⚛️ quantum physics

Quasiparticle-induced transitions in a fluxonium qubit

By employing controlled on-chip quasiparticle injection and accounting for superconducting gap asymmetry, this study successfully isolates and characterizes quasiparticle-induced transitions in a fluxonium qubit, thereby resolving previous discrepancies in inferred quasiparticle densities between its small junction and junction array.

Original authors: Maksim Litskevich, Kesavan Manivannan, Benjamin Byrd, Pavel D. Kurilovich, Vladislav D. Kurilovich, Gianluigi Catelani, Ivan V. Pechenezhskiy

Published 2026-08-14

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Original authors: Maksim Litskevich, Kesavan Manivannan, Benjamin Byrd, Pavel D. Kurilovich, Vladislav D. Kurilovich, Gianluigi Catelani, Ivan V. Pechenezhskiy

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Quantum Playground and the Invisible Ghosts

Imagine a world where electricity doesn't flow like water in a pipe, but instead behaves like a wave of probability, allowing particles to exist in two places at once. This is the realm of quantum computing, where scientists build tiny machines called "qubits" to solve problems that would take regular computers millions of years. To make these qubits work, researchers freeze them to temperatures colder than deep space and shield them from every bit of noise in the universe. But there's a sneaky troublemaker that keeps popping up: "quasiparticles."

Think of a superconducting wire as a perfectly organized dance floor where electrons pair up and move in perfect unison. These pairs are called Cooper pairs. A quasiparticle is like a dancer who got kicked out of the line, stumbling around alone and breaking the rhythm of the whole floor. When these lone dancers bump into the qubit, they cause it to lose its quantum information, a process called "decoherence." Scientists have spent years trying to figure out exactly how often these glitches happen and where they come from, because if we can't stop them, our quantum computers will never be reliable enough to fix real-world problems.

The Mystery of the Missing Ghosts in the Fluxonium

In this study, a team of researchers from Syracuse University, Harvard, Google, and other institutions decided to investigate these troublemakers inside a specific type of quantum bit called a "fluxonium." You can think of a fluxonium as a very sensitive, heavy-duty swing set. Unlike its cousin, the "transmon" qubit, the fluxonium is built to be very tough against electrical noise, but this toughness comes with a catch: it's so good at ignoring electrical charges that scientists can't easily "see" when a quasiparticle jumps across its junctions. It's like trying to count how many people are sneaking into a concert by listening for the sound of their footsteps, but the concert hall is so soundproof you can't hear a thing.

Usually, when scientists want to know how many quasiparticles are causing trouble, they just wait and see how long the qubit stays excited before it falls back down. But this method is like trying to guess how many people are in a room by watching the door open and close; it's hard to tell if the noise is coming from the people you're looking for or just the wind blowing the door. To solve this, the researchers built a special "quasiparticle injector" right on the same chip as their qubit. Imagine a tiny, controlled sprinkler that shoots a burst of these rogue dancers onto the dance floor on command. By turning this sprinkler on and off, they could create a known amount of chaos and measure exactly how much faster the qubit lost its energy compared to when the sprinkler was off.

What They Found: The Size Matters

The team discovered something surprising about how these quasiparticles behave. For a long time, scientists assumed that the "gap" between energy levels in the superconducting materials was the same everywhere in the circuit, like a perfectly flat floor. They also assumed that the quasiparticles were very cold and had low energy, not having enough energy to do much. However, the researchers found that in their fluxonium, the floor wasn't flat at all. The superconducting material on one side of the junction was slightly different in thickness than the other, creating a "gap asymmetry."

This difference in thickness acted like a bouncer at a club. When the quasiparticles tried to jump across the junction to cause trouble, the bouncer (the gap difference) stopped many of them, especially when the qubit was in a specific state called the "half-integer flux quantum" point. The researchers showed that if you ignore this bouncer, your math predicts that the qubit should be much more sensitive to quasiparticles at that specific point than it actually is. But once they accounted for the bouncer, the math matched the experiment perfectly.

