Self-balanced quantum random number generator based on vacuum fluctuation measurement and method of use

Abstract

The present invention provides a self-balanced quantum random number generator based on vacuum fluctuation measurement and a usage method, comprising: a laser, a vacuum state generator, a homodyne detection module, a weak signal amplifier, an analog-to-digital converter, an entropy evaluation module, and a post-processing module; the homodyne detection module includes a beam splitter, a photodetector, an adjustable optical attenuator, and a subtractor; the output end of the laser is connected to one input end of the beam splitter; the output end of the vacuum state generator is connected to the other input end of the beam splitter; the output end of the beam splitter is connected to the input end of the adjustable optical attenuator; the output end of the adjustable optical attenuator is connected to the input end of the photodetector; the output end of the photodetector is connected to the subtractor; the weak signal amplifier, the analog-to-digital converter, the entropy evaluation module, and the post-processing module are connected in sequence; the input end of the weak signal amplifier is connected to the output end of the subtractor. The present invention can obtain quantum random numbers with higher randomness and effectively remove the DC bias in the random numbers.

Description

Technical Field

[0001] The present invention relates to the technical field of quantum random numbers. Specifically, it relates to a quantum random number generation device based on vacuum fluctuations and a self-balancing quantum random number generator, and particularly to a self-balancing quantum random number generator based on vacuum fluctuation measurement and its usage method. Background Art

[0002] With the development of global computer and information technologies, communication and exchanges have become increasingly frequent, and information security in communication has drawn more and more attention from people. To meet the growing demand for communication security, one of the most important communication methods, quantum communication, has gained people's favor. As an important part of quantum communication, the random number generator has a very important impact on the security foundation of quantum communication. In addition, the random number theory is also one of the most important components in cryptography. Nowadays, random numbers play very important roles not only in the field of cryptography but also in many other scientific research fields, such as statistical sampling, random algorithms, cryptography, information communication security, and many other sciences and technologies.

[0003] A random number is a sequence of numbers or symbols that satisfies certain statistical properties and does not have any fixed or obvious patterns. According to the generation method of random numbers, they can be divided into two categories: pseudo-random numbers and true random numbers. Pseudo-random numbers are usually generated by using deterministic computer software algorithms and short random seed sequences. The random number sequences generated by such deterministic algorithms are not completely random, and they do not have true randomness in nature. Therefore, in applications with high security requirements, pseudo-random number sequences can no longer meet the needs.

[0004] True random number sequences are generated by true random number generators, which generally generate by measuring and sampling non-deterministic physical phenomena. Usually, true random numbers satisfy the following three characteristics: non-repeatability, unpredictability, and unbiasedness. There are many physical random sources that generate non-deterministic physical phenomena, such as atmospheric noise, electronic noise, frequency jitter, radiation decay, etc. However, limited by classical physical mechanisms and existing sampling and extraction means, the coding rate of random number sequences is very low and cannot meet the actual needs. With the rapid development of quantum technology, there have been great breakthroughs in the selection of physical random sources and sampling measurement technologies for true random numbers. True random number generators designed by using the quantum characteristics of physical random sources have a secure source of randomness and a high coding rate. Therefore, quantum random number generators have very important applications in the field of information security.

[0005] Information security often involves the encryption of key pair information, and the basis of keys is random numbers. Quantum random numbers based on quantum mechanics ensure the randomness of random numbers due to the fundamental principle of uncertainty in quantum mechanics. Therefore, quantum random number generators are an important development direction for random numbers.

[0006] Currently, there are many schemes for quantum random number generators, such as the scheme based on single-photon path selection, the scheme based on photon arrival time, the scheme based on laser phase fluctuations, etc. However, the existing schemes for quantum random number generators have many disadvantages. Some systems are complex and difficult to control, some have a low random number generation rate, some require a complex phase stabilization system and are not conducive to integration, and some require large-scale instrument equipment with high costs.

[0007] In recent years, the quantum random number generation method based on vacuum state measurement has become a new method for generating quantum random numbers. By measuring the vacuum state and extracting random bits from the measurement results, the purpose of generating random numbers is achieved.

[0008] Currently, the number of random number bits obtained by the quantum random number generation method based on vacuum state measurement is relatively low. Because the devices such as photodetectors and amplifiers in the generation method are affected by parameters such as current or temperature, there are bias and asymmetry problems. These problems cause obvious bias in the sampled data and make the data statistical histogram asymmetric, ultimately resulting in poor randomness of the random numbers. Summary of the Invention

[0009] Aiming at the defects in the prior art, the present invention provides a self-balanced quantum random number generator based on vacuum fluctuation measurement and a usage method.

