arXiv subjects

Nicola Casali

Publications and source records attributed to Nicola Casali.

8 recordsLinked to original sources

arXiv2026

Quantitative characterization of superconducting qubits as particle detectors

Ionizing radiation is a major source of correlated errors in superconducting quantum processors, yet the mechanisms responsible for the qubit response to particle interactions remain only partially understood. In this work, we operate superconducting qubits as particle detectors while simultaneously monitoring the deposited energy with an independent semiconductor cryogenic sensor. This complementary measurement provides an absolute determination of the particle interaction rate in the chip, enabling the first direct measurement of the detection efficiency of superconducting qubits exposed to environmental radiation. We measure individual qubit detection efficiencies of about 30-40$\%$, increasing to approximately 50$\%$ when combining the response of two qubits. Under the conservative assumption that the efficiency loss is entirely determined by a finite detection threshold, we derive an upper limit on the effective energy threshold of the detector of $70\pm20~\mathrm{(stat)}\pm30~\mathrm{(syst)}~\mathrm{keV}$. Measurements with radioactive sources producing different deposited-energy spectra further show that the detection efficiency decreases for lower-energy interactions. We further investigate the origin of the qubit response by injecting controlled thermal pulses with a resistive heater. Although these pulses deposit energies comparable to those released by particle interactions, they do not reproduce the radiation-induced signatures, demonstrating that the qubit response to radiation cannot be explained by a transient increase in substrate temperature alone. Our results establish an experimental framework for quantitatively connecting particle energy deposition to radiation-induced responses in superconducting quantum circuits.

physics.ins-det↗

arXiv2026

A Cryogenic Muon Tagging System Based on Kinetic Inductance Detectors for Superconducting Quantum Processors

Ionizing radiation has emerged as a potential limiting factor for superconducting quantum processors, inducing quasiparticle bursts and correlated errors that challenge fault-tolerant operation. Atmospheric muons are particularly problematic due to their high energy and penetration power, making passive shielding ineffective. Therefore, monitoring the real-time muon flux is crucial to guide the development of alternative error-correction or mitigation strategies. We present the design, simulation, and first operation of a cryogenic muon-tagging system based on Kinetic Inductance Detectors (KIDs), developed as a stand-alone cryogenic particle-tagging module for superconducting quantum processors. The system consists of two KIDs arranged in a vertical stack and operated at $\sim$20 mK. Monte Carlo simulations based on Geant4 guided the prototype design and provided reference expectations for muon-tagging efficiency and accidental coincidences due to ambient $γ$-rays. We observed a muon-induced coincidence rate among the top and bottom detectors of (192 $\pm$ 9)$\times10^{-3}$ events/s, in excellent agreement with the Monte Carlo prediction. The prototype achieves a muon-tagging efficiency of about 90% with negligible dead time. These results demonstrate the feasibility of operating a muon-tagging system at millikelvin temperatures and represent a key step toward the integration of cryogenic veto systems with multi-qubit chips to mitigate muon-induced errors.

quant-ph↗

arXiv2025

A Comprehensive Framework for Uncertainty Quantification of Voxel-wise Supervised Models in IVIM MRI

Accurate estimation of intravoxel incoherent motion (IVIM) parameters from diffusion-weighted MRI remains challenging due to the ill-posed nature of the inverse problem and high sensitivity to noise, particularly in the perfusion compartment. In this work, we propose a probabilistic deep learning framework based on Deep Ensembles (DE) of Mixture Density Networks (MDNs), enabling estimation of total predictive uncertainty and decomposition into aleatoric (AU) and epistemic (EU) components. The method was benchmarked against non probabilistic neural networks, a Bayesian fitting approach and a probabilistic network with single Gaussian parametrization. Supervised training was performed on synthetic data, and evaluation was conducted on both simulated and an in vivo dataset. The reliability of the quantified uncertainties was assessed using calibration curves, output distribution sharpness, and the Continuous Ranked Probability Score (CRPS). MDNs produced more calibrated and sharper predictive distributions for the diffusion coefficient D and fraction f parameters, although slight overconfidence was observed in pseudo-diffusion coefficient D*. The Robust Coefficient of Variation (RCV) indicated smoother in vivo estimates for D* with MDNs compared to Gaussian model. Despite the training data covering the expected physiological range, elevated EU in vivo suggests a mismatch with real acquisition conditions, highlighting the importance of incorporating EU, which was allowed by DE. Overall, we present a comprehensive framework for IVIM fitting with uncertainty quantification, which enables the identification and interpretation of unreliable estimates. The proposed approach can also be adopted for fitting other physical models through appropriate architectural and simulation adjustments.

eess.IV↗

arXiv2025

Evaluating radiation impact on transmon qubits in above and underground facilities

