Superconducting quantum circuits are no longer “only” a platform for quantum computing: they have become an extremely versatile metrological tool for fundamental physics and for ultra-sensitive detection at microwave frequencies. In this research line, I work on quantum sensing architectures based on superconducting qubits and on Josephson-based strategies for single-microwave-photon detection, with a strong emphasis on realistic operation: noise, dark counts, decision rules, and measurable figures of merit.
A unifying idea is simple: in cryogenic microwave experiments the relevant signals can be so weak that they are best described statistically. Whether the output is a qubit state, a switching event in a Josephson element, or a time-tagged detection click, the central question becomes: how do we optimize sensitivity while controlling false positives and maintaining robustness in a noisy environment?
Superconducting qubits can act as exquisitely controllable, tunable quantum systems that translate weak external perturbations into measurable changes—frequency shifts, dephasing patterns, transition rates, or state-population changes. My contribution here focuses on the modeling and design logic of sensing protocols that are compatible with experimental constraints: finite coherence times, non-ideal readout, amplifier noise, and limited control bandwidth.
A practical perspective I often adopt is to treat the full sensing chain as an estimation problem: define the parameter to be inferred (field amplitude, spectral component, modulation signature), identify the optimal control and readout observable, and quantify performance in terms of sensitivity and confidence under realistic noise.
Detecting single microwave photons is challenging because their energy is tiny (orders of magnitude below optical photons). Josephson devices offer a compelling route because they naturally provide threshold-like dynamics: a weak perturbation can trigger a macroscopic, measurable response (e.g., a switch to a voltage state) if the device is biased near a metastable boundary.
My work on photon detection uses Josephson junctions as stochastic threshold detectors. The photon is not treated as a “cartoon particle”, but as an input that modifies the escape dynamics. This leads to a program with clear, quantitative targets:
maximize detection efficiency (true-positive probability),
minimize dark counts (false positives due to thermal activation and noise),
and optimize decision rules using measurable observables such as switching times, lifetime distributions, and voltage-pulse statistics.
A key point—especially for students—is that the device does not merely “click or not click”. The full distribution of switching times and lifetimes contains rich information and can be exploited to improve discrimination between real events and noise.
Across both qubit-based sensing and Josephson detection, I am interested in the bridge between theory and the lab: how a proposal translates into calibration steps, what diagnostics are needed, and which figures of merit truly matter (ROC curves, confidence intervals, stability margins, temperature dependence, bandwidth constraints, and sensitivity scaling).
This is also where my broader expertise in rare events and stochastic dynamics naturally enters: the same tools used to describe thermal escape and non-Gaussian activation can become design tools for better detectors and more reliable sensing protocols.
Modeling at the right level of abstraction
I use models that are detailed enough to capture the relevant physics (metastability, escape dynamics, decoherence channels), but simple enough to be calibrated and compared to standard experimental observables.
Statistical decision theory for detection
I treat detection as a hypothesis-testing problem: define observables (switching time, lifetime, qubit population), derive (or numerically learn) decision rules, and quantify efficiency vs dark-count tradeoffs.
Noise-aware design
Rather than adding noise “at the end”, I incorporate noise sources and fluctuations from the start, because they shape thresholds, tails of distributions, and ultimately the practical feasibility of a device.
Experiment-facing outputs
I aim to deliver quantities that experimentalists can directly measure and optimize: switching histograms, temperature scaling, pump/drive parameter maps, and sensitivity estimates under realistic constraints.
Optimizing single-photon detection via lifetime statistics
Develop and benchmark decision rules that use the full lifetime/switching-time distribution to improve detection at fixed dark-count rates; propose calibration workflows.
Noise-robust sensing protocols with superconducting qubits
Compare sensing strategies (continuous drive, pulsed sequences, adaptive protocols) under realistic decoherence and readout noise, and identify regimes where qubits provide an advantage for fundamental-physics targets.
End-to-end modeling of a cryogenic sensing chain
Combine detector/qubit dynamics with amplifier noise and readout filtering to predict system-level sensitivity and to identify bottlenecks that limit performance.
Detection under structured or non-Gaussian noise
Explore how non-thermal noise backgrounds reshape false-trigger rates and propose discriminating signatures (e.g., tail diagnostics) to separate true events from noise artifacts.
If you are an experimental group, I’m especially happy to collaborate when there is access to real datasets (switching traces, qubit time series, calibration sweeps): even modest amounts of data can strongly constrain models and accelerate design iterations.
C. Guarcello, A. S. Piedjou Komnang, C. Barone, A. Rettaroli, C. Gatti, S. Pagano, G. Filatrella, Josephson-based scheme for the detection of microwave photons, Physical Review Applied 16, 054015 (2021).
A. S. Piedjou Komnang, C. Guarcello, C. Barone, S. Pagano, G. Filatrella, Analysis of Josephson junction lifetimes for the detection of single photons in a thermal noise background, in 2021 IEEE 14th Workshop on Low Temperature Electronics (WOLTE), pp. 1–4 (2021).
A. S. Piedjou Komnang, C. Guarcello, C. Barone, C. Gatti, S. Pagano, V. Pierro, A. Rettaroli, G. Filatrella, Analysis of Josephson junctions switching time distributions for the detection of single microwave photons, Chaos, Solitons & Fractals 142, 110496 (2021).
G. Filatrella, C. Barone, G. Carapella, C. Gatti, V. Granata, C. Guarcello, C. Mauro, A. S. Piedjou Komnang, V. Pierro, A. Rettaroli, S. Pagano, Theoretical and Numerical Estimate of Signal-to-Noise-Ratio in the Analysis of Josephson Junctions Lifetime for Photon Detection, IEEE Transactions on Applied Superconductivity 33(1), 0600105 (2023).
R. Moretti, et al. (including C. Guarcello; Qub-IT Collaboration), Quantum sensing with superconducting qubits for Fundamental Physics, IEEE Transactions on Applied Superconductivity 34(3), 1700705 (2024).
R. Grimaudo, D. Valenti, B. Spagnolo, G. Filatrella, C. Guarcello, Josephson-junction-based axion detection through resonant activation, Physical Review D 105, 033007 (2022).