Abstract: Various aspects of the disclosure relate to verification of data sets used for real-time processes and/or batch processes. A computing platform negotiates, by a first quantum node, a shared key group with at least a second quantum node and calculates an exclusive or (XOR) value of a pair of the first quantum node and the second quantum node. The first quantum service node performs a shared key grouping with the second quantum node and then selects a quantum key relay link between a real-time node and a batch source node. The computing platform selects a corresponding state of all virtual quantum nodes associated with the quantum key relay link and encapsulates a virtual quantum link state between any two quantum service nodes in the quantum network into a database decision engine data file.

Abstract: Aspects of the disclosure relate to intelligently aggregating data using a convolutional network quantum processor. Using an artificial intelligence model, a computing platform may identify dependencies derived from a consumer request and corresponding values. For each configuration of dependency and corresponding value, the computing platform may determine a likelihood of success. The computing platform may alter the configurations and may determine a likelihood of success for each altered configuration. The computing platform may train a convolutional network to analyze the consumer request using the configurations, the altered configurations, and/or corresponding likelihoods of success. The convolutional network may generate a function that describes the dependencies derived from the consumer request. Using a quantum processing model, the computing platform may analyze different states of the function in parallel and may determine whether to approve or deny the consumer request based on the analysis.

Abstract: A system for implementing a quantum-based application programming interface (API) failure detection and virtualization is disclosed. The system receives an API data packet and converts the API data packet into a set of quantum state arrays. The system generates a unified buffer array that is associated with the corresponding tasks from among the API data packets. The system validates that the unified buffer array corresponds to a quantum representation of the API data packet by comparing the unified buffer array with a vector that comprises binary bits associated with the API data packet and determining that the unified buffer array corresponds to the vector.

Abstract: Aspects of the disclosure relate to quantum cloud computing. A computing platform may receive an event processing request from a user. The computing platform may obtain, via a first API, external consumer data corresponding to the user. The computing platform may generate, based on the external consumer data, a response code, indicating whether or not the external consumer data is authenticated. The computing platform may generate, based on the response code, response information, indicating whether or not to process the event processing request. Based on identifying that the response information indicates that the event processing request should be processed, the computing platform may send, to an enterprise computing device, one or more commands directing the enterprise computing device to process the event processing request, which may cause the enterprise computing device to process the event processing request.

Abstract: Various aspects of the disclosure relate to verification of data sets used for real-time processes and/or batch processes. A computing platform negotiates, by a first quantum node, a shared key group with at least a second quantum node and calculates an exclusive or (XOR) value of a pair of the first quantum node and the second quantum node. The first quantum service node performs a shared key grouping with the second quantum node and then selects a quantum key relay link between a real-time node and a batch source node. The computing platform selects a corresponding state of all virtual quantum nodes associated with the quantum key relay link and encapsulates a virtual quantum link state between any two quantum service nodes in the quantum network into a database decision engine data file.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: A quantum computing platform may receive application programming interface (API) information. The quantum computing platform may convert the API information to a two qubit state. The quantum computing platform may apply, to the converted API information, a CNOT gate, which may produce a trip wire flag value of zero or one. Based on identifying a trip wire flag value of zero, the quantum computing platform may activate a quantum trip wire, which may cause at least a portion of the API information to be routed to an overflow processing system.

Abstract: Aspects of the disclosure relate to quantum cloud computing. A computing platform may receive an event processing request from a user. The computing platform may obtain, via a first API, external consumer data corresponding to the user. The computing platform may generate, based on the external consumer data, a response code, indicating whether or not the external consumer data is authenticated. The computing platform may generate, based on the response code, response information, indicating whether or not to process the event processing request. Based on identifying that the response information indicates that the event processing request should be processed, the computing platform may send, to an enterprise computing device, one or more commands directing the enterprise computing device to process the event processing request, which may cause the enterprise computing device to process the event processing request.

Abstract: Aspects of the disclosure relate to intelligently aggregating data using a convolutional network quantum processor. Using an artificial intelligence model, a computing platform may identify dependencies derived from a consumer request and corresponding values. For each configuration of dependency and corresponding value, the computing platform may determine a likelihood of success. The computing platform may alter the configurations and may determine a likelihood of success for each altered configuration. The computing platform may train a convolutional network to analyze the consumer request using the configurations, the altered configurations, and/or corresponding likelihoods of success. The convolutional network may generate a function that describes the dependencies derived from the consumer request. Using a quantum processing model, the computing platform may analyze different states of the function in parallel and may determine whether to approve or deny the consumer request based on the analysis.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.

Abstract: Aspects of the disclosure relate to dynamic model configuration and execution. A computing platform may receive first model data comprising first model execution configuration data and first model output configuration data. The computing platform may generate a first model based on the first model execution configuration data. The computing platform may distribute, to a plurality of computing platforms, the first model, the first model execution configuration data, and the first model output configuration data. The computing platform may receive a second request to execute one or more models from a third computing platform. The computing platform may receive, from the third computing platform, first model execution data. The computing platform may execute the first model based on the first model execution data and the first model execution configuration data to generate a first model output score.