CN117236452B

CN117236452B - Quantum entanglement resource scheduling method and device and electronic equipment

Info

Publication number: CN117236452B
Application number: CN202311199614.2A
Authority: CN
Inventors: 方堃
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2023-09-15
Filing date: 2023-09-15
Publication date: 2024-10-15
Anticipated expiration: 2043-09-15
Also published as: CN117236452A

Abstract

The disclosure provides a quantum entanglement resource scheduling method and device and electronic equipment, relates to the technical field of quantum computing, and particularly relates to the technical field of quantum entanglement. The specific implementation scheme is as follows: receiving a quantum application request of a quantum network; acquiring expected output state information under a quantum entanglement transformation scene of a quantum network from a quantum application request, and acquiring a target error; determining a first relation based on the output state information and the target error, wherein the first relation is a minimum optimized function relation between the optimal conversion rate of the quantum entanglement preparation scene and the dimension of the maximum entanglement state under a first preset condition, the first preset condition is that the conversion error from the maximum entanglement state to the output state information is smaller than or equal to the target error, and the conversion error is measured based on the distance between the Schmitt vectors of the quantum states under the quantum entanglement preparation scene; determining a value of optimal conversion based on the first relationship; and carrying out resource scheduling on the quantum application service based on the quantum application request and the value of the optimal conversion rate.

Description

Quantum entanglement resource scheduling method and device and electronic equipment

Technical Field

The disclosure relates to the technical field of quantum computing, in particular to the technical field of quantum entanglement, and specifically relates to a quantum entanglement resource scheduling method, a quantum entanglement resource scheduling device and electronic equipment.

Background

The quantum network may be used to perform quantum application services, for example, the quantum communication system may deploy quantum key distribution application services to enable secure information transfer using quantum entanglement states, and for example, the quantum network may deploy communication application services to effectively allocate entanglement resources to various nodes of the quantum network for communication.

Quantum entanglement is a very specific and unique phenomenon in quantum mechanics, where two or more quantum systems enter a closely related complex state. In this state, the quantum states of the individual systems cannot be defined individually, but rather need to be considered in combination with all other systems as a whole.

In order to ensure the practical effect of quantum entanglement applications, a given bell state needs to be converted into a quantum entanglement state required for the application through a certain operation, which is called quantum entanglement preparation, before actually being put into use.

When entanglement resources are scheduled for quantum application requests in a quantum network, direct scheduling is usually performed on the basis of entanglement resources obtained in a quantum entanglement preparation scene of the quantum network.

Disclosure of Invention

The disclosure provides a quantum entanglement resource scheduling method and device and electronic equipment.

According to a first aspect of the present disclosure, there is provided a quantum entanglement resource scheduling method, comprising:

receiving a quantum application request of a quantum network, wherein the quantum application request is used for scheduling entanglement resources to execute quantum application services;

Acquiring expected output state information under a quantum entanglement transformation scene of the quantum network from the quantum application request, and acquiring a target error;

Determining a first relation based on the output state information and the target error, wherein the first relation is a minimum optimized functional relation between the optimal conversion rate of the quantum entanglement preparation scene and the dimension of the maximum entanglement state under a first preset condition, the first preset condition is that the conversion error from the maximum entanglement state input under the quantum entanglement preparation scene to the output state information is smaller than or equal to the target error, and the conversion error is measured based on the distance between the Schmitt vectors of the quantum states under the quantum entanglement preparation scene;

Determining a value of the optimal conversion rate based on the first relationship;

And scheduling resources of the quantum application service based on the quantum application request and the value of the optimal conversion rate.

According to a second aspect of the present disclosure, there is provided a quantum entanglement resource scheduling device comprising:

the receiving module is used for receiving a quantum application request of the quantum network, wherein the quantum application request is used for scheduling entanglement resources to execute quantum application services;

the acquisition module is used for acquiring expected output state information under a quantum entanglement transformation scene of the quantum network from the quantum application request and acquiring a target error;

The first determining module is configured to determine a first relationship based on the output state information and the target error, where the first relationship is a minimum optimized functional relationship between an optimal conversion rate of the quantum entanglement preparation scene and a dimension of a maximum entanglement state under a first preset condition, and the first preset condition is that a conversion error from the maximum entanglement state input under the quantum entanglement preparation scene to the output state information is less than or equal to the target error, and the conversion error is measured based on a distance between schmitt vectors of the quantum states under the quantum entanglement preparation scene;

a second determining module configured to determine a value of the optimal conversion rate based on the first relationship;

And the resource scheduling module is used for scheduling the resource of the quantum application service based on the quantum application request and the value of the optimal conversion rate.

According to a third aspect of the present disclosure, there is provided an electronic device comprising:

at least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform any one of the methods of the first aspect.

According to a fourth aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform any of the methods of the first aspect.

According to a fifth aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements any of the methods of the first aspect.

According to the technology disclosed by the invention, the problem that the flexibility of the quantum network to the resource scheduling of the quantum application service is relatively poor in the related technology is solved, and the flexibility and the accuracy of the quantum network to the resource scheduling of the quantum application service can be improved.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

fig. 1 is a flow diagram of a quantum entanglement resource scheduling method according to a first embodiment of the present disclosure;

FIG. 2 is a schematic representation of quantum state copy number versus average conversion for quantum entanglement preparation;

fig. 3 is a schematic structural view of a quantum entanglement resource scheduling device according to a second embodiment of the present disclosure;

fig. 4 is a schematic block diagram of an example electronic device used to implement embodiments of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

First embodiment

As shown in fig. 1, the present disclosure provides a quantum entanglement resource scheduling method, including the steps of:

step S101: a quantum application request of a quantum network is received, the quantum application request being for scheduling entangled resources for execution of a quantum application service.

In this embodiment, the quantum entanglement resource scheduling method relates to the technical field of quantum computing, in particular to the technical field of quantum entanglement, and can be widely applied to the scheduling scene of quantum network entangled resources of quantum application service. The quantum entanglement resource scheduling method of the embodiment of the disclosure can be executed by the quantum entanglement resource scheduling device of the embodiment of the disclosure. The quantum entanglement resource scheduling device of the embodiment of the disclosure can be configured in any electronic equipment to execute the quantum entanglement resource scheduling method of the embodiment of the disclosure.

