Random number generation method and system based on quantum tunneling effect

Abstract

The invention discloses a quantum tunneling effect-based random number generation method and system, the system comprises a composite entropy source module, a self-adaptive bias control module, a self-adaptive post-processing module and an output module, the composite entropy source module connects two types of physical effect entropy sources in parallel, and utilizes the noise characteristic complementation of the two types of physical effect entropy sources to improve the entropy value of an original random sequence, so that the random number generation efficiency is improved. The self-adaptive bias control module monitors two kinds of noise output in real time through a double-channel feedback circuit. According to the quantum random number generator, the composite entropy source is combined with the self-adaptive algorithm, so that the quantum random number generator with higher stability and high speed is realized. The method is high in technical maturity, and has a good application prospect in the information security fields such as electric power Internet of Things and mobile terminals.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of quantum random numbers and physical noise, and particularly relates to a random number generation method and system based on quantum tunneling effect. BACKGROUND

[0002] The existing quantum random number generation scheme based on quantum tunneling effect has the following limitations: on the one hand, a single entropy source is greatly disturbed by the environment, for example, the tunneling probability is greatly affected by temperature and bias, and the stability of the tunneling probability is insufficient; on the other hand, the post-processing algorithm cannot dynamically adapt to noise changes, affecting the randomness of the output sequence. SUMMARY

[0003] The present application provides a random number generation method and system based on quantum tunneling effect, aiming to realize a quantum random number generator with higher stability and rate by combining a composite entropy source with an adaptive algorithm.

[0004] The present application is realized by the following technical solutions:

[0005] A random number generation method based on quantum tunneling effect, generating a first random signal based on a first entropy source, generating a second random signal based on a second entropy source, using a feedback control circuit to monitor the state of the two entropy sources in real time, if one or both of the entropy sources are in a non-ideal noise state, mode one is entered; if both of the entropy sources are in an ideal noise state, mode two is entered; outputting random numbers through mode one or mode two;

[0006] Further, mode one includes the following steps: superimposing the first random signal and the second random signal through an adder to obtain a superimposed signal, converting the superimposed signal into a binary sequence A through an ADC, and processing the binary sequence A through a first post-processing algorithm to obtain an output random number sequence B;

[0007] Further, mode two includes the following steps: converting the first random signal and the second random signal into binary sequences C and D through TDC and ADC respectively, processing the binary sequences C and D through second and third post-processing algorithms respectively to obtain binary sequences E and F respectively, and performing XOR operation on the binary sequences E and F to obtain an output random number sequence G;

[0008] Further, the first entropy source includes any one of a single photon avalanche diode (SPAD), an avalanche photodiode (APD), and a CMOS; and the second entropy source includes any one of a Zener diode, a Schottky diode, and a standard silicon PN junction diode;

[0009] Further, the first, second and third post-processing algorithms each include any one of a Toeplitz Extractor, a Von Neumann Correction.

[0010] Further, on the basis of the above steps, a strategy for switching between mode one and mode two is further included, wherein the strategy includes setting a minimum frequency of mode switching, and if mode two is maintained for a long time, randomly switching to mode one.

[0011] A random number generation method system based on quantum tunneling effect includes a composite entropy source module, an adaptive bias control module, an adaptive post-processing module and an output module. The composite entropy source module connects a first entropy source and a second entropy source in parallel as an entropy source, uses the complementary noise characteristics of the two to improve the entropy value of the original random sequence. The adaptive bias control module monitors the two noise outputs in real time through a double-channel feedback circuit, monitors the working state of the two entropy sources in real time and switches modes, if one or both entropy sources are in a non-ideal noise state, enter mode one function module; if both entropy sources are in an ideal noise state, enter mode two function module; output random numbers through mode one function module or mode two function module; the output module integrates and serially converts the circuit and outputs the random number sequence in real time.

[0012] Further, the mode one function module includes an adder module, an ADC sampling module and a first post-processing module, wherein the adder module is used to superimpose the first random signal and the second random signal to obtain a superimposed signal; the ADC sampling module is used to convert the superimposed signal into a binary sequence A; the first post-processing module is used to process the binary sequence A through a first post-processing algorithm to obtain an output random number sequence B; wherein the first post-processing algorithm includes any one of a Toeplitz Extractor and a Von Neumann Correction.

[0013] Further, the mode two function module includes a TDC sampling module, an ADC sampling module, a second post-processing module, a third post-processing module and an XOR operation module; wherein the TDC sampling module is used to perform time-to-digital conversion on random pulses to extract a binary sequence through the parity of adjacent pulse intervals; the ADC sampling module is used to convert an analog signal into a binary sequence through sampling.

