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Scientists Make Advances in Programmable Qudit-based Quantum Processor

Remember when qubits — with a “b” — used to be so exotic? Scientists say that qudits — that’s with a “d” — offer a multi-level alternative to typical qubits that could provide a larger state space to store and process information, which could lead to less complex circuits and enhanced algorithm efficiency.

Now, an international team of scientists report on a programmable qudit-based quantum processor in silicon-photonic integrated circuits. The researchers, who report their findings in Nature, also demonstrated how the device enhances quantum computational parallelism.

The team said that the integrated photonic quantum technology for qudit-based quantum computing offers enhanced capacity, accuracy and efficiency, and could accelerate the creation of a large-scale quantum computer.

In addition to tipping the scale toward the advantages of using silicon-photonic quantum computers, they suggest that the qudit-enhanced design offers numerous improvements over pure qubit approaches.

“Controlling and programming quantum devices to process quantum information by the unit of quantum dit, i.e., qudit, provides the possibilities for noise-resilient quantum communications, delicate quantum molecular simulations, and efficient quantum computations, showing great potential to enhance the capabilities of qubit-based quantum technologies,” the researchers write.

According to the researchers, the processor monolithically integrates all the key functionalities and capabilities of initialization, manipulation and measurement of the two quantum quart — or, ququart — states and multi-value quantum-controlled logic gates with high-level fidelities.

“By reprogramming the configuration of the processor, we implemented the most basic quantum Fourier transform algorithms, all in quaternary, to benchmark the enhancement of quantum parallelism using qudits, which include generalised Deutsch-Jozsa and Bernstein-Vazirani algorithms, quaternary phase estimation and fast factorization algorithms,” they write.

The team implemented more than one million high-fidelity preparations, operations and projections of qudit states in the processor.

Researchers on the paper include: Yulin Chi, Jieshan Huang, Zhanchuan Zhang, Jun Mao, Zinan Zhou, Xiaojiong Chen, Chonghao Zhai, Jueming Bao, Tianxiang Dai, Huihong Yuan, Ming Zhang, Daoxin Dai, Bo Tang, Yan Yang, Zhihua Li, Yunhong Ding, Leif K. Oxenløwe, Mark G. Thompson, Jeremy L. O’Brien, Yan Li, Qihuang Gong and Jianwei Wang.

Jeremy O’Brien is the CEO of PsiQuantum, a leader in silicon photonics, which the company believes is the only way to achieve the necessary scale required for error correction and deliver a fault-tolerant, general-purpose quantum computer.

Research institutions involved in the work included Peking University, Zhejiang University, Chinese Academy of Sciences, Technical University of Denmark, University of Bristol and The University of Western Australia

The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

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Jake Vikoren

Jake Vikoren

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Deep Prasad

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Matt Swayne

With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Quantum Insider since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses. [email protected]

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The Future of Materials Discovery: Reducing R&D Costs significantly with GenMat’s AI and Machine Learning Tools

When: July 13, 2023 at 11:30am

What: GenMat Webinar

Jake Vikoren

Jake Vikoren

Company Speaker

Deep Prasad

Deep Prasad

Company Speaker

Araceli Venegas

Araceli Venegas

Company Speaker

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