arXiv subjects

Alessandro Bruno

Publications and source records attributed to Alessandro Bruno.

At least 19 recordsLinked to original sources

arXiv2026

Transparency-engineered SQUID cells for Kerr-free three-wave-mixing Josephson metamaterials

We introduce a transparency-engineered rf-SQUID cell for Kerr-free three-wave-mixing Josephson metamaterials. This design replaces the conventional tunnel-junction element with an effective Josephson element formed by two junctions in series, yielding a non-sinusoidal energy-phase relation that can be used as a tunable nonlinear design resource. We show that the asymmetry between the two series junctions and the applied flux bias provide independent control over the local expansion of the rf-SQUID potential, enabling operating points where the leading quartic Kerr term is suppressed while the cubic nonlinearity remains finite. We derive the corresponding Kerr-free condition, identify the resulting operating ridge in parameter space, and analyze the local stability and passive-matching constraints that bound its physically accessible portion. Our results provide a compact unit-cell design principle for three-wave-mixing Josephson metamaterials and suggest a route toward Kerr-suppressed Josephson traveling-wave parametric amplifiers.

cond-mat.supr-con↗

arXiv2026

Dynamical Reduction of Two Series Josephson Junctions to a Synthetic High-Transparency Josephson Element

Two conventional Josephson junctions connected in series can reproduce, in the static limit in which the currents through the capacitive and resistive channels are negligible, the current-phase relation of a single effective weak link with tunable transparency. Therefore, the two-junction series can be treated as a single synthetic high-transparency element. Here, we investigate to what extent this mapping remains valid under finite-frequency drive and retaining the junctions' resistive and capacitive terms. The full resistively and capacitively shunted junction equations are compared with an effective synthetic element with tunable transparency that retains the synthetic tunable-transparency current-phase relation together with effective capacitive and dissipative terms, thus reducing the two second order degree of freedom system to a single second order degree of freedom. The resulting single-element dynamics is compared with the complete two-junction system under ac excitation. The agreement is quantified through a normalized root-mean-square error between the full and effective voltage waveforms. A broad low-error region is found at low drive frequency, while pronounced deviations emerge as the drive frequency approaches the relevant plasma-frequency scale and at larger drive amplitudes. The results provide a quantitative dynamical criterion for using the reduced single-element description of a synthetic high-transparency Josephson element in superconducting circuits.

cond-mat.supr-con↗

arXiv2026

The Gain-Engineered Transmon

The interaction between a qubit and its environment can be engineered such that one error channel dominates over all others, resulting in noise bias. This property enables error correction codes to focus on the dominant error type, thereby significantly reducing the number of physical systems required for fault-tolerant quantum computation. However, engineering noise bias typically introduces complexity at the physical system level, which decreases its usefulness by limiting scalability. Here, we introduce and experimentally realize a noise-biased qubit in a standard transmon-readout resonator circuit, one of the most common superconducting architectures, by only adding a single microwave tone. We encode the qubit in the transmon $|\mathrm{g}\rangle$- and $|\mathrm{f}\rangle$-states, and engineer a frequency-selective gain channel that counteracts single-photon loss errors between the computational states. We demonstrate an order-of-magnitude enhancement in relaxation time compared to the $|\mathrm{g}\rangle-|\mathrm{e}\rangle$ encoding, conceding only a factor-of-two decrease in the echo-coherence time. Furthermore, we show that this qubit is compatible with fast, high-fidelity operations. Our results open a path towards using this system as a simple building-block for hardware-efficient quantum error detection and correction schemes.

quant-ph↗

arXiv2026

Matched Outcomes, Divergent Gaze: How Foveated MLLMs Search Compared to Humans

Human visual search is serial: the fovea must land on a candidate to confirm it, and those landings form a scanpath. Whether multimodal large language models (MLLMs), given the same foveated input, search as humans do bears on their use as models of human vision and on attention-alignment scores. We compare three general-purpose MLLMs with human eye-movement scanpaths on goal-directed search (COCO-Search18), driving each model fixation by fixation through an identical, human-matched foveated view and assessing it along three axes: the decision of target presence, the efficiency of reaching the target, and the gaze process itself. The axes dissociate. On the decision and on target acquisition the models match or exceed humans, detecting present targets near ceiling and reaching them on the first saccade more often than people do. The gaze process is not human. Under the human-matched condition, all three share one signature: low-entropy, large-amplitude, self-consistent scanpaths that agree with themselves far more closely than two humans agree with each other. That is consistent with a single-pass, non-serial architecture rather than a limit of acuity. Matched retinal input reproduces where humans look but not how the looking unfolds in time, and no degradation regime recovers human-like search at human-like success. The gap sits on a process axis that answer-alignment and saliency metrics do not measure. Because they miss it, such metrics cannot certify human-like vision, and zero-shot models suit outcome and spatial questions but not temporal, process-level ones.

