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IlKwon Sohn

Publications and source records attributed to IlKwon Sohn.

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Efficient Quantum Modular Reduction: Crandall reduction and its Fault-tolerant resource analysis

Modular arithmetic is central to quantum algorithms for cryptographic problems, including Shor's algorithm and Grover-based cryptanalysis, with modular reduction contributing substantially to circuit cost. Pseudo-Mersenne moduli $q=2^n-c$ allow classical Crandall reduction to replace division with folding and constant arithmetic, providing a structural opportunity for more efficient quantum modular reduction than Barrett reduction. We translate this advantage into a reversible quantum setting by deriving explicit folding and normalization conditions for $2n$-bit inputs. To the best of our knowledge, this constitutes the first exact reversible quantum circuit formulation of Crandall reduction. Based on this formulation, we develop two variants: Crandall reduction-1 is designed to minimize execution cost through one-step normalization, whereas Crandall reduction-2 uses two-step normalization to support a wider range of $c$ with limited overhead. Logical resource estimates show that both variants require fewer qubits and lower T-count and T-depth than optimized folding Barrett reduction. At $n=10$, Crandall reduction-1 reduces both T-count and T-depth by approximately 46.9% relative to optimized folding Barrett reduction. Surface-code analysis further shows that, at $n=20$ under the Sparse Blossom decoder, the estimated runtimes of the two variants are 30.05 ms and 35.39 ms, respectively, compared with 53.77 ms for optimized folding Barrett reduction. These results demonstrate the practical value of exploiting modulus-specific arithmetic structure in fault-tolerant quantum circuit design.

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Syndrome-as-Header: A Quantum Label-Switching Architecture via Uncorrectable Error Injection

Scaling quantum networks beyond point-to-point links requires packet forwarding that can tolerate control-plane timing uncertainty. Existing optical-burst switching (OBS) and quantum-wrapper-based packet switching (QW) rely on external classical headers whose jitter-prone processing must remain aligned with in-flight quantum payloads, creating guard-window or fiber-delay-line budget failures. This paper proposes Syndrome-as-Header (SAH), a quantum label-switching architecture that embeds routing labels into the syndrome structure of an encoded payload. The proposed scheme uses Uncorrectable Error Injection (UEI) to map flow labels to reference syndromes and builds a syndrome-space header codebook whose decoding regions remain distinguishable under correctable channel-induced syndrome deviations. Core routers extract the syndrome header, suppress the correctable residual channel-error component, and swap labels without measuring or decoding the logical payload. SAH supports FAST forwarding and VERIFICATION mode, the latter providing end-to-end consistency checking while retaining swappable labels. In NSFNet timing benchmarks with common per-hop quantum error correction (QEC), SAH eliminates the external-header/payload alignment condition, so timing uncertainty appears as memory residence and delivered latency rather than alignment-budget drops. With a $T_2$-based memory-residence penalty, the advantage depends on router memory coherence; for sufficiently long coherence, SAH maintains higher acceptance and throughput than OBS+QEC and QW+QEC under high jitter.

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Asymmetry-aided measurement-based quantum repeaters and distributed quantum computing with a decoder-free client

Distributed quantum computation needs to move logical qubits across lossy optical links, yet this transmission layer is usually designed separately from the computation it serves. We treat the two together by recognizing that a measurement-based quantum repeater is a two-dimensional code foliated along the transmission axis, so that the dominant channel loss is concentrated on the transmitted sector while the locally measured qubits are largely spared. Matching a code's distance to this structural asymmetry, we show that a rectangular Bacon-Shor subsystem code transmits a logical qubit markedly more efficiently than transmission-unaware encodings. Over continental distances, its cost-optimal repeater density is about an order of magnitude lower than that of a recent $[[48,6,8]]$ benchmark at comparable transmission rate, and roughly half that of a symmetric code of equal size. Moreover, we extend the framework to a central-to-client round trip in which a code-level, distance-preserving code switch joins the transmission legs to the client's computation, and joint decoding of the heterogeneous syndrome record at the central node lets distributed quantum computation proceed with a decoder-free client.

