CN110969255B - Artificial intelligence autonomous learning system and method based on quantum principle - Google Patents
Artificial intelligence autonomous learning system and method based on quantum principle Download PDFInfo
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Abstract
The invention discloses an artificial intelligence autonomous learning system and method based on a quantum principle, comprising a state generating device, a quantum superposition state generating device and a quantum superposition state generating device, wherein the state generating device is used for generating a quantum superposition state; the state detector is used for measuring parameters of the quantum superposition state and sending detection results to the controller; the controller is used for controlling the action of the actuator; and the relative arrangement of the state generating device and the state detector is adjusted according to the feedback information of the external detector; the external processor receives the action result of the executor, and gives feedback information in combination with the expected result; the external detector detects the feedback signal and sends the signal to the controller. By applying quantum effects in the microcosmic field to the artificial intelligence decision stage, the aim of avoiding early exposure of decision results under the condition that data, logic, algorithms and the like are all known is fulfilled. Meanwhile, the artificial intelligence obtains unpredictability similar to human thinking, so that the artificial intelligence has more flexibility in behavior. The mode can also achieve the purpose of autonomous learning by continuously repeating decision making and feedback processes.
Description
Technical Field
The invention relates to the technical field of crossing of artificial intelligence and quantum mechanics, in particular to an artificial intelligence autonomous learning system and method based on a quantum principle.
Background
At present, a certain decision mechanism is formed by leading-in of early data and setting of logic and threshold values. When a new decision is needed, a decision result can be obtained by inputting data to be decided and matching with a proper algorithm. Fixed inputs, fixed algorithms, bring about often the same decision results. If all preconditions, such as data, logic, algorithms, etc., are known, then there will be certainty in the decision result. This certainty is sometimes the effect we want, but it is not all the advantage it brings. When such mechanisms are applied to artificial intelligence decisions, there is a possibility that the decision results will be exposed in advance. Meanwhile, the artificial intelligence loses the unpredictability similar to human thinking, and the behavior of the artificial intelligence lacks flexibility.
For example, in a scenario where artificial intelligence is used to randomly draw winning numbers, if an external person predicts various logics, algorithms and databases designed inside the artificial intelligence in advance, it is highly possible to derive winning numbers through the same algorithm. In the scenario of making company decisions by adopting artificial intelligence, if external personnel predict various logics, algorithms and databases which are designed in the artificial intelligence in advance, the next strategic trend of the company is known by the same calculation process, so that economic leakage is caused. In the scene of interaction with a person created by adopting artificial intelligence, as well, when the scene is in real interaction with the person, fixed feedback is often generated on fixed information, so that the user loses the pleasure of communicating with the user.
Disclosure of Invention
In order to solve the technical problems, the embodiment of the invention provides an artificial intelligence autonomous learning system and method based on a quantum principle.
The embodiment of the invention discloses the following technical scheme:
the first aspect of the invention provides an artificial intelligence autonomous learning system based on quantum principle, the system comprising:
the state generating device is used for forming a quantum superposition state by acting on the microscopic particles;
the state detector is used for measuring the parameters of the quantum superposition state and sending the detection result to the controller;
the controller is used for controlling the actuator to perform corresponding actions according to the detection result; adjusting the relative arrangement of the state generating device and the state detector according to the feedback information of the external detector;
the actuator executes actions after receiving signals of the controller;
the external processor is used for receiving the action result of the executor and giving feedback information by combining the expected result;
and the external detector is used for detecting the feedback signal and sending the feedback signal to the controller.
Further, the state generating device includes:
a particle emitter for emitting individual microscopic particles;
a particle dispenser having a plurality of through-holes, the emitted individual microparticles passing through one of the through-holes.
Further, the state detectors are particle detectors, the number of the state detectors is the same as that of the through holes, the state detectors are closely attached to the through holes, and the state detectors are used for detecting particle signals emitted close to the through holes and sending detection results to the controller; the actuator has the same action types as the particle detectors in number and one-to-one correspondence, and executes actions after receiving signals of the controller.
Further, the controller adjusts the relative angle of the particle emitter and the particle dispenser according to the feedback signal of the external detector.
Further, the state generating device comprises a laser emitter for emitting a light beam with a set wavelength within a set time, and the ground state atoms are excited by the light beam.
