Unmanned aerial vehicle quantum network entanglement routing method with guaranteed fidelity

Abstract

The invention provides an unmanned aerial vehicle quantum network entanglement routing method with guaranteed fidelity. The method comprises the following steps: step 1, establishing entanglement connection between adjacent quantum nodes; step 2, establishing a path selection method with end-to-end fidelity as measurement; step 3, an entanglement purification method of hop-by-hop multiple attempts; and step 4, an evaluation method based on network throughput. The method is used for solving the problem of lack of unmanned aerial vehicle quantum entanglement network routing protocols, an entanglement purification scheme for guaranteeing the fidelity is given, and the end-to-end fidelity is effectively guaranteed. According to the method, the entanglement switching path taking the end-to-end fidelity as the routing metric is selected, so that the network throughput is further enhanced, and the quantum nodes of the unmanned aerial vehicle are protected.

Description

Technical Field

[0001] The present invention belongs to the field of network protocols and quantum technology, and specifically relates to a fidelity-guaranteed unmanned aerial vehicle quantum network entanglement routing method. Background Art

[0002] In recent years, with the rapid development of quantum information technology, quantum networks, especially quantum secure communication networks, have achieved remarkable achievements. Quantum secure communication networks are based on quantum key distribution technology (QKD), which can provide security against quantum computing for classical communications. At present, in order to further support quantum applications such as quantum computing and quantum sensing, many countries have made quantum networks based on quantum entanglement as the focus of subsequent research in quantum information technology. The second quantum technology revolution, which aims to promote the application of quantum information technology, has greatly promoted the development of key network equipment such as quantum memory and quantum repeaters, making the construction and implementation of quantum entangled networks possible.

[0003] Quantum entanglement networks are mostly based on optical fiber or satellite links, and the transmission of quantum information over long distances is achieved through entanglement exchange technology. However, the infrastructure distribution of optical fiber-based quantum networks is relatively fixed, and satellite-based quantum links can only be established at specific ground locations within a limited time window. Therefore, relying solely on optical fiber and satellite quantum links cannot meet all the needs of future quantum network construction. Compared with satellite and optical fiber links, drone platforms have the characteristics of access anytime, anywhere, flexible mobility, and rapid networking. Building an airborne quantum entanglement network with drone mobile platforms as nodes can provide real-time and secure coverage without being affected by fixed infrastructure and regions. Drone quantum entanglement networks can provide full-time and full-domain access services for multi-dimensional users including ground, high altitude, and ocean. It has become an indispensable and important puzzle piece in building a global quantum Internet.

[0004] The routing design with the goal of selecting entanglement exchange paths to extend the entanglement distribution distance is one of the important problems that need to be solved in the UAV quantum entanglement network, which can be called the entanglement routing problem. In classical networks, routing algorithms have been developed and applied in the network. However, since quantum entangled networks are essentially different from classical networks, the routing algorithms used in classical networks cannot be directly applied to quantum entangled networks. In addition, the dynamics and limited energy of UAV nodes make the entanglement routing problem more complicated than other types of quantum networks. In recent years, some studies have focused on the entanglement routing problem of quantum wireless networks and proposed some innovative methods. These studies have important reference significance for the research on entanglement routing technology based on UAV entanglement distribution. However, these existing studies rarely fully consider the entanglement fidelity. In fact, in quantum networks based on entanglement exchange, the fidelity of the distributed entangled pairs decays hop by hop due to the influence of environmental noise. In order to meet the fidelity requirements of terminal quantum applications, entanglement purification technology is essential. Therefore, the quantum entangled network based on UAV needs to further study the fidelity-guaranteed entanglement routing algorithm. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention proposes a fidelity-guaranteed drone quantum network entanglement routing method, which specifically includes the following steps:

[0006] Step 1: Establish entangled connections between adjacent quantum nodes;

[0007] The quantum nodes of drones are equipped with key physical devices that generate entanglement. Before the path-finding task begins, each adjacent node uses the onboard physical devices to establish an entangled connection.

