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Quantum network

A quantum network is a system of interconnected quantum nodes, such as quantum processors, sensors, or repeaters, linked by quantum communication channels that transmit quantum states like qubits, enabling the distribution of and entanglement across distances using phenomena such as superposition and no-cloning, which surpass the capabilities of classical networks. These networks rely on quantum channels for primary , often supplemented by classical channels for , error correction, and control signals, forming a hybrid infrastructure that addresses the fragility of quantum states. components include quantum to extend range by mitigating signal loss and decoherence, as well as entanglement sources for generating shared quantum correlations between distant nodes. The foundational tasks of quantum networks encompass reliable transmission, entanglement generation and distribution, and secure , which underpin advanced functionalities. Applications of quantum networks span secure communication through quantum key distribution (QKD), which provides immune to ; distributed quantum sensing for enhanced precision in fields like detection; and networked , allowing modular systems to collaborate on complex problems beyond single-device limits. Recent developments, such as testbeds at institutions like , demonstrate practical implementations for experimenting with distributed quantum applications, while software frameworks enable the execution of arbitrary network-based quantum programs. Major challenges include overcoming and noise, which degrade states over distance; developing efficient state transduction between disparate quantum modalities (e.g., photons to atoms); and scaling to metropolitan or global extents without prohibitive infrastructure costs. Interfacing diverse quantum hardware and managing routing protocols for entanglement distribution remain critical hurdles, though coordinated research efforts aim to standardize architectures for broader adoption. The vision of a full quantum internet, proposed in stages from basic connectivity to advanced computation, continues to drive progress toward transformative technologies.

Introduction

Definition and core principles

A quantum network is an interconnected system of quantum devices designed to distribute and process quantum states, harnessing quantum mechanical phenomena like superposition and entanglement to enable functionalities unattainable by classical networks. This framework supports the transmission of across nodes, facilitating and distributed by treating quantum states as the fundamental carriers of data. At the heart of quantum networks lies the , the basic unit of , analogous to the classical bit but with enhanced capabilities. A is a two-level quantum system that can occupy the states |0\rangle or |1\rangle, or any superposition thereof, expressed as |\psi\rangle = \alpha |0\rangle + \beta |1\rangle, where \alpha and \beta are complex amplitudes satisfying |\alpha|^2 + |\beta|^2 = 1. This superposition allows a single to encode an infinite continuum of states, enabling where n qubits can represent up to $2^n classical states simultaneously. In contrast to classical bits, which are strictly 0 or 1, qubits' probabilistic nature underpins the computational advantages of quantum systems. A pivotal core principle is the , which prohibits the perfect replication of an arbitrary unknown due to the linearity of . First proven by Wootters and Zurek, this theorem arises because attempting to clone a superposition would violate the unitarity of quantum evolution, as the output state would not match the required form for all inputs. Consequently, quantum networks cannot amplify or copy signals in the manner of classical optical repeaters, instead relying on direct transmission of qubits or protocols like entanglement swapping to propagate information over distances. This limitation enhances security—any interception attempt disturbs the state detectably—but demands novel architectures to mitigate losses and decoherence. Quantum entanglement further distinguishes these networks, referring to a correlation between qubits where measuring one instantly determines the state of the other, even if separated by vast distances, without classical . This non-local linkage enables the distribution of shared quantum resources essential for network operations. Overall, these principles—superposition, entanglement, and no-cloning—fundamentally differentiate quantum networks from classical ones by prohibiting unrestricted copying while unlocking unprecedented information processing and paradigms.

Historical overview

The foundations of quantum networks trace back to early theoretical work in quantum information theory during the late 1960s and 1970s. Stephen Wiesner introduced the concept of conjugate coding around 1970, which demonstrated the no-cloning theorem's implications for by using non-orthogonal quantum states, serving as a key precursor to . This idea, though initially unpublished until , highlighted the potential of to enable information-theoretically secure protocols that classical systems could not achieve. A pivotal advancement came in 1984 with the proposal of the protocol by Charles Bennett and , marking the first practical (QKD) scheme for secure key exchange over point-to-point links using photon polarization states. Building on this, the concept of was theoretically proposed in 1993 by Bennett and colleagues, enabling the transfer of an unknown quantum state between distant parties via entanglement and classical communication, without physical transport of the particle itself. This was experimentally demonstrated for the first time in 1997 by teams led by and Dik Bouwmeester, achieving teleportation of photon states over laboratory distances, which laid groundwork for extending across networks. The 2000s saw the emergence of quantum repeater concepts essential for scaling quantum networks beyond direct transmission limits imposed by loss in quantum channels. In 1998, Hans Briegel, Wolfgang Dür, Juan Ignacio Cirac, and proposed a quantum repeater protocol that combines entanglement purification, , and to distribute high-fidelity entanglement over long distances, addressing in optical fibers. Subsequent refinements in the early 2000s by Dür and others focused on fault-tolerant implementations using atomic ensembles and error correction, paving the way for practical network architectures. By the , research shifted toward multi-node quantum networks, with landmark achievements including the distribution of entanglement over more than 100 km; for instance, in 2015, groups in the demonstrated robust entanglement links in a metropolitan setting. A significant milestone came in 2017 when Chinese researchers demonstrated satellite-based entanglement distribution over 1200 km using the Micius satellite, advancing prospects for global-scale quantum networks.

