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PubblicazioneSeeing what you hear: Compression of rat visual perceptual space by task-irrelevant sounds( 2025)The brain combines information from multiple sensory modalities to build a consistent representation of the world. The principles by which multimodal stimuli are integrated in cortical hierarchies are well studied, but it is less clear whether and how unimodal inputs shape the processing of signals carried by a different modality. In rodents, for instance, direct connections from primary auditory cortex reach visual cortex, but studies disagree on the impact of these projections on visual cortical processing. Both enhancement and suppression of visually evoked responses by auditory inputs have been reported, as well as sharpening of orientation tuning and improvement in the coding of visual information. Little is known, however, about the functional impact of auditory signals on rodent visual perception. Here we trained a group of rats in a visual temporal frequency (TF) classification task, where the visual stimuli to categorize were paired with simultaneous but taskirrelevant auditory stimuli, to prevent high-level multisensory integration and investigate instead the spontaneous, direct impact of auditory signals on the perception of visual stimuli. Rat classification of visual TF was strongly and systematically altered by the presence of sounds, in a way that was determined by sound intensity but not by its temporal modulation. To investigate the mechanisms underlying this phenomenon, we developed a Bayesian ideal observer model, combined with a neural coding scheme where neurons linearly encode visual TF but are inhibited by concomitant sounds by a measure that depends on their intensity. This model captured very precisely the full spectrum of rat perceptual choices we observed, supporting the hypothesis that auditory inputs induce an effective compression of the visual perceptual space. This suggests an important role for inhibition as the key mediator of auditory-visual interactions and provides clear, mechanistic hypotheses to be tested by future work on visual cortical codes.
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PubblicazioneElectro-mechanical wrinkling of soft dielectric films bonded to hyperelastic substrates( 2026)Active control of wrinkling in soft film-substrate composites using electric fields is a critical challenge in tunable material systems. Here, we investigate the electro-mechanical instability of a soft dielectric film bonded to a hyperelastic substrate, revealing the fundamental mechanisms that enable on-demand surface patterning. For the linearized stability analysis, we use the Stroh formalism and the surface impedance method to obtain exact and sixth-order approximate bifurcation equations that signal the onset of wrinkles. We derive the explicit bifurcation equations giving the critical stretch and critical voltage for wrinkling, as well as the corresponding critical wavenumber. We look at scenarios where the voltage is kept constant and the stretch changes, and vice versa. We provide the thresholds of the shear modulus ratio rc0 or pre-stretch λc0 below which the film-substrate system wrinkles mechanically, prior to the application of a voltage. These predictions offer theoretical guidance for practical structural design, as the shear modulus ratio r and/or the pre-stretch λ can be chosen to be slightly greater than rc0 and/or λc0, so that the film-substrate system wrinkles with a small applied voltage. Finally, we simulate the full nonlinear behavior using the Finite Element method (FEniCS) to validate our formulas and conduct a post-buckling analysis. This work advances the fundamental understanding of electro-mechanical wrinkling instabilities in soft material systems. By enabling active control of surface morphologies via applied electric fields, our findings open new avenues for adaptive technologies in soft robotics, flexible electronics, smart surfaces, and bioinspired systems.
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PubblicazioneNeural Empirical Interpolation Method for Nonlinear Model Reduction( 2025)In this paper, we introduce the neural empirical interpolation method (NEIM), a neural network-based alternative to the discrete empirical interpolation method for reducing the time complexity of computing the nonlinear term in a reduced-order model (ROM) for a parameterized nonlinear partial differential equation. NEIM is a greedy algorithm which accomplishes this reduction by approximating an affine decomposition of the nonlinear term of the ROM, where the vector terms of the expansion are given by neural networks depending on the ROM solution, and the coefficients are given by an interpolation of some “optimal” coefficients. Because NEIM is based on a greedy strategy, we are able to provide a basic error analysis to investigate its performance. NEIM has the advantages of being easy to implement in models with automatic differentiation, of being a nonlinear projection of the ROM nonlinearity, of being efficient for both nonlocal and local nonlinearities, and of relying solely on data and not the explicit form of the ROM nonlinearity. We demonstrate the effectiveness of the methodology on solution-dependent and solution-independent nonlinearities, a nonlinear elliptic problem, and a nonlinear parabolic model of liquid crystals. Code availability: https://github.com/maxhirsch/NEIM. © 2025 Society for Industrial and Applied Mathematics
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PubblicazioneSystematic bias in LISA ringdown analysis due to waveform inaccuracy( 2025)Inaccurate modeling of gravitational-wave signals can introduce systematic biases in the inferred source parameters. As detector sensitivities improve and signals become louder, mitigating such waveform-induced systematics becomes increasingly important. In this work, we assess the systematic biases introduced by an incomplete description of the ringdown signal from massive black hole binaries in the LISA band. Specifically, we investigate the impact of mode truncation in the ