Abstract: The illustrative embodiments provide a method, system, and computer program product for quantum feature kernel alignment using a hybrid classical-quantum computing system. An embodiment of a method for hybrid classical-quantum decision maker training includes receiving a training data set. In an embodiment, the method includes selecting, by a first processor, a sampling of objects from the training set, each object represented by at least one vector. In an embodiment, the method includes applying, by a quantum processor, a set of quantum feature maps to the selected objects, the set of quantum maps corresponding to a set of quantum kernels. In an embodiment, the method includes evaluating, by a quantum processor, a set of parameters for a quantum feature map circuit corresponding to at least one of the set of quantum feature maps.

Abstract: Systems and techniques that facilitate Hamiltonian simulation based on simultaneous-diagonalization are provided. In various embodiments, a partition component can partition one or more Pauli operators of a Hamiltonian into one or more subsets of commuting Pauli operators. In various embodiments, a diagonalization component can generate one or more simultaneous-diagonalization circuits corresponding to the one or more subsets. In various aspects, a one of the one or more simultaneous-diagonalization circuits can diagonalize the commuting Pauli operators in a corresponding one of the one or more subsets. In various embodiments, an exponentiation component can generate one or more exponentiation circuits corresponding to the one or more subsets. In various aspects, a one of the one or more exponentiation circuits can exponentiate the simultaneously diagonalized commuting Pauli operators in a corresponding one of the one or more subsets.

Abstract: Techniques for mitigating readout error for quantum expectation are presented. Calibration component applies first random Pauli gates to qubits at first output of first circuit prior to first readout measurements of the qubits. Estimation component applies second random Pauli gates to qubits at second output of second circuit prior to second readout measurements of the qubits, and generates an error-mitigated readout determination based on first random Pauli gates applied to qubits at first circuit output and second random Pauli gates applied to qubits at second circuit output. Calibration component determines calibration data based on first readout measurements. Estimation component determines estimation data based on second readout measurements.

Abstract: Techniques that combine quantum error correction and quantum error mitigation are used to simulate a fault-tolerant T-gate with low sampling overhead using the quasiprobability decomposition method. In some embodiments, the T-gate can be simulated using two logical bits and a magic state preparation that mitigates the need for magic state distillation and consequently has a low sampling overhead. Alternatively, the T-gate can be simulated based on code deformation performed on the surface code. Noise is removed from the T-gate using quasiprobability decomposition based on a learned logical error rate.

Abstract: Techniques and a system to facilitate quantum computation are provided. In one example, a system includes a processor that executes computer executable components stored in a memory; a quantum feature map circuit component that estimates a kernel associated with a feature map; and a support vector machine component that performs a classification using the estimated kernel.

Abstract: Systems and techniques that facilitate Hamiltonian simulation based on simultaneous-diagonalization are provided. In various embodiments, a partition component can partition one or more Pauli operators of a Hamiltonian into one or more subsets of commuting Pauli operators. In various embodiments, a diagonalization component can generate one or more simultaneous-diagonalization circuits corresponding to the one or more subsets. In various aspects, a one of the one or more simultaneous-diagonalization circuits can diagonalize the commuting Pauli operators in a corresponding one of the one or more subsets. In various embodiments, an exponentiation component can generate one or more exponentiation circuits corresponding to the one or more subsets. In various aspects, a one of the one or more exponentiation circuits can exponentiate the simultaneously diagonalized commuting Pauli operators in a corresponding one of the one or more subsets.

Abstract: Techniques using short depth circuits as quantum classifiers are described. In one embodiment, a system is provided that comprises: quantum hardware, a memory that stores computer-executable components and a processor that executes computer-executable components stored in the memory. In one implementation, the computer-executable components comprise a calibration component that calibrates quantum hardware to generate a short depth quantum circuit. The computer-executable components further comprise a cost function component that determines a cost function for the short depth quantum circuit based on an initial value for a parameter of a machine-learning classifier. The computer-executable components further comprise a training component that modifies the initial value for the parameter during training to a second value for the parameter based on the cost function for the short depth quantum circuit.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate external port measurement of qubit port responses 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 an analysis component that can analyze responses of a multi-mode readout device coupled to a qubit. The computer executable components can further comprise an assignment component that can assign a readout state of the qubit based on the responses. In some embodiments, the multi-mode readout device can be electrically coupled to at least one of the qubit or an environment of the qubit based on a defined electrical coupling value.

Abstract: The illustrative embodiments provide a method, system, and computer program product for quantum feature kernel alignment using a hybrid classical-quantum computing system. An embodiment of a method for hybrid classical-quantum decision maker training includes receiving a training data set. In an embodiment, the method includes selecting, by a first processor, a sampling of objects from the training set, each object represented by at least one vector. In an embodiment, the method includes applying, by a quantum processor, a set of quantum feature maps to the selected objects, the set of quantum maps corresponding to a set of quantum kernels. In an embodiment, the method includes evaluating, by a quantum processor, a set of parameters for a quantum feature map circuit corresponding to at least one of the set of quantum feature maps.

Abstract: Implementing a hybrid classical-quantum neural network includes constructing, by at least a first processor, a neural network for classification of input data. The neural network includes a plurality of neural network components. The at least a first processor initiates training of the neural network using training data. The at least a first processor identifies one or more of the plurality of neural network components for replacement. A quantum processor constructs a quantum component corresponding to the one or more network components. The one or more identified neural network components of the neural network are replaced with the quantum component to construct a hybrid classical-quantum neural network.

