Quasiparticle Poisoning in Quantum Devices

• Quasiparticle poisoning is a phenomenon where nonequilibrium quasiparticles disrupt the charge parity and quantum states in superconducting and topological circuits.
• It arises from diverse mechanisms such as phonon bursts, photon absorption, particle impacts, and vortex-mediated effects, each with distinct temporal and spatial signatures.
• Mitigation strategies including phonon downconversion, gap engineering, and dynamic QP extraction are essential for enhancing device performance and quantum error correction.

Quasiparticle poisoning (QP poisoning) is a universal decoherence channel in superconducting and topological nanoelectronic systems, arising when nonequilibrium fermionic excitations (quasiparticles) change the parity or local occupation of key circuit elements, destroy quantum coherence, and limit device performance. This phenomenon is driven by multiple microscopic mechanisms—including pair-breaking phonon bursts, radiation absorption, and charge injection—and the relevant timescales, spatial spread, and mitigation strategies are highly system- and material-dependent. Precise experimental protocols and theoretical models have quantified QP poisoning in applications ranging from qubit circuits and calorimeters to Majorana platforms. The following review synthesizes the physical principles, dominant mechanisms, kinetic models, numerical metrics, and mitigation strategies of QP poisoning, directly referencing measurements and theory from primary literature.

1. Physical Origin and Mechanisms of Quasiparticle Poisoning

QP poisoning is initiated by the appearance of nonequilibrium Bogoliubov quasiparticles which tunnel across Josephson junctions, transition into Majorana modes, or populate subgap or Andreev bound states, thereby altering the charge parity or quantum state of the system. In Al-based superconducting circuits, only a single quasiparticle tunneling or diffusing into a sensitive region can open a relaxation or dephasing channel. The observed origin of excess QPs is system-specific:

• Phonon bursts from stress relaxation: Following cooldown, differential thermal contraction between a substrate (e.g., Si) and its adhesive or mounting structure stores elastic stress. Creep or microfracture of the glue–crystal interface releases this energy as athermal phonon bursts (10–1000 eV) (Anthony-Petersen et al., 2022). These ballistically propagate in the crystal and break Cooper pairs in adjacent superconducting films.
• High-energy photon absorption: In modern transmons, millimeter-wave photons (energies $h\nu \geq 2\Delta$) break Cooper pairs when resonantly absorbed at antenna modes in the device, dramatically exceeding equilibrium QP densities (Liu et al., 2022).
• Particle-initiated phonons: Impacts by cosmic rays or $\gamma$-rays in the substrate generate high-energy charge and phonon cascades, yielding correlated, chip-wide QP bursts via pair-breaking phonons (Larson et al., 10 Mar 2025, Yelton et al., 23 Feb 2024).
• SFQ and digital circuit operation: Operation of SFQ (single-flux quantum) controllers on quantum–classical hybrid chips leads to local QP production at the SFQ site, with subsequent phonon-mediated propagation to the qubits (Liu et al., 2023).
• Vortex-mediated multiplication: In the presence of trapped vortices, nonequilibrium QPs can multiply via enhanced QP–QP interactions and impact ionization in vortex cores, causing substantial increases in QP density on sub-100 ps timescales (Park et al., 5 Nov 2025).
• Direct electronic tunneling or thermally-activated transitions: In Majorana nanowires and low-disorder Josephson junctions, QP poisoning can arise from above-gap or subgap-level tunneling, governed by the microstructure and disorder of the proximitized material (Karzig et al., 2020).

2. Quantitative Models of QP Burst Rate and Evolution

The time-evolution of QP poisoning from phononic, radiative, or tunneling origins is typically modeled with rate equations, incorporating system-specific sources, propagation dynamics, and loss terms.

• Stress relaxation model: The rate of microfracture-driven phonon bursts is empirically found to decay as

$R(t) = R_0 \exp(-t/\tau) + R_\mathrm{bg}$

where $R_0$ is the initial post-cooldown rate, $\tau \approx 6$–$10~\text{days}$, and $R_\mathrm{bg}$ is the long-time background (e.g., cosmic muons) (Anthony-Petersen et al., 2022).

• QP–dynamics kinetic equation: The evolution of the reduced QP density $x_\mathrm{qp}(t) = n_\mathrm{qp}(t)/n_\mathrm{cp}$ follows

$\dot{x}_\mathrm{qp}(t) = -r x^2 - s x + G(t)$

where: - $r \sim (20~\text{ns})^{-1}$ is the pair recombination rate (Al), - $s$ is the single-particle trapping rate (e.g., due to vortices or normal-metal traps), - $G(t)$ is the generation term, with contributions from sparse phonon bursts, radiation events, etc.

