High-temperature high-pressure synthesis process data security transmission method based on quantum encryption

Abstract

This invention relates to the field of process data security technology and discloses a method for secure transmission of high-temperature and high-pressure synthesis process data based on quantum encryption. The method acquires a real-time set of process parameters from a high-temperature and high-pressure synthesis equipment, extracting time-series variation data of temperature, pressure, and reaction rate. Dynamic key pairs are generated based on a quantum key distribution protocol, and the process parameter set is divided into sensitive and non-sensitive data segments. The sensitive data segments are quantum-state encoded, and the encoded quantum state data packets are transmitted via polarized photon sequences. The bit error rate of the quantum channel is monitored in real time; if the bit error rate exceeds a preset threshold, a key update process is triggered, the quantum key is reallocated, and the current transmission session is discarded. At the receiving end, the quantum state data packets are parsed, the sensitive data segments are reconstructed using the dynamic key pairs, and finally merged with the non-sensitive data segments to form a complete set of process parameters. This invention achieves the principle of secure transmission of process data under extreme operating conditions.

Description

Technical Field

[0001] This invention relates to the field of process data security technology, specifically a method for secure transmission of high-temperature and high-pressure synthesis process data based on quantum encryption. Background Technology

[0002] High-temperature and high-pressure synthesis processes are widely used in new material research and development, specialty chemical production, and other fields. Precise control and real-time monitoring of process parameters are crucial for product quality and production safety. This process data often involves core intellectual property rights and key technical secrets, possessing extremely high commercial value and requiring strict confidentiality. Traditional process data transmission often employs wired or wireless networks combined with classical encryption algorithms for protection. However, in harsh industrial environments such as high temperature, high pressure, and strong electromagnetic interference, traditional encryption transmission methods face severe challenges. The security of classical encryption algorithms is based on computational complexity assumptions; with the development of quantum computing technology, their long-term security is threatened. Furthermore, the complex electromagnetic environment in industrial settings can easily lead to increased data transmission error rates, affecting data integrity and real-time performance.

[0003] Existing data transmission schemes have significant shortcomings in addressing eavesdropping and interference. Traditional encryption technologies cannot guarantee absolute information security in principle, and the key distribution process itself may become a security vulnerability. In high-temperature and high-pressure synthesis scenarios, process parameters need to be continuously and in real-time transmitted to the monitoring center for analysis and decision-making. Any data leakage or tampering could lead to major production accidents or technology leaks. Current systems lack the ability to perceive and adaptively adjust the quality of data transmission channels in real time. When channel conditions deteriorate, they can usually only retransmit data or reduce the transmission rate, making it difficult to balance security and real-time requirements.

[0004] Quantum encryption technology, especially quantum key distribution, can achieve theoretical information security based on the principles of quantum mechanics, providing a new solution for sensitive data transmission. However, its application in industrial environments, especially under extreme conditions, is still in the exploratory stage. How to combine quantum encryption with the characteristics of real-time industrial data streams to achieve efficient, stable, and secure transmission is a key problem that needs to be solved. Existing quantum communication schemes are mostly designed for the communication field and do not fully consider the high real-time, periodic, and multi-parameter correlation characteristics of industrial control data. Therefore, a dedicated method is needed that can adapt to high-temperature and high-pressure industrial environments and effectively integrate quantum security mechanisms with the needs of process data transmission. Summary of the Invention

[0005] The purpose of this invention is to provide a secure data transmission method for high-temperature and high-pressure synthesis processes based on quantum encryption, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides a method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption, the method comprising:

[0007] High-temperature and high-pressure synthesis processes are widely used in new material research and development, specialty chemical production, and other fields. Precise control and real-time monitoring of process parameters are crucial for product quality and production safety. This process data often involves core intellectual property rights and key technical secrets, possessing extremely high commercial value and requiring strict confidentiality. Traditional process data transmission often employs wired or wireless networks combined with classical encryption algorithms for protection. However, in harsh industrial environments such as high temperature, high pressure, and strong electromagnetic interference, traditional encryption transmission methods face severe challenges. The security of classical encryption algorithms is based on computational complexity assumptions; with the development of quantum computing technology, their long-term security is threatened. Furthermore, the complex electromagnetic environment in industrial settings can easily lead to increased data transmission error rates, affecting data integrity and real-time performance.

[0008] Existing data transmission schemes have significant shortcomings in addressing eavesdropping and interference. Traditional encryption technologies cannot guarantee absolute information security in principle, and the key distribution process itself may become a security vulnerability. In high-temperature and high-pressure synthesis scenarios, process parameters need to be continuously and in real-time transmitted to the monitoring center for analysis and decision-making. Any data leakage or tampering could lead to major production accidents or technology leaks. Current systems lack the ability to perceive and adaptively adjust the quality of data transmission channels in real time. When channel conditions deteriorate, they can usually only retransmit data or reduce the transmission rate, making it difficult to balance security and real-time requirements.

[0009] Quantum encryption technology, especially quantum key distribution, can achieve theoretical information security based on the principles of quantum mechanics, providing a new solution for sensitive data transmission. However, its application in industrial environments, especially under extreme conditions, is still in the exploratory stage. How to combine quantum encryption with the characteristics of real-time industrial data streams to achieve efficient, stable, and secure transmission is a key problem that needs to be solved. Existing quantum communication schemes are mostly designed for the communication field and do not fully consider the high real-time, periodic, and multi-parameter correlation characteristics of industrial control data. Therefore, a dedicated method is needed that can adapt to high-temperature and high-pressure industrial environments and effectively integrate quantum security mechanisms with the needs of process data transmission.

[0010] Compared with the prior art, the beneficial effects of the present invention are:

[0011] This invention generates dynamic key pairs through a quantum key distribution protocol, providing a theoretical foundation for information security in process data encryption. Traditional encryption methods rely on the computational complexity of mathematical problems, which are vulnerable to being cracked by future advanced computing technologies. In contrast, the security of quantum key distribution is guaranteed by the fundamental principles of quantum mechanics; any eavesdropping will introduce a detectable disturbance, fundamentally solving the security problem of key distribution and providing long-term, reliable security for process data protection in critical fields such as high-temperature, high-pressure synthesis.

[0012] By dividing process parameters into sensitive and non-sensitive data segments and implementing quantum state encoding transmission only for the sensitive data segments, resource utilization efficiency is optimized. Quantum encrypted transmission has high requirements for channels and environment, and using quantum transmission for all data may be costly and inefficient. This method, through data hierarchical transmission, uses high-security quantum transmission for the most critical sensitive parameters, while non-sensitive data can be encrypted using classical methods. This balances system complexity and transmission efficiency while ensuring the security of core secrets.