[0008] Step 2: Establish a path selection method based on end-to-end fidelity;

[0009] After the neighboring nodes complete the entanglement distribution, the path selection task needs to be performed for the source node-destination node pair SD in the network that needs to establish a long-distance entanglement connection; the path finding method based on the end-to-end fidelity is selected;

[0010] Step 3: A hop-by-hop multiple-attempt entanglement purification method;

[0011] The quantum channel is modeled as a phase-damped channel; assuming that the onboard entangled source generates a For the EPR entangled state of n-hop phase damping channel, the fidelity of the entangled state established by entanglement exchange is F i for:

[0012]

[0013] In the formula, |φ + > 12represents the Bell state vector, |·> is called the right vector, "+" represents superposition, "1" and "2" represent two quantum bits, |00> 12 indicates that both qubits are in the ground state |0>, |11> 12 Indicates that both qubits are in the excited state |1>, the channel coefficient q = 1-p, p is the phase damping coefficient, q i is the q value of the i-th phase damping channel; if the minimum fidelity threshold required for quantum applications is F th , in order to ensure that the fidelity of the established end-to-end entanglement connection is higher than F th , establish a hop-by-hop entanglement purification method; after the 1-hop entanglement distribution is completed, according to formula (1), substitute the corresponding q value of the phase damping channel, and calculate and evaluate the fidelity of the next hop in turn; since q i The value is known, according to q i It is possible to calculate all F i ; if F i <F th , i = 2,…, n, then the corresponding link (u, v) in the network needs to be purified as shown in formulas (2)-(4), where u and v represent different quantum nodes respectively; entanglement purification produces an entangled pair with higher fidelity at the expense of two entangled pairs with lower fidelity; considering the bit flip error, the fidelity F of the entangled pair after purification is pur Calculated as:

[0014]

[0015] In the formula, f 1 ,f 2 is the fidelity of the two Bell pairs used for purification; since entanglement purification is probabilistic, the probability of successful purification is P pur satisfy:

[0016] P pur (f 1 ,f 2 ) = f 1 f 2 +(1-f 1 )(1-f 2 )(3)

[0017] To ensure the success rate of the purification operation, assume that the decoherence time of the quantum memory is Γ. If a purification attempt fails, more attempts will be made within a time period of Γ. Since the probability of success of one attempt is P pur , P pur YesP pur (f 1 ,f 2), so the probability of success in M ​​attempts is calculated as 1-(1-P pur ) M , then considering the probabilistic nature of entanglement purification, the expected fidelity F after successful purification is suc for:

[0018]

[0019] Where M is the number of purification times. For the links that need to be purified after evaluation, it can be seen from formula (4) that after the link is purified, the fidelity of the entangled pairs distributed on the link will be improved to F suc , F suc Yes F suc (f 1 ,f 2 ), for this purification link, substitute the purified fidelity F suc , from formula (1), we know that the channel coefficient q of the link can be converted into Since q = 1-p, the new equivalent damping coefficient p' of the link is calculated as After the above hop-by-hop purification method, the end-to-end entanglement connection is established through entanglement exchange;

[0020] Step 4: Evaluation method based on network throughput;

[0021] For the throughput of link (u,v), the expected throughput is defined as follows:

[0022]

[0023] Among them, N e is the number of entangled pairs consumed by the purification operation, and the capacity c(u,v) is the maximum number of entangled pairs that can be generated on the quantum channel; considering the worst purification case, let N e =2M; Assuming the number of path hops is h, the expected path throughput between source node s and destination node d is calculated as T(s,d)=min[T(u,v)]l h-1 .

[0024] In step 3 of a specific embodiment of the present invention, M=3.