Further, the state detector is a timing detector and is used for detecting whether photons are emitted within a set time so as to judge whether energy level transition occurs to the excited state atoms or not, and sending a detection result to the controller; and the actuator executes the action after receiving the signal of the controller.
Further, the controller adjusts the relative time between the laser emitter light emission and the timing detector measurement according to the feedback signal of the external detector.
The second aspect of the invention provides an artificial intelligence autonomous learning method based on a quantum principle, which comprises the following steps:
the microscopic particles are acted through a state generating device to form a quantum superposition state;
measuring the parameter of the quantum superposition state through a state detector, so that the quantum superposition state of the parameter is randomly collapsed to a classical state with a certain probability;
the controller is used for controlling the executor to implement corresponding actions by taking the classical state measured by the state detector as a decision result;
receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
the relative setting of the state generating device and the state detector is adjusted through the controller according to the feedback signal, so that the quantum superposition state function distribution of the same parameter is changed in the next event, and the probability of obtaining different classical states in the next measurement is changed; if the feedback signal is not received, no adjustment is performed.
Further, the method specifically comprises the following steps:
emitting individual microparticles by a particle emitter; the microscopic particles are ejected through a particle distributor to form a quantum superposition state;
acquiring particle path information through a particle detector to enable the superposition state to collapse;
the controller takes the path information as a decision result to control the executor to implement corresponding actions;
receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
and adjusting the relative angles of the particle emitter and the particle distributor according to the feedback signals through the controller, so that the probability of measuring different path information at the next event is changed.
Further, the method specifically comprises the following steps:
emitting a light beam with a set wavelength through a laser emitter; the light beam acts on the ground state atoms to enable the ground state atoms to transition to an excited state; stopping the light beam action, and forming a quantum superposition state by the existence of the transition probability of the excited state atoms;
acquiring track energy level information through a timing detector to enable the superposition state to collapse;
the controller takes the track energy level information as a decision result to control the executor to implement corresponding actions;
receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
and adjusting the relative time measured by the laser emitter and the timing detector according to the feedback signal by the controller, so that the probability of measuring different track energy level information at the next event is changed.
The effects provided in the summary of the invention are merely effects of embodiments, not all effects of the invention, and one of the above technical solutions has the following advantages or beneficial effects:
1. the invention uses quantum principle to make the action result of the executor be random decision result, and the occurrence of various results has a certain probability. Even if all external input conditions and internal decision mechanisms are accurately known, decision results cannot be accurately predicted, only the probability of occurrence of various results can be obtained, and before the decision results are implemented, all the results have the probability of occurrence and cannot be eliminated in advance, so that the confidentiality of the final results is ensured, and information leakage is prevented.
2. And (3) giving a feedback signal to the action result of the actuator in combination with the expected result, and acting on a random decision process through the feedback signal to perform decision correction, thereby influencing the subsequent decision. The way this affects is to change the probability that a decision result will be made, rather than to produce a deterministic result. The probability of each result is changed by autonomously adjusting the quantum effect generation and measurement process, but the possibility of a certain result is not completely excluded, so that the decision can be further changed towards the expected direction, and the accurate effect of avoiding the change is predicted in advance.
3. After the system completes initial setting, various subsequent decision generation, action implementation, feedback collection and decision correction can be completed by the system independently, and the system is continuously circulated through repeated steps without interference, so that the purpose of independent learning is achieved.
4. The artificial intelligence generated based on the scheme has the advantages that the thinking mode of the artificial intelligence has the unpredictability of human thinking, the behaviors are more flexible and changeable, the user can obtain similar feeling of communicating with a real person when communicating with the artificial intelligence, and more fun is obtained.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a schematic diagram of the system of embodiment 1 of the present invention;
FIG. 3 is a schematic view of the structure of embodiment 2 of the system according to the present invention;
fig. 4 is a schematic flow chart of the method of the present invention.
Detailed Description
In order to clearly illustrate the technical features of the present solution, the present invention will be described in detail below with reference to the following detailed description and the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different structures of the invention. In order to simplify the present disclosure, components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and processes are omitted so as to not unnecessarily obscure the present invention.
