMPUTING FOR NON-INTRUSIVE REDUCED-ORDER MODELS

QUICK BYTE: Higher-order quantum reservoir computing used to forecast complex dynamical systems such as sea surface temperature reduces training time and memory usage compared to traditional neural networks. This improves accuracy and efficiency in predicting nonlinear systems when the underlying equations are unknown.

SIGNIFICANCE: Forecasting complex dynamical systems is essential for fields such as meteorology, oceanography, and finance. While this can be done using first-principles-based models such as differential equations, the underlying equations are not always known. In those cases, machine learning is particularly effective, as it excels at extracting underlying patterns from data.

The caveat is that many machine learning models rely on training neural networks, which can be computationally expensive and require extensive amounts of memory. As an alternative, the researchers present a quantum mechanics-inspired machine learning strategy that can forecast complex dynamical systems with comparatively reduced training time and memory usage. Specifically, they focus on using a hybrid quantum reservoir computing model that integrates quantum systems with classical linear feedback connections for situations where the underlying equations are not available.

Reservoir computing uses a fixed and randomly connected network (this is the reservoir) to process input streams nonlinearly and project them into high-dimensional space. Quantum reservoir computing extends this concept by implementing the reservoir using quantum systems. Higher-order quantum reservoir computing takes this another step further by organizing quantum systems into an ensemble reservoir.

The researchers applied HQRC to forecast sea surface temperatures using data from the NOAA Optimal Interpolation dataset. They demonstrated that HQRC significantly outperforms traditional machine learning models like LSTMs and GRUs in terms of accuracy and computational efficiency. This approach shows the potential of quantum machine learning techniques for real-world prediction challenges, providing stable and accurate forecasts for complex nonlinear dynamical systems.

RESULTS: 

• HQRC outperforms traditional ML models in forecasting accuracy and efficiency, and reduces training time and memory usage compared to neural networks

• Successfully demonstrated on NOAA sea surface temperature dataset

• Provides stable and accurate forecasts for complex nonlinear dynamical systems

HONORABLE RESEARCH MENTIONS:

Efficient quantum circuits are constructed using the Levin-Wen string net model to simulate the non-Abelian properties of Fibonacci anyons. These circuits initialize the ground state, create excitations, and demonstrate their braiding and fusion properties using minimal qubits. This research provides a foundation for experimental exploration of topological quantum computation on current quantum hardware. —> link to Minimal Quantum Circuits for Simulating Fibonacci Anyons

A new method for individually addressing and entangling trapped ions uses microwave fields and acheives a spatial resolution of just a few microns. Dynamical decoupling is used to suppress unwanted interactions using a design that could enable all-to-all connectivity between ions in a chain with very low crosstalk errors. This technique could make microwave-driven logic a more practical approach for building large-scale quantum processors by reducing the need for ion shuttling. —> link to Individually Addressed Quantum Gate Interactions Using Dynamical Decoupling

How different types of weak measurements affect measurement-induced phase transitions in random quantum circuits is investigated using numerical techniques. The critical properties and universality class of these transitions appear to be largely unaffected by using weak vs. strong projective measurements. Their results suggest that weak and strong measurement protocols lead to the same underlying logarithmic conformal field theory description of the transition. —> link to Critical properties of weak measurement induced phase transitions in random quantum circuits

UNTIL TOMORROW.