Fundamental Concepts

Quantum entanglement in networks

Quantum entanglement forms the cornerstone of quantum networks, enabling correlations between distant quantum systems that underpin secure communication and distributed quantum computing. It occurs when two or more particles, such as qubits, are prepared in a shared quantum state such that the state of one particle cannot be described independently of the others, even across arbitrary distances. A canonical example is the Bell state |\Phi^+\rangle = \frac{1}{\sqrt{2}} \left( |00\rangle + |11\rangle \right), where measurements on one qubit instantaneously determine the outcome on the other, exhibiting perfect anticorrelation or correlation depending on the basis. These states demonstrate non-local correlations that violate Bell inequalities, such as the Clauser-Horne-Shimony-Holt (CHSH) inequality, providing empirical evidence against local hidden variable theories and confirming the quantum mechanical nature of entanglement. Entanglement generation in quantum networks relies on several methods tailored to produce reliable correlated states. A prevalent probabilistic approach is (SPDC) in nonlinear crystals, such as beta-barium borate (BBO), where a pump laser splits into two lower-frequency whose polarizations or frequencies are entangled, conserving and . This technique has achieved high-fidelity entangled pairs with rates up to millions per second, though heralding is required to confirm pair creation. For more deterministic sources essential for scalable networks, atomic ensembles—groups of collectively excited atoms—or trapped ions are employed; in the former, in ensembles like atoms generates Stokes entangled with spin excitations, while in the latter, laser-driven gates create entanglement between ion hyperfine states with fidelities exceeding 99%. These methods enable on-demand entanglement, with trapped ion systems demonstrating storage times over seconds. In quantum networks, entanglement acts as a versatile resource for linking nodes, facilitating protocols like —where an unknown state is transferred using shared entanglement and classical communication—and enabling the distribution of without direct state transmission. Its utility is quantified through metrics such as , a measure for two- systems defined as C(\rho) = \max(0, \sqrt{\lambda_1} - \sqrt{\lambda_2} - \sqrt{\lambda_3} - \sqrt{\lambda_4}) (where \lambda_i are eigenvalues of a constructed ), which ranges from 0 for separable states to 1 for maximally entangled ones, or the entanglement of formation, which calculates the minimal ensemble needed to produce the state, providing an operational cost in terms of maximally entangled pairs. These quantifiers assess the resource quality, with high (e.g., >0.9) indicating robust links suitable for network operations. Entanglement is typically distributed via quantum channels between nodes, preserving for further processing. A key mechanism for extending entanglement across networks is the entanglement swapping protocol, which interconnects multiple short-distance entangled pairs to form long-range links without direct interaction between endpoints. In this process, suppose two independent entangled pairs are established: qubits A and B in one , and qubits C and D in another. A central performs a Bell-state (BSM) on qubits B and C, projecting them into one of the four Bell states and thereby entangling A and D, whose correlation is confirmed by classical communication of the BSM outcome. This swapping, first proposed theoretically and experimentally realized with photons, succeeds with probability 50% per BSM in ideal linear optics setups and is repeated across nodes to bridge macroscopic distances, mitigating loss in quantum channels. The protocol's after swapping can reach 0.83 in early demonstrations, scaling with improvements in local entanglement generation.

Quantum information transmission

Quantum information transmission in quantum networks involves protocols that enable the transfer of quantum states between distant nodes while preserving their and superposition properties. Two primary paradigms exist: direct state transfer, where a quantum particle carrying the state is physically sent through a channel, and entanglement-based transmission, which leverages pre-shared entanglement to encode and reconstruct the state without directly transmitting the particle itself. Direct transfer is limited by decoherence and loss in physical channels, whereas entanglement-based methods, such as , allow for faithful state transfer using a combination of local operations and classical communication. The quantum teleportation protocol exemplifies entanglement-based transmission. In this scheme, sender and receiver share an entangled pair of s, such as a . To transmit an unknown state |\psi\rangle = \alpha |0\rangle + \beta |1\rangle, performs a joint Bell-state measurement on her and the entangled partner, obtaining one of four possible outcomes with equal probability. She then sends these two classical bits to via a classical . Based on the outcome, applies a corresponding Pauli correction (, X, Z, or XZ) to his entangled , reconstructing |\psi\rangle with perfect fidelity in the ideal case. This process consumes one ebit of entanglement per teleported and requires two classical bits, highlighting the hybrid nature of quantum networks. Entanglement swapping can extend this to multi-hop networks by linking distant pairs. Another key protocol is superdense coding, which enhances classical information transmission using quantum resources. If Alice and Bob share a maximally entangled Bell state, Alice can encode two classical bits into a single qubit by applying one of four unitary operations (identity, X, Z, or XZ) to her share of the entanglement. She sends this qubit to Bob, who measures the pair in the Bell basis, decoding the two bits with perfect fidelity. Without entanglement, sending two classical bits would require two qubits or bits; thus, superdense coding doubles the classical capacity of the quantum channel, achieving a capacity of 2 bits per qubit. This protocol underscores the advantage of quantum networks for hybrid classical-quantum communication. Quantum channels in networks are inherently noisy, modeled by error channels that degrade transmitted states. A common model is the depolarizing channel, which with probability p replaces the input density operator \rho with the maximally mixed state I/2, and with probability $1-p leaves it unchanged: \mathcal{E}(\rho) = (1-p) \rho + p \frac{I}{2}. This models symmetric decoherence from environmental interactions, such as phase flips or bit flips in qubit transmission. In quantum networks, such errors reduce the fidelity of teleported or directly transferred states, necessitating error correction for long-distance communication. The of transmission quantifies the preservation of the original state. The average \bar{F}, averaged over all pure input states on the , measures the overall performance of a or : \bar{F} = \int d\psi \langle \psi | \mathcal{E}(|\psi\rangle\langle\psi|) | \psi \rangle, where the integral is over the . For ideal , \bar{F} = 1; classical measure-and-prepare strategies achieve at most \bar{F} = 2/3 for qubits. In noisy like depolarizing with parameter p, \bar{F} = 1 - \frac{p}{2}, dropping below 2/3 for p > 2/3, below which quantum advantages vanish. These metrics guide the design of reliable quantum links. A fundamental limitation is the , which prohibits using shared entanglement alone for superluminal signaling. Local operations on one part of an entangled state do not alter the reduced of the distant part, preventing without a classical channel. This theorem ensures compatibility with in quantum networks, as seen in where classical communication is essential for state . In classical-quantum hybrid protocols, classical channels play a crucial role by conveying measurement outcomes or corrections, as in where the two classical bits enable Bob to recover the state. This hybrid approach mitigates quantum channel limitations, allowing scalable networks where distribution is paired with reliable classical feedback for high-fidelity transmission.

