CN116108593A

CN116108593A - Method and device for judging importance of combat network node based on quantum technology

Info

Publication number: CN116108593A
Application number: CN202111333576.6A
Authority: CN
Inventors: 安宁波; 李叶; 窦猛汉
Original assignee: Origin Quantum Computing Technology Co Ltd
Current assignee: Origin Quantum Computing Technology Co Ltd
Priority date: 2021-11-11
Filing date: 2021-11-11
Publication date: 2023-05-12

Abstract

The invention discloses an importance judging method and device of a combat network node based on quantum technology, wherein the method comprises the following steps: receiving and responding to configuration operation of the combat network model, configuring the combat network model and displaying, wherein the combat network model comprises: the nodes and the connecting edges between the nodes; and receiving and responding to the calculation operation of node importance ranking aiming at the combat network model, ranking the importance of the nodes by utilizing a quantum node importance ranking technology, and obtaining and displaying a ranking result. By utilizing the embodiment of the invention, the parallel acceleration advantage of quantum computation can be exerted, the problem that the quantum computation technology is applied to judgment of the importance of the network node in battle is solved, and the blank of the related technology is filled.

Description

Method and device for judging importance of combat network node based on quantum technology

Technical Field

The invention belongs to the technical field of quantum computing, and particularly relates to an importance judging method and device of a combat network node based on a quantum technology.

Background

The quantum computer is a kind of physical device which performs high-speed mathematical and logical operation, stores and processes quantum information according to the law of quantum mechanics. When a device processes and calculates quantum information and operates on a quantum algorithm, the device is a quantum computer. Quantum computers are a key technology under investigation because of their ability to handle mathematical problems more efficiently than ordinary computers, for example, to accelerate the time to crack RSA keys from hundreds of years to hours.

The quantum computing simulation is a simulation computation which simulates and follows the law of quantum mechanics by means of numerical computation and computer science, and is taken as a simulation program, and the high-speed computing capability of a computer is utilized to characterize the space-time evolution of the quantum state according to the basic law of quantum bits of the quantum mechanics.

In the military field, informationized warfare is the relative amount of the opposing parties in the physical domain, the information domain and the cognitive domain, and is the countermeasure of the system and the system. However, limitations of the conventional combat simulation modeling and simulation method are insufficient to describe the antagonistic nature of the informationized war system, and a corresponding quantum computing technology is not applied to the actual combat system at present so as to effectively identify the importance of the combat units in the actual combat system, which is a problem to be solved urgently.

Disclosure of Invention

The invention aims to provide an importance judging method and device for a combat network node based on a quantum technology, which are used for solving the defects in the prior art, can exert the parallel acceleration advantage of quantum computing, solve the problem that the quantum computing technology is applied to the importance judgment of the combat network node, and fill the blank of the related technology.

An embodiment of the present application provides a method for determining importance of a combat network node based on quantum technology, the method including:

receiving and responding to configuration operation of the combat network model, configuring the combat network model and displaying, wherein the combat network model comprises: the nodes and the connecting edges between the nodes;

and receiving and responding to the calculation operation of node importance ranking aiming at the combat network model, ranking the importance of the nodes by utilizing a quantum node importance ranking technology, and obtaining and displaying a ranking result.

Optionally, the configuring the combat network model includes:

determining the node type of the fight network node and the connecting edges between the nodes;

determining the number of nodes under each node type, and calculating the edge probability among the nodes;

and determining a connection mode among the fight network nodes, and configuring a fight network model of the fight system according to the node type, the node number, the connection edge probability and the connection mode.

Optionally, the node type includes: sensor nodes, decision maker nodes, affector nodes and target nodes.

Optionally, the calculating the edge probability between the nodes includes:

and calculating the ratio of the number of the actually existing connecting edges to the number of the possibly existing connecting edges between one type of nodes and the other type of nodes, and taking the ratio as the connecting edge probability between the nodes.

Optionally, the connection mode includes: random connections, tree hierarchy connections, scaleless network connections, or small world network connections.

Optionally, the ranking the importance of the nodes by using a quantum node importance ranking technique includes:

constructing a Hamiltonian amount corresponding to the combat network model;

obtaining a corresponding linear equation according to the Ha Midu quantity;

and solving the linear equation by utilizing a quantum linear solving technology to obtain a sequencing result.

