I am going to post here all newly submitted articles on the arXiv related to superconducting circuits. If your article has been accidentally forgotten, feel free to contact me
27
Jul
2026
Numerical Modeling of Quasiparticle-Induced Dissipation in Fluxonium Qubits
Nonequilibrium quasiparticles (QPs) generated by stray infrared and ionizing radiation can limit the performance of superconducting quantum processors and present challenges for quantum
error correction schemes. Models of QP-induced energy relaxation commonly assume that the characteristic energy of the QPs and the qubit transition energy are both small relative to the superconducting gap. Under these assumptions, certain qubits such as the fluxonium would exhibit protection against QP-induced dissipation at specific bias points. Here, we show that this is not necessarily the case, numerically analyzing the predicted rate of QP-induced dissipation in fluxonium qubits for different QP energy distributions and for QPs created via photon-assisted tunneling processes. We find that accounting for small numerical factors, existing theoretical models predict sensitivity to QP-induced errors at bias points previously thought to be protected. We find that inclusion of asymmetry in the superconducting gap energy across the junction can reintroduce suppression of QP-induced relaxation, as expected. Additionally, for QPs created by photon-assisted tunneling, we predict that T1 protection will only occur for a specific energy of pair-breaking radiation. This understanding of fluxonium sensitivity to QP-induced dissipation informs the development of fluxonium-based processors and future QP-mitigation strategies.
26
Jul
2026
Purcell-Engineered Hybrid Coupler for Leakage-Suppressed Robust CZ Gates
We propose a Purcell-engineered notch-filter hybrid coupler for superconducting controlled-Z (CZ) gates that combines coherent interaction engineering with leakage-selective dissipation.
The architecture integrates a nonlinear transmon coupler with a coupled Purcell-filter and notch-resonator subsystem, providing additional control over both the coherent interaction pathways and the engineered dissipative environment. The filter branch reshapes the effective interaction pathways, while the notch resonator further tailors the frequency response of the coupled filter network and preserves strong leakage-selective dissipation.
Using dressed-eigenstate analysis together with Lindblad master-equation simulations, we show that the proposed architecture substantially reduces leakage and improves the worst-case computational-state fidelity compared with an optimized single-transmon coupler while remaining robust over a broad range of coherence assumptions and device parameters. The optimized gate achieves Favg=99.74%, Fmin=99.62%, and a maximum leakage probability of 1.6×10−3. These results demonstrate that engineered dissipation complements conventional coherent interaction engineering and provides an additional design degree of freedom for realizing robust, high-fidelity superconducting CZ gates.
Mitigation of Measurement-Induced State Transitions via a Fast-Load and Fast-Clear Readout
High-fidelity and rapid qubit readout is essential for superconducting quantum processors, typically realized through the quantum non-demolition (QND) dispersive interaction within
a qubit-resonator architecture. However, the achievable readout speed and fidelity are fundamentally limited by measurement-induced state transitions (MIST). For a transmon qubit, MIST is highly sensitive to the offset charge ng due to the charge dispersion of its higher-lying energy levels. In this work, we systematically investigate ng-dependent MIST dynamics governed by the diabaticity and symmetry of pulse shaping within a charge-sensitive transmon architecture. We engineer fast-load and fast-clear pulses that effectively suppress resonator photon overshoots, thereby demonstrating a highly practical strategy to mitigate MIST without requiring complex waveforms or real-time feedback. Utilizing active gate-voltage control and rapid feedback, the measurement-induced transition probability is precisely mapped against ng and the steady-state resonator photon number, exhibiting strong agreement with numerical Floquet branch analysis. Ultimately, we evaluate the ng-averaged total error probabilities for both readout and post-readout stages, verifying that a straightforward three-step pulse scheme consistently minimizes overall readout errors. Within the framework of large-scale superconducting quantum processors, this practical, hardware-free approach inherently offers a better trade-off between the readout signal-to-noise ratio and QND preservation.
24
Jul
2026
Can a quantum circuit detect the Unruh effect?
The Unruh effect predicts that an accelerating observer perceives the Minkowski vacuum as a thermal bath, yet direct detection remains experimentally inaccessible. Its timelike counterpart,
arising from the entanglement of massless fields between the future and past light cones, offers a more feasible route but requires a detector whose transition frequency follows a specific conformal-time scaling. We propose and analyze a practical implementation of such a detector using superconducting fluxonium circuits, which naturally provide two quasi-degenerate ground states and a tunable excited state, forming an effective Λ-system. By modulating the excited-state transition frequency in Minkowski time, the detector accumulates a geometric phase associated with the timelike Unruh effect. Open-system simulations predict ∼10% shift in the ground-state population within 530 ns, representing a three-order-of-magnitude sensitivity enhancement over two-level Unruh-DeWitt detectors. These results establish a realistic quantum-circuit platform for experimentally probing the timelike Unruh effect and, more broadly, for testing fundamental nature of quantum fields using engineered quantum systems.