Superconducting qubits can be sensitive to abrupt energy deposits caused by cosmic rays and ambient radioactivity. While previous studies have explored correlated effects in time and space due to cosmic ray interactions, we present the first direct comparison of a transmon qubit's performance measured at two distinct sites: the above-ground SQMS facility (Fermilab, US) and the deep-underground Gran Sasso Laboratory (Italy). Despite the stark difference in radiation levels, we observe a similar average qubit relaxation time of approximately 80 microseconds at both locations. To further investigate potential radiation-induced events, we employ a fast decay detection protocol, comparing the relative rates of triggered events between the two environments. Although intrinsic noise remains the dominant source of single errors in superconducting qubits, our analysis revealed a significant excess of radiation-induced events for high-coherence transmon qubits operated above-ground. Finally, using $γ$-ray sources with increasing activity levels, we evaluate the qubit response in a controlled low-background environment.

quant-ph↗

arXiv2022

Operating in a deep underground facility improves the locking of gradiometric fluxonium qubits at the sweet spots

We demonstrate flux-bias locking and operation of a gradiometric fluxonium artificial atom using two symmetric granular aluminum (grAl) loops to implement the superinductor. The gradiometric fluxonium shows two orders of magnitude suppression of sensitivity to homogeneous magnetic fields, which can be an asset for hybrid quantum systems requiring strong magnetic field biasing. By cooling down the device in an external magnetic field while crossing the metal-to-superconductor transition, the gradiometric fluxonium can be locked either at $0$ or $Φ_0/2$ effective flux bias, corresponding to an even or odd number of trapped fluxons, respectively. At mK temperatures, the fluxon parity prepared during initialization survives to magnetic field bias exceeding $100 \,Φ_0$. However, even for states biased in the vicinity of $1 \,Φ_0$, we observe unexpectedly short fluxon lifetimes of a few hours, which cannot be explained by thermal or quantum phase slips. When operating in a deep-underground cryostat of the Gran Sasso laboratory, the fluxon lifetimes increase to days, indicating that ionizing events activate phase slips in the grAl superinductor.

quant-ph↗

arXiv2021

Final results of CALDER: Kinetic inductance light detectors to search for rare events

The next generation of bolometric experiments searching for rave events, in particular for the neutrino-less double beta decay, needs fast, high-sensitivity and easy-to-scale cryogenic light detectors. The CALDER project (2014-2020) developed a new technology for light detection at cryogenic temperature. In this paper we describe the achievements and the final prototype of this project, consisting of a $5\times5$ cm$^2$, 650 $μ$m thick silicon substrate coupled to a single kinetic inductance detector made of a three-layer aluminum-titanium-aluminum. The baseline energy resolution is 34$\pm$1(stat)$\pm$2(syst) eV RMS and the response time is 120 $μ$s. These features, along with the natural multiplexing capability of kinetic inductance detectors, meet the requirements of future large-scale experiments.

physics.ins-det↗

arXiv2020

Reducing the impact of radioactivity on quantum circuits in a deep-underground facility

As quantum coherence times of superconducting circuits have increased from nanoseconds to hundreds of microseconds, they are currently one of the leading platforms for quantum information processing. However, coherence needs to further improve by orders of magnitude to reduce the prohibitive hardware overhead of current error correction schemes. Reaching this goal hinges on reducing the density of broken Cooper pairs, so-called quasiparticles. Here, we show that environmental radioactivity is a significant source of nonequilibrium quasiparticles. Moreover, ionizing radiation introduces time-correlated quasiparticle bursts in resonators on the same chip, further complicating quantum error correction. Operating in a deep-underground lead-shielded cryostat decreases the quasiparticle burst rate by a factor fifty and reduces dissipation up to a factor four, showcasing the importance of radiation abatement in future solid-state quantum hardware.

cond-mat.supr-con↗

arXiv2017

Model for the Cherenkov light emission of TeO$_{2}$ cryogenic calorimeters

The most sensitive process able to probe the Majorana nature of neutrinos and discover Lepton Number Violation is the neutrino-less double beta decay. Thanks to the excellent energy resolution, efficiency and intrinsic radio-purity, cryogenic calorimeters are primed for the search for this process. A novel approach able to improve the sensitivity of the current experiments is the rejection of $α$ interactions, that represents the dominant background source. In TeO$_2$ calorimeters, $α$ particles can be tagged as, in contrast to electrons, they do not emit Cherenkov light. Nevertheless, the very low amount of detected Cherenkov light undermines the complete rejection of $α$ background. In this paper we compare the results obtained in previous measurements of the TeO$_2$ light yield with a detailed Monte Carlo simulation able to reproduce the number of Cherenkov photons produced in $β/γ$ interactions within the calorimeter and their propagation in the experimental set-up. We demonstrate that the light yield detectable from a $5\times5\times5$~cm$^{3}$ TeO$_2$ bolometer can be increased by up to 60% by increasing the surface roughness of the crystal and improving the light detector design. Moreover, we study the possibility to disentangle $α$, $β$ and $γ$ interactions, which represent the ultimate background source. Unfortunately $γ$ rejection is not feasible but $α$ rejection can be achieved exploiting high sensitivity light detectors.

physics.ins-det↗