Optionally, the solving the linear equation by using a quantum linear solving technology to obtain a sorting result includes:

and solving the linear equation through a quantum circuit for realizing the HIL algorithm to obtain a sequencing result.

Yet another embodiment of the present application provides an importance judging device of a combat network node based on quantum technology, the device including:

the configuration module is used for receiving and responding to the configuration operation of the combat network model, configuring and displaying the combat network model, wherein the combat network model comprises: the nodes and the connecting edges between the nodes;

and the sequencing module is used for receiving and responding to the calculation operation of node importance sequencing aiming at the combat network model, sequencing the importance of the nodes by utilizing a quantum node importance sequencing technology, and obtaining and displaying a sequencing result.

A further embodiment of the present application provides a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of the above when run.

Yet another embodiment of the present application provides an electronic device comprising a memory having a computer program stored therein and a processor configured to run the computer program to perform the method of any of the above.

Compared with the prior art, the method for judging the importance of the fight network node based on the quantum technology is used for configuring and displaying the fight network model by receiving and responding to the configuration operation of the fight network model, wherein the fight network model comprises the following steps: the nodes and the connecting edges between the nodes; and receiving and responding to the calculation operation aiming at node importance sequencing of the combat network model, sequencing the importance of the nodes by utilizing a quantum node importance sequencing technology, obtaining and displaying a sequencing result, thereby exerting the parallel acceleration advantage of quantum calculation, solving the problem that the quantum calculation technology is applied to combat network node importance judgment, and filling the blank of the related technology.

Drawings

Fig. 1 is a hardware block diagram of a computer terminal of a method for judging importance of a combat network node based on quantum technology according to an embodiment of the present invention;

fig. 2 is a flow chart of a method for judging importance of a combat network node based on quantum technology according to an embodiment of the present invention;

FIG. 3 is a schematic view of a combat loop according to an embodiment of the present invention;

fig. 4 is an abstract schematic diagram of a combat network according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a random combat network according to an embodiment of the present invention;

fig. 6 is a schematic diagram of a node network according to an embodiment of the present invention;

fig. 7 is a schematic diagram of a quantum circuit corresponding to an HHL algorithm according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of an importance judging device of a combat network node based on quantum technology according to an embodiment of the present invention.

Detailed Description

The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.

The embodiment of the invention firstly provides a method for judging the importance of a combat network node based on a quantum technology, which can be applied to electronic equipment such as a computer terminal, in particular to a common computer, a quantum computer and the like.

The following describes the operation of the computer terminal in detail by taking it as an example. Fig. 1 is a hardware block diagram of a computer terminal according to an embodiment of the present invention, which is a method for determining importance of a combat network node based on quantum technology. As shown in fig. 1, the computer terminal may include one or more (only one is shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data, and optionally, a transmission device 106 for communication functions and an input-output device 108. It will be appreciated by those skilled in the art that the configuration shown in fig. 1 is merely illustrative and is not intended to limit the configuration of the computer terminal described above. For example, the computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

The memory 104 may be used to store software programs and modules of application software, such as program instructions/modules corresponding to the method for determining importance of a network node based on quantum technology in the embodiments of the present application, and the processor 102 executes the software programs and modules stored in the memory 104, thereby performing various functional applications and data processing, that is, implementing the method described above. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, which may be connected to the computer terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission means 106 is arranged to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module for communicating with the internet wirelessly.

It should be noted that a real quantum computer is a hybrid structure, which includes two major parts: part of the computers are classical computers and are responsible for performing classical computation and control; the other part is quantum equipment, which is responsible for running quantum programs so as to realize quantum computation. The quantum program is a series of instruction sequences written by a quantum language such as the qlunes language and capable of running on a quantum computer, so that the support of quantum logic gate operation is realized, and finally, quantum computing is realized. Specifically, the quantum program is a series of instruction sequences for operating the quantum logic gate according to a certain time sequence.

In practical applications, quantum computing simulations are often required to verify quantum algorithms, quantum applications, etc., due to the development of quantum device hardware. Quantum computing simulation is a process of realizing simulated operation of a quantum program corresponding to a specific problem by means of a virtual architecture (namely a quantum virtual machine) built by resources of a common computer. In general, it is necessary to construct a quantum program corresponding to a specific problem. The quantum program, namely the program for representing the quantum bit and the evolution thereof written in the classical language, wherein the quantum bit, the quantum logic gate and the like related to quantum computation are all represented by corresponding classical codes.