[0025] The present invention first considers the influence of environmental noise. The present invention models the quantum channel as a phase-damped channel and gives the relationship between the entanglement exchange path and the fidelity of the quantum link under the Bell state. Then, considering the probability of entanglement purification, in order to provide end-to-end fidelity guarantee, the present invention proposes a hop-by-hop entanglement purification method with multiple attempts within the decoherence time. Finally, considering the fragility of the quantum link and the limited energy of the nodes in the drone quantum entanglement network, the present invention selects the entanglement exchange path with end-to-end fidelity as the routing metric to complete the design of FGER_D.

[0026] The advantages of the present invention are as follows:

[0027] 1. In response to the lack of quantum entanglement network routing protocols for drones, the present invention proposes a quantum entanglement routing protocol FGER_D that comprehensively considers the characteristics of drone networks.

[0028] 2. To address the problem of hop-by-hop attenuation of entanglement fidelity in a noisy environment, the present invention provides an entanglement purification scheme with fidelity assurance, which effectively ensures end-to-end fidelity.

[0029] 3. The present invention selects the entanglement exchange path with end-to-end fidelity as the routing metric, which further enhances the network throughput and protects the drone quantum nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is an example of a diamond topology routing, where Figure 1 (a) shows the original topology, Figure 1 (b) shows the topology after purification;

[0031] Figure 2 is the performance comparison under different fidelity thresholds, where Figure 2 (a) shows the throughput, Figure 2 (b) shows the average end-to-end fidelity, Figure 2 (c) shows the average consumed entanglement logarithm;

[0032] Figure 3 is the performance comparison under different entanglement exchange success rates, where Figure 3 (a) shows the throughput, Figure 3 (b) shows the average end-to-end fidelity;

[0033] Figure 4 is the performance comparison under different number of time slots, where Figure 4 (a) shows the throughput, Figure 4 (b) shows the average end-to-end fidelity, Figure 4 (c) shows the number of network nodes;

[0034] Figure 5 is the performance comparison under different link capacities, where Figure 5 (a) shows the throughput, Figure 5 (b) shows the average end-to-end fidelity. DETAILED DESCRIPTION

[0035] The following is combined with Figures 1 to 5 The present invention is described in detail with reference to the accompanying drawings and examples.

[0036] The present invention proposes a fidelity-guaranteed drone quantum network entanglement routing method, which specifically includes the following steps:

[0037] Step 1: Establish entangled connections between adjacent quantum nodes;

[0038] Since the drone quantum network is based on the characteristics of quantum entanglement, the entanglement routing protocol must first complete the distribution of entanglement between adjacent quantum nodes. Because the drone quantum nodes are equipped with key physical devices that generate entanglement (such as quantum repeaters and quantum memories), before the pathfinding task begins, each adjacent node in the present invention uses the above-mentioned airborne physical devices to establish a successful entanglement connection. The technology involved in this paragraph is well known to those skilled in the art and will not be repeated here.

[0039] Step 2: Establish a path selection method based on end-to-end fidelity;

[0040] After the adjacent nodes complete the entanglement distribution, the path selection task needs to be performed for the source node-destination node pairs (SD pairs) in the network that need to establish long-distance entanglement connections.

[0041] In the quantum entangled network based on drones, two characteristics put forward new requirements for the selection of routing metrics. On the one hand, the battery-powered drone nodes have limited energy. When the energy of the node is lower than the minimum standard to support the operation of the network, the drone node will exit the network. On the other hand, the fragility of the quantum link established by the quantum entangled network based on drones cannot be ignored.

[0042] In addition to the above factors, the current quantum entanglement network based on drones is mainly used for relaying, and the number of network nodes is relatively small. The traditional routing scheme using the minimum hop count algorithm will cause excessive energy consumption of some nodes, resulting in the drop of these nodes. In summary, using end-to-end fidelity as a routing metric can solve these problems to a certain extent, and has the following advantages: First, paths with high end-to-end fidelity are less affected by noise during the entanglement distribution process, and the system coherence is better, which can effectively protect the quantum link; secondly, given the application request fidelity threshold, paths with high end-to-end fidelity may not require entanglement purification operations, thereby releasing more entanglement resources, making the network have more end-to-end entangled connections, and improving network throughput. Therefore, the present invention selects a pathfinding method based on end-to-end fidelity as a measure.

