The increasingly complex quantum electronic circuits with a number of coupled quantum degrees of freedom will become intractable to be simulated on classical computers, and requires quantum computers for an efficient simulation. In turn, it will be a central concept in quantum-aided design for next-generation quantum processors. Here, we demonstrate variational quantum eigensolvers to simulate superconducting quantum circuits with varying parameters covering a plasmon-transition regime, which reveals an advanced post-transmon qubit, "plasmonium". We fabricate this new qubit and demonstrate that it exhibits not only high single- and two-qubit gate fidelities (99.85(1)% and 99.58(3)%, respectively), but also a shrinking (by 60%) physical size and larger (by 50%) anharmonicity than the transmon, which can bring a number of advantages for scaling up multi-qubit devices. Our work opens the way to designing advanced quantum processors using existing quantum computing resources.
The increasingly complex quantum electronic circuits with a number of coupled quantum degrees of freedom will become intractable to be simulated on classical computers, and requires quantum computers for an efficient simulation. In turn, it will be a central concept in quantum-aided design for next-generation quantum processors. Here, we demonstrate variational quantum eigensolvers to simulate superconducting quantum circuits with varying parameters covering a plasmon-transition regime, which reveals an advanced post-transmon qubit, "plasmonium". We fabricate this new qubit and demonstrate that it exhibits not only high single- and two-qubit gate fidelities (99.85(1)% and 99.58(3)%, respectively), but also a shrinking (by 60%) physical size and larger (by 50%) anharmonicity than the transmon, which can bring a number of advantages for scaling up multi-qubit devices. Our work opens the way to designing advanced quantum processors using existing quantum computing resources.
Abstract The past half century has witnessed the rapid development of integrated circuits from several to billions of electronic components, where a crucial enabling method was the electronic computer-aided design. Similarly, simulations of the quantum electrocircuits will play a key role in designing advanced quantum computers. While these simulations could be done classically on a small scale, the resources required for the classical simulations will grow exponentially with the complexity of the strongly-correlated quantum hardwares. Here, we demonstrate quantum computer-aided design of a new high-performance superconducting qubit based on variational quantum simulations. The discovered new qubits intrinsically have important features superior to the widely used transmons qubits, because the new design eliminates the charge noise but without sacrificing anharmonicity and thus has a larger anharmonicity than the transmons. The new qubit - which we call “plasmonium” - is compatible with the control technologies in the transmon, exhibits long coherence time, and can bring in a number of practical advantages, including shrinking physical sizes, improving gate and readout fidelity, reducing state leakage, and alleviating frequency crowding in multi-qubit devices.
With the increasing size of quantum processors, submodules that constitute the processor hardware will become too large to accurately simulate on a classical computer. Therefore, one would soon have to fabricate and test each new design primitive and parameter choice in time-consuming coordination between design, fabrication, and experimental validation. Here we show how one can design and test the performance of next-generation quantum hardware---by using existing quantum computers. Focusing on superconducting transmon processors as a prominent hardware platform, we compute the static and dynamic properties of individual and coupled transmons. We show how the energy spectra of transmons can be obtained by variational hybrid quantum-classical algorithms that are well suited for near-term noisy quantum computers. In addition, single- and two-qubit gate simulations are demonstrated via Suzuki-Trotter decomposition. Our methods pave a promising way towards designing candidate quantum processors when the demands of calculating submodule properties exceed the capabilities of classical computing resources.
This thesis mainly summarizes two experiments that relate to building a quantum computer out of superconducting transmon qubits. Transmon qubits have emerged as one of the foremost solid state qubits, realizing processors with more than ten qubits and demonstrating small scale quantum algorithms as well as quantum error correction schemes. Right now, there is a race between different academic and industry research groups to scale up transmon qubit processors. The first experiment was a demonstration of qubit control by selective broadcasting in order to reduce the scaling of expensive electronics with the number of qubits for individual single-qubit control. We demonstrated that we can bring two transmon qubits to the same frequency (combining fabrication accuracy and in-situ fine tuning) and use the same hardware to control both, routing the pulses with a nanosecond-timescale vector switch matrix. Despite the compromises required by this technique, we show a scalable path to single qubit control beyond the threshold required for quantum error correction. In benchmarking, we take into account gate leakage due to the fact that transmons are fundamentally multi-level systems. In the second experiment we establish entanglement between two transmon qubits on different chips. We use an entanglement by measurement scheme and demonstrate that we can overcome minor fabrication imperfections by shaping our measurement pulses. Ultimately, performance is mainly limited by photon loss between the chips and up to the amplification chain. This entanglement mediated by traveling photons could be used to make a distributed transmon processor where computations are spread across several chip modules. This modularity could enable connectivities that cannot be realized on chip and ease fabrication requirements, as modules could be individually fabricated and selected. Thus, both of these experiments fit into the larger effort to converge on the hardware, control equipment and architecture of a future large-scale transmon quantum computer. Other experiments I contributed to are summarized in the conclusion chapter to show the diverse physics that can be studied in cQED experiments.
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.
Scaling of superconducting-based quantum computers has been possible since the invention of transmon qubits due to their low charge noise sensitivity. However, pursuing fault-tolerant and computationally powerful quantum processors may require incorporating more qubits, which may amplify the complexity of the large design space exploration and simulation. Inspired by the recent CMOS Machine Learning assisted electronic design automation to solve similar issues, we claim this work is the first to demonstrate applying machine learning in superconducting circuit design. To start, we attempt to predict the characteristics of individual transmon qubits with a machine learning-based approach based on the simulation data collected with relevant software frameworks like Qiskit Metal and ANSYS Electronics. Our approach aims to perform forward modeling to predict the qubit engineering parameters such as frequency. On the other hand, the machine learning-based model can also infer, through inverse modeling, the candidate sets of design space parameters like the device dimensions satisfying a particular specification while obeying the geometrical constraint of the transmon types. This work paves an alternative way for future applications in designing and automating superconducting quantum computing circuits.
Quantum computers have gained widespread interest as they can potentially solve problems that are intractable even for today’s supercomputers, such as the simulation of quantum systems as initially proposed by Feynman. To achieve such tremendous progress, a quantum computer relies on processing the information stored in quantum bits (qubits), the fundamental units of quantum computation, similar to the bits in a classical (i.e., non-quantum) processor. In general, a quantum processor comprising several qubits is connected through a quantum-to-classical interface consisting of classical electrical circuits for manipulating and reading out their quantum state. The accuracy of an operation on a qubit is characterized using the fidelity, which is 100 % in case of a perfect operation. In practice, a fidelity between 99 % and 99.9 % is typically achieved in today’s experiments with less than 100 qubits, limited by non-idealities in the control signals and by the implementation of the physical qubit itself. Since such qubit fidelities are too low to execute relevant quantum algorithms, quantum error correction schemes have been developed which rely on a much larger number of qubits to correct for possible errors, resulting in the need for quantum processors with thousands or millions of qubits. Solid-state qubits promise the largescale integration required to scale to millions of qubits, as they exploit the lithographic fabrication techniques borrowed from the semiconductor industry. However, state-of-theart solid-state qubits, such as transmons and single-electron spin qubits, must be typically cooled to cryogenic temperatures in a dilution refrigerator to exhibit quantum behavior. Because of the limited number of qubits (< 100) in state-of-theart solid-state quantum processors, the classical controller is currently implemented by general-purpose instruments or by tailor-made controllers operating at room temperature connected via several wires to the qubits in the cryogenic chamber. However, these systems must scale to support millions of qubits. While scaling up the underlying quantum processor is already exceptionally challenging, building the electronics required to interface such a large-scale processor is just as relevant and arduous.