[0013] A dynamic security control mechanism for the transmission process is established by real-time monitoring of the quantum channel bit error rate and setting an update threshold. Industrial environments are complex, and channel quality may change dynamically. This method, through continuous monitoring of the bit error rate, can promptly detect channel attenuation or potential eavesdropping interference. Once the bit error rate exceeds the limit, the system automatically triggers a key update and abandons the current session, effectively preventing data leakage under insecure channel conditions and embodying the principles of proactive defense and adaptive security.

[0014] Using polarized photon sequences to transmit quantum state data packets enhances transmission robustness in extreme environments. High-temperature and high-pressure environments may be accompanied by strong electromagnetic noise and physical disturbances. Polarization coding has a certain anti-interference capability compared to other quantum coding methods, which helps maintain the stability of quantum states under harsh conditions, improves the transmission success rate, and ensures the continuity and reliability of process monitoring data.

[0015] Finally, at the receiving end, sensitive data is restored and merged with non-sensitive data, ensuring the integrity and availability of the process parameter set. This method ensures the absolute security of critical sensitive data in the transmission link while maintaining the integrity of the entire dataset at the application layer. This enables the monitoring system to obtain comprehensive and accurate process information for analysis and decision-making, meeting the dual requirements of industrial production for data security and availability. Attached Figure Description

[0016] Figure 1 This is a schematic diagram illustrating the working principle of the high-temperature and high-pressure synthesis process data security transmission method based on quantum encryption described in this invention.

[0017] Figure 2A flowchart for obtaining real-time process parameter sets for high-temperature and high-pressure synthesis equipment;

[0018] Figure 3 This is a flowchart illustrating the dynamic key pair generation based on a quantum key distribution protocol.

[0019] Figure 4 This is a graph showing the correlation between key strength and channel performance in a quantum communication system. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figure 1 This invention provides a method for secure transmission of high-temperature and high-pressure synthesis process data based on quantum encryption. The method integrates quantum key distribution technology with process parameter monitoring to achieve secure transmission of sensitive data during the synthesis process. The overall implementation scheme is as follows: A real-time process parameter set is obtained from the high-temperature and high-pressure synthesis equipment, containing time-series changes in temperature, pressure, and reaction rate; a dynamic key pair is generated based on a quantum key distribution protocol, and the process parameter set is divided into sensitive data segments and non-sensitive data segments; the sensitive data segments are quantum-state encoded, and the encoded quantum state data packets are transmitted via polarized photon sequences; the bit error rate of the quantum channel is monitored in real time during transmission; if the bit error rate exceeds a preset threshold, a key update process is triggered, the quantum key is reallocated, and the current transmission session is discarded; at the receiving end, the quantum state data packets are parsed, the sensitive data segments are restored using the dynamic key pair, and finally merged with the non-sensitive data segments to form a complete process parameter set.

[0022] Example 1: See Figure 2In acquiring real-time process parameters for the high-temperature and high-pressure synthesis equipment, collecting temperature gradient distribution data from multiple probe sensors within the synthesis reactor is a fundamental operation. The internal space of the synthesis reactor is divided into multiple virtual grid nodes, each equipped with a high-temperature and high-pressure resistant platinum resistance temperature sensor. The sensor collects temperature readings at a fixed frequency, and the temperature gradient distribution data is obtained by calculating the spatial differences between readings from adjacent nodes. The data acquisition system records the axial and radial temperature distribution profiles of the reactor at each sampling moment. Periodic pulsating peak monitoring of the pressure vessel is performed simultaneously. A piezoelectric dynamic pressure sensor is installed on the pressure vessel wall, capturing high-frequency pressure fluctuations within the vessel. Periodic pulsating peaks are extracted from the pressure waveform using a peak detection algorithm. The algorithm sets a hysteresis threshold to eliminate noise interference, and the maximum value within each pressure cycle is recorded as the pulsating peak. The reactant feed rate is measured in real-time by a Coriolis mass flow meter, and the product formation rate is calculated using an online laser particle size analyzer to measure the product concentration change per unit time. The system calculates the difference between the feed rate and the product formation rate and generates dynamic equilibrium parameters for the reaction. These dynamic equilibrium parameters are stored in time-series format, with the positive or negative value reflecting the equilibrium state of the reaction process.

[0023] Temperature gradient distribution data, periodic pulsation peak values, and reaction dynamic equilibrium parameters need to be aligned to a unified time reference, derived from a high-precision atomic clock, with each data point accompanied by a millisecond-level timestamp. The alignment process employs an interpolation synchronization method, resampling data sequences from different acquisition frequencies onto a unified time axis to generate a three-dimensional process parameter matrix. The first dimension of the three-dimensional process parameter matrix represents the time series, the second dimension represents the projection of the temperature gradient distribution data onto a spatial grid, and the third dimension integrates the scalar values ​​of pressure pulsation peak values ​​and reaction dynamic equilibrium parameters. The matrix generation algorithm automatically detects missing data intervals and fills them using spline interpolation to ensure the spatiotemporal continuity of the matrix data. The deployment scheme of the multi-probe sensor needs to consider the geometric characteristics of the synthesis reactor; the sensors are arranged at equal intervals along the reactor axis and in a concentric circle distribution pattern in the radial direction. A temperature compensation mechanism is enabled for the acquisition of temperature gradient distribution data, with the compensation coefficient dynamically adjusted based on the sensor calibration curve. Multi-scale analysis is introduced for the detection of periodic pulsation peak values ​​in the pressure vessel, setting peak extraction thresholds for pulsation components in different frequency ranges. Moving average filtering is introduced in the calculation of reaction dynamic equilibrium parameters to eliminate the influence of instantaneous fluctuations on equilibrium judgment. The timestamp alignment process uses a hardware-level clock synchronization protocol to reduce timing errors introduced by software delays.

[0024] The data structure of the three-dimensional process parameter matrix adopts a tensor format, and the underlying storage uses block encoding technology to support fast read and write operations. The matrix generation module verifies the physical rationality of the data; for example, the temperature gradient distribution data should conform to the heat conduction law, the pressure pulsation peak should be within the pressure limit of the vessel, and the reaction dynamic equilibrium parameters should show a convergence trend. Data points that fail verification are marked as abnormal, triggering the sensor calibration process. After matrix generation, it is automatically compressed and cached in local memory, preparing the data source for subsequent quantum-encrypted transmission. The multi-probe sensor network of the synthesis reactor adopts a distributed acquisition architecture, with each sensor node equipped with an independent signal conditioning circuit. Temperature gradient distribution data is collected to the central processor via a fieldbus. The pressure vessel monitoring system includes multiple redundant acquisition channels, and periodic pulsation peak data is uploaded after digital filtering. The calculation of reaction dynamic equilibrium parameters introduces a real-time mass balance equation, and the difference between the feed rate and the product formation rate is dimensionless, making the parameters comparable across processes. The timestamp alignment algorithm uses adaptive delay compensation to eliminate the influence of differences in response time between different sensors.