[0043] Step 3: A hop-by-hop multiple-attempt entanglement purification method;

[0044] In order to successfully establish a connection request between SD pairs, it is necessary to complete the entanglement exchange hop by hop on the selected routing path. When the entangled pairs are distributed in free space, the fidelity of the entangled particle pairs will decrease hop by hop due to the influence of environmental noise. The present invention models the quantum channel as a typical quantum noise channel, that is, a phase damped channel. Assume that the airborne entangled source generates a For the EPR entangled state of n-hop phase damping channel, the fidelity of the entangled state established by entanglement exchange is F i for:

[0045]

[0046] In the formula, |φ + > 12 represents the Bell state vector, |·> is called the right vector, "+" represents superposition, "1" and "2" usually represent two quantum bits, |00 12 indicates that both qubits are in the ground state |0>, |11> 12 Indicates that both qubits are in the excited state |1>, the channel coefficient q = 1-p, p is the phase damping coefficient, q i is the q value of the i-th phase damping channel. From equation (1), we can see that when the environmental noise has a greater impact on the entangled pair, the fidelity drops sharply and the end-to-end fidelity cannot be guaranteed. If the minimum fidelity threshold required by quantum applications is F th , in order to ensure that the fidelity of the established end-to-end entanglement connection is higher than F th , the present invention establishes a hop-by-hop entanglement purification method. After the 1-hop entanglement distribution is completed, according to formula (1), the corresponding q value of the phase damping channel is substituted to calculate and evaluate the fidelity of the next hop in turn. i The value is known, according to q i All F can be calculated i If F i <F th ,i=2,…,n, then the corresponding link (u,v) in the network needs to be purified as shown in formulas (2)-(4), where u and v represent different quantum nodes. The specific process is as follows. Entanglement purification produces an entangled pair with higher fidelity at the expense of two entangled pairs with lower fidelity. Considering the bit flip error, the fidelity F of the entangled pair after purification is pur It can be calculated as:

[0047]

[0048] In the formula, f 1 ,f 2 is the fidelity of the two Bell pairs used for purification. Since entanglement purification is probabilistic, the probability of successful purification is P pur satisfy:

[0049] P pur (f 1 ,f 2 ) = f 1 f 2 +(1-f 1 )(1-f2 )(3)

[0050] Since the probability of success of a purification operation in one attempt is not high, in order to ensure the success rate of the purification operation, the present invention proposes a solution: assuming that the decoherence time of the quantum memory is Γ, if a purification attempt fails, more attempts will be made within the time period of Γ. Since the probability of success of one attempt is P pur , P pur YesP pur (f 1 ,f 2 ), so the probability of success in M ​​attempts can be calculated as 1-(1-P pur ) M , then considering the probabilistic nature of entanglement purification, the expected fidelity F after successful purification is suc for:

[0051]

[0052] Wherein, M is the number of purification times. In one embodiment of the present invention, M=3. For the link that needs to be purified after evaluation, it can be seen from formula (4) that after the link is purified, the fidelity of the entangled pair distributed on the link will be improved to F suc , F suc Yes F suc (f 1 ,f 2 ), for this purification link, substitute the purified fidelity F suc , from formula (1), we can see that the channel coefficient q of the link can be converted into Since q = 1-p, the new equivalent damping coefficient p' of the link can be calculated as After the above hop-by-hop purification method (Formulas (1)-(4)), the end-to-end entanglement connection is established through entanglement exchange. The establishment method is well known to those skilled in the art and will not be described again.

