Quantum Computing

Research Summary for April 2023


By Dr Chris Mansell, Senior Scientific Writer on Terra Quantum

Below is a summary of some of the interesting research papers in quantum computing and communications we’ve looked at over the past month.


Title: Experimental Twin-Field Quantum Key Distribution Over 1000km Fiber Distance
Organization: China University of Science and Technology; Chinese Academy of Sciences; Photon Technology (Zhejiang) Co,. Ltd.; Yangtze Optical Fiber and Cable Joint Stock Co. Ltd.; Tsinghua University
Quantum key distribution (QKD) allows two remote parties to share a random secret key so they can communicate privately. The main practical problem of QKD is that the achievable rate at which keys can be generated becomes very low when the communicating parties are separated by great distances. In this experiment, the twin-field QKD protocol was implemented and the key rate was measured for distances from 202 km to 1002 km. By developing and employing several methods to increase lock levels, the reported results exceed all previous demonstrations of twin field QKD.
Link: https://arxiv.org/abs/2303.15795

Title: Development and Demonstration of Efficient Read Error Mitigation Techniques for use in the NISQ Algorithm
Organization: Rigetti Computing
State tomography estimation and classical image tomography are both observable estimation methods that use many random measurements efficiently. For NISQ devices, measurement error must be taken into account. The authors of this preprint analyze the impact of such errors on forecast state estimators and consider various strategies for reducing them. They devised a fast and accurate error mitigation technique which they implemented on Rigetti’s Aspen-11 superconducting quantum processor. They processed a million measurements in under a minute and a half, a task that would have taken seventeen hours without their new approach.
Link: https://arxiv.org/abs/2303.17741

Title: High-fidelity, Flex-Frequency Two-Qubit Fluxonium Gate with Transmon Coupler
Organizations: Massachusetts Institute of Technology; MIT Lincoln Laboratory
Composite superconducting circuit components, such as fluxonium qubits and transmons, have been the subject of considerable research and development. In this preprint, researchers have created a new superconducting quantum processor based on logic gates between pairs of fluxonium qubits coupled together via transmons. Compared with the previous setup, this design directly results in a stronger desired clutch and a weaker unwanted clutch. The logic gates, which involve microwaves driving Rabi oscillations, could be tuned to operate in the 2 GHz range, which would allow frequency collisions to be avoided in larger devices with many qubits. With sophisticated precision and coherence times, researchers already have a number of ideas to further push the forefront of this exciting field.
Link: https://arxiv.org/abs/2304.06087

Title: Mitigation of State-Reference Error: Strategies for High Accuracy Quantum Chemical Computing
Organization: Chalmers University of Technology;
This paper describes a chemical-inspired strategy for mitigation of reference state (REM) error. Due to the efficient way in which REM can be implemented – with minimal post-processing on classical computers and one or no additional measurements – it can be combined with other error mitigation techniques, such as read mitigation. Small molecules, such as hydrogen and lithium hydride, were analyzed using a variational quantum eigen solving algorithm running on two superconducting NISQ processors: ibmq_quito and Särimner. Applying REM increases the computational accuracy of energy calculations by up to two times.
Link: https://pubs.acs.org/doi/10.1021/acs.jctc.2c00807

Title: Quantum critical dynamics in a programmable 5,000 qubit rotating glass
Organization: D-Wave Quantum Inc.; Boston University; Simon Fraser University
For more than 20 years, D-Wave has pioneered the field of quantum annealing. The number of qubits in their device has followed an impressive upward trajectory. Various scientific investigations have been carried out regarding noise, coherence, entanglement, the types of problems that can be solved and the speed at which they can be solved. Recently, the important issue regarding the relationship between thermal annealing and coherent quantum annealing was resolved for their 2000-qubit devices. Now, based on these results in their new Nature paper, they show coherent dynamics for their larger, more connected annealer called “Advantage”, which has 5,000 qubits arranged in a “Pegasus” layout.
Link: https://www.nature.com/articles/s41586-023-05867-2