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3D Stacked Surface-Code Architecture for Measurement-Free Fault-Tolerant Quantum Error Correction

Mid-circuit measurements are a major bottleneck for superconducting quantum processors because they are slower and noisier than gates. Measurement-free quantum error correction (mfec) replaces repeated measurements and classical feed-forward by coherent quantum feedback, but existing mfec protocols suffer from severe connectivity overhead when mapped to planar surface-code architectures: transversal interactions between logical patches require SWAP chains of length $O(d)$ in the code distance, which increase depth and generate hook errors. This work introduces a 3D stacked surface-code architecture for measurement-free fault-tolerant quantum error correction that removes this connectivity bottleneck. Vertical transversal couplers between aligned surface-code patches enable coherent parity mapping and feedback with zero SWAP overhead, realizing constant-depth $O(1)$ inter-layer operations in d while preserving local 2D stabilizer checks. A fault-tolerant mfec protocol for the surface code is constructed that suppresses hook errors under realistic noise. An analytical performance model shows that the 3D architecture overcomes the readout error floor and achieves logical error rates orders of magnitude below both standard measurement-based surface codes and 2D mfec variants in regimes with slow, noisy measurements, identifying 3D integration as a key enabler for scalable measurement-free fault tolerance.

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Structural encoding with classical codes for computational-basis bit-flip correction in the early fault-tolerant regime

Achieving reliable performance on early fault-tolerant quantum hardware will depend on protocols that manage noise without incurring prohibitive overhead. We propose a novel framework that integrates quantum computation with the functionality of classical error correction. In this approach, quantum computation is performed within the codeword subspace defined by a classical error correction code. The correction of various types of errors that manifest as bit flips is carried out based on the final measurement outcomes. The approach leverages the asymmetric structure of many key algorithms, where problem-defining diagonal operators (e.g., oracles) are paired with fixed non-diagonal operators (e.g., diffusion operators). The proposed encoding maps computational basis states to classical codewords. This approach commutes with diagonal operators, obviating their overhead and confining the main computational cost to simpler non-diagonal components. Noisy simulations corroborate this analysis, demonstrating that the proposed scheme serves as a viable protocol-level layer for enhancing performance in the early fault-tolerant regime.

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Enhanced Extrapolation-Based Quantum Error Mitigation Using Repetitive Structure in Quantum Algorithms

Quantum error mitigation is a crucial technique for suppressing errors especially in noisy intermediate-scale quantum devices, enabling more reliable quantum computation without the overhead of full error correction. Zero-Noise Extrapolation (ZNE), which we mainly consider in this work, is one of prominent quantum error mitigation methods. For algorithms with deep circuits - such as iterative quantum algorithms involving multiple oracle calls - ZNE's effectiveness is significantly degraded under high noise. Extrapolation based on such low-fidelity data often yields inaccurate estimates and requires substantial overhead. In this study, we propose a lightweight, extrapolation-based error mitigation framework tailored for structured quantum algorithms composed of repeating operational blocks. The proposed method characterizes the error of the repeated core operational block, rather than the full algorithm, using shallow circuits. Extrapolation is used to estimate the block fidelity, followed by a reconstruction of the mitigated success probability. We validate our method via simulations of the 6-qubit Grover's algorithm on IBM's Aer simulator, then further evaluating it on the real 127-qubit IBM Quantum system based on Eagle r3 under a physical noise environment. Our results, particularly those from Aer simulator, demonstrate that the core block's error follows a highly consistent exponential decay. This allows our technique to achieve robust error mitigation, overcoming the limitations of conventional ZNE which is often compromised by statistically unreliable data from near-random behavior under heavy noise. In low-noise conditions, our method approaches theoretical success probability, outperforms ZNE. In high-noise conditions, ZNE fails to mitigate errors due to overfitting of its extrapolation data, whereas our method achieves over a 20% higher success probability.