Key Components

Quantum nodes and end devices

Quantum nodes and end devices serve as the endpoints in quantum networks, where is generated, stored, processed, and interfaced with communication channels. These devices typically consist of quantum processors capable of manipulating qubits, along with interfaces for converting between stationary matter qubits and flying photonic qubits. Matter-based nodes, such as those using trapped ions or superconducting qubits, excel in local quantum operations due to their long times and high gate fidelities, while light-based nodes, including single-photon sources and detectors, facilitate efficient entanglement distribution over optical links. Matter-based quantum nodes rely on atomic or solid-state systems to host qubits with robust storage and processing capabilities. Trapped ion nodes, for instance, use laser-cooled ions like ^{171}Yb^+ to prepare quantum states through and , achieving times up to seconds and entanglement fidelities exceeding 90% in local gates such as CNOT operations. Superconducting qubit nodes, fabricated from Josephson junctions in microwave circuits, enable fast local gates (on the order of nanoseconds) and have demonstrated loss-tolerant entanglement generation, with times reaching microseconds under cryogenic conditions. These nodes often integrate quantum memories, such as atomic spin ensembles, with times up to seconds via techniques like (EIT), allowing temporary storage of photonic qubits for network synchronization. In contrast, light-based quantum nodes emphasize photonic components for direct interaction with transmission media. Single-photon sources, commonly based on quantum dots or in nonlinear crystals, generate indistinguishable photons on demand with purities over 99%, essential for creating Bell states in entanglement swapping protocols. Photon detectors, such as superconducting nanowire single-photon detectors (SNSPDs), achieve detection efficiencies above 90% and low dark counts, enabling high-fidelity Bell-state measurements critical for verifying entanglement at network endpoints. Hybrid light-matter interfaces in these nodes, like cavity-enhanced coupling, bridge the two paradigms by mapping photonic states to matter qubits with fidelities around 80-90%. Prominent examples of matter-based end devices include nitrogen-vacancy (NV) centers in diamond, which operate at room temperature and support multi-qubit registers with spin coherence times of milliseconds. NV centers prepare triplet spin states via optical excitation and perform local gates with fidelities over 99%, as demonstrated in a three-node quantum network where remote entanglement was achieved over 1.3 km with 92% fidelity. These devices integrate with classical electronics for microwave control and readout, enabling scalable control of nuclear spins as ancillary qubits. Scalability of quantum nodes faces significant challenges, particularly in intra-node . In trapped systems, beyond tens of s requires advanced architectures to maintain all-to-all , often limited by addressing precision. Superconducting nodes typically employ layouts for nearest-neighbor coupling, but transitioning to architectures could reduce wiring complexity and improve error rates in large-scale processors, though cryogenic remains a hurdle. NV centers benefit from diamond's lattice for natural arrays, yet extraction efficiency below 10% constrains network integration. Overall, achieving modular designs with >100 s while preserving >99% fidelities is essential for practical quantum networks.