An artificial intelligence autonomous learning system based on quantum principle as shown in fig. 1 comprises a state generating device, a state detector, a controller, an executor, an external processor and an external detector. The state generating device forms a quantum superposition state by acting on the microscopic particles; the state detector measures the parameters of the quantum superposition state and sends the detection result to the controller; the controller controls the executor to make corresponding actions according to the detection result; adjusting the relative arrangement of the state generating device and the state detector according to the feedback information of the external detector; the actuator executes the action after receiving the signal of the controller; the external processor is used for receiving the action result of the executor and giving feedback information by combining the expected result; the external detector is used for detecting the feedback signal and sending the feedback signal to the controller.
Example 1
As shown in fig. 2, the state generating device includes a particle emitter for emitting individual microscopic particles and a particle dispenser; the particle dispenser has a plurality of through-holes through one of which the emitted individual microparticles pass. The state detectors are particle detectors, the number of the state detectors is the same as that of the through holes, the state detectors are closely attached to the through holes and used for detecting particle signals emitted by the state detectors close to the through holes, and the detection results are sent to the controller; the types of the actions of the executors are the same as the number of the particle detectors and are in one-to-one correspondence, and the actions are executed after the signals of the controller are received. The controller adjusts the relative angle of the particle emitter and the particle dispenser according to the feedback signal from the external detector.
The particle emitter is a laser emitter for emitting a single photon. The main principle of the laser transmitter emitting a single photon is: the working medium absorbs external energy and then transits from a ground state to an excited state, when the excited state transits back to the ground state, photons are emitted, and the photons are amplified, controlled and output through the resonant cavity to form a laser beam. When the input of external energy is continuously reduced, the amplification effect of the resonant cavity is restrained, or the single photon emission is achieved through a pulse attenuation mode. At this time, the single emission power is similar to the energy of one photon, and can be calculated by planck energy formula e=hv. Where h is the Planck constant and v is the frequency of the light.
In addition, single photons can be emitted by an isolated fluorescent molecular method, a diamond nano particle color center method, a single atom coupling optical cavity method, a quantum dot energy level transition method, a quantum dot resonance excitation method, a diazo chemical method and the like.
The particle distributor is a double slit screen, and the slit spacing and the slit width on the double slit screen are required to be close to or smaller than the wavelength of the light wave with the frequency, so that the photons show volatility when passing through the double slit screen. For example, red wavelengths are typically 640-780nm, then when such wavelengths are selected, the slit spacing and slit width need to be close to or less than this length order of magnitude to cause the light to exhibit significantly fluctuating.
In particular, in the embodiment, in order to make a single photon generate volatility, the slot pitch reaches the order of 1000nm, that is, the fluctuation attribute thereof can be obviously observed, but actually, it is expected to reach the order of 10 μm or slightly higher, and it can be realized. The slit width may be in the order of μm. In the case of electrons, the shorter the distance required, the shorter the wavelength of the de broglie wave, the more significant fluctuations can be observed in the gap distance of the order of 10nm, which in practice is expected to reach the order of 100nm or slightly higher, which can also be achieved. For the slit width, the order of 10nm was used.
The particle detector is a photon detector, and two photon detectors are arranged close to the back of the double slit screen to detect the slit through which photons actually pass, so as to restore the granularity of the photons. The photon detector adopts SPD photon detector, is an ultra-low noise device, has strong sensitivity, and can detect the minimum energy unit of light, namely photons. The detection result is transmitted to the controller in an electric signal mode by the photon detector.
The action mechanism of the above process is to utilize the wave grain biphase property of photons, and can be verified by a Young's double slit test and a variant test thereof. When photons are emitted to the middle of the double slits, the probability of passing through the double slits is 50% respectively, and the photons cannot be predicted in advance, so that the photon has real randomness.
When the controller receives the signal of the left detector, an instruction is sent to enable the left actuator to act, such as flashing, sound, rotation and the like; when the controller receives the signal from the right detector, it will send out instruction to make the right actuator act, such as flashing, sound, rotation, etc.
