CV-QKD real-time parameter estimation method and system for resisting local oscillation light intensity fluctuation

Abstract

The invention provides a CV-QKD real-time parameter estimation method and system for resisting local oscillation light intensity fluctuation, and the method comprises the steps: obtaining an initial shot noise calibration value through calibrating an LO intensity value before the start of a quantum key distribution process; in the quantum key distribution process, the received LO is subjected to beam splitting, the stronger path is used for coherent detection of quantum signal light, and the weaker path is used for LO intensity fluctuation monitoring; performing parameter estimation according to data obtained by coherent detection and the initial shot noise calibration value to obtain over-noise epsilon'and transmissivity T '; and according to the LO intensity fluctuation monitoring result, the LO intensity fluctuation monitoring result is considered in the parameter estimation process, and the over-noise epsilon'and the transmissivity T 'are corrected to obtain the over-noise epsilon and the transmissivity T close to the ideal LO condition. According to the method, the performance and the safety of the Gaussian modulation coherent state protocol CV-QKD system can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of continuous variable quantum key distribution (CV-QKD), and in particular to a CV-QKD real-time parameter estimation method and system capable of resisting local oscillator light intensity fluctuations. Background Art

[0002] CV-QKD allows two remote communication parties (sender Alice and receiver Bob) to establish a secure key through an insecure quantum channel. This technology is based on the uncertainty principle and the no-cloning theorem in quantum physics, and has provable unconditional security and detectability against eavesdropping. In recent years, CV-QKD has attracted much attention due to its good compatibility with existing standard optical communication components and its high code rate advantage at medium and short distances, and its secure code rate and transmission distance have also been continuously expanded. As the most widely developed CV-QKD protocol, the Gaussian modulated coherent state protocol has a maximum transmission distance of more than 200 kilometers, and the secure code rate at a transmission distance of 100 kilometers can reach the sub-Mbps level. In addition, the CV-QKD field networking application demonstration based on this protocol has been completed. At the same time, researchers have developed a quantum access network solution based on this protocol and completed experimental verification. In general, the CV-QKD solution based on this protocol is expected to become an effective solution for future secure quantum communications.

[0003] Although CV-QKD has made significant progress in theoretical research, experimental technology and practical verification, the deviation between theoretical models and actual implementation is still one of the core factors that limit its performance improvement and affect its actual security. For example, in actual implementation, the local oscillator (LO) is a necessary condition for achieving stable coherent detection. It can be used as a natural filter to effectively suppress background noise. However, in the actual implementation of the local oscillator CV-QKD scheme, since LO is transmitted through an untrusted quantum channel, this inevitably introduces some security vulnerabilities. The eavesdropper (Eve) may use these vulnerabilities to launch quantum hacking attacks to obtain system key information, such as LO intensity fluctuation attack, LO wavelength attack, LO calibration attack, saturation attack, polarization attack, etc. However, in the theoretical security analysis, the actual non-ideality of LO is not considered. In addition, LO is also closely related to the calibration of the shot noise of the CV-QKD system, and one of the main difficulties in the implementation of CV-QKD is high-precision shot noise calibration. The Shot Noise Unit (SNU) in CV-QKD plays the most important basic role in experiments and data analysis. As a normalization parameter, its size has an important influence on the calculation of the excess noise value introduced by the eavesdropper, which in turn greatly affects the number of keys that can be extracted from the original statistical data. Many quantum hacker attacks also hide their attack behavior by forging the estimated value of SNU.