Quantum channels and physical media

Quantum channels in quantum networks serve as the physical pathways for transmitting , primarily in the form of photons carrying qubits, and are broadly categorized into guided and unguided types. Guided channels, such as optical fibers, provide controlled environments for signal propagation with typical rates of approximately 0.2 dB/km at a of , enabling relatively long-distance transmission before significant loss occurs. In contrast, unguided channels, including free-space , expose quantum signals to atmospheric , which induces beam wandering, , and phase fluctuations that degrade signal fidelity over distances exceeding a few kilometers. Loss and decoherence represent primary limitations in these channels, with photon loss arising from absorption and scattering that follows an exponential decay with propagation distance, often quantified by the channel's transmission probability η ≈ e^{-αL}, where α is the and L is the length. Decoherence manifests as due to environmental interactions, such as thermal vibrations in fibers or refractive index variations in free space, which randomize the quantum state's and reduce entanglement . In guided media, chromatic further impacts qubit by causing temporal broadening of wave packets, particularly for or time-bin encoded s, limiting the effective channel length without compensation. Wavelength selection is critical for minimizing losses, with the telecom C-band (1530–1565 ) favored for its low in silica fibers, approximately 0.2 dB/km, making it ideal for integrating quantum networks with existing infrastructure. However, many quantum emitters operate in the visible or near- range, necessitating quantum frequency conversion to shift photons to the infrared telecom bands while preserving quantum properties like indistinguishability and entanglement; techniques such as in nonlinear crystals achieve efficiencies up to 80% for visible-to-IR conversion. The ultimate capacity of quantum channels is bounded by the Holevo quantity, which quantifies the maximum reliable classical information transmittable per use as \chi = S(\rho) - \int S(\rho_x) \, p(x) \, dx, where S denotes the , \rho is the average state of the ensemble, and \rho_x are the conditional states with probabilities p(x). This bound highlights the trade-offs between quantum and classical communication limits in lossy environments, often requiring quantum repeaters to extend practical distances.

Quantum repeaters and purification

In quantum networks, direct transmission of quantum information over long distances is severely limited by exponential attenuation in communication channels, such as optical fibers, where photon loss scales as e^{-\alpha L} with attenuation coefficient \alpha and distance L. This results in an exponentially decreasing success probability for entanglement distribution, making it impractical beyond a few hundred kilometers without amplification, which is forbidden by the no-cloning theorem. Quantum repeaters address this by dividing the total distance into shorter segments, generating elementary entanglement links locally, and then extending them through purification and swapping operations, thereby reducing the overall resource scaling from exponential to polynomial in distance. Two primary types of exist: trusted repeaters and untrusted quantum repeaters. Trusted repeaters function as classical relays that measure incoming quantum states, store keys, and re-encrypt for forwarding, relying on the security of the intermediate but not preserving full quantum end-to-end. In contrast, untrusted quantum repeaters operate without trusting the nodes, using inherently quantum protocols to generate and extend entanglement across the network, ensuring even against compromised repeaters. Central to untrusted quantum repeaters are protocols for entanglement purification and swapping. Entanglement purification extracts high-fidelity entangled pairs from a larger set of noisy, low-fidelity pairs produced over lossy channels, using local quantum operations and classical communication (). A seminal example is the Bennett-Brassard-Popescu-Schumacher-Smolin-Wootters (BBPSSW) protocol, which employs bilateral controlled-NOT (CNOT) gates and measurements on multiple copies to "hash" errors, probabilistically yielding near-maximally entangled states from imperfect ones, such as Werner states with fidelity above 0.5. Entanglement swapping then extends these purified links by performing fusion operations, typically partial measurements, at intermediate nodes to connect disjoint entangled pairs into longer-distance entanglement without direct transmission. To mitigate errors from decoherence and imperfect operations during storage and manipulation, quantum repeaters incorporate correction techniques. Quantum error-correcting codes, such as the surface code, encode logical qubits into a two-dimensional of physical qubits, tolerating local rates up to approximately 1% while suppressing overall failure rates exponentially with code distance. Heralded entanglement generation complements this by using detection events to confirm successful creation of entangled states, such as via or atomic Raman processes, allowing repeaters to retry failed attempts without corrupting stored . Early experimental implementations of quantum repeaters have demonstrated these principles using the Duan-Lukin-Cirac-Zoller (DLCZ) protocol, which employs atomic ensembles as quantum memories. In DLCZ, entanglement is generated heralded by detecting a single Stokes photon from collective spin excitations (spin squeezing) in Rydberg-blockaded atomic clouds, enabling elementary links over tens of meters with fidelities around 0.5-0.7, followed by swapping via photon detection. Demonstrations include storage times exceeding 1 ms and distribution over 100 km in fiber, with recent advances as of 2025 extending entanglement between quantum memories to over 420 km in fiber, paving the way for scalable networks despite challenges in memory efficiency.