[0010] According to a self-balanced quantum random number generator based on vacuum fluctuation measurement and a usage method provided by the present invention, the scheme is as follows:

[0011] In the first aspect, a self-balanced quantum random number generator based on vacuum fluctuation measurement is provided. The quantum random number generator includes: a laser, a vacuum state generator, a homodyne detection module, a weak signal amplifier, an analog-to-digital converter, an entropy evaluation module, and a post-processing module;

[0012] Among them, the homodyne detection module includes a beam splitter, a photodetector, an adjustable optical attenuator, and a subtractor;

[0013] The output end of the laser is connected to one input end of the beam splitter; the output end of the vacuum state generator is connected to the other input end of the beam splitter; the output end of the beam splitter is connected to the input end of the variable optical attenuator; the output end of the variable optical attenuator is connected to the input end of the photodetector; the output end of the photodetector is connected to the subtractor; the weak signal amplifier, analog-to-digital converter, entropy evaluation module, and post-processing module are connected in sequence; the input end of the weak signal amplifier is connected to the output end of the subtractor.

[0014] Preferably, the laser is used to output continuous and stable laser light;

[0015] The vacuum state generator is used to generate a vacuum state;

[0016] The homodyne detection module realizes the measurement of the vacuum state;

[0017] The weak signal amplifier is an operational amplifier that realizes the amplification of the electrical signal;

[0018] The analog-to-digital converter is a balun and analog-to-digital conversion chip that realizes the digital conversion of the electrical signal;

[0019] The entropy evaluation module and the post-processing module are implemented using an FPGA chip.

[0020] Preferably, the laser light output by the laser interferes with the vacuum state output by the vacuum state generator to obtain interference light;

[0021] The beam splitter is a 50:50 beam splitter with a random polarization direction that splits the interference light; the variable optical attenuator adjusts the light intensity of the split interference light to control the balance state of the homodyne detection module; the photodetector converts the optical signal into an electrical signal; the subtractor uses the electrical signal detected by the photodetector to obtain a differential current.

[0022] Preferably, the variable optical attenuator automatically adjusts the balance state of the light intensity of the upper arm and the lower arm of the variable optical attenuator through a self-balancing algorithm.

[0023] Preferably, the steps of the self-balancing algorithm include:

[0024] Step 1): Adjust the voltage of the upper arm of the variable optical attenuator so that the input value of the digital-to-analog converter is n1, adjust the voltage of the lower arm of the variable optical attenuator so that the input value of the digital-to-analog converter is n2, and read the mean value of the DC component of the output voltage value of the homodyne detection module as ν. ν is the output voltage value amplified by the weak signal amplifier of the current difference between the upper arm and the lower arm of the variable optical attenuator of the homodyne detection module, expressed as ν = f(n1 - n2); it is known that the minimum adjustment value of n1 is 0 mv, and the maximum adjustment value is 2w mv, w is the number of bits of accuracy of the digital-to-analog converter chip, and in this case, let B = 0mv, T = 2 w mv, the algorithm goes to step 2);

[0025] Step 2): Determine ν. If -50mv≤ν≤50mv, output n1 and stop the algorithm. If 50mv≤ν, the algorithm goes to step 3). If -50mv≥ν, the algorithm goes to step 4.

[0026] Step 3): Let T = n1, adjust the voltage of the upper arm of the variable optical attenuator so that the input value of the digital-to-analog converter is Read again the DC component mean value ν of the output voltage value of the homodyne detection module after being amplified by the weak signal amplifier, and the algorithm goes to step 2);

[0027] Step 4): Let B = n1, adjust the voltage of the upper arm of the variable optical attenuator so that the input value of the digital-to-analog converter is The DC component mean value ν of the output voltage of the homodyne detection module amplified by the weak signal amplifier is read again, and the algorithm goes to step 2).