Quantum circuits, which are one embodiment of quantum programs, also weigh sub-logic circuits, are the most commonly used general quantum computing models, representing circuits that operate on qubits under an abstract concept, the composition of which includes qubits, circuits (timelines), and various quantum logic gates, and finally the results often need to be read out by quantum measurement operations.

Unlike conventional circuits, which are connected by metal lines to carry voltage or current signals, in a quantum circuit, the circuit can be seen as being connected by time, i.e., the state of the qubit naturally evolves over time, as indicated by the hamiltonian operator, during which it is operated until a logic gate is encountered.

One quantum program is corresponding to one total quantum circuit, and the quantum program refers to the total quantum circuit, wherein the total number of quantum bits in the total quantum circuit is the same as the total number of quantum bits of the quantum program. It can be understood that: one quantum program may consist of a quantum circuit, a measurement operation for the quantum bits in the quantum circuit, a register to hold the measurement results, and a control flow node (jump instruction), and one quantum circuit may contain several tens to hundreds or even thousands of quantum logic gate operations. The execution process of the quantum program is a process of executing all quantum logic gates according to a certain time sequence. Note that the timing is the time sequence in which a single quantum logic gate is executed.

It should be noted that in classical computation, the most basic unit is a bit, and the most basic control mode is a logic gate, and the purpose of the control circuit can be achieved by a combination of logic gates. Similarly, the way in which the qubits are handled is a quantum logic gate. Quantum logic gates are used, which are the basis for forming quantum circuits, and include single-bit quantum logic gates, such as Hadamard gates (H gates, ada Ma Men), bery-X gates (X gates), bery-Y gates (Y gates), bery-Z gates (Z gates), RX gates, RY gates, RZ gates, and the like; two or more bit quantum logic gates, such as CNOT gates, CR gates, CZ gates, iSWAP gates, toffoli gates, and the like. Quantum logic gates are typically represented using unitary matrices, which are not only in matrix form, but also an operation and transformation. The effect of a general quantum logic gate on a quantum state is calculated by multiplying the unitary matrix by the matrix corresponding to the right vector of the quantum state.

Informationized warfare is the relative amount of the opposing parties in the physical, information and cognitive domains, and is the system-to-system countermeasure. The limitations of the traditional combat simulation modeling and simulation methods are not enough to describe the antagonistic nature of the informationized war system. As a new method for researching the informationized war system, the war system simulation experiment needs to carry out integral modeling on the war system covering the physical domain, the information domain and the cognitive domain in order to vividly simulate the characteristics of the informationized war system, so as to meet the requirements of the system countermeasure simulation.

The system is a special system, the function of the system is determined by the internal structure of the system, and the system can be characterized by a complex network. The idea of using a complex network to study the modeling problems of a war system and a system is considered as one of the important ways of simulating a real war system most probably.

Most of traditional combat network models represented by the Lanchester equation describe combat damage from an integral and average angle, do not deeply consider the relationship among all units in the combat system, and cannot well reflect system structural factors such as battlefield perception, information transmission, command control, assistance coordination and the like. Modern combat is more prominent with network-based architecture, where each party in the battlefield is a dynamic network with internal units coupled in a specific manner, and the combat actions are no longer set-based, but network-based, so that the combat actions can be more reasonably described by studying the rules of the war from the perspective of a complex network.

Referring to fig. 2, fig. 2 is a flow chart of a method for judging importance of a combat network node based on quantum technology according to an embodiment of the present invention, which may include the following steps:

s201, receiving and responding to configuration operation of a combat network model, configuring the combat network model and displaying, wherein the combat network model comprises: the nodes and the connecting edges between the nodes;

specifically, the terminal may receive and respond to a configuration operation of the user for the combat network model, configure the combat network model, and display the combat network model on the front-end interface.

In a specific implementation manner, the configuration combat network model may include:

s2011, determining node types of the combat network nodes and connecting edges among the nodes;

specifically, the node types may include: sensor nodes, decision maker nodes, affector nodes and target nodes.

In graph theory, the network is a graph g= (V, E) consisting of a set of nodes V and a set of edges E. Each edge in E has a pair of points in V corresponding to it. If any pair of points (i, j) corresponds to the same edge as (j, i), the network is called an undirected graph, otherwise, the network is called a directed graph. The construction of the network model is finally summarized into the generation and evolution rules of the nodes and the edges. In a complex network-based combat model, individual combat units are considered nodes and interactions between combat units are considered edges.

