Quantum integrated sensing and communication (QISAC) enables simultaneous parameter estimation and secure information transmission based on shared entanglement resources, making it a promising research direction for future quantum information networks. In practical quantum channels, however, depolarizing noise, decoherence, and potential eavesdropping perturbations may degrade entanglement resources, increase the quantum bit error rate, and reduce both secrecy capacity and sensing performance. To address these limitations, this paper proposes a coding-enhanced QISAC (CE-QISAC) scheme. Based on the shared entanglement framework of existing QISAC protocols, the proposed scheme incorporates Bivariate Bicycle (BB) quantum low-density parity-check codes and a low-complexity belief propagation with localized statistics decoding (BP-LSD) algorithm to protect transmitted quantum states through error correction, thereby reducing the logical quantum bit error rate. The secrecy capacity under coding enhancement is analyzed according to the decoded logical error rate, while the waterfall effect of BB codes is further exploited to improve security detection sensitivity. Results show that the proposed scheme maintains high secrecy capacity in the nominal noise regime, mitigates the impact of depolarizing noise on parameter estimation, and reduces decoding complexity, providing a feasible approach for quantum integrated sensing and secure direct communication over noisy quantum channels.
Quantum integrated sensing and communication (QISAC) enables simultaneous parameter estimation and secure information transmission based on shared entanglement resources, making it a promising research direction for future quantum information networks. In practical quantum channels, however, depolarizing noise, decoherence, and potential eavesdropping perturbations may degrade entanglement resources, increase the quantum bit error rate, and reduce both secrecy capacity and sensing performance. To address these limitations, this paper proposes a coding-enhanced QISAC (CE-QISAC) scheme. Based on the shared entanglement framework of existing QISAC protocols, the proposed scheme incorporates Bivariate Bicycle (BB) quantum low-density parity-check codes and a low-complexity belief propagation with localized statistics decoding (BP-LSD) algorithm to protect transmitted quantum states through error correction, thereby reducing the logical quantum bit error rate. The secrecy capacity under coding enhancement is analyzed according to the decoded logical error rate, while the waterfall effect of BB codes is further exploited to improve security detection sensitivity. Results show that the proposed scheme maintains high secrecy capacity in the nominal noise regime, mitigates the impact of depolarizing noise on parameter estimation, and reduces decoding complexity, providing a feasible approach for quantum integrated sensing and secure direct communication over noisy quantum channels.
Quantum communication and quantum metrology are widely compelling applications in the field of quantum information science, and quantum remote sensing is an intersection of both. Despite their differences, there are notable commonalities between quantum communication and quantum remote sensing, as they achieve their functionalities through the transmission of quantum states. Here we propose a quantum integrated sensing and communication (QISAC) protocol, which achieves quantum sensing under the Heisenberg limit while simultaneously enabling quantum secure communication through the transmission of entanglements. We have theoretically proven its security against eavesdroppers. The security of QISAC is characterized by the secrecy capacity for the information bit as well as asymmetric Fisher information gain for sensing. Through simulations conducted under the constraints of limited entanglement resources, we illustrate that QISAC maintains high accuracy in the estimation of phase. Hence, our QISAC offers a fresh perspective for applications of future quantum networks. Published by the American Physical Society 2024
Quantum secure direct communication (QSDC) enables the message sender to directly transmit messages to the message receiver through quantum channel without keys. Environmental noise is the main obstacle for QSDC's practicality. For enhancing QSDC's noise robustness, we introduce the quantum error correction (QEC) code into QSDC and propose the QSDC protocol based on the redundancy code. This QSDC protocol correlates atomic state with the electron–photon entangled pairs and transmits photons in quantum channels for two rounds. The parties can construct the remote atomic logical entanglement channel and decode messages with the heralded photonic Bell state measurement (BSM) and single electron measurement. This QSDC protocol is unconditionally secure in theory and has some advantages. First, benefiting from the heralded photonic BSM, it can eliminate the influence from photon transmission loss and has the potential to realize long-distance secure message transmission. Second, taking use of the error correction function of the repetition code, the error rate caused by the decoherence during the second round of photon transmission can be reduced, which can reduce the message error and increase the secret message capacity. Third, the whole protocol is feasible under current experimental condition. Our QSDC protocol can be extended to use other stronger QEC code. It provides a promising method to promote QSDC's practicality in the future.
