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Fabrizio Berritta

Publications and source records attributed to Fabrizio Berritta.

8 recordsLinked to original sources

Adaptive Spectroscopy of Fast Two-Level-System Dynamics in Superconducting Qubits

Parasitic two-level-system (TLS) defects are a major source of energy relaxation and temporal instability in superconducting quantum processors. Our sub-second adaptive spectroscopy reveals telegraphic switching of TLSs with a characteristic timescale of a few seconds and spectral diffusion with diffusivity $D \approx 0.9~\mathrm{MHz}^2/\mathrm{s}$. These timescales are about $3 \times 10^2$ times faster than what is observed in conventional nonadaptive spectroscopy, which typically requires hours of measurement time. We resolve such fast dynamics on a field-programmable gate array (FPGA)-based controller that enables measurement of frequency- and time-resolved relaxations with sub-second temporal resolution in flux-tunable superconducting qubits. We observe similar defect dynamics across multiple qubits in independently fabricated devices measured in different laboratories. We correlate TLS-induced fluctuations with gate-level errors using randomized benchmarking. Our results reveal a previously inaccessible regime of frequency-resolved TLS dynamics and redefine the timescales relevant to TLS-aware characterization and calibration of superconducting quantum processors.

quant-ph

Operating a bistable qubit

Parasitic two-level-system (TLS) defects limit the stability and performance of solid-state quantum processors. Their interaction with a qubit can cause discrete, stochastic shifts of the qubit frequency, making the qubit bistable. We experimentally demonstrate an adaptive protocol for operating a bistable qubit with high fidelity using a classical controller powered by a field-programmable gate array (FPGA). Our "1-bit feedback" protocol estimates the qubit's bistable frequency from only one single-shot measurement, reaching the information limit set by the qubit's intrinsic entropy. We validate the protocol in a superconducting qubit by suppressing TLS-induced Ramsey beating, and deploy it to stabilize gate fidelities over time with approximately 136 kHz estimation bandwidth and a 77% error reduction. Our approach provides a simple, yet fundamentally efficient strategy for mitigating dephasing errors induced by strongly coupled TLS defects, and may enable the operation of large future qubit arrays suffering from few remaining, discrete instabilities.

quant-ph

Millisecond-Scale Calibration and Benchmarking of Superconducting Qubits

Superconducting qubit parameters drift on sub-second timescales, motivating calibration and benchmarking techniques that can be executed on millisecond timescales. We demonstrate an on-FPGA workflow that co-locates pulse generation, data acquisition, analysis, and feed-forward, eliminating CPU round trips. Within this workflow, we introduce sparse-sampling and on-FPGA inference tools, including computationally efficient methods for estimation of exponential and sine-like response functions, as well as on-FPGA implementations of Nelder-Mead optimization and golden-section search. These methods enable low-latency primitives for readout calibration, spectroscopy, pulse-amplitude calibration, coherence estimation, and benchmarking. We deploy this toolset to estimate $T_1$ in 10 ms, optimize readout parameters in 100 ms, optimize pulse amplitudes in 1 ms, and perform Clifford randomized gate benchmarking in 107 ms on a flux-tunable superconducting transmon qubit. Running a closed-loop on-FPGA recalibration protocol continuously for 6 hours enables more than 74,000 consecutive recalibrations and yields gate errors that consistently retain better performance than the baseline initial calibration. Correlation analysis shows that recalibration suppresses coupling of gate error to control-parameter drift while preserving a coherence-linked performance. Finally, we quantify uncertainty versus time-to-decision under our sparse sampling approaches and identify optimal parameter regimes for efficient estimation of qubit and pulse parameters.

quant-ph

Real-time adaptive tracking of fluctuating relaxation rates in superconducting qubits

The fidelity of operations on a solid-state quantum processor is fundamentally bounded by environmental decoherence. Characterizing environmental fluctuations is challenging because the acquisition time of nonadaptive experimental protocols limits temporal precision and can average out rapid features of the underlying dynamics. Here, we overcome this temporal-resolution limit by two orders of magnitude using a field-programmable gate-array (FPGA) powered classical controller that adaptively and continuously tracks the relaxation-time fluctuations of two fixed-frequency superconducting transmon qubits, which exhibit average relaxation times of approximately 0.17 ms and occasionally exceed 0.5 ms. We report events in which the relaxation time switches by nearly an order of magnitude over timescales of just tens of milliseconds, rather than minutes or hours as previously reported. Our real-time Bayesian estimation protocol estimates relaxation times within a few milliseconds, close to the decoherence timescale itself. Our statistical analysis further suggests that some of these fast fluctuations arise from two-level systems switching at rates up to 10 Hz, four orders of magnitude faster than earlier reports. These results redefine the timescales relevant for calibration in superconducting quantum processing units, establish a reference for rapid relaxation-rate characterization in device screening, and improve our understanding of fast relaxation dynamics.

