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Applied Physics Letters

Alternating-bias assisted annealing of micrometer-scale Josephson junctions

Qingyu Wang, Jie Zhao, Wenchang Yan, Wei Xin, Yang Yu

Published Aug 31, 2026• 0 citations
Publisher

Abstract

Alternating-bias assisted annealing (ABAA) has been effectively utilized to tune the normal-state resistance of sub-micrometer Josephson junctions (JJs). However, how the annealing efficiency is affected by pre-annealing thermal history, oxidation exposure, and junction geometry remains unexplored for micrometer-scale devices. Here, we systematically investigate the ABAA behavior in micrometer-scale JJs to address the growing demands of modern superconducting devices. The dependence of resistance tuning on the pre-annealing heating time, annealing temperature, bias voltage, oxidation exposure, junction linewidth, and aspect ratio is thoroughly characterized. Our results will contribute a predictive framework for the precise resistance control of micrometer-scale JJs, thereby guiding the deterministic fabrication of high-performance superconducting quantum hardware.

DOI
10.1063/5.0347836

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Alternating-bias assisted annealing (ABAA) has been effectively utilized to tune the normal-state resistance of sub-micrometer Josephson junctions (JJs). However, how the annealing efficiency is affected by pre-annealing thermal history, oxidation exposure, and junction geometry remains unexplored for micrometer-scale devices. Here, we systematically investigate the ABAA behavior in micrometer-scale JJs to address the growing demands of modern superconducting devices. The dependence of resistance tuning on the pre-annealing heating time, annealing temperature, bias voltage, oxidation exposure, junction linewidth, and aspect ratio is thoroughly characterized. Our results will contribute a predictive framework for the precise resistance control of micrometer-scale JJs, thereby guiding the deterministic fabrication of high-performance superconducting quantum hardware.
Recent advances in the alternating-bias-assisted annealing (ABAA) technique have successfully mitigated intrinsic Josephson-junction (JJ) fabrication variations. This new technique enables precision qubit frequency tuning alongside simplicity. However, it is critical to enhance tuning throughput and yield while investigating the factors that drive targeting performance as the technology scales. Here, we characterize ABAA tuning performance within a 150-mm wafer process flow and extend this technique to simultaneous, multi-channel tuning, demonstrating that a wafer-scale JJ resistance tuning precision of σ=0.50±0.05%σ=0.50\pm0.05\%σ=0.50±0.05% alongside a component-level yield of ≥98.8%\ge 98.8\%≥98.8% can be achieved. Furthermore, we demonstrate a strong correlation between yield, tuning speed, and junction breakdown voltage, establishing the latter as a vital process control parameter for meeting production goals. Finally, we demonstrate a successful implementation of ABAA tuning on a quad-module quantum processor (Rigetti Cepheus-1-36Q), where we achieve an empirical frequency targeting precision of σ∼30 MHzσ\sim 30\text{ MHz}σ∼30 MHz in both qubit and qubit-qubit detuning frequencies, contributing to high median two-qubit gate fidelities. These results confirm the efficacy and scalability of ABAA for high-precision Hamiltonian targeting, a critical enabler for modular superconducting quantum processor technology.
Superconducting quantum processors are one of the leading platforms for realizing scalable fault-tolerant quantum computation (FTQC). The recent demonstration of post-fabrication tuning of Josephson junctions using alternating-bias assisted annealing (ABAA) technique and a reduction in junction loss after ABAA illuminates a promising path towards precision tuning of qubit frequency while maintaining high coherence. Here, we demonstrate precision tuning of the maximum∣0⟩→∣1⟩\vert 0\rangle\rightarrow\vert 1\rangle∣0⟩→∣1⟩transition frequency(f01max⁡)(f_{01}^{\max})(f01max​)of tunable transmon qubits by performing ABAA at room temperature using commercially available test equipment. We characterize the impact of junction relaxation and aging on resistance spread after tuning, and demonstrate a frequency equivalent tuning precision of 7.7 MHz (0.17%) based on targeted resistance tuning on hundreds of qubits, with a resistance tuning range up to 18.5%. Cryogenic measurements on tuned and untuned qubits show evidence of improved coherence after ABAA with no significant impact on tunability. Despite a small global offset, we show an empiricalf01max⁡f_{01}^{\max}f01max​tuning precision of 18.4 MHz by tuning a set of multi-qubit processors targeting their designed Hamiltonians. We experimentally characterize high-fidelity parametric resonance iSWAP gates on two ABAA-tuned 9-qubit processors with fidelity as high as 99.51±0.20%\pm 0.20{\%}±0.20%. On the best-performing device, we measured across the device a median fidelity of 99.22% and an average fidelity of 99.13$\pm$0.12%. Yield modeling analysis predicts high detuning-edge-yield using ABAA beyond the 1000-qubit scale. These results demonstrate the cutting-edge capability of frequency targeting using ABAA and open up a new avenue to systematically improving Hamiltonian targeting and optimization for scaling high-performance superconducting quantum processors.