[0004] Traditional SNU calibration mainly includes the following two methods: one is that before QKD, the communicating parties calibrate the LO intensity value in advance to obtain the SNU value, and use the calibration value for parameter estimation during the QKD process; the other is to calibrate the slope of the linear relationship between the local oscillator light power and the SNU value before QKD, and then measure the power of the local oscillator light in real time during the QKD process to calibrate the SNU value. For the first method, Eve can easily steal the key by forging the SNU estimate. For the second method, the response curve of the homodyne detector is easy to change over time, especially under the influence of the attacker. It is worth noting that neither of the above two methods considers the impact of LO intensity fluctuations on SNU calibration. Due to the non-ideality of the laser source itself, as well as the influence of factors such as temperature changes, environmental disturbances, and Eve manipulation (for the local oscillator system) during the QKD process, the intensity of the LO will fluctuate, which may also have an important impact on the performance and security of the system under the condition that the mean intensity remains unchanged. In 2021, a research team from the University of Toronto in Canada provided a security proof of a CV-QKD system with an intensity fluctuation source, indicating that small fluctuations in the signal light intensity can have a significant impact on the performance of the system. In 2023, a research team from Beijing University of Posts and Telecommunications in China described an attack method against a discrete modulation CV-QKD system, in which Eve concealed its attack on the signal pulse by simulating random fluctuations in the LO intensity around its mean and successfully stole the key. The above research shows that the impact of laser signal intensity fluctuations should be fully considered in parameter estimation or SNU calibration. In response to LO intensity fluctuations, although researchers have developed a real-time SNU calibration method to ensure the security of the system, this method is greatly affected by statistical fluctuations, and the introduction of equivalent optical switches will also reduce the efficiency of QKD. In summary, inaccurate existing shot noise calibration will lead to a decrease in the accuracy of parameter estimation, which will affect the performance and security of the system, and thus limit the efficient implementation of CV-QKD. Summary of the invention

[0005] In view of the problem that the local oscillator light intensity fluctuation has a great impact on the shot noise calibration and parameter estimation in the experimental implementation of the Gaussian modulated coherent state CV-QKD protocol, the present invention provides a CV-QKD real-time parameter estimation method and system that resists the local oscillator light intensity fluctuation. By real-time monitoring of the local oscillator light intensity fluctuation, the parameter estimation method is corrected to eliminate the influence of the local oscillator light intensity fluctuation on the parameter estimation, so that the system security code rate is restored to a value close to the ideal local oscillator light condition. The method proposed by the present invention is applicable to both the local oscillator CV-QKD scheme and the local local oscillator CV-QKD scheme.

[0006] The present invention provides a CV-QKD real-time parameter estimation method for resisting local oscillator light intensity fluctuations, comprising the following steps:

[0007] Step 1, before the quantum key distribution process begins, obtain an initial shot noise calibration value by calibrating the LO intensity value;

[0008] Step 2: During the quantum key distribution process, an asymmetric beam splitter is used to split the received LO. The stronger beam is used for coherent detection of quantum signal light, and the weaker beam is used for monitoring LO intensity fluctuations.

[0009] Step 3, perform parameter estimation based on the data obtained by coherent detection and the initial shot noise calibration value to obtain the excess noise ε′ and transmittance T′;

[0010] Step 4: According to the LO intensity fluctuation monitoring result, the LO intensity fluctuation monitoring result is taken into account in the parameter estimation process, and the excess noise ε′ and transmittance T′ are corrected to obtain the excess noise ε and transmittance T under the condition close to the ideal LO.

[0011] Further, the initial shot noise calibration value obtained in step 1 is expressed as:

[0012] SNU=A 2 |α LO | 2

[0013] Where A represents the detector amplification factor, I Lo =|α LO | 2 represents the average intensity of LO.

[0014] Furthermore, the LO intensity fluctuation monitoring in step 2 includes the mean and variance of the LO intensity fluctuation; according to the monitoring result of the weaker LO intensity fluctuation and based on the strength ratio relationship of the two LOs, the statistics such as the mean and variance of the stronger LO intensity fluctuation can be accurately calculated.

[0015] Furthermore, in step 3, according to the maximum likelihood estimation relationship between the excess noise ε′ and the transmittance T′, the initial shot noise calibration value obtained in step 1 is used as the normalization parameter, and the excess noise ε′ and the transmittance T′ of the system are estimated through the parameter estimation step in the CV-QKD post-processing.

[0016] Furthermore, each round of parameter estimation is based on the initial shot noise calibration value, and there is no need to update the initial shot noise calibration value according to the monitoring result of LO intensity fluctuation.

