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arXiv:2505.13958 · Physical Review X

Demonstrating Coherent Quantum Routers for Bucket-Brigade Quantum Random Access Memory on a Superconducting Processor

Sheng Zhang, Yun-Jie Wang, Peng Wang, Ren-Ze Zhao, Xiaoyan Yang, Zean Zhao, Tian-Le Wang, Haifeng Zhang, Zhifei Li, Yuan Wu, Haoran Tao, Liang-Liang Guo, Lei Du, Chi Zhang, Zhi-Long Jia, Weicheng Kong, Zhuo‐Zhi Zhang, Xiang‐Xiang Song, Yu-Chun Wu, Zhaoyun Chen, Peng Duan, Guo‐Ping Guo

Published Jul 24, 2026• 0 citations
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Abstract

Quantum routers (QRouters) are essential components of bucket-brigade quantum random access memory (QRAM), enabling quantum applications such as Grover’s search and quantum machine learning. Despite significant theoretical advances, achieving scalable and coherent QRouters experimentally remains challenging. Here, we demonstrate coherent quantum routers using a superconducting quantum processor, laying a practical foundation for scalable QRAM systems. The quantum router at the core of our implementation utilizes the transition composite gate scheme, wherein auxiliary energy levels temporarily mediate conditional interactions. By leveraging two-qubit primitives in its construction, the quantum router preserves straightforward initialization and calibration while significantly reducing circuit depth and duration relative to traditional gate-based decompositions. Moreover, by encoding routing addresses in the nonadjacent qutrit states | 0 ⟩ and | 2 ⟩ , our design inherently enables erasure-detection capability, providing efficient postselection to mitigate routing errors. Experimentally, we achieve an average fidelity of 94.8% across three individual QRouters, and we validate scalability through a two-layer quantum routing network achieving a fidelity of 82.4%. Our results represent a significant advancement in quantum routing technology, providing enhanced fidelity, built-in error resilience, and practical scalability crucial for the development of future QRAM and large-scale quantum computing architectures.

DOI
10.1103/h5m3-qrn9

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Quantum routers (QRouters) are essential components of bucket-brigade quantum random access memory (QRAM), enabling quantum applications such as Grover’s search and quantum machine learning. Despite significant theoretical advances, achieving scalable and coherent QRouters experimentally remains challenging. Here, we demonstrate coherent quantum routers using a superconducting quantum processor, laying a practical foundation for scalable QRAM systems. The quantum router at the core of our implementation utilizes the transition composite gate scheme, wherein auxiliary energy levels temporarily mediate conditional interactions. By leveraging two-qubit primitives in its construction, the quantum router preserves straightforward initialization and calibration while significantly reducing circuit depth and duration relative to traditional gate-based decompositions. Moreover, by encoding routing addresses in the nonadjacent qutrit states | 0 ⟩ and | 2 ⟩ , our design inherently enables erasure-detection capability, providing efficient postselection to mitigate routing errors. Experimentally, we achieve an average fidelity of 94.8% across three individual QRouters, and we validate scalability through a two-layer quantum routing network achieving a fidelity of 82.4%. Our results represent a significant advancement in quantum routing technology, providing enhanced fidelity, built-in error resilience, and practical scalability crucial for the development of future QRAM and large-scale quantum computing architectures.
Quantum random access memory (QRAM) enables efficient classical data access for quantum computers -- a prerequisite for many quantum algorithms to achieve quantum speedup. Despite various proposals, the experimental realization of QRAM remains largely unexplored. Here, we experimentally investigate the circuit-based bucket-brigade QRAM with a superconducting quantum processor. To facilitate the experimental implementation, we introduce a hardware-efficient gate decomposition scheme for quantum routers, which effectively reduces the depth of the QRAM circuit by more than 30% compared to the conventional controlled-SWAP-based implementation. We further propose an error mitigation method to boost the QRAM query fidelity. With these techniques, we are able to experimentally implement the QRAM architectures with two and three layers, achieving query fidelities up to 0.800 ±\pm± 0.026 and 0.604$\pm$0.005, respectively. Additionally, we study the error propagation mechanism and the scalability of our QRAM implementation, providing experimental evidence for the noise resilience nature of the bucket-brigade QRAM architecture. Our results highlight the potential of superconducting quantum processors for realizing a scalable QRAM architecture.
The implementation of a quantum router capable of performing both quantum signal routing and quantum addressing (a Q 2 -router) represents a key step toward building quantum networks and quantum random access memories. We realize a Q 2 -router that uses fixed-frequency transmon qubits to implement a routing protocol based on two native controlled- i gates. These gates leverage a large Z Z interaction to selectively route information according to a quantum address. We find an estimated average routing fidelity of 95.3 % , with errors arising primarily from decoherence or state preparation and measurement. We present a comprehensive calibration and characterization of both the c- i gates and the overall routing protocol through randomized benchmarking techniques and state tomography.
The bucket-brigade architecture [1], [2]—a tree-based quantum memory encoding scheme—is a QRAM encoding design with one of the lowest known computational complexities. It theoretically offers a polylogarithmic complexity [3]–[5], although in practical gate-based implementations, the gate count scales exponentially with the number of qubits. Despite theoretical advancements, no algorithm yet exists that can generate QRAM basis encoding circuits for arbitrary input datasets, which is a significant barrier to practical encoding scalability. This paper proposes an algorithm capable of generating such circuits more efficiently than the standard bucket-brigade construction, thus reducing the number of address accesses and overall gate complexity. The asymptotic upper bound of the encoding circuit generated by our algorithm is derived to be O(2k~(k~+d)),O\left({{2^{\tilde k}}(\tilde k + d)}\right),O(2k~(k~+d)), which achieves asymptotically exponential savings over general unitary synthesis as shown later in the paper. The resulting circuits provide a quantum data encoding layer that can be composed with downstream query or transform routines when needed. An example vector will be used throughout this paper to demonstrate a 60% gate count reduction. This is the first automated implementation of its kind-a foundational step towards developing a scalable QRAM encoding for quantum computing systems.
Quantum random access memory (QRAM)—memory which stores classical data but allows queries to be performed in superposition—is required for the implementation of numerous quantum algorithms. While naive implementations of QRAM are highly susceptible to decoherence and hence not scalable, it has been argued that the bucket-brigade QRAM architecture [Giovannetti et al., Phys. Rev. Lett. 100, 160501 (2008)] is highly resilient to noise, with the infidelity of a query scaling only logarithmically with the memory size. In prior analyses, however, this favorable scaling followed directly from the use of contrived noise models, thus leaving open the question of whether experimental implementations would actually enjoy the purported scaling advantage. In this work, we study the effects of decoherence on QRAM in full generality. Our main result is a proof that this favorable infidelity scaling holds for arbitrary error channels (including, e.g., depolarizing noise and coherent errors). Our proof identifies the origin of this noise resilience as the limited entanglement among the memory’s components, and it also reveals that significant architectural simplifications can be made while preserving the noise resilience. We verify these results numerically using a novel classical algorithm for the efficient simulation of noisy QRAM circuits. Our findings indicate that QRAM can be implemented with existing hardware in realistically noisy devices, and that high-fidelity queries are possible without quantum error correction. Furthermore, we also prove that the benefits of the bucket-brigade architecture persist when quantum error correction is used, in which case the scheme offers improved hardware efficiency and resilience to logical errors.
Quantum random access memory (QRAM)-memory which stores classical data but allows queries to be performed in superposition-is required for the implementation of numerous quantum algorithms.While naive implementations of QRAM are highly susceptible to decoherence and hence not scalable, it has been argued that the bucket-brigade QRAM architecture [Giovannetti et al., Phys. Rev. Lett. 100, 160501 (2008)] is highly resilient to noise, with the infidelity of a query scaling only logarithmically with the memory size.In prior analyses, however, this favorable scaling followed directly from the use of contrived noise models, thus leaving open the question of whether experimental implementations would actually enjoy the purported scaling advantage.In this work, we study the effects of decoherence on QRAM in full generality.Our main result is a proof that this favorable infidelity scaling holds for arbitrary error channels (including, e.g., depolarizing noise and coherent errors).Our proof identifies the origin of this noise resilience as the limited entanglement among the memory's components, and it also reveals that significant architectural simplifications can be made while preserving the noise resilience.We verify these results numerically using a novel classical algorithm for the efficient simulation of noisy QRAM circuits.Our findings indicate that QRAM can be implemented with existing hardware in realistically noisy devices, and that high-fidelity queries are possible without quantum error correction.Furthermore, we also prove that the benefits of the bucket-brigade architecture persist when quantum error correction is used, in which case the scheme offers improved hardware efficiency and resilience to logical errors.
Quantum random access memory (QRAM) is a common architecture resource for algorithms with many proposed applications, including quantum chemistry, windowed quantum arithmetic, unstructured search, machine learning, and quantum cryptography. Here, we propose two bucket-brigade QRAM architectures based on high-coherence superconducting resonators, which differ in their realizations of the conditional-routing operations. In the first, we directly construct cavity-controlled controlled- SWAP ( CSWAP ) operations, while in the second, we utilize the properties of giant-unidirectional emitters (GUEs). For both architectures, we analyze single- and dual-rail implementations of a bosonic qubit. In the single-rail encoding, we can detect first-order ancilla errors, while the dual-rail encoding additionally allows for the detection of photon losses. For parameter regimes of interest, the postselected infidelity of a QRAM query in a dual-rail architecture is nearly an order of magnitude below that of a corresponding query in a single-rail architecture. These findings suggest that dual-rail encodings are particularly attractive as architectures for QRAM devices in the era before fault tolerance. Published by the American Physical Society 2024