Since the war system is a typical complex system consisting of many subsystems and elements with autonomous properties, such social behavioural entities must interact with each other, and this effect manifests itself as a two-way countermeasure in the war process, cooperation and synergy inside the parties, union and alliance between the parties, etc. Therefore, to perform combat descriptive modeling, first, complex battlefields are abstracted, including abstraction of combat units and abstraction of combat processes, i.e. how to define nodes and edges in a combat network.

In order to better reflect actions such as detection, decision, striking and the like in the modern combat process, a single combat unit can be abstracted into three classes, and three classes of nodes are corresponding in a network model:

the first category is sensor node S: the subsystem representing the scout, surveillance class, which includes all entities providing spatial awareness of the battle, is responsible for accepting measurable phenomena derived from other nodes and passing to the decision maker.

The second category is decision maker node D: representing the center of command control that accepts messages from and controls the sensors or affector.

The third category is influencer node I: and the entity capable of performing soft and hard killing can be used for receiving the instruction of the decision maker to attack or interfere with the enemy target and influence the states of other nodes.

Therefore, the combat system of the combat party can be abstracted into a network formed by connecting three types of S, D, I nodes. However, in order to facilitate the problem development, an asymmetric model structure is considered herein, that is, it is assumed that one of the parties involved in the war (such as the red party) is composed of three types of nodes, and that the nodes can be coupled by a continuous edge, while the other party (the blue party) is composed of an isolated target node T, so that the whole model is represented as a war network composed of four types of S, D, I, T nodes.

Modern combat theory holds that command control is an OODA loop process of Observation (organization), positioning (organization), decision (precision), action (Action). By referring to the theory of the OODA operational loop and combining the abstraction of the operational unit, the concept of the operational loop can be built in the model, as shown in FIG. 3. The fight process is described in abstract terms as a loop in which a sensor finds a target and then transmits the target information to a decision maker, which analyzes the situation and directs the affector to perform a military operation on the target. The battle loop is a cyclical process in which after a single action is completed, the sensor re-senses the damage to the enemy target and communicates the result to the decision maker, which decides whether to proceed with the action.

The standard operational loop (Standard Operation Loop, simply SOL) depicted in fig. 3 is one of the simplest system operational networks. In modern combat, however, the links between the combat units are more intimate. The sensors can communicate with each other, and the sharing of battlefield information is shown; the decision-makers can be mutually connected, and the cooperation of command and control is reflected. The concept of a generalized operational ring (Generalized Operation Loop) can thus be extended, i.e. the process of S and D in the operational ring can be participated by members of multiple S and D.

Interactions between elements during the course of a battle can be abstracted into directed edges, which represent the links between nodes. Directed edge exposure symptom stream from T to S; the directed side from S to D is information flow; the directed edge sent from the D is a command control flow; the directed edge to T emanating from I is the attack energy flow. Thus, a directed network is formed by nodes and directed edges, which represents the network topology of the battlefield under certain parameters. Since the attack of the blue party on the red party is not considered, the network topology structure is essentially an attack network of the red party on the blue party, and the aim is to study the relationship between the network topology parameters of the red party and the attack capability of the red party. The networks described above are by way of example only and are not limiting of the invention.

Illustratively, to abstract the combat network model, the following principles and assumptions may be set:

1) No isolated S, I node exists in the initial network, namely, all the combat units at the starting moment are considered to be under control;

2) Each S or I can only be connected with one D and is a bidirectional edge, so that information between S, I and D is transferred, and meanwhile, each S or I is guaranteed not to receive commands from different D, and command conflict is prevented;

3) Each D can be connected with a plurality of S or I (bi-directionally) to represent the number of sensors and influencers controlled by each decision maker;

4) Different S can be connected (bi-directional), and different connection rates represent the sharing degree of information. When all S are connected to each other, this represents the highest level of sharing of information, which of course also means a huge communication cost. The communication rate between S is 0 under the traditional combat condition, namely S only reports the condition to the D to which the S belongs;

5) The different D can be connected (bi-directionally) to represent the organization coordination of different decision units;

6) And the S and the I can be connected with each other, and the one-way (I points to S) represents the detection, the positioning and other behaviors of the S to the I node.

From the above basic principles and assumptions, an abstract representation of a combat network is obtained, as can be seen in fig. 4.