The quantum network may be a quantum key distribution network, a quantum communication network, or a network for performing quantum computation in a quantum computer, which is not particularly limited herein.

The quantum network may be functionally divided into multiple layers, which may include an upper quantum application service layer and a lower service support layer, which may receive quantum application requests sent by the upper quantum application service layer to schedule entanglement resources for execution of quantum application services.

Optionally, the quantum application service includes any one of:

quantum key distribution application services;

a communication application service;

Distributed quantum computing application services.

In one scenario, the quantum key distribution application service and the communication application service can schedule entangled resources prepared by the underlying service support layer through quantum entanglement, so as to realize safe information transmission. In another scenario, the distributed quantum computing application service may schedule entangled resources prepared by quantum entanglement by the underlying service support layer to perform complex algorithms, such as distributed quantum computing.

The quantum application request may carry a service identifier, an entangled resource number, entangled resource characteristics, and the like, and the quantum application service needs to use a quantum state indicated by the entangled resource characteristics to implement the corresponding service, where the quantum state indicated by the entangled resource characteristics needs to be prepared by a maximum entangled state.

Step S102: and acquiring expected output state information under a quantum entanglement transformation scene of the quantum network from the quantum application request, and acquiring a target error.

A common example is two entangled particles whose spin states may be indeterminate, but interrelated. Even though the two particles are far apart, their spin states remain entangled. For example, if one of the particles is measured with its spin up, then wherever the other particle is, its spin is measured, with the result being necessarily down. In particular, this correlation is independent of the physical distance of the entangled particles. This situation is beyond the understanding of classical physics because, from the point of view of classical physics, two objects that are far apart are unlikely to have such a "transient" interaction. This phenomenon can be approximated by the term "forces of evil-like superspeed". However, this is an essential feature of the quantum world and has been confirmed by a large number of experiments.

Quantum entanglement is important not only in theory but also in practical applications such as quantum computing, quantum cryptography, and quantum communication. In the field of quantum computing, quantum entanglement is considered as a key factor in achieving large-scale quantum computing. With entangled qubits, quantum computers can process a large amount of information, exceeding the processing power of classical computers.

Secondly, quantum entanglement plays a vital role in quantum cryptography, particularly in quantum key distribution protocols, a secure cryptographic key is created for both parties of communication by quantum entanglement, and any attempt to steal the key breaks the entangled state and is detected. In addition, due to the "forces of evil-like over-spacing effect" of entangled particles, changing the state of one particle can instantaneously affect another particle entangled with it, which makes long-range quantum communication and quantum clock synchronization possible, no matter how far apart the two particles are. In quantum invisible transport states, "transport" of one quantum state from one place to another can be accomplished by utilizing quantum entanglement.

The quantum entanglement can also be applied to the fields of quantum precision measurement and the like, and higher precision and sensitivity are provided compared with the traditional technology. The nature of quantum entanglement allows communication and computation beyond the limits of classical theory, opening new possibilities for technological development.

In quantum information processing, different tasks may require different types of quantum entanglement. While the maximum entanglement state (e.g., bell state) is the most entangled two-state and is useful in many applications, not all quantum information tasks require or are best suited for using the maximum entanglement state. For example, in certain quantum computing algorithms, certain entangled states may be required as initial or intermediate states of the computation. In some protocols for quantum communications, non-maximally entangled states may be required to achieve more efficient or secure information transfer. In quantum sensing and quantum metrology, a particular entangled state may provide better performance or greater precision than the maximum entangled state. While the maximum entangled state is useful in many situations, it is considered to be an important issue in quantum information processing to convert the maximum entangled state to other entangled states, which is critical for achieving a broader and more efficient quantum information task.

To ensure the practical effect of quantum entanglement applications, a given quantum entanglement (usually an ideal bell state) needs to be converted into the quantum entanglement required for the application by a certain operation, which is called quantum entanglement preparation, before it is actually put into use.

In step S102, the output state information refers to a quantum state expected to be output in the quantum entanglement preparation process, that is, a quantum state to be prepared, where the quantum state is obtained by tensor product on the basis of n target quantum states, the target quantum states are quantum states on two quantum systems, the dimensions of the two quantum systems may be the same, the dimension of one quantum system may be d, and n is the copy number of the output state information. For the quantum state |ψ > _AB on any AB quantum system, the output state information can be expressed as

Ideally, the quantum states obtained by quantum entanglement of bell states are required to be the same as those expected to be output, and since the conversion requirements are often too strict, the conversion rate (or cost) is very high, so that in practical applications, it is often required that the error between the quantum states obtained by quantum entanglement of bell states and those expected to be output meet a given error threshold. The error threshold is a target error, and when the conversion error from the bell state input by quantum entanglement preparation to the quantum state expected to be output is smaller than or equal to the target error, that is, the error between the quantum state obtained by quantum entanglement preparation through the bell state and the quantum state expected to be output is smaller than or equal to the error threshold, the error between the quantum state obtained by quantum entanglement preparation through the bell state and the quantum state expected to be output meets the error threshold.

Under the condition that the quantum application request is acquired, the expected output state information under the quantum entanglement transformation scene of the quantum network can be acquired from the quantum application request based on entanglement resource characteristics and entanglement resource quantity carried by the quantum application request. When the desired output state information is not the maximum entangled state, the quantum network may start a quantum entanglement preparation scenario to prepare entangled resources, so as to obtain entangled resources required to be used by the quantum application service.

The target error can be preset, the quantum application request can carry the target error, and the target error can be obtained from the quantum application request correspondingly.

