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Andrea Giachero

Publications and source records attributed to Andrea Giachero.

At least 19 recordsLinked to original sources

FIREQ: FPGA Instrumentation for Readout and Qubit control

We present FIREQ (FPGA Instrumentation for Readout and Qubit control), an open-source RFSoC-based framework for the control and readout of superconducting qubits. FIREQ combines a modular AXI-compliant firmware architecture with a PYNQ-based software stack designed to support extensible hardware integration, deterministic experiment timing, and low-overhead execution of repeated calibration and characterization workflows. The firmware implements direct RF synthesis and acquisition, trigger-based sequencing, programmable pulse generation, frequency-multiplexed readout, and memory-efficient acquisition and waveform buffering. The software adopts a client-server architecture with streamed data transfer and dependency-aware configuration updates to reduce host-device and reconfiguration overhead during parameter sweeps. On an AMD Zynq UltraScale+ RFSoC ZCU216, FIREQ generates RF pulses up to 9.3 GHz with a pulse-duration resolution of 107 ps and an event-timing resolution of 1.7 ns. FPGA resource utilization is compared with representative open-source RFSoC control frameworks, showing a low BRAM footprint while retaining full-rate I/Q generation and acquisition. The RF output is characterized in terms of phase noise, noise spectral density, and inter-channel timing skew. End-to-end operation is validated on a superconducting qubit through resonator spectroscopy, Rabi, Ramsey, and relaxation measurements, yielding T1 = 6.94 us and T2* = 13.50 us. FIREQ can therefore be used both as a qubit-control platform and as an experimental environment for evaluating alternative control and readout IP architectures.

quant-ph

Operation of Unshielded Kinetic-Inductance Traveling-Wave Parametric Amplifiers in Multi-Tesla Fields

Cryogenic parametric amplifiers are used to amplify radio-frequency signals for a range of applications in basic and applied science. Both Josephson Parametric Amplifiers and Josephson Traveling-Wave Parametric Amplifiers have been used as first-stage amplifiers enabling readout chains operating within a few quanta of the quantum limit. However, these devices are highly sensitive to magnetic fields, having critical current suppressed by the Fraunhofer effect, requiring substantial field-free zones. In a dark matter axion search experiment, axions convert to detectable microwave photons in the presence of a strong magnetic field, necessitating amplifiers that can reliably operate close to these environments. Kinetic-inductance Traveling-Wave Parametric Amplifiers (KTWPAs) may be the ideal candidate for this type of application having high critical magnetic field of the materials used throughout their construction. In this letter we demonstrate that KTWPAs can provide high gain (>20dB) over a multi-GHz bandwidth in spite of from multiple exposures to multi-Tesla fields. Further, we explore operational characteristics of these devices under harsh conditions as a function of overall field strength, device orientation within the field, applied bias current, and pump power & frequency. In so doing, we find KTWPA gain vanishes in devices oriented perpendicularly to a field of 0.02T, but gain values >10dB are achievable in fields over 1T when oriented near~parallel to the device plane, with peak gain achieved with an applied 0.25T to 0.5T field. It is our expectation that KTWPAs will expand the accessibility of quantum-limited RF measurements in the presence of Tesla-scale fields.

hep-ex

Hardware-Aware Fermion-to-Qubit Mappings for Simulating the 2D Hubbard Model on Heavy-Hexagon Quantum Processors

Quantum simulation of strongly correlated fermionic systems is among the most promising near- term applications of quantum computing, but its practical efficiency depends critically on the choice of fermion-to-qubit mapping and on the connectivity of the underlying hardware. In this work we address this problem in the context of the two-dimensional Hubbard model, simulated on IBM superconducting quantum processors with heavy-hexagon connectivity. We numerically benchmark the Jordan-Wigner, Bravyi-Kitaev, and Bonsai transformations, evaluating their Pauli weight and SWAP overhead across seven heavy-hexagon chips of increasing size. We show that, while the Bravyi-Kitaev mapping initially exhibits a lower Pauli weight, this advantage is eliminated once routing costs are taken into account, confirming the Bonsai mapping as the most hardware-efficient baseline transformation for this architecture. We then use the Bonsai mapping to construct the qubit Hamiltonian of the 2D spinful Fermi-Hubbard model, introducing a simulated annealing algorithm that optimizes the assignment of Majorana strings to lattice sites, reducing the cost function by nearly 50% percent. Finally, we simulate on quantum hardware the time evolution of fermionic states up to 6x6 lattices, confirming the viability of the Bonsai encoding for hardware-aware large-scale two-dimensional simulations.

