Laser phase noise quantum random number generator

Abstract

The invention discloses a laser phase noise quantum random number generator which comprises a light source module, an unequal arm interference light path, a detection module, a sampling module, a control processing module and a driving module. The light source module generates light signals and outputs the light signals to the detection module through the unequal-arm interference light path, the detection module detects the intensity of the interference light signals, the sampling module carries out high-speed sampling on output results of the detection module, and sampling data of the sampling module is calculated and analyzed through the control processing module to obtain the size of phase drift. Then, an electric signal is generated through a driving module to load a compensation phase to the unequal arm interference light path to offset phase drift, so that the laser phase noise quantum random number generator reaches a stable state; and when the laser phase noise quantum random number generator reaches a stable state, the control processing module performs entropy evaluation and randomness extraction on the sampling data to generate a random sequence. Through the structural arrangement, the control precision and the feedback compensation speed are effectively improved.

Description

Technical Field

[0001] The present application belongs to the technical field of quantum random number generators, and in particular, relates to a laser phase noise quantum random number generator. Background Art

[0002] Practical quantum random number generators (QRNGs) can be divided into discrete and continuous schemes according to the dimensions of the measurement results. Among them, the detection output results of discrete QRNGs are discrete, with simple principles and clear physical models, but the random number generation rate is limited by factors such as the dead time, afterpulse, and time jitter of single-photon detectors. Currently, the fastest can only reach the order of 100Mbps. In contrast, continuous QRNGs have significant advantages in terms of generation rate. By adopting high-bandwidth photodetectors or coherent detectors, the current random number generation rate has reached the order of 100Gbps. Its representative schemes include measuring laser phase noise, measuring amplified spontaneous radiation noise, and measuring vacuum fluctuation noise. Among them, the laser phase noise measurement scheme detects and extracts the random phase fluctuations of the laser light field by constructing an unequal-arm interferometer optical path. The phase fluctuations of the laser light field originate from the spontaneous radiation of atoms inside the laser, which is a typical quantum random process. Therefore, it has good randomness and can be used to generate true random sequences. This scheme has received extensive attention and research since it was proposed, and its generation rate has been increased from the initial 100Mbps to 100Gbps. In particular, the interference optical path and detection devices used in this scheme can be integrated into chips based on technologies such as silicon-based photonics. Therefore, this scheme also has good prospects for miniaturization and chipization, and is expected to achieve low-cost mass production and large-scale practical applications in the future.

[0003] However, in the actual use environment, due to factors such as vibration and temperature changes, the unequal-arm interferometer optical path of the laser phase noise scheme QRNG will inevitably introduce additional phase drift. This phase drift caused by the environment usually changes randomly within [-π,π) at a frequency of the order of 100 Hz, and will significantly affect the statistical distribution of the detection results, thereby changing the minimum entropy of the original random sequence, which is not conducive to the stable and efficient generation of random numbers by the system. Therefore, it is necessary to compensate for the phase drift through certain technical means. At present, the unequal-arm interferometer optical path is generally phase modulated quickly through feedback control methods to offset the phase drift introduced by the environment. The basic principle is as follows: Figure 1 As shown, the laser generates an optical signal After the beam splitter (BS1), it is divided into two optical signals E1 and E2 with equal intensity. Compared with E2, E1 passes through an additional optical fiber delay line (DL). The two optical signals interfere at BS2 and output light fields E3 and E4. E3 is detected by the photodetector (PD) to obtain the current signal I (that is, the original random signal). The final random sequence can be obtained through analog-to-digital converter (ADC) sampling and data post-processing (PP); E4 is detected by the optical power meter (PM) as a feedback optical signal to obtain the current interference light intensity information, and then analyzed and calculated by the control unit (CU) to generate a feedback control signal. Finally, the piezoelectric controller (PC) receives the signal from the CU to generate a corresponding control voltage and load it onto the phase modulator (PS) to complete the phase feedback control. Specifically, the original random signal I can be expressed as

[0004] I=I0+I0·cos(ω0T d +Δθ(t)+φ s +φ c )