Step S103: based on the output state information and the target error, determining a first relation, wherein the first relation is a minimum optimized functional relation of the optimal conversion rate of the quantum entanglement preparation scene and the dimension of the maximum entanglement state under a first preset condition, the first preset condition is that the conversion error from the maximum entanglement state input under the quantum entanglement preparation scene to the output state information is smaller than or equal to the target error, and the conversion error is measured based on the distance between the Schmitt vectors of the quantum states under the quantum entanglement preparation scene.

The basic idea of quantum entanglement preparation is to convert one or more pairs of bell states into a specified quantum entanglement state through a series of Local Operations and Classical Communication (LOCC), the less the initial bell state it is desired to consume for conversion, the better and the difference between the converted quantum state and the specified quantum state is guaranteed to be less than a given error threshold epsilon. If m pairs of bell states can be converted into n pairs of designated quantum entanglement states by a certain LOCC operating scheme, then the entanglement preparation conversion rate (or cost) of the scheme is m/n, i.e. m/n pairs of bell states need to be consumed per preparation of a pair of designated quantum entanglement states on average.

For example, if it is desired to convert 5 pairs of the initial bell state to 10 pairs of the designated quantum entanglement state, then the conversion rate of this entanglement preparation process can be said to be 5/10 or 0.5. Thus, the lower the conversion (or cost), the higher the efficiency of the entanglement preparation process, the less bell state is consumed.

The quantum entanglement preparation conversion rate is used as a key parameter for measuring entanglement preparation protocol efficiency, and the calculation of the quantum entanglement preparation conversion rate has a vital meaning. First, because the quantum resources (e.g., initial quantum entanglement states) available in actual quantum information handling systems are often limited, understanding and calculation of entanglement preparation conversions can help to more effectively manage these resources for optimal system performance.

Second, comparing the conversion rates of different entanglement preparation protocols may guide the selection of the most efficient protocol under specific conditions, or optimize the existing protocol to increase its efficiency. Furthermore, since entanglement is susceptible to errors and noise, entanglement preparation as a means of reducing these effects, its conversion rate can reflect the effect of the preparation, indicating whether further error correction is required.

And, the optimal conversion rate of entanglement preparation can be used as a benchmark for measuring the performance of the quantum information processing system. Comparing the theoretically expected conversion with the actual measured conversion, it is possible to evaluate whether the system performance is expected or whether potential room for improvement is revealed. The optimal conversion rate can be calculated, and the corresponding optimal entanglement preparation protocol can be found, so that the efficiency of quantum entanglement preparation operation is maximized, and the quantum entanglement preparation method has very important practical value.

In specific product requirements and application scenes, the application of calculating the conversion rate of quantum entanglement preparation is particularly important.

1. In designing and constructing quantum computers, high quality entangled states need to be generated and manipulated to perform complex quantum algorithms. In this process, quantum entanglement preparation conversion rate provides an important efficiency index. For example, if the conversion (or cost) of a certain entanglement preparation protocol is found to be high, it may be necessary to find a more efficient protocol or to retrofit existing entanglement generation and preparation techniques. Furthermore, comparing the theoretical expected and actually measured conversions can help to evaluate the actual performance of the quantum computer and to determine the technical problems that may exist.

2. In quantum communication systems, such as quantum key distribution protocols, entangled states are often used to enable secure information transfer. However, loss and noise during transmission may reduce the quality of the entangled state, resulting in reduced security of information transmission. In this case, entanglement preparation is very important. By calculating the conversion rate, it is possible to know how much original entanglement resources are needed to guarantee a secure information transmission under given system conditions.

3. In building a quantum network, entangled resources need to be efficiently allocated to the various nodes of the network. Knowing the conversion of entanglement preparation, these resources can be better planned and managed, for example, to determine which nodes need more entanglement resources, or how to adjust the topology of the network to optimize resource utilization.

In summary, calculating the conversion rate of quantum entanglement preparation plays a key role in various quantum information products and applications, and has important significance in promoting the progress of quantum information technology. Since different schemes have different quantum entanglement preparation conversions, how to find schemes with optimal conversions and calculate corresponding optimal conversions is a widely focused issue in the industry.

The objective of this embodiment is to determine the optimal conversion rate of quantum entanglement preparation by performing quantum entanglement preparation under any given finite resource quantum entanglement state and error threshold, and perform resource scheduling on the quantum application service based on the quantum application request and the value of the optimal conversion rate. Thus, entangled resources which can be obtained by quantum entanglement preparation can be simulated through the value of the optimal conversion rate, and the flexibility and accuracy of the quantum network for resource scheduling of quantum application services are correspondingly improved. Furthermore, the optimal conversion rate can also be used for optimizing the conversion efficiency in the quantum entanglement preparation process and scheduling entanglement resources in the quantum entanglement preparation process.

In step S103, there are various conversion error modes for defining quantum states, and different error defining modes are applicable to different usage scenarios, and the corresponding calculation difficulties are also completely different. The conversion error can be understood as limiting the quantum state input by the quantum entanglement preparation to be a pure state (namely, a maximum entangled state), and carrying out quantum entanglement preparation through the maximum entangled state to obtain a quantum state, wherein the error between the quantum state and the output state information expected by the quantum entanglement preparation is smaller than or equal to the target error.

Under the definition of the conversion error described above, the optimal conversion rate of the quantum entanglement preparation is represented as the following formula (1).

The above formula (1) is the first relationship determined,For a first preset condition, epsilon is the target error,In order to convert the error of the signal,The minimum dimension of the quantum states required for quantum entanglement preparation can be equivalent to the optimal conversion, which can be determined byCalculated, n is the copy number of the output state information, m is more than or equal to 2, and m is a positive integer,The maximum entanglement between quantum systems A and B is equivalent to log ₂ m for Bell states, i.e. m is the dimension of the quantum states input by quantum entanglement preparation.

Conversion errors can be measured by the distance between schmitt vectors of quantum states in a quantum entanglement preparation scenario. Optionally, the conversion error is measured based on a trace norm of the schmitt vector of the quantum state in the quantum entanglement preparation scene, which may be a 1-norm of the schmitt vector of the quantum state in the quantum entanglement preparation scene, and the multiple may be any multiple, for example, the conversion error may be 1/2 of the 1-norm of the schmitt vector of the quantum state in the quantum entanglement preparation scene.