[0014] Further, the second and third post-processing algorithms each include any one of a Toeplitz Extractor algorithm, a Von Neumann Correction algorithm; and the exclusive or operation module is configured to calculate an exclusive or value of the two sequences.

[0015] The random number generation method and system based on quantum tunneling effect have the following beneficial effects:

[0016] (1) Stability: composite entropy source + double feedback control, dynamically switching post-processing strategies according to noise, ensuring the randomness quality and stability of the output sequence.

[0017] (2) High speed: adaptive post-processing algorithm dynamically switches according to noise state, improving the output rate. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The figure is a schematic diagram of the technical principle of the present application.

[0019] Figure 2 The figure is a schematic diagram of mode one in the technical principle of the present application.

[0020] Figure 3 The figure is a schematic diagram of mode two in the technical principle of the present application. DETAILED DESCRIPTION

[0021] The embodiments of the present application will be described in detail below with reference to the accompanying drawings: The present embodiments are implemented on the premise of the technical solution of the present application, and detailed implementation modes and specific operation processes are given, but the protection scope of the present application is not limited to the following embodiments.

[0022] A random number generation method based on quantum tunneling effect, as shown in Figure 1 , includes the following operation steps: generating a first random signal based on a first entropy source, generating a second random signal based on a second entropy source, using a feedback control circuit to monitor the state of the two entropy sources in real time, if one or both of the entropy sources is in a non-ideal noise state, mode one is entered; if both of the entropy sources are in an ideal noise state, mode two is entered; through mode one (as shown in Figure 2 ) or mode two (as shown in Figure 3The output random number is outputted; wherein, mode one includes the following steps: superimposing the first random signal and the second random signal by an adder to obtain a superimposed signal, converting the superimposed signal into a binary sequence A by an ADC, and processing the binary sequence A by a first post-processing algorithm to obtain an output random number sequence B; mode two includes the following steps: converting the first random signal and the second random signal into binary sequences C and D by a TDC and an ADC respectively, processing the binary sequences C and D by a second and a third post-processing algorithm respectively to obtain binary sequences E and F respectively, and performing an exclusive OR operation on the binary sequences E and F to obtain an output random number sequence G; wherein, the first entropy source includes any one of a single photon avalanche diode (SPAD), an avalanche photodiode (APD) and a CMOS; the second entropy source includes any one of a Zener diode, a Schottky diode and a standard silicon PN junction diode; the first, second and third post-processing algorithms include any one of a Toeplitz Extractor and a Von Neumann Correction.

[0023] In a possible embodiment, on the basis of the above steps, a strategy for switching between mode one and mode two is further included, wherein the strategy includes setting a minimum frequency of mode switching, and randomly switching to mode one if mode two is used for a long time.

[0024] A random number generation system based on quantum tunneling effect includes a composite entropy source module, an adaptive bias control module, an adaptive post-processing module and an output module; the features are as follows:

[0025] (1) Composite entropy source module: a Zener diode (tunneling effect, noise is smooth) and an avalanche diode SPAD (dark current tunneling effect, noise randomness is strong) are connected in parallel as entropy sources, the noise characteristics of the two are complementary, and the entropy value of the original random sequence is improved. The Zener diode branch works in reverse bias (close to the breakdown voltage 3.3V), uses the electron tunneling effect to generate random voltage fluctuations, and outputs a low-frequency noise signal (10kHz-1MHz). The SPAD branch works in Geiger mode, and uses the dark current tunneling effect to generate a random pulse signal without light source excitation, and outputs a high-frequency noise signal (1MHz-100MHz). In a possible embodiment, a 1N5230 Zener diode (reverse breakdown voltage 3.3V, reverse bias provided by a charge pump, connected in series with a 1kΩ current limiting resistor) and an APD210 avalanche diode are connected in parallel, working in Geiger mode, and the two noise signals are isolated by a 0.1μF capacitor.

[0026] (2) Adaptive bias control circuit: used to monitor the working state of two entropy sources in real time through a double-channel feedback circuit, that is, whether the reverse bias of the diode is in the target range capable of maintaining the tunneling probability at 48%-52% is measured in real time through a temperature sensor; the dark count rate of the SPAD or APD is counted in real time (sampling period 1ms) and it is judged whether it is in the target range (100k-200k counts / s), if it deviates from the target value (100k-200k counts / s), adjust the SPAD bias (range 20V-30V). If it deviates from the target range, it is determined that the entropy source is in a non-ideal noise state. In one possible embodiment, a temperature sensor output is used, which is linearly related to the current signal (1μA / ℃), which is input to the FPGA after I / V conversion, and the FPGA controls the charge pump output bias (range 2.5V-5V) through a PID algorithm; the FPGA samples the SPAD dark count rate at a sampling frequency of 10MHz, and a bias adjustment is triggered when the deviation exceeds 5%.