And after receiving the execution result of the executor, the external processor responds to the execution result of the executor by combining the expected result. If the action signal sent by the actuator is consistent with the expected result, the external processor feeds back a positive signal; if the action signal sent by the actuator is inconsistent with the expected result, the external processor feeds back a negative signal. The positive signal and the negative signal are expressed in different forms according to different external environments, such as smiling and crying faces of a person, or upward or downward of a thumb, etc. When the outside is a non-human object, whether the implementation effect is consistent with the assumption can be used as a positive and negative signal. For example, assuming that the action performed is pushing the table by the left actuator, the effect can be divided into pushing and not pushing, the pushing is set to be a positive signal, and the not pushing is set to be a negative signal. The external detector detects the feedback signal and sends the feedback signal to the controller.
The controller determines whether it is positive or negative. If it is a positive signal, a command will be issued to rotate the firing angle of the laser transmitter slightly in the direction of the previous decision. For example, if a positive signal is generated by the left slit, the emission angle is slightly deflected to the left. If negative, a command will be issued to rotate the firing angle of the laser transmitter slightly in the opposite direction to the previous decision. Similar effects can be achieved by moving the dual slit screen with the laser firing stationary.
Since the photons have volatility when propagating, the wave function follows probability distribution, and the maximum point of the probability distribution is necessarily the midpoint of the straight line track. Deflection of the firing angle will result in a greater probability of the slot on the side being selected for the next decision, while the slot on the far side will be less.
By repeating the above processes repeatedly, the system can make judgment on the feedback of the outside caused by the decision, and the probability of occurrence of the next decision is continuously adjusted through the judgment.
Example 2
As shown in fig. 3, the state generating device includes a laser emitter for emitting a light beam of a set wavelength for a set time, and exciting the ground state atoms with the light beam. The state detector is a timing detector and is used for detecting whether photons are emitted within a set time so as to judge whether the excited state atoms undergo energy level transition or not and sending a detection result to the controller. The actuator performs an action upon receiving a signal from the controller. The controller adjusts the relative time between the laser emitter light emission and the timing detector measurement according to the feedback signal of the external detector.
In the light beam emitted by the laser emitter, when a large number of photons irradiate to the ground state atoms, the electron orbits of the photons can be transited to an excited state. Such as a hydrogen atom, whose ground state electron orbital energy level differs from the lowest excited state electron orbital energy level by about 10.2 ev. When irradiated with photons of this energy, only the atoms are excited to the lowest excited state. At this time, the photon corresponding wavelength is about 1.21×10 -7 m。
The ground state atoms will be in the lowest excited state after being irradiated. When the irradiation is stopped, the light will spontaneously return to the ground state within a certain period of time, and a photon is emitted. Average value of this timeI.e. its energy level average lifetime, is about 2.1 x 10, as considered by conventional experience -9 s。
The timing detector is a nanosecond level detector for detecting the time of the clock in the range of 2.1X10 -9 And judging whether the excited state atoms generate energy level transition or not by judging whether photons are emitted within s, and feeding back the result to the controller in the form of an electric signal.
The mechanism of action of the above process is an energy level orbital transition mechanism using atoms. The time that the atoms stay at the orbit is a random value before the transition of the energy level orbit, but the probability of transition occurring near the average lifetime of the energy level is the largest and gradually decreases to both sides.
The controller recognizes the signal from the timing detector and controls the corresponding actuator. When the signal received by the controller is that transition occurs, an instruction is sent to enable the left actuator to act, such as flashing, sound, rotation and the like; when the signal received by the controller is that transition does not occur, an instruction is sent to enable the right actuator to act, such as flashing, sound, rotation and the like.
And after receiving the execution result of the executor, the external processor responds to the execution result of the executor by combining the expected result. If the action signal sent by the actuator is consistent with the expected result, the external processor feeds back a positive signal; if the action signal sent by the actuator is inconsistent with the expected result, the external processor feeds back a negative signal. The positive signal and the negative signal are represented in different forms according to different external environments, such as smiling face and crying face of a person, or upward or downward of thumb, etc. When the outside is a non-human object, whether the implementation effect is consistent with the assumption can be used as a positive and negative signal. For example, assuming that the action performed is pushing the table by the left actuator, the effect can be divided into pushing and not pushing, the pushing is set to be a positive signal, and the not pushing is set to be a negative signal. The external detector detects the feedback signal and sends the feedback signal to the controller.