Alternatively, the conversion error is expressed as:

Wherein T (|beta > -lambda >) is the conversion error, |beta > is the maximum entangled state, |lambda > is the desired output state information in the quantum entangled preparation scene, p _λ is the Schmitt vector of the output state information |lambda >, p _β is the Schmitt vector of the maximum entangled state |beta >, r is the Schmitt vector of the quantum state output in the quantum entangled preparation scene, prob (d) represents the set of probability distribution vectors with all dimensions d, and d is the quantum system dimension of the output state information.

I.e.The 1/2 of the 1-norm of the schmitt vector of the quantum state in the quantum entanglement preparation scenario can be represented by the following formula (2).

The value of |x| ₁ is the 1-norm of the vector x, and beta, i.e., |phi _m >, can be the maximum entanglement between quantum systems A and B, lambda, i.eThe desired output state information in the context of quantum entanglement can be prepared for the quantum states, which can be the quantum states of quantum systems a and B.

It should be noted that, for the quantum state |ψ > _AB under one copy on any of the quantum systems a and B, there is a schmitt decompositionWherein |i > _A,|i>_B is the basis vector on the quantum systems A and B, respectively, d is the dimension of the quantum system A, the system dimensions of the quantum systems A and B are the same, and p _i is arranged in descending order (p ₁≥p₂≥...≥p_d). P _ψ＝(p₁,p₂,...,p_d) is the schmitt vector for the quantum state |ψ > _AB.

For any vector p, note p _(K) is the sum of the first K largest elements of vector p, i.eFor any two vectors of length d, the notation r > p _β denotes that for any K e {1,2,.. D }, the sum of the first K largest elements of vector r is greater than or equal to the sum of the first K largest elements of vector p _β. Wherein r > p _β is the condition required to be satisfied by the optimization function in the above formula (2)Is an optimization function.

Step S104: based on the first relationship, a value of the optimal conversion is determined.

Wherein the value of the optimal conversion rate is used for optimizing the conversion efficiency in the quantum entanglement preparation process or scheduling entanglement resources in the quantum entanglement preparation process.

Under the condition of providing expected output state information and target errors in a quantum entanglement preparation scene, the dimension of a quantum state input by quantum entanglement preparation can be solved under a first preset condition through related calculation software, so that the value of an optimization function in a first relation is at a minimum value, and the minimum value is the value of the optimal conversion rate of the quantum entanglement preparation.

On the premise of obtaining the value of the optimal conversion rate of the quantum entanglement preparation, related applications such as quantum key distribution protocol application, quantum network construction application, debugging application of a quantum entanglement preparation algorithm, distributed quantum computing application and the like can be carried out based on the value of the optimal conversion rate, and in the applications, the conversion efficiency in the quantum entanglement preparation process can be optimized based on the optimal conversion rate, and entanglement resources in the quantum entanglement preparation process can be scheduled.

Step S105: and scheduling resources of the quantum application service based on the quantum application request and the value of the optimal conversion rate.

The most amount of output state information is expected, and the more the cost required for quantum entanglement preparation, namely the maximum entanglement state amount, is required to be, so that more entanglement resources are prepared and generated for scheduling. However, the cost of quantum entanglement preparation is related to the noise environment and hardware equipment of the nodes in the quantum network, and the maximum entanglement acquired by the nodes in the quantum network is typically limited under the limitations of the corresponding noise environment and hardware equipment. Nodes may refer to quantum devices, or may refer to modules in a quantum computer, and are not specifically limited herein.

The maximum number of entanglement resources which can be prepared under the corresponding cost of quantum entanglement preparation can be simulated based on the value of the optimal conversion rate, the quantum application request also carries the quantity of entanglement resources which need to be scheduled, and when the maximum number of entanglement resources which can be prepared is larger than or equal to the quantity of entanglement resources in the quantum application request, quantum entanglement preparation operation can be executed in response to the quantum application request, entanglement resources can be correspondingly prepared, and quantum application services can be scheduled to an upper layer.

In the case where the maximum number of entanglement resources available for preparation is smaller than the number of entanglement resources in the quantum application request, the quantum entanglement preparation operation may be not performed, but the response to the quantum application request may be directly denied.

In this embodiment, a quantum application request of a quantum network is received; based on a quantum application request, triggering nodes in the quantum network to acquire expected output state information and target errors in a quantum entanglement preparation scene; based on the output state information and the target error, constructing an optimization function to determine the optimal conversion rate of the quantum entanglement preparation scene; and then, carrying out resource scheduling on the quantum application service based on the quantum application request and the value of the optimal conversion rate. Therefore, the entanglement resources available in the quantum entanglement preparation can be simulated through the value of the optimal conversion rate, and the flexibility and the accuracy of the quantum network on resource scheduling of the quantum application service are correspondingly improved.

And the conversion error from the maximum entangled state to the output state information is measured based on the distance between the Schmitt vectors of the quantum states in the quantum entangled preparation scene, a minimum optimization function relation between the optimal conversion rate of the quantum entangled preparation and the dimension of the maximum entangled state of the quantum entangled preparation input under a first preset condition is constructed based on the output state information and the target error of the quantum entangled preparation, and then the value of the optimal conversion rate of the quantum entangled preparation is obtained by solving the minimum optimization function relation. The method is applicable to determination of the optimal conversion rate of quantum entanglement preparation under the conditions of any given limited resource quantum entanglement state and error threshold, so that the flexibility of determination of the optimal conversion rate of quantum entanglement preparation can be improved, the requirements of practical application scenes are met, and further the conversion efficiency in the quantum entanglement preparation process and entanglement resources in the quantum entanglement preparation process can be optimized more accurately.

Optionally, the step S105 specifically includes:

determining entanglement resources which can be prepared in a quantum entanglement preparation scene of the quantum network based on the value of the optimal conversion rate;

and carrying out resource scheduling on the quantum application service under the condition that the available entangled resource is larger than or equal to the entangled resource requested by the quantum application request.

