This work proposes a concept of using quantum entanglement for synchronizing semantic structures between remote observers without the need for classical data transmission. In contrast to traditional interpretations of the no-communication theorem, we demonstrate that quantum correlation can be used for instantaneous synchronization of complex patterns, the information extraction of which occurs through semantic filtering and contextual validation. The proposed QHSC (Quantum Holistic Semantic Communication) protocol uses post-selection, temporal signature verification, and AI-based reconstruction of meaning from fragments to distinguish Alice's correlated signal from Bob's local noise. We show that the probability of random generation of a complete semantic pattern by local noise tends exponentially to zero, while quantum correlation ensures deterministic pattern matching between Alice and Bob. Furthermore, we demonstrate that the algorithmic core of QHSC possesses the property of physical layer agnosticism and can be deployed on existing classical communication channels, solving critical problems of resilient communication in electronic warfare conditions, deep-sea and space communication, and critical medical telemetry.
This work proposes a concept of using quantum entanglement for synchronizing semantic structures between remote observers without the need for classical data transmission. In contrast to traditional interpretations of the no-communication theorem, we demonstrate that quantum correlation can be used for instantaneous synchronization of complex patterns, the information extraction of which occurs through semantic filtering and contextual validation. The proposed QHSC (Quantum Holistic Semantic Communication) protocol uses post-selection, temporal signature verification, and AI-based reconstruction of meaning from fragments to distinguish Alice's correlated signal from Bob's local noise. We show that the probability of random generation of a complete semantic pattern by local noise tends exponentially to zero, while quantum correlation ensures deterministic pattern matching between Alice and Bob. Furthermore, we demonstrate that the algorithmic core of QHSC possesses the property of physical layer agnosticism and can be deployed on existing classical communication channels, solving critical problems of resilient communication in electronic warfare conditions, deep-sea and space communication, and critical medical telemetry.
This work proposes a concept of using quantum entanglement for synchronizing semantic structures between remote observers without the need for classical data transmission. In contrast to traditional interpretations of the no-communication theorem, we demonstrate that quantum correlation can be used for instantaneous synchronization of complex patterns, the information extraction of which occurs through holistic pattern analysis. The proposed QHSC (Quantum HS Communication) protocol introduces a novel multi-level verification framework that distinguishes Alice's correlated signal from Bob's local noise through structural pattern matching. We show that the probability of random generation of a complete semantic pattern by local noise tends to zero, while quantum correlation ensures deterministic pattern matching between Alice and Bob.Furthermore, we demonstrate that the algorithmic core of QHSC possesses the property of physical layer agnosticism and can be deployed on existing classical communication channels, solving critical problems of resilient communication in challenging environments.
Semantic communication (SC) enables bandwidth-efficient coordination in multi-agent systems by transmitting meaning rather than raw bits. However, when agents employ heterogeneous sensing modalities and AI architectures, perfect bit-level transmission no longer guarantees mutual understanding. Although deep learning methods for semantic compression have advanced, the information-theoretic limits of semantic alignment under heterogeneity remain poorly understood. Notably, semantic ambiguity shares the same mathematical structure as quantum contextuality, as both arise from cohomological obstructions, motivating a quantum formulation of SC. In this paper, an information-theoretic framework for quantum semantic communication is proposed using sheaf cohomology. Multi-agent semantic networks are modeled as quantum sheaves, where agents meaning spaces are Hilbert spaces connected by quantum channels. The first sheaf cohomology group is shown to characterize irreducible semantic ambiguity, representing a fundamental obstruction to alignment that no local processing can resolve. The minimum communication rate required for semantic alignment is proven to scale with the logarithm of the dimension of the cohomological space, establishing a semantic analog of Shannon limits. For entanglement-assisted channels, the achievable capacity is shown to strictly exceed classical bounds, with each shared ebit reducing the required classical communication by one bit, providing a rigorous interpretation of shared context. Additionally, quantum contextuality is shown to reduce cohomological obstructions, and a duality between quantum discord and integrated semantic information is established, linking quantum correlations to irreducible semantic content. This framework provides rigorous foundations for quantum-enhanced semantic communication in autonomous multi-agent systems.
This paper explores integrating quantum technologies with semantic communications to address the challenges of transmitting knowledge graph embeddings over traditional communication channels. As communication systems evolve to facilitate knowledge sharing and processing among natural and artificial intelligent agents, they encounter issues such as inefficiency, inaccuracy, and high complexity. To address these challenges, we propose a novel approach called quantum semantic communications, which integrates quantum technologies into the emerging framework of semantic communications. The primary goal of this protocol is to transmit semantic features efficiently, minimizing resource consumption while ensuring robustness. Our approach involves extracting semantic data from knowledge graphs using pre-trained large language model encoder and graph neural network as semantic encoders to generate compact knowledge representations transmitted over quantum communication channels. To assess the effectiveness of our protocol, we analyze performance metrics such as quantum semantic fidelity and F1 score under various noise conditions, including depolarizing, amplitude damping, and dephasing. Our simulations show that the proposed quantum semantic communication approach remains robust even in a low signal-to-noise regime.
