TWI757694B - Method of generating true random numbers based on quantum computing - Google Patents

Abstract

A method of generating true random numbers based on quantum computing is provided. A computer apparatus receives a plurality of classical binary bits generated by measurement of a plurality of qubits from a quantum computer via network and stores the classical binary bits in a storage module, loads and removes the classical binary bits with a length corresponding to a random range from the storage module as a random sequence, executes a process of transforming format on the random sequence for obtaining a random number and outputs the random number. The present disclosed example can effectively provide the true random numbers being unpredictable and without repeatability, and improve the credibility of application based on the random numbers.

Description

Generating method of true random numbers based on quantum operation

The present invention is related to quantum operations, and particularly relates to a method for generating true random numbers based on quantum operations.

Most of the existing random number generation methods use pseudo random technology. The above simulation random number technology is to set a random number seed (seed) first, and execute a random number algorithm based on the random number seed to generate a random number.

Since the existing random number generation method uses a fixed random number seed and a random number algorithm to generate random numbers, there is actually a law among the generated random numbers, which can be predicted and repeated.

Furthermore, when the random value can be predicted or repeated, the application based on the random value (such as encryption and decryption or casino games) will be at risk of being cracked.

Therefore, the existing methods for generating analog random numbers have the above problems, and more effective solutions are urgently needed.

The main purpose of the present invention is to provide a method for generating true random numbers based on quantum operations, which can generate true random numbers.

In order to achieve the above-mentioned object, the present invention provides a method for generating true random numbers based on quantum operations, comprising the following steps: a) receiving multiple data obtained by performing measurements on multiple qubits from a quantum computer via a network in a computer device; b) store a plurality of classical bits in the storage module of the computer device; c) read a plurality of classical bits of corresponding length from the storage module based on the random number range requested by the random number as a random number sequence , and delete a plurality of classical bits read from the storage module; d) perform format conversion processing on the random number sequence to obtain random values; and, e) output random values.

The present invention can effectively generate unpredictable and non-repetitive real random numbers, and can improve the reliability of random number applications.

1: Computer equipment

100: Processing modules

101: Network Modules

102: Human Machine Interface

103: Storage Module

1030: Random Number Generation Program

1031: Classical bit buffer

104: Function module

2: Quantum Computer

20: Cloud Application Platform

200: Quantum Computer Program

3: Internet

4: External computer equipment

50-52, 70: Hadamard logic gate

60-62, 83: measurement logic gate

7, 8: Quantum logic circuits

71, 72, 81: single control inverse logic gate

80, 82: double control inverse logic gate

S10-S14: The first random number generation step

S20-S22: Ignore error measurement steps

S30-S32, S40-S43: Considering the error measurement steps

S50-S59: the second random number generating step

S60-S64: The third random number generation step

S70-S72: Fourth random number generation step

S80-S81: Random number application steps

FIG. 1 is a structural diagram of a true random number generation system according to an embodiment of the present invention.

FIG. 2 is a flowchart of a method for generating a true random number according to the first embodiment of the present invention.

FIG. 3 is a partial flowchart of a method for generating a true random number according to a second embodiment of the present invention.

FIG. 4 is a partial flowchart of a method for generating a true random number according to a third embodiment of the present invention.

FIG. 5 is a flowchart of a method for generating a true random number according to a fourth embodiment of the present invention.

FIG. 6 is a partial flowchart of a method for generating a true random number according to a fifth embodiment of the present invention.

FIG. 7 is a partial flowchart of a method for generating a true random number according to a sixth embodiment of the present invention.

FIG. 8 is a partial flowchart of a method for generating a true random number according to a seventh embodiment of the present invention.

FIG. 9 is a structural diagram of a quantum logic circuit according to an embodiment of the present invention.

FIG. 10 is a structural diagram of a quantum logic circuit according to an embodiment of the present invention.

Hereinafter, several preferred embodiments of the present invention will be described in detail in conjunction with the drawings.

At present, most computer equipments use classical binary bits as the smallest data unit for operation or storage. Classical bits can only be set to one of 0 and 1.

Compared with classical bits, quantum bits (Qubits) are described by vectors, and the quantum state can be 0 or 1 during the operation process, and a definite quantum state (such as 0 or 1) can only be obtained after measurement. ). Also, when the qubit is in a superposition, the probability of being 0 and the probability of being 1 are both 50%.

Specifically, classical bits and qubits mainly have the following differences:

1. The quantum state of a qubit is described by a normalized vector, which can be represented by an abstract Dirac Notation, namely |0> and |1>; classical bits are represented by A value of 0 or 1 is used to describe it.

Second, because the quantum state is a vector, a single qubit can be in a linear superposition of |0> and |1>; a classical bit cannot be described by a superposition state.

3. When multiple qubits interact with each other, they are in a state of quantum entanglement, that is, when the state of one qubit changes, it will instantly affect the other qubit; multiple classical bits are independent of each other, There is no interaction.

Fourth, the measurement results of qubits are related to the selected measurement substrate, and the measurement substrate can affect the probability of each measurement result (quantum state) of the measurement result; the classical bit does not need to be measured. Furthermore, it has been proposed in the related art that 0 and 1 can be randomly generated by using an appropriate measurement substrate so that different measurement results (eg, 0 and 1) of the qubit have the same probability. In addition, the above-mentioned making different measurement results of qubits have the same probability is a common technique in the field of quantum computing, and will not be repeated here.

First, please refer to FIG. 1 , which is a structural diagram of a real random number generation system according to an embodiment of the present invention.

In order to solve the problem that the existing analog random numbers can be predicted and repeated, the present invention proposes a real random number generation method, which is applied to the true random number generation system shown in FIG. 1 . The true random number generation method of the present invention can generate random classical bits based on quantum operations to generate true random numbers. Moreover, since the measurement results of qubits are truly random, that is, unpredictable and repeatable, the measurement results can be used to generate real random numbers.

Specifically, the true random number generation system of the present invention mainly includes a computer device 1 and at least one quantum computer 2 (a plurality of quantum computers 2 are taken as an example in FIG. 1 ).

Computer equipment 1 is a general-purpose computer (such as smart phones, notebook computers, tablet computers, personal computers, smart wearable devices, and other electronic computers or traditional computers), which are mainly composed of a large number of integrated circuits and are used based on classical bits. (0 and 1) perform operations and data storage.

Each quantum computer 2 performs operations and data storage based on qubits. Quantum computer 2 is a common computer device in the field of quantum computing, and its detailed architecture and operating principles will not be repeated here.

In one embodiment, the quantum computer 2 is used as a cloud server to provide specified cloud services through quantum computing. Specifically, the quantum computer 2 may include a cloud application platform 20, and the cloud application platform 20 may be used to execute a quantum computer program 200 for implementing quantum algorithms, thereby providing the aforementioned cloud services (eg, generating random classical bits through quantum algorithms) ).

The computer equipment 1 mainly includes a network module 101, a human-machine interface 102, a storage module 103, and a processing module 100 electrically connected to the above-mentioned modules.

The network module 101 (such as a mobile network module or a Wi-Fi network module, etc.) is used to connect to the network 3 (such as the Internet), and can connect to the remote quantum computer 2 through the network 3 to Perform data transfers (eg request/receive random classical bits).

The human-machine interface 102 may include input devices (eg, keyboard, mouse, and/or touchpad, etc.) and output devices (eg, speakers, indicator lights, and/or displays, etc.), and is used to interact with the user (eg, presentations described later). random value).

The storage module 103 may include a transient computer-readable medium (such as RAM) and a non-transitory computer-readable medium (such as ROM, flash memory, solid state drive, magnetic hard disk, etc.), and is used for storage material.

In one embodiment, the non-transitory computer-readable medium may include the random number generator 1030 . The computer program 1030 records a computer-executable program code. After the processing module 100 executes the aforementioned program code, the method for generating a random number according to various embodiments of the present invention described later can be executed.

In one embodiment, the storage module 103 further includes a classical bit buffer 1031 . The classical bit buffer 1031 can be a transient computer-readable medium or a non-transitory computer-readable medium, which is not limited, and is used for storing classical bits received from the quantum computer 2 .

The processing module 100 (eg, CPU, MCU, GPU or other processors) is used to control the operation of each module of the computer device 1 .

In one embodiment, the computer device 1 further includes one or more functional modules 104 (one functional module 104 is taken as an example in FIG. 1 ). The function module 104 is electrically connected to the processing module 100 for realizing a specific function.