quant-ph

Multi-stage Quantum Amplifier Readout Chain

Multi-stage cryogenic readout chains with a wide bandwidth and added noise within a few quanta of the quantum limit are frequently constructed using traveling-wave parametric amplifiers (TWPAs) as the first stage, and a semiconductor amplifier as the second stage. Unfortunately for highly-scaled superconducting detector arrays, or quantum information systems, and space-based observatories, the power dissipation of the semiconductor amplifier becomes problematic from the perspective of available cryogenic cooling power at \mbox{3~K to 4~K}. Here we demonstrate a readout chain based on a two-stage kinetic inductance TWPA (KTWPA). This quantum-amplifier-based-readout-chain (QARC) provides sufficient gain that a cryogenic semiconductor follow-on amplifier can be eliminated without degradation of the system noise. In this way, the QARC dissipates approximately three orders of magnitude less power than readout chains containing semiconductor amplifiers while adding noise of less than 2~quanta over a 1~GHz bandwidth. In addition, by leveraging the high power handling of kinetic inductance technology, the QARC maintains an input compression point of -93~dBm, which exceeds that of many contemporary Josephson-junction-based parametric amplifiers.

quant-ph

When is randomization advantageous in quantum simulation?

We study the regimes in which Hamiltonian simulation benefits from randomization. We introduce a sparse-QSVT construction based on composite stochastic decompositions, where dominant terms are treated deterministically and smaller contributions are sampled stochastically. Crucially, we analyze how stochastic and approximation errors propagate through block-encoding and QSVT procedures. To benchmark this approach, we construct ensembles of random Hamiltonians with controlled coefficient dispersion, locality, and number of terms, designed to favor randomization, and therefore providing an upper bound on its practical advantage. For Hamiltonians with many terms and highly inhomogeneous coefficient distributions, randomized methods reduce gate counts by up to an order of magnitude. However, this advantage is confined to moderate-precision regimes: as the target error decreases, deterministic methods become more efficient, with a crossover near $\varepsilon \sim 10^{-3}$. Although this regime partially overlaps with quantum chemistry Hamiltonians, realistic systems exhibit additional structure, such as commutation patterns, not captured by our model, which are expected to further favor deterministic approaches.

quant-ph

Doppler-induced tunable and shape-preserving frequency conversion of microwave wave packets

In superconducting electronics, the ability to control the frequency of microwave wave packets is crucial for several applications, such as the operation of superconducting quantum processors and the readout of superconducting sensors. We introduce a new approach to microwave frequency conversion that harnesses a dynamic Doppler effect induced by a propagating front that separates regions of different phase velocities. Employing a high-kinetic-inductance superconducting transmission line in a travelling-wave geometry, we were able to implement frequency shifts of microwave wave packets at 500$\,$MHz and 4$\,$GHz of up to 3.7$\,$% while fully preserving their temporal shape. In contrast to conventional methods based on frequency-mixing, our Doppler-induced frequency-conversion method avoids spurious mixing products, is continuously tunable by a quasi-dc current amplitude, and allows to imprint arbitrary patterns on the instantaneous frequency profile of temporally long wave packets. By engineering transmission lines that allow for larger phase-velocity changes and/or by cascading multiple Doppler-induced frequency conversions, an unlimited amount of frequency shifting is in principle attainable. These features demonstrate the potential of our frequency-conversion technique as a promising tool for advanced control of microwave wave packets for different quantum applications.

quant-ph

Achieving speedup in Dark Matter search experiments with a transmon-based NISQ algorithm

Coherent detection of ultralight bosonic dark matter can be achieved by monitoring slow Rabi oscillations in superconducting qubits. We introduce an ancilla-assisted, gate-based protocol that enhances sensitivity to the hidden photon kinetic mixing parameter $\epsilon$ using a single two-qubit gate, bypassing the need to maintain long-lived multi-qubit entangled states and remaining compatible with the limitations of modern quantum hardware. We characterized the increase in sensitivity accounting for decoherence, thermal occupation, errors in readout and reset, indicating up to a ten-fold reduction in the required integration time to reach the same exclusion limit on $\epsilon$ achievable via Rabi-sampling experiments. Under plausible hardware assumptions and three years of data taking, the projected $95\%$ C.L. exclusion limit on the hidden photon mixing parameter reaches $\epsilon\approx 1\times 10^{-14}$ across $2.5$-$6.0$ GHz ($10$-$25$ \textmu eV).

