arXiv subjects

Tianjie Hu

Publications and source records attributed to Tianjie Hu.

6 recordsLinked to original sources

arXiv2026

Quantum Network Routing based on Surface Code Error Correction

Quantum networks encounter unavoidable channel noises and erasure errors, presenting a huge obstacle in designing protocols that attain both high reliability and efficiency. Typically, quantum networks fall into two categories: those utilize quantum entanglements for quantum teleportation, and those directly transfer the actual quantum messages. In this paper, we present SurfNet, a quantum network that inherits the main advantages from both categories. It employs surface codes as logical qubits for encoding messages, and utilizes two parallel communication channels to fault-tolerantly transfer each surface code in a modular manner. Our approach of using surface codes can timely correct both operational and photon loss errors within the network, and the integration of the two channels within the network can greatly improve network throughput. For the implementation of SurfNet, we propose a novel network architecture, designed to better integrate surface codes into quantum networks. We also propose a novel error correction decoder, designed to fully utilize the modular characteristic of surface codes within our network. Simulation results demonstrate that SurfNet with its decoder significantly enhances the communication fidelity within quantum networks.

quant-ph↗

arXiv2026

A Fine-Grained and Efficient Reliability Analysis Framework for Noisy Quantum Circuits

Evaluating the reliability of noisy quantum circuits is essential for implementing quantum algorithms on noisy quantum devices. However, current quantum hardware exhibits diverse noise mechanisms whose compounded effects make accurate and efficient reliability evaluation challenging. While state fidelity is the most faithful indicator of circuit reliability, it is experimentally and computationally prohibitive to obtain. Alternative metrics, although easier to compute, often fail to accurately reflect circuit reliability, lack universality across circuit types, or offer limited interpretability. To address these challenges, we propose a fine-grained, scalable, and interpretable framework for efficient and accurate reliability evaluation of noisy quantum circuits. Our approach performs a state-independent analysis to model how circuit reliability progressively degrades during execution. We introduce the Noise Proxy Circuit (NPC), which removes all logical operations while preserving the complete sequence of noise channels, thereby providing an abstraction of cumulative noise effects. Based on the NPC, we define Proxy Fidelity, a reliability metric that quantifies both qubit-level and circuit-level reliability. We further develop an analytical algorithm to estimate Proxy Fidelity under depolarizing, thermal relaxation, and readout error channels. The proposed framework achieves fidelity-level reliability estimation while remaining execution-free, scalable, and interpretable. Experimental results show that our method accurately estimates circuit fidelity, with an average absolute difference (AAD) ranging from 0.031 to 0.069 across diverse circuits and devices.

quant-ph↗

arXiv2025

Dynamic Routing in Space-Ground Integrated Quantum Networks

Quantum networks emerge as fundamental frameworks for addressing various large-scale problems. There are two primary architectures: space-based quantum networks, which deploy satellites with free space channels to interconnect users, and ground-based quantum networks, which utilize optical fibers to interconnect users. In this paper, we explore space-ground integrated quantum networks that incorporate both satellites and optical fibers into the infrastructure. This integrated network features three forms of communication: using only free space links, only ground links, or a hybrid usage of free space and ground links. We formulate the routing problem in space-ground integrated quantum networks as an integer programming and propose two solutions: using a linear relaxation and a greedy algorithm. The linear relaxation algorithm allows timely scheduling of additional entanglement purification, whereas the greedy algorithm enables quick scheduling. Simulation results demonstrate their effective balancing between network throughput and communication fidelity.

quant-ph↗

arXiv2024

Detecting Fraudulent Services on Quantum Cloud Platforms via Dynamic Fingerprinting

Noisy Intermediate-Scale Quantum (NISQ) devices, while accessible via cloud platforms, face challenges due to limited availability and suboptimal quality. These challenges raise the risk of cloud providers offering fraudulent services. This emphasizes the need for users to detect such fraud to protect their investments and ensure computational integrity. This study introduces a novel dynamic fingerprinting method for detecting fraudulent service provision on quantum cloud platforms, specifically targeting machine substitution and profile fabrication attacks. The dynamic fingerprint is constructed using a \textit{single} probing circuit to capture the unique error characteristics of quantum devices, making this approach practical because of its trivial computational costs. When the user examines the service, the execution results of the probing circuit act as the device-side fingerprint of the quantum device providing the service. The user then generates the user-side fingerprint by estimating the expected execution result, assuming the correct device is in use. We propose an algorithm for users to construct the user-side fingerprint with linear complexity. By comparing the device-side and user-side fingerprints, users can effectively detect fraudulent services. Our experiments on the IBM Quantum platform, involving seven devices with varying capabilities, confirm the method's effectiveness.

cs.CR↗

arXiv2023

SurfaceNet: Fault-Tolerant Quantum Networks with Surface Codes

Quantum networks serve as the means to transmit information, encoded in quantum bits or qubits, between quantum processors that are physically separated. Given the instability of qubits, the design of such networks is challenging, necessitating a careful balance between reliability and efficiency. Typically, quantum networks fall into two categories: those utilize quantum entanglements for quantum teleportation, and those directly transfer quantum message. In this paper, we present SurfaceNet, a quantum network in the second category that employs surface codes as logical qubits for preserving and transferring message. Our approach of using surface codes can fault-tolerantly correct both operational and photon loss errors within the network. We propose a novel one-way quantum communication procedure, designed to better integrate surface codes into our network architecture. We also propose an efficient routing protocol that optimizes resource utilization for our communication procedure. Simulation results demonstrate that SurfaceNet significantly enhances the overall communication fidelity.

quant-ph↗

arXiv2023

MORE: Measurement and Correlation Based Variational Quantum Circuit for Multi-classification

Quantum computing has shown considerable promise for compute-intensive tasks in recent years. For instance, classification tasks based on quantum neural networks (QNN) have garnered significant interest from researchers and have been evaluated in various scenarios. However, the majority of quantum classifiers are currently limited to binary classification tasks due to either constrained quantum computing resources or the need for intensive classical post-processing. In this paper, we propose an efficient quantum multi-classifier called MORE, which stands for measurement and correlation based variational quantum multi-classifier. MORE adopts the same variational ansatz as binary classifiers while performing multi-classification by fully utilizing the quantum information of a single readout qubit. To extract the complete information from the readout qubit, we select three observables that form the basis of a two-dimensional Hilbert space. We then use the quantum state tomography technique to reconstruct the readout state from the measurement results. Afterward, we explore the correlation between classes to determine the quantum labels for classes using the variational quantum clustering approach. Next, quantum label-based supervised learning is performed to identify the mapping between the input data and their corresponding quantum labels. Finally, the predicted label is determined by its closest quantum label when using the classifier. We implement this approach using the Qiskit Python library and evaluate it through extensive experiments on both noise-free and noisy quantum systems. Our evaluation results demonstrate that MORE, despite using a simple ansatz and limited quantum resources, achieves advanced performance.

quant-ph↗