cs.CV↗

arXiv2026

Quantum theory of a three-photon Kerr parametric oscillator

We investigate the quantum properties of a nonlinear Kerr oscillator driven by a three-photon pump. We derive both exact and approximate analytical expressions for the ground state of this interacting model. The exact solution arises at an exact spectral degeneracy, while the approximate solution describes regimes of quasi-degeneracy of the energy spectrum. In both cases, the threefold (quasi)degenerate ground-state manifold consists of quantum superpositions of three macroscopically distinct states. These states differ qualitatively from conventional three-component Schr\"odinger's cat states due to the presence of squeezing with a distinctive parametric dependence. By varying the detuning between the oscillator and the three-photon pump, we show that the squeezing can be enhanced, suppressed, or even reversed, leading to a squeezing-to-anti-squeezing transition. We analyze the generation and stabilization of these superposition states, their robustness against perturbations and analytically quantify the leakage to excited states. Our analysis elucidates how the three-photon Kerr parametric oscillator can be used to encode a Kerr-cat qutrit protected against phase-flip errors.

quant-ph↗

arXiv2026

CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation

Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet CT enhancement is still largely evaluated using image quality metrics with limited perceptual and clinical validity, while existing datasets remain focused on isolated restoration tasks, hindering unified benchmarking across diverse degradation types. We present CT-DegradBench, a dataset and benchmark for CT degradation detection and severity estimation under controlled single- and mixed-artifact settings. CT-DegradBench enables systematic evaluation across multiple degradation families and severity levels within a common experimental framework. We further propose SeSpeCT (Semantic-Spectral CT degradation estimation), a framework that combines semantic priors from medical vision-language models with complementary frequency-domain cues for artifact analysis. SeSpeCT constructs a training-free semantic quality axis in the multimodal embedding space using radiology-informed text prompts, without task-specific fine-tuning, and combines it with spectral features that capture degradation-specific frequency patterns. The resulting representation enables joint prediction of artifact type and severity. Experimental results show that SeSpeCT consistently outperforms the evaluated baselines under both single- and mixed-degradation settings. The framework is available at https://github.com/yousranb/CT-DEGRADBENCH.

cs.CV↗

arXiv2026

What They Saw, Not Just Where They Looked: Semantic Scanpath Similarity via VLMs and NLP metric

Scanpath similarity metrics are central to eye-movement research, yet existing methods predominantly evaluate spatial and temporal alignment while neglecting semantic equivalence between attended image regions. We present a semantic scanpath similarity framework that integrates vision-language models (VLMs) into eye-tracking analysis. Each fixation is encoded under controlled visual context (patch-based and marker-based strategies) and transformed into concise textual descriptions, which are aggregated into scanpath-level representations. Semantic similarity is then computed using embedding-based and lexical NLP metrics and compared against established spatial measures, including MultiMatch and DTW. Experiments on free-viewing eye-tracking data demonstrate that semantic similarity captures partially independent variance from geometric alignment, revealing cases of high content agreement despite spatial divergence. We further analyze the impact of contextual encoding on description fidelity and metric stability. Our findings suggest that multimodal foundation models enable interpretable, content-aware extensions of classical scanpath analysis, providing a complementary dimension for gaze research within the ETRA community.

cs.CV↗

arXiv2026

Connection-angle dependence of proton anisotropy in ground-level enhancement events