Solving the Discrepancy

This finding helps solve a long-standing mystery. In previous studies, scientists had measured the "upper bounds" (the worst-case estimates) of how many quasiparticles were in the small junction versus the large array of junctions in the circuit. They consistently found that the small junction seemed to have way more troublemakers than the big array—sometimes ten times more. This didn't make sense, because the quasiparticles should be spread out evenly.

The authors suggest that this discrepancy wasn't because the small junction was actually dirtier. Instead, it was because the old math models were missing the "bouncer" effect. The models assumed the gap was the same everywhere, which made the big array look like it was causing a huge amount of trouble (because the math predicted it should be very sensitive). When the researchers added the gap difference to their model, the big array's sensitivity dropped, and the math showed that the quasiparticle density was actually the same in both the small junction and the big array.

The Takeaway

While the team couldn't perfectly measure the "excitation" rate (how often the qubit got kicked up to a higher energy) because the qubit sometimes leaked into hidden, higher energy states that confused their sensors, they were very confident about the "de-excitation" rate (how often it fell down). Their results suggest that the uneven thickness of the superconducting films is a key player in how quasiparticles cause errors. This means that by carefully engineering the thickness of these films, scientists might be able to build better, more stable quantum computers that are naturally protected from these invisible ghosts. The paper doesn't claim to have fixed the problem yet, but it provides a much clearer map of where the trouble is coming from, suggesting that the "bouncer" effect is a crucial piece of the puzzle that everyone had been missing.

Technical Summary: Quasiparticle-Induced Transitions in a Fluxonium Qubit

Problem Statement
Quasiparticles (QPs) represent a significant source of decoherence in superconducting qubits. While mitigation strategies have been developed for transmon qubits, isolating QP effects in fluxonium qubits remains challenging. Unlike transmons, fluxoniums are insensitive to offset charge, which precludes the use of charge-parity detection to identify quasiparticle tunneling events. Furthermore, previous studies attempting to bound QP densities in fluxoniums by measuring energy-relaxation times ( $T_1$ ) have reported a persistent discrepancy: the inferred upper bound for QP density in the small Josephson junction ( $x_{qp}^{small}$ ) is consistently an order of magnitude higher than that in the junction array ( $x_{qp}^{array}$ ).

This discrepancy has been difficult to resolve because standard theoretical models used to extract these bounds rely on two simplifying assumptions: (1) the superconducting (SC) energy gaps in the junction leads are equal ( $\Delta_L = \Delta_H$ ), and (2) the characteristic energy width of the QP distribution ( $\delta E_{qp}$ ) is much smaller than the qubit transition energy ( $\hbar\omega_{01}$ ). The authors posit that these assumptions may be invalid, particularly near the half-integer flux quantum (HFQ) bias point where $\hbar\omega_{01}$ is minimized, potentially leading to incorrect inferences about QP densities.

Methodology
To address these challenges, the authors employed a controlled on-chip quasiparticle injection scheme combined with measurements of quasi-instantaneous qubit transition rates.

Device Architecture: The experiment utilized a fluxonium qubit fabricated on a high-resistivity silicon substrate. The circuit consists of a small Josephson junction shunted by a large inductor (implemented as an array of larger junctions). A dedicated Josephson junction injector was co-fabricated on the same chip.
Injection Mechanism: QPs were generated by applying a voltage bias ( $V_{inj}$ ) to the injector junction above the Cooper-pair breaking threshold ( $2\Delta_{Al}/e$ ). This process generates Cooper-pair-breaking phonons that propagate through the substrate to the qubit, increasing the QP density in both the small junction and the junction array.
Measurement Protocol: Instead of relying on conventional $T_1$ decay measurements, which convolve relaxation dynamics with QP recovery times, the authors measured the excitation ( $\Gamma_\uparrow$ ) and de-excitation ( $\Gamma_\downarrow$ ) rates over short time windows. By preparing the qubit in either the ground ( $|0\rangle$ ) or excited ( $|1\rangle$ ) state and measuring population dynamics with and without injection, they isolated the QP-induced contribution ( $\Delta\Gamma = \Gamma_{inj} - \Gamma_{bg}$ ) by subtracting background rates.
Flux Dependence: Measurements were performed across a range of external magnetic flux biases ( $\Phi_{ext}$ ), specifically targeting the integer flux quantum (IFQ) and HFQ points.