Substrate-metal interface engineering enhances TaN/Ta thin film superconducting resonator performance
Tantalum has been demonstrated as a promising material for superconducting qubits. However, comparatively little attention has been given to its nitrides. Tantalum nitride exhibits
a range of stoichiometries, resulting in a variety of material properties, including both superconducting and non-superconducting phases. Owing to this versatility, tantalum nitrides can serve multiple purposes in superconducting qubits: as seed layers for alpha-Ta growth, as a superconducting base material and as a non-superconducting barrier in the Josephson junction. In this study, we explore the performance of superconducting TaN and Ta thin film combinations on silicon substrates in terms of internal quality factor Qi. We find that standalone TaN films exhibit Qi values of about 1.5×10^5 at 100mK in the single-photon regime. Surprisingly, a resonator made from Ta grown on a few-nanometers-thick TaN seed layer yields largely the same performance. However, adding an additional, few-nanometers-thick Ta buffer layer between the Si substrate and this TaN seed layer enhances Qi significantly up to 5.9×10^5. Supporting transmission electron microscopy measurements reveal nitrogen accumulation and structural disorder at the TaN-Si interface, while this interfacial modification is suppressed when the Ta buffer layer is introduced. The observed improvement in resonator performance is consistent with a reduction of interface-related two-level system losses and strongly supports the hypothesis that controlling the substrate-metal interface is pivotal for the performance of superconducting qubit circuitry.
Low loss superconducting resonators enabled by aluminum microstructural engineering and dielectric trimming
Material losses in superconducting circuits fundamentally limit qubit coherence times and resonator quality factors. Most research efforts focus on mitigating losses at circuit interfaces,
including metal–substrate, substrate–air, and metal–air interfaces. However, the correlation between TLS and non-TLS losses with the intrinsic properties of the superconducting metal and the dielectric edge smoothness is not well studied. In this work, we link the aluminum film grain size to non-TLS losses and the dielectric trimming profile and roughness to TLS loss; both loss mechanisms are subsequently mitigated. To reduce metal-related losses, we engineer the aluminum microstructure by heating during deposition, increasing grain size and reducing grain boundary density. Beyond mitigating metal losses, we introduce a two-step etching technique, Tropic etching, to suppress dielectric TLS loss by producing an ultra-smooth silicon surface with minimal defects and redeposition. These results lay out the fabrication pathway for aluminum resonators with lower loss, demonstrating two-orders-of-magnitude improvement in quality factor from 6×104 to 2.3×106. Since aluminum is the basis for most high-coherence Josephson junctions and dielectric edges are inherent to all common device geometries, the improvements in aluminum microstructure and edge profiling, presented here, can enhance the performance of superconducting quantum devices.
Capacitive Loading in Two-dimensional Fluxonium Quantum Processors
Capacitive loading has emerged as a major obstacle to scaling fluxonium qubits from one-dimensional to highly connected two-dimensional (2D) architectures, yet its physical origin remains
poorly understood. We derive an analytical relation between the qubit capacitance budget and the achievable capacitive coupling to external circuit elements, identifying the parasitic capacitances of Josephson junctions and Josephson junction arrays as the dominant source of capacitive loading while showing that the qubit-pad geometry can instead be engineered to mitigate it. Building on these insights, we formulate practical design principles and numerically demonstrate ultrafast, high-fidelity two-qubit gates in 2D fluxonium architectures. Our results reveal that capacitive loading does not constitute a fundamental limit for 2D fluxonium quantum processors.
Quantum advantage of nonlinear quantum battery and superconducting circuit implementation
A quantum battery is a novel energy storage device that operates on the principles of quantum mechanics. To enhance the charging performance of quantum batteries and further provide
theoretical support for their physical implementation, we constructed an optical-field-dependent nonlinear quantum battery model. Meanwhile, we solved for the unbiased form of nonlinear interactions in this model, where the charging power of the proposed model exhibits a superlinear quantum advantage, and the charging time saturates the quantum speed limit. Through theoretical analysis, we confirm that this quantum advantage arises from the quantum effect of multiphoton absorption. Subsequently, with the derived nonlinear function form, we further investigated other properties of this nonlinear quantum battery. Finally, an experimental design scheme for this nonlinear quantum battery in superconducting quantum circuits is presented.
23
Jul
2026
Quasiparticle-induced transitions in a fluxonium qubit
Quasiparticles are a prominent decoherence source in superconducting qubits, but their effects are notoriously difficult to isolate in fluxonium. Unlike a transmon, fluxonium is insensitive
to offset charge, precluding charge-parity detection of quasiparticle tunneling. We address this challenge by measuring the excitation and de-excitation rates in a fluxonium qubit under controlled on-chip quasiparticle injection. We show that to accurately model the external magnetic flux dependence of the quasiparticle-induced transition rates, it is necessary to account for the superconducting gap asymmetry across the Josephson junctions. A comparison between theory and experiment constrains the relative quasiparticle contributions of the junction array and the small junction and helps explain previously reported discrepancies between the bounds on the quasiparticle densities inferred for these two circuit elements.
22
Jul
2026
Component-Level Inverse Design of Transmon Qubits Using Neural Networks
Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer chooses
a 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.