The paradigm of semantic and goal-oriented communication offers a transition toward highly efficient AI-native connect-compute-actuate 6G networks. Unlike current content-blind communication and ML/AI training, interactions among intelligent agents capture essential information properties, facilitating practical support for understanding and effective goal attainment. However, its full potential is hindered by excessive energy consumption, wireless system resource consumption, and computational limitations. Graph-based knowledge and communication systems effectively represent, communicate, and process complex, causal, structural, and multidimensional semantic meanings. Operating in terms of semantic entities, relationships, contextual logic, and reasoning rules, these systems face challenges in transmitting graphs over classical wireless channels, given the associated resource costs. To overcome this, we explore integrating quantum technology into semantic communication, presenting a novel approach - quantum semantic communications. In our study, we focus on sharing semantic knowledge graphs through quantum mechanical principles, utilizing remote state preparation within quantum protocols. We evaluate the tradeoffs between semantic graphs and quantum channel costs to determine the feasibility of our protocol. Additionally, we explore the scalability of the quantum approach and demonstrate the computational gains achievable in polynomial time.
Based upon quantum-inspired entanglement in quantum-classical hybrids, a simple algorithm for instantaneous transmissions of non-intentional messages (chosen at random) to remote distances is proposed. The idea is to implement instantaneous transmission of conditional information on remote distances via a quantum-classical hybrid that preserves superposition of random solutions, while allowing one to measure its state variables using classical methods. Such a hybrid system reinforces the advantages, and minimizes the limitations, of both quantum and classical characteristics. Consider n observers, and assume that each of them gets a copy of the system and runs it separately. Although they run identical systems, the outcomes of even synchronized runs may be different because the solutions of these systems are random. However, the global constrain must be satisfied. Therefore, if the observer #1 (the sender) made a measurement of the acceleration v(sub 1) at t =T, then the receiver, by measuring the corresponding acceleration v(sub 1) at t =T, may get a wrong value because the accelerations are random, and only their ratios are deterministic. Obviously, the transmission of this knowledge is instantaneous as soon as the measurements have been performed. In addition to that, the distance between the observers is irrelevant because the x-coordinate does not enter the governing equations. However, the Shannon information transmitted is zero. None of the senders can control the outcomes of their measurements because they are random. The senders cannot transmit intentional messages. Nevertheless, based on the transmitted knowledge, they can coordinate their actions based on conditional information. If the observer #1 knows his own measurements, the measurements of the others can be fully determined. It is important to emphasize that the origin of entanglement of all the observers is the joint probability density that couples their actions. There is no centralized source, or a sender of the signal, because each receiver can become a sender as well. An observer receives a signal by performing certain measurements synchronized with the measurements of the others. This means that the signal is uniformly and simultaneously distributed over the observers in a decentralized way. The signals transmit no intentional information that would favor one agent over another. All the sequence of signals received by different observers are not only statistically equivalent, but are also point-by-point identical. It is important to assume that each agent knows that the other agent simultaneously receives the identical signals. The sequences of the signals are true random, so that no agent could predict the next step with the probability different from those described by the density. Under these quite general assumptions, the entangled observers-agents can perform non-trivial tasks that include transmission of conditional information from one agent to another, simple paradigm of cooperation, etc. The problem of behavior of intelligent agents correlated by identical random messages in a decentralized way has its own significance: it simulates evolutionary behavior of biological and social systems correlated only via simultaneous sensoring sequences of unexpected events.
Quantum communication has reached a rate bottleneck, yet enhancing its throughput remains of profound significance. Here we propose a scheme termed quantum semantic communication-a novel paradigm that integrates semantic communication with quantum secure direct communication to realize highly efficient, task-oriented, and intrinsically secure information transmission. In quantum semantic communication, meaningful semantic content is directly encoded into quantum states, whereby the fundamental laws of quantum physics guarantee inherent eavesdropping-detection capability and information-theoretic security. By harnessing semantic compression and artificial intelligence-assisted encoding strategies, this approach surpasses the intrinsic rate constraints of conventional quantum secure direct communication. Simulation results show that quantum semantic communication can surpass the Wyner secure information bound compared with conventional quantum secure direct communication systems and demonstrate its potential to break through the linear distance bound of quantum communication. These findings pave the way for high-rate secure communication.