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Quantum Information Processing in the Frequency Domain

Hsuan‐Hao Lu

Published Dec 1, 2020• 0 citations
OpenAlex

Abstract

Quantum technologies promise to revolutionize information processing through dramatic computational speed-ups and ultimate security compared with classical counterparts. As matter-based qubit systems increase in size, however, counteracting decoherence becomes challenging and places limits on how large a stand-alone system can be. These limitations, coupled with the many quantum computing platforms under development, have led researchers to view modular architectures, connected by a quantum network, as a promising path to large-scale quantum computing. Our group reported in several studies this year, progress on multiple fronts in such systems, using photons as quantum information carriers in the frequency domain.

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Quantum technologies promise to revolutionize information processing through dramatic computational speed-ups and ultimate security compared with classical counterparts. As matter-based qubit systems increase in size, however, counteracting decoherence becomes challenging and places limits on how large a stand-alone system can be. These limitations, coupled with the many quantum computing platforms under development, have led researchers to view modular architectures, connected by a quantum network, as a promising path to large-scale quantum computing. Our group reported in several studies this year, progress on multiple fronts in such systems, using photons as quantum information carriers in the frequency domain.
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Quantum computation has emerged as a prominent research field with the potential to revolutionize information processing. Recent advancements have focused on extending qubit coherence times and enhancing error correction and fault-tolerant protocols, achieving coherence time to gate time ratios as high as 10⁸ and reducing error rates to as low as 0.143% ± 0.003% per cycle for 101 qubit system. The next critical challenge lies in scaling up qubit systems to support large-scale quantum computation that exceeds the performance of classical supercomputer. In this study, we summarize the working mechanisms, physical properties, gate operations, and limitations of three leading qubit platforms—superconducting qubits, trapped-ion qubits, and neutral atom qubits. Through a systematic comparison, we identify the key challenges that hinder qubit system scalability. Finally, we outline future research directions to address these challenges, including exploring the fundamental physics underpinning long coherence times, improving control tools such as laser systems, enhancing material quality and fabrication precision, and investigating hybrid quantum architectures. We hope this study offers a valuable perspective for researchers working toward the development of scalable and reliable quantum computing systems.
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Quantum computers have the potential to deliver speed-ups for solving certain important problems that are intractable for classical counterparts, making them a promising avenue for advancing modern computation. However, many quantum algorithms require deep quantum circuits, which are challenging to implement on current noisy devices. To address this limitation, variational quantum algorithms (VQAs) have been actively developed, enabling practical quantum computing in the noisy intermediate-scale quantum (NISQ) era. Among them, the variational quantum eigensolver (VQE) stands out as a leading approach for solving problems in quantum chemistry, many-body physics, and even integer factorization. The VQE algorithm can be implemented on various quantum hardware platforms, including photonic systems, quantum dots, trapped ions, neutral atoms, and superconducting circuits. In particular, photonic platforms offer several advantages: they operate at room temperature, exhibit low decoherence, and support multiple degrees of freedom, making them suitable for scalable, high-dimensional quantum computation. Here we present methodologies for realizing VQE on photonic systems, highlighting their potential for practical quantum computing. We first provide a theoretical overview of the VQE framework, focusing on the procedure for variationally estimating ground state energies. We then explore how photonic systems can implement these processes, showing that a wide variety of problems can be addressed using either multiple qubit states or a single qudit state.
Photons have been a flagship system for studying quantum mechanics, advancing quantum information science, and developing quantum technologies. Quantum entanglement, teleportation, quantum key distribution, and early quantum computing demonstrations were pioneered in this technology because photons represent a naturally mobile and low-noise system with quantum-limited detection readily available. The quantum states of individual photons can be manipulated with very high precision using interferometry, an experimental staple that has been under continuous development since the 19th century. The complexity of photonic quantum computing devices and protocol realizations has raced ahead as both underlying technologies and theoretical schemes have continued to develop. Today, photonic quantum computing represents an exciting path to medium- and large-scale processing. It promises to put aside its reputation for requiring excessive resource overheads due to inefficient two-qubit gates. Instead, the ability to generate large numbers of photons—and the development of integrated platforms, improved sources and detectors, novel noise-tolerant theoretical approaches, and more—have solidified it as a leading contender for both quantum information processing and quantum networking. Our concise review provides a flyover of some key aspects of the field, with a focus on experiment. Apart from being a short and accessible introduction, its many references to in-depth articles and longer specialist reviews serve as a launching point for deeper study of the field.