S2012, determining the number of nodes under each node type, and calculating the edge probability among the nodes;

specifically, the edge probability between the nodes is calculated, and the ratio of the number of actually existing edges between one type of node and another type of node to the number of possibly existing edges can be calculated as the edge probability between the nodes.

The network model is established mainly according to corresponding generation parameters. The main parameters include:

1) Number of various types of nodes: the number of the S, D, I, T nodes is N respectively _T 、N _S 、N _D 、N _I 。

2) Edge probability between various nodes: edge probability P between T, S class nodes _TS Defined as the ratio of the number of edges actually present to the number of all edges that may be present between the T, S class of nodes, represents the efficiency of the discovery objective, namely:

P _TS ＝N _TS /(N _T ×N _S )

wherein N is _TS The number of edges actually existing among T, S nodes is the same as the following;

edge probability P between IT class nodes _IT The ratio of the number of actually existing edges to the number of edges possibly existing between I, T nodes is defined to represent the capability of an attack target, namely:

P _IT ＝N _IT /(N _I ×N _T )

IS class node edge probability P _IS Defined as the ratio of the number of edges actually present to the number of edges that may be present between I, S class nodes, represents the tracking sensing capability of the affector, namely:

P _IS ＝N _IS /(N _I ×N _S )

the probability of edge connection between SS class nodes is defined as the ratio of the actual number of edges between the S class nodes to the number of edges which may be large, and represents the degree of information sharing, namely:

wherein,,

represents N _S The number of possible ordered combinations of the optional two nodes, i.e. the number of combinations of ordered combinations.

Edge probability P between DD class nodes _DD The ratio of the number of the actually existing edges to the number of the possible edges among the class D nodes is defined to represent the communication degree of a command system, namely:

wherein,,

represents N _D Optionally the number of possible ordered combinations of two nodes.

It should be noted that, the class II nodes are not connected by default, the class TT nodes are not connected by default, and the class DT nodes are not connected by default; default connection between the ID class nodes and default connection between the SD class nodes.

S2013, determining a connection mode among the fight network nodes, and configuring a fight network model of the fight system according to the node type, the node number, the connection edge probability and the connection mode.

Specifically, the connection modes include, but are not limited to: random connections, tree hierarchy connections, scaleless network connections, or small world network connections.

Different network topologies have different effects on combat, so that after the edge probabilities are defined, different connection modes should be determined. Taking the connection between the decision makers D as an example, the connection may be random, may be in tree hierarchy, or may be in different forms such as a scaleless network, a small world network, etc. The problems reflected by the connection modes which are not passed are different, for example, different attack strategies can be reflected by different connection modes of the I, T nodes.

After parameters such as various nodes, edges, edge probability, connection modes and the like are determined, a combat network model can be generated. For convenience of description and application of the model, it may be assumed that various connections are performed in a random connection manner, and finally a random combat network model of random connection is obtained, which may be shown in fig. 5. In addition, for example, an array may be used to represent the connection relationship between each node in the program, where when the value of an element in the array is 0, it indicates that no edge is connected between two corresponding nodes, and conversely when the value of the element is equal to 1, an adjacency matrix of the network may be constructed, so as to facilitate analysis of the importance of the network node.

S202, receiving and responding to the calculation operation of node importance ranking aiming at the combat network model, ranking the importance of the nodes by utilizing a quantum node importance ranking technology, and obtaining and displaying a ranking result.

In a combat network, the number of combat loops is an important indicator that directly characterizes the combat capabilities of the network. The number of combat loops refers to the number of combat loops formed in the combat network, i.e. the number of shortest paths to complete one combat process. In addition, nodes with a relatively large number of combat loops passing through the nodes are often important, and direct calculation of the combat loops in the combat network is often complicated. Therefore, under the actual background of real-time combat, the node with a large number of combat loops can be approximately estimated, which is greatly beneficial to accelerating the protection of the nodes of the my combat, and the reasonable and efficient allocation of resources.

Specifically, the terminal may receive and respond to a calculation operation of node importance ranking for the combat network model by the user, rank the importance of the nodes by using a quantum node importance ranking technique, obtain a ranking result, and display the ranking result on the front end interface.

Specifically, the hamiltonian corresponding to the combat network model may be constructed; obtaining a corresponding linear equation according to the Ha Midu quantity; and solving the linear equation by utilizing a quantum linear solving technology to obtain a sequencing result. For example, the linear equation may be solved by a quantum circuit for implementing the HHL algorithm to obtain a ranking result.