Network Architectures

Fiber-optic based networks

Fiber-optic based quantum networks leverage standard optical fibers as the primary transmission medium for quantum information, enabling the distribution of quantum states such as entangled photons over terrestrial distances while integrating with existing telecommunication infrastructure. These networks utilize the low-loss properties of silica fibers at telecom wavelengths (around 1550 nm), which minimize photon absorption and allow for practical deployment in urban and metropolitan settings. By employing single-mode fibers, quantum signals can propagate with attenuation rates as low as 0.2 dB/km, supporting entanglement distribution without active amplification over tens of kilometers. A key advantage of fiber-optic quantum networks is their compatibility with established telecom infrastructure, allowing quantum channels to coexist with classical data traffic through (WDM), where quantum signals occupy distinct spectral bands to avoid interference. This multiplexing reduces deployment costs by enabling shared use of fiber links, including underutilized "dark fibers" that are leased or dedicated for quantum purposes without disrupting conventional services. For instance, dark fiber networks have facilitated real-world tests of quantum protocols over urban loops exceeding 10 km, demonstrating seamless integration with minimal modifications to existing cabling. Despite these benefits, fiber-optic systems face significant challenges from environmental and material effects that degrade . Raman scattering, both spontaneous and stimulated, generates noise photons that can mimic quantum signals and reduce , particularly in standard solid-core fibers where light interacts strongly with the glass material. in fibers causes polarization rotations over distance, necessitating active stabilization to preserve the quantum state's encoding. Additionally, erbium-doped fiber amplifiers (EDFAs), commonly used for classical signals, introduce through ; this is mitigated by relying on passive, unamplified fibers for quantum transmission, limiting link lengths to avoid excessive loss. Notable deployments include the SwissQuantum (SQS) network in during the 2010s, a three-node (QKD) spanning several kilometers of fiber to validate protocols in a real-world setting. Similarly, the QKD Network, operational since 2010, interconnects 10 nodes via a switched optical over metropolitan fibers, achieving rates up to 100 kbps for applications like secure video transmission. These examples highlight reliable entanglement distribution over 50 km without repeaters, as demonstrated in experiments linking trapped ions to photons through deployed fibers with fidelities exceeding 90%. For extending beyond such distances, quantum repeaters are essential, as explored in the key components section. Recent enhancements focus on specialized fibers and integrated devices to overcome limitations. Hollow-core fibers, which guide light through an air-filled core, reduce latency by up to 30% compared to solid-core counterparts and suppress Raman noise due to minimal material interaction, enabling higher-fidelity quantum transmission over longer spans. Integration with platforms further advances on-chip quantum links, allowing compact generation and manipulation of entangled photons directly interfaced with fiber networks for scalable, low-loss connections. These developments pave the way for denser, more efficient fiber-based quantum architectures compatible with future quantum internet backbones.

Free-space and satellite networks

Free-space quantum networks enable unguided transmission of through the atmosphere or , offering advantages in mobility and long-distance connectivity compared to guided media like fiber optics. These networks rely on , where quantum states such as photons are sent via beams between sender and receiver. Key challenges include , which causes the signal to spread over distance, reducing coupling efficiency into detectors, and the need for precise pointing accuracy to maintain alignment despite relative motion or vibrations. systems correct for these issues by using deformable mirrors and wavefront sensors to compensate for atmospheric , which distorts the beam and induces . Atmospheric effects significantly impact free-space quantum transmission, including scattering by aerosols and molecules, as well as absorption by gases like water vapor and oxygen. Optimal wavelengths fall within transmission windows such as 800-1000 nm, where losses are minimized due to lower molecular absorption compared to other bands. Weather conditions exacerbate these losses; for instance, fog, rain, or clouds can increase scattering and attenuation by orders of magnitude, limiting link availability to clear nights in many experiments. Turbulence, characterized by refractive index fluctuations, further degrades beam quality, but mitigation techniques like spatial mode adaptation help preserve entanglement fidelity. Satellite-based free-space networks extend quantum links globally by orbiting at altitudes of hundreds of kilometers, avoiding ground-based atmospheric limitations over long paths. China's Micius satellite, launched in 2016, demonstrated entanglement over 1200 km between the and ground stations in Delingha and , , achieving a Bell inequality violation with S = 2.37 ± 0.09, confirming . It also enabled (QKD) over a 7600 km intercontinental link by relaying keys between ground stations in and via satellite-to-ground downlinks, producing 1.1 kbit/s secret key rates after error correction. These experiments used downconversion sources at 810 nm for pairs, with achieving pointing accuracies better than 1 arcsecond. For shorter-range ground-to-ground links, free-space quantum networks support urban or mobile applications, such as building-to-building connections in metropolitan areas. Experiments have demonstrated QKD over several kilometers between stationary ground stations using telescopes for beam steering, with rates up to 1 kbit/s in clear conditions. Drone-based platforms enable dynamic links, as shown in a 2021 demonstration where two drones relayed entangled photons over 1 km between ground stations, maintaining quantum correlations despite motion, with fidelities above 80%. These approaches leverage lightweight optics and GPS for tracking, paving the way for ad-hoc quantum networks in environments where fixed infrastructure is impractical.