[0027] (3) Post-processing unit: the post-processing algorithm implements the above-mentioned first, second and third post-processing methods in the FPGA.

[0028] (4) Output module integrated and serial conversion circuit, supports SPI / I2C interface.

[0029] The above shows and describes the basic principles and main features of the present application and the advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only to illustrate the principles of the present application, and various changes and improvements can be made to the present application without departing from the spirit and scope of the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for generating random numbers based on the quantum tunneling effect, characterized in that, A first random signal is generated based on a first entropy source, and a second random signal is generated based on a second entropy source. A feedback control circuit is used to monitor the state of the two entropy sources in real time. If one or both entropy sources are in a non-ideal noise state, the system switches to mode one; if both entropy sources are in an ideal noise state, the system switches to mode two. Random numbers are output through mode one or mode two.

2. The random number generation method based on quantum tunneling effect according to claim 1, characterized in that, Mode 1 includes the following steps: superimposing the first random signal and the second random signal using an adder to obtain a superimposed signal; converting the superimposed signal into a binary sequence A using an ADC; and processing the binary sequence A using a first post-processing algorithm to obtain an output random number sequence B.

3. The random number generation method based on quantum tunneling effect according to claim 1, characterized in that, Mode 2 includes the following steps: converting the first random signal and the second random signal into binary sequences C and D respectively through TDC and ADC; processing the binary sequences C and D respectively using the second and third post-processing algorithms to obtain binary sequences E and F respectively; and performing an XOR operation on the binary sequences E and F to obtain the output random number sequence G.

4. The random number generation method based on quantum tunneling effect according to claim 1, characterized in that, The first entropy source includes any one of a single-photon avalanche diode (SPAD), avalanche photodiode (APD), or CMOS; the second entropy source includes any one of a Zener diode, a Schottky diode, or a standard silicon PN junction diode.

5. The random number generation method based on quantum tunneling effect according to claim 1, characterized in that, The first, second, and third post-processing algorithms each include either the Toeplitz Extractor algorithm or the Von Neumann Correction algorithm.

6. The random number generation method based on quantum tunneling effect according to claim 1, characterized in that, Based on the above steps, a strategy for switching between mode one and mode two is also included. The strategy includes setting a minimum frequency for mode switching. If the mode is in mode two for a long time, the mode will be randomly switched to mode one.

7. A system for a random number generation method based on quantum tunneling effect as described in claim 1, comprising a composite entropy source module, an adaptive bias control module, an adaptive post-processing module, and an output module. The composite entropy source module uses a first entropy source and a second entropy source connected in parallel as entropy sources, utilizing the complementary noise characteristics of the two to increase the entropy value of the original random sequence. The adaptive bias control module monitors the two noise outputs in real time through a dual-channel feedback circuit, and switches modes by monitoring the working state of the two entropy sources in real time. If one or both entropy sources are in a non-ideal noise state, it switches to the mode one function module; if both entropy sources are in an ideal noise state, it switches to the mode two function module. Random numbers are output through the mode one function module or the mode two function module. The output module integrates a parallel-to-serial conversion circuit and outputs the random number sequence in real time.

8. The system for a random number generation method based on quantum tunneling effect according to claim 7, characterized in that, The Mode 1 functional module includes an adder module, an ADC sampling module, and a first post-processing module. The adder module is used to superimpose a first random signal and a second random signal to obtain a superimposed signal. The ADC sampling module is used to convert the superimposed signal into a binary sequence A. The first post-processing module is used to process the binary sequence A using a first post-processing algorithm to obtain an output random number sequence B. The first post-processing algorithm includes either the Toeplitz Extractor algorithm or the Von Neumann Correction algorithm.

9. The system for a random number generation method based on quantum tunneling effect according to claim 7, characterized in that, The Mode 2 functional modules include: a TDC sampling module, an ADC sampling module, a second post-processing module, a third post-processing module, and an XOR operation module; wherein, the TDC sampling module is used to perform time-to-digital conversion on random pulses and extract binary sequences by the parity of adjacent pulse intervals; the ADC sampling module is used to convert analog signals into binary sequences through sampling.

10. The system for a random number generation method based on quantum tunneling effect according to claim 7, characterized in that, The second and third post-processing algorithms include either the Toeplitz Extractor algorithm or the Von Neumann Correction algorithm, respectively; the XOR operation module is used to calculate the XOR value of the two sequences.

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