[0053] To more clearly illustrate the purification process of FGER_D, Figure 1 Given a diamond topology routing example, in which F th =0.80. The phase damping coefficient p of each channel is reflected on each edge, and the q value of different channels can be calculated. First, FGER_D finds the path with the highest end-to-end fidelity (thick solid line) and evaluates the fidelity hop by hop. For example, according to formula (1), p 1 =0.10, p 2 =0.08, so q 1 =0.90,q 2 =0.92, therefore, F 2 =(1+0.9 2*0.92 2 ) / 2=0.842792. 2 >F th , so the node s 1 and r 1 The formed link (s 1 ,r 1 ) does not require purification. Accordingly, F is calculated 3 <F th , then you need to 1 and r 2 The formed link (r 1 ,r 2 ) is purified, and after purification, the damping coefficient is updated (arrow). Then the purified F 3 It can be calculated as follows:

[0054]

[0055] In the formula, p 1 ,p',p 3 The values ​​of are given in the figure, and the corresponding q i The value can be expressed by the relationship 1-p i Complete the calculation.

[0056] Since F 3 The fidelity constraint F is satisfied. 3 >F th , so the node r 2 and d 1 The formed link (r 2 ,d 1 ) does not need to be purified. Note that if the relationship F 3 <F th , then the link (r 2 ,d 1 For other cases, by repeating the above process between SD pairs, a hop-by-hop multiple-attempt entanglement purification method is established, which can ensure the end-to-end fidelity of the entanglement connection.

[0057] Step 4: Evaluation method based on network throughput;

[0058] Whether it is a quantum network or a classical network, the measurement of network performance is essential. In this invention, an evaluation mechanism based on network throughput will be established. Considering the entanglement exchange success rate l and the probabilistic nature of entanglement purification, the network throughput is defined. For the throughput of the link (u, v), the expected throughput is defined as follows:

[0059]

[0060] Among them, Ne is the number of entangled pairs consumed by the purification operation, and the capacity c(u,v) is the maximum number of entangled pairs that can be generated on the quantum channel. Here, we consider the worst purification case and set N e =2M. Assuming the number of path hops is h, the expected path throughput between source node s and destination node d can be calculated as T(s,d)=min[T(u,v)]l h-1 .

[0061] The present invention uses Python simulation software to perform numerical simulation to evaluate the performance of FGER_D. The Waxman random topology model is used in the simulation, which does not assume any specific network topology. For the comparison algorithm, the existing routing protocol QCPS based on the minimum hop count algorithm is used. Since there is no purification operation in QCPS, QCPS_WP with purification operation is also used as the comparison algorithm to explore the effects of different link fidelity thresholds, entanglement exchange success rate, number of time slots, and link capacity on network throughput and average end-to-end entanglement fidelity.

[0062] In the simulation of the present invention, considering that mature quantum memory will become possible, a quantum bit can be stored for several minutes with high fidelity, which will ensure the number of attempts of purification operation. The initial phase damping coefficient of each quantum link satisfies p~N(0.15,0.02). In terms of parameter setting, the default number of network nodes is 20, and the communication radius R between drone nodes is 200m. In addition, the initial energy of the node is 60J, and a complete communication process will consume 1J of energy of the node. When the energy of the node is lower than 2J, the node will exit the network.

[0063] Firstly, under different fidelity thresholds, the performance of the proposed algorithm is compared from three aspects: network throughput, average end-to-end fidelity and average consumed entanglement pairs. As control variables, the entanglement exchange success rate is set to 0.9, the number of time slots is set to 300, and the link capacity is set to 20 in this group of simulations.

