SearcharxivSearch

arXiv subjects

Yuexun Huang

Publications and source records attributed to Yuexun Huang.

6 recordsLinked to original sources

GadIR: A Spatial-Topology Preserving Compiler for Quantum Many-Body Systems Simulation

Simulating quantum many-body systems has been one of the most important applications of quantum computation. For simulation, the Hamiltonian of a physical system is compiled into quantum programs with native instructions for quantum hardware. In previous works, the Hamiltonian is represented as Pauli strings, then compiled and optimized based on the quantum circuit model. Such representation paradigm neglects the spatial topology of original physical models, which is vital information to reducing the overhead of compiling many-body systems Hamiltonians. To address such neglect, we introduce a spatial-topology preserving compiler for quantum many-body simulation. Using Pauli gadgets as the representations of the Hamiltonian, we introduce our intermediate representation -- GadIR, to preserve the spatial-topology information of original physical models. Our compiler frontend performs the group reduction algorithm based on Pauli gadget model, which is a hardware-independent optimization. Our compiler backend performs trotterization and scheduling on Pauli gadgets, then synthesizes the Pauli gadgets into hardware-native quantum programs. We evaluate our compiler on all the canonical quantum many-body system models, while achieving a significant reduction on compilation overhead regarding four major quantum architectures. Overall, our spatial-topology preserving IR exploits the compilation optimization space for quantum many-body systems Hamiltonian.

quant-ph

Photonic Quantum Computing on Spin Memory Architecture with Tree-Encoded Fusion

Photonic quantum computing provides a promising route toward quantum computation by naturally supporting the measurement-based quantum computation (MBQC) model. In MBQC, programs are executed through measurements on a pre-generated graph state, whose construction largely depends on probabilistic fusion operations. However, fusion operations in PQC are vulnerable to two major error sources: fusion failure and fusion erasure. As a result, MBQC compilation must account for both error mechanisms to generate reliable and efficient photonic executions. Prior state-of-the-art MBQC compilation, represented by OneAdapt, is designed for all-photonic architectures and mainly focuses on handling fusion failures. Nevertheless, it does not explicitly model fusion erasures induced by photon loss, which can be substantially more damaging than fusion failures. To mitigate fusion erasure errors, we introduce a new MBQC compilation scheme built upon the spin qubit quantum memory. We propose tree-encoded fusion, an encoding strategy that suppresses erasure errors during graph-state generation. We further incorporate this scheme into a compiler framework with algorithms that reduce the execution overhead of quantum programs. We evaluate the proposed framework using a realistic PQC simulator on six representative quantum algorithm benchmarks across multiple program scales. The results show that tree-encoded fusion achieves better robustness than alternative fusion-encoding strategies, and that our compiler provides exponential improvement over OneAdapt. In addition, we validate the feasibility of our approach through a proof-of-concept demonstration on real PQC hardware.

quant-ph

Scaling Quantum Networks via Phase-Stable Vacuum Beam Guide: Architectural Blueprint and Benchmark

Scaling quantum networks to continental distances requires physical infrastructure capable of overcoming both exponential attenuation and severe phase decoherence. While the concept of vacuum beam guide (VBG) has recently emerged as a promising low-loss solution, we move beyond it by proposing a rigorous physical-layer architectural blueprint anchored by empirical data and methods from Advanced LIGO, particularly regarding its interferometric stability in dynamic environments. To evaluate its system-level viability, we benchmark this architecture against various protocols across quantum communication, metrology, and computation. Ultimately, we identify no fundamental technical blockers to scaling this infrastructure.

quant-ph

Space-time Peer-to-Peer Distribution of Multi-party Entanglement for Any Quantum Network

Graph states are a class of important multiparty entangled states, of which bell pairs are the special case. Realizing a robust and fast distribution of arbitrary graph states in the downstream layer of the quantum network can be essential for further large-scale quantum networks. We propose a novel quantum network protocol called P2PGSD inspired by the classical Peer-to-Peer (P2P) network to efficiently implement the general graph state distribution in the network layer, which demonstrates advantages in resource efficiency and scalability over existing methods for sparse graph states. An explicit mathematical model for a general graph state distribution problem has also been constructed, above which the intractability for a wide class of resource minimization problems is proved and the optimality of the existing algorithms is discussed. In addition, we leverage the spacetime quantum network inspired by the symmetry from relativity for memory management in network problems and used it to improve our proposed algorithm. The advantages of our protocols are confirmed by numerical simulations showing an improvement of up to 50% for general sparse graph states, paving the way for a resource-efficient multiparty entanglement distribution across any network topology.

quant-ph

A Scalable and Robust Compilation Framework for Emitter-Photonic Graph State

Quantum graph states are critical resources for various quantum algorithms, and also determine essential interconnections in distributed quantum computing. There are two schemes for generating graph states probabilistic scheme and deterministic scheme. While the all-photonic probabilistic scheme has garnered significant attention, the emitter-photonic deterministic scheme has been proved to be more scalable and feasible across several hardware platforms. This paper studies the GraphState-to-Circuit compilation problem in the context of the deterministic scheme. Previous research has primarily focused on optimizing individual circuit parameters, often neglecting the characteristics of quantum hardware, which results in impractical implementations. Additionally, existing algorithms lack scalability for larger graph sizes. To bridge these gaps, we propose a novel compilation framework that partitions the target graph state into subgraphs, compiles them individually, and subsequently combines and schedules the circuits to maximize emitter resource utilization. Furthermore, we incorporate local complementation to transform graph states and minimize entanglement overhead. Evaluation of our framework on various graph types demonstrates significant reductions in CNOT gates and circuit duration, up to 52% and 56%. Moreover, it enhances the suppression of photon loss, achieving improvements of up to x1.9.

cs.AR

Vacuum Beam Guide for Large-Scale Quantum Networks

The vacuum beam guide (VBG) presents a completely different solution for quantum channels to overcome the limitations of existing fiber and satellite technologies for long-distance quantum communication. With an array of aligned lenses spaced kilometers apart, the VBG offers ultra-high transparency over a wide range of optical wavelengths. With realistic parameters, the VBG can outperform the best fiber by three orders of magnitude in terms of attenuation rate. Consequently, the VBG can enable long-range quantum communication over thousands of kilometers with quantum channel capacity beyond $10^{13}$ qubit/sec, orders of magnitude higher than the state-of-the-art quantum satellite communication rate. Remarkably, without relying on quantum repeaters, the VBG can provide a ground-based, low-loss, high-bandwidth quantum channel that enables novel distributed quantum information applications for computing, communication, and sensing.

quant-ph