[0028] In a second aspect, a method for using a self-balancing quantum random number generator based on vacuum fluctuation measurement is provided, the method comprising:

[0029] Step S1: the pulsed laser generated by the laser is fed as local oscillator light into one input end of a 50:50 beam splitter, and the vacuum state generated by the vacuum state generator is fed as signal light into the other input end of the 50:50 beam splitter, whereby the local oscillator light interferes with the vacuum state to obtain interference light;

[0030] Step S2: The optical beam splitter splits the input interference light into two, and the split interference light is subjected to light intensity adjustment by the control module algorithm through the adjustable optical attenuator to control the balance state of the homodyne detection module;

[0031] Step S3: The attenuated light is converted into an electrical signal by a photodetector, a differential current is generated by a subtractor, and the differential current is sent to a weak signal amplifier for electrical signal amplification;

[0032] Step S4: The amplified electrical signal is converted into a digital electrical signal via an analog-to-digital converter, and the converted digital signal obtains the original data of the quantum random number generator;

[0033] Step S5: The obtained raw data is transmitted to the entropy evaluation module and the post-processing module to process the raw data and finally generate random numbers.

[0034] According to a third aspect, a device is provided, comprising:

[0035] One or more processors;

[0036] A storage device for storing one or more programs,

[0037] When the one or more programs are executed by the one or more processors, the one or more processors implement the steps in the method.

[0038] In a fourth aspect, a computer-readable storage medium storing a computer program is provided, and when the computer program is executed by a processor, the steps in the method are implemented.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention can generate more random numbers by adjusting with a self-balancing algorithm, thereby generating true random numbers with better randomness and effectively removing the DC bias in the random numbers.

[0041] Other beneficial effects of the present invention will be described in the specific implementation manners through the introduction of specific technical features and technical solutions. Those skilled in the art should be able to understand the beneficial technical effects brought by the technical features and technical solutions through these introductions. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] By reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings, other features, objects, and advantages of the present invention will become more apparent:

[0043] Figure 1 Is an implementation device of a self-balancing quantum random number generator based on vacuum fluctuation measurement;

[0044] Figure 2 Is a schematic diagram of the implementation process of the self-balancing algorithm. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those of ordinary skill in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0046] An embodiment of the present invention provides a self-balancing quantum random number generator based on vacuum fluctuation measurement, referring to Figure 1As shown in the figure, the quantum random number generator includes: a laser, a vacuum state generator, a homodyne detection module, a weak signal amplifier, an analog-to-digital converter, an entropy evaluation module, and a post-processing module. The homodyne detection module further includes a beam splitter, a photodetector, an adjustable optical attenuator, and a subtractor. The entropy evaluation module and the post-processing module form an FPGA post-processing module, which is implemented using an FPGA chip. The FPGA post-processing module realizes the evaluation of the quantum entropy of the original data and the preprocessing of the original data, and finally outputs random numbers.

[0047] Among them, the laser is used to output continuous and stable local oscillator light; the vacuum state generator is used to generate a vacuum state; the beam splitter is used to interfere the signal light and the local oscillator light, and divide the interfered light into two beams with equal intensity.

[0048] The adjustable optical attenuator adjusts the light intensity of the split light to control the balance state of the homodyne detection module; the photodetector is used to detect the light intensity of the coherent light and convert it into a current signal. The subtractor is used to generate a differential current from the detected current intensity. The weak signal amplifier is used to convert the differential current into a voltage signal and amplify it. The analog-to-digital converter is used to convert the analog electrical signal into a digital electrical signal.

[0049] The FPGA post-processing module is used to perform entropy evaluation, encoding, and debiasing on the analysis data to generate random numbers.

[0050] The output end of the laser is connected to one input end of the beam splitter; the output end of the vacuum state generator is connected to the other input end of the beam splitter; the output end of the beam splitter is connected to the input end of the adjustable optical attenuator; the output end of the adjustable optical attenuator is connected to the input end of the photodetector; the output end of the photodetector is connected to the subtractor; the weak signal amplifier, the analog-to-digital converter, the entropy evaluation module, and the post-processing module are connected in sequence; the input end of the weak signal amplifier is connected to the output end of the subtractor.

[0051] When using the random number generator provided by the present invention, the pulsed laser generated by the laser is used as the local oscillator light and enters one input end of a 50:50 beam splitter, and the vacuum state generated by the vacuum state generator is used as the signal light and enters the other input end of the 50:50 beam splitter. The local oscillator light and the vacuum state are coherently interfered; the optical beam splitter divides the input interference light into two; the split light is adjusted in light intensity by the adjustable optical attenuator to control the balance state of the homodyne detection module; the attenuated light is converted into an electrical signal by the photodetector, and a differential current is generated by the subtractor and sent to the weak signal amplifier for electrical signal amplification. The amplified electrical signal is converted from an analog electrical signal to a digital electrical signal by the analog-to-digital converter, and the converted digital signal obtains the original data of the quantum random number generator. The obtained original data is transmitted to the FPGA post-processing module to realize the processing of the original data, including entropy evaluation and post-processing, and finally generate random numbers.