[0025] The generation process of the 3D process parameter matrix includes a data quality assessment step, with assessment indicators including data integrity, consistency, and timeliness. The matrix's dimensional parameters are adjusted according to the specific synthesis process; for example, for long-duration high-pressure synthesis processes, the sampling interval for the time dimension is appropriately extended to reduce data volume. Matrix data is organized in memory in a circular buffer, supporting real-time rolling updates. The matrix export interface provides multiple data format conversion functions, facilitating seamless integration with quantum encryption modules. The acquisition of temperature gradient distribution data needs to overcome thermal noise interference in high-temperature environments; sensor signals employ differential transmission mode, and the temperature gradient distribution data undergoes wavelet denoising preprocessing. Periodic pulsation peak detection of the pressure vessel, combined with Fast Fourier Transform, accurately identifies the pulsation characteristics of different frequency components. The calculation of reaction dynamic equilibrium parameters incorporates a reaction kinetic model, making the parameters more reflective of the essential characteristics of the synthesis process. The 3D process parameter matrix generation algorithm optimizes memory access patterns, improving the processing efficiency of large data volumes.

[0026] The layout of the multi-probe sensor was optimized through computational fluid dynamics simulation to ensure that the temperature gradient distribution data accurately reflects the thermal field distribution within the reactor. The algorithm for detecting pressure pulsation peaks incorporates a machine learning classifier to distinguish between real pulsations and equipment vibration noise. Time series analysis of the reaction dynamic equilibrium parameters identifies the dynamic characteristics of the reaction system. The storage of the three-dimensional process parameter matrix uses a columnar compression format to reduce data bandwidth consumption during transmission. The temperature monitoring system for the synthesis reactor includes multi-layered protection mechanisms, and multi-point cross-validation is implemented during temperature gradient distribution data acquisition. The pressure vessel safety monitoring system integrates multiple sensor fusion technologies, performing correlation analysis between periodic pulsation peak data and vessel stress-strain data. The calculation of the reaction dynamic equilibrium parameters incorporates an adaptive filtering algorithm to dynamically adjust parameter sensitivity. The generation process of the three-dimensional process parameter matrix includes an integrity verification step to ensure that the matrix data accurately reconstructs the complete information of the synthesis process. The matrix data undergoes format standardization processing before being injected into the quantum encryption pipeline to eliminate the impact of data source differences on the encryption effect.

[0027] Example 2: See Figure 3 The process of generating dynamic key pairs based on the quantum key distribution protocol begins with the initial negotiation phase before the transmission of the process parameter matrix. The transmitter calls a quantum random number generator to produce a sequence of weakly coherent optical pulses. The average number of photons per pulse is controlled below 0.1 to meet the security requirements of quantum communication. The pulse sequence is transmitted to the receiver through an optical fiber channel. The receiver uses a single-photon detector array to capture the incident photons. The detector uses an avalanche photodiode operating in Geiger mode. The polarization state information of the captured photons is compared with a local reference in real time, and the basis vector comparison result is fed back to the transmitter. The transmitter selects matching polarization state combinations based on the basis vector comparison result. The selection principle is that both parties choose qubits with the same measurement basis to retain. The selected qubit sequence constitutes the initial key seed.

[0028] The initial key seed needs to be purified by a two-way verification mechanism. This mechanism uses a parity check protocol. The sending end divides the initial key seed into data blocks and calculates the parity check value for each block. The check value is transmitted to the receiving end through a classic authentication channel. The receiving end performs the same calculation on its local key seed and compares the check values. Data blocks that do not match are marked as potentially intercepted by a third party and discarded. The purified key bit sequence enters the hash enhancement stage. Hash enhancement uses the SHA-256 algorithm for multiple rounds of transformation. Each round of hash operation outputs ciphertext of the same length as the input key bits. The resulting dynamic key pair is stored in a tamper-proof security module. When performing quantum state encoding on sensitive data segments, the system scans the three-dimensional process parameter matrix to identify temperature mutation ranges and pressure exceedance nodes. The identification algorithm is based on the sliding window differential method, with the window size dynamically adjusted according to process characteristics. The identified sensitive data segments are converted into fixed-width binary sequences. The conversion process uses the IEEE 754 floating-point standard to maintain data precision. The binary sequence is quantized and mapped according to the phase angle of the polarized photon sequence. The mapping rule adopts the four-state encoding scheme of the BB84 protocol, and each binary bit corresponds to a photon in a specific polarization state.

[0029] The quantized data packet requires a header. The timestamp checksum embedded in the header originates from a high-precision clock source and is encrypted using the HMAC algorithm to prevent tampering. A key index identifier is associated with records in the dynamic key pool, and the index structure uses a B+ tree to optimize query efficiency. The complete quantum state data packet is loaded onto the optical carrier via a polarization modulator, with the modulation depth adaptively adjusted according to the channel signal-to-noise ratio. The quantum key distribution protocol incorporates multiple security mechanisms: phase randomization of weakly coherent optical pulses resists photon number splitting attacks, and single-photon detectors are equipped with post-pulse suppression circuits to reduce false detection rates. Active phase compensation technology is introduced during basis vector matching to eliminate the influence of optical fiber channel polarization drift. The retransmission strategy of the bidirectional verification mechanism sets a maximum number of retries to prevent denial-of-service attacks, and a true random number seed is injected during the hash enhancement stage to increase the key entropy value. The sensitive data segment identification algorithm integrates an anomaly detection model; the determination of temperature mutation intervals combines historical data trend analysis; and the identification of pressure exceeding limits introduces a multi-sensor voting mechanism. Cyclic redundancy check codes are added during the binary sequence conversion process, and depolarization channel coding is used during the quantization mapping stage to correct transmission errors. The data packet header information is encoded with forward error correction, and the timestamp checksum synchronization mechanism supports nanosecond-level precision calibration.