For example, when the functional module 104 is a camera, an image of the environment can be captured and provided to the processing module 100 for processing; when the functional module 104 is a person detector (such as a PIR sensor), it can detect Whether the tester enters the environment; when the function module 104 is a gaming machine, it can operate according to the data (such as random values) provided by the processing module 100; when the function module 104 is a security module (such as encryption/decryption) module or verification module), the data can be encrypted/decrypted or verified.

In one embodiment, the real random number generation system further includes an external computer device 4 . The external computer device 4 (such as a gaming machine, a storage device with encryption/decryption function, or an encryption/decryption device, etc.) is a general-purpose computer and is connected to the network 3 . The external computer device 4 can obtain data (such as control commands) from the computer device 1 via the network 3 or random values), and operate according to the received data (such as generating game results, performing data encryption/decryption, etc.).

Please also refer to FIG. 2 , which is a flowchart of a method for generating a true random number according to the first embodiment of the present invention. The method for generating a true random number in this embodiment includes the following steps.

Step S10 : the processing module 100 of the computer device 1 controls the network module 101 to receive a plurality of classical bits from the quantum computer 2 via the network 3 . Specifically, the quantum computer 2 can perform measurement on a plurality of qubits to obtain a plurality of randomly generated classical bits, and transmit these classical bits to the computer device 1 .

Step S11 : the processing module 100 stores the received classical bits in the classical bit buffer 1031 of the storage module 103 .

Step S12: The processing module 100 reads a plurality of classical bits of the corresponding length from the classical bit buffer 1031 of the storage module 103 based on the random number range (eg, 1 to 10, or -100 to -100, etc.) of the random number request. The bits are used as a random number sequence, and a plurality of classical bits read from the classical bit buffer 1031 are deleted, that is, the used classical bits are deleted.

Step S13: The processing module 100 performs format conversion processing on the random number sequence to obtain random values.

In one embodiment, the processing module 100 processes the random number according to the random number format (such as 1's complement, 2's complement, decimal or hexadecimal, etc.) required by the random number request. Sequences perform format conversion to produce garbled values that match the format.

In one embodiment, the processing module 100 directly converts the random number sequence from binary to carry

Step S14: The processing module 100 outputs random values. Specifically, the processing module 100 can display the random value, read the random value through the man-machine interface 102, or transmit the random value to the external computer device 4 through the network module 101 and the network 3, which is not limited.

In this way, the present invention can effectively generate unpredictable and non-repetitive real random numbers, and can improve the reliability of random number applications.

In an example, if the random number request requires five random numbers (number of random numbers) between 0 and 127 (random number range), the processing module 100 reads 8 random numbers from the classical bit buffer 1031 at a time. classical bits (8 bits can represent all positive integers from 0 to 127 in decimal) as a random number sequence to calculate a random value, and perform the aforementioned reading and calculation five times (40 bits in total) to obtain five random value.

In another example, if the random number request is for a random number (number of random numbers) between -4 and +4 (random number range), the processing module 100 reads from the classical bit buffer 1031 4 classical bits are used as a random number sequence (4 bits can represent all integer values from -7 to +7 in decimal) to calculate a random value, and when the random value exceeds the random number range (such as -5 or 6) ), read and calculate again until the obtained random value meets the random number range.

In one embodiment, the classical bit buffer 1031 is a first-in-first-out memory (such as a register, a buffer, a flash memory, etc.) etc.), step S11 is to store a plurality of classical bits in the classical bit buffer 1031 in a first-in, first-out manner, and step S12 is to read a plurality of classical bits from the classical bit buffer 1031 in a first-in, first-out manner Yuan. In other words, the classical bit (group) of the classical bit buffer 1031 that is stored the earliest will be read out the earliest.

In one embodiment, the computer device 1 can repeatedly perform steps S10 - S11 to fill up the classical bit buffer 1031 . In this way, when the computer device 1 receives a random number request, it can directly execute steps S12-S14 to output the random value, thereby saving the waiting time of steps S10-S11.

In one embodiment, the computer device 1 executes steps S10-S11 to obtain random classical bits only when receiving a random number request, and then executes steps S12-S14 to output a random value.