quant-ph

Efficient Qubit Calibration by Binary-Search Hamiltonian Tracking

We present and experimentally implement a real-time protocol for calibrating the frequency of a resonantly driven qubit, achieving exponential scaling in calibration precision with the number of measurements, up to the limit imposed by decoherence. The real-time processing capabilities of a classical controller dynamically generate adaptive probing sequences for qubit-frequency estimation. Each probing evolution time and drive frequency are calculated to divide the prior probability distribution into two branches, following a locally optimal strategy that mimics a conventional binary search. The scheme does not require repeated measurements at the same setting, as it accounts for state preparation and measurement errors. Its use of a parametrized probability distribution favors numerical accuracy and computational speed. We show the efficacy of the algorithm by stabilizing a flux-tunable transmon qubit, leading to improved coherence and gate fidelity. As benchmarked by gate-set tomography, the field-programmable gate array (FPGA) powered control electronics partially mitigates non-Markovian noise, which is detrimental to quantum error correction. The mitigation is achieved by dynamically updating and feeding forward the qubit frequency. Our protocol highlights the importance of feedback in improving the calibration and stability of qubits subject to drift and can be readily applied to other qubit platforms.

quant-ph

Physics-informed tracking of qubit fluctuations

Environmental fluctuations degrade the performance of solid-state qubits but can in principle be mitigated by real-time Hamiltonian estimation down to time scales set by the estimation efficiency. We implement a physics-informed and an adaptive Bayesian estimation strategy and apply them in real time to a semiconductor spin qubit. The physics-informed strategy propagates a probability distribution inside the quantum controller according to the Fokker-Planck equation, appropriate for describing the effects of nuclear spin diffusion in gallium-arsenide. Evaluating and narrowing the anticipated distribution by a predetermined qubit probe sequence enables improved dynamical tracking of the uncontrolled magnetic field gradient within the singlet-triplet qubit. The adaptive strategy replaces the probe sequence by a small number of qubit probe cycles, with each probe time conditioned on the previous measurement outcomes, thereby further increasing the estimation efficiency. The combined real-time estimation strategy efficiently tracks low-frequency nuclear spin fluctuations in solid-state qubits, and can be applied to other qubit platforms by tailoring the appropriate update equation to capture their distinct noise sources.

cond-mat.mes-hall

Real-time two-axis control of a spin qubit

Optimal control of qubits requires the ability to adapt continuously to their ever-changing environment. We demonstrate a real-time control protocol for a two-electron singlet-triplet qubit with two fluctuating Hamiltonian parameters. Our approach leverages single-shot readout classification and dynamic waveform generation, allowing full Hamiltonian estimation to dynamically stabilize and optimize the qubit performance. Powered by a field-programmable gate array (FPGA), the quantum control electronics estimates the Overhauser field gradient between the two electrons in real time, enabling controlled Overhauser-driven spin rotations and thus bypassing the need for micromagnets or nuclear polarization protocols. It also estimates the exchange interaction between the two electrons and adjusts their detuning, resulting in extended coherence of Hadamard rotations when correcting for fluctuations of both qubit axes. Our study emphasizes the critical role of feedback in enhancing the performance and stability of quantum devices affected by quasistatic noise. Feedback will play an essential role in improving performance in various qubit implementations that go beyond spin qubits, helping realize the full potential of quantum devices for quantum technology applications.

cond-mat.mes-hall

Gate reflectometry in dense quantum dot arrays

Silicon quantum devices are maturing from academic single- and two-qubit devices to industrially-fabricated dense quantum-dot (QD) arrays, increasing operational complexity and the need for better pulsed-gate and readout techniques. We perform gate-voltage pulsing and gate-based reflectometry measurements on a dense 2$\times$2 array of silicon quantum dots fabricated in a 300-mm-wafer foundry. Utilizing the strong capacitive couplings within the array, it is sufficient to monitor only one gate electrode via high-frequency reflectometry to establish single-electron occupation in each of the four dots and to detect single-electron movements with high bandwidth. A global top-gate electrode adjusts the overall tunneling times, while linear combinations of side-gate voltages yield detailed charge stability diagrams. To test for spin physics and Pauli spin blockade at finite magnetic fields, we implement symmetric gate-voltage pulses that directly reveal bidirectional interdot charge relaxation as a function of the detuning between two dots. Charge sensing within the array can be established without the involvement of adjacent electron reservoirs, important for scaling such split-gate devices towards longer 2$\times$N arrays. Our techniques may find use in the scaling of few-dot spin-qubit devices to large-scale quantum processors.

cond-mat.mes-hall