Welcome to the Quantum Realm. 

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

Look, yesterday’s news was mildly exciting at best. Today, it’s a firehose of information. Enjoy 🔥  

Also, happy IBM Challenge kickoff day to all participating!

🗓️ THIS WEEK

Wednesday, June 5 - Friday, June 14 | IBM Quantum Challenge 2024 — Register here!

Thursday, June 6 | QaaS w/ Quantonix

Saturday, June 8 | Towards Practical Quantum Computing: Addressing Crosstalk and Circuit Optim w/ Washington DC Quantum Computing Meetup

Sunday, June 9 | QTM-X Weekly Quantum Education Session 3/10: Entanglement

📰 NEWS QUICK BYTES

⚡️ AQADOC powers the future with quantum innovation: The AQADOC project is funded by the Ile-de-France Region and led by Welinq in partnership with EDF to develop distributed quantum computing for energy production and management. This initiative brings together key players in quantum to parallelize computations across multiple quantum processors and address challenges in energy transition through advanced algorithms. The project will focus on applications such as battery simulation, optimal energy routing, and structural simulations of power plants and dams.

⛄️ Chilling innovation is upgrading quantum data centers: SureCore has just revealed new static random-access memory modules for quantum computing “systems on chips” that operate at cryogenic temperatures as low as 4K, which is a significant breakthrough for the cooling and downsizing of quantum computer data centers. Developed in collaboration with Semiwise and funded by InnovateUK, these modules will integrate with qubits within the cryostat to reduce both cooling costs and space requirements. Pretty uh…cool.

⚔️ Quantum forces unite against advanced error correction: QPerfect and QuEra Computing have announced a collaboration to develop and evaluate tensor network methods for quantum error correction by using QPerfect’s MIMIQ virtual quantum computer to simulate and model complex quantum algorithms. This partnership has the potential to advance the accuracy of quantum error correction on QuEra’s neutral-atom quantum computers.

🏛️ Ancient inspiration for quantum innovation: Scientists at the University of Chicago have developed a new algorithm to improve the efficiency and accuracy of molecular simulations on quantum computers. Uniquely inspired by ancient Alexandrian techniques, the algorithm combines random sampling with physical constraints to reduce the number of measurements needed as well as noise. This innovation holds promise for advancing quantum computing's role in predicting molecular behaviors and simulating chemical reactions.

🏔️ Montana just got a photonic upgrade: Funded by the U.S. Air Force's Applied Quantum CORE grant, ORCA Computing will supply Montana State University with two PT-1 quantum photonics systems, giving the university new capabilities in quantum technology applications. These systems will be used to accelerate the development and deployment of quantum solutions in security, communications, sensing, and computing. This partnership is part of MSU's mission to bring advanced quantum technologies from concept to market.

🏭️ Photons are getting their own industrial revolution: Quandela has launched its first manufacturing pilot line for high-performance photonic qubit devices in Massy, France, as part of an initiative to accelerate the deployment of error-corrected quantum computers. Located at The Photovoltaic Institute of Île-de-France, this plant will initially produce over 2K devices annually, scaling to 10K. This new site shows Quandela's commitment to industrializing quantum technology.

⚠️ Embracing AI, tackling quantum risks, and rethinking market stability: Two-week old news, but worth the mention. In a discussion at Yale SOM, SEC Chair Gary Gensler emphasized the agency's evolving focus on financial stability and introduced several policy projects dedicated to enhancing market resilience. He highlighted the importance of AI in monitoring financial markets and acknowledged the systemic risks posed by quantum computing, while expressing skepticism about the transformative potential of blockchain technology. Watch discussion below 🔻 

☕️ FRESHLY BREWED RESEARCH

Quantum optimization using a 127-qubit gate-model IBM quantum computer can outperform quantum annealers for nontrivial binary optimization problems: A comprehensive quantum solver for binary combinatorial optimization problems is introduced and tested on a 127-qubit IBM gate-model quantum computer, demonstrating performance improvements over quantum annealers and previous gate-model implementations. Breakdown here. (Press release here.)

The computational power of random quantum circuits in arbitrary geometries: This paper presents advancements in Quantinuum's H2 quantum computer that enable it to operate with up to 56 qubits with high connectivity and high fidelity. This improved computational power put to the test on random circuit sampling tasks demonstrates challenges for classical simulation. Breakdown here. (Press release here.)

High-Fidelity Spin Qubit Shuttling via Large Spin-Orbit Interactions: This paper investigates the high-fidelity shuttling of spin qubits in semiconducting quantum computers and shows that large spin-orbit interactions can be used to improve coherence during shuttling. This approach is particularly relevant as it allows for the integration of control electronics on-chip without the need for previously suggested external modifications.

Supercurrent-induced spin switching via indirect exchange interaction: Supercurrents can induce spin switching in quantum systems through indirect exchange interactions between spin impurities placed on the surface of a conventional superconductor. This demonstrated nature of supercurrents offers a practical and efficient method for low-dissipation spin manipulation which has implications for the advancement of spintronic devices and quantum computing technologies.

Photonic implementation of the quantum Morra game: A photonic implementation of the quantum Morra game demonstrates a two-player game where quantum strategies provide a winning advantage to one player. By using a linear optics setup with polarization-encoded photons, the study successfully reproduces the classical game within the quantum regime, which allows them to explore new applications in quantum information and communication.

High-fidelity remote entanglement of trapped atoms mediated by time-bin photons: High-fidelity remote entanglement between trapped atomic qubit memories using time-bin encoded photons achieves a 97% entanglement fidelity, as well as highlights the potential for achieving fidelities beyond 99.9%. The presented method contributes to a positive outlook on the potential of long-distance quantum communication and scalable quantum networks.