Please refer to FIG. 1 to FIG. 3 together. FIG. 3 is a partial flowchart of a method for generating a true random number according to a second embodiment of the present invention. FIG. 3 is used to describe step S10 of FIG. 2 in more detail.

In this embodiment, in order to improve the measurement efficiency of the qubit, the error of the quantum computer is directly ignored, and the measurement is directly performed and the measurement result is used to generate a random value.

Specifically, step S10 may include the following steps S20-S22.

Step S20 : the quantum computer 2 performs the Hadamard logic gate operation on each qubit respectively, so that each qubit becomes a superposition state. The Hadamard logic gate operation is a common technique in the field of quantum computing, and is mainly used to turn qubits into a superposition state (ie, in a linear superposition of |0> and |1>), and the details of its calculation will not be repeated here.

Step S21: The quantum computer 2 performs measurement processing on each qubit in the superposition state, respectively, to measure the quantum state of each qubit to obtain a classical bit. The quantum computer 2 can generate a plurality of classical bits by separately performing measurements on a plurality of qubits.

In an embodiment, in order to obtain better execution efficiency, the quantum computer 2 performs measurements on three qubits each time to obtain three classical bits, but it is not limited to this, and can also measure five qubits. The bits are measured separately to obtain five classical bits, and so on.

Step S22 : the quantum computer 2 transmits the obtained classical bits to the computer device 1 via the network 3 .

Thus, the present invention can effectively obtain classical bits from qubits through measurement.

Please also refer to FIG. 9 , which is a structural diagram of a quantum logic circuit according to an embodiment of the present invention. The aforementioned steps S20-S21 can be represented by the quantum logic circuit shown in FIG. 9 . Furthermore, the aforementioned quantum computer program 200 can be used to implement the quantum logic circuit shown in FIG. 9 .

In the example of FIG. 9, three qubits q0-q2 are measured to obtain three measurement results (C), namely, three classical bits.

Specifically, in this example, the three qubits q0-q2 first pass through the Hadamard logic gates 50-52 to become superposition states. Next, the quantum states of the three qubits q0-q2 in the superposition state are measured by the measurement logic gates 60-62, so as to obtain the zeroth classical bit from the qubit q0 and obtain the first classical bit from the qubit q1 A classical bit, and a second classical bit (ie, the output of control line C) is obtained from qubit q2.

Please refer to FIG. 1 , FIG. 2 and FIG. 4 together. FIG. 4 is a partial flowchart of a method for generating a true random number according to a third embodiment of the present invention. FIG. 4 is used to describe step S10 of FIG. 2 in more detail.

Qubits are susceptible to external disturbances (such as thermal noise), resulting in errors (such as bit flip errors, bit-flip errors, such as quantum state |0> being disturbed and becoming |1>), which will reduce the measurement results. quality.

In this regard, in this embodiment, in order to eliminate the influence of the above errors, a plurality of qubits (as a distinction, hereinafter referred to as working qubits) are used as a qubit group (for example, two working qubits are one set of qubits, or five working qubits as a set of qubits), without limitation), and perform measurements on each qubit to obtain a classical bit (that is, this embodiment is use multiple qubits to generate a classical bit) to improve the quality of the measurement results.

Specifically, step S10 may include the following steps S30-S32.

Step S30: The quantum computer 2 makes the multiple working qubits of the qubit group become entangled. In an entangled state, the quantum states of multiple working qubits interact with each other.

And, in the absence of error, the quantum states of multiple working qubits will be the same due to mutual influence. In the presence of a bit flip error, the quantum state of one (or more) working qubits can be flipped to be different from the quantum states of the other working qubits.

Step S31: The quantum computer 2 determines a classical bit according to the multiple quantum states of the multiple working qubits in the entangled state.

In one embodiment, a plurality of quantum states of a plurality of working qubits in an entangled state are measured, and a majority vote is used to determine a classical bit according to the plurality of quantum states. For example, if the measured quantum states of the three working qubits are 0, 0, and 1, the classical bit is set to 0 (majority) based on a majority vote. The above principle is that the probability of error in the qubit is smaller than the probability of the normal state.

In one embodiment, in addition to a plurality of working qubits, each qubit group further includes auxiliary qubits as error correcting codes.