Superconducting qubits (SQ) are favorable technology for quantum computing due to their macroscopic nature, coherence times, and gate speeds [1]. Materials synthesis and processing methods for SQs are common to fabrication in the semiconductor industry, promising easy scalability. Josephson junctions (JJ) are critical components of SQs and consist of a thin dielectric layered between two superconducting electrodes [2]. The prototypical JJ is an Al/AlOx/Al sandwich structure, as aluminum forms a thin, self-limiting oxide [2, 3]. Amorphous alumina (a-AlOx) has also seen widespread adoption as a dielectric in semiconducting devices due to favorable properties such as high breakdown fields and low leakage currents [4]. Aluminum oxidation follows Cabrera-Mott (CM) mechanisms, where adatom-induced fields drive Al-ion diffusion towards the surface [3]. Pappas et al. introduced alternating bias assisted annealing (ABAA), an electrical processing technique to tune JJ resistance [5]. ABAA applies alternating voltage pulses, below the JJ breakdown field but above the CM field, hypothesized to facilitate ionic diffusion and anneal the oxide. Via scanning transmission electron microscopy (STEM), they demonstrated that ABAA induces a measurable change on the Al electron energy loss near-edge structure (EELS-ELNES), suggestive of potential changes in bonding and homogenization of the oxide [5]. Junction resistance with ABAA can be tuned to a narrow distribution, improving device performance [6]. Iaia et al. studied the influence of ABAA in thicker a-AlOx layers in superconducting resonators designed to study two level system defects (TLS) in the amorphous dielectric [7]. They note pronounced impact of ABAA applied and measured at mK temperatures (cryogenic alternating bias stimulation, CABS) on TLS behavior, which are reversible when the device is annealed to 10 K. In this work, we investigate the influence of ABAA on a-AlOx film structure using 4D STEM fluctuation electron microscopy (FEM). Synthesis and processing of the device is described in Iaia et al. [7]. Briefly, a ∼50 nm thick a-AlOx layer was synthesized via thermal atomic layer deposition (ALD), which differs from conventional a-AlOx growth in JJs. ABAA processing was applied with ±100 MV/m fields at 353 K over 30 hours. STEM sample thickness was controlled between 0.4 – 0.7 λEMFPAlOx⁠. 4D STEM experiments were performed at 300 kV on the Lawrence Berkeley National Laboratory TEAM I, collected with a Dectris Arina detector, with a 1.2 mrad and 2 pA probe to minimize beam damage [8]. Thickness was calculated for each real space position based on the transmitted intensity of the diffraction zero-beam using a vacuum dataset for reference. The variance was normalized for thickness at each pixel and averaged across each row of diffraction patterns. Several datasets were collected, aligned, normalized, and averaged to improve statistics. Variance profiles are compared as a function of depth to understand a-AlOx medium range order across the device thickness. Figure 1 shows FEM analysis of a resonator. Fluctuation electron microscopy (FEM) variance was calculated using the Vr method for each pixel [9]. Variance is a metric which tracks how speckle intensity as a function of k fluctuates across a dataset [10]. Speckles originate from individual ordered atomic clusters in the amorphous material aligned on Bragg conditions [10]. A low variance is suggestive of a lower speckle-contrast amorphous halo with little fluctuation across the dataset, or a more uniform and amorphous structure. In contrast, a higher variance suggests stronger speckle contrast intensity fluctuations, with sources arising from both discrete speckles and changes across the dataset, or a more heterogeneous and ordered amorphous material. Figure 1 compares FEM normalized variance profiles between the as-made (AM) and ABAA devices, and Figure 2 isolates the peak variance values at ∼3 and ∼7 nm-1 as a function of distance from the TiN electrode. In the AM device, a pronounced decrease in the variance is observed near the TiN interface, suggesting a substantial reduction in amorphous structural order. This variance reduction extends several nm into the film. We speculate this may be attributable to TiN interfacial effects during the initial stages of the ALD growth. Datasets collected with different cross-sections, probe currents, shorter dwell times, and different scan geometries all show comparable TiN interfacial