Hybrid and integrated architectures

Hybrid quantum network architectures combine multiple transmission media, such as fiber-optic and free-space channels, to overcome the limitations of individual approaches and enable broader coverage. These designs often incorporate fiber-to-free-space converters that interface guided and unguided optical links, allowing seamless entanglement distribution across diverse environments. For instance, experiments have demonstrated polarization-entangled pairs distributed over a campus-scale three-node using off-the-shelf devices to bridge fiber and free-space segments, achieving viable fidelity for early quantum communication systems. Satellite-ground hybrid systems further extend this paradigm by integrating satellite-based free-space links with terrestrial fiber networks, providing global-scale entanglement distribution that mitigates fiber attenuation over long distances and atmospheric losses in free-space propagation. A proposed protocol outperforms pure ground- or satellite-based designs by optimizing entanglement generation and swapping across both media, enabling high-fidelity connections over continental scales for applications like . Such architectures leverage low-Earth satellites for inter-continental while relying on for dense metropolitan connectivity, ensuring robust global coverage. Integrated plays a crucial role in these hybrid systems by miniaturizing quantum nodes through photonic integrated circuits (PICs), which consolidate multiple functions on a single chip to enhance scalability and reduce losses. platforms, prized for their strong electro-optic effects and low propagation losses, host PICs that integrate entangled photon sources—such as whispering gallery mode resonators for —along with detectors and switches like asymmetric Mach-Zehnder interferometers achieving up to 25 dB extinction ratios. These components enable on-chip entanglement generation, routing, and detection, forming compact nodes compatible with hybrid media interfaces and supporting microwave-optical transduction for heterogeneous quantum operations. Network topologies in hybrid architectures adapt classical designs to quantum constraints, balancing connectivity with entanglement preservation. Star configurations centralize through a , simplifying but limiting due to single-point failures and bottleneck losses in entanglement . In contrast, topologies provide redundant paths, enhancing resilience and allowing opportunistic entanglement that exploits probabilistic quantum links for higher end-to-end . Entanglement algorithms, such as reactive and proactive variants, select sequences of short-range entanglements for , prioritizing and times over classical metrics like ; these are particularly effective in setups for dynamic, heterogeneous networks. Scalability in hybrid and integrated architectures relies on modular designs with standardized layers to accommodate heterogeneous nodes, including diverse like and memories. Projects like MadQCI demonstrate this through (SDN) for , deploying 28 modular QKD units across nine sites with vendor-agnostic based on standards, enabling dynamic routing over 1.9–33.1 km links and multi-domain expansion. Similarly, InterQnet employs full-stack co-design with protocols for integrating first-generation and error mitigation, facilitating communication across heterogeneous platforms via centralized control and modular error correction layers. These approaches ensure , allowing incremental scaling from local to global networks without overhauling underlying .

Applications

Quantum communication and security

Quantum communication in quantum networks primarily revolves around (QKD), a that enables two parties, , to generate a shared secret key for encrypting classical data with unconditional security guaranteed by . Unlike classical cryptography, which relies on computational hardness assumptions, QKD detects eavesdropping attempts (by an adversary, Eve) through the and Heisenberg's , as any measurement by Eve introduces detectable disturbances in the quantum states. This allows for , where the key is secure against any computationally unbounded attacker, provided the and devices are properly authenticated. The foundational QKD protocol is , proposed by Bennett and in , which uses polarization-encoded qubits transmitted over optical channels. Alice sends photons in one of four polarization states: horizontal (0°), vertical (90°), or diagonals (45°, 135°), randomly choosing between two bases (rectilinear or diagonal) for each bit. Bob measures in a randomly selected basis, and they publicly compare bases via a classical channel, retaining only matching basis outcomes (sifting), which yields a raw key with approximately 50% efficiency. Security is ensured through privacy amplification, where they estimate the quantum bit error rate (QBER) from a subset of bits; if the QBER exceeds 11%, Eve's presence is inferred, and no secure key is generated, as this threshold marks the point where her information gain compromises secrecy. Post-processing includes error correction to reconcile discrepancies and privacy amplification to distill a secure key from the raw one. An entanglement-based alternative is the E91 protocol, introduced by Ekert in 1991, which distributes entangled photon pairs to , who measure in randomly chosen bases. Unlike , E91 achieves device-independent security by verifying the entanglement through Bell inequality violations; if the exceeds the classical bound (S > 2), it certifies that the shared measurements are correlated without Eve's full knowledge, enabling even with imperfect devices. This protocol leverages quantum networks for entanglement distribution, briefly referencing the need for reliable pairwise entanglement to initiate the process. Security proofs for E91 also rely on information-theoretic bounds, bounding Eve's knowledge based on observed correlations. To extend QKD in quantum networks with untrusted intermediate nodes, measurement-device-independent QKD (MDI-QKD) was developed by Lo et al. in 2012, where send states to a central untrusted that performs a measurement without revealing information. This mitigates detector side-channel attacks, as the relay only announces measurement outcomes classically, allowing to post-process securely. For longer distances, twin-field QKD (TF-QKD), proposed by Lucamarini et al. in 2018, enables up to 1002 km over fiber by having send phase-randomized weak coherent pulses to a central node, which interferes "twin" fields with matching phases; this achieves a square-root dependence on channel transmittance, surpassing the fundamental rate-distance limit of point-to-point QKD without . Practical implementations of these protocols are available in commercial quantum networks, such as ID Quantique's XG Series systems, which integrate BB84-based QKD for high-availability in fiber-optic infrastructures, supporting rates suitable for and applications. The rate in such weak coherent pulse schemes approximates R \approx \frac{\eta \mu e^{-\mu}}{2}, where \eta is the overall detection efficiency and \mu is the mean number per pulse (typically optimized around 0.1–0.5 to minimize multi-photon events exploitable by ); this formula captures the single-photon contribution after sifting, with full rates incorporating states for security against photon-number-splitting attacks. These systems demonstrate the feasibility of quantum-secure communication in real-world networks, prioritizing conceptual robustness over exhaustive benchmarks.