[0052] An adjustable optical attenuator automatically adjusts the balance state of the optical intensities of the upper arm and the lower arm of the adjustable optical attenuator through a self-balancing algorithm.

[0053] The steps of the self-balancing algorithm include:

[0054] Step 1): Adjust the voltage of the upper arm of the adjustable optical attenuator to make the input value of the digital-to-analog converter be n1, adjust the voltage of the lower arm of the adjustable optical attenuator to make the input value of the digital-to-analog converter be n2, and read the average value of the DC component of the output voltage value of the homodyne detection module as ν. ν is the output voltage value amplified by the weak signal amplifier of the current difference between the upper arm and the lower arm of the adjustable optical attenuator of the homodyne detection module, and can be expressed as ν = f(n1 - n2). It is known that the minimum adjustment value of n1 is 0 mv, the maximum adjustment value is 2 w mv, w is the number of bits of the accuracy of the digital-to-analog converter chip. At this time, let B = 0 mv, T = 2 w mv, and the algorithm proceeds to Step 2.

[0055] Step 2): Judge ν. If -50 mv ≤ ν ≤ 50 mv, output n1 and stop the algorithm. If 50 mv ≤ ν, the algorithm proceeds to Step 3. If -50 mv ≥ ν, the algorithm proceeds to Step 4.

[0056] Step 3): Let T = n1, and adjust the voltage of the upper arm of the adjustable optical attenuator to make the input value of the digital-to-analog converter be Read the average value of the DC component of the output voltage value amplified by the weak signal amplifier of the homodyne detection module again as ν, and the algorithm proceeds to Step 2.

[0057] Step 4): Let B = n1, and adjust the voltage of the upper arm of the adjustable optical attenuator to make the input value of the digital-to-analog converter be Read the average value of the DC component of the output voltage value amplified by the weak signal amplifier of the homodyne detection module again as ν, and the algorithm proceeds to Step 2.

[0058] The present invention also provides a method for using a self-balancing quantum random number generator based on vacuum fluctuation measurement. Referring to Figure 2 as shown, the method includes:

[0059] Step S1: Use the pulsed laser generated by the laser as the local oscillator light to enter one input end of the 50:50 beam splitter, and use the vacuum state generated by the vacuum state generator as the signal light to enter the other input end of the 50:50 beam splitter. The local oscillator light and the vacuum state interfere to obtain the interference light.

[0060] Step S2: The optical beam splitter divides the input interference light into two parts. The divided interference light is adjusted in optical intensity through the adjustable optical attenuator by the control module algorithm to control the balance state of the homodyne detection module.

[0061] Step S3: The attenuated light is converted into an electrical signal by a photodetector. A subtractor generates a differential current and sends this differential current to a weak signal amplifier for electrical signal amplification.

[0062] Step S4: The amplified electrical signal is converted from an analog electrical signal to a digital electrical signal by an analog-to-digital converter. The converted digital signal becomes the raw data of the quantum random number generator.

[0063] Step S5: The obtained raw data is transmitted to an entropy evaluation module and a post-processing module to process the raw data and finally generate random numbers.

[0064] The embodiment of the present invention provides a self-balanced quantum random number generator based on vacuum fluctuation measurement and its usage method. By adjusting with a self-balanced algorithm, more random numbers can be generated, thereby generating true random numbers with better randomness and effectively removing the DC bias in the random numbers.

[0065] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be regarded as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or the structures within the hardware component.