quant-ph

Impact of embedded $^{163}$Ho on the performance of the transition-edge sensor microcalorimeters of the HOLMES experiment

We present a detailed investigation of the performance of transition-edge sensor (TES) microcalorimeters with $^{163}$Ho atoms embedded by ion implantation, as part of the HOLMES experiment aimed at neutrino mass determination. The inclusion of $^{163}$Ho atoms introduces an excess heat capacity due to a pronounced Schottky anomaly, which can affect the detector's energy resolution, signal height, and response time. We fabricated TES arrays with varying levels of $^{163}$Ho activity and characterized their performance in terms of energy resolution, decay time constants, and heat capacity. The intrinsic energy resolution was found to degrade with increasing $^{163}$Ho activity, consistent with the expected scaling of heat capacity. From the analysis, we determined the specific heat capacity of $^{163}$Ho to be $(2.9 \pm 0.4 \mathrm{(stat)} \pm 0.7 \mathrm{(sys)})$ J/K/mol at $(94 \pm 1)$\,mK, close to the literature values for metallic holmium. No additional long decay time constants correlated with $^{163}$Ho activity were observed, indicating that the excess heat capacity does not introduce weakly coupled thermodynamic systems. These results suggest that our present TES microcalorimeters can tolerate $^{163}$Ho activities up to approximately 5 Bq without significant performance degradation. For higher activities, reducing the TES transition temperature is necessary to maintain energy resolution. These findings provide critical insights for optimizing TES microcalorimeters for future neutrino mass experiments and other applications requiring embedded radioactive sources. The study also highlights the robustness of TES technology in handling implanted radionuclides while maintaining high-resolution performance.

physics.ins-det

Compact Superconducting Kinetic Inductance Traveling Wave Parametric Amplifiers with On-chip rf Components

Quantum computing systems and fundamental physics experiments using superconducting technologies frequently require signal amplification chains operating near the quantum limit of added noise. Both Josephson parametric amplifiers (JPAs) and traveling wave parametric amplifiers (TWPAs) have been used as first-stage amplifiers to enable readout chains operating within a few quanta or less of the quantum limit. These devices are also presently entering the commercial industry. However, nearly all demonstrations and existing products require bulky external microwave components for interconnection and application of requisite biases. These components -- cabling interconnects, bias tees, directional couplers, and diplexers -- increase the overall amplifier footprint, installation complexity, and reduce already limited available cryogenic volumes. Additionally, these components introduce loss and reflections which impact the measurement efficiency and readout system noise performance; thus making it more difficult to operate near the quantum limit. Here we present the design and validation of microfabricated bias tees and directional couplers for operating three-wave mixing kinetic inductance TWPAs (KITs). We report the performance of KITs integrated with the microfabricated rf components. Using these devices we demonstrate reduction in the amplifier installation footprint by a factor of nearly five and elimination of all external, lossy microwave components previously required to operate a KIT. Our device displays a 2.8 GHz 3 dB bandwidth with a median true gain of 17.5 dB and median system noise of 3.4 quanta. These efforts represent the first full integration of all rf components mandatory for TWPA operation on-chip. Our results mark significant progress towards the miniaturization and simplification of parametric amplifier setups and will aid in their more widespread applicability.

quant-ph

Effect of 2$^\text{nd}$ harmonic current--phase relation on a behavior of a Josephson Traveling Wave Parametric Amplifier

We numerically investigate the behavior of a Josephson traveling wave parametric amplifier assuming a current-phase relation with a second--harmonic contribution. We find that varying the weight of harmonic terms in the Josephson current affects the gain profile. The analysis of gain characteristics, phase-space portraits, Poincar\'e sections, and Fourier spectra demonstrates that the nonsinusoidal contribution influences the operating mode and stability of the device. In particular, we identify the optimal weighting of harmonic contributions that maximizes amplification, achieving gains up to $\sim 13\;\text{dB}$ in a device without dispersion engineering.

cond-mat.supr-con

Machine learning-assisted techniques for Compton-background discrimination in Broad Energy Germanium (BEGe) detector