The entanglement resources which can be prepared in the quantum entanglement preparation scene of the quantum network can be determined based on the value of the optimal conversion rate and the cost of quantum entanglement preparation. And then comparing the entanglement resources which are determined based on the value of the optimal conversion rate and can be prepared with entanglement resources requested by the quantum application request, and carrying out resource scheduling on the quantum application service based on the comparison result.

In the case where the available entanglement resources determined based on the value of the optimal conversion rate are greater than or equal to those requested by the quantum application request, at this time, there are enough entanglement resources for scheduling, and thus, the corresponding entanglement resources can be scheduled to an upper layer for the quantum application service.

In this way, resource scheduling for quantum application services can be achieved based on the value of optimal conversion.

Optionally, the method further comprises:

And refusing to respond to the quantum application request under the condition that the available entanglement resources are smaller than entanglement resources requested by the quantum application request.

Thus, by simulating the entanglement resources available for quantum entanglement preparation based on the value of the optimal conversion rate, the quantum entanglement preparation operation is not required in the case that the entanglement resources are smaller than those requested by the quantum application request, and the response to the quantum application request can be directly refused, so that unnecessary operations are reduced.

Optionally, the method further comprises:

and under the condition that the available entanglement resources are smaller than entanglement resources requested by the quantum application request, adjusting the maximum entanglement state input in a quantum entanglement preparation scene of the quantum network based on the value of the optimal conversion rate so as to improve the available entanglement resources in the quantum entanglement preparation scene.

Under the condition that the available entanglement resources are smaller than entanglement resources requested by quantum application requests, the least cost required by quantum entanglement preparation can be determined based on the value of the optimal conversion rate and the quantity of entanglement resources in the quantum application requests, so that safe information transmission is ensured. The cost of the quantum network in the quantum entanglement preparation scene is adjusted, for example, the cost of the quantum network in the quantum entanglement preparation scene is increased, so that quantum entanglement preparation is carried out, more entanglement resources can be obtained for resource scheduling, and the flexibility and accuracy of quantum entanglement resource scheduling can be further improved.

In the above formula (1), the quantum stateIs |AB| ⁿ, and as n exponentially increases, directly solving the calculationThe complexity of (c) also increases exponentially with n, so the complexity of solving the optimal conversion can be reduced by converting the first relationship.

Optionally, the step S104 specifically includes:

Performing schmitt decomposition on the output state information to convert the first relation into a second relation and a third relation, wherein the second relation is a relation between the optimal conversion rate and a first variable, the third relation is a minimum optimized functional relation between the first variable and the dimension of the maximum entangled state under a second preset condition, the second preset condition is that a first target norm of a schmitt vector of the output state information is greater than or equal to a first target value, the first target value is obtained by subtracting the target error from 1, the first target norm is a sum of the first m maximum elements of the schmitt vector of the output state information, m is a dimension of the maximum entangled state input by the quantum entangled preparation scene, and m is an integer greater than or equal to 2;

Determining a value of the first variable based on the third relationship;

A value of the optimal conversion is determined based on the second relationship and the value of the first variable.

In this embodiment, the output state information in the above formula (1) may be subjected to schmitt decomposition to convert the first relationship into a second relationship and a third relationship, that is, the above formula (1) is converted into the second relationship and the third relationship, the second relationship may be represented by the following formula (3), and the third relationship may be represented by the following formula (4).

Wherein, in the above formulas (3) and (4),As a first variable which is to be taken as a first,Schmitt vector for outputting state informationIs selected from the group consisting of a first target norm,Is a second preset condition.

As can be seen from the above formulas (3) and (4), for calculationCan be calculated firstThen solving the minimum optimization function in the third relation under the second preset condition to obtain a first variableSubstituting the value of the first variable into the second relation to obtainSo that an optimal conversion rate of the quantum entanglement preparation can be obtained.

In this way, by converting the first relationship into the second relationship and the third relationship to determine the optimal conversion rate, the complexity of solving the optimal conversion rate can be reduced.

Optionally, the determining the value of the first variable based on the third relationship includes:

acquiring a Schmitt vector of the output state information;

Sequentially acquiring a first target norm of the Schmitt vector of the output state information according to the order from m to m; and outputting the value of the first variable under the condition that the first target norm of the Schmitt vector of the output state information is larger than or equal to 1 minus the target error.

The output state information may be obtained in various ways, for example, by performing schmitt decomposition on the output state information, the schmitt vector of the output state information may be obtained. For another example, the schmitt decomposition is performed on the first quantum state in one copy of the output state information to obtain a schmitt vector of the first quantum state, and the schmitt vector of the output state information is determined based on the schmitt vector of the first quantum state by using the symmetry of the quantum state indicated by the output state information and the schmitt vector of the output state information.

Under the condition that the Schmitt vectors of the output state information are acquired, sequentially acquiring first target norms of the Schmitt vectors of the output state information according to the order from m to m; and under the condition that the first target norm is obtained, judging whether the first target norm is larger than or equal to 1 minus the target error, namely judging whether a second preset condition is met, and if so, outputting the value of the first variable.

Therefore, the solution of the optimization function in the third relation can be realized, the value of the first variable is obtained, and the second relation is further solved, so that the value of the optimal conversion rate of quantum entanglement preparation is obtained.

In the determination of the schmitt vector of the output state information, due to the quantum stateIs larger in dimension and directly calculates quantum state correspondingly with the increase of n indexThe schmitt vector of the output state information is determined based on the schmitt vector of the first quantum state in one copy of the output state information by utilizing the symmetry of the quantum state indicated by the output state information and the schmitt vector of the output state information, so that the complexity in the schmitt vector determination process of the output state information is reduced.