In a specific implementation, to implement the network node importance ranking, first, the following indicators affecting the network node importance are defined:

1. the node degree in the weighted directed network is also called the strength of the node, and is defined as the sum of the weights of the edges connected with the node, and the strength of the directed network is divided into the outgoing strength and the incoming strength according to the different directions of the edges, namely:

wherein W is _ij 、W _ji The weights of the sides i-j and j-i are V _i ⁱⁿ V _i ^out Is the set of in-nodes and the set of out-nodes of the node i,

D _i the input intensity, the output intensity, and the total intensity (first intensity) of the node i.

2. For a weighted directed network graph G, in a local network centered on node i, there is

If the path j- > i- > k is the shortest path for the node j to reach the node k (i.e., the node j is not directly connected with the node k), the path is considered to be locally irreplaceable, and the total number of locally irreplaceable paths passing through the node i can be defined as locally irreplaceable traffic R _i ：

Wherein,,

V _j ^out for the node j's set of egress nodes, +.>

G is the ingress node set of node k _jk For calculating the intermediate parameters of the local non-alternative path, when the node j is not directly connected with the node k, if the intersection of the node j's exit node set and the node k's entry node set comprises the node i, g _jk =1, indicating that there is a locally non-alternative path through node i, otherwise, indicating that there is no.

Taking the network diagram of fig. 6 as an example, the sides between O, A, B, C, D, E, F, G, H nodes are undirected, which can be understood as bi-directional connections between nodes. For node B and node E, R can be obtained _B =6, respectively: ABC, CBA, ABE, EBA, ABD, DBA; r is R _E =6, BEH, HEB, CEG, GEC, DEF, FED respectively. If only take R as _i To judge the importance of the node i, then due to R _B ＝R _E These are known to be equally important. However, as can be seen from an analysis of FIG. 6, if point B is deleted, point A is disconnected from the rest of the nodes, whereas deleting point E does not affect the connectivity between the other nodes in the graph, mainly because of R _i Only one local index has limited information to express, so the index alone cannot effectively represent the importance of the node.

3. For a weighted directed network graph G, in a local network centered on node i, there is

If all the ingress nodes j reach all the egress nodes k, the total number of paths is +.>

Then the local uniqueness UR of node i can be defined _i ：

Continuing to take the example of figure 6 as an example,

so the importance of point B is higher than that of point E, and the result is reasonable. However, UR _A If only the local uniqueness index of the node is considered, the importance of point a is greater than that of point B, which is obviously unreasonable. At this time, R _A ＝2，R _B It is reasonable that if the local irreplaceable traffic of the node is taken as the standard, the importance of point B is higher than point a=6. Thus, from the above analysis, neither of these two metrics alone can be used to evaluate node importance. Both can show that the node is locally irreplaceable to different degrees, if only the former is considered, the local uniqueness of the node can not be shown, and if only the latter is considered, the local irreplaceable flow of the node can not be shown.

4. To balance local irreplaceable flows R _i And local uniqueness UR _i These two indices may be used in combination. For a weighted directed graph G, a first local non-replaceable value U for node i may be defined _i ：

U _i ＝R _i *UR _i

Continuing to take fig. 6 as an example, the index is validated for rationality to obtain U _A ＝2，U _B ＝3，

That is, the importance of the node A, B, E is B > a > E in turn, as determined by the first local irreplaceable value, which is reasonable as can be seen in fig. 6.

5. From the above, the node importance is determined to some extent by the respective indexes (weight W, first intensity D, local irreplaceable flow R, local uniqueness UR, first local irreplaceable value U). However, the importance between nodes is interactive, and the interactive effect can be reflected on each index, namely when the index value of the node j is larger than that of the connected node i, the node j is enhanced on the node i, and the node i is weakened on the node j. Since the network is directionally weighted, the degree of interaction between nodes and the weightsRelated to the following. The influence of the output weight and the input weight on the node is the same, the influence coefficient of the node j on the node i is the ratio of the sum of the output weight and the input weight to the total weight of the node j, the influence coefficient of the node i on the node i is the ratio of the sum of the output weight and the input weight to the total weight of the node i, and then a second local irreplaceable value of the node i after the influence of the connected node j is defined

Wherein U is _j For the first local irreplaceable value of node j, alpha represents the importance degree of the influence of the node on the connected node, and 0.ltoreq.alpha.ltoreq.1, deltaU _ji To represent intermediate parameters of node interactions (intermediate calculations involve, are not real, Δd _ji The same applies),

represented as a union of the ingress and egress nodes.