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Bounding quantum uncommon information with quantum neural estimators

In classical information theory, uncommon information refers to the amount of information that is not shared between two messages, and it admits an operational interpretation as the minimum communication cost required to exchange the messages. Extending this notion to the quantum setting, quantum uncommon information is defined as the amount of quantum information necessary to exchange two quantum states. While the value of uncommon information can be computed exactly in the classical case, no direct method is currently known for calculating its quantum analogue. Prior work has primarily focused on deriving upper and lower bounds for quantum uncommon information. In this work, we propose a new approach for estimating these bounds by utilizing the quantum Donsker-Varadhan representation and implementing a gradient-based optimization method. Our results suggest a pathway toward efficient approximation of quantum uncommon information using variational techniques grounded in quantum neural architectures.

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Reducing Circuit Depth in Quantum State Preparation for Quantum Simulation Using Measurements and Feedforward

Reducing circuit depth and identifying an optimal trade-off between circuit depth and width is crucial for successful quantum computation. In this context, midcircuit measurement and feedforward have been shown to significantly reduce the depth of quantum circuits, particularly in implementing logical gates. By leveraging these techniques, we propose several parallelization strategies that reduce quantum circuit depth at the expense of increasing width in preparing various quantum states relevant to quantum simulation. With measurements and feedforward, we demonstrate that utilizing unary encoding as a bridge between two quantum states substantially reduces the circuit depth required for preparing quantum states, such as sparse quantum states and sums of Slater determinants within the first quantization framework, while maintaining an efficient circuit width. Additionally, we show that a Bethe wave function, characterized by its high degree of freedom in its phase, can be probabilistically prepared in a constant-depth quantum circuit using measurements and feedforward. We anticipate that our study will contribute to the reduction of circuit depth in initial state preparation, particularly for quantum simulation, which is a critical step toward achieving quantum advantage.

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Fault-tolerant and secure long-distance quantum communication via uncorrectable-error-injection

Quantum networks aim to facilitate the fault-tolerant and secure transmission of quantum states across distant devices. The widely adopted quantum teleportation scheme requires multiple rounds of entanglement swapping and purification, leading to significant resource overhead and operational complexity. In this study, we propose a novel fault-tolerant and secure quantum communication scheme based on uncorrectable error injection. Our method exploits a quantum state encoding scheme based on quantum error correction codes, which strategically introduces uncorrectable errors to enhance security. It eliminates the need for entanglement distribution while reducing resource requirements. The injected errors protect against eavesdropping by preventing unauthorized parties from retrieving meaningful information. Security analysis shows that as the data length and encoded message size increase, information leakage becomes negligible relative to the size of the total message. Comparative performance analysis with existing approaches indicates that our method reduces transmission overhead while maintaining comparable fidelity in low-error regimes. These findings suggest that the proposed method offers a scalable and practical alternative for secure long-distance quantum communication, distributed quantum computing, and future quantum internet applications.

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Error correctable efficient quantum homomorphic encryption using Calderbank-Shor-Steane codes

The integration of quantum error correction codes and homomorphic encryption schemes is essential for achieving fault-tolerant secure cloud quantum computing. However, owing to the significant overheads associated with these schemes, their efficiency is paramount. In this study, we develop an efficient quantum homomorphic encryption scheme based on quantum error correction codes that uses a single encoding process to simultaneously perform encryption and encoding. By using a longer quantum error correction code, both the security and error-correction capabilities of the scheme are improved. Through comprehensive evaluations, we demonstrate that the proposed scheme is more secure than the conventional permutation-key-based QHE scheme when the number of maximally mixed states is not more than twice the length of the quantum error-correction code. The proposed scheme offers a more secure and efficient approach to quantum cloud computing, potentially paving the way for more practical and scalable quantum cryptographic protocols.

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