Ground Level Enhancements (GLEs) probe the earliest, highest-energy solar energetic particles and thus provide a unique window onto particle release and transport from the low corona to 1 AU. We present a uniform, event-resolved analysis of the early anisotropy for ten well-observed GLEs, combining consistently reconstructed neutron-monitor pitch-angle distributions (PADs) with Parker-spiral footpoint mapping. We find a clear, monotonic decline of initial anisotropy with increasing magnetic connection angle: well-connected events exhibit strong, persistent forward-directed beams, while poorly connected events show systematically weaker and more rapidly decaying anisotropies. This relationship holds across a wide range of flare classes and CME speeds, demonstrating that magnetic connectivity and interplanetary transport, rather than eruption magnitude, dominate the directional properties of the earliest relativistic arrivals at Earth. A principal component analysis was applied to time-resolved spectral and angular parameters to separate source-driven changes from transport effects. By explicitly identifying and removing secondary sunward (back-scattered) components-attributable to scattering and reflection from solar-wind structures and transient interplanetary features-from the PAD fits, we isolate the intrinsic relaxation of the primary forward beam and show that apparent departures from simple exponential decay are frequently attributable to reflected or delayed populations rather than prolonged source injection. The empirical anisotropy--connection-angle relation reported here provides an event-resolved, quantitative benchmark that constrains focused-transport and shock-acceleration models and offers immediate operational value: rapid footpoint estimates can meaningfully limit expected initial beaming and directional radiation risk.

astro-ph.SR↗

arXiv2026

SPGen: Stochastic scanpath generation for paintings using unsupervised domain adaptation

Understanding human visual attention is key to preserving cultural heritage We introduce SPGen a novel deep learning model to predict scanpaths the sequence of eye movementswhen viewers observe paintings. Our architecture uses a Fully Convolutional Neural Network FCNN with differentiable fixation selection and learnable Gaussian priors to simulate natural viewing biases To address the domain gap between photographs and artworks we employ unsupervised domain adaptation via a gradient reversal layer allowing the model to transfer knowledge from natural scenes to paintings Furthermore a random noise sampler models the inherent stochasticity of eyetracking data. Extensive testing shows SPGen outperforms existing methods offering a powerful tool to analyze gaze behavior and advance the preservation and appreciation of artistic treasures.

cs.CV↗

arXiv2026

Effects of the May 2024 Solar Storm on the Earth's Radiation Belts Observed by CALET on the International Space Station

In May 2024, extraordinary solar activity triggered a powerful solar storm, impacting Earth and producing the extreme geomagnetic storm of May 10-11, the most intense since 2003. This had significant effects on the magnetosphere, leading to the creation of a new long-lasting component of relativistic electrons and to flux changes in the South-Atlantic Anomaly. Here we present radiation-belt observations made by the Calorimetric Electron Telescope (CALET) on the International Space Station. Specifically, we took advantage of the count rates from three layers of the CALET charge detector and imaging calorimeter. We show that the new electron storage ring extended to energies in the multi-MeV range and down to L=2.2, well below the nominal slot-region barrier of L=2.8, and persisted for several months, depending on energy. The evolution of the new radiation-belt configuration over time was characterized by estimating the decay rates as a function of energy and L.

physics.space-ph↗

arXiv2025

Enhancing Kerr-Cat Qubit Coherence with Controlled Dissipation

Quantum computing crucially relies on maintaining quantum coherence for the duration of a calculation. Bosonic quantum error correction protects this coherence by encoding qubits into superpositions of noise-resilient oscillator states. In the case of the Kerr-cat qubit (KCQ), these states derive their stability from being the quasi-degenerate ground states of an engineered Hamiltonian in a driven nonlinear oscillator. KCQs are experimentally compatible with on-chip architectures and high-fidelity operations, making them promising candidates for a scalable bosonic quantum processor. However, their bit-flip time must increase further to fully leverage these advantages. Here, we present direct evidence that the bit-flip time in a KCQ is limited by leakage out of the qubit manifold and experimentally mitigate this process. We coherently control the leakage population and measure it to be > 9%, twelve times higher than in the undriven system. We then cool this population back into the KCQ manifold with engineered dissipation, identify conditions under which this suppresses bit-flips, and demonstrate increased bit-flip times up to 3.6 milliseconds. By employing both Hamiltonian confinement and engineered dissipation, our experiment combines two paradigms for Schr\"odinger-cat qubit stabilization. Our results elucidate the interplay between these stabilization processes and indicate a path towards fully realizing the potential of these qubits for quantum error correction.

quant-ph↗

arXiv2025

The 2024 July 16 Solar Event: A Challenge To The Coronal Mass Ejection Origin Of Long-Duration Gamma-Ray Flares