[0005] Where I0 is a constant related to the light field intensity, detector responsivity, etc., ω0 is the central angular frequency of the light field, T d is the delay introduced by DL. Δθ(t)=θ(t+T d )-θ(t) is the difference in the initial phase of the light field at different times, which is a zero-mean Gaussian random variable originating from the spontaneous radiation effect inside the laser, and is also the core object that needs to be extracted in this scheme. s The phase drift introduced by the environment, φ c is the compensation phase of the feedback control loading. Assuming ideally, there is no phase drift and phase feedback control, that is, φ s =φ c =0, then the signal I is

[0006] I=I0+I0·cos(ω0T d +Δθ(t))

[0007] where ω0T d is a constant, then ω0T d +Δθ(t) has a fixed statistical distribution characteristic, so the signal I can be sampled, minimum entropy evaluated, and randomness extracted to generate a random sequence. However, in actual systems, affected by environmental factors, φ s Generally, the random fluctuation of the frequency of 100Hz will directly affect the statistical distribution of the signal I, causing the minimum entropy of the acquisition result to change dynamically, making it impossible to perform stable randomness evaluation and extraction. Therefore, it is necessary to control φ through feedback. c To offset φ s The signal I is usually stabilized in the following state by phase compensation.

[0008] I t =I0+I0·cos(π / 2+Δθ(t))=I0+I0·sin(-Δθ(t))

[0009] At this time, the signal I t The statistical distribution is stable and has significant amplitude, which is conducive to generating random sequences.

[0010] However, this method relies on the optical power meter to measure and evaluate the intensity of the interfering optical signal to complete the feedback control. Its disadvantages are: 1) the optical power meter is an independent device with a large size, which increases the complexity of the system composition, and is particularly unfavorable for the miniaturization and integrated design of the QRNG system; 2) ordinary optical power meters have limited measurement accuracy and the measurement frequency is generally on the order of 10 Hz, while the frequency of phase drift change is on the order of 100 Hz, so it is difficult to achieve fast and accurate feedback control. Although the measurement frequency of high-speed optical power meters can far exceed the 10 kHz level, they are expensive, which significantly increases the system cost. Summary of the invention

[0011] The purpose of this application is to address the problems faced by the existing laser phase noise QRNG based on optical power meter to achieve phase feedback control, such as large size, high complexity, slow speed, limited accuracy, etc., and disclose a laser phase noise quantum random number generator. By adopting PD and ADC to detect and sample the interference light signal, it can quickly and in real time analyze the intensity of the interference light signal of the current QRNG system, quantify and calculate the phase drift size, and perform feedback control, thereby effectively improving the control accuracy and feedback compensation speed.

[0012] The purpose of this application is achieved through the following technical solutions:

[0013] A laser phase noise quantum random number generator, comprising: a light source module, an unequal-arm interference optical path, a detection module, a sampling module, a control processing module and a driving module;

[0014] The light source module generates a light signal and outputs it to the detection module through the unequal-arm interference optical path. The detection module detects the intensity of the interference light signal. The sampling module performs high-speed sampling on the output result of the detection module. The sampling data of the sampling module is calculated and analyzed by the control processing module to obtain the size of the phase drift. Then, the driving module generates an electrical signal to load the compensation phase on the unequal-arm interference optical path to offset the phase drift, so that the laser phase noise quantum random number generator reaches a stable state.

[0015] At the same time, when the laser phase noise quantum random number generator reaches a stable state, the control processing module performs entropy evaluation and randomness extraction on the sampled data to generate a random sequence.

[0016] According to a preferred embodiment, the initialization phase of the laser phase noise quantum random number generator includes:

[0017] First, power on, and the control processing module sets the compensation phase φ through the drive module. c = 0, the detection module performs photoelectric detection on the interference light signal to generate an output signal I = I0 + I0·cos(π / 2 + Δθ(t) + φ e ), where I0 is a constant related to the light field intensity and the detector responsivity, Δθ(t) is the difference in the initial phase of the light field at different times, and φ e is the equivalent phase drift of the output signal I compared to the target stable state;

[0018] The sampling module samples the detection output signal at a sampling rate of f s , the sampling data length is N, and then based on the sampling data {I1, I2, ... I N} Perform the following statistical calculations

[0019] I0=(max(I i )+min(I i )) / 2

[0020]

[0021] Among them, I b is the mean of the sampled data Normalized bias compared to I0.

