A selection of the most important recent news, articles, and papers about quantum computing.
News, Articles, and Analyses
Testing spooky action at a distance | MIT News | Massachusetts Institute of Technology
https://news.mit.edu/2024/testing-spooky-action-distance-0731
Author: School of Engineering | Department of Mathematics | Department of Physics | Department of Electrical Engineering and Computer Science
(Wednesday, July 31, 2024) “MIT has signed a four-year collaboration agreement with the Novo Nordisk Foundation Quantum Computing Programme (NQCP) at Niels Bohr Institute at the University of Copenhagen, focused on accelerating quantum computing hardware research.”
Introducing Quantinuum Nexus: Our All-in-one Quantum Computing Platform
https://www.quantinuum.com/news/introducing-quantinuum-nexus-our-all-in-one-quantum-computing-platform
“Quantinuum is excited to introduce the beta availability of Quantinuum Nexus, our comprehensive quantum computing platform. Nexus is built to simplify quantum computing workflows with its expert design and full-stack support. We are inviting quantum users to apply for beta availability; accepted users can work closely with Quantinuum on how Nexus can be adopted and customized for you.”
Infleqtion’s Quantum Computer Live at UK Testbed – The Futurum Group
https://futurumgroup.com/insights/quantum-in-context-infleqtions-quantum-computer-live-at-uk-testbed/
Author: Dr. Bob Sutor
“Infleqtion UK installed the first testbed at the NQCC campus after being named a winner of a £30 million funding competition.”
Technical Papers, Articles, and Preprints
[2407.20134] Modular quantum processor with an all-to-all reconfigurable router
https://arxiv.org/abs/2407.20134
Authors: Wu, Xuntao; Yan, Haoxiong; Andersson, Gustav; Anferov, Alexander; Chou, Ming-Han; Conner, Christopher R.; Grebel, Joel; Joshi, Yash J.; Li, Shiheng; Miller, Jacob M.; Povey, Rhys G.; Qiao, Hong; Cleland, Andrew N.
(Monday, July 29, 2024) “Superconducting qubits provide a promising approach to large-scale fault-tolerant quantum computing. However, qubit connectivity on a planar surface is typically restricted to only a few neighboring qubits. Achieving longer-range and more flexible connectivity, which is particularly appealing in light of recent developments in error-correcting codes, however usually involves complex multi-layer packaging and external cabling, which is resource-intensive and can impose fidelity limitations. Here, we propose and realize a high-speed on-chip quantum processor that supports reconfigurable all-to-all coupling with a large on-off ratio. We implement the design in a four-node quantum processor, built with a modular design comprising a wiring substrate coupled to two separate qubit-bearing substrates, each including two single-qubit nodes. We use this device to demonstrate reconfigurable controlled-Z gates across all qubit pairs, with a benchmarked average fidelity of $96.00\%\pm0.08\%$ and best fidelity of $97.14\%\pm0.07\%$, limited mainly by dephasing in the qubits. We also generate multi-qubit entanglement, distributed across the separate modules, demonstrating GHZ-3 and GHZ-4 states with fidelities of $88.15\%\pm0.24\%$ and $75.18\%\pm0.11\%$, respectively. This approach promises efficient scaling to larger-scale quantum circuits, and offers a pathway for implementing quantum algorithms and error correction schemes that benefit from enhanced qubit connectivity.”
[2407.21225] AI methods for approximate compiling of unitaries
https://arxiv.org/abs/2407.21225
Authors: Kremer, David; Villar, Victor; Vishwakarma, Sanjay; Faro, Ismael; Cruz-Benito, Juan
(Tuesday, July 30, 2024) “This paper explores artificial intelligence (AI) methods for the approximate compiling of unitaries, focusing on the use of fixed two-qubit gates and arbitrary single-qubit rotations typical in superconducting hardware. Our approach involves three main stages: identifying an initial template that approximates the target unitary, predicting initial parameters for this template, and refining these parameters to maximize the fidelity of the circuit. We propose AI-driven approaches for the first two stages, with a deep learning model that suggests initial templates and an autoencoder-like model that suggests parameter values, which are refined through gradient descent to achieve the desired fidelity. We demonstrate the method on 2 and 3-qubit unitaries, showcasing promising improvements over exhaustive search and random parameter initialization. The results highlight the potential of AI to enhance the transpiling process, supporting more efficient quantum computations on current and future quantum hardware.”
Spins hop between quantum dots in new quantum processor – Physics World
https://physicsworld.com/a/spins-hop-between-quantum-dots-in-new-quantum-processor/
(Wednesday, July 31, 2024) “Hopping-based logic achieved at high fidelity”
[2408.00758] To reset, or not to reset — that is the question
https://arxiv.org/abs/2408.00758
Authors: Gehér, György P.; Jastrzebski, Marcin; Campbell, Earl T.; Crawford, Ophelia
(Thursday, August 01, 2024) “Whether to reset qubits, or not, during quantum error correction experiments is a question of both foundational and practical importance for quantum computing. Text-book quantum error correction demands that qubits are reset after measurement. However, fast qubit reset has proven challenging to execute at high fidelity. Consequently, many cutting-edge quantum error correction experiments are opting for the no-reset approach, where physical reset is not performed. It has recently been postulated that no-reset is functionally equivalent to reset procedures, as well as being faster and easier. For memory experiments, we confirm numerically that resetting provides no benefit. On the other hand, we identify a remarkable difference during logical operations. We find that unconditionally resetting qubits can reduce the duration of fault-tolerant logical operation by up to a factor of two as the number of measurement errors that can be tolerated is doubled. We support this with numerical simulations. However, our simulations also reveal that the no-reset performance is superior if the reset duration or infidelity exceeds a given threshold. Lastly, we introduce two novel syndrome extraction circuits that can reduce the time overhead of no-reset approaches. Our findings provide guidance on how experimentalists should design future experiments.”