The controller determines whether the feedback signal is positive or negative. If it is a positive signal, an instruction will be issued to slightly increase the timing interval of the timing detector. If the signal is negative, a command is issued to slightly narrow the timing interval of the timing detector. A similar effect can be achieved by changing the way the laser transmitter stops irradiating time while the timing interval of the timing detector is unchanged.
Since the intra-energy-level transition time of the excited state atoms obeys the probability distribution, the maximum point of the probability distribution is necessarily the energy-level average life time. A change in the relative detection time interval will cause a change in probability at the next decision.
By repeating the above processes repeatedly, the system can make judgment on the feedback of the outside caused by the decision, and the probability of occurrence of the next decision is continuously adjusted through the judgment.
As shown in fig. 4, an artificial intelligence autonomous learning method based on quantum principle, the principle includes the following steps:
s1, acting on microscopic particles through a state generating device to form a quantum superposition state;
s2, measuring the parameter of the quantum superposition state through a state detector, so that the quantum superposition state of the parameter is randomly collapsed to a classical state with a certain probability;
s3, using classical states measured by the state detector as decision results through the controller, and controlling the executor to implement corresponding actions;
s4, receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
s5, adjusting the relative arrangement of the state generating device and the state detector according to the feedback signal through the controller.
In step S5, the controller adjusts the relative settings of the state generating device and the state detector according to the feedback signal, so that the quantum superposition function distribution of the same parameter changes in the next event, and the probability of obtaining different classical states in the next measurement changes; if the feedback signal is not received, no adjustment is performed.
Corresponding to system example 1 above:
the implementation process of the step S1 is as follows: emitting individual microparticles by a particle emitter; the microscopic particles are ejected through a particle distributor to form a quantum superposition state;
the implementation process of the step S2 is as follows: acquiring particle path information through a particle detector to enable the superposition state to collapse;
the implementation process of the step S3 is as follows: the controller takes the path information as a decision result to control the executor to implement corresponding actions;
the implementation process of the step S4 is as follows: receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
the implementation process of the step S5 is as follows: and adjusting the relative angles of the particle emitter and the particle distributor according to the feedback signals through the controller, so that the probability of measuring different path information at the next event is changed.
Corresponding to system example 2 above:
the implementation process of the step S1 is as follows: emitting a light beam with a set wavelength through a laser emitter; the light beam acts on the ground state atoms to enable the ground state atoms to transition to an excited state; stopping the light beam action, and forming a quantum superposition state by the existence of the transition probability of the excited state atoms;
the implementation process of the step S2 is as follows: acquiring track energy level information through a timing detector to enable the superposition state to collapse;
the implementation process of the step S3 is as follows: the controller takes the track energy level information as a decision result to control the executor to implement corresponding actions;
the implementation process of the step S4 is as follows: receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
the implementation process of the step S5 is as follows: and adjusting the relative time measured by the laser emitter and the timing detector according to the feedback signal by the controller, so that the probability of measuring different track energy level information at the next event is changed.
The foregoing is only a preferred embodiment of the present invention, and it will be apparent to those skilled in the art that modifications and variations can be made without departing from the principles of the present invention, or that single system decision results can be used in other alternative or combined schemes of the same principle system as input data or set-up data, and such modifications, variations, alternatives or combinations are also considered to be within the scope of the present invention.
Claims (8)
1. An artificial intelligence autonomous learning system based on quantum principle, characterized in that the system comprises:
the state generating device is used for forming a quantum superposition state by acting on the microscopic particles;
the state detector is used for measuring the parameters of the quantum superposition state and sending the detection result to the controller;
the controller is used for controlling the actuator to perform corresponding actions according to the detection result; adjusting the relative arrangement of the state generating device and the state detector according to the feedback information of the external detector;
the actuator executes actions after receiving signals of the controller;
the external processor is used for receiving the action result of the executor and giving feedback information by combining the expected result;
the external detector is used for detecting the feedback signal and sending the feedback signal to the controller;
the state generating device includes:
a particle emitter for emitting individual microscopic particles;
a particle dispenser having a plurality of through-holes, the emitted individual microparticles passing through one of the through-holes;
the state detectors are particle detectors, the number of the state detectors is the same as that of the through holes, the state detectors are closely attached to the through holes, and the state detectors are used for detecting particle signals emitted close to the through holes and sending detection results to the controller; the actuator has the same action types as the particle detectors in number and one-to-one correspondence, and executes actions after receiving signals of the controller.