Quantum low-density parity-check codes are promising candidates towards scalable fault-tolerant quantum computation. Among these, bivariate bicycle (BB) codes offer superior encoding rates and large code distance compared to surface codes. However, their requirement on long-range stabilizer measurements poses significant challenges for implementation on realistic hardware with limited connectivity, such as superconducting circuit platforms. In this work, we introduce a novel hardware-software co-design that leverages a programmable communication network architecture to address these limitations. Our approach utilizes a 2D toric network of oscillators as a flexible communication fabric linking qubits at each site. Such architecture significantly reduces the number of long-range couplers required from O(n) to O(n). Dual-rail qubits, along with native gates including Swap-Wait-Swap gates and beamsplitter SWAPs, ensure that long-range two-qubit gates can be executed with high fidelity and low latency. To further enhance performance, our qubit layout and routing algorithm utilize symmetries of the codes and enable maximum parallelism for long-range two-qubit gates, maintaining a low syndrome extraction cycle duration and scalability over the code length. We perform circuit-level simulation with realistic noise modeling based on experimental hardware parameters, observing an logical error rate per logical qubit per cycle of 3.06\% for [[18,4,4]] BB code, 2.6× less than the existing experimental result. These findings provide a practical roadmap and identify key technological advancements needed to achieve low-overhead fault-tolerant quantum computing at scale.
Quantum dense coding enables the transmission of two classical bits of information through the exchange of a single qubit, provided that an entangled state is shared between the communicating parties. While this protocol achieves a fundamental increase in channel capacity, its practical realization is strongly influenced by the presence of noise in realistic quantum channels. This work presents a simulation-based study of dense coding performance under two representative noise models: the depolarizing channel and the amplitude damping channel. Using Qiskit Aer, the bit error rate (BER), frame error rate (FER), and effective channel capacity are evaluated across a range of noise parameters. In addition, a classical threefold repetition strategy is examined as a lightweight error-mitigation technique. Results indicate that depolarizing noise produces more rapid degradation in both BER and channel capacity compared to amplitude damping, while repetition coding provides partial improvement in reliability at the expense of resource overhead. These findings highlight the trade-offs between efficiency and robustness in noisy implementations of dense coding and motivate further exploration of more advanced quantum error correction methods.
In the quest for fault-tolerant quantum computation, the delicate nature of qubits demands the need for robust quantum error correction. Quantum error correcting codes, the quantum counterpart to classical error correcting codes in information theory, have been developed to address the unique challenges quantum bits face against the noise of their environment in storing information. These codes include but are not limited to the Kitaev surface code, toric code, rotated surface code, generalized bicycle code, and bivariate bicycle code. Fast and reliable decoders for these quantum error correcting codes are needed to correct errors and achieve fault tolerance on these qubits. The belief propagation algorithm, which is a efficient and reliable heuristic for decoding classical low-density parity check codes, has been generalized to different types of quantum error correction codes. Paired with the ordered statistics decoding algorithm as a post-processing step from the soft outputs of the belief propagation decoder, belief propagation and ordered statistics decoding has been one of the most promising avenues of efficient quantum error correction. This thesis combines the state-of-the-art belief propagation and ordered statistics decoding algorithms with the exploration of the neural belief propagation algorithm to leverage classical deep learning machines to learn message passing patterns in decoding the newest quantum codes, the rotated surface code and bivariate bicycle code. The neural network exploits the local lattice structure of these codes to adjust the trainable weights and biases to more learn message update patterns more efficiently than the vanilla belief propagation algorithm. In this thesis, we prove a new threshold for the physical error rate on the rotated surface code using a neural belief propagation algorithm and ordered statistics decoding that consistently outperforms the threshold established by the vanilla belief propagation algorithm with ordered statistics decoding. We additionally show the results for similar efforts on the bivariate bicycle codes, and discuss the difficulties in achieving a threshold using the current neural belief propagation algorithms.
Quantum integrated sensing and communication (QISAC) is emerging as a key paradigm for next-generation quantum technologies, in which entanglement, coherence, and non-classical correlations are jointly exploited to enable secure communication, distributed sensing, and networked quantum functionalities. As quantum systems transition from laboratory demonstrations to deployable infrastructures, performance is increasingly limited not by individual components but by cross-layer interactions among hardware noise, channel loss, error-management strategies, and network architecture. This survey presents a system-level architectural framework for QISAC, focusing on how physical-layer constraints, quantum channel characteristics, and error-mitigation mechanisms jointly determine end-to-end performance and architectural feasibility in scalable quantum networks. We analyze representative quantum hardware platforms-including superconducting circuits, trapped ions, neutral atoms, photonic systems, and solid-state spin qubits-through the lens of coherence time, fidelity, interface capability, and technology readiness, emphasizing their implications for networked sensing and communication rather than device-level operation. The roles of quantum error correction (QEC) and entanglement purification are examined as complementary error-management layers, highlighting trade-offs among resource overhead, latency, and achievable entanglement fidelity under realistic noise and memory constraints. We further connect these architectural considerations to QISAC-enabled applications such as distributed quantum sensing, quantum key distribution (QKD), and repeater-assisted entanglement distribution, clarifying how hardware limitations and error-management choices propagate to application-level performance. By synthesizing noise, error management, and network co-design into a unified system perspective, this survey provides design-oriented insights and architectural guidelines for building scalable, noise-resilient QISAC networks.