[0030] The driving voltage of the polarization modulator is pre-distorted to compensate for the nonlinear characteristics of photoelectric conversion. The transmission frame structure of the quantum state data packet includes a preamble for clock synchronization; the preamble uses a golden sequence with good autocorrelation. The receiver is equipped with a polarization controller to dynamically track polarization state rotation, and the quantum decoder uses a balanced zero-difference detection scheme to improve the signal-to-noise ratio. The execution efficiency of the quantum key distribution protocol is optimized through a pipelined architecture, with pulse sequence generation and basis vector comparison processed in parallel. The update cycle of the dynamic key pair is dynamically adjusted according to the security policy, and the key pool uses a rolling update mechanism to ensure forward and backward security. A layered encryption strategy is introduced for the encoding of sensitive data segments, with different encoding strengths for data of different security levels. An adaptive modulation mechanism is introduced for the transmission of quantum state data packets, automatically switching to a more robust encoding scheme when the channel quality deteriorates. The system monitors the quantum bit error rate in real time, triggering a key renegotiation process when the error rate exceeds a threshold. Hardware-level security protection for the entire encoding and transmission chain is implemented through a dedicated security chip, the core of which is to generate the root key using a physically non-clonable function and establish a hardware-isolated trusted execution environment. All key generation and cryptographic operations are performed within a secure area inside the chip, ensuring that sensitive data is never exposed to the external bus. Side-channel attack protection measures include multi-dimensional safeguards: timing characteristics are balanced through instruction randomization, power consumption differences are eliminated using power balancing circuits, and electromagnetic shielding layers attenuate radiation leakage. Physical protection integrates an optical sensor network to detect unpacking attempts, and a power monitoring circuit defends against voltage spike attacks. The trusted execution environment (TEA) uses a hardware-enforced isolation mechanism to define a secure world, and integrity measurements are performed before critical operations. The security chip and encryption module communicate via an encrypted secure bus, and a real-time security monitor verifies the system status. This system achieves end-to-end protection from data input to quantum modulation output, meeting the requirements for side-channel attack protection.

[0031] The generation of polarized photon sequences employs a feedback control mechanism, and the laser driving current is stabilized above a critical value to ensure photon statistical properties. The quantized mapping table is updated periodically to prevent pattern analysis attacks, and a version identifier is added to the data packet header to support protocol upgrades. The quantum channel and classical channel are physically isolated, and bidirectional verification information is ensured integrity through digital signatures. The analysis of the three-dimensional process parameter matrix and the identification of sensitive data are performed simultaneously; the matrix traversal algorithm optimizes cache hit rate and improves processing speed. The assembly of binary sequences uses bit-field operations to reduce memory usage, and phase angle mapping establishes a lookup table to accelerate the encoding process. The encapsulation format of quantum state data packets is compatible with standard quantum communication frameworks, supporting interconnection with other quantum network devices. The entire quantum encryption process achieves end-to-end security protection, forming a closed-loop security system from dynamic key pair generation to quantum state data packet transmission. The system's operational status is monitored in real time to assess security, and abnormal operations trigger automatic protection mechanisms. The anti-interference capability of the quantum key distribution protocol is enhanced through multi-path redundant transmission, and the reliability of sensitive data segment encoding is guaranteed by multiple verifications.

[0032] See Figure 4 In the performance evaluation of quantum communication systems, the dynamic correlation between key strength and bit error rate is visualized using a dual-axis plot, while channel transmission reliability is presented through a composite area plot and a line graph. Specifically, the changes in key strength and bit error rate during quantum key generation are designed with a dual vertical axis: the left axis maps key strength (range 0.7-0.95), and the right axis maps bit error rate (range 0-0.08). The solid black line represents the sawtooth fluctuations in key strength, and the dashed line depicts the low-range oscillations in bit error rate. The time axis spans 50 seconds, intuitively reflecting the inverse relationship between stability and error rate during key generation. The quantum channel transmission performance analysis integrates an area plot (gray filled area represents channel quality 0-1.0) and a line graph (black dashed line represents photon loss rate 0-0.14), with the time axis extending to 80 seconds. The area coverage and curve trends reveal the synergistic change mechanism between channel quality and photon loss. During parameter configuration, the key strength axis is subdivided in 0.05 increments (from 0.95 to 0.00), the bit error rate axis is incremented in 0.01 steps, and the time axis is in 10-second units; the channel quality axis uses a linear scale (0-1.0), and the photon loss rate axis has a gradient of 0.02. The visualization technology follows the IEEE format specification, with differentiated line widths to enhance the distinction of data dimensions, and the overall layout highlights the dynamic coupling effect between quantum key stability and channel reliability.

[0033] Example 3: The real-time monitoring of the bit error rate (BER) of a quantum channel begins with the statistical analysis of the number of lost polarized photons and the number of polarization state distortions within a continuous transmission window. The size of the continuous transmission window is dynamically adjusted according to channel conditions, and the window length is determined by an adaptive algorithm to balance real-time performance and accuracy. The number of lost polarized photons is recorded using a high-precision photon counter integrated into the photoelectric detection module at the receiver. The number of polarization state distortions is measured by a polarization analyzer, which uses Stokes parameters to calculate the amplitude of polarization state changes. The statistical results are uploaded to the BER calculation unit in real time. The calculation unit uses a sliding window averaging method to process the data, reducing the impact of instantaneous fluctuations. The detection of the number of lost polarized photons is based on timestamp comparison. Each transmitted photon is associated with a unique identifier. If the receiver does not detect the corresponding identifier within a predetermined time window, it is recorded as a loss event. A threshold is set for determining the number of polarization state distortions. When the measured polarization angle deviates from the theoretical value by more than a predetermined tolerance, it is counted as a distortion event.

[0034] When calculating the ratio of the number of lost polarized photons to the number of polarization state distortions relative to the total transmission volume, the total transmission volume refers to the total number of polarized photons transmitted within a continuous transmission window. The ratio is calculated using the following formula to evaluate channel quality:

[0035]

[0036] in: This represents the channel bit error rate indicator. Indicates the number of polarized photons lost. Indicates the number of polarization state distortions. This indicates the total transmission volume. The characters in the formula have the following meanings: It is the number of photon transmission failure events in the quantization channel. It is the number of events that quantize polarization state distortion. The baseline value represents the total number of photons transmitted. (Proportion) The calculated results are compared with the dynamically adjusted threshold, which is dynamically updated based on historical channel performance data. The threshold update algorithm considers channel noise levels and environmental interference factors. When the proportion... When the dynamic adjustment threshold is exceeded, the system determines that the quantum channel is in an unstable state. The determination logic is integrated into the state machine, and the state transition triggers the corresponding processing flow.

[0037] Once the quantum channel is determined to be unstable, the system immediately suspends the transmission of process parameters. The suspension mechanism is implemented through an interrupt signal, and all in-transit data packets are buffered in temporary storage. Simultaneously, a backup fiber optic link is activated for key redistribution. This backup fiber optic link employs a physically isolated redundant path, and link switching is controlled by an optical switch to ensure millisecond-level latency. The key redistribution process reuses the quantum key distribution protocol but optimizes parameters to adapt to the characteristics of the backup link, such as reducing the pulse rate to compensate for link loss. When the key update process is triggered, the system destroys the remaining unused dynamic key pairs in the current session. The destruction operation uses a secure erasure algorithm to overwrite the storage area, preventing key remnants. A destruction confirmation signal is sent to the log system to record the audit trail. Subsequently, a negotiation request pulse containing a new basis vector combination is sent to the receiver. This new basis vector combination is generated by a quantum random number generator, and the pulse encoding uses differential phase shift keying modulation. The negotiation request pulse includes a session identifier and a sequence number for matching responses.

