Abstract: 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.

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: Techniques are provided for improving quantum computing devices. The technology can facilitate generating a sequence of sparse matrices representing a quantum computing device and a noise model. A system can comprise a memory that can store computer executable components and a processor that can execute the computer executable components stored in the memory. The computer executable components can include a term identifier that can identify a plurality of time-dependent terms in a machine-parseable representation of a quantum computing device. The computer executable components can further include a sparse matrix generator that can generate a first sparse matrix for ones of the plurality of time-dependent terms, resulting in a plurality of first sparse matrices.

Abstract: 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.

Abstract: Systems, computer-implemented methods and/or computer program products are provided for facilitating error mitigation for classical data output from a classical system and/or for qubit data output from a quantum system. 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 computation component that performs error mitigation employing less than a full set of assignment matrix elements. In one or more embodiments, the error mitigation can be performed without constructing an assignment matrix. Additionally and/or alternatively, the computer executable components can comprise a computation component that performs error mitigation employing an iterative solver using the less than a full set of assignment matrix elements as the initial input set for the iterative solver.

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 method is performed to compile input data including a plurality of pulse sequences, hardware parameters obtained from a computing device, and a mathematical model with time-dependent control parameters to decrease a computation time of the input data. The method also includes providing the input data to the computing device to allow the computing device to run a computation of the input data. The method further includes converting the pulse sequences into memory-aligned arrays to decrease the computation time of the input data. The method includes calculating optimized output data using an adaptive step size computation to decrease the computation time needed to compute the output data.

Abstract: A method is performed to compile input data including a plurality of pulse sequences, hardware parameters obtained from a computing device, and a mathematical model with time-dependent control parameters to decrease a computation time of the input data. The method also includes providing the input data to the computing device to allow the computing device to run a computation of the input data. The method further includes converting the pulse sequences into memory-aligned arrays to decrease the computation time of the input data. The method includes calculating optimized output data using an adaptive step size computation to decrease the computation time needed to compute the output data.

Abstract: A method is performed to compile input data including a plurality of pulse sequences, hardware parameters obtained from a computing device, and a mathematical model with time-dependent control parameters to decrease a computation time of the input data. The method also includes providing the input data to the computing device to allow the computing device to run a computation of the input data. The method further includes converting the pulse sequences into memory-aligned arrays to decrease the computation time of the input data. The method includes calculating optimized output data using an adaptive step size computation to decrease the computation time needed to compute the output data.

Abstract: A method is performed to compile input data including a plurality of pulse sequences, hardware parameters obtained from a computing device, and a mathematical model with time-dependent control parameters to decrease a computation time of the input data. The method also includes providing the input data to the computing device to allow the computing device to run a computation of the input data. The method further includes converting the pulse sequences into memory-aligned arrays to decrease the computation time of the input data. The method includes calculating optimized output data using an adaptive step size computation to decrease the computation time needed to compute the output data.

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: Techniques are provided for improving quantum computing devices. The technology can facilitate generating a sequence of sparse matrices representing a quantum computing device and a noise model. A system can comprise a memory that can store computer executable components and a processor that can execute the computer executable components stored in the memory. The computer executable components can include a term identifier that can identify a plurality of time-dependent terms in a machine-parseable representation of a quantum computing device. The computer executable components can further include a sparse matrix generator that can generate a first sparse matrix for ones of the plurality of time-dependent terms, resulting in a plurality of first sparse matrices.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate visualizing arbitrary pulse shapes and schedules in quantum computing applications are provided. According to an embodiment, a system can a processor that can execute computer executable components stored in memory. The system can further comprise a collection component that can receive a pulse schedule of pulse data and control parameters of a quantum device comprising default pulse data of the quantum device. The system can further comprise a plotting component that can generate a plot of the pulse schedule based on the pulse data, the control parameters, and the default pulse data. The system can further comprise a visualization component that can generate a display of the pulse schedule.

Abstract: 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.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate visualizing arbitrary pulse shapes and schedules in quantum computing applications are provided. According to an embodiment, a system can a processor that can execute computer executable components stored in memory. The system can further comprise a collection component that can receive a pulse schedule of pulse data and control parameters of a quantum device comprising default pulse data of the quantum device. The system can further comprise a plotting component that can generate a plot of the pulse schedule based on the pulse data, the control parameters, and the default pulse data. The system can further comprise a visualization component that can generate a display of the pulse schedule.

Abstract: Techniques facilitating local optimization of quantum circuits are provided. In one example, a computer-implemented method comprises applying, by a device operatively coupled to a processor, respective weights to matrix elements of a first matrix corresponding to a quantum circuit according to respective numbers of quantum gates between respective pairs of qubits in the quantum circuit; transforming, by the device, the first matrix into a second matrix based on the respective weights of the matrix elements; and permuting, by the device, respective qubits in the quantum circuit according to the second matrix, resulting in a permuted quantum circuit.

Abstract: Techniques facilitating local optimization of quantum circuits are provided. In one example, a computer-implemented method comprises applying, by a device operatively coupled to a processor, respective weights to matrix elements of a first matrix corresponding to a quantum circuit according to respective numbers of quantum gates between respective pairs of qubits in the quantum circuit; transforming, by the device, the first matrix into a second matrix based on the respective weights of the matrix elements; and permuting, by the device, respective qubits in the quantum circuit according to the second matrix, resulting in a permuted quantum circuit.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate visualizing arbitrary pulse shapes and schedules in quantum computing applications are provided. According to an embodiment, a system can a processor that can execute computer executable components stored in memory. The system can further comprise a collection component that can receive a pulse schedule of pulse data and control parameters of a quantum device comprising default pulse data of the quantum device. The system can further comprise a plotting component that can generate a plot of the pulse schedule based on the pulse data, the control parameters, and the default pulse data. The system can further comprise a visualization component that can generate a display of the pulse schedule.