It is worth mentioning that, after repeated experiments by the inventors, the three working qubits can have the best entangled state and can be used to produce the best measurement results. In this regard, the following description takes three working qubits as an example, but this should not limit the number of multiple working qubits in the qubit group of the present invention (it can also be two, five or nine). and many more).

Specifically, step S31 in this embodiment may include steps S40-S43. Step S40: The quantum computer 2 performs a double-controlled inverse logic gate operation on the first working qubit, the second working qubit and the auxiliary qubit, so as to affect the quantum state of the auxiliary qubit.

Step S41: The quantum computer 2 performs a single-controlled inverse logic gate operation on the first working qubit and the second working qubit, so as to affect the quantum state of the second working qubit.

Step S42: The quantum computer 2 performs a double-controlled inverse logic gate operation on the second working qubit, the third working qubit and the auxiliary qubit, so as to affect the quantum state of the auxiliary qubit again.

Step S43: The quantum computer 2 performs measurement processing on the quantum state of the auxiliary qubit to obtain a classical bit.

Next, step S32 is performed: the quantum computer 2 transmits the obtained classical bit to the computer device 1 via the network 3 .

Thereby, the present invention can effectively correct the error of the qubit, improve the randomness of the qubit, and obtain a random number with better quality.

Please also refer to FIG. 10 , which is a structural diagram of a quantum logic circuit according to an embodiment of the present invention. Step S30 in FIG. 4 can be implemented using the quantum logic circuit 7 shown in FIG. 10 , and steps S40 to S43 can be implemented using the quantum logic circuit 8 shown in FIG. 10 . Furthermore, the aforementioned quantum computer program 200 can be used to implement the quantum logic circuits 7 and 8 shown in FIG. 10 .

In the example of Fig. 10, logical operations are performed on the three working qubits q0-q2 and the auxiliary qubit a0, and the final measurement result (C) of the auxiliary qubit a0 is used as the zeroth classical bit. .

In the quantum logic circuit 7, the working qubits q0-q2 are turned into an entangled state. Specifically, the working qubit q0 is brought into a superposition state by the Hadamard logic gate 70, the working qubit q0-q1 is entangled by the single-controlled inverse logic gate 71, and the working qubit is made by the single-controlled inverse logic gate 72. Elements q0, q2 are entangled.

Next, in the quantum logic circuit 8, the working qubits q0-q2 of the entangled state are entangled with the auxiliary qubit a0, and the quantum state of the auxiliary qubit is used to obtain a classical bit. Specifically, take the working qubits q0 and q1 as the control bits, and take the auxiliary qubit a0 as the target bit to implement the double-controlled inverse logic gate 80; take the working qubit q1 as the control bit, and take the working qubit The element q1 is the target bit to implement the single-controlled inverse logic gate 81; the working qubits q1 and q2 are used as the control bits, and the auxiliary qubit a0 is used as the target bit to implement the double-controlled inverse logic gate 82. In this way, the working qubits q1, q2, and q3 will entangle the auxiliary qubit a0, that is, the quantum state of the auxiliary qubit a0 can be used to reflect the quantum states of the working qubits q1, q2, and q3.

Finally, the quantum state of the auxiliary qubit a0 is measured by the measurement logic gate 83 to obtain the zeroth classical bit (ie, the output of the control line C).

Please refer to FIG. 1 to FIG. 5 together. FIG. 5 is a flowchart of a method for generating a true random number according to a fourth embodiment of the present invention. In this embodiment, the addition of classical bits (corresponding to steps S10-S11 in FIG. 2, namely steps S50-S54 in FIG. 5) and the generation of random numbers (corresponding to steps S12-S14 in FIG. 2, that is, steps in FIG. 5) S55-S59) are independently executed (sequentially executed or processed in parallel), and there is no execution sequence relationship.

In addition, in this embodiment, the user can set (or automatically set by the computer device 1 ) the supplementary condition, and when the supplementary condition is satisfied, the computer device 1 will automatically supplement the classical bits of the classical bit buffer 1031 .

Step S50 : the computer device 1 generates a classical bit generation request, and sends the classical bit generation request to the cloud application platform 20 of the quantum computer 2 via the network 3 .

Step S51 : the quantum computer performs measurement on a plurality of qubits to obtain a plurality of randomly generated classical bits, and returns these classical bits to the computer device 1 via the network 3 .