[0038] Upon receiving a negotiation request pulse, the receiving end returns a response pulse. The polarization direction of the response pulse is determined by the local basis vector. The system compares the polarization directions of the pulses from the sending and receiving ends to ensure consistency. Consistency checks are performed using a correlation function; a match is considered successful when the correlation coefficient exceeds a set threshold. After a successful match, a new generation of dynamic key pairs is generated. The generation process incorporates a key expansion algorithm to increase entropy. The new dynamic key pair is synchronized to the key pools at both ends, and a three-way handshake is used in the synchronization protocol to ensure consistency. The system integrates multiple monitoring points to monitor the bit error rate of the quantum channel in real time. Statistics on the number of lost polarized photons introduce a misjudgment correction mechanism, such as distinguishing between photon loss and missed detections caused by detector dead time. Measurement of the number of polarization state distortions compensates for the fiber birefringence effect. The continuous transmission window adjustment strategy is based on the channel capacity model; the window size is inversely correlated with the data transmission rate to ensure real-time monitoring. The proportional calculation unit uses floating-point arithmetic to maintain accuracy, and the calculation results are smoothed to avoid jitter.

[0039] The derivation of the dynamically adjusted threshold relies on historical channel data, which is stored in a circular buffer. The threshold calculation uses a weighted moving average method, with recent data given higher weight. A hysteresis comparator is introduced to determine channel instability, preventing frequent state flips. When pausing process parameter transmission, the system saves the transmission context for easy resumption upon recovery. The startup of the backup fiber optic link undergoes link quality verification, during which test pulses are sent to measure round-trip delay. The key update process ensures thoroughness in the destruction phase, with the number of erasures of the remaining dynamic key pairs meeting security standards. The transmission power of the negotiation request pulse is adaptively adjusted to compensate for the attenuation of the backup link. An entropy source is introduced to enhance randomness in the generation of new basis vector combinations. Polarization direction consistency checks for response pulses are performed in multiple dimensions, including polarization angle and tensor analysis. The synchronization process for the next-generation dynamic key pair is encrypted to prevent man-in-the-middle attacks. Key pool updates use atomic operations to avoid inconsistencies caused by partial updates. The entire bit error rate monitoring and key update chain is automated, requiring no manual intervention. The algorithm for detecting the number of lost polarized photons optimizes time synchronization accuracy, and clock synchronization between the transmitter and receiver uses the IEEE 1588 protocol. The measurement of polarization distortion order integrates temperature compensation to eliminate thermally induced polarization drift. Dynamic memory allocation is used to manage the continuous transmission window, adapting to different data loads. The output format of the proportional calculation results is standardized for easy interaction with other system modules.

[0040] An adaptive mechanism for dynamically adjusting thresholds incorporates a machine learning model, with training data derived from long-term channel monitoring records. Response time to unstable channel conditions is optimized to the microsecond level, reducing data transmission interruption duration. The backup fiber optic link switching strategy includes fault fallback logic, automatically switching back after the primary link recovers. The key update process strengthens authentication during the negotiation phase to prevent spoofing attacks. The transmission of new basis vector combinations is encrypted, using the previous key for confidentiality. The receiver sensitivity of response pulses is dynamically adjusted to adapt to changing channel conditions. The storage of next-generation dynamic key pairs adopts a distributed architecture, reducing the risk of single-point failures. The real-time monitoring system for the quantum channel's bit error rate operates 24 / 7, with monitoring data backed up to secure storage. The key update process log records complete audit information, meeting compliance requirements. The entire system design balances performance and security, suitable for the harsh environment of high-temperature, high-pressure synthesis processes. The statistical analysis of polarization photon loss introduces redundant detection channels, with cross-validation improving accuracy. The measurement of polarization distortion counts employs multi-sensor fusion to eliminate measurement bias. Optimized boundary handling of continuous transmission windows avoids data truncation. The output interface of the proportional calculation unit is compatible with multiple protocols, supporting system integration.

[0041] The dynamic threshold update cycle is configurable to adapt to different application needs. The results of channel instability assessments are displayed in real-time on the monitoring interface to assist in operational decision-making. The maintenance status of backup fiber optic links is checked periodically to ensure availability. Performance metrics of the key update process are monitored, such as update time and success rate. Operation records for destroying the remaining parts of dynamic key pairs are logged to trigger alarm mechanisms. The encoding format of negotiation request pulses is versioned, supporting backward compatibility. The polarization direction consistency check algorithm for response pulses optimizes computational efficiency and reduces processing latency. The generation rate of next-generation dynamic key pairs is adjustable, balancing security and efficiency. The real-time monitoring system for the quantum channel's bit error rate seamlessly integrates with the upstream data acquisition module, providing real-time feedback of bit error rate data to the transmission control layer. The key update process is integrated with the existing security framework, supporting policy-driven updates.

[0042] Example 4: When parsing quantum state data packets at the receiving end, the system extracts a timestamp checksum from the header of the quantum state data packet. The timestamp checksum is stored in an encrypted format, and the decryption key is pre-set in the receiving end's security module. The decrypted timestamp is compared with the local atomic clock; if the time difference exceeds the allowable range, the data packet is discarded. When matching the dynamic key pair index in the local key pool, the index query algorithm uses a hash table structure, and the query result returns the corresponding dynamic key pair. The polarized photon sequence is decoded using the matched key pair. The decoding process is based on the principle of quantum measurement. Each photon state of the polarized photon sequence is projected onto the measurement basis through a polarization beam splitter, and the measurement result is converted into a binary sequence. After restoring the sensitive data segment to binary form, the system verifies whether the decoded temperature mutation range and pressure over-limit nodes meet the safety threshold range of the original data. The verification algorithm traverses each numerical point in the data segment and compares its relationship with the upper and lower limits of the safety threshold. When merging into a complete set of process parameters, the decoded sensitive data segment is inserted into the corresponding empty position of the non-sensitive data segment according to the timestamp. The insertion operation uses memory mapping technology to avoid performance loss caused by data copying. To verify the temporal continuity of temperature gradient distribution data and pressure pulsation peaks, the verification method calculates the numerical difference between adjacent time points. Points with a difference exceeding a set tolerance are marked as discontinuities. When the difference in the reaction dynamic equilibrium parameters exceeds a fault tolerance threshold, a local data retransmission request is triggered. The fault tolerance threshold is dynamically adjusted according to process specifications, and the retransmission request is sent to the transmitter via the control channel. See Table 1 for the verification results of quantum state data packet parsing.