Title: Robust Dequantization of Quantum Singular Value Transformations and Quantum Machine Learning Algorithms
Organization: Nagoya University
Ewin Tang has shown that most of the quantum machine learning algorithms in the Quantum Random Access Memory model do not have a quantum advantage. That is, classical algorithms that can sample quantum states work just as well. However, François Le Gall has noticed in his new research that it might make more sense to investigate classical algorithms that can only do this rough sampling. He found that even under these new conditions, the classic algorithm was still running fast. These results apply to the classical versions of six different algorithms, including the quantum singular value transformation and supervised clustering algorithms.
Link: https://arxiv.org/abs/2304.04932

Title: Universal noise-precision relations in variational quantum algorithms
Organization: Osaka University; JST, PRESTO; RIKEN Center for Quantum Computing
In this paper, the authors analytically estimate the error in the cost function of a variational quantum algorithm that is subject to Gaussian noise. They provide insight into what influences this sensitivity to noise and show how there is a trade-off between trainability and the noise resistance of the cost function. They tested their approximations by numerically simulating a variational quantum eigensolver for spin chains and toy problems associated with variational compilation. They also devised new error mitigation techniques and made their code easily available online.
Link: https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.023025

Title: Matrix-Density Renormalization Group Algorithm for Simulating Quantum Circuits with Finite Fidelity
Organization: Atos Quantum Laboratory; University of Grenoble Alpes; Cornell University; Flatiron Institute
In this new paper, the researchers ask whether it is more difficult for quantum computers to outperform classical computers for useful or useless tasks. They show that useful tasks are related to the real world, which is largely understandable and structured. Algorithms, both classical and quantum, can try to take advantage of this structure. Completely pointless tasks, on the other hand, don’t necessarily lead to interesting insights, which means there’s a lot of flexibility for designing quantum circuits that classical computers make extremely difficult to simulate. Although random quantum circuits do this, researchers developed classical algorithms that can simulate them up to hundreds of qubits. Compared to the previous classical algorithm, it has better scaling with the number of qubits, but suffers exponential difficulty when simulating a higher fidelity quantum processor.
Link: https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.4.020304

Title: A Framework for Demonstrating Practical Quantum Excellence: The Quantum Race Against the Classical Generative Model
Organizations: Zapata Computing Canada Inc.; Vector Institute, MaRS Center; University of Waterloo; University of Toronto
The latest generative AI models can look through large databases of images and then generate new, new images, in the sense that they are not in the original database, but still have a similar style and the right type of content. Such a model is said to be able to generalize well. Numerically testing the performance of these generalizations may not seem easy. However, the author of this preprint provides a framework for doing just that. In particular, they show how the generative quantum model compares to the classical model. They create a synthetic data set, the proportions of which are accessible to the model. The newly generated data is compared with the rest of the original data using a cost function that assesses their numerical similarity. The results show that the quantum circuit Born machine is highly competitive in terms of its output diversity. In addition, they are more efficient than classic models when only equipped with limited data.
Link: https://arxiv.org/abs/2303.15626

Title: Quantum resistance in blockchain networks
Organization: IDB-Inter-American Development Bank; LACChain-Global Alliance for Blockchain Ecosystem Development at LAC; quantity; Escuela de Ingenieria y Ciencias, Mexico
Today’s blockchains face critical risks related to their digital signatures and cryptographic keys. Because blockchains are distributed ledgers that store data, the “save now, decrypt later” threat (also known as the “hack today, crack tomorrow” threat) is a very serious problem – there is nothing to hack because everything is already stored. In this paper, the authors address this risk by developing an open-source, end-to-end framework to adapt an Ethereum-based blockchain to be quantum resilient as well as robust and scalable. This framework combines entropy quantum sourcing, post-quantum certificates, post-quantum keys, transaction signing, and chain signature verification. Three ways of carrying out this verification step were tested. They involve solid smart contracts, precompiled smart contracts and code written in the assembly language of the Ethereum Virtual Machine.
Link: https://www.nature.com/articles/s41598-023-32701-6

April 28, 2023


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