Similarly, constructing a strength interaction formula, and calculating a second strength of the node i after being influenced by the connected nodes

Wherein D is _j Is the first strength of node j.

Preferably, the second local irreplaceable value and the second intensity may be pre-processed first. Data preprocessing is generally an important preferred step in data analysis, and the preprocessed data values change, but have no effect on the importance ranking of the network nodes, as ranking is a comparison of relativity.

The second local non-alternative value may be treated as:

wherein the said

The third local irreplaceable value of the node i obtained by processing is represented, p represents the classification category number of the node, and can be set (to be distinguished from the node type of the combat network) by itself: for example, if the nodes are classified into two categories according to importance, p=2, and the importance may be classified into unimportant and important, for example, the importance of the unimportant node is set to 0, and the importance of the important node is set to 1; alternatively, the nodes are classified into four categories, eight categories, etc. according to importance, then p=4, 8 … …;

Maximum and minimum values among the second local non-replaceable values.

The second intensity may be treated as:

wherein,,

representing the third intensity of the processed node i, < ->

Maximum and minimum values in the respective second intensities.

Aiming at the weighted directed graph network, the static length M for realizing the importance ordering of the network nodes is as follows:

wherein lambda is ₁ Represents the degree of influence of the local irreplaceability of the connected nodes i and j on the importance of the node, lambda ₂ Representing the influence degree of the intensity of the connected nodes i and j on the importance of the nodes, wherein lambda is more than or equal to 0 ₁ ≤1，0≤λ ₂ ≤1，λ ₁ +λ ₂ ＝1；

Or is:

the local elastic potential energy function among the nodes is constructed by combining the weights of the edges as follows:

wherein S is _i 、S _j To quantify the importance value of node i, node j, H _ji Representing the elastic potential energy of the node j→i. The total elastic potential energy of the system is the sum of local elastic potential energy, when the total potential energy is the lowest, the system is the most stable, the importance value of the corresponding node is the optimal solution, and the total elastic potential energy, namely the Hami quantity of the whole network model system is as follows:

since the Hamiltonian volume has a convex value, the Hamiltonian volume can be manufactured by

Searching the optimal sequencing value to obtain a linear equation, wherein the process is as follows: />

Is provided with

Thereby:

namely:

since k=1, …, N, a system of linear equations is obtained:

wherein A is:

the method comprises the following steps:

according to matrix A and

outputting a quantum state S containing the importance ordering result of the network node to be ordered by utilizing a quantum circuit corresponding to the HIL algorithm, wherein A, S and +.>

Is satisfied with the linear relationship:

At present, a linear system is the core in many scientific and engineering fields, and because the HIL algorithm has an exponential acceleration effect under specific conditions compared with a classical algorithm, the HIL algorithm can be widely applied to scenes such as data processing, machine learning, numerical calculation and the like in the future. The HHL algorithm solves a problem of solving a linear equation: using an N x N hermite matrix a and an N-dimensional vector b to output N-dimensional vectors

Those skilled in the art will appreciate that an exemplary quantum circuit for implementing the HHL algorithm, as shown in fig. 7, may include: phase estimation module Phase estimation, controlled rotation module R (lambda ^-1 ) rotation, phase estimation inverse operation module inverse phase estimation. Variations or modified versions of the HHL algorithm are reasonably possible in practical applications, and the invention is not limited thereto.

Illustratively, by constructing and running the quantum circuits corresponding to the HHL algorithm, the solution satisfies the linear relationship:

the result of S in (2) is assumed to be obtained by:

S＝-0.337022|0000>+0.104781|0001>+0.666747|0010>-0.1579781|0011>-0.1579782|0100>+0.452335|0101>-0.1902991|0110>-0.1902992|0111>-0.190286|1000>+0|1001>+0|1010>+0|1011>+0|1100>+0|1101>+0|1110>+0|1111>

according to the network nodes to be ordered, the amplitude values of the network nodes to be ordered can be taken for comparison, and the amplitude values corresponding to the quantum states |1001>, |1010>, |1011>, |1100>, |1101>, |1110>, |1111> are not existed, so that the amplitude values corresponding to the quantum states need to be ignored. Comparing the quantum state amplitude values of the network nodes 0 to 8 to be sequenced to obtain: 0.666747 > 0.452335 > 0.104781 > -0.1579781 > -0.1579782 > -0.190286 > -0.1902991 > -0.1902992 > -0.337022. The importance ranking of the network nodes to be ranked is known as: node 2, node 5, node 1, node 3, node 4, node 8, node 6, node 7, node 0.