[0043] Table 1: Verification Results of Quantum State Data Packet Analysis

[0044] The timestamp checksum parsing of the quantum state data packet header uses an asymmetric encryption algorithm, with the public key pre-installed in the receiver's hardware security module. Timestamp comparison takes network transmission latency into account, and the allowed time difference range is configured according to channel characteristics. The matching process of the dynamic key pair index is logged in an audit log, and failed matching attempts trigger alarms. Decoding of the polarized photon sequence is performed in real time, with the decoder using an FPGA for low-latency processing. Forward error correction is incorporated into the binary sequence reconstruction.

[0045] The verification process for sensitive data segments includes data integrity verification and hash value comparison to ensure data has not been tampered with. Verification of temperature mutation ranges focuses on checking the rationality of data mutation points, while verification of pressure exceeding limits analyzes pressure change trends. Data insertion in merge operations employs a transaction mechanism, rolling back all changes in case of insertion failure. Time sequence continuity verification calculates the first derivative of data points, marking points with abnormal derivatives as suspicious. Triggering conditions for local data retransmission requests are configurable, and retransmission requests include detailed problem descriptions. The system records metadata for each retransmission request to optimize transmission parameters. Fault tolerance threshold adjustments are based on historical data statistics, and the threshold update cycle is configurable. Quantum state packet header parsing optimizes parsing efficiency, and the timestamp checksum format is standardized. Dynamic key pair index storage uses a distributed architecture to improve query performance. The polarized photon sequence decoding algorithm optimizes photon utilization efficiency and reduces errors caused by photon loss. A clock recovery mechanism is incorporated into the binary sequence restoration process to ensure data synchronization.

[0046] The verification of sensitive data segments incorporates a machine learning model, with training data derived from historical normal process parameters. The machine learning model employs an isolated forest anomaly detection algorithm, trained on a database of historical normal process parameters, extracting statistical features of temperature, pressure, and reaction rate for unsupervised training. During online application, the model extracts features from real-time incoming sensitive data segments and calculates anomaly scores. If the score exceeds a dynamic threshold set based on historical data distribution, the sensitive data segment is deemed anomaly, triggering a visual alarm and generating a standardized report containing the anomaly score, feature contribution, and confidence interval. Verification of temperature abrupt changes is combined with equipment characteristic curves, while pressure exceeding limits is checked against vessel design parameters. Verification of temperature abrupt changes utilizes the equipment characteristic curve library, comparing the real-time temperature change rate with the curve's allowable value. Pressure exceeding limits are checked against pressure vessel design parameters, verifying whether the real-time pressure value exceeds the design safety margin. Verification results are linked to equipment operating status logs, generating a timestamped verification report. The performance of the merging operation is optimized using memory pool technology to reduce memory fragmentation. The algorithm for time-series continuity verification employs multi-scale analysis to identify anomalies at different frequencies. The implementation of partial data retransmission requests considers network load, and retransmission priority is graded according to data importance. The fault tolerance threshold is derived using statistical process control methods, dynamically adapting to process changes. The entire parsing and merging process achieves high reliability, with redundant backups for critical steps. Parsing of the quantum state data packet header supports multiple time formats, compatible with different time sources. The maintenance of the dynamic key pair index employs a lazy loading strategy to improve memory utilization efficiency. Decoding of the polarized photon sequence integrates temperature compensation, eliminating the influence of ambient temperature on polarization measurements. The output format for the restored binary sequence is configurable, supporting the needs of subsequent processing modules.

[0047] The verification results of sensitive data segments generate detailed reports with standardized report formats. Verification records for temperature abrupt change ranges document the distribution characteristics of values ​​exceeding limits, and checks the operating status of associated equipment at pressure exceeding limits. Data structure optimization for merging operations optimizes cache locality, improving access speed. Tolerance values ​​for time sequence continuity verification are set differently based on data type. The transmission protocol for partial data retransmission requests is reliable, and a retransmission acknowledgment mechanism ensures request delivery. The application of fault tolerance thresholds considers the characteristics of different production stages, setting different thresholds for different stages. The derivation of fault tolerance thresholds is based on the control chart principle in Statistical Process Control (SPC), calculating the moving range and moving average of process parameters in real time, and setting the threshold to the mean ± 3 times the standard deviation. The threshold is automatically updated based on the real-time data stream to adapt to process drift. The system provides a real-time monitoring interface for the parsing and merging process, visually displaying the data stream status. For time format errors, a backup parser is attempted; for checksum errors, data packets are discarded and the error code is recorded. The dynamic key pair index is updated using atomic operations with database transaction properties, ensuring that the updates to the index version number, key value, and other associated metadata are completed as an indivisible whole, preventing inconsistencies caused by partial updates. The decoder for the polarized photon sequence has a built-in temperature sensor that monitors the ambient temperature in real time and performs software compensation based on a pre-calibrated temperature-polarization deviation lookup table.

[0048] The dynamic key pair index is updated atomically to ensure consistency. Decoder calibration of the polarized photon sequence is performed periodically, with calibration data stored in non-volatile memory. The binary sequence restoration logic verifies data boundaries to prevent buffer overflows. The verification process for sensitive data segments is scalable, supporting the addition of new verification rules. The verification algorithm for temperature mutation ranges optimizes computational complexity, and the checking of pressure exceedance nodes is parallelized. The verification process for sensitive data segments adopts a plug-in architecture; new verification rules can be dynamically added by implementing standard interfaces and registering them in the verification rule library. The temperature mutation range verification algorithm optimizes complexity by dividing long time-series data into segments for parallel computation. Pressure exceedance node checks are processed in parallel on multi-core CPUs using independent threads for each sensor data stream. The transaction isolation level for merging operations is configurable, balancing performance and consistency. The results of time-series continuity verification are stored in a time-series database, supporting historical queries.

[0049] The implementation of partial data retransmission requests considers bandwidth limitations, with retransmission data volume adaptively adjusted. An expert knowledge base is incorporated into the fault tolerance threshold adjustment mechanism to improve the rationality of threshold settings. The entire system design emphasizes maintainability, and the modular architecture facilitates upgrades and expansion. Performance monitoring of quantum state packet header parsing is implemented, with key indicators collected in real time. The dynamic key pair index caching strategy is optimized to improve hit rate. Decoding quality assessment of polarized photon sequences and bit error rate statistics are used for system optimization. Binary sequence reconstruction output buffer management balances throughput and latency. Verification results of sensitive data segments are linked to the device alarm system, triggering device status checks upon verification failure. Verification data for temperature mutation ranges is archived for post-event analysis. Environmental parameters are recorded for pressure exceeding limits to aid root cause analysis. Memory usage optimization for merging operations reduces memory consumption. Priority management of partial data retransmission requests prioritizes the retransmission of critical data. The application of fault tolerance thresholds is logged to meet auditing requirements. The system provides a complete application programming interface, supporting integration with third-party systems.