• Pair-breaking phonon transport: For substrate-mediated QP poisoning (qubit arrays or SFQ–qubit hybrids), phonon transport is treated with anisotropic wave equations and Monte Carlo simulations, tracking absorption probabilities, downconversion at normal-metal or engineered traps, and recovery timescales on the order of $O(50~\mu\text{s})$ (Yelton et al., 23 Feb 2024, Larson et al., 10 Mar 2025, Patel et al., 2016).
• Majorana parity dynamics: In topological systems, stochastic parity-flip (poisoning) rates $\Gamma_\mathrm{QP}$ are introduced as explicit terms in master equations, determining the timescale of decoherence and visible features in transport and noise (Karzig et al., 2020, Colbert et al., 2013, Svetogorov et al., 2021, Boström et al., 9 Sep 2024).

3. Experimental Quantification: Protocols and Performance Metrics

Experimental approaches leverage charge-sensitive qubit devices, resonator quality factor, or transport signatures to quantify QP poisoning rates and spatial/temporal footprints.

Representative protocols and extracted metrics:

Platform	Measured	Observed Range	Timescale
Charge-sensitive transmon arrays (Larson et al., 10 Mar 2025, Yelton et al., 23 Feb 2024)	Parity flip rate ($\Gamma_p$), offset charge jumps	$\Gamma_p \sim 10^{-3}$–$0.1~\text{s}^{-1}$ (background to active $\gamma$)	$100~\mu$s event recovery, $\tau_\mathrm{parity}>10^3$ s with mitigation
TES calorimeter (Anthony-Petersen et al., 2022)	Phonon burst rate ($R$) in energy bins	$R_0 \sim 0.1~\text{Hz}$ (high stress), $<10^{-3}$ Hz (low stress)	Decay constant $\tau \approx 6$–$10~\text{days}$
Microwave resonator (Patel et al., 2016)	QP-induced loss ($1/Q_{\mathrm{qp}}$), QP density	$x_\mathrm{qp} \sim 10^{-5}$–$3 \times 10^{-4}$ (near injector)	Poisoning time $\tau_p \sim 30$–$150~\mu\text{s}$, recovers in $200$–$300~\mu$s
Majorana nanowires (Colbert et al., 2013, Karzig et al., 2020)	Parity lifetime ($\tau_p$), resonance broadening	$\tau_p \sim 0.1~\mu$s–$1$ s depending on architecture	Timescales determined by system disorder, geometry, and QP bath coupling

Device-specific charge-tomography protocols enable real-time identification of QP poisoning coincident with radiation-induced events. In the context of repeated $\gamma$-ray impacts, the observed correlated charge and parity jumps can be spatially mapped, yielding chip-wide poisoning in the absence of phonon-mitigation structures and sub-mm footprints when mitigation is present (Larson et al., 10 Mar 2025).

4. Consequences and Impact on Quantum Hardware

QP poisoning reduces $T_1$ and $T_2$ times in superconducting qubits, both through direct relaxation induced by QP tunneling and by introducing correlated errors in large-scale qubit arrays. In Majorana-based topological qubits, single QP events break parity conservation, causing decoherence and logical errors, and may even induce Kondo physics under certain poisoning regimes (Plugge et al., 2016). For parameters relevant to Al-based transmons, observed QP densities far exceed equilibrium predictions, and poisoning is known to cause both continuous decoherence (limiting gate and memory operation) and rare catastrophic events (error bursts after radiation impacts) (Liu et al., 2022, Yelton et al., 23 Feb 2024).

Correlated poisoning is a fundamental barrier to scalable quantum error correction. Monte Carlo modeling and experiments show that, in the absence of mitigation, a single particle or photon impact can simultaneously poison the majority of a chip, raising the two-qubit error rate above practical error-correction thresholds (Larson et al., 10 Mar 2025, Yelton et al., 23 Feb 2024).