It can be seen that the combat network model is configured and displayed by receiving and responding to a configuration operation of the combat network model, wherein the combat network model comprises: the nodes and the connecting edges between the nodes; and receiving and responding to the calculation operation aiming at node importance sequencing of the combat network model, sequencing the importance of the nodes by utilizing a quantum node importance sequencing technology, obtaining and displaying a sequencing result, thereby exerting the parallel acceleration advantage of quantum calculation, solving the problem that the quantum calculation technology is applied to combat network node importance judgment, and filling the blank of the related technology.

Referring to fig. 8, fig. 8 is a schematic structural diagram of an importance judging device of a combat network node based on quantum technology according to an embodiment of the present invention, corresponding to the flow shown in fig. 2, the device includes:

a configuration module 801, configured to receive and respond to a configuration operation of a combat network model, configure the combat network model, and display the combat network model, where the combat network model includes: the nodes and the connecting edges between the nodes;

the ranking module 802 is configured to receive and respond to a calculation operation for ranking the importance of the nodes of the combat network model, rank the importance of the nodes by using a quantum node importance ranking technique, obtain a ranking result, and display the ranking result.

Specifically, the configuration module includes:

the determining unit is used for determining the node type of the combat network node and the connecting edges among the nodes;

the computing unit is used for determining the number of nodes under each node type and computing the edge probability among the nodes;

the configuration unit is used for determining the connection mode among the fight network nodes and configuring a fight network model of the fight system according to the node type, the node number, the connection edge probability and the connection mode.

Specifically, the node types include: sensor nodes, decision maker nodes, affector nodes and target nodes.

Specifically, the computing unit is specifically configured to:

Specifically, the connection mode includes: random connections, tree hierarchy connections, scaleless network connections, or small world network connections.

Specifically, the sorting module includes:

the construction unit is used for constructing the Hamiltonian quantity corresponding to the combat network model;

an obtaining unit, configured to obtain a corresponding linear equation according to the Ha Midu quantity;

and the solving unit is used for solving the linear equation by utilizing a quantum linear solving technology to obtain a sequencing result.

Specifically, the solving unit is specifically configured to:

The embodiment of the invention also provides a storage medium, in which a computer program is stored, wherein the computer program is configured to perform the steps of any of the method embodiments described above when run.

Specifically, in the present embodiment, the above-described storage medium may be configured to store a computer program for executing the steps of:

s1, receiving and responding to configuration operation of a combat network model, configuring the combat network model and displaying, wherein the combat network model comprises: the nodes and the connecting edges between the nodes;

s2, receiving and responding to the calculation operation of node importance ranking aiming at the combat network model, ranking the importance of the nodes by utilizing a quantum node importance ranking technology, and obtaining and displaying a ranking result.

Specifically, in the present embodiment, the storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.

The present invention also provides an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.

Specifically, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.

Specifically, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:

While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Claims

1. The utility model provides a method for judging importance of a combat network node based on quantum technology, which is characterized by comprising the following steps:

2. The method of claim 1, wherein the configuring the combat network model comprises:

3. The method of claim 2, wherein the node type comprises: sensor nodes, decision maker nodes, affector nodes and target nodes.

4. The method of claim 2, wherein said calculating the edge probability between the nodes comprises:

5. The method according to claim 2, wherein the connection means comprises: random connections, tree hierarchy connections, scaleless network connections, or small world network connections.

6. The method of claim 1, wherein said ranking the importance of the nodes using quantum node importance ranking techniques comprises:

constructing a Hamiltonian amount corresponding to the combat network model;

obtaining a corresponding linear equation according to the Ha Midu quantity;

7. The method of claim 6, wherein solving the linear equation using quantum linear solving techniques to obtain a ranked result comprises:

8. An importance judging device of a combat network node based on quantum technology, characterized in that the device comprises:

9. A computer terminal comprising a machine-readable storage medium having stored therein a computer program and a processor arranged to run the computer program to perform the method of any of claims 1-7.

10. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a computer, implements the method of any of claims 1-7.