[0017] The present invention also provides a CV-QKD real-time parameter estimation system capable of resisting local oscillator light intensity fluctuations, comprising:

[0018] An initial shot noise calibration module is used for Alice and Bob to obtain an initial shot noise calibration value by calibrating the LO intensity value before the quantum key distribution process begins;

[0019] An asymmetric beam splitter is used for splitting the received LO by Bob during the quantum key distribution process;

[0020] A coherent detection module is used for coherent detection of quantum signal light using a stronger LO output by an asymmetric beam splitter;

[0021] A photodetector is used to monitor the LO intensity fluctuation of the weaker LO output from the asymmetric beam splitter;

[0022] A parameter estimation module is used to perform parameter estimation based on the data obtained by coherent detection and the initial shot noise calibration value to obtain the excess noise ε′ and the transmittance T′;

[0023] The parameter estimation correction module is used to take the LO intensity fluctuation monitoring results into account during the parameter estimation process, correct the excess noise ε′ and the transmittance T′, and obtain the excess noise ε and the transmittance T close to the ideal LO condition.

[0024] Further, the initial shot noise calibration value obtained by the initial shot noise calibration module is expressed as:

[0025] SNU=A 2 |α LO | 2

[0026] Where A represents the detector amplification factor, I Lo =|α LO | 2 represents the average intensity of LO.

[0027] Furthermore, the LO intensity fluctuation monitoring performed by the photodetector obtains a LO intensity fluctuation monitoring result including a mean and a variance of the LO intensity fluctuation; according to the weaker LO intensity fluctuation monitoring result and based on the intensity ratio relationship between the two LO paths, the statistical quantities such as the mean and the variance of the stronger LO intensity fluctuation can be accurately calculated.

[0028] Furthermore, in the parameter estimation module, based on the maximum likelihood estimation relationship between the excess noise ε′ and the transmittance T′, the initial shot noise calibration value obtained by the initial shot noise calibration module is used as a normalization parameter, and the excess noise ε′ and the transmittance T′ of the system are estimated through the parameter estimation step in the CV-QKD post-processing.

[0029] Furthermore, in the parameter estimation module, each round of parameter estimation is based on the initial shot noise calibration value, and there is no need to update the initial shot noise calibration value according to the monitoring result of the LO intensity fluctuation.

[0030] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0031] The present invention adopts a method for monitoring the intensity fluctuation of the local oscillator light at the signal receiving end to perform real-time correction on the parameter estimation process of the Gaussian modulated coherent state CV-QKD system, so as to optimize and improve the system security code rate. At the signal receiving end, a part of the local oscillator light is split, and the real-time monitoring of the local oscillator light intensity is completed by a photoelectric detector. According to the mean and variance of the local oscillator light intensity fluctuation obtained by monitoring, the traditional parameter estimation process is corrected to obtain the corrected system transmittance and excess noise value, and the system security code rate under conditions close to the ideal local oscillator light is restored, effectively eliminating the influence of LO intensity fluctuation on system performance. The real-time parameter estimation method proposed in the present invention only needs to split a small part of the local oscillator light for intensity fluctuation monitoring to achieve an effect equivalent to real-time calibration of shot noise, which will not affect the efficiency of quantum key distribution, and will not introduce additional excess noise. In addition, the real-time monitoring of the local oscillator light by the present invention can effectively resist quantum hacker attacks on the local oscillator light. In summary, the present invention can effectively improve the performance and security of the Gaussian modulated coherent state protocol CV-QKD system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Flow chart of a CV-QKD real-time parameter estimation method for resisting local oscillator light intensity fluctuations in an embodiment of the present invention.

