Abstract: A method and system determine network based access to restricted systems. The method includes receiving a request for a permission access status of a party seeking access to one of the restricted systems. A database of periodically updated lists of entities is accessed. A name of the party is extracted from the request. A determination is made whether the name does not match one of the entities. The name is decomposed into parts if the name not matching one of the entities. A determination is made whether any of the parts of the name matches one of the entities. A denial of access status is forwarded from the computer server to an external computing device if any of the parts of the name matches one of the entities.

Abstract: Techniques for facilitating quantum pulse optimization using machine learning are provided. In one example, a system includes a classical processor and a quantum processor. The classical processor employs a quantum pulse optimizer to generate a quantum pulse based on a machine learning technique associated with one or more quantum computing processes. The quantum processor executes a quantum computing process based on the quantum pulse.

Abstract: A method and system determine network based access to restricted systems. The method includes receiving a request for a permission access status of a party seeking access to one of the restricted systems. A database of periodically updated lists of entities is accessed. A name of the party is extracted from the request. A determination is made whether the name does not match one of the entities. The name is decomposed into parts if the name not matching one of the entities. A determination is made whether any of the parts of the name matches one of the entities. A denial of access status is forwarded from the computer server to an external computing device if any of the parts of the name matches one of the entities.

Abstract: The illustrative embodiments provide a method, system, and computer program product for validating quantum algorithms using a machine learning model. In an embodiment, a method includes receiving a training data set. In an embodiment, a method includes training, by a first processor, a machine learning model with the training data set for validation of quantum circuits. In an embodiment, a method includes generating, by the machine learning model, a set of rules for validation of quantum circuits.

Abstract: Techniques for quantum data post-processing are provided. In one example, a system includes a quantum programming component and a post-processing component. The quantum programming component receives quantum output data that includes a set of quantum results for a quantum circuit in response to simulation of the quantum circuit. The post-processing component adjusts the quantum output data associated with the quantum circuit based on client system data indicative of information for a client system that consumes the quantum output data.

Abstract: Techniques for managing and compressing quantum output data (QOD) associated with quantum computing are presented. In response to receiving QOD from a quantum computer, a compressor component can compress QOD at first compression level to generate first compressed QOD, and can compress QOD at second compression level to generate second compressed QOD, the second compressed QOD can be less compressed than the first compressed QOD. Compressor management component (CMC) can determine whether first QOD includes sufficient data to enable it to be suitably processed by quantum logic. If so, CMC can allow first compressed QOD to continue to be sent to quantum logic and can discard second compressed QOD. If not sufficient, CMC can determine that second compressed QOD is to be processed by quantum logic. If CMC determines second compressed QOD does not include sufficient data, CMC can determine that the QOD is to be processed by quantum logic.

Abstract: Techniques for managing and compressing quantum output data (QOD) associated with quantum computing are presented. In response to receiving QOD from a quantum computer, a compressor component can compress QOD at first compression level to generate first compressed QOD, and can compress QOD at second compression level to generate second compressed QOD, the second compressed QOD can be less compressed than the first compressed QOD. Compressor management component (CMC) can determine whether first QOD includes sufficient data to enable it to be suitably processed by quantum logic. If so, CMC can allow first compressed QOD to continue to be sent to quantum logic and can discard second compressed QOD. If not sufficient, CMC can determine that second compressed QOD is to be processed by quantum logic. If CMC determines second compressed QOD does not include sufficient data, CMC can determine that the QOD is to be processed by quantum logic.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate evaluation of quantum circuit optimization routines and knowledge base generation are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a compilation component that concurrently executes different quantum circuit optimization sequences on multiple copies of a quantum circuit. The computer executable components can further comprise an identification component that identifies at least one of the different quantum circuit optimization sequences that generates an output quantum circuit comprising defined criteria.

Abstract: A hybrid data processing environment comprising a classical computing system and a quantum computing system is configured. A configuration of a first quantum circuit is produced from the classical computing system, the first quantum circuit being executable using the quantum computing system. Using the quantum computing system, the first quantum circuit is executed. Using a pattern recognition technique, a portion of the first quantum circuit that can be transformed using a first transformation operation to satisfy a constraint on the quantum circuit design is identified. The portion is transformed to a second quantum circuit according to the first transformation operation, wherein the first transformation operation comprises reconfiguring a gate in the first quantum circuit such that a qubit used in the gate complies with the constraint on the quantum circuit design while participating in the second quantum circuit. Using the quantum computing system, the second quantum circuit is executed.

Abstract: A hybrid data processing environment, including a classical and a quantum computing system, is configured. A configuration of a first quantum circuit, executable using the quantum computing system is produced. A first analysis operation is configured for use in a first analysis pass. The first analysis operation specifies a type of analysis to be performed on the quantum circuit. Using an output of an execution of the first analysis operation, a portion of the first quantum circuit that should be transformed to satisfy a constraint on the quantum circuit design is identified. In a first transformation pass according to a first transformation operation, the portion is transformed, resulting in a second quantum circuit, by reconfiguring a gate in the first quantum circuit such that a qubit used in the gate complies with the constraint on the quantum circuit design while participating in the second quantum circuit.

