arXiv subjects

Jixuan Ruan

Publications and source records attributed to Jixuan Ruan.

8 recordsLinked to original sources

arXiv2026

FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration

LLM-based evolution has emerged as a promising way to improve agents by refining non-parametric artifacts, but its wall-clock cost remains a major bottleneck. We identify that this cost comes from synchronized stage execution and imbalance inside each LLM-heavy stage. We present FlashEvolve, an efficient framework that replaces synchronized execution with asynchronous workers and queues, allowing different stages and steps to overlap. To handle data staleness introduced by asynchrony, FlashEvolve tracks artifact versions and applies different policies to update, discard, or patch stale artifacts. Unlike weight-space staleness in asynchronous RL, language-space staleness is inspectable and repairable: a stale artifact is not just delayed work, but readable evidence that the LLM can reflect on, revise, and turn into useful evolution signal. FlashEvolve further improves throughput and token efficiency with speculative stage completion and adaptive workflow control. On GEPA workloads, FlashEvolve improves proposal throughput by $3.5\times$ on local vLLM and $4.9\times$ on API serving over synchronous GEPA. The same design also applies to ACE and Meta-Harness.

cs.LG↗

arXiv2026

Bridging Superconducting and Neutral-Atom Platforms for Efficient Fault-Tolerant Quantum Architectures

The transition to the fault-tolerant era exposes the limitations of homogeneous quantum systems, where no single qubit modality simultaneously offers optimal operation speed, connectivity, and scalability. In this work, we propose a strategic approach to Heterogeneous Quantum Architectures (HQA) that synthesizes the distinct advantages of the superconducting (SC) and neutral atom (NA) platforms. We explore two architectural role assignment strategies based on hardware characteristics: (1) We offload the latency-critical Magic State Factory (MSF) to fast SC devices while performing computation on scalable NA arrays, a design we term MagicAcc, which effectively mitigates the resource-preparation bottleneck. (2) We explore a Memory-Compute Separation (MCSep) paradigm that utilizes NA arrays for high-density qLDPC memory storage and SC devices for fast surface-code processing. Our evaluation, based on a comprehensive end-to-end cost model, demonstrates that principled heterogeneity yields significant performance gains. Specifically, our designs achieve $752\times$ speedup over NA-only baselines on average and reduce the physical qubit footprint by over $10\times$ compared to SC-only systems. These results chart a clear pathway for leveraging cross-modality interconnects to optimize the space-time efficiency of future fault-tolerant quantum computers.

quant-ph↗

arXiv2025

TrapSIMD: SIMD-Aware Compiler Optimization for 2D Trapped-Ion Quantum Machines

Modular trapped-ion (TI) architectures offer a scalable quantum computing (QC) platform, with native transport behaviors that closely resemble the Single Instruction Multiple Data (SIMD) paradigm. We present FluxTrap, a SIMD-aware compiler framework that establishes a hardware-software co-design interface for TI systems. FluxTrap introduces a novel abstraction that unifies SIMD-style instructions -- including segmented intra-trap shift SIMD (S3) and global junction transfer SIMD (JT-SIMD) operations -- with a SIMD-enriched architectural graph, capturing key features such as transport synchronization, gate-zone locality, and topological constraints. It applies two passes -- SIMD aggregation and scheduling -- to coordinate grouped ion transport and gate execution within architectural constraints. On NISQ benchmarks, FluxTrap reduces execution time by up to $3.82 \times$ and improves fidelity by several orders of magnitude. It also scales to fault-tolerant workloads under diverse hardware configurations, providing feedback for future TI hardware design.

quant-ph↗

arXiv2025

OnePerc: A Randomness-aware Compiler for Photonic Quantum Computing

The photonic platform holds great promise for quantum computing. Nevertheless, the intrinsic probabilistic characteristics of its native fusion operations introduces substantial randomness into the computing process, posing significant challenges to achieving scalability and efficiency in program execution. In this paper, we introduce a randomness-aware compilation framework designed to concurrently achieve scalability and efficiency. Our approach leverages an innovative combination of offline and online optimization passes, with a novel intermediate representation serving as a crucial bridge between them. Through a comprehensive evaluation, we demonstrate that this framework significantly outperforms the most efficient baseline compiler in a scalable manner, opening up new possibilities for realizing scalable photonic quantum computing.

