Commentary and a selection of the most important recent news, articles, and papers about Quantum.
Today’s Brief Commentary
Today’s links are primarily about quantum computing, with a couple of others thrown in about a quantum game and quantum networking.
Start paying attention to the Imec company for quantum-related technology. It shows up twice in the links below. Remember, quantum computing is not only about qubits; it’s about all the different parts of the systems and the supply chain for obtaining them.
I want to highlight an interesting research paper from IBM researchers in the Quantum Computing – Technical section below. The scientists show that combining two different kinds of error-correcting codes produces better results than just using one. I hadn’t really considered this before, but it makes a lot of sense when you think about it. Combine individual technologies to optimize the ultimate result you are after.
Computing is heterogeneous.
I put that statement on its own line because we all need to be reminded of those three words. It has been this way for decades, going back to the point where we added Arithmetic Processing Units (APUs) and Floating Point Units (FPUs) to Central Processing Units (CPUs), if not before. These weren’t hybrid systems but integrated systems made of heterogeneous components!
Games
Gamified Universal Quantum Literacy: Quantum Odyssey by Quarks Interactive – Inside Quantum Technology
Author: Brian Siegelwax
(Thursday, November 7, 2024) “For over five years, Quarks Interactive has been developing a video game called Quantum Odyssey. Since the beginning, it has set out to be a fun and visual medium for bringing quantum literacy to the masses. There are no math, physics, or coding prerequisites to play this game, so all ages and backgrounds can benefit”
Quantum Computing
Imec Bets on Silicon Spin Qubits for Scalable Quantum Computers | EE Times Europe
https://www.eetimes.eu/imec-bets-on-silicon-spin-qubits-for-scalable-quantum-computers/
Author: Pat Brans
(Wednesday, June 19, 2024) “How does imec take silicon spin qubits from lab to fab to prepare them for use on an industrial scale?”
Fractional gates reduce circuit depth at the utility scale | IBM Quantum Computing Blog
https://www.ibm.com/quantum/blog/fractional-gates
Authors: Daniella Garcia Almeida; Kaelyn Ferris; Naoki Kanazawa; Blake Johnson; and Robert Davis
Commentary: Buried in this is the statement that IBM is removing pulse-level control from all its quantum computing systems. I think this will be controversial among the research users. Other than saying that they are focusing on higher-level features, IBM might want to share pulse-level usage numbers.
(Thursday, November 7, 2024) “Fractional gates are a new type of quantum logic gate that can help to increase the efficiency of utility-scale experiments.”
IonQ – IonQ to Increase Performance and Scale of Quantum Computers with Photonic Integrated Circuits in Collaboration with imec
Commentary: Photonic integrated circuits (PICs) are essential for reducing the SWaP-C (Size, Weight, Power and Cost) of quantum computing and networking technologies that use photonics.
(Thursday, November 7, 2024) “IonQ (NYSE: IONQ), a leader in the quantum computing industry, announced today that it is developing photonic integrated circuits (PICs) and chip-scale ion trap technology for trapped ion quantum computing in partnership with imec , a world-renowned RD center in nanoelectronics and digital technologies. By optimizing the design, production, and integration of chip-scale photonic devices and ion traps for scalable and high-performance quantum computers, the developments aim to push the boundaries of quantum computing performance. Traditional trapped ion quantum computing approaches rely on bulk optics for laser light modulation, delivery, and photon collection. By moving traditional bulk optical components into integrated photonic devices, IonQ aims to reduce overall hardware system size and cost, increase qubit count, and improve system performance and robustness. Chip-scale optical technologies and IonQ’s tight integration with imec’s trap manufacturing and packing are expected”
RIKEN, NTT, and Amplify Inc. Introduce General-Purpose Optical Quantum Computer | Quantum Insider
Author: Cierra Choucair
Commentary: I suspect some details in the press release were lost or confused in translation, but RIKEN is now a quantum computing player to watch.
(Monday, November 11, 2024) “A collaboration has developed a general-purpose optical quantum computer, which is accessible through the cloud.”
Quantum Computing – Technical
[2312.06451] JuliQAOA: Fast, Flexible QAOA Simulation
https://arxiv.org/abs/2312.06451
Authors: Golden, John; Bärtschi, Andreas; O’Malley, Daniel; Pelofske, Elijah; and Eidenbenz, Stephan
Commentary: I’d love to see more quantum software written in Julia.