features, so we believe this effect is not attributable to electron or ion beam damage [8]. The ABAA-treated device shows only a modest variance reduction near the TiN interface. This suggests that ABAA increases the a-AlOx ordering near the interface. While the a-AlOx structure as a function of depth is more homogeneous after ABAA, the a-AlOx structure near the TiN interface can be thought of as more heterogeneous, peppered with well-ordered atomic clusters. We interpret this change as ABAA-induced ionic diffusion allowing the oxide to find more stable configurations [4,5]. ABAA thus offers a straightforward means to modify both the structure and properties of ALD AlOx layers inside devices [11]. Overview of spatially-resolved FEM measurements. A 4D STEM dataset is depicted by a virtual brightfield (vBF) image (top left). Each diffraction pattern’s variance is calculated, normalized based on the pixel thickness, and averaged across each row. Variances are compared as a function of depth in the AlOx layer. A representative diffraction pattern is shown (top right), with rings corresponding to maxima in the variance. Spatially resolved, normalized variance plots are shown for the as-made (bottom left) and ABAA (bottom right) devices with colors corresponding to locations depicted by the vBF colorbar. FEM comparisons between AM and ABAA devices. The AM device shows reduced variance near the TiN interface, mostly mitigated via ABAA processing.
Abstract We demonstrate a transformational technique for controllably tuning the electrical properties of individual aluminum-oxide tunnel junctions. Using conventional test equipment to apply an alternating bias to a heated tunnel barrier, giant increases in the room temperature resistance, greater than 70%, can be achieved. The rate of resistance change is shown to be strongly temperature- dependent, and is weakly dependent on junction size in the sub-micron regime. In order to measure their tunneling properties at mK temperatures, we characterized transmon qubit junctions treated with this alternating-bias assisted annealing (ABAA) technique. The measured frequencies follow the Ambegaokar-Baratoff relation between the shifted resistance and critical current. Further, these studies show a reduction of junction-contributed loss on the order of ≈ 0.3 × 10−6, and indicate that there is a reduction in resonant-and off-resonant-two level system defects when compared to untreated samples. Imaging with high-resolution TEM shows that the barrier is still predominantly amorphous with a more uniform distribution of aluminum coordination across the barrier relative to untreated junctions. This new approach is expected to be widely applicable to a broad range of devices that rely on amorphous aluminum oxide, and is likely applicable to many other metal- insulator-metal devices.
Variability in Josephson junction area and resistance remains a central challenge in scaling fixed-frequency superconducting qubit architectures, where resistance fluctuations translate into qubit-frequency dispersion and potential frequency collisions. Here, we present a fabrication strategy that combines large-area process control on 200 mm wafers with chip-level electrical fine-tuning to improve junction-resistance repeatability. Within a central 80 × 80 mm 2 field on 200 mm wafers, the Manhattan-style aluminum junction process yielded relative standard deviations of 5.1–5.2% in junction area (RSD A ) and 5.8–7.2% in room-temperature resistance (RSD R ). Alternating-bias assisted annealing (ABAA) further reduced chip-level RSD R to 1.3% in a chip with all 20 junctions tuned and to 1.7% for 16 tuned junctions in a cryogenically characterized 20-qubit chip. In a cross-chip comparison, the coherence distributions of the ABAA-treated chip and the untreated reference chip overlapped. These results show that large-area feed-forward correction and post-fabrication tuning can improve junction-parameter repeatability in fixed-frequency superconducting circuits.
Josephson junctions (JJs) are critical components in superconducting quantum circuits, where their electrical properties directly determine qubit transition frequencies. While advances in fabrication have enabled precise control over junction area and oxide thickness, the influence of junction geometry beyond area has remained largely unexplored. Here, we report clear and reproducible evidence that the normal-state resistance (Rn) of JJs depends strongly on geometric parameters, demonstrating that (Rn) exhibits a systematic and reproducible dependence on junction geometry beyond simple area scaling. To account for this behavior, we introduce an edge-resistance model that incorporates perimeter-related contributions to (Rn). Our findings highlight the crucial role of geometric design in JJ electrical characteristics and provide a practical framework for improving frequency precision and uniformity in large-scale superconducting quantum processors.