2. The artificial intelligence autonomous learning system based on quantum principles of claim 1, wherein the controller adjusts the relative angles of the particle emitter and the particle dispenser based on feedback signals from an external detector.
3. The artificial intelligence autonomous learning system based on quantum principle according to claim 1, wherein the state generating means includes a laser emitter for emitting a light beam of a set wavelength for a set time, and exciting a ground state atom with the light beam.
4. The artificial intelligence autonomous learning system based on quantum principle according to claim 3, wherein the state detector is a timing detector for detecting whether photons are emitted within a set time to determine whether energy level transition occurs to excited state atoms, and transmitting the detection result to the controller; and the actuator executes the action after receiving the signal of the controller.
5. The artificial intelligence autonomous learning system based on quantum principle according to claim 4, wherein the controller adjusts the relative time of the laser transmitter light emission and the timing detector measurement according to the feedback signal of the external detector.
6. A method of quantum principle based artificial intelligence autonomous learning using the system of claim 1, the method comprising:
the microscopic particles are acted through a state generating device to form a quantum superposition state;
measuring the parameter of the quantum superposition state through a state detector, so that the quantum superposition state of the parameter is randomly collapsed to a classical state with a certain probability;
the controller is used for controlling the executor to implement corresponding actions by taking the classical state measured by the state detector as a decision result;
receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
the relative setting of the state generating device and the state detector is adjusted through the controller according to the feedback signal, so that the quantum superposition state function distribution of the same parameter is changed in the next event, and the probability of obtaining different classical states in the next measurement is changed; if the feedback signal is not received, no adjustment is performed.
7. The artificial intelligence autonomous learning method based on the quantum principle according to claim 6, characterized in that the method specifically comprises:
emitting individual microparticles by a particle emitter; the microscopic particles are ejected through a particle distributor to form a quantum superposition state;
acquiring particle path information through a particle detector to enable the superposition state to collapse;
the controller takes the path information as a decision result to control the executor to implement corresponding actions;
receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
and adjusting the relative angles of the particle emitter and the particle distributor according to the feedback signals through the controller, so that the probability of measuring different path information at the next event is changed.
8. The artificial intelligence autonomous learning method based on the quantum principle according to claim 6, characterized in that the method specifically comprises:
emitting a light beam with a set wavelength through a laser emitter; the light beam acts on the ground state atoms to enable the ground state atoms to transition to an excited state; stopping the light beam action, and forming a quantum superposition state by the existence of the transition probability of the excited state atoms;
acquiring track energy level information through a timing detector to enable the superposition state to collapse;
the controller takes the track energy level information as a decision result to control the executor to implement corresponding actions;
receiving an action signal of an actuator through an external processor, and sending a feedback signal by combining an expected result;
and adjusting the relative time measured by the laser emitter and the timing detector according to the feedback signal by the controller, so that the probability of measuring different track energy level information at the next event is changed.
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| JP2019175482A (en) * | 2019-05-24 | 2019-10-10 | 株式会社フューチャーアイ | Learning support system |
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| CN207037107U (en) * | 2017-06-28 | 2018-02-23 | 华中科技大学 | The detection system of pump atom is returned in a kind of atomic interferometer based on microwave |
| CN110276470A (en) * | 2018-03-14 | 2019-09-24 | 株式会社日立高新技术 | Exploration device, heuristic approach and plasma treatment appts |
| CN109147880A (en) * | 2018-08-21 | 2019-01-04 | 广东博云公共平台网络科技有限公司 | Management system and method based on Internet of Things block chain quantum bit artificial intelligence |
| CN109934351A (en) * | 2019-03-06 | 2019-06-25 | 南京航空航天大学 | A kind of quantum learning aid algorithm and the modified fuzzy sliding mode controlling method based on quantum learning aid algorithm |
| JP2019175482A (en) * | 2019-05-24 | 2019-10-10 | 株式会社フューチャーアイ | Learning support system |
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