High Purity Germanium (HPGe) detectors are powerful detectors for gamma-ray spectroscopy. The sensitivity to low-intensity gamma-ray peaks is often hindered by the presence of Compton continuum distributions, originated by gamma-rays emitted at higher energies. This study explores novel, pulse shape-based, machine learning-assisted techniques to enhance Compton background discrimination in Broad Energy Germanium (BEGe TM) detectors. We introduce two machine learning models: an autoencoder-MLP (Multilayer Perceptron) and a Gaussian Mixture Model (GMM). These models differentiate single-site events (SSEs) from multi-site events (MSEs) and train on signal waveforms produced in the detector. The GMM method differs from previous machine learning efforts in that it is fully unsupervised, hence not requiring specific data labelling during the training phase. Being both label-free and simulation-agnostic makes the unsupervised approach particularly advantageous for tasks where realistic, high-fidelity labeling is challenging or where biases introduced by simulated data must be avoided. In our analysis, the full-energy Peak-to-Compton ratio of the 137-Cs, a radionuclide contained in a cryoconite sample, exhibits an improvement from 0.238 in the original spectrum to 0.547 after the ACM data filtering and 0.414 after the GMM data filtering, demonstrating the effectiveness of these methods. The results also showcase an enhancement in the signal-to-background ratio across many regions of interest, enabling the detection of lower concentrations of radionuclides.

physics.ins-det

Local fermion-to-qudit mappings: a practical recipe for four-level systems

In this paper, we present a new set of local fermion-to-qudit mappings for simulating fermionic lattice systems. We focus on the use of multi-level qudits, specifically ququarts. Traditional mappings, such as the Jordan-Wigner transformation (JWT), while useful, often result in non-local operators that scale unfavorably with system size. To address these challenges, we introduce mappings that efficiently localize fermionic operators on qudits, reducing the non-locality and operator weights associated with JWT. We propose one mapping for spinless fermions and two mappings for spinful fermions, comparing their performance in terms of qudit-weight, circuit depth, and gate complexity. By leveraging the extended local Hilbert space of qudits, we show that these mappings enable more efficient quantum simulations in terms of two-qudit gates, reducing hardware requirements without increasing computational complexity. We validate our approach by simulating prototypical models such as the spinless t-V model and the Fermi-Hubbard model in two dimensions, using Trotterized time evolution. Our results highlight the potential of qudit-based quantum simulations in achieving scalability and efficiency for fermionic systems on near-term quantum devices.

quant-ph

Enhanced feature encoding and classification on distributed quantum hardware

The steady progress of quantum hardware is motivating the search for novel quantum algorithm optimization strategies for near-term, real-world applications. In this study, we propose a novel feature map optimization strategy for Quantum Support Vector Machines (QSVMs), designed to enhance binary classification while taking into account backend-specific parameters, including qubit connectivity, native gate sets, and circuit depth, which are critical factors in noisy intermediate scale quantum (NISQ) devices. The dataset we utilised belongs to the neutrino physics domain, with applications in the search for neutrinoless double beta decay. A key contribution of this work is the parallelization of the classification task to commercially available superconducting quantum hardware to speed up the genetic search processes. The study was carried out by partitioning each quantum processing unit (QPU) into several sub-units with the same topology to implement individual QSVM instances. We conducted parallelization experiments with three IBM backends with more than 100 qubits, ranking the sub-units based on their susceptibility to noise. Data-driven simulations show how, under certain restrictions, parallelized genetic optimization can occur with the tested devices when retaining the top 20% ranked sub-units in the QPU.

quant-ph

Qibocal: an open-source framework for calibration of self-hosted quantum devices

Calibration of quantum devices is fundamental to successfully deploy quantum algorithms on current available quantum hardware. We present Qibocal, an open-source software library to perform calibration and characterization of superconducting quantum devices within the Qibo framework. Qibocal completes the Qibo middleware framework by providing all necessary tools to easily (re)calibrate self-hosted quantum platforms. After presenting the layout and the features of the library, we give an overview on some of the protocols implemented to perform single and two-qubit gates calibration. Finally, we present applications involving recalibration and monitoring of superconducting platforms.

quant-ph

Driving a Josephson Traveling Wave Parametric Amplifier into chaos: effects of a non-sinusoidal current-phase relation