In one embodiment, the classical bit generation request includes user information, and the cloud application platform 20 executes the process of step S51 only when the user information is verified.

Step S52 : the computer device 1 stores the received classical bits in the classical bit buffer 1031 .

Step S53 : the computer device 1 determines whether the preset supplementary condition is satisfied, and the supplementary condition may be pre-stored in the storage module 103 .

In one embodiment, the supplementary conditions may be that the free space of the classical bit buffer 1031 is greater than a predetermined value (ie, the remaining classical bits are too few), the predetermined time interval has elapsed (such as 10 minutes), and each time the network is connected 3 Time and/or each time a random number request is received, without limitation.

If the computer device 1 determines that the preset replenishment conditions are satisfied, steps S50 - S53 are performed again to replenish the classical bits to the classical bit buffer 1031 again.

If the computer device 1 determines that the preset supplementary condition is not satisfied, step S54 is executed: the computer device 1 determines whether to end the supplementary function (eg, the user closes the supplementary function or disconnects from the network 3 , etc.).

If the computer device 1 determines that the supplementary function does not need to be terminated, step S53 is performed again. When the computer device 1 determines that the supplementary function is terminated, the method is terminated.

In the aforementioned embodiment, once the connection of the network 3 is interrupted and the classical bits stored in the classical bit buffer 3 are used up, the computer device 1 will not be able to generate random values, which will cause inconvenience to the user.

In order to solve the above problem, this embodiment further proposes a function of providing real random numbers and simulated random numbers in a mixed manner, which is mainly realized by executing steps S55-S59.

Step S55: The computer device 1 determines whether any random number request is received. For example, the random number request is received from the external computer device 4 or the user inputs the random number request through the human-machine interface 102 .

If the computer device 1 determines that no random number request has been received, step S55 is performed again.

If the computer device 1 receives the random number request, step S56 is executed: the computer device 1 determines whether the network 3 is connected, and the classical bit supplementation of steps S50-S52 can be performed.

If the computer device 1 determines that the network 3 is connected, step S57 is executed: the computer device 1 executes a true random number generating program (steps S12-S14 in FIG. 2 ) to obtain a random value belonging to a true random number.

If the computer device 1 determines that the network 3 is not connected, step S58 is executed: the computer device 1 further determines whether the total length of the remaining classical bits currently stored in the classical bit buffer 1031 satisfies the random number of the random number request range and/or number of random numbers.

For example, if there are only 39 bits left in the classical bit buffer 1031, but the random numbers range from 0 to 1023 (that is, each random value requires 10 bits), and 5 random values are required, that is, a total of 50 bits are required , the computer device 1 can determine that the classical bits are insufficient to generate all random numbers.

For example, if the classical bit buffer 1031 has only 4096 bits left, but the random number ranges from 0 to 1048575 (that is, each random value requires 20 bits), and requires 10 random values, that is, a total of 2000 bits are required , the computer device 1 can determine that the classical bits are sufficient to generate all random numbers.

If the computer device 1 determines that the classical bits remaining in the classical bit buffer 1031 are sufficient, step S57 is executed to generate a true random number.

If the computer device 1 determines that the classical bits remaining in the classical bit buffer 1031 are not enough, step S59 is executed: the computer device 1 executes the simulated random number generation program based on the random number range requested by the random number to generate a plurality of simulated random number bits The element is used as a random number sequence, and the format conversion process is performed on the random number sequence to obtain a random value that conforms to the format.

In this way, the present invention can provide user random numbers at any time, and provide high-quality real random numbers when the network 3 is connected.

It is worth mentioning that step S58 is not a necessary step in this embodiment. In one embodiment, the real random number generation method of the present invention can also be modified to directly execute the simulated random number generation program (step S59 ) when it is determined that the network 3 is not connected (step S56 , No).

In one embodiment, the computer device 1 can be provided with a quantum logic circuit (such as the quantum logic circuit shown in FIG. 9 or FIG. 10 , or it can be implemented by moving a quantum computer program 200 to the computer device 1 for execution. now). In step S59, the computer device 1 obtains random numbers by simulating and executing a quantum algorithm (such as the aforementioned true random number generating program) at the local end through the quantum logic circuit.

