Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer choosesa layout geometry, simulates it, extracts circuit parameters such as capacitances, and refines the geometry. We study the inverse version of this task using a neural-network workflow that maps target Hamiltonian parameters directly to component-level layout parameters, which we subsequently demonstrate on a planar transmon layout. During training, we pair the inverse model with a frozen forward surrogate model and evaluate the loss in Hamiltonian space rather than in layout-parameter space. In validation against a conventional EM solver, 97% of generated designs produce usable geometries, and the inverse-plus-surrogate pipeline reaches mean percent errors of 0.73% for qubit frequency and 1.58% for anharmonicity, comparable to or below the fabrication and simulation-to-measurement uncertainty expected for academic-process transmon devices of this type. A single pipeline query takes approximately 56 ms on CPU, versus approximately 2 min for a conventional EM capacitance extraction on the same hardware, a speedup of more than 2,100 times. Batching minimizes the AI model inference overhead, reducing the runtime to 0.24 ms per sample on CPU and 2.5 microseconds per sample on GPU, resulting in speedups of 5.0 x 10^5 and 4.8 x 10^7, respectively, relative to a single conventional CPU EM extraction. Our results indicate that component-level inverse design usefully extends and complements conventional EM simulation, including for small datasets on the order of 1,000 samples.
Superconducting quantum circuit design is reliant on accurately mapping design parameters to a quantum Hamiltonian. Designers typically rely on computationally intensive finite-elementelectromagnetic simulations. However, effective circuit-level models can in principle capture much of the relevant physics for these systems, reducing the need for finite-element simulations. A barrier to implementing these simpler models has been the prevalence of distributed elements such as coplanar waveguides resonators in device designs. Techniques for modeling these distributed elements have been developed, but may be difficult to scale, reduce intuition, and give inaccurate results under strong coupling. In this work we describe a simple effective circuit-level model that faithfully reproduces the scattering parameters, and subsequently can predict certain Hamiltonian parameters, for a coupled, distributed element within a broader two-port network even up to strong coupling. Our approach does not explicitly require an electromagnetic simulation. Our model, along with other common lumped models used in black box quantization, is publicly available to researchers via an open-source code package, .
Multimode circuits provide an avenue for flexible control of single and multi-qubit gates. In this work we implement a multimode circuit known as a trimon integrated in a planar geometry.The trimon features three transmon-like modes with strong all-to-all ZZ coupling. We demonstrate high fidelity operations on the trimon, achieving flexible control of its rich state space. This includes qubit rotations conditioned on one or both other qubits, unconditional single-qubit rotations, and both excitation-conserving and double-excitation two-qubit entangling gates. Through multi-tone driving we are able to implement all 16 two-qubit Pauli operators in the two-qubit space. We further demonstrate using the trimon as a qudit with up to 8 states and higher coherence than typical transmon-based implementations. Our results show a compact, highly controllable device that can potentially replace transmons in standard superconducting processor architectures.
In this short review we describe the process of designing a superconducting circuit device for quantum information applications. We discuss the factors that must be considered to implementa desired effective Hamiltonian on a device. We describe the translation between a device’s physical layout, the circuit graph, and the effective Hamiltonian. We go over the process of electromagnetic simulation of a device layout to predict its behavior. We also discuss concerns such as connectivity, crosstalk suppression, and radiation shielding, and how they affect both on-chip design and enclosure structures. This paper provides an overview of the challenges in superconducting quantum circuit design and acts as a starter document for researchers working on any of these challenges.
We utilize a superconducting qubit processor to experimentally probe the transition from non-Markovian to Markovian dynamics of an entangled qubit pair. We prepare an entangled statebetween two qubits and monitor the evolution of entanglement over time as one of the qubits interacts with a small quantum environment consisting of an auxiliary transmon qubit coupled to its readout cavity. We observe the collapse and revival of the entanglement as a signature of quantum memory effects in the environment. We then engineer the non-Markovianity of the environment by populating its readout cavity with thermal photons to show a transition from non-Markovian to Markovian dynamics, reaching a regime where the quantum Zeno effect creates a decoherence-free subspace that effectively stabilizes the entanglement between the qubits.
Quasiparticle (QP) effects play a significant role in the coherence and fidelity of superconducting quantum circuits. The Andreev bound states of high transparency Josephson junctionscan act as low-energy traps for QPs, providing a mechanism for studying the dynamics and properties of both the QPs and the junction. We study the trapping and clearing of QPs from the Andreev bound states of epitaxial Al-InAs Josephson junctions incorporated in a superconducting quantum interference device (SQUID) galvanically shorting a superconducting resonator to ground. We use a neighboring voltage-biased Josephson junction to inject QPs into the circuit. Upon the injection of QPs, we show that we can trap and clear QPs when the SQUID is flux-biased. We examine effects of the microwave loss associated with bulk QP transport in the resonator, QP-related dissipation in the junction, and QP poisoning events. By monitoring the QP trapping and clearing in time, we study the dynamics of these processes and find a time-scale of few microseconds that is consistent with electron-phonon relaxation in our system and correlated QP trapping and clearing mechanisms. Our results highlight the QP trapping and clearing dynamics as well as the associated time-scales in high transparency Josephson junctions based fabricated on Al-InAs heterostructures.