Abstract: One or more time correlations of noise within a quantum computing circuit of a quantum processor are determined. The quantum computing circuit includes one or more qubits. A coherence time for each qubit is determined, and one or more stretch factors are determined based upon the time correlations of the noise and the coherence times. A first loop is initialized that performs for each of the stretch factors: initializing the qubits to a ground state, executing the quantum computing circuit with a the stretch factor, performing one or more single-qubit post-rotations associated with one or more expectation values, measuring a state of each qubit to determine the one or more expectation values of interest, and resetting each qubit to the ground state. A mitigated estimate is determined for the expectation values based upon an extrapolation of the expectation values determined for each stretch factor.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate external port measurement of qubit port responses 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 an analysis component that can analyze responses of a multi-mode readout device coupled to a qubit. The computer executable components can further comprise an assignment component that can assign a readout state of the qubit based on the responses. In some embodiments, the multi-mode readout device can be electrically coupled to at least one of the qubit or an environment of the qubit based on a defined electrical coupling value.

Abstract: One or more time correlations of noise within a quantum computing circuit of a quantum processor are determined. The quantum computing circuit includes one or more qubits. A coherence time for each qubit is determined, and one or more stretch factors are determined based upon the time correlations of the noise and the coherence times. A first loop is initialized that performs for each of the stretch factors: initializing the qubits to a ground state, executing the quantum computing circuit with a the stretch factor, performing one or more single-qubit post-rotations associated with one or more expectation values, measuring a state of each qubit to determine the one or more expectation values of interest, and resetting each qubit to the ground state. A mitigated estimate is determined for the expectation values based upon an extrapolation of the expectation values determined for each stretch factor.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate external port measurement of qubit port responses 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 an analysis component that can analyze responses of a multi-mode readout device coupled to a qubit. The computer executable components can further comprise an assignment component that can assign a readout state of the qubit based on the responses. In some embodiments, the multi-mode readout device can be electrically coupled to at least one of the qubit or an environment of the qubit based on a defined electrical coupling value.

Abstract: A technique relates to reducing qubits required on a quantum computer. A Fermionic system is characterized in terms of a Hamiltonian. The Fermionic system includes Fermions and Fermionic modes with a total number of 2M Fermionic modes. The Hamiltonian has a parity symmetry encoded by spin up and spin down parity operators. Fermionic modes are sorted such that the first half of 2M modes corresponds to spin up and the second half of 2M modes corresponds to spin down. The Hamiltonian and the parity operators are transformed utilizing a Fermion to qubit mapping that transforms parity operators to a first single qubit Pauli operator on a qubit M and a second single qubit Pauli operator on a qubit 2M. The qubit M having been operated on by the first single qubit Pauli operator and the qubit 2M having been operated on by the second single qubit Pauli operator are removed.

Abstract: Techniques and a system to facilitate quantum computation are provided. In one example, a system includes a processor that executes computer executable components stored in a memory; a quantum feature map circuit component that estimates a kernel associated with a feature map; and a support vector machine component that performs a classification using the estimated kernel.

Abstract: A technique relates to reducing qubits required on a quantum computer. A Fermionic system is characterized in terms of a Hamiltonian. The Fermionic system includes Fermions and Fermionic modes with a total number of 2M Fermionic modes. The Hamiltonian has a parity symmetry encoded by spin up and spin down parity operators. Fermionic modes are sorted such that the first half of 2M modes corresponds to spin up and the second half of 2M modes corresponds to spin down. The Hamiltonian and the parity operators are transformed utilizing a Fermion to qubit mapping that transforms parity operators to a first single qubit Pauli operator on a qubit M and a second single qubit Pauli operator on a qubit 2M. The qubit M having been operated on by the first single qubit Pauli operator and the qubit 2M having been operated on by the second single qubit Pauli operator are removed.

Abstract: A technique relates to reducing qubits required on a quantum computer. A Fermionic system is characterized in terms of a Hamiltonian. The Fermionic system includes Fermions and Fermionic modes with a total number of 2M Fermionic modes. The Hamiltonian has a parity symmetry encoded by spin up and spin down parity operators. Fermionic modes are sorted such that the first half of 2M modes corresponds to spin up and the second half of 2M modes corresponds to spin down. The Hamiltonian and the parity operators are transformed utilizing a Fermion to qubit mapping that transforms parity operators to a first single qubit Pauli operator on a qubit M and a second single qubit Pauli operator on a qubit 2M. The qubit M having been operated on by the first single qubit Pauli operator and the qubit 2M having been operated on by the second single qubit Pauli operator are removed.

Abstract: Techniques using short depth circuits as quantum classifiers are described. In one embodiment, a system is provided that comprises: quantum hardware, a memory that stores computer-executable components and a processor that executes computer-executable components stored in the memory. In one implementation, the computer-executable components comprise a calibration component that calibrates quantum hardware to generate a short depth quantum circuit. The computer-executable components further comprise a cost function component that determines a cost function for the short depth quantum circuit based on an initial value for a parameter of a machine-learning classifier. The computer-executable components further comprise a training component that modifies the initial value for the parameter during training to a second value for the parameter based on the cost function for the short depth quantum circuit.

Abstract: A technique relates to reducing qubits required on a quantum computer. A Fermionic system is characterized in terms of a Hamiltonian. The Fermionic system includes Fermions and Fermionic modes with a total number of 2M Fermionic modes. The Hamiltonian has a parity symmetry encoded by spin up and spin down parity operators. Fermionic modes are sorted such that the first half of 2M modes corresponds to spin up and the second half of 2M modes corresponds to spin down. The Hamiltonian and the parity operators are transformed utilizing a Fermion to qubit mapping that transforms parity operators to a first single qubit Pauli operator on a qubit M and a second single qubit Pauli operator on a qubit 2M. The qubit M having been operated on by the first single qubit Pauli operator and the qubit 2M having been operated on by the second single qubit Pauli operator are removed.