[0050] The parsing of quantum state data packet headers supports data compression formats, reducing transmission overhead. A robust backup mechanism for dynamic key pair indexes prevents data loss. The polarized photon sequence decoder has self-diagnostic capabilities, promptly identifying hardware issues. The binary sequence reconstruction output format conversion is compatible with various data processing tools. The verification process for sensitive data segments allows for configurable verification strength to adapt to different security requirements. The verification algorithm for temperature abrupt changes provides precision adjustment options, and the check for pressure exceeding limits supports multiple threshold settings. The data consistency guarantee mechanism for merging operations is robust, and the algorithm for temporal continuity verification is continuously optimized to improve detection accuracy. The implementation of local data retransmission requests considers network topology and selects the optimal retransmission path. The derivation process of fault tolerance thresholds is transparent, and the threshold adjustment history is traceable.

[0051] Example 5: When a local data retransmission request is triggered, the system performs continuity analysis on the reaction dynamic equilibrium parameters. These parameters are derived from real-time process data streams. The analysis algorithm uses sliding window detection technology to identify discontinuous time intervals. Discontinuous time intervals in the reaction dynamic equilibrium parameters are marked using differential calculation. The system calculates the rate of change of the reaction dynamic equilibrium parameters at adjacent time points. When the rate of change exceeds a preset threshold, it is determined to be a discontinuity point. Data intervals within a specific time range before and after the discontinuity point are marked as retransmission areas. The marking operation uses red identifiers to mark the data sequence, and simultaneously generates a retransmission interval descriptor recording the start and end timestamps and abnormal characteristic values. Retransmission commands are only initiated for quantum state data packets corresponding to the marked intervals. The retransmission commands are transmitted through a dedicated control channel, and the command format uses a standardized protocol encapsulation. The retransmission command includes metadata information for the marked interval, including the interval number, data packet sequence number, timestamp range, and data integrity check value. The historical bit error rate (BER) history from the previous transmission is appended to the retransmission command. The BER history history is extracted from the channel monitoring database, and the record format includes the BER values ​​in the time series and the corresponding channel quality indicators.

[0052] When adjusting the coding strength, the system analyzes the historical bit error rate (BER) data from the previous transmission. The analysis of the BER history uses a trend prediction algorithm, and the prediction results drive the adjustment of coding parameters. Based on the BER history, the transmission rate of the polarized photon sequence is reduced using a step-down strategy, with the initial descent step dynamically calculated based on the BER value. The redundancy ratio of the parity bits in the quantum state data packets is increased. The redundancy ratio is calculated based on Shannon coding theory, and the parity bit insertion positions use an interleaved distribution scheme. A key index identifier for the previous decoding failure is embedded in the header of the retransmitted data packet. This key index identifier is embedded using an extended header field, and the receiver prioritizes processing data packets containing specific identifiers after parsing. The continuity analysis of the dynamic balance parameters sets multi-level detection sensitivity, which is dynamically adjusted according to the synthesis process stage. A conservative strategy is used when marking discontinuous time intervals, including all suspected anomalies to avoid missed detections. The transmission of retransmission commands is guaranteed to be reliable, employing an acknowledgment retransmission mechanism to ensure command delivery. The additional content of the BER history is compressed to reduce control channel bandwidth usage. The adjustment of the polarized photon sequence transmission rate considers channel capacity balance to avoid excessive reduction that could impact transmission efficiency. Redundant insertion of check bits in quantum state data packets optimizes coding efficiency while maintaining effective data throughput. The priority handling mechanism for key index identifiers is configurable, granting higher processing privileges to important data packets.

[0053] The system implements a complete retransmission pipeline, forming a closed-loop control from anomaly detection to retransmission completion. Data consistency during retransmission is ensured through a version number mechanism to prevent data corruption. Coding strength adjustment parameters take effect in real time, and the adjustment effect is optimized through feedback from the monitoring system. Anomaly detection of the dynamic balance parameters incorporates a machine learning model, with model training data derived from historical normal process parameters. Interpolation algorithms are used to determine the boundaries of marked intervals, smoothing edge data. Retransmission command generation is automated, requiring no manual intervention. Analysis results of historical bit error rate data are visualized to assist in operational decision-making. The transmission rate adjustment algorithm optimizes convergence speed, quickly adapting to channel changes. The calculation of the parity bit redundancy ratio is performed in real time, with the ratio value dynamically updated. The key index identifier embedding format is standardized, compatible with various decoding devices. The triggering conditions for local data retransmission requests can be flexibly configured to meet the needs of different process scenarios. The effectiveness of the retransmission mechanism is verified through simulation testing, with test cases covering various abnormal scenarios. The stability of coding strength adjustment has been verified through long-term operation, with smooth parameter adjustments and no abrupt changes. Monitoring data of the dynamic balance parameters is stored in a historical database for subsequent analysis and optimization. Metadata management for marked intervals utilizes database indexing technology, supporting fast querying and retrieval. The transmission status of retransmission commands is monitored in real time, and failed commands are automatically retransmitted. The storage period for historical error rate records is configurable, and expired data is automatically cleaned up. Transmission rate adjustment granularity is fine-grained, supporting differentiated settings based on data packet type. The algorithm for redundant parity bit insertion optimizes computational complexity and reduces processing latency.

[0054] The parsing efficiency of the key index identifier is optimized to avoid becoming a system bottleneck. The system provides detailed logs of the retransmission process, including the complete retransmission trajectory. Historical parameters for coding strength adjustment are traceable, supporting troubleshooting and analysis. The entire retransmission mechanism is designed for robustness, capable of handling various boundary conditions. Anomaly detection of dynamic balancing parameters incorporates multi-dimensional feature analysis to improve detection accuracy. The merging strategy for marked intervals is optimized, automatically merging adjacent intervals to reduce the number of retransmissions. Priority management of retransmission commands is intelligent, prioritizing the retransmission of important data. The algorithm for analyzing historical bit error rate records is continuously optimized to improve prediction accuracy. The upper and lower limit protection mechanism for transmission rate adjustment is robust, preventing parameters from exceeding limits. The maximum value limit for the redundancy ratio of check bits balances reliability and efficiency. The processing of the key index identifier is pipelined, improving processing throughput. The implementation of local data retransmission requests is seamlessly integrated with existing transmission protocols, maintaining system compatibility. Performance indicators of the retransmission mechanism are monitored in real time, with key indicators including retransmission success rate and average retransmission delay. The response time for coding strength adjustment is optimized to ensure timely adaptation to channel changes. The sampling frequency of the dynamic equilibrium parameters is adaptively adjusted, improving detection accuracy during high-frequency sampling. A robust verification mechanism for marked intervals allows for the elimination of mis-marked intervals through secondary detection. Encrypted transmission of retransmission commands ensures security and prevents command tampering. Strict access control over historical error rate records protects system security. The transmission rate adjustment algorithm incorporates an inertia factor to avoid parameter oscillations. Optimized bit distribution for redundant check bit insertion maximizes error correction capability. A robust caching mechanism for key index identifiers improves identifier lookup efficiency.