Please refer to FIG. 1 to FIG. 6 together. FIG. 6 is a partial flowchart of a method for generating a true random number according to a fifth embodiment of the present invention. In this embodiment, a random number filtering function is further provided. The user can set a random number condition (such as no consecutive numbers or no repetition, etc.) in the random number request, and the computer device 1 will filter the generated random number value according to the set random number condition.

Specifically, the method for generating a true random number in this embodiment includes the following steps.

Step S60: The computer device 1 accepts the random number request. The random number request includes the random number condition and the random number quantity.

Step S61: The computer device 1 executes a random number generating program to generate a random value. The random number generating program may be the aforementioned real random number generating program, an analog random number generating program, or a combination of the two, which is not limited.

Step S62: The computer device 1 determines whether the generated random value meets the random number condition.

Taking the random number condition as an example of non-consecutive numbers, the computer device 1 determines whether the generated random number is a consecutive number with other previously generated random numbers (for example, the random number 3 has been generated before, if the random number 2 is generated this time, it can be It is judged to be a consecutive number. If a random value of 1 is generated this time, it can be judged to be a non-consecutive number).

Taking the random number condition as non-repetition as an example, the computer device 1 determines whether the generated random value is consecutive with other previously generated random values (for example, the random value 13 has been generated before, if the random value 13 is generated this time, and It can be determined to be repeated; if a random value of 7 is generated this time, it can be determined to be non-repetitive).

If the computer device 1 determines that the generated random value meets the random number condition, step S64 is executed.

If the computer device 1 determines that the generated random value does not meet the random number condition, step S63 is executed: the computer device 1 deletes the random value that does not meet the condition.

Next, step S64 is executed: the computer device 1 determines whether the number of generated random numbers of the sum condition reaches the number of random numbers.

If the number of random numbers has not been reached, step S61 is performed again; otherwise, the computer device 1 outputs all random numbers and ends this execution.

Please refer to FIG. 1 to FIG. 7 together. FIG. 7 is a partial flowchart of a method for generating a true random number according to a sixth embodiment of the present invention. In this embodiment, a trigger function is further provided. The computer device 1 will only accept the request for setting random numbers after being triggered, and generate random values accordingly.

Specifically, the method for generating a true random number in this embodiment includes the following steps.

Step S70 : the computer device 1 determines whether the preset trigger condition is satisfied, and the trigger condition may be pre-stored in the storage module 103 .

In one embodiment, the trigger condition may be a random number request received from the external computer device 4 .

In one embodiment, the functional module 104 is a camera, which continuously captures environmental images and sends them to the processing module 100 (or to a cloud server for AI face recognition) to detect and recognize human faces. The aforementioned trigger condition may be that a human face is detected, or the human face has passed the identification verification.

In one embodiment, the function module 104 is a PIR sensor for triggering a signal when a user is detected. The aforementioned trigger condition may be receiving a trigger signal from the PIR sensor, that is, detecting a user.

If the computer device 1 determines that the trigger condition is not satisfied, step S70 is performed again to continue the determination.

If the computer device 1 determines that the trigger condition is satisfied, step S71 is executed: the computer device 1 accepts the user's random number request operation via the man-machine interface 102 , and sets the random number request according to the random number request operation.

In an embodiment, the aforementioned random number request operation is to input a random number range, a random number and/or a random number condition, but it is not limited thereto.

Step S72 : the computer device 1 generates one or more corresponding random values based on the random number request (the method of generating the random values is as described above, and will not be repeated here).

In this way, the user can make the computer device 1 quickly enter an acceptable operation state by triggering the computer device 1 , thereby effectively improving the efficiency of inputting requests.

Please refer to FIG. 1 to FIG. 8 together. FIG. 8 is a partial flowchart of a method for generating a true random number according to a seventh embodiment of the present invention. The one or more random values generated by the present invention can be applied to different fields, such as information security, games and games, and so on.

Specifically, the computer device 1 may perform step S80 or S81 to apply the generated random value after generating the random value.

Step S80: The computer device 1 performs encryption processing based on the generated random value.

In one embodiment, the computer device 1 can generate an encryption key based on the random value, and use the encryption key to cooperate with a corresponding encryption algorithm (eg, OpenSSL) to perform software encryption on the data or the device.