quant-ph↗

arXiv2025

OneAdapt: Adaptive Compilation for Resource-Constrained Photonic One-Way Quantum Computing

Measurement-based quantum computing (MBQC), a.k.a. one-way quantum computing (1WQC), is a universal quantum computing model, which is particularly well-suited for photonic platforms. In this model, computation is driven by measurements on an entangled state, which serves as an intermediate representation (IR) between program and hardware. However, compilers on previous IRs lacks the adaptability to the resource constraint in photonic quantum computers. In this work, we propose a novel IR with new optimization passes. Based on this, it realizes a resource-adaptive compiler that minimizes the required hardware size and execution time while restricting the requirement for fusion devices within an adaptive limit. Moreover, our optimization can be integrated with Quantum Error Correction (QEC) to improve the efficiency of photonic fault-tolerant quantum computing (FTQC).

quant-ph↗

arXiv2024

SymBreak: Mitigating Quantum Degeneracy Issues in QLDPC Code Decoders by Breaking Symmetry

Quantum error correction (QEC) is critical for scalable and reliable quantum computing, but existing solutions, such as surface codes, incur significant qubit overhead. Quantum low-density parity check (qLDPC) codes have recently emerged as a promising alternative, requiring fewer qubits. However, the lack of efficient decoders remains a major barrier to their practical implementation. In this work, we introduce SymBreak, a novel decoder for qLDPC codes that adaptively modifies the decoding graph to improve the performance of state-of-the-art belief propagation (BP) decoders. Our key contribution is identifying quantum degeneracy as a root cause of the convergence issues often encountered in BP decoding of quantum LDPC codes. We propose a solution that mitigates this issue at the decoding graph level, achieving both fast and accurate decoding. Our results demonstrate that SymBreak outperforms BP and BP+OSD-a more complex variant of BP-with a $16.17\times$ reduction in logical error rate compared to BP and $3.23\times$ compared to BP+OSD across various qLDPC code families. With only an $18.97$% time overhead compared to BP, SymBreak provides significantly faster decoding times than BP+OSD, representing a major advancement in efficient and accurate decoding for qLDPC-based QEC architectures.

quant-ph↗

arXiv2024

CaliScalpel: In-Situ and Fine-Grained Qubit Calibration Integrated with Surface Code Quantum Error Correction

Quantum Error Correction (QEC) is a cornerstone of fault-tolerant, large-scale quantum computing. However, qubit error drift significantly degrades QEC performance over time, necessitating periodic calibration. Traditional calibration methods disrupt quantum states, requiring system downtime and making in situ calibration infeasible. We present CaliScalpel, an innovative framework for in situ calibration in surface codes. The core idea behind CaliScalpel is leveraging code deformation to isolate qubits undergoing calibration from logical patches. This allows calibration to proceed concurrently with computation, while code enlargement maintains error correction capabilities with minimal qubit overhead. Additionally, CaliScalpel incorporates optimized calibration schedules derived from detailed device characterization, effectively minimizing physical error rates. Our results show that CaliScalpel achieves concurrent calibration and computation with modest qubit overhead and negligible execution time impact, marking a significant step toward practical in situ calibration in surface-code-based quantum computing systems.

quant-ph↗

arXiv2024

PowerMove: Optimizing Compilation for Neutral Atom Quantum Computers with Zoned Architecture

Neutral atom-based quantum computers (NAQCs) have recently emerged as promising candidates for scalable quantum computing, largely due to their advanced hardware capabilities, particularly qubit movement and the zoned architecture (ZA). However, fully leveraging these features poses significant compiler challenges, as it requires addressing complexities across gate scheduling, qubit allocation, qubit movement, and inter-zone communication. In this paper, we present PowerMove, an efficient compiler for NAQCs that enhances the qubit movement framework while fully integrating the advantages of ZA. By recognizing and leveraging the interdependencies between these key aspects, PowerMove unlocks new optimization opportunities, significantly enhancing both scalability and fidelity. Our evaluation demonstrates an improvement in fidelity by several orders of magnitude compared to the state-of-the-art methods, with execution time improved by up to 3.46x and compilation time reduced by up to 213.5x. We will open-source our code later to foster further research and collaboration within the community.

quant-ph↗