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Classical and quantum optimization of quantum processors

Tim Menke

Published Jan 1, 2022• 0 citations
OpenAlex

Abstract

Quantum interactions are strikingly different from their classical counterparts, and they lead to counter-intuitive effects such as quantum entanglement. The advances in quantum science and technology over the past two decades have shown that such interactions can be harnessed in quantum devices to address hard computational problems. The field of quantum computation has emerged, and superconducting circuits have become a leading platform for quantum processors. Because of the large design space and the difficulty to simulate design prototypes on a classical computer, a key challenge in quantum processor engineering is to translate desired quantum characteristics into a circuit design. A particular obstacle has been the implementation of interactions between multiple quantum bits (qubits) in one coupling mechanism. Multi-qubit interactions are necessary for a number of applications in quantum annealing, analog quantum simulation, and digital quantum computation. In this work, we develop classical and quantum computational methods to address the challenge of implementing such interactions. We present a computational method for automated design of superconducting circuits. Our method performs a parallelized, closed-loop optimization to design superconducting circuit diagrams that match predefined properties, such as dispersion features and noise sensitivities. We employ it to design a coupler for superconducting flux qubits that mediates 4-qubit interactions. The coupler circuit is then realized experimentally. We find that it has the desired ground state dispersion properties versus flux and that it does not adversely affect the lifetime of a connected flux qubit. Moreover, the coupling concept can be extended by systematically adding loops to the coupler. In a second iteration, we implement a circuit architecture in which the coupler mediates interactions between three flux qubits. The system Hamiltonian is estimated via multi-qubit pulse sequences that implement Ramsey-type interferometry between all neighboring excitation manifolds. We verify that the multi-qubit system exhibits a 3-qubit coupling that is coherently tunable, which is important for practical applications. Finally, we address the challenge that complex multi-qubit circuits are difficult to simulate accurately on a classical computer as they become larger. As a solution, we propose quantum algorithms to design and test the performance of next-generation quantum hardware on a quantum computer. We have therefore addressed the challenge of quantum device design both from a classical optimization and from a quantum computational angle.