[0055] The system implements an intelligent retransmission strategy, dynamically selecting retransmission timing based on network conditions. The retransmission packet scheduling algorithm is fair and reasonable, avoiding channel congestion. The coding strength adjustment parameters have strong self-learning capabilities, continuously optimizing over long-term operation. The abnormal pattern recognition capability of the dynamic balancing parameters is continuously enhanced, becoming more accurate with longer system operation. Metadata for marked intervals is compressed and stored, saving storage space. Redundant backups are used for the transmission path of retransmission commands, improving command delivery reliability. Analysis of historical bit error rate records is used for preventative maintenance, identifying potential channel problems early. The sensitivity parameter for transmission rate adjustment can be adjusted online to adapt to different application scenarios. A minimum redundancy ratio for check bits is set to ensure basic reliability. The key index identifier's lifecycle management is robust, with expired identifiers automatically becoming invalid.

[0056] The processing flow for partial data retransmission requests is standardized and complies with industry standards. The retransmission mechanism is highly scalable and supports future functional expansion. The parameter interface for encoding strength adjustment is open, facilitating integration with third-party systems. The entire retransmission system is designed according to modular principles, with clearly defined responsibilities for each component. A real-time monitoring interface for dynamic balancing parameters intuitively displays the data flow status, highlighting abnormal intervals. The metadata export function for marked intervals is comprehensive, supporting offline analysis. The transmission status of retransmission commands is pushed to the monitoring center in real time for centralized management. Statistical analysis reports on historical bit error rates are generated regularly for system optimization. Historical curves of transmission rate adjustments are visualized to help understand channel variation patterns. The actual effect of the parity bit redundancy ratio is quantitatively evaluated to guide parameter tuning. Audit tracking of key index identifier usage meets security and compliance requirements.

[0057] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0058] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption, characterized in that, Includes the following steps: Obtain the real-time process parameter set of the high-temperature and high-pressure synthesis equipment, and extract the time-series variation data of temperature, pressure and reaction rate; Dynamic key pairs are generated based on a quantum key distribution protocol, and the set of process parameters is divided into sensitive data segments and non-sensitive data segments. Quantum state encoding is performed on sensitive data segments, and the encoded quantum state data packets are transmitted through polarized photon sequences. The error rate of the quantum channel is monitored in real time. If the error rate exceeds the preset threshold, the key update process is triggered to reallocate the quantum key and discard the current transmission session. The quantum state data packets at the receiving end are parsed, and the sensitive data segments are restored using dynamic key pairs. These are then merged with the non-sensitive data segments to form a complete set of process parameters. The quantum state encoding of the sensitive data segment includes: Identify temperature abrupt changes and pressure over-limit nodes that exceed safety thresholds in the three-dimensional process parameter matrix; The data segments corresponding to the mutation interval and the overlimit node are converted into binary sequences and then quantized according to the phase angle of the polarized photon sequence. Embed a timestamp checksum and a key index identifier in the header of the encoded quantum state data packet; The real-time monitoring of the bit error rate of the quantum channel includes: Statistical analysis of the number of polarized photons lost and the number of polarization state distortions within a continuous transmission window; Calculate the ratio of the number of data loss and the number of distortions to the total number of transmissions. When the ratio exceeds the dynamic adjustment threshold, it is determined to be a channel unstable state. In unstable channel conditions, process parameter transmission is paused, and a backup fiber optic link is activated for key redistribution.

2. The method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption according to claim 1, characterized in that, The set of real-time process parameters for the high-temperature and high-pressure synthesis equipment includes: Temperature gradient distribution data from multiple probe sensors inside the synthesis reactor were collected, and periodic pulsation peak values ​​of the pressure vessel were recorded. The time difference between the reactant feed rate and the product formation rate is extracted and denoted as the reaction dynamic equilibrium parameter. The temperature gradient distribution data, periodic pulsation peaks, and reaction dynamic equilibrium parameters are aligned by timestamps to generate a three-dimensional process parameter matrix.

3. The method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption according to claim 2, characterized in that, The generation of dynamic key pairs based on the quantum key distribution protocol includes: Before transmitting the process parameter matrix, a single-photon detection pulse sequence is sent to the receiving end; Based on the basis vector comparison results fed back by the receiver, the matching polarization states are selected as the initial key seed; A two-way verification mechanism is used to remove key bits that have been intercepted by third parties, and the remaining key bits are hash-enhanced to serve as the final dynamic key pair.

4. The method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption according to claim 3, characterized in that, The trigger key update process includes: Destroy any unused portions of the dynamic key pair in the current session; Send a negotiation request pulse containing the new basis vector combination to the receiving end; Based on the consistency of the polarization direction of the response pulses at the receiving end, a new generation of dynamic key pairs is generated and synchronized to the key pools at both ends.

5. The method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption according to claim 4, characterized in that, The quantum state data packets received by the parsing receiver include: Extract the timestamp checksum from the packet header and match it with the dynamic key pair index in the local key pool; By decoding the polarized photon sequence using a matched key pair, the sensitive data segment is restored to binary form. Verify whether the temperature mutation range and pressure over-limit nodes after decoding meet the safety threshold range of the original data.

6. The method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption according to claim 5, characterized in that, The merging into a complete set of process parameters includes: Insert the decoded sensitive data segments into the corresponding empty positions of the non-sensitive data segments according to their timestamps; Verify the temporal continuity between temperature gradient distribution data and pressure pulsation peaks; When the difference in the dynamic equilibrium parameters of the reaction exceeds the fault tolerance threshold, a local data retransmission request is triggered.

7. The method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption according to claim 6, characterized in that, The triggering of the partial data retransmission request includes: Discontinuous time intervals in the dynamic equilibrium parameters of the labeled reaction; Retransmission commands are only sent to quantum state data packets corresponding to the marked intervals; The retransmission command includes the historical bit error rate of the previous transmission so that the sender can adjust the coding strength.

8. The method for secure data transmission in high-temperature and high-pressure synthesis processes based on quantum encryption according to claim 7, characterized in that, The adjustment of coding strength includes: Reduce the transmission rate of polarized photon sequences based on historical bit error rate records; Increase the redundancy ratio of check bits in quantum state data packets; The key index identifier of the previous decoding failure is embedded in the header of the retransmitted data packet so that the receiving end can process it first.

Images