Optionally, the obtaining the schmitt vector of the output state information includes:

acquiring a Schmitt vector of a first quantum state under one copy in the output state information;

Based on the quantum system dimension of the output state information, carrying out distribution processing on the copy number of the output state information to obtain W pieces of distribution information, wherein one piece of distribution information comprises a distribution result and the repetition number of the distribution result;

Based on the W pieces of allocation information, performing polynomial combination on first elements in the Schmitt vectors of the first quantum states to obtain W pieces of second elements corresponding to W pieces of allocation results one by one and the repetition times of each second element, wherein the repetition times of the second elements are the repetition times of the allocation results corresponding to the second elements;

arranging the W second elements in descending order to obtain a target vector;

the schmitt vector of the output state information is obtained by arranging the target vector according to the repetition times of each second element.

Therefore, the Schmitt vector of the output state information can be efficiently determined based on the target vector and the repetition times of the second element in the target vector by utilizing the symmetry of the output state information, so that the first target norm of the Schmitt vector of the output state information can be efficiently calculated, and the solving complexity of the optimal conversion rate is reduced.

Optionally, sequentially acquiring the first target norms of the schmitt vectors of the output state information according to the order from m to m; outputting a value of the first variable if a first target norm of the schmitt vector of the output state information is greater than or equal to 1 minus the target error, comprising:

Sequentially determining a second label of an element corresponding to the first label in a schmitt vector of the output state information and a first addition of a third element in the schmitt vector of the output state information according to the sequence from small to large of a first label of the second element in the target vector, based on the repetition times of the second element, wherein the third element comprises the element corresponding to the second label and an element positioned before the element corresponding to the second label;

Outputting a value of the first variable if the first sum is greater than or equal to 1 minus the target error;

wherein the first variable has a value of 2 and N is the second index, P is the first sum, s _i is the second element corresponding to the first index i in the target vector, and epsilon is the target error.

The specific process of efficiently calculating the schmitt vector of the output state information and efficiently solving the value of the first variable is as follows:

input: schmitt vector p _ψ＝(p₁,p₂,...,p_d of the first quantum state), positive integer n is not less than 1, target error epsilon [0,1];

And (3) outputting:

Step 1: and carrying out distribution processing on the copy number of the output state information based on the quantum system dimension of the output state information. Specifically, consider that n ₁+n₂+...+n_d =n and the integer n _i is equal to or greater than 0, then the corresponding n ₁,n₂,...,n_d values share Seed, and each case corresponds to a repetition number

Step 2: based on the W distribution information, performing polynomial combination on the first element in the Schmitt vector of the first quantum state to calculateA different polynomialObtaining W second elements corresponding to W distribution results one by one and the repetition times of each second element;

Step 3: arranging the W second elements according to a descending order to obtain a target vector (s ₁,s₂,...,s_W), recording the repetition number corresponding to the second elements s _i as v _i, and arranging the schmitt vector of the output state information according to the repetition number of each second element by the target vector, so that the schmitt vector of the output state information can be determined based on the schmitt vector of the first quantum state in one copy of the output state information by utilizing the quantum state indicated by the output state information and the symmetry of the schmitt vector thereof;

Step 4: let n=0, p=0, where N and P are intermediate variables for recording a first addition of a first index of a second element in the target vector, a second index of a corresponding element in the schmitt vector of the output state information, and a third element in the schmitt vector of the output state information in a cycle from small to large. The second label refers to the maximum label of the element corresponding to the first label in the schmitt vector of the output state information, if the first label is 1, and the repetition number of the second element corresponding to the first label 1 is 10, the element corresponding to the first label in the schmitt vector of the output state information is the element with the labels 1 to 10, the maximum label is 10, the second label is 10, and the first summation is the summation of the elements with the labels 1 to 10 in the schmitt vector of the output state information;

step 5: for each i e {1,2,., W } loops:

step 5.1: let n=n+v _i,P＝P+v_is_i;

Step 5.2: if 1- ε is less than or equal to P, return As an output, whereA top rounding function (i.e., a minimum integer not less than x); otherwise, the loop is continued.

The output is the first variableCorresponding to the value of (2) and can outputIs that

In the step 5, W cycles are needed at most, that is, W is a polynomial degree about n, so that the solution of the minimum optimization function in the third relationship can be performed under the second preset condition with high efficiency, to obtain the value of the first variable, and to obtain the value of the optimal conversion rate of the quantum entanglement preparation.

If the memory space of the new polynomial is allowed, the loop degree can be reduced to a logarithmic number with respect to n by a dichotomy search. Optionally, sequentially acquiring the first target norms of the schmitt vectors of the output state information according to the order from m to m; outputting a value of the first variable if a first target norm of the schmitt vector of the output state information is greater than or equal to 1 minus the target error, comprising:

Determining W second sums corresponding to the W first marks one by one based on W first marks of the W second elements in the target vector and the repetition times of the second elements in the target vector, wherein the second sums are sums of fourth elements in the Schmitt vector of the output state information, and the fourth elements comprise elements corresponding to the first marks and elements before the elements corresponding to the first marks;

Performing dichotomy search on the first target value, and outputting the value of the first variable under the condition that the first target value is located in a target interval by searching;

Wherein the target interval is an interval of (P _c,P_c+1), and the value of the first variable is 2 and C is a binary value in the binary search, s _c+1 is a second element corresponding to the first index c+1 in the target vector, N _c+1 is a second index of an element corresponding to the first index c+1 in the schmitt vector of the output state information, P _c is a second addition corresponding to the first index c, and P _c+1 is a second addition corresponding to the first index c+1.

Optionally, in the binary search, when the first target value is less than or equal to a second sum corresponding to the first index c, an upper bound of a binary search interval is adjusted to be a binary value in the binary search, and when the first target value is greater than a second sum corresponding to the first index c+1, a lower bound of the binary search interval is adjusted to be a second target value, where the second target value is a binary value added by 1 in the binary search.