We present a multi-spacecraft analysis of the 2024 July 16 Long-Duration Gamma-Ray Flare (LDGRF) detected by the Large Area Telescope on the Fermi satellite. The measured >100 MeV $\gamma$-ray emission persisted for over seven hours after the flare impulsive phase, and was characterized by photon energies exceeding 1 GeV and a remarkably-hard parent-proton spectrum. In contrast, the phenomena related to the coronal mass ejection (CME)-driven shock linked to this eruption were modest, suggesting an inefficient proton acceleration unlikely to achieve the energies well-above the 300 MeV pion-production threshold to account for the observed $\gamma$-ray emission. Specifically, the CME was relatively slow (~600 km/s) and the accompanying interplanetary type-II/III radio bursts were faint and short-duration, unlike those typically detected during large events. In particular, the type-II emission did not extend to kHz frequencies and disappeared ~5.5 hours prior to the LDGRF end time. Furthermore, the associated solar energetic particle (SEP) event was very weak, short-duration, and limited to a few tens of MeV, even at magnetically well-connected spacecraft. These findings demonstrate that a very-fast CME resulting in a high-energy SEP event is not a necessary condition for the occurrence of LDGRFs, challenging the idea that the high-energy $\gamma$-ray emission is produced by the back-precipitation of shock-accelerated ions into the solar surface. The alternative origin scenario based on local particle trapping and acceleration in large-scale coronal loops is instead favored by the observation of giant arch-like structures of hot plasma over the source region persisting for the entire duration of this LDGRF.

astro-ph.HE↗

arXiv2025

Modeling Beyond MOS: Quality Assessment Models Must Integrate Context, Reasoning, and Multimodality

This position paper argues that Mean Opinion Score (MOS), while historically foundational, is no longer sufficient as the sole supervisory signal for multimedia quality assessment models. MOS reduces rich, context-sensitive human judgments to a single scalar, obscuring semantic failures, user intent, and the rationale behind quality decisions. We contend that modern quality assessment models must integrate three interdependent capabilities: (1) context-awareness, to adapt evaluations to task-specific goals and viewing conditions; (2) reasoning, to produce interpretable, evidence-grounded justifications for quality judgments; and (3) multimodality, to align perceptual and semantic cues using vision-language models. We critique the limitations of current MOS-centric benchmarks and propose a roadmap for reform: richer datasets with contextual metadata and expert rationales, and new evaluation metrics that assess semantic alignment, reasoning fidelity, and contextual sensitivity. By reframing quality assessment as a contextual, explainable, and multimodal modeling task, we aim to catalyze a shift toward more robust, human-aligned, and trustworthy evaluation systems.

cs.CV↗

arXiv2025

Implementation and readout of maximally entangled two-qubit gates quantum circuits in a superconducting quantum processor

Besides noticeable challenges in implementing low-error single- and two-qubit quantum gates in superconducting quantum processors, the readout technique and analysis are a key factor in determining the efficiency and performance of quantum processors. Being able to efficiently implement quantum algorithms involving entangling gates and asses their output is mandatory for quantum utility. In a transmon-based 5-qubit superconducting quantum processor, we compared the performance of quantum circuits involving an increasing level of complexity, from single-qubit circuits to maximally entangled Bell circuits. This comparison highlighted the importance of the readout analysis and helped us optimize the protocol for more advanced quantum algorithms. Here we report the results obtained from the analysis of the outputs of quantum circuits using two readout paradigms, referred to as "multiplied readout probabilities" and "conditional readout probabilities". The first method is suitable for single-qubit circuits, while the second is essential for accurately interpreting the outputs of circuits involving two-qubit gates.

quant-ph↗

arXiv2025

Memory-Efficient 3D High-Resolution Medical Image Synthesis Using CRF-Guided GANs

Generative Adversarial Networks (GANs) have many potential medical imaging applications. Due to the limited memory of Graphical Processing Units (GPUs), most current 3D GAN models are trained on low-resolution medical images, these models cannot scale to high-resolution or are susceptible to patchy artifacts. In this work, we propose an end-to-end novel GAN architecture that uses Conditional Random field (CRF) to model dependencies so that it can generate consistent 3D medical Images without exploiting memory. To achieve this purpose, the generator is divided into two parts during training, the first part produces an intermediate representation and CRF is applied to this intermediate representation to capture correlations. The second part of the generator produces a random sub-volume of image using a subset of the intermediate representation. This structure has two advantages: first, the correlations are modeled by using the features that the generator is trying to optimize. Second, the generator can generate full high-resolution images during inference. Experiments on Lung CTs and Brain MRIs show that our architecture outperforms state-of-the-art while it has lower memory usage and less complexity.