[0064] like Figure 2 As shown in (a), the throughput of all schemes decreases with the increase of the fidelity threshold. Due to the lack of purification operation, QCPS shows the worst performance and is close to failure when the fidelity threshold is 0.90. QCPS_WP and FGER_D adopt the purification method proposed in this invention to ensure their throughput performance. By selecting the path with the highest end-to-end fidelity, FGER_D consumes fewer entangled pairs compared to QCPS_WP, allowing FGER_D to establish more end-to-end entangled connections. In addition, the relatively small number of nodes in the drone quantum entanglement network used for relay weakens the impact of the "number of hops", thereby bringing higher network throughput to FGER_D. To verify the above hypothesis, Figure 2(c) provides the average number of entangled pairs consumed by QCPS_WP and FGER_D, among which FGER_D indeed shows better performance. Figure 2 (b) shows the average end-to-end fidelity of each scheme. QCPS is only effective at lower thresholds, while QCPS_WP and FGER_D provide good fidelity guarantees at various thresholds, among which FGER_D shows better performance. When the fidelity threshold is 0.85, the end-to-end fidelity of QCPS_WP exceeds that of FGER_D, which may be because FGER_D does not need to be purified at this threshold, while the fidelity of QCPS_WP is improved after purification.

[0065] When the entanglement exchange success rate of each quantum link varies in the range of 0.6 to 1, the performance of different schemes is as follows Figure 3 As shown, in this set of simulations the fidelity threshold is set to 0.8, the number of time slots is set to 300, and the link capacity is set to 20.

[0066] Figure 3 (a) and Figure 3 (b) Describes the impact of the entanglement exchange success rate on the throughput and average end-to-end fidelity in QCPS, QCPS_WP and FGER_D. From these two figures, the following conclusions can be drawn. First, the increase in the entanglement exchange success rate slightly improves the throughput of both QCPS_WP and FGER_D, and the throughput of FGER_D is better than that of QCPS_WP. Second, the throughput of QCPS is not affected by the entanglement exchange success rate. This is because when the fidelity threshold is 0.80, since there is no purification operation in QCPS, the path with more than 2 hops does not meet the threshold requirement. Therefore, the increase in the entanglement exchange success rate does not lead to an increase in throughput. Third, at different entanglement exchange success rates, both QCPS_WP and FGER_D provide good end-to-end fidelity guarantees. Although the average end-to-end fidelity of QCPS is higher than 0.80, as shown in Figure 3 As shown in (a), it can only guarantee end-to-end fidelity for part of the path.

[0067] In order to study the effect of the number of time slots on the performance of FGER_D, the results of network throughput, average end-to-end fidelity, and number of network nodes are recorded, respectively, as follows: Figure 4 As shown, the entanglement exchange success rate is set to 0.9, the fidelity threshold is set to 0.80, and the link capacity is set to 20.

[0068] From these figures, we can see that as the number of time slots increases, some drone nodes begin to exit the network. Due to the high node utilization caused by the QCPS algorithm, network nodes exit faster and more frequently. Figure 4(c) shows that the reduction in the number of nodes will also lead to a decrease in its network throughput, while FGER_D alleviates this problem to a certain extent and maintains a relatively stable throughput. In addition, the end-to-end fidelity of QCPS_WP and FGER_D remains relatively stable in different time slots, which once again highlights the superiority of the purification method proposed in the present invention.

[0069] Next, we keep the default settings and change the link capacity from 10 to 30. The simulation results are as follows Figure 5 As shown, the entanglement exchange success rate is set to 0.9, the fidelity threshold is 0.80, and the number of time slots is 300.

[0070] exist Figure 5 In (a), the throughput of QCPS_WP and FGER_D gradually increases with the increase of link capacity. This is because more link capacity allows more end-to-end entangled connections to be established, which provides an increase in throughput. Since the number of end-to-end entangled connections required by the network is set to 10, QCPS is not affected by the link capacity. Since QCPS does not need to be purified, its throughput is saturated. In addition, FGER_D, which uses end-to-end fidelity as the routing metric, still has a significant advantage in fidelity performance.

[0071] In summary, the effectiveness of the proposed method is verified through simulation experiments. From the evaluation results, FGER_D has higher throughput and average end-to-end fidelity than QCPS and QCPS_WP, and has a longer network lifetime. In addition, QCPS_WP and FGER_D with purification operations perform much better than QCPS, especially in high-fidelity threshold scenarios.