Key Contributions and Results

Isolation of QP-Induced Rates: The study successfully isolated QP-induced transition rates from background losses. The background-subtracted de-excitation rate ( $\Delta\Gamma_\downarrow$ ) exhibited two distinct peaks of comparable magnitude centered at the IFQ and HFQ.
Role of SC Gap Asymmetry: The authors demonstrated that the assumption of equal SC gaps ( $\Delta_L = \Delta_H$ $Δ_{L} = Δ_{H}$ ) is insufficient to explain the data. In their device, the aluminum films forming the junction leads have different thicknesses (40 nm and 80 nm), resulting in a significant gap asymmetry ( $\delta\Delta \approx 1.72$ $δ Δ \approx 1.72$ GHz).
- Theory predicts that if $\Delta_L = \Delta_H$ , the HFQ peak should be significantly larger than the IFQ peak.
- The experimental observation of comparable peak heights is reconciled only by accounting for the finite $\delta\Delta$ . The gap difference suppresses the QP-induced de-excitation rate at the HFQ (where $\hbar\omega_{01}$ is small) due to the condition $\delta E_{qp} \lesssim \delta\Delta - \hbar\omega_{01}$ .
Resolution of Density Discrepancy: By incorporating the measured $\delta\Delta$ $δ Δ$ and an effective QP temperature ( $k_B T_{qp}/h \approx 1.2$ $k_{B} T_{q p} / h \approx 1.2$ GHz) derived from a co-fabricated transmon, the authors fitted the flux dependence of $\Delta\Gamma_\downarrow$ $Δ Γ_{↓}$ using a single parameter: a common QP density ( $x_{qp}$ $x_{q p}$ ) for both the small junction and the array.
- The fit yielded $x_{qp} \approx 3.6 \times 10^{-6}$ , consistent with transmon measurements.
- This result suggests that the previously reported disparity between $x_{qp}^{small}$ and $x_{qp}^{array}$ likely arises from the use of models that neglect $\delta\Delta$ , rather than a genuine physical difference in QP densities between the circuit elements.
Excitation Rate Anomalies: The study observed an apparent inversion where the QP-induced excitation rate exceeded the de-excitation rate near the HFQ. The authors attribute this to leakage into higher qubit states ( $|2\rangle, |3\rangle, \dots$ ) that are misidentified as the $|1\rangle$ state during readout, rather than a violation of detailed balance or a non-equilibrium QP distribution.

Significance
The paper claims that accurately modeling QP-induced energy relaxation in fluxonium qubits requires accounting for the hierarchy of energy scales, specifically the relationship between the qubit transition energy ( $\hbar\omega_{01}$ ), the SC gap asymmetry ( $\delta\Delta$ ), and the QP energy distribution width ( $\delta E_{qp}$ ).

The primary significance lies in resolving the long-standing discrepancy in inferred QP densities. The authors argue that the assumption of equal SC gaps, common in previous analyses, leads to an overestimation of QP density bounds in the small junction relative to the array. By demonstrating that SC gap asymmetry strongly suppresses transitions at the HFQ, the work suggests that "gap engineering" (deliberately designing asymmetric gaps) could be an effective mitigation strategy for QP-induced decoherence in fluxoniums, similar to strategies used in transmons. The study underscores the necessity of moving beyond simplified models to correctly interpret decoherence mechanisms in low-frequency superconducting qubits.