cs.CV↗

arXiv2025

Comparative clinical evaluation of "memory-efficient" synthetic 3d generative adversarial networks (gan) head-to-head to state of art: results on computed tomography of the chest

Generative Adversarial Networks (GANs) are increasingly used to generate synthetic medical images, addressing the critical shortage of annotated data for training Artificial Intelligence systems. This study introduces CRF-GAN, a novel memory-efficient GAN architecture that enhances structural consistency in 3D medical image synthesis. Integrating Conditional Random Fields within a two-step generation process allows CRF-GAN improving spatial coherence while maintaining high-resolution image quality. The model's performance is evaluated against the state-of-the-art hierarchical (HA)-GAN model. Materials and Methods: We evaluate the performance of CRF-GAN against the HA-GAN model. The comparison between the two models was made through a quantitative evaluation, using FID and MMD metrics, and a qualitative evaluation, through a two-alternative forced choice (2AFC) test completed by a pool of 12 resident radiologists, to assess the realism of the generated images. Results: CRF-GAN outperformed HA-GAN with lower FID and MMD scores, indicating better image fidelity. The 2AFC test showed a significant preference for images generated by CRF-Gan over those generated by HA-GAN. Additionally, CRF-GAN demonstrated 9.34% lower memory usage and achieved up to 14.6% faster training speeds, offering substantial computational savings. Discussion: CRF-GAN model successfully generates high-resolution 3D medical images with non-inferior quality to conventional models, while being more memory-efficient and faster. The key objective was not only to lower the computational cost but also to reallocate the freed-up resources towards the creation of higher-resolution 3D imaging, which is still a critical factor limiting their direct clinical applicability. Moreover, unlike many previous studies, we combined qualitative and quantitative assessments to obtain a more holistic feedback on the model's performance.

eess.IV↗

arXiv2024

Physics-Based Simulation of the 2013 April 11 Solar Energetic Particle Event

Solar energetic particles (SEPs) can pose hazardous radiation risks to both humans and spacecraft electronics in space. Numerical modeling based on first principles offers valuable insights into the underlying physics of SEPs and provides synthetic observables for SEPs at any time and location in the inner heliosphere. In this work, we present a numerical scheme, which conserves the number of particles based on integral relations for Poisson brackets \citep{sokolov2023high}, to solve the kinetic equation for particle acceleration and transport processes. We implement this scheme within the Space Weather Modeling Framework, developed at the University of Michigan. In addition, we develop a new shock-capturing tool to study the coronal mass ejection-driven shock originating from the low solar corona. These methodological advancements are applied to conduct a comprehensive study of a historical SEP event on April 11, 2013. Multi-spacecraft observations, including SOHO, SDO, GOES and ACE near Earth, and STEREO-A/B, are used for model--data comparison and validation. We show synthetic observables, including extreme ultraviolet and white-light images, proton time--intensity profiles, and energy spectra, and discuss their differences and probable explanations compared to observations. Our simulation results demonstrate the application of the Poisson bracket scheme with a particle solver to simulating a historical SEP event. We also show the capability of extracting the complex shock surface using our shock-capturing tool and understand how the complex shock surface affects the particle acceleration process.

astro-ph.SR↗

arXiv2024

Towards novel tunability schemes for hybrid ferromagnetic transmon qubits

Flux tuning of qubit frequencies in superconducting quantum processors is fundamental for implementing single and multi-qubit gates in quantum algorithms. Typical architectures involve the use of DC or fast RF lines. However, these lines introduce significant heat dissipation and undesirable decoherence mechanisms, leading to a severe bottleneck for scalability. Among different solutions to overcome this issue, we propose integrating tunnel Superconductor-Insulating-thin superconducting interlayer-Ferromagnet-Superconductor Josephson junctions (SIsFS JJs) into a novel transmon qubit design, the so-called ferrotransmon. SIsFS JJs provide memory properties due to the presence of ferromagnetic barriers and preserve at the same time the low-dissipative behavior of tunnel-insulating JJs, thus promoting an alternative tuning of the qubit frequency. In this work, we discuss the fundamental steps towards the implementation of this hybrid ferromagnetic transmon. We will give a special focus on the design, simulations, and preliminary experimental characterization of superconducting lines to provide in-plane magnetic fields, fundamental for an on-chip control of the qubit frequencies in the ferrotransmon.

cond-mat.supr-con↗