Distributed quantum computing

Distributed quantum computing leverages quantum networks to interconnect remote quantum processors, enabling collaborative execution of quantum algorithms that surpass the capabilities of isolated devices. This paradigm addresses the limitations of single quantum processing units (QPUs) by distributing computational tasks across networked nodes, where entanglement links facilitate non-local operations. Key approaches include quantum computing, in which a client delegates computation to a remote without disclosing the input or , preserving through protocols. Another foundational model is measurement-based quantum computing (MBQC), which relies on distributed generation and measurement of entangled cluster states to drive computations in a one-way manner, allowing scalable across network-connected modules. Central protocols in distributed quantum computing involve teleported gates, where entanglement shared via quantum channels enables the remote implementation of entangling operations, such as controlled-NOT gates, between qubits in separate nodes. Quantum gate teleportation (QGT) consumes a single Bell pair per gate and supports universal computation by combining local operations with network-distributed entanglement, minimizing communication overhead compared to circuit cutting techniques. In MBQC protocols, resource allocation focuses on creating large-scale cluster states across the network, with measurements on one node propagating computational effects to distant qubits, as formalized in agent-based models for multi-party computations. These protocols ensure by incorporating error correction tailored to network-induced noise, such as loss in links. Architectures for distributed quantum computing emphasize modularity, interconnecting small-scale QPUs via quantum networks to form larger logical processors. In modular designs, ion-trap or superconducting modules are linked through photonic channels, allowing hierarchical scaling where local handle intra-module operations and teleported manage inter-module entanglement. Fault-tolerant thresholds in these networked systems require physical error rates below approximately $10^{-3} per to suppress logical errors, a stricter criterion than in monolithic setups due to additional link infidelity, but achievable with distributed error-correcting codes like surface-code variants adapted for networks. Such architectures support ecosystem-level integration, including resource scheduling and verification for multi-client scenarios. The primary benefit of distributed quantum computing is enhanced scalability, overcoming qubit coherence limits and fabrication constraints of single devices by pooling resources from multiple networked processors. For instance, experiments with trapped-ion modules have demonstrated two-qubit gates teleported over approximately 2-meter optical links, achieving gate fidelities of 86%. This approach also facilitates blind computation in multi-client settings, as shown in photonic networks where users verify server outputs without revealing computations, paving the way for secure, cloud-based quantum services. In 2025, the development of QNodeOS, a programmable operating system for quantum networks, has enabled high-level execution of distributed quantum programs, further advancing practical applications. Overall, these advancements position quantum networks as a cornerstone for practical, large-scale quantum information processing.

Quantum sensing and metrology

In quantum metrology, the precision for estimating a parameter such as phase or frequency using N independent probes is fundamentally limited by the standard quantum limit (SQL), which scales as \delta \theta \sim 1/\sqrt{N}. This arises from the shot-noise scaling in separable quantum states, where uncorrelated measurements add variances that grow with the square root of the probe number. In contrast, leveraging entanglement across the probes enables the Heisenberg limit (HL), achieving a superior scaling of \delta \theta \sim 1/N, which quadratically enhances sensitivity by correlating the quantum resources coherently. Quantum networks distribute such entanglement among spatially separated nodes, allowing metrology tasks to exploit collective quantum correlations over extended distances, as generated through photonic links or repeaters. Distributed sensing in quantum networks applies these principles to measure global parameters, such as averaged shifts, with entanglement-enhanced across fiber arrays or ensembles. For instance, a four- continuous-variable entangled network has experimentally demonstrated deterministic sensing of an averaged displacement, achieving precision beyond the SQL through balanced and saturating the quantum Cramér-Rao bound under realistic efficiencies (e.g., \eta = 0.735). Clock via quantum networks further utilizes entanglement to align temporal references with sub-SQL ; one-way protocols employing Greenberger-Horne-Zeilinger states transmitted between s yield accuracy, minimizing errors from propagation delays and outperforming classical methods by factors tied to the number of measurements (N = 6000). Representative examples include entanglement-based magnetometry using nitrogen-vacancy (NV) centers in , where spins are linked via photonic interfaces to form networked sensors for detecting weak . These setups mediate spin-photon entanglement without direct excitation, enabling distributed NV arrays to probe biological or material samples at sensitivities approaching the HL for femtotesla-scale fields. Conceptual extensions to gravitational wave detection envision global quantum arrays of entangled interferometers, enhancing low-frequency strain measurements through networked phase accumulation that pushes beyond current quantum limits in observatories like . Key protocols in networked include quantum illumination, which distributes entangled signal-ancilla pairs across nodes for target detection in entanglement-breaking , offering error exponents superior to classical strategies even with partial entanglement preservation. Recent advances, such as squeezed light protocols demonstrated in 2025, improve efficiency in quantum network sensing by reducing in optical channels, enhancing precision for distributed metrology tasks. The further underpins these advances by quantifying the maximum extractable precision in multi-parameter distributed , as in linear networks where it bounds correlations for phases across nodes and guides optimal entanglement usage.