[0033] Figure 2 Schematic diagram of the LO intensity fluctuation monitoring structure in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0035] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Example

[0037] In view of the problem that the local oscillator light intensity fluctuation has a great impact on the shot noise calibration and parameter estimation in the experimental implementation of the Gaussian modulated coherent state CV-QKD protocol, this embodiment proposes a CV-QKD real-time parameter estimation method that resists the local oscillator light intensity fluctuation. This method is applicable to the Gaussian modulated coherent state CV-QKD protocol. Figure 1 As shown, the method comprises the following steps:

[0038] Step 1: Before the quantum key distribution process begins, Alice and Bob obtain an initial shot noise calibration value by calibrating the LO intensity value; the obtained initial shot noise calibration value is expressed as:

[0039] SNU=A 2 |α LO | 2

[0040] Where A represents the detector amplification factor, I Lo =|α LO | 2 represents the average intensity of LO.

[0041] Step 2, such as Figure 2 As shown in the figure, in the process of quantum key distribution, Bob uses an asymmetric beam splitter to split the received LO. The stronger one is used for coherent detection of quantum signal light, and the weaker one is used for monitoring LO intensity fluctuation. Among them, the asymmetric beam splitter can be selected in a 10 / 90 ratio. On the one hand, the use of a high-sensitivity photodetector can monitor the intensity of the weaker LO in real time, including the mean and variance of the LO intensity fluctuation. The coefficient k is used to describe the fluctuation factor of the random fluctuation of the LO intensity, and E is used to describe the fluctuation factor of the random fluctuation of the LO intensity. k and V k On the other hand, the stronger LO is strong enough to complete the coherent detection of quantum signal light. Subsequently, based on the ratio of the intensities of the two LOs, the statistical quantities such as the mean and variance of the intensity fluctuation of the stronger LO can be accurately calculated.

[0042] In step 3, Alice and Bob perform parameter estimation based on the data obtained by coherent detection and the initial shot noise calibration value to obtain the over-noise ε′ and transmittance T′. Specifically, for the Gaussian modulated coherent state CV-QKD protocol, the associated variables of Alice and Bob usually satisfy the standard linear model, that is, y=tx+z, where x represents the original data on Alice's side, y represents the original data on Bob's side, z represents the noise of the quantum channel, and t represents the channel and detection loss. According to the maximum likelihood estimation relationship between the over-noise ε′ and the transmittance T′, the initial shot noise calibration value obtained in step 1 is used as the normalization parameter, and the over-noise ε′ and transmittance T′ of the system are estimated through the parameter estimation step in the CV-QKD post-processing. It is worth noting that each round of parameter estimation is based on the initial shot noise calibration value, and there is no need to update the initial shot noise calibration value based on the monitoring results of the LO intensity fluctuation.

[0043] Step 4: According to Bob's monitoring results of LO intensity fluctuations, the LO intensity fluctuation monitoring results are taken into account in the parameter estimation process, and the excess noise ε′ and transmittance T′ are corrected to obtain excess noise ε and transmittance T close to the ideal LO conditions. The coefficient k is used to describe the fluctuation factor of the random fluctuation of LO intensity, and E k and V k denote the mean and variance of LO intensity fluctuations, respectively, which can be measured by the LO intensity monitoring process in step 2. The parameter estimation process in post-processing is modified to consider V k The actual value is calibrated to get the influence of the noise ε and transmittance T under the ideal LO condition. Then, the secure quantum key extraction is completed through other steps of data post-processing.

[0044] The present invention can improve the security code rate of the GMCS CV-QKD system for the following reasons:

[0045] In coherent detection, the role of LO includes providing a stable phase reference, signal amplification, and signal filtering. Under high-precision real-time shot noise calibration or parameter estimation conditions, the actual values ​​of transmittance T and excess noise ε are close to the values ​​under ideal LO conditions, that is, the LO intensity fluctuation is zero. In actual implementation, the LO intensity fluctuates randomly around the mean, which will affect the parameter estimation results, and then affect the number of keys extracted by the communicating parties from the original statistical data, and may even endanger the security of QKD. For the Gaussian modulated coherent state CV-QKD protocol, considering the random fluctuation of LO intensity, if the communicating parties still use the initial shot noise calibration value obtained by the average LO intensity calibration before QKD as the normalized parameter for parameter estimation during the QKD process, the excess noise ε′ obtained by parameter estimation is greater than the actual value ε, while the transmittance T′ is less than the actual value T. Since the influence of excess noise on the security code rate is more obvious, the security code rate obtained by the calibration of the communicating parties is lower than the actual value. Therefore, by correcting the parameter estimation process through the real-time monitoring results of LO intensity fluctuations, the actual transmittance and excess noise values ​​can be obtained, that is, the system performance is restored to a security code rate value close to the ideal LO condition, thereby obtaining a higher and more accurate security code rate value. At the same time, Eve's manipulation of LO can also be detected by monitoring the changes in LO intensity and its intensity fluctuations. In summary, the CV-QKD real-time parameter estimation method proposed in the present invention that resists local oscillator light intensity fluctuations can effectively improve the performance and security of Gaussian modulated coherent state continuous variable quantum key distribution systems.