Abstract: Systems and methods that can facilitate a quantum adaptive execution method based on previous quantum circuits and its intermediate results. This can generate an optimized adaptive compilation methodology for a specific backend and the previous quantum circuits dependents and thus redirect by the job dispatcher to the right quantum backend. Some of the quantum circuits can be dependent on other quantum circuits based on the intermediate results produced by the previous circuits. Hence, it is valuable that a system can manage the optimization of circuits based on its dependencies and by the results generated by the previous quantum circuits. In this way, the system can get an optimal result for a quantum circuit and inject it to the compiler unit to generate an adaptive compilation result. The resulted post-processing unit is the one in charge to apply this logic and manage the input/output of data to push it in the compiler units and the job dispatcher.

Abstract: Techniques for managing and compressing quantum output data (QOD) associated with quantum computing are presented. In response to receiving QOD from a quantum computer, a compressor component can compress QOD at first compression level to generate first compressed QOD, and can compress QOD at second compression level to generate second compressed QOD, the second compressed QOD can be less compressed than the first compressed QOD. Compressor management component (CMC) can determine whether first QOD includes sufficient data to enable it to be suitably processed by quantum logic. If so, CMC can allow first compressed QOD to continue to be sent to quantum logic and can discard second compressed QOD. If not sufficient, CMC can determine that second compressed QOD is to be processed by quantum logic. If CMC determines second compressed QOD does not include sufficient data, CMC can determine that the QOD is to be processed by quantum logic.

Abstract: Systems and methods that can facilitate a quantum adaptive execution method based on previous quantum circuits and its intermediate results. This can generate an optimized adaptive compilation methodology for a specific backend and the previous quantum circuits dependents and thus redirect by the job dispatcher to the right quantum backend. Some of the quantum circuits can be dependent on other quantum circuits based on the intermediate results produced by the previous circuits. Hence, it is valuable that a system can manage the optimization of circuits based on its dependencies and by the results generated by the previous quantum circuits. In this way, the system can get an optimal result for a quantum circuit and inject it to the compiler unit to generate an adaptive compilation result. The resulted post-processing unit is the one in charge to apply this logic and manage the input/output of data to push it in the compiler units and the job dispatcher.

Abstract: Techniques regarding the dispatchment of adapted quantum computer programs are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a dispatch component that can adapt a quantum circuit of a quantum computer program comprised within a queue based on a parameter of a quantum computer that is assigned to execute the quantum computer program.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate adaptive compilation of quantum computing jobs are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a selection component that selects a quantum device to execute a quantum program based on one or more run criteria. The computer executable components can further comprise an adaptive compilation component that modifies the quantum program based on one or more attributes of the quantum device to generate a modified quantum program compilation of the quantum program.

Abstract: Techniques for facilitating quantum pulse optimization using machine learning are provided. In one example, a system includes a classical processor and a quantum processor. The classical processor employs a quantum pulse optimizer to generate a quantum pulse based on a machine learning technique associated with one or more quantum computing processes. The quantum processor executes a quantum computing process based on the quantum pulse.

Abstract: The illustrative embodiments provide a method, system, and computer program product for validating quantum algorithms using a machine learning model. In an embodiment, a method includes receiving a training data set. In an embodiment, a method includes training, by a first processor, a machine learning model with the training data set for validation of quantum circuits. In an embodiment, a method includes generating, by the machine learning model, a set of rules for validation of quantum circuits.

Abstract: A hybrid data processing environment comprising a classical computing system and a quantum computing system is configured. A configuration of a first quantum circuit is produced from the classical computing system, the first quantum circuit being executable using the quantum computing system. Using the quantum computing system, the first quantum circuit is executed. Using a pattern recognition technique, a portion of the first quantum circuit that can be transformed using a first transformation operation to satisfy a constraint on the quantum circuit design is identified. The portion is transformed to a second quantum circuit according to the first transformation operation, wherein the first transformation operation comprises reconfiguring a gate in the first quantum circuit such that a qubit used in the gate complies with the constraint on the quantum circuit design while participating in the second quantum circuit. Using the quantum computing system, the second quantum circuit is executed.

Abstract: A hybrid data processing environment, including a classical and a quantum computing system, is configured. A configuration of a first quantum circuit, executable using the quantum computing system is produced. A first analysis operation is configured for use in a first analysis pass. The first analysis operation specifies a type of analysis to be performed on the quantum circuit. Using an output of an execution of the first analysis operation, a portion of the first quantum circuit that should be transformed to satisfy a constraint on the quantum circuit design is identified. In a first transformation pass according to a first transformation operation, the portion is transformed, resulting in a second quantum circuit, by reconfiguring a gate in the first quantum circuit such that a qubit used in the gate complies with the constraint on the quantum circuit design while participating in the second quantum circuit.

Abstract: Techniques regarding the dispatchment of adapted quantum computer programs are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a dispatch component that can adapt a quantum circuit of a quantum computer program comprised within a queue based on a parameter of a quantum computer that is assigned to execute the quantum computer program.