[0022] According to a preferred embodiment, the control stage of the laser phase noise quantum random number generator includes:

[0023] According to the normalized bias I calculated in the initialization phase b , the control processing module completes the equivalent phase drift φ e Calculate and then load the compensation phase φ to the unequal arm optical path through the driving module c To offset the effect of phase drift.

[0024] According to a preferred embodiment, in the control stage, the control processing module is controlled according to I b Calculate the equivalent phase shift φ e The size process includes:

[0025] When I b >0,φ e <0,φ e The value of is φ1 or φ2, where: φ1 = -arcsin(I b ), φ2=-π-φ1;

[0026] When I b<0,φ e >0, the value of φ4 is φ3 or φ4, where: φ3=-arcsin(I b ),φ4=π-φ3.

[0027] According to a preferred embodiment, in the control stage, the control processing module e Calculate the compensation phase φ c and its modulation voltage V c Size, including:

[0028] φ c =-φ e

[0029]

[0030] Where V π is the half-wave voltage of the phase modulator.

[0031] According to a preferred embodiment, in the control stage, the control processing module applies a modulation voltage V to the phase modulator in the unequal-arm interferometer through the driving module. c and determine the compensation effect;

[0032] When I b >0,φ e The value is φ1 or φ2, so the corresponding V c The values ​​are:

[0033] or

[0034] When I b <0, the corresponding V c The values ​​are:

[0035] or

[0036] According to a preferred embodiment, when I b >0, the control processing module firstly converts V c1 Load it to the phase modulator and collect data to calculate its normalized offset I b1 ; Then V c2 Load it to the phase modulator and collect data to calculate its normalized offset I b2 , so according to I b1 ,I b2 The absolute value of V determines the correct modulation voltage r , that is |I b1 |<|I b2 |, then V r =V c1 ;|Ib1 |>|I b2 |, then V r =V c2 .

[0037] According to a preferred embodiment, when I b When <0, the control processing module firstly converts V c3 Load it to the phase modulator and collect data to calculate its normalized offset I b3 ; Then V c4 Load it to the phase modulator and collect data to calculate its normalized offset I b4 , so according to I b3 ,I b4 The absolute value of V determines the correct modulation voltage r , that is |I b3 |<|I b4 |, then V r =V c3 ;|I b3 |>|I b4 |, then V r =V c4 .

[0038] According to a preferred embodiment, the stabilization phase of the laser phase noise quantum random number generator includes:

[0039] In the process of generating random sequences, the normalized bias I is calculated based on the sampled data. b To conduct real-time dynamic feedback control to maintain a stable state;

[0040] When I b Its absolute value is less than the preset threshold I th When |I b | th , it is considered that the laser phase noise quantum random number generator is in a controllable stage. At this time, the modulation voltage is fine-tuned through the PID algorithm, and the system generates random sequences normally;

[0041] When I b Its absolute value is greater than the preset threshold I th When |I b |>I th , it is considered that the laser phase noise quantum random number generator is in an uncontrollable stage, stops outputting random number sequences, and re-executes the system initialization stage and control stage processes to ensure that the system returns to a stable state.

[0042] ​The aforementioned main scheme of the present application and its further options can be freely combined to form multiple schemes, all of which are schemes that can be adopted and claimed for protection in the present application. After understanding the scheme of the present application, those skilled in the art can understand that there are multiple combinations based on the prior art and common knowledge, all of which are technical schemes to be protected by the present application, and they are not exhaustively listed here.

[0043] Beneficial effects of this application:

[0044] This application uses PD and ADC to detect and sample the interference light signal, which can quickly and in real time analyze the intensity of the interference light signal of the current QRNG system, quantify the phase drift size and perform feedback control, effectively improving the control accuracy and speed. In particular, the QRNG solution proposed in the present invention can be integrated into a chip using optical and electrical integration processes such as silicon-based photonics or CMOS, which can reduce system costs while improving design integration. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is the basic principle diagram of the laser phase noise QRNG system;

[0046] Figure 2 is the normalized bias with φ e Change curve;

[0047] Figure 3 This is a schematic diagram of the basic structure of the laser phase noise quantum random number generator of this application;

[0048] Figure 4 This is a schematic diagram of a first embodiment of the laser phase noise quantum random number generator of the present application;

[0049] Figure 5 This is a schematic diagram of a second embodiment of the laser phase noise quantum random number generator of the present application;

[0050] Figure 6 This is a schematic diagram of a third embodiment of the laser phase noise quantum random number generator of the present application;

[0051] Figure 7 This is a schematic diagram of a fourth embodiment of the laser phase noise quantum random number generator of the present application;

[0052] Figure 8 It is a schematic diagram of a fifth embodiment of the laser phase noise quantum random number generator of the present application;

[0053] Fig. 9 This is a schematic diagram of the sixth embodiment of the laser phase noise quantum random number generator of the present application. DETAILED DESCRIPTION

[0054] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0055] It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0056] It should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the application is usually placed when in use. They are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0057] In the description of this application, it should also be noted that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0058] In addition, the present application would like to point out that, in the present application, unless the specific structure, connection relationship, positional relationship, power source relationship, etc. are specifically written out, the structure, connection relationship, positional relationship, power source relationship, etc. involved in the present application are all known by those skilled in the art on the basis of the prior art without creative work.

[0059] The output signal I of the system can be expressed as

[0060] I=I0+I0·cos(ω0I d +Δθ(t)+φ s +φ c )

[0061] =I0+I0·cos[π / 2+Δθ(t)+(φ s +ω0T d -π / 2)+φ c ]

[0062] =I0+I0·cos(π / 2+Δθ(t)+φ e +φ c )

[0063] where φ e =φ s +ω0T d -π / 2 can be viewed as the output signal I compared to the target steady state I t The equivalent phase drift of c Make φ e +φ c = 0 to achieve a stable effect, so how to analyze and calculate φ c The size of is the key to the problem.

[0064] When setting φ c =0, the output signal I can be expressed as

[0065] I=I0+I0·cos(π / 2+Δθ(t)+φ e )

[0066] At this time, the output signals are Δθ(t) and φ c function. Among them, Δθ(t) is a zero-mean Gaussian random variable and changes very quickly, up to the GHz level; and φ c The size of φ depends entirely on s The changing frequencies of the two are consistent, both at the order of 100 Hz, which is much smaller than the changing speed of Δθ(t). e The sampling rate of the changing frequency samples the output signal in a short time, and the φ contained in the sampled data can be considered e Basically unchanged, further by calculating the mean of the sampled data The influence of Δθ(t) can be smoothed out, that is

[0067]

[0068] Where N is the length of the sampled data for calculating the signal mean, T s =1 / f s is the sampling period, f s Sampling frequency. Considering φ e The frequency of change is on the order of 100 Hz, so in order to ensure that the sampling time is within φ e Basically unchanged, the sampling frequency f sThe sampling frequency must be 10kHz, 100kHz or above, and the overall sampling time T = N·T s It must be controlled within 10ms. The normalized offset of the mean of the sampled data compared to I0 can be further calculated as

[0069]

[0070] I b Only with φ e The relationship is related and is a trigonometric function. Given a laser line width Δf = 10 MHz, a delay T d =0.5ns and other typical conditions, set N = 1000, f s =500kHz Calculated output signal normalized offset I b Follow φ e The simulation curve changes as Figure 2 shown.

[0071] from Figure 2 It can be seen that the following rules exist:

[0072] 1) When φ e <0, I b >0; when φ e >0, I b <0.

[0073] 2) When φ e <0, for a normalized bias value, φ e There are two possible values ​​φ1 and φ2 corresponding to it, and φ1+φ2=-π;

[0074] 3) When φ e >0, for a normalized bias value, φ e There are two possible values ​​φ3 and φ4 corresponding to it, and φ3+φ4=π.

[0075] Therefore, according to the normalized offset calculated from the sampled data, the equivalent phase drift φ at this time can be derived: e The possible value of φ is then compensated by PS modulation c =-φ e , and determine φ based on the normalized offset after modulation e Phase feedback control can be completed by accurately compensating the phase.

[0076] In summary, the present application discloses a laser phase noise quantum random number generator, such as Figure 3 The laser phase noise quantum random number generator comprises: a light source module, an unequal-arm interference optical path, a detection module, a sampling module, a control processing module and a driving module.

[0077] Among them, the light source module generates a light signal and outputs it to the detection module through the unequal-arm interference light path. The detection module detects the intensity of the interference light signal. The sampling module performs high-speed sampling on the output result of the detection module. The sampling data of the sampling module is calculated and analyzed by the control processing module to obtain the size of the phase drift, and then the driving module generates an electrical signal to load the compensation phase on the unequal-arm interference light path to offset the phase drift, so that the laser phase noise quantum random number generator reaches a stable state; at the same time, when the laser phase noise quantum random number generator reaches a stable state, the control processing module performs entropy value evaluation and randomness extraction on the sampling data to generate a random sequence.

[0078] The detailed working principle and steps are as follows.

[0079] Step 1: Initialization phase. First, power on the QRNG system, and the control processing module sets the compensation phase φ through the drive module. c = 0, the detection module performs photoelectric detection on the interference light signal to generate an output signal I = I0 + I0·cos(π / 2 + Δθ(t) + φ e ). The sampling module samples the detection output signal at a sampling rate of f s , the sampling data length is N. Among them, f can be set according to the actual environment s is 10kHz, 100kHz, 1MHz, 1GHz, etc., and N is 1000, 10000, 100000, 1000000, etc. Then based on the sampling data {I1,I2,...I N} Perform the following statistical calculations:

[0080] I0=(max(I i )+min(I i )) / 2

[0081]

[0082] In addition to the statistical calculation based on the sampling data according to the above method, the calculation of I0 can also be obtained by calibrating the detection output signal using an oscilloscope. In the initialization stage, the QRNG system does not generate the final random sequence.

[0083] Step 2: Control phase. According to the normalized bias I calculated in the initialization phase b , the control processing module further calculates the equivalent phase drift φ e , and then the compensation phase φ is loaded to the unequal arm optical path through the driving module c =-φ e To offset the influence of phase drift, the detailed process is as follows.

[0084] 1) Control processing module according to I bCalculate the equivalent phase shift φ e The size process includes:

[0085] When I b >0,φ e <0,φ e The value of is φ1 or φ2, where: φ1 = -arcsin(I b ), φ2=-π-φ1;

[0086] When I b <0,φ e >0,φ e The value of is φ3 or φ4, where: φ3=-arcsin(I b ),φ4=π-φ3.

[0087] 2) The control processing module is based on φ e Calculate the compensation phase φ c and its modulation voltage V c Size, including:

[0088] φ c =-φ e

[0089]

[0090] Where V π is the half-wave voltage of the phase modulator.

[0091] 3) The control processing module applies the modulation voltage V to the phase modulator in the unequal arm interferometer through the driving module. c and determine the compensation effect;

[0092] When I b >0,φ e The value is φ1 or φ2, so the corresponding V c The values ​​are:

[0093] or

[0094] Therefore, the control processing module needs to firstly pass V c1 Load it to the phase modulator and collect data to calculate its normalized offset I b1 ; Then V c2 Load it to the phase modulator and collect data to calculate its normalized offset I b2 The normalized bias corresponding to the correct modulation voltage should be close to 0 in theory, so according to I b1 ,I b2 The absolute value of can determine the correct modulation voltage V r , that is |I b1|<|I b2 |, then V r =V c1 ;|I b1 |>|I b2 |, then V r =V c2 .

[0095] When I b <0, the corresponding V c The values ​​are:

[0096] or

[0097] When I b When <0, the control processing module firstly converts V c3 Load it to the phase modulator and collect data to calculate its normalized offset I b3 ; Then V c4 Load it to the phase modulator and collect data to calculate its normalized offset I b4 , so according to I b3 ,I b4 The absolute value of V determines the correct modulation voltage r , that is |I b3 |<|I b4 |, then V r =V c3 ;|I b3 |>|I b4 |, then V r =V c4 .

[0098] Step 3: Stabilization phase. After the control phase, it can be considered that the correct compensation phase has been loaded through feedback control, and the system has reached the expected stable state. At this time, the final random sequence can be generated. However, since the phase drift changes with time, the system still needs to calculate the normalized bias I based on the sampled data. b To perform real-time dynamic feedback control to maintain a stable state.

[0099] When I b Its absolute value is less than the preset threshold I th When |I b | th , it is considered that the laser phase noise quantum random number generator is in a controllable stage. At this time, the modulation voltage is fine-tuned through the PID algorithm, and the system generates random sequences normally;

[0100] When I b Its absolute value is greater than the preset threshold I th When |I b |>I​th , it is considered that the laser phase noise quantum random number generator is in an uncontrollable stage, stops outputting random number sequences, and re-executes the aforementioned steps 1 and 2 to ensure that the system returns to a stable state.

[0101] Example 1

[0102] refer to Figure 4 As shown, based on the above principle scheme, a typical embodiment can be constructed based on discrete optoelectronic devices, using PD and ADC to detect and sample the interference light signal, and using a programmable logic gate array (FPGA) as a control processing module. On the one hand, it completes the feedback control related calculations and loads the compensation phase of the interference light path through a digital-to-analog converter (DAC) to keep the system stable; on the other hand, it completes data post-processing to generate the final random sequence.

[0103] Example 2

[0104] refer to Figure 5 As shown, on the basis of Example 1, a typical example 2 can be constructed based on discrete optoelectronic devices. The PD detection output signal is simultaneously input to ADC1 and ADC2 for sampling, wherein the ADC1 sampling result is output to a microcontroller (MCU) or a digital signal processor (DSP) to complete feedback control related calculations; the ADC2 sampling result is output to the FPGA to generate the final random sequence. Compared with Example 1, the phase feedback control and random number generation functions can be implemented in parallel, effectively reducing the complexity of FPGA control logic and hardware resource requirements, while improving system work efficiency.

[0105] Example 3

[0106] refer to Figure 6 As shown, on the basis of Example 2, a typical example 3 can be constructed based on discrete optoelectronic devices. PD1 and PD2 are used to detect the two output optical signals of BS2 respectively. Compared with Example 2, the interference optical signal can be fully utilized to improve the detection output intensity. At the same time, the bandwidth and responsivity of PD1 and PD2 and the sampling rate and bit number of ADC1 and ADC2 and other key performance parameters can be flexibly adjusted according to actual needs, thereby reducing hardware costs.

[0107] Embodiments 4 to 6

[0108] refer to Figures 7 to 9As shown, embodiments 1-3 can be integrated into chips based on optical and electrical integration processes. They include optical chip and electrical chip parts respectively. The optical chip part includes an indium phosphide (InP) platform part and a silicon-based (SOI) part. The InP part mainly realizes the integration of laser light sources, and the SOI part mainly realizes the integration of unequal arm interferometers and PDs. The electrical chip part can realize the integration of devices such as ADC, MCU, DSP, FPGA, DAC based on the CMOS platform, and can also realize all electrical chip functions by designing application-specific integrated circuits (ASICs) to further improve the design integration. Compared with embodiments 1-3 implemented using discrete optoelectronic devices, embodiments 4-6 use an integrated process to realize the chip integration of light and electricity of the QRNG system, which significantly reduces the system volume while having the prospect of low cost and large-scale mass production, and can also use optoelectronic packaging technology to further improve the design integration, significantly improving the level of practicality.

[0109] This application uses PD and ADC to detect and sample the interference light signal, which can quickly and in real time analyze the intensity of the interference light signal of the current QRNG system, quantify the phase drift size and perform feedback control, effectively improving the control accuracy and speed. In particular, the QRNG solution proposed in the present invention can be integrated into a chip using optical and electrical integration processes such as silicon-based photonics or CMOS, which can reduce system costs while improving design integration.

[0110] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A laser phase noise quantum random number generator, characterized in that: The laser phase noise quantum random number generator comprises: a light source module, an unequal-arm interference optical path, a detection module, a sampling module, a control processing module and a driving module; The light source module generates a light signal and outputs it to the detection module through the unequal-arm interference optical path. The detection module detects the intensity of the interference light signal. The sampling module performs high-speed sampling on the output result of the detection module. The sampling data of the sampling module is calculated and analyzed by the control processing module to obtain the size of the phase drift. Then, the driving module generates an electrical signal to load the compensation phase on the unequal-arm interference optical path to offset the phase drift, so that the laser phase noise quantum random number generator reaches a stable state. At the same time, when the laser phase noise quantum random number generator reaches a stable state, the control processing module performs entropy evaluation and randomness extraction on the sampled data to generate a random sequence.

2. The laser phase noise quantum random number generator according to claim 1, characterized in that: The initialization stage of the laser phase noise quantum random number generator includes: First, power on, and the control processing module sets the compensation phase φ through the drive module. c = 0, the detection module performs photoelectric detection on the interference light signal to generate an output signal I = I0 + I0·cos(π / 2 + Δθ(t) + φ e ), where I0 is a constant related to the light field intensity and the detector responsivity, Δθ(t) is the difference in the initial phase of the light field at different times, and φ e is the equivalent phase drift of the output signal I compared to the target stable state; The sampling module samples the detection output signal at a sampling rate of f s , the sampling data length is N, and then based on the sampling data {I1, I2, ... I N } Perform the following statistical calculations I0=(max(I i )+min(I i )) / 2 Among them, I b is the mean of the sampled data Normalized bias compared to I0.

3. The laser phase noise quantum random number generator according to claim 2, characterized in that: The control stage of the laser phase noise quantum random number generator includes: According to the normalized bias I calculated in the initialization phase b , the control processing module completes the equivalent phase drift φ e Calculate and then load the compensation phase φ to the unequal arm optical path through the driving module c To offset the effect of phase drift.

4. The laser phase noise quantum random number generator according to claim 3, characterized in that: In the control stage, the control processing module is based on I b Calculate the equivalent phase shift φ e The size process includes: When I b >0,φ e <0,φ e The value of is φ1 or φ2, where: φ1 = -arcsin(I b ), φ2=-π-φ1; When I b When <0, φ e >0,φ e The value of is φ3 or φ4, where: φ3=-arcsin(I b ),φ4=π-φ3.

5. The laser phase noise quantum random number generator according to claim 4, characterized in that: In the control stage, the control processing module is based on φ e Calculate the compensation phase φ c and its modulation voltage V c Size, including: f c =-φ e Where V π is the half-wave voltage of the phase modulator.

6. The laser phase noise quantum random number generator according to claim 5, characterized in that: In the control stage, the control processing module applies the modulation voltage V to the phase modulator in the unequal-arm interferometer through the driving module. c and determine the compensation effect; When I b >0,φ e The value is φ1 or φ2, so the corresponding V c The values ​​are: or When I b <0, the corresponding V c The values ​​are: or 7. The laser phase noise quantum random number generator according to claim 6, characterized in that: When I b >0, the control processing module firstly converts V c1 Load it to the phase modulator and collect data to calculate its normalized offset I b1 ; Then V c2 Load it to the phase modulator and collect data to calculate its normalized offset I b2 , so according to I b1 ,I b2 The absolute value of V determines the correct modulation voltage r , that is |I b1 |<|I b2 |, then V r =V c1 ;|I b1 |>|I b2 |, then V r =V c2 .

8. The laser phase noise quantum random number generator according to claim 6, characterized in that: When I b When <0, the control processing module firstly converts V c3 Load it to the phase modulator and collect data to calculate its normalized offset I b3 ; Then V c4 Load it to the phase modulator and collect data to calculate its normalized offset I b4 , so according to I b3 ,I b4 The absolute value of V determines the correct modulation voltage r , that is |I b3 |<|I b4 |, then V r =V c3 ;|I b3 |>|I b4 |, then V r =V c4 .

9. The laser phase noise quantum random number generator according to claim 1, characterized in that: The stabilization phase of the laser phase noise quantum random number generator includes: In the process of generating random sequences, the normalized bias I is calculated based on the sampled data. b To conduct real-time dynamic feedback control to maintain a stable state; When I b Its absolute value is less than the preset threshold I th When |I b |<I th , it is considered that the laser phase noise quantum random number generator is in a controllable stage. At this time, the modulation voltage is fine-tuned through the PID algorithm, and the system generates random sequences normally; When I b Its absolute value is greater than the preset threshold I th When |I b |>I th , it is considered that the laser phase noise quantum random number generator is in an uncontrollable stage, stops outputting random number sequences, and re-executes the system initialization stage and control stage processes to ensure that the system returns to a stable state.

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