Qiskit Code Assistant: training LLMs for generating quantum computing code: Training of specialized large language models is used to generate high-quality quantum computing code using the Qiskit library. It highlights the unique challenges in quantum code generation, presents a new benchmark for evaluating quantum computing code, and demonstrates that their model outperforms existing models in generating accurate quantum code, and ultimately makes quantum computing more accessible and efficient for developers.

UNTIL TOMORROW.

BREAKDOWN

Quantum optimization using a 127-qubit gate-model IBM quantum computer can outperform quantum annealers for nontrivial binary optimization problems

🔍️ SIGNIFICANCE: 

• A quantum solver for binary combinatorial optimization problems is demonstrated using a gate-model quantum computer, specifically a 127-qubit IBM quantum computer. This solver outperforms existing quantum annealers, which were renown for optimization problems, applicable to various industries such as logistics, finance, and networking.

• This new solver shows significant improvements over previous methods by consistently delivering correct solutions for problems with up to 127 qubits. It also showcases the first time a gate-model quantum computer has outperformed a quantum annealer for a class of binary optimization problems (specifically HOBO).

🧪 METHODOLOGY: 

• The key innovation here is Q-CTRL's automated quantum solver workflow, which includes: a customized variational ansatz, a hybrid classical-quantum loop for parameter optimization, and overhead-free post-processing to correct bit-flip errors without additional quantum hardware execution.

• More on the ansatz and hybrid loop: Unlike traditional QAOA, which starts with an equal superposition state, this approach uses arbitrary rotation operators for each qubit, allowing for better initial state preparation and iterative updates of the initial state parameters alongside conventional QAOA parameters. The ansatz circuit is compiled once and circuit parameters updated in real-time based on feedback from the classical optimizer during the hybrid quantum-classical optimization loop.

• The solver incorporates an automated error-suppression pipeline that includes layout selection, dynamical decoupling for crosstalk and dephasing suppression, gate-waveform replacement, and readout-error mitigation.

• The solver uses a covariance matrix adaptation evolution strategy for the classical optimization component, which is fast, stochastic, and derivative-free. The objective function used is conditional value-at-risk which leads to faster convergence.

• After circuit execution, a classical post-processing step using a naïve greedy optimization is implemented to mitigate uncorrelated bit-flip errors.

📊 OUTCOMES & OUTLOOK: 

• The solver was tested on Max-Cut instances for random regular graphs up to 120 nodes. For denser graphs, it succeeded for 4-regular graphs up to 80 nodes and 7-regular graphs up to 50 nodes. Compared to previous results on trapped-ion quantum computers, this solver demonstrated up to 9x increase in the likelihood of success for 32-qubit problems.

• The solver was applied to a 127-qubit spin-glass model (HOBO problem) with linear, quadratic, and cubic interaction terms. It found the correct ground state energy in four out of six instances tested and showed a 1500x increase in the likelihood of finding the minimum energy compared to a D-Wave annealer.

• This solver consistently outperformed a heuristic local solver and

  represented the largest nontrivial quantum optimizations successfully solved on hardware to date.

• The implications of these results are substantial in that they demonstrate the practical utility of gate-model quantum computers for solving complex optimization problems which have industrial relevance.

BREAKDOWN

The computational power of random quantum circuits in arbitrary geometries

🔍 SIGNIFICANCE: 

• The computational power of random quantum circuits implemented on Quantinuum’s H2 quantum computer is explored. H2 now supports up to 56 qubits with high connectivity and an exceptionally high two-qubit gate fidelity of 99.843%. Previous methods demonstrated classical simulation challenges primarily with 2D quantum circuits, but the improved connectivity and fidelity of the H2 architecture extend these capabilities.

• Unlike previous studies that focused on specific gate optimizations or error correction, this research is centered around the combined effects connectivity and high gate fidelities have on achieving computations that are classically impractical at larger scales and depths — and ultimately demonstrates the power of quantum computation over classical.

🧪 METHODOLOGY: 

• A series of upgrades to the Quantinuum H2 quantum computer now allows for operations on up to 56 qubits with arbitrary connectivity. The race track-shaped surface-electrode trap features each qubit encoded in hyperfine states of 171Yb+ ions with 138Ba+ ions as sympathetic coolants.

• The key innovations include the implementation of advanced transport waveforms and the use of automated compilation steps for optimal qubit placement and routing.

• The circuits tested varied in geometry, including highly connected random graphs. Randomized benchmarking and mirror benchmarking were conducted to estimate gate fidelities and overall circuit performance.

• They focused on RCS, which involves sampling from the output distributions of random quantum circuits, and they used exact tensor network contraction techniques to benchmark classical simulation difficulties.

📊 OUTCOMES & OUTLOOK: 

• The study found that the H2 quantum computer can execute circuits with arbitrary connectivity and high gate fidelities and achieve performance levels that significantly hinder classical simulability, even at relatively low circuit depths.

• The results show that classical simulation difficulty scales exponentially with circuit depth and qubit number in highly connected geometries which establishes a clear computational advantage for the H2 quantum computer.

• Mirror benchmarking and linear cross-entropy benchmarking confirm high fidelity in the output states of these circuits and suggest that the H2 system's computational power is mostly limited by qubit number rather than gate fidelity or clock speed.

• This implies the path forward in scaling quantum computations as well as demonstrates the practicality and scalability of the QCCD architecture.