Abstract: A method of performing a computational process using a quantum computer includes measuring a coupling strength of each trapped ion in an ion chain and each motional mode of the ion chain, wherein the trapped ions comprises first trapped ions that are addressable by laser beams, and second trapped ions that are not addressable by laser beams, computing a first map of the first trapped ions to the motional modes, wherein the motional mode comprises first motional modes that are allocated by the first map and second motional modes that are unallocated by the first map, measuring frequencies of the first motional modes, computing a second map of the first trapped ions to the second motional modes, measuring frequencies of the second motional modes, and outputting the measured frequencies of the motional modes, to be used for computing a pulse to be applied to the ion chain.

Abstract: The present disclosure relates to channel estimation, at a receiving device of a communication system employing a (re)configurable surface. The channel estimation includes beamforming search to obtain trained reflection coefficients of the configurable surface and an angle of arrival, AoA, of the signals at the receiving device. Then, based on the configurable surface and the obtained AoA at the receiving device, reflection coefficients of the configurable surface are derived for an ideal channel portion between the transmitting device and the configurable surface. According to a relation between the trained reflection coefficients and the estimated reflection coefficients, the estimation of the characteristics of a channel between the transmitting device and the configurable surface is performed.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: The disclosure describes various aspects of quantum computer simulators. In an aspect, a method for characterizing a quantum computer simulator includes identifying simulator processes supported by the quantum computer simulator, generating, for each simulator process, characteristic curves for different gates or quantum operations, the characteristic curves including information for predicting the time it takes to simulate each of the gates or quantum operations in a respective simulator process, and providing the characteristic curves to select one of the simulator processes to simulate a circuit, quantum program, or quantum algorithm that uses at least some of the gates or quantum operations. In another aspect, a method for optimizing simulations in a quantum computer simulator is described where a simulator process is selected for simulation of a circuit, quantum program, or quantum algorithm based on characteristic curves that predict a time it takes for the simulation to be carried out.

Abstract: The disclosure describes various aspects of a software-defined quantum computer. For example, a software-defined quantum computing architecture for allocating qubits is described that includes an application programming interface (API); a quantum operating system (OS) on which the API executes, with the quantum OS including a resource manager and a switch; and a plurality of quantum cores connected by the switch of the quantum resource OS. Moreover, the resource manager of the quantum resource OS determines an allocation of a plurality of qubits in the plurality of quantum cores.

Abstract: The disclosure describes various aspects of a software-defined quantum computer. For example, a method is described for generating an intermediate representation of source code for a software-defined quantum computer. The method includes performing a lexical analysis on a high-level intermediate representation of a quantum programming language; performing semantic analysis on an output of the lexical analysis; and generating a mid-level intermediate representation of the quantum programming language based on an output of the semantic analysis.

Abstract: The disclosure describes various aspects of a software-defined quantum computer. For example, a software-defined quantum computer and an expandable/modular quantum computer are described. Also described are at least a software-defined quantum architecture, a resource manager workflow, a quantum compiler architecture, hardware description language configuration, levels of application programming interface (API) access points, and exception handling in software-defined quantum architecture.

Abstract: Technologies are described herein to implement quantum hybrid computations. Embodiments include receiving a hybrid program, assigning respective functions corresponding to the hybrid program to either of CPU processing or QPU processing, scheduling processing for the respective functions, initiating execution of the hybrid program, and collating results of the execution of the classical-quantum hybrid program.

Abstract: Technologies are described herein to track information storage resources in a quantum circuit during compile time or runtime of a program by which quantum algorithms are built.

Abstract: Technologies are described herein to implement quantum hybrid computations. Embodiments include receiving a hybrid program, assigning respective functions corresponding to the hybrid program to either of CPU processing or QPU processing, scheduling processing for the respective functions, initiating execution of the hybrid program, and collating results of the execution of the classical-quantum hybrid program.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to a combinatorial optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient method for an optimization routine executed by the classical computer in solving a problem in a hybrid quantum-classical computing system, which can provide improvement over the conventional method for an optimization by conventional stochastic optimization methods.

Abstract: Technologies are described herein to compile a Turing-complete quantum programming language program into a quantum circuit. The techniques described and recited herein include compiling TCQPL source code to generate a quantum circuit by generating a function object ensemble, generating an abstract syntax tree from received source code, and annotating nodes corresponding to the abstract syntax tree with corresponding function objects.

Abstract: Technologies are described herein to compile a Turing-complete quantum programming language program into a quantum circuit. The techniques described and recited herein include compiling TCQPL source code to generate a quantum circuit by generating a function object ensemble, generating an abstract syntax tree from received source code, and annotating nodes corresponding to the abstract syntax tree with corresponding function objects.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: Embodiments described herein are generally related to a method and a system for performing a computation using a hybrid quantum-classical computing system, and, more specifically, to providing an approximate solution to an optimization problem using a hybrid quantum-classical computing system that includes a group of trapped ions. A hybrid quantum-classical computing system that is able to provide a solution to a combinatorial optimization problem may include a classical computer, a system controller, and a quantum processor. The methods and systems described herein include an efficient and noise resilient method for constructing trial states in the quantum processor in solving a problem in a hybrid quantum-classical computing system, which provides improvement over the conventional method for computation in a hybrid quantum-classical computing system.

Abstract: Technologies are described herein to track information storage resources in a quantum circuit during compile time or runtime of a program by which quantum algorithms are built.

Abstract: Technologies are described herein to implement quantum hybrid computations. Embodiments include receiving a hybrid program, assigning respective functions corresponding to the hybrid program to either of CPU processing or QPU processing, scheduling processing for the respective functions, initiating execution of the hybrid program, and collating results of the execution of the classical-quantum hybrid program.