[0066] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A self-balanced quantum random number generator based on vacuum fluctuation measurement, characterized in that The quantum random number generator includes: a laser, a vacuum state generator, a homodyne detection module, a weak signal amplifier, an analog-to-digital converter, an entropy evaluation module, and a post-processing module; Among them, the homodyne detection module includes a beam splitter, a photodetector, an adjustable optical attenuator, and a subtractor; The output end of the laser is connected to one input end of the beam splitter; the output end of the vacuum state generator is connected to the other input end of the beam splitter; the output end of the beam splitter is connected to the input end of the adjustable optical attenuator; the output end of the adjustable optical attenuator is connected to the input end of the photodetector; the output end of the photodetector is connected to the subtractor; the weak signal amplifier, the analog-to-digital converter, the entropy evaluation module, and the post-processing module are connected in sequence; the input end of the weak signal amplifier is connected to the output end of the subtractor; The steps of the self-balancing algorithm include: Step 1): Adjust the voltage of the upper arm of the variable optical attenuator so that the input value of the digital-to-analog converter is , adjust the voltage of the lower arm of the variable optical attenuator so that the input value of the digital-to-analog converter is , read the mean value of the DC component of the output voltage value of the homodyne detection module as , is the output voltage value amplified by the weak signal amplifier of the current difference between the upper arm and the lower arm of the variable optical attenuator of the homodyne detection module, expressed as ; it is known that has a minimum adjustment value of 0 mv and a maximum adjustment value of mv, is the number of bits of the accuracy of the digital-to-analog converter chip. At this time, let B = 0 mv and T = mv, and the algorithm goes to step 2); Step 2): Determine , if 0 , output , and stop the algorithm; if , transfer the algorithm to Step 3); if , transfer the algorithm to Step 4); Step 3): Let T = , adjust the voltage of the upper arm of the variable optical attenuator so that the input value of the digital-to-analog converter is , and read the mean value of the DC component of the output voltage value amplified by the weak signal amplifier of the homodyne detection module again , and the algorithm goes to Step 2); Step 4): Let B = , adjust the voltage of the upper arm of the variable optical attenuator so that the input value of the digital-to-analog converter is , and read the mean value of the DC component of the output voltage value amplified by the weak signal amplifier of the homodyne detection module again , and the algorithm goes to Step 2).

2. The self-balanced quantum random number generator based on vacuum fluctuation measurement according to claim 1, wherein The laser is used to output continuous and stable laser light; The vacuum state generator is used to generate a vacuum state; The homodyne detection module realizes the measurement of the vacuum state; The weak signal amplifier is an operational amplifier, which realizes the amplification of the electrical signal; The analog-to-digital converter is a balun and an analog-to-digital conversion chip, which realizes the digital conversion of the electrical signal; The entropy evaluation module and the post-processing module are implemented using an FPGA chip.

3. The self-balanced quantum random number generator based on vacuum fluctuation measurement according to claim 1, characterized in that The laser light output by the laser interferes with the vacuum state output by the vacuum state generator as a local oscillator to obtain interference light; The beam splitter is a 50:50 beam splitter with a random polarization direction, which splits the interference light; the adjustable optical attenuator adjusts the light intensity of the split interference light to control the balance state of the homodyne detection module; The photodetector converts the optical signal into an electrical signal; the subtractor uses the electrical signal detected by the photodetector to obtain a differential current.

4. The self-balanced quantum random number generator based on vacuum fluctuation measurement according to claim 1, wherein The adjustable optical attenuator automatically adjusts the balance state of the light intensity between the upper arm and the lower arm of the adjustable optical attenuator through a self-balancing algorithm.

5. A method for using a self-balanced quantum random number generator based on vacuum fluctuation measurement, characterized in that, The self-balancing quantum random number generator based on vacuum fluctuation measurement according to any one of claims 1-4 includes: Step S1: Use the pulsed laser generated by the laser as the local oscillator light to enter one input end of a 50:50 beam splitter, and use the vacuum state generated by the vacuum state generator as the signal light to enter the other input end of the 50:50 beam splitter. The local oscillator light interferes with the vacuum state to obtain interference light; Step S2: The optical beam splitter divides the input interference light into two. The split interference light is adjusted in light intensity through an adjustable optical attenuator by a control module algorithm to control the balance state of the homodyne detection module; Step S3: The attenuated light is converted into an electrical signal by the photodetector, and a differential current is generated by the subtractor and sent to the weak signal amplifier for electrical signal amplification; Step S4: The amplified electrical signal is converted from an analog electrical signal to a digital electrical signal by the analog-to-digital converter, and the converted digital signal obtains the original data of the quantum random number generator; Step S5: The obtained original data is transmitted to the entropy evaluation module and the post-processing module to realize the processing of the original data and finally generate random numbers.

6. A device, characterized in that, The device includes: One or more processors; A storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, such that the one or more processors implement the steps of the method according to claim 5.

7. A computer-readable storage medium storing a computer program, characterized in that, The computer program, when executed by a processor, implements the steps of the method according to claim 5.

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