[0046] In order to make the advantages and features of the present invention more clearly understood, the present invention is further described in detail with reference to examples, as follows:

[0047] Step 1, obtain the initial shot noise calibration value:

[0048] Before the quantum key distribution observation, Bob cuts off the quantum signal light and turns on the LO light. He calibrates the LO intensity value to calibrate the initial shot noise calibration value. The LO intensity here corresponds to the average intensity, that is, SNU = A 2 |α LO | 2 .

[0049] Step 2, LO intensity fluctuation monitoring signal acquisition:

[0050] In the process of quantum key distribution, Bob uses an asymmetric beam splitter with a splitting ratio of 10 / 90 to split the LO. The stronger LO is used for coherent detection of quantum signal light, and the weaker one is used for real-time monitoring of LO intensity fluctuations. The following corrections are made to the parameter estimation process based on the monitoring results.

[0051] Step 3, CV-QKD system parameter estimation:

[0052] In the Gaussian modulated coherent state CV-QKD protocol, assuming that the coherent state prepared by Alice is |α S >=|α S |e iθ =|X S +iP S >, where α S and θ represent the amplitude and phase of the modulated optical signal respectively, X S and P S is a product with a mean of 0 and a variance of V M N0 is a Gaussian random number. Assume that the normalized data detected by Bob is (X B ,P B ). For homodyne detection, for ease of analysis, taking the orthogonal component X of the signal light as an example, Alice's signal is represented by X S =|α S |cosθ. The corresponding output signal of Bob after the label coherent detection is X out .

[0053] Step 3.1, under ideal LO conditions, the intensity fluctuation is 0, then after normalization with the initial shot noise calibration value as the normalization parameter, we have:

[0054]

[0055] Where η is the detector efficiency, X A The orthogonal components describing the initial state prepared by Alice have a variance of V M +1, X E Describe the pattern of Eve injected through the quantum channel, whose variance is V E =1+Tε / (1-T), X υ represents the coupling mode introduced by the detector imperfectly, and its variance is υ=1+υ el / (1-η). So X S and X B The following relationship exists:

[0056]

[0057] Step 3.2: Under non-ideal LO conditions, the fluctuation factor k is introduced to describe the random fluctuation of LO intensity, that is, the actual LO intensity is expressed as kI LO , for a stably operating CV-QKD system, the variance of its intensity fluctuation is V K , the mean value of the intensity fluctuation is E k = <k>=1, the above two parameters can be obtained through the monitoring process in step 2. (X′ B ,P B ′) is the data detected by Bob under the condition of LO intensity fluctuation (calibrated with the initial shot noise calibration value as the normalization parameter). At this time, the signal detected by Bob is expressed as: At the same time, the variables at both Alice and Bob satisfy the relationship:

[0058]

[0059] For the Gaussian modulated coherent state CV-QKD protocol, the associated variables of Alice and Bob usually satisfy the standard linear model, that is, y = tx + z. For this model, the maximum likelihood estimator is It is expressed as follows:

[0060]

[0061] Through the above relationship, the expressions of transmittance and excess noise under intensity fluctuation conditions can be obtained using the initial shot noise calibration value obtained in step 1 as the normalization parameter:

[0062]

[0063] Step 4, CV-QKD system parameter correction:

[0064] The variance of the LO intensity fluctuation V is measured k , the actual value can be restored, that is, the transmittance and excess noise close to the ideal LO conditions are obtained, which are expressed as follows:

[0065]

[0066] By modifying the parameter estimation process and other post-processing steps, the optimized security code rate of the CV-QKD system under the condition of LO intensity fluctuation can be calculated, which is close to the security code rate value under ideal LO conditions.

