International Business Machines Corporation

Ismael Faro Sertage

Jay Michael Gambetta

Francisco Jose Martin Fernandez

Ali Javadiabhari

Paul Nation

Lev Samuel Bishop

Marco Pistoia

Andrew P Wack

Andrew W Cross

Daniel Joseph Friedman

Alberto Valdes Garcia

Utz Bacher

Michael Man Behrendt

Peng Liu

Divya Gopinath

Yahya Mesgarpour Tousi

Renier Rodriguez Morales

Blake Johnson

Iván Durán Martínez

Sanjay Kumar Lalta Prasad Vishwakarma

Sanket Panda

Juan Cruz Benito

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.

Quantum circuit optimization routine evaluation and knowledge base generation

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.

Natural language processing for restricting user access to systems

A compatibility is ascertained between a configuration of a quantum processor (q-processor) of a quantum cloud compute node (QCCN) in a quantum cloud environment (QCE) and an operation requested in a first instruction in a portion (q-portion) of a job submitted to the QCE, the QCE including the QCCN and a conventional compute node (CCN), the CCN including a conventional processor configured for binary computations. In response to the ascertaining, a quantum instruction (q-instruction) is constructed corresponding to the first instruction. The q-instruction is executed using the q-processor of the QCCN to produce a quantum output signal (q-signal). The q-signal is transformed into a corresponding quantum computing result (q-result). A final result is returned to a submitting system that submitted the job, wherein the final result comprises the q-result.

Job processing in quantum computing enabled cloud environments

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.

Dynamic quantum data output post-processing

A method for validation and runtime estimation of a quantum algorithm includes receiving a quantum algorithm and simulating the quantum algorithm, the quantum algorithm forming a set of quantum gates. The method further includes analyzing a first set of parameters of the set of quantum gates and analyzing a second set of parameters of a set of qubits performing the set of quantum gates. The method further includes transforming, in response to determining at least one of the first set of parameters or the second set of parameters meets an acceptability criterion, the quantum algorithm into a second set of quantum gates.

Validating and estimating runtime for quantum algorithms

One or more computer processors receive a domain name system (DNS) request in response to a client connecting to a compute resource. The one or more computer processors decoding the DNS request into one or more provision parameters. The one or more computer processors determining that the compute resource is unavailable for a connection with the client utilizing the identified IP address. The one or more computer processors, responsive to determining that the compute resource is not available or not ready, provisioning and deploying a new compute resource according to the one or more decoded provision parameters, wherein the new compute resource is available to the client under the identified IP address.

Domain name based deployment

Systems and techniques that facilitate backend quantum runtimes are provided. In various embodiments, a system can comprise a backend receiver component that can access a computer program provided by a client device, wherein the computer program is configured to indicate a quantum computation. In various aspects, the system can further comprise a backend runtime manager component that can host the computer program by instantiating a backend classical computing resource. In various instances, the backend classical computing resource can orchestrate both classical execution of the computer program and quantum execution of the quantum computation indicated by the computer program.

Backend quantum runtimes

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.

Quantum pulse optimization using machine learning

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.

Machine learning quantum algorithm validator

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.

Quantum data post-processing

Techniques facilitating quantum software developer kit and framework as a service are provided. 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 an execution component that executes, on a quantum device located within a cloud computing environment, a code based on an identification of the code received from a communication device. A quantum software development kit can execute on the communication device.

Quantum software developer kit and framework

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.

Quantum circuit optimization using machine learning

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.

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Chappaqua, NY, United States of America

Ismael Faro Sertage