The specific process of searching the schmitt vector for efficiently calculating the output state information by adopting the dichotomy and efficiently solving the value of the first variable is as follows:

And (3) outputting:

Step 4: let N ₀＝0,P₀ =0, where N ₀ and P ₀ are intermediate variables for recording the second label of the element corresponding to the first label in the schmitt vector of the output state information and the second sum of the fourth element in the schmitt vector of the output state information in the cycle from small to large of the first label of the second element in the target vector. Wherein the second label refers to the maximum label of the element corresponding to the first label in the schmitt vector of the output state information, and the fourth element comprises the element corresponding to the first label and the element before the element corresponding to the first label in the schmitt vector of the output state information;

step 5: for any j e {1,2,., W }, calculate the second label And a second addition

Step 6: let the lower bound a=0 and the upper bound b=w of the dichotomy search;

Step 7: the following loop is performed until the output is returned:

Step 7.1: let two-component Wherein the method comprises the steps ofA lower rounding function;

Step 7.2: if P _c＜1-ε≤P_c+1, return As an output, the output is the value of the first variable;

step 7.3: let b=c if 1- ε is less than or equal to P _c;

step 7.4: let a=c+1 if 1- ε > P _c+1.

Accordingly, it can outputIs that

The determination scheme of the optimal conversion rate of quantum entanglement preparation of the embodiment can be suitable for the situation of any given limited resource quantum entanglement state and any given error threshold value, and meets the requirements of practical application scenes. In particular, the computational complexity involved grows polynomial with the number of copies of the quantum states that need to be prepared, which is very efficient in practical use scenarios. In addition, when the error threshold is taken to be zero or the number of copies of the quantum state to be prepared is taken to be large enough, the determination of the optimal conversion rate of quantum entanglement preparation under ideal conditions can also be covered. Therefore, the use scene is greatly expanded while ensuring high-efficiency calculation, and the method meets the actual application requirements better.

The actual effects of the present embodiment are shown below with a specific example. Consider the quantum state that needs to be preparedThe schmitt vector is p _ψ = (0.9, 0.1), the error threshold epsilon=0.1, and the quantum state copy number n takes a value of 1 to 1000.

FIG. 2 is a graph showing the relationship between the quantum state copy number and the average conversion rate of the quantum entanglement preparation, as shown in FIG. 2, the horizontal axis represents the quantum state copy number, and the vertical axis represents the average conversion rate, namelyThe horizontal line 201 represents the progressive value of the curve 202 as n approaches infinity, which can be given by shannon entropy of the p vector, obtained using a 16G memory and a normal notebook operation of the Intel Core i7 TH GEN processor, with a practical calculation time of approximately 10 seconds. In contrast, directly solving the optimal conversion rate for quantum entanglement preparation based on equation (1) above requires computing and storing vectors of length 2 ¹⁰⁰⁰, far beyond the computational power of existing supercomputers. Therefore, an efficient calculation mode of the optimal conversion rate of the quantum entanglement preparation has important practical value.

Second embodiment

As shown in fig. 3, the present disclosure provides a quantum entanglement resource scheduling device 300, comprising:

A receiving module 301, configured to receive a quantum application request of a quantum network, where the quantum application request is used to schedule entangled resources to execute a quantum application service;

The obtaining module 302 is configured to obtain, from the quantum application request, desired output state information in a quantum entanglement transformation scenario of the quantum network, and obtain a target error;

A first determining module 303, configured to determine a first relationship based on the output state information and the target error, where the first relationship is a minimum optimized functional relationship between an optimal conversion rate of the quantum entanglement preparation scenario and a dimension of a maximum entanglement state under a first preset condition, and the first preset condition is that a conversion error from the maximum entanglement state input under the quantum entanglement preparation scenario to the output state information is less than or equal to the target error, and the conversion error is measured based on a distance between schmitt vectors of the quantum states under the quantum entanglement preparation scenario;

a second determining module 304, configured to determine a value of the optimal conversion rate based on the first relationship;

And a resource scheduling module 305, configured to perform resource scheduling on the quantum application service based on the quantum application request and the value of the optimal conversion rate.

Optionally, the resource scheduling module 305 is specifically configured to:

Optionally, the apparatus further includes:

and the refusal response module is used for refusing to respond to the quantum application request under the condition that the available entanglement resource is smaller than the entanglement resource requested by the quantum application request.

Optionally, the apparatus further includes:

And the adjusting module is used for adjusting the maximum entanglement state input in the quantum entanglement preparation scene of the quantum network based on the value of the optimal conversion rate under the condition that the entanglement resources which can be prepared are smaller than entanglement resources requested by the quantum application request so as to improve the entanglement resources which can be prepared in the quantum entanglement preparation scene.

Optionally, the quantum application service includes any one of the following:

quantum key distribution application services;

a communication application service;

Distributed quantum computing application services.

Optionally, the second determining module 304 includes:

The conversion sub-module is used for performing schmitt decomposition on the output state information to convert the first relation into a second relation and a third relation, wherein the second relation is a relation between the optimal conversion rate and a first variable, the third relation is a minimum optimized function relation between the first variable and the dimension of the maximum entangled state under a second preset condition, the second preset condition is that a first target norm of a schmitt vector of the output state information is greater than or equal to a first target value, the first target value is 1 minus the target error, the first target norm is a sum of the first m maximum elements of the schmitt vector of the output state information, m is a dimension of the maximum entangled state input by the quantum entangled preparation scene, and m is an integer greater than or equal to 2;

a first determination submodule for determining a value of the first variable based on the third relation;

A second determination submodule for determining a value of the optimal conversion based on the second relation and the value of the first variable.

Optionally, the first determining submodule includes:

An obtaining unit, configured to obtain a schmitt vector of the output state information;

The output unit is used for sequentially acquiring first target norms of the Schmidt vectors of the output state information according to the order from m to m; and outputting the value of the first variable under the condition that the first target norm of the Schmitt vector of the output state information is larger than or equal to 1 minus the target error.

Optionally, the acquiring unit is specifically configured to:

arranging the W second elements in descending order to obtain a target vector;

Optionally, the output unit is specifically configured to:

Optionally, in the binary search, when the first target value is less than or equal to a second sum corresponding to the first index, an upper bound of a binary search interval is adjusted to be a binary value in the binary search, and when the first target value is greater than the second sum corresponding to the first index, a lower bound of the binary search interval is adjusted to be a second target value, where the second target value is a binary value added by 1 in the binary search.