[0067] Through the above LO intensity fluctuation real-time monitoring process, the information of LO intensity fluctuation variance can be obtained in real time, and the security code rate of the CV-QKD system under the condition close to the ideal LO can be restored, thus solving the problem of limited performance of the CV-QKD system caused by LO intensity fluctuation. At the same time, according to the results of LO real-time monitoring, possible LO quantum hacker attacks can be defended, further improving the security of the system.

[0068] Corresponding to the above method, this embodiment further provides a CV-QKD real-time parameter estimation system that resists local oscillator light intensity fluctuations, including:

[0069] The initial shot noise calibration module is used for Alice and Bob to obtain an initial shot noise calibration value by calibrating the LO intensity value before the quantum key distribution process begins; wherein the initial shot noise calibration value obtained by the initial shot noise calibration module is expressed as:

[0070] SNU=A 2 |α LO | 2

[0071] Where A represents the detector amplification factor, I Lo =|α LO | 2 represents the average intensity of LO.

[0072] An asymmetric beam splitter is used for splitting the received LO by Bob during the quantum key distribution process;

[0073] A coherent detection module is used for coherent detection of quantum signal light using a stronger LO output by an asymmetric beam splitter;

[0074] A photoelectric detector is used to monitor the LO intensity fluctuation of the weaker LO output by the asymmetric beam splitter; the LO intensity fluctuation monitoring results obtained by the LO intensity fluctuation monitoring performed by the photoelectric detector include the mean and variance of the LO intensity fluctuation; according to the weaker LO intensity fluctuation monitoring results and based on the intensity ratio relationship of the two LOs, the statistical quantities such as the mean and variance of the stronger LO intensity fluctuation can be accurately calculated.

[0075] The parameter estimation module is used to perform parameter estimation based on the data obtained by coherent detection and the initial shot noise calibration value to obtain the excess noise ε′ and the transmittance T′; wherein, according to the maximum likelihood estimation relationship between the excess noise ε′ and the transmittance T′, the initial shot noise calibration value obtained by the initial shot noise calibration module is used as a normalization parameter, and the excess noise ε′ and the transmittance T′ of the system are estimated through the parameter estimation step in the CV-QKD post-processing. Each round of parameter estimation is based on the initial shot noise calibration value, and the initial shot noise calibration value does not need to be updated according to the monitoring results of the LO intensity fluctuation.

[0076] The parameter estimation correction module is used to take the LO intensity fluctuation monitoring results into account during the parameter estimation process, correct the excess noise ε′ and the transmittance T′, and obtain the excess noise ε and the transmittance T close to the ideal LO condition.

[0077] The working principle of each functional module in the system refers to the above method and will not be repeated here.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.< / k>

Claims

1. A CV-QKD real-time parameter estimation method that resists local oscillator light intensity fluctuations, characterized in that: The steps include: Step 1, before the quantum key distribution process begins, an initial shot noise calibration value is obtained by calibrating the LO intensity value; Step 2: During the quantum key distribution process, an asymmetric beam splitter is used to split the received LO. The stronger beam is used for coherent detection of quantum signal light, and the weaker beam is used for monitoring LO intensity fluctuations. Step 3: Parameter estimation is performed based on the data obtained from coherent detection and the initial shot noise calibration value to obtain the excess noise ε ′ and transmittance T ′ ; Step 4: Based on the LO intensity fluctuation monitoring results, the LO intensity fluctuation monitoring results are taken into account in the parameter estimation process, and the over-noise ε ′ and transmittance T ′ Correction is performed to obtain the excess noise ε and transmittance T close to the ideal LO conditions.

2. The CV-QKD real-time parameter estimation method for resisting local oscillator light intensity fluctuation according to claim 1, characterized in that: The initial shot noise calibration value obtained in step 1 is expressed as: SNU=A 2 |a LO | 2 Where A represents the detector amplification factor, I Lo =|α LO | 2 represents the average intensity of LO.

3. The CV-QKD real-time parameter estimation method for resisting local oscillator light intensity fluctuation according to claim 1, characterized in that: The LO intensity fluctuation monitoring in step 2 includes the mean and variance of the LO intensity fluctuation; According to the monitoring results of the intensity fluctuation of the weaker LO and based on the proportional relationship between the intensities of the two LOs, the statistical quantities such as the mean and variance of the intensity fluctuation of the stronger LO can be accurately calculated.

4. The CV-QKD real-time parameter estimation method for resisting local oscillator light intensity fluctuation according to claim 1, characterized in that: In step 3, according to the excess noise ε ′ and transmittance T ′ The maximum likelihood estimation relationship of is used, and the initial shot noise calibration value obtained in step 1 is used as the normalization parameter. The excess noise ε of the system is estimated through the parameter estimation step in the CV-QKD post-processing. ′ and transmittance T ′ .

5. The CV-QKD real-time parameter estimation method for resisting local oscillator light intensity fluctuation according to claim 4, characterized in that: Each round of parameter estimation is based on the initial shot noise calibration value, and there is no need to update the initial shot noise calibration value based on the monitoring results of LO intensity fluctuations.

6. A CV-QKD real-time parameter estimation system that resists local oscillator light intensity fluctuations, characterized in that: include: An initial shot noise calibration module is used for Alice and Bob to obtain an initial shot noise calibration value by calibrating the LO intensity value before the quantum key distribution process begins; An asymmetric beam splitter is used for splitting the received LO by Bob during the quantum key distribution process; A coherent detection module is used for coherent detection of quantum signal light using a stronger LO output by an asymmetric beam splitter; A photodetector is used to monitor the LO intensity fluctuation of the weaker LO output from the asymmetric beam splitter; The parameter estimation module is used to perform parameter estimation based on the data obtained from coherent detection and the initial shot noise calibration value to obtain the excess noise ε ′ and transmittance T ′ ; The parameter estimation correction module is used to take the LO intensity fluctuation monitoring results into account during the parameter estimation process and to correct the over-noise ε ′ and transmittance T ′ Correction is performed to obtain the excess noise ε and transmittance T close to the ideal LO conditions.

7. The CV-QKD real-time parameter estimation system for resisting local oscillator light intensity fluctuation according to claim 6, characterized in that: The initial shot noise calibration value obtained by the initial shot noise calibration module is expressed as: SNU=A 2 |a LO | 2 Where A represents the detector amplification factor, I Lo =|α LO | 2 represents the average intensity of LO.

8. The CV-QKD real-time parameter estimation system for resisting local oscillator light intensity fluctuation according to claim 6, characterized in that: The LO intensity fluctuation monitoring performed by the photodetector, the LO intensity fluctuation monitoring results obtained include the mean and variance of the LO intensity fluctuation; According to the monitoring results of the intensity fluctuation of the weaker LO and based on the proportional relationship between the intensities of the two LOs, the statistical quantities such as the mean and variance of the intensity fluctuation of the stronger LO can be accurately calculated.

9. The CV-QKD real-time parameter estimation system for resisting local oscillator light intensity fluctuation according to claim 6, characterized in that: In the parameter estimation module, according to the excess noise ε ′ and transmittance T ′ The maximum likelihood estimation relationship of is used, the initial shot noise calibration value obtained by the initial shot noise calibration module is used as the normalization parameter, and the system excess noise ε is estimated through the parameter estimation step in the CV-QKD post-processing ′ and transmittance T ′ .

10. The CV-QKD real-time parameter estimation system for resisting local oscillator light intensity fluctuation according to claim 9, characterized in that: In the parameter estimation module, each round of parameter estimation is based on the initial shot noise calibration value, and there is no need to update the initial shot noise calibration value according to the monitoring result of LO intensity fluctuation.

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