5. Mitigation Strategies and Engineering Approaches

Suppression of QP poisoning involves a cross-disciplinary set of material, device, and architectural optimizations. Solutions are contingent upon the dominant poisoning mechanism:

• Phonon downconversion: Patterned normal-metal (e.g., Cu) islands on the back side of the chip act as phonon absorbers, reducing the effective mean-free-path of pair-breaking phonons and shrinking the correlated error footprint by $10\times$–$100\times$ (Larson et al., 10 Mar 2025, Yelton et al., 23 Feb 2024, Patel et al., 2016).
• Stress and mechanical engineering: Avoiding adhesives and minimizing differential stress at crystal interfaces can reduce phonon burst rates by more than two orders of magnitude, as seen in the comparison between glued and wire-bonded Si crystals (Anthony-Petersen et al., 2022).
• Electronic structure and gap engineering: Modulating the superconducting gap profile (via film thickness or materials choice) to create barriers for low-energy QPs near junctions can suppress QP tunneling and extend parity lifetimes beyond $10^3$ s (Kamenov et al., 2023). In Majorana/SC hybrid structures, gap tuning via electrostatic gates enables active control of QP tunneling rates by more than two orders of magnitude (Nguyen et al., 2022).
• Photon and device shielding: Multilayer, light-tight enclosures and on-chip IR / mm-wave filters suppress excess pair-breaking photons, reducing the steady-state QP background and improving $T_1$ times (Liu et al., 2022).
• Dynamic extraction: S–I–S' tunnel junctions (“QP pumps”) situate a narrow-gap superconductor near a large-gap region to actively extract nonequilibrium QPs under bias, achieving up to an order-of-magnitude reduction in QP density (Marín-Suárez et al., 2020).
• Vortex management: Zero-field-cooling and engineered pinning mitigate vortex trapping, which otherwise catalyzes QP multiplication and accelerates poisoning under nonequilibrium drive (Park et al., 5 Nov 2025).
• Periodic monitoring and error correction: In periodically-driven Majorana nanowires, generation of multiple end-Majorana modes in a single wire enables active syndrome extraction and correction of single QP events with quadratic suppression of logical error rates (Bomantara et al., 2019).

6. Theoretical Limits, Parameter Dependence, and Scaling

Realistic estimates for the residual QP poisoning rate depend critically on device architecture (floating islands vs. extended films), material disorder, QP subgap state density, and environmental shielding:

• Floating mesoscopic Majorana islands ($L \ll L_\gamma$) can exhibit QP parity lifetimes up to $1~\text{day}$ in optimized environments, whereas bulk SCs revert to rapid poisoning ($0.1~\mu$s–$1$ ms) due to continuous QP baths (Karzig et al., 2020).
• For moderately-disordered, floating islands, subgap-state poisoning is exponentially suppressed at low temperature $T \ll \Delta$ and long mean free path $\ell/\xi \gg 1$.
• In Al-transmons, six orders of magnitude suppression in QP tunneling rate is achieved with proper gap-engineering, yielding charge-parity lifetimes $>10^3$ s and single-qubit $T_1$ improvements up to $4\times$ at base temperature (Kamenov et al., 2023).

Mitigation efficacy and QP management must be assessed in the context of target logical error rates. For the surface code, correlated error footprints must be reduced below a per-event probability threshold ($p_{\rm th}\sim0.25$ for $\gamma$ events at $0.04~\text{s}^{-1}$) to enable effective code operation (Larson et al., 10 Mar 2025).

7. Outlook and Design Principles

Practical suppression of QP poisoning is an essential requirement for scalable, fault-tolerant superconducting and topological quantum CPUs. The following design principles summarize best practices emerging from the literature:

• Minimize and decouple differential mechanical stresses at all interfaces to suppress phonon bursts (Anthony-Petersen et al., 2022).
• Engineer structured phonon sinks and optimize the phonon mean-free-path to confine QP bursts and reduce spatially correlated error events (Yelton et al., 23 Feb 2024, Larson et al., 10 Mar 2025).
• Employ gap engineering and on-chip filtering to harden qubits against direct pair-breaking by environmental photons and QPs (Kamenov et al., 2023, Liu et al., 2022).
• Incorporate dynamic and static normal-metal QP traps, judicious vortex pinning, and active QP extraction near sensitive elements (Patel et al., 2016, Park et al., 5 Nov 2025, Marín-Suárez et al., 2020).
• For Majorana-based topological qubits, favor isolated floating-island architectures, low-disorder materials, and build error-correction schemes directly into device design to actively detect and correct poisoning (Karzig et al., 2020, Bomantara et al., 2019).

A confluence of materials engineering, phononic/acoustic design, parity-monitoring electronics, and topological error correction is required to push QP poisoning below fault-tolerant error thresholds across the relevant timescales and spatial scales of next-generation quantum hardware.