(Monday, December 11, 2023) “We introduce JuliQAOA, a simulation package specifically built for the Quantum Alternating Operator Ansatz (QAOA). JuliQAOA does not require a circuit-level description of QAOA problems, or another package to simulate such circuits, instead relying on a more direct linear algebra implementation. This allows for increased QAOA-specific performance improvements, as well as improved flexibility and generality. JuliQAOA is the first QAOA package designed to aid in the study of both constrained and unconstrained combinatorial optimization problems, and can easily include novel cost functions, mixer Hamiltonians, and other variations. JuliQAOA also includes robust and extensible methods for learning optimal angles. Written in the Julia language, JuliQAOA outperforms existing QAOA software packages and scales well to HPC-level resources. JuliQAOA is available at https://github.com/lanl/JuliQAOA.jl.”
[2411.03202] Architectures for Heterogeneous Quantum Error Correction Codes
https://arxiv.org/abs/2411.03202
Authors: Stein, Samuel; Xu, Shifan; Cross, Andrew W.; Yoder, Theodore J.; Javadi-Abhari, Ali; Liu, Chenxu; Liu, Kun; Zhou, Zeyuan; Guinn, Charles; ; …; and Li, Ang
Commentary: In the future, we may need two or more kinds of error-correction to achieve fault tolerance within a single system.
(Tuesday, November 5, 2024) “Quantum Error Correction (QEC) is essential for future quantum computers due to its ability to exponentially suppress physical errors. The surface code is a leading error-correcting code candidate because of its local topological structure, experimentally achievable thresholds, and support for universal gate operations with magic states. However, its physical overhead scales quadratically with number of correctable errors. Conversely, quantum low-density parity-check (qLDPC) codes offer superior scaling but lack, on their own, a clear path to universal logical computation. Therefore, it is becoming increasingly evident is becoming that there are significant advantages to designing architectures using multiple codes. Heterogeneous architectures provide a clear path to universal logical computation as well as the ability to access different resource trade offs. To address this, we propose integrating the surface code and gross code using an ancilla bus for inter-code data movement. This approach involves managing trade-offs, including qubit overhead, a constrained instruction set, and gross code (memory) routing and management. While our focus is on the gross-surface code architecture, our method is adaptable to any code combination and the constraints generated by that specific architecture. Motivated by the potential reduction of physical qubit overhead, an ever important feature in the realization of fault tolerant computation, we perform the first full system study of heterogeneous error-correcting codes, discovering architectural trade-offs and optimizing around them. We demonstrate physical qubit reductions of up to 6.42x when executing an algorithm to a specific logical error rate, at the cost of up to a 3.43x increase in execution time.”
Scaling whole-chip QAOA for higher-order ising spin glass models on heavy-hex graphs | npj Quantum Information
https://www.nature.com/articles/s41534-024-00906-w
Authors: Pelofske, Elijah; Bärtschi, Andreas; Cincio, Lukasz; Golden, John; and Eidenbenz, Stephan
Commentary: Interesting paper from computational scientists at Los Alamos National Laboratory.
(Wednesday, November 6, 2024) “We show that the quantum approximate optimization algorithm (QAOA) for higher-order, random coefficient, heavy-hex compatible spin glass Ising models has strong parameter concentration across problem sizes from 16 up to 127 qubits for p = 1 up to p = 5, which allows for computationally efficient parameter transfer of QAOA angles. Matrix product state (MPS) simulation is used to compute noise-free QAOA performance. Hardware-compatible short-depth QAOA circuits are executed on ensembles of 100 higher-order Ising models on noisy IBM quantum superconducting processors with 16, 27, and 127 qubits using QAOA angles learned from a single 16-qubit instance using the JuliQAOA tool. We show that the best quantum processors find lower energy solutions up to p = 2 or p = 3, and find mean energies that are about a factor of two off from the noise-free distribution. We show that p = 1 QAOA energy landscapes remain very similar as the problem size increases using NISQ hardware gridsearches with up to a 414 qubit processor.”
Quantum Networking
QUANT-NET: Quantum Application Network Testbed for Novel Entanglement Technology
“Funded by the Advanced Scientific Computing Research (ASCR) division of the U.S. Department of Energy’s Office of Science, the Quantum Application Network Testbed for Novel Entanglement Technology (QUANT-NET) project brings together world-leading experts from Lawrence Berkeley National Laboratory (Berkeley Lab), University of California, Berkeley (UC Berkeley), the California Institute of Technology, and the University of Innsbruck to construct a testbed for quantum networking technologies.”