Claims

1. A fidelity-guaranteed entanglement routing method for drone quantum networks, It is characterized in that The method specifically comprises the following steps: Step 1: Establish entangled connections between adjacent quantum nodes; The quantum nodes of drones are equipped with key physical devices that generate entanglement. Before the path-finding task begins, each adjacent node uses the onboard physical devices to establish an entangled connection. Step 2: Establish a path selection method based on end-to-end fidelity; After the neighboring nodes complete the entanglement distribution, the path selection task needs to be performed for the source node-destination node pair SD in the network that needs to establish a long-distance entanglement connection; the path finding method based on the end-to-end fidelity is selected; Step 3: A hop-by-hop multiple-attempt entanglement purification method; Modeling quantum channels as phase-damped channels; Assume that the onboard entanglement source generates an For the EPR entangled state of n-hop phase damping channel, the fidelity of the entangled state established by entanglement exchange is F i for: In the formula, |φ + > 12 represents the Bell state vector, |·> is called the right vector, "+" represents superposition, "1" and "2" represent two quantum bits, |00> 12 indicates that both qubits are in the ground state |0>, |11> 12 It means that both qubits are in the excited state |1〉, the channel coefficient q=1-p, p is the phase damping coefficient, q i is the q value of the i-th phase damping channel; If the minimum fidelity threshold required for quantum applications is F th , in order to ensure that the fidelity of the established end-to-end entanglement connection is higher than F th , establish a hop-by-hop entanglement purification method; After the one-hop entanglement distribution is completed, according to formula (1), the corresponding q value of the phase damping channel is substituted and the fidelity of the next hop is calculated and evaluated in turn; since q i The value is known, according to q i It is possible to calculate all F i ; if F i <F th , i = 2,…, n, then the corresponding link (u, v) in the network needs to be purified as shown in formulas (2)-(4), where u and v represent different quantum nodes respectively; entanglement purification produces an entangled pair with higher fidelity at the expense of two entangled pairs with lower fidelity; considering the bit flip error, the fidelity F of the entangled pair after purification is pur Calculated as: In the formula, f 1 ,f 2 is the fidelity of the two Bell pairs used for purification; since entanglement purification is probabilistic, the probability of successful purification is P pur satisfy: P pur (f 1 ,f 2 )=f 1 f 2 +(1-f 1 )(1-f 2 ) (3) To ensure the success rate of the purification operation, assume that the decoherence time of the quantum memory is Γ. If a purification attempt fails, more attempts will be made within a time period of Γ. Since the probability of success of one attempt is P pur , P pur YesP pur (f 1 ,f 2 ), so the probability of success in M ​​attempts is calculated as 1-(1-P pur ) M , then considering the probabilistic nature of entanglement purification, the expected fidelity F after successful purification is suc for: Where M is the number of purification times. For the links that need to be purified after evaluation, it can be seen from formula (4) that after the link is purified, the fidelity of the entangled pairs distributed on the link will be improved to F suc , F suc Yes F suc (f 1 ,f 2 ), for this purification link, substitute the purified fidelity F suc , from formula (1), we know that the channel coefficient q of the link can be converted into Since q = 1-p, the new equivalent damping coefficient p' of the link is calculated as After the above hop-by-hop purification method, the end-to-end entanglement connection is established through entanglement exchange; Step 4: Evaluation method based on network throughput; For the throughput of link (u,v), the expected throughput is defined as follows: Among them, N e is the number of entangled pairs consumed by the purification operation, and the capacity c(u,v) is the maximum number of entangled pairs that can be generated on the quantum channel; considering the worst purification case, let N e =2M; Assuming the number of path hops is h, the expected path throughput between source node s and destination node d is calculated as T(s,d)=min[T(u,v)]l h-1 .

2. The fidelity-guaranteed drone quantum network entanglement routing method as claimed in claim 1, It is characterized in that In step 3, M=3.

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