Step S81: The computer device 1 calculates the game result based on the generated random value.

In one embodiment, the game is a dice game, and the computer device 1 generates random numbers between 1-6 as the points of the electronic dice, but not limited to this, all games using random numbers can be generated by using the present invention. the true random numbers to improve randomness.

In conclusion, the random value generated by the present invention has excellent usability. Moreover, since the generated random numbers of the present invention cannot be predicted and repeated, the security of encryption and the fairness of the game are further improved.

The above description is only a preferred specific example of the present invention, and therefore does not limit the scope of the patent of the present invention. Therefore, all equivalent changes made by using the content of the present invention are all included in the scope of the present invention. bright.

S10-S14: The first random number generation step

Claims (9)

A method for generating true random numbers based on quantum operations, comprising: a) receiving a plurality of classical bits obtained by performing measurements on a plurality of qubits from a quantum computer in a computer device via a network; The classical bits are stored in a storage module of the computer equipment; c) when a random number request is received and the network is connected, based on the random number range of the random number request, the corresponding length of the storage module is read from the storage module. The plurality of classical bits are used as a random number sequence, and the plurality of read classical bits are deleted from the storage module; d) when the random number request is received and the network is not connected, based on the random number The requested random number range executes an analog random number generating program to generate a plurality of analog random number bits as the random number sequence; e) performs a format conversion process on the random number sequence to obtain a random value; and f) outputs the random number Random values. The method for generating true random numbers based on quantum operations as described in claim 1, wherein the step a) comprises the following steps: a11) respectively performing Hadamard logic gate operations on each of the qubits on the quantum computer to make each of the quantum The bit becomes a superposition state; a12) performing measurement processing on each of the qubits in the superposition state to obtain the plurality of classical bits; and a13) transmitting the plurality of classical bits to the computer device via a network. The method for generating true random numbers based on quantum operations as described in claim 1, wherein the step a) is to perform measurement on each qubit group to obtain one of the classical bits, and each qubit group includes at least two this qubit. The method for generating true random numbers based on quantum operations as described in claim 3, wherein the step a) comprises the following steps: a21) on the quantum computer, the plurality of working qubits of the qubit group become entangled a22) determining a classical bit according to a plurality of quantum states of the plurality of working qubits of the entangled state; and a23) transmitting the classical bit to the computer device via a network. The method for generating true random numbers based on quantum operations as described in claim 4, wherein the step a22) is to measure the plurality of quantum states of the plurality of working qubits in the entangled state, and adopt majority according to the plurality of quantum states decision to determine the classical bit. The method for generating true random numbers based on quantum operations as described in claim 4, wherein each of the qubit groups further includes an auxiliary qubit, and includes three of the working qubits; the step a22) further includes the following Steps: a221) perform a double control inverse logic gate operation on the first working qubit, the second working qubit and the auxiliary qubit; a222) perform a double control inverse logic gate operation on the first working qubit and the first working qubit and the auxiliary qubit; Two of the working qubits perform a single control inverse gate operation; a223) perform the double control inverse gate operation on the second of the working qubit, the third of the working qubit and the auxiliary qubit and a224) perform a measurement process on the auxiliary qubit to obtain one of the classical bits. The method for generating true random numbers based on quantum operations as claimed in claim 1, wherein the step b) is to store the plurality of classical bits in the storage module in a first-in, first-out manner, and the step c) is to use an advanced The first-out approach comes from the storage module reading the plurality of classical bits. The method for generating true random numbers based on quantum operations as described in claim 1, further comprising the following steps: g) Repeatedly executing at least one of the step c) and the step d) and the step f) based on a random number requested by the random number to generate the random numbers whose number is consistent with the random number, and in If any of the random values does not meet the random number condition of the random number request, delete the random value. The method for generating true random numbers based on quantum operations as described in claim 1, wherein the step c) further includes a step c1) after receiving the random number request, not connected to the network and the multiplicity stored in the storage module When the total length of the classical bits satisfies the random number range, read the classical bits from the storage module as the random number sequence, and delete the read classical bits from the storage module ; This step d) is when the random number request is received, the network is not connected, and the total length of the plurality of classical bits stored in the storage module is less than the random number range, the random number request based on the random number request. The analog random number generation program is executed in the number range.

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