Optionally, the conversion error is measured based on a trace norm of a schmitt vector of quantum states in the quantum entanglement preparation scenario.

Alternatively, the conversion error is expressed as:

The quantum entanglement resource scheduling device 300 provided by the present disclosure can realize each process realized by the quantum entanglement resource scheduling method embodiment, and can achieve the same beneficial effects, and for avoiding repetition, a detailed description is omitted here.

In the technical scheme of the disclosure, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the personal information of the user accord with the regulations of related laws and regulations, and the public order colloquial is not violated.

According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

FIG. 4 illustrates a schematic block diagram of an example electronic device that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 4, the apparatus 400 includes a computing unit 401 that can perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM) 402 or a computer program loaded from a storage unit 408 into a Random Access Memory (RAM) 403. In RAM 403, various programs and data required for the operation of device 400 may also be stored. The computing unit 401, ROM 402, and RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.

Various components in device 400 are connected to I/O interface 405, including: an input unit 406 such as a keyboard, a mouse, etc.; an output unit 407 such as various types of displays, speakers, and the like; a storage unit 408, such as a magnetic disk, optical disk, etc.; and a communication unit 409 such as a network card, modem, wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The computing unit 401 may be a variety of general purpose and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 401 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the quantum entanglement resource scheduling method. For example, in some embodiments, the quantum entanglement resource scheduling method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 400 via the ROM 402 and/or the communication unit 409. When the computer program is loaded into RAM 403 and executed by computing unit 401, one or more steps of the quantum entanglement resource scheduling method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the quantum entanglement resource scheduling method in any other suitable way (e.g. by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims

1. A quantum entanglement resource scheduling method, comprising:

Determining a value of the first variable based on the third relationship;

Determining a value of the optimal conversion based on the second relationship and the value of the first variable;

2. The method of claim 1, wherein the scheduling the quantum application service for resources based on the quantum application request and the value of the optimal conversion rate comprises:

3. The method of claim 2, further comprising:

4. The method of claim 2, further comprising:

5. The method of claim 1, wherein the quantum application service comprises any one of:

quantum key distribution application services;

a communication application service;

Distributed quantum computing application services.

6. The method of claim 1, wherein the determining the value of the first variable based on the third relationship comprises:

acquiring a Schmitt vector of the output state information;

7. The method of claim 6, wherein the obtaining the schmitt vector of output state information comprises:

arranging the W second elements in descending order to obtain a target vector;

8. The method according to claim 7, wherein the first target norms of the schmitt vectors of the output state information are sequentially acquired in order of m from small to large; outputting a value of the first variable if a first target norm of the schmitt vector of the output state information is greater than or equal to 1 minus the target error, comprising:

9. The method according to claim 7, wherein the first target norms of the schmitt vectors of the output state information are sequentially acquired in order of m from small to large; outputting a value of the first variable if a first target norm of the schmitt vector of the output state information is greater than or equal to 1 minus the target error, comprising:

Wherein the target interval is an interval of (P _c,P_c+1), and the value of the first variable is 2 and C is a binary value in the binary search, s _c+1 is a second element corresponding to the first index c+1 in the target vector, N _c+1 is a second index of an element corresponding to the first index c+1 in the schmitt vector of the output state information, P _c is a second addition corresponding to the first index c, P _c+1 is a second addition corresponding to the first index c+1, and epsilon is a target error.

10. The method according to claim 9, wherein in the dichotomy search, an upper bound of a dichotomy search interval is adjusted to be a dichotomy value in the dichotomy search if the first target value is less than or equal to a second addition corresponding to a first index c, and a lower bound of the dichotomy search interval is adjusted to be a second target value if the first target value is greater than a second addition corresponding to a first index c+1, the second target value being a dichotomy value in the dichotomy search plus 1.

11. The method of claim 1, wherein the conversion error is measured based on a trace norm of a schmitt vector of quantum states in the quantum entanglement preparation scenario.

12. The method of claim 11, wherein the conversion error is represented as:

Wherein T (|β > →|λ >) is the conversion error, |β >) is the maximum entangled state, |λ > isthe desired output state information in the quantum entanglement preparation scene, p _λ is the schmitt vector of the output state information|λ >, p _β is the schmitt vector of the maximum entangled state |β >, r is the schmitt vector of the quantum state output in the quantum entanglement preparation scene, prob (d) represents the set of probability distribution vectors with all dimensions d, and d is the quantum system dimension of the output state information.

13. A quantum entanglement resource scheduling device, comprising:

A second determination submodule for determining a value of the optimal conversion based on the second relation and the value of the first variable;

14. The apparatus of claim 13, wherein the resource scheduling module is specifically configured to:

15. The apparatus of claim 14, further comprising:

16. The apparatus of claim 14, further comprising:

17. The apparatus of claim 13, wherein the quantum application service comprises any one of:

quantum key distribution application services;

a communication application service;

Distributed quantum computing application services.

18. The apparatus of claim 13, wherein the first determination submodule comprises:

19. The apparatus of claim 18, wherein the obtaining unit is specifically configured to:

arranging the W second elements in descending order to obtain a target vector;

20. The device according to claim 19, wherein the output unit is specifically configured to:

21. The device according to claim 19, wherein the output unit is specifically configured to:

22. The apparatus of claim 21, wherein in the binary search, an upper bound of a binary search interval is adjusted to be a binary value in the binary search if the first target value is less than or equal to a second sum corresponding to a first index c, and a lower bound of the binary search interval is adjusted to be a second target value if the first target value is greater than a second sum corresponding to a first index c+1, the second target value being a binary value in the binary search plus 1.

23. The apparatus of claim 13, wherein the conversion error is measured based on a trace norm of a schmitt vector of quantum states in the quantum entanglement preparation scenario.

24. The apparatus of claim 23, wherein the conversion error is represented as:

25. An electronic device, comprising:

at least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-12.

26. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-12.

27. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any of claims 1-12.