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Quantum interactions are strikingly different from their classical counterparts, and they lead to counter-intuitive effects such as quantum entanglement. The advances in quantum science and technology over the past two decades have shown that such interactions can be harnessed in quantum devices to address hard computational problems. The field of quantum computation has emerged, and superconducting circuits have become a leading platform for quantum processors. Because of the large design space and the difficulty to simulate design prototypes on a classical computer, a key challenge in quantum processor engineering is to translate desired quantum characteristics into a circuit design. A particular obstacle has been the implementation of interactions between multiple quantum bits (qubits) in one coupling mechanism. Multi-qubit interactions are necessary for a number of applications in quantum annealing, analog quantum simulation, and digital quantum computation. In this work, we develop classical and quantum computational methods to address the challenge of implementing such interactions. We present a computational method for automated design of superconducting circuits. Our method performs a parallelized, closed-loop optimization to design superconducting circuit diagrams that match predefined properties, such as dispersion features and noise sensitivities. We employ it to design a coupler for superconducting flux qubits that mediates 4-qubit interactions. The coupler circuit is then realized experimentally. We find that it has the desired ground state dispersion properties versus flux and that it does not adversely affect the lifetime of a connected flux qubit. Moreover, the coupling concept can be extended by systematically adding loops to the coupler. In a second iteration, we implement a circuit architecture in which the coupler mediates interactions between three flux qubits. The system Hamiltonian is estimated via multi-qubit pulse sequences that implement Ramsey-type interferometry between all neighboring excitation manifolds. We verify that the multi-qubit system exhibits a 3-qubit coupling that is coherently tunable, which is important for practical applications. Finally, we address the challenge that complex multi-qubit circuits are difficult to simulate accurately on a classical computer as they become larger. As a solution, we propose quantum algorithms to design and test the performance of next-generation quantum hardware on a quantum computer. We have therefore addressed the challenge of quantum device design both from a classical optimization and from a quantum computational angle.
Nonpairwise multiqubit interactions present a useful resource for quantum information processors. Their implementation would facilitate more efficient quantum simulations of molecules and combinatorial optimization problems, and they could simplify error suppression and error correction schemes. Here, we present a superconducting circuit architecture in which a coupling module mediates two-local and three-local interactions between three flux qubits by design. The system Hamiltonian is estimated via multiqubit pulse sequences that implement Ramsey-type interferometry between all neighboring excitation manifolds in the system. The three-local interaction is coherently tunable over several MHz via the coupler flux biases and can be turned off, which is important for applications in quantum annealing, analog quantum simulation, and gate-model quantum computation.
Abstract Superconducting circuits have emerged as a promising platform to build quantum processors. The challenge of designing a circuit is to compromise between realizing a set of performance metrics and reducing circuit complexity and noise sensitivity. At the same time, one needs to explore a large design space, and computational approaches often yield long simulation times. Here, we automate the circuit design task using SCILLA. The software SCILLA performs a parallelized, closed-loop optimization to design superconducting circuit diagrams that match predefined properties, such as spectral features and noise sensitivities. We employ it to design 4-local couplers for superconducting flux qubits and identify a circuit that outperforms an existing proposal with a similar circuit structure in terms of coupling strength and noise resilience for experimentally accessible parameters. This work demonstrates how automated design can facilitate the development of complex circuit architectures for quantum information processing.
The field of quantum information has been a fast growing field of research in the last few decades. The reason for this development is the potentially immense power of quantum computers, capable of solving hard problems in a fraction of the time it would take a classical computer. Quantum annealers are a type of quantum computer that seek to solve computational problems by finding the ground state of a quantum system. This type of quantum computer has been implemented on a large scale using superconducting flux quantum bits, but the computational power is limited. One potential improvement to help in this context is the implementation of multi-body interactions between quantum bits. Many-body interactions would be useful in allowing quantum annealers to solve more complex problems that are relevant in various areas of quantum information and science and implementing quantum error correction. \n \nWe present a superconducting device that implements a strong and tunable in sign and magnitude three-body interaction between superconducting flux quantum bits. The circuit design proposed has vanishing two-body interactions and robustness against noise and parameter variations. This circuit behaves as an ideal computational basis ZZZ coupler in a simulated three-qubit quantum annealing experiment. These properties are confirmed by calculations based on the Born-Oppenheimer approximation, a two-level spin model for the coupling circuit, and full numerical diagonalization. \n \nThe proposed circuit is based on already available technology and therefore could be readily implemented in the next generation of quantum annealing hardware. This work will be relevant for advanced quantum annealing protocols and future developments of high-order many-body interactions in quantum computers and simulators.
Abstract Quantum annealing provides a way of solving optimization problems by encoding them as Ising spin models which are implemented using physical qubits. The solution of the optimization problem then corresponds to the ground state of the system. Quantum tunneling is harnessed to enable the system to move to the ground state in a potentially high non-convex energy landscape. A major difficulty in encoding optimization problems in physical quantum annealing devices is the fact that many real world optimization problems require interactions of higher connectivity, as well as multi-body terms beyond the limitations of the physical hardware. In this work we address the question of how to implement multi-body interactions using hardware which natively only provides two-body interactions. The main result is an efficient circuit design of such multi-body terms using superconducting flux qubits in which effective N -body interactions are implemented using N ancilla qubits and only two inductive couplers. It is then shown how this circuit can be used as the unit cell of a scalable architecture by applying it to a recently proposed embedding technique for constructing an architecture of logical qubits with arbitrary connectivity using physical qubits which have nearest-neighbor four-body interactions. It is further shown that this design is robust to non-linear effects in the coupling loops, as well as mismatches in some of the circuit parameters.
Quantum computing, a paradigm shift with the potential to revolutionize fields ranging from cryptography to optimization, is rapidly evolving. This survey delves into the key quantum computing architectures—gate-based and quantum annealing—and their profound impact on circuit design and optimization. Gate-based systems, such as those utilizing superconducting qubits and trapped ions, offer versatile platforms capable of executing a broad array of quantum algorithms. However, they present unique challenges for circuit designers, including noise sensitivity, scalability, and the need for complex error correction circuits. Quantum annealing, exemplified by D-Wave systems, offers a more specialized approach to solving optimization problems, requiring distinct circuit design considerations focused on energy efficiency and coherence preservation.This paper reviews the foundational research on these architectures, compares their respective design challenges, and examines the optimization techniques that have emerged in response to these challenges. Gate count reduction, error correction, and hybrid quantum-classical methods are highlighted as key approaches for improving circuit efficiency and scalability in quantum systems. Furthermore, this survey emphasizes the importance of interdisciplinary collaboration between quantum physicists, electrical engineers, and computer scientists to address the complex challenges associated with quantum circuit design. By combining expertise from these fields, researchers can develop innovative solutions that bridge the gap between theoretical concepts and practical hardware implementations. Ultimately, this survey underscores the need for continued innovation at the intersection of quantum computing and electrical engineering, as researchers strive to overcome current limitations and develop practical, large-scale quantum systems that can harness the full potential of this revolutionary technology.
Superconducting circuits have emerged as a promising platform to build quantum processors. The challenge of designing a circuit is to compromise between realizing a set of performance metrics and reducing circuit complexity and noise sensitivity. At the same time, one needs to explore a large design space, and computational approaches often yield long simulation times. Here we automate the circuit design task using SCILLA, a software for automated discovery of superconducting circuits. SCILLA performs a parallelized, closed-loop optimization to design circuit diagrams that match pre-defined properties such as spectral features and noise sensitivities. We employ it to discover 4-local couplers for superconducting flux qubits and identify a circuit that outperforms an existing proposal with similar circuit structure in terms of coupling strength and noise resilience for experimentally accessible parameters. This work demonstrates how automated discovery can facilitate the design of complex circuit architectures for quantum information processing.