Challenges and Advances

Technical challenges in scalability

One of the primary technical challenges in scaling quantum networks is decoherence, which arises from environmental coupling that disrupts quantum states through mechanisms such as energy relaxation (characterized by T1 time) and (characterized by time). In superconducting qubits, commonly considered for network nodes, these coherence times are typically on the order of milliseconds, with recent advancements achieving up to 1.43 ms for fluxonium qubits, though network-induced errors from imperfect entanglement swapping further exacerbate decoherence during transmission. Scalability barriers in quantum networks are compounded by the overhead associated with quantum , where must significantly exceed gate operation speeds to maintain across multiple nodes, often leading to degradation in performance as size increases. A fundamental rate-loss governs deployment, exemplified by the 1/e rule, which states that the secret key rate or entanglement generation rate scales as η^(1/e) per channel use, with η as the channel transmittance (η = e^(-L/l_att), where L is distance and l_att is the of ~20-50 km for fiber ), limiting the viable segment length between to distances where losses do not drop below e^(-1). Integration challenges further hinder , particularly in interfacing diverse platforms, such as converting quantum states between trapped-ion qubits and photons for , where efficiencies remain below 1% due to mode mismatch and collection losses, necessitating systems that bridge matter-based memories and flying qubits. Standardization of quantum interfaces, akin to for entanglement distribution and control protocols, is also lacking, impeding across heterogeneous nodes and requiring unified frameworks to manage diverse qubit modalities without introducing additional errors. Mitigation strategies focus on developing high-fidelity components, with fidelities exceeding 99% essential for suppressing error accumulation in chains, as lower thresholds lead to prohibitive overhead in error correction. Trade-offs between cryogenic and room-temperature operations pose additional hurdles; superconducting qubits demand dilution refrigerators for millisecond but complicate integration due to thermal isolation, whereas room-temperature alternatives like nitrogen-vacancy centers in offer simpler deployment at the cost of shorter times (~1 ms) and higher susceptibility.

Recent experimental progress

In 2021, researchers at QuTech in demonstrated the first multi-node entanglement-based quantum network using three remote solid-state qubits based on nitrogen-vacancy centers in , enabling the distribution of multipartite entanglement and basic network protocols over laboratory distances. This experiment laid the groundwork for scalable quantum routing by incorporating entanglement swapping between nodes. Building on this, in 2022, a superconducting quantum network prototype connected two physically separated nodes, each with three qubits, achieving entanglement purification and protection against decoherence through microwave photon exchange. A significant advancement in long-distance quantum key distribution (QKD) occurred in , when a team achieved non-relay QKD over 1,002 km of ultralow-loss using a dual-band phase-matching approach in a twin-field protocol, generating secure keys at a rate of 0.003 bits per second. Complementing fiber-based efforts, the Micius satellite enabled relay-assisted QKD demonstrations extending effective ranges beyond 1,000 km by integrating space-to-ground links with ground stations. In 2024, researchers demonstrated metropolitan-scale heralded entanglement between solid-state qubits over 10 km using NV centers. Additionally, QuTech achieved a 25 km quantum network link between Dutch cities, representing a key step toward city-scale quantum connectivity. Emerging milestones include 2025 demonstrations of drone- and vehicle-based , achieving secret key rates on the order of kHz over dynamic free-space links. These experiments support flexible quantum links with entanglement fidelities around 85%. Collaborative initiatives, such as the EU Quantum Internet Alliance, have driven integrated testbeds across for multi-node entanglement routing, while the Quantum Networking and Communications Research Roadmap outlines national efforts toward scalable prototypes.

Future directions and quantum internet

The quantum internet represents a transformative vision for global information exchange, centered on the widespread distribution of to achieve unconditional security in communications and to facilitate advanced distributed . This network would enable protocols like (QKD) for unbreakable encryption and entanglement-based computing tasks that surpass classical limits. Development is anticipated in phased milestones: from 2025 to 2030, efforts will focus on establishing regional networks with entanglement demonstrations over metropolitan and national distances, building on pilot deployments to create interconnected urban and continental infrastructures. Beyond 2030, intercontinental links via and fiber hybrids are projected to form a fully global quantum backbone, supporting seamless entanglement swapping across borders. Emerging technologies are poised to address key limitations in quantum network reliability and efficiency. Topological qubits, leveraging exotic quasiparticles like Majorana fermions, offer inherent robustness against decoherence and noise, enabling more stable long-distance entanglement in networks. AI-optimized routing, powered by frameworks such as deep Q-networks, will dynamically manage entanglement generation and distribution to minimize and maximize in complex topologies. Complementing these, services will provide on-demand access to remote quantum processors and entanglement sources, allowing broader adoption without the need for specialized local hardware. Societal impacts of the quantum internet extend to enhanced security and innovation across sectors. In the Internet of Things (IoT), quantum-secure channels will protect vast device networks from eavesdropping, ensuring privacy for sensitive data streams in smart cities and healthcare. Distributed quantum simulations will accelerate drug discovery by modeling protein folding and molecular dynamics with unprecedented accuracy, potentially reducing development timelines from years to months. Economically, the quantum technology ecosystem, including networks and computing, is forecasted to deliver up to $1 trillion in value by 2040 through productivity gains in pharmaceuticals, finance, and materials science. Policy and ethical considerations are integral to realizing this vision responsibly. International standardization initiatives, such as the Internet Engineering Task Force's (IETF) Post-Quantum Use In Protocols (PQUIP) working group, are developing guidelines for integrating quantum-resistant algorithms into protocols like TLS to ensure interoperability and . Ethical challenges include mitigating risks from quantum , where advanced adversaries could exploit vulnerabilities in early to forge signatures or intercept entangled states, underscoring the need for robust frameworks.

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