In this work, we develop a comprehensive numerical analysis of the dynamic response of a Josephson Traveling Wave Parametric Amplifier (JTWPA) by varying the driving parameters, with a focus on the pathways leading to chaotic behavior. By tuning the working conditions, we capture the broad spectrum of dynamical regimes accessible to JTWPAs, delineating the settings under which transition to chaos occurs. Furthermore, we extend our investigation to device formed by junctions characterized by a non--sinusoidal current phase relation (CPR) and exploring the impact of its shape on the amplifier's performance. Through the study of gain characteristics, Poincar\'e sections, and Fourier spectra, we provide an in-depth understanding of how non-linearity and CPR nonsinusoidality influence the JTWPAs' operational effectiveness and stability. This investigation offers insights into optimizing the device designs for enhanced performance and robustness against chaotic disruptions, in order to establish a framework for predicting and controlling JTWPA behavior in practical applications. This effort will pave the way for the development of devices with tailored dynamic responses and for advancements in quantum computing and precision measurement technologies, where stability and high fidelity are of paramount importance.

cond-mat.supr-con

Kinetic inductance current sensor for visible to near-infrared wavelength transition-edge sensor readout

Single-photon detectors based on the superconducting transition-edge sensor are used in a number of visible to near-infrared applications, particularly for photon-number-resolving measurements in quantum information science. To be practical for large-scale spectroscopic imaging or photonic quantum computing applications, the size of visible to near-infrared transition-edge sensor arrays and their associated readouts must be increased from a few pixels to many thousands. In this manuscript, we introduce the kinetic inductance current sensor, a scalable readout technology that exploits the nonlinear kinetic inductance in a superconducting resonator to make sensitive current measurements. Kinetic inductance current sensors can replace superconducting quantum interference devices for many applications because of their ability to measure fast, high slew-rate signals, their compatibility with standard microwave frequency-division multiplexing techniques, and their relatively simple fabrication. Here, we demonstrate the readout of a visible to near-infrared transition-edge sensor using a kinetic inductance current sensor with 3.7 MHz of bandwidth. We measure a readout noise of 1.4 pA/$\sqrt{\text{Hz}}$, considerably below the detector noise at frequencies of interest, and an energy resolution of $(0.137 \pm 0.001)$ eV at 0.8 eV, comparable to resolutions observed with non-multiplexed superconducting quantum interference device readouts.

physics.ins-det

Spectroscopic measurements and models of energy deposition in the substrate of quantum circuits by natural ionizing radiation

Naturally occurring background radiation is a source of correlated decoherence events in superconducting qubits that will challenge error-correction schemes. To characterize the radiation environment in an unshielded laboratory, we performed broadband, spectroscopic measurements of background events in silicon substrates located inside a millikelvin refrigerator, an environment representative of superconducting qubit systems. We measured the background spectra in silicon substrates of two thicknesses, 0.5 mm and 1.5 mm, and obtained the average event rate and the integrated power deposition. In a 25 mm^2 area and the thinner substrate, these values are 0.023 events per second and 4.9 keV/s, counting events that deposit at least 40 keV. We find the background spectrum to be nearly featureless. Its intensity decreases by a factor of 40,000 between 100 keV and 3 MeV for silicon substrates 0.5 mm thick. We find the cryogenic measurements to be in good agreement with predictions based on measurements of the terrestrial gamma-ray flux, published models of cosmic-ray fluxes, a crude model of the cryostat, and radiation-transport simulations. No free parameters are required to predict the background spectra in the silicon substrates. The good agreement between measurements and predictions allow assessment of the relative contributions of terrestrial and cosmic background sources and their dependence on substrate thickness. Our spectroscopic measurements are performed with superconducting microresonators that transduce deposited energy to a readily detectable electrical signal. We find that gamma-ray emissions from radioisotopes are responsible for the majority of events depositing E<1.5 MeV, while nucleons among the cosmic-ray secondary particles cause most events that deposit more energy. These results suggest several paths to reducing the impact of background radiation on quantum circuits.

quant-ph

Assessment of few-hits machine learning classification algorithms for low energy physics in liquid argon detectors

The physics potential of massive liquid argon TPCs in the low-energy regime is still to be fully reaped because few-hits events encode information that can hardly be exploited by conventional classification algorithms. Machine learning (ML) techniques give their best in these types of classification problems. In this paper, we evaluate their performance against conventional (deterministic) algorithms. We demonstrate that both Convolutional Neural Networks (CNN) and Transformer-Encoder methods outperform deterministic algorithms in one of the most challenging classification problems of low-energy physics (single- versus double-beta events). We discuss the advantages and pitfalls of Transformer-Encoder methods versus CNN and employ these methods to optimize the detector parameters, with an emphasis on the DUNE Phase II detectors ("Module of Opportunity").

physics.ins-det