aiqbench analysis
This paper proposes Trident, a three-level memory hierarchy for fault-tolerant quantum computers that reduces the cost of verifying qubit loads from high-density storage. Its reported speedups of 2.8× and 4.2× come from simulated architecture comparisons, not hardware, and the paper claims only a 4.9% increase in physical qubit cost. For quantum readers, the main point is that architectural overhead, not just code design, is becoming a bottleneck for practical fault-tolerant machines.
Trident: Efficient Load Verification for Yoked Surface Codes using a Three-Level Memory Hierarchy
arXiv:2610.32152v1 Announce Type: new Abstract: Fault-Tolerant Quantum Computers (FTQCs) commonly use the surface code to encode program qubits as error-corrected logical qubits. Unfortunately, the surface code has a poor encoding rate, so recent work has proposed Yoked Surface Codes (YSCs), which concatenate the surface code with a high-rate quantum code. The surface code qubits in YSCs are protected by the checks, or yokes, of the high-rate code. YSCs have 1D and 2D variants, which are $1.8\times$ and $4.5\times$ more efficient than the surface code, respectively. Modern FTQC architectures use a two-level hierarchy: surface codes perform logical operations (compute) while 2D YSCs store idle program qubits (memory). To load a qubit from memory, the FTQC first performs retrieval, which logically moves a program qubit from a 2D YSC into a surface code (8 cycles). However, retrieval is not fault-tolerant, so the FTQC must verify the load by measuring all the yokes of the 2D YSC (178 cycles). As verification dominates memory access latency, eliminating it can provide a speedup of $5.7\times$. Our goal is to reduce the verification overhead of 2D YSCs while retaining their storage efficiency. We exploit the fact that 1D YSCs, though less storage-efficient, incur negligible verification latency. We propose Trident, which expands the two-level hierarchy into a three-level hierarchy by adding a small intermediate level containing a 1D YSC (L1). If most loads hit L1 rather than L2 (2D YSC tier), it can significantly reduce verification overhead. We present two variants: Trident-D (demand-driven) and Trident-P (prefetch-driven), which achieve speedups of $2.8\times$ and $4.2\times$, respectively, while increasing the physical qubit cost of memory by only 4.9%.
Abstract:Fault-Tolerant Quantum Computers (FTQCs) commonly use the surface code to encode program qubits as error-corrected logical qubits. Unfortunately, the surface code has a poor encoding rate, so recent work has proposed Yoked Surface Codes (YSCs), which concatenate the surface code with a high-rate quantum code. The surface code qubits in YSCs are protected by the checks, or yokes, of the high-rate code. YSCs have 1D and 2D variants, which are $1.8\times$ and $4.5\times$ more efficient than the surface code, respectively. Modern FTQC architectures use a two-level hierarchy: surface codes perform logical operations (compute) while 2D YSCs store idle program qubits (memory). To load a qubit from memory, the FTQC first performs retrieval, which logically moves a program qubit from a 2D YSC into a surface code (8 cycles). However, retrieval is not fault-tolerant, so the FTQC must verify the load by measuring all the yokes of the 2D YSC (178 cycles). As verification dominates memory access latency, eliminating it can provide a speedup of $5.7\times$. Our goal is to reduce the verification overhead of 2D YSCs while retaining their storage efficiency. We exploit the fact that 1D YSCs, though less storage-efficient, incur negligible verification latency. We propose Trident, which expands the two-level hierarchy into a three-level hierarchy by adding a small intermediate level containing a 1D YSC (L1). If most loads hit L1 rather than L2 (2D YSC tier), it can significantly reduce verification overhead. We present two variants: Trident-D (demand-driven) and Trident-P (prefetch-driven), which achieve speedups of $2.8\times$ and $4.2\times$, respectively, while increasing the physical qubit cost of memory by only 4.9%.
arXiv:2610.32152 [quant-ph]
(or arXiv:2610.32152v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2610.32152 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
https://doi.org/10.1145/3845814.3850031 Focus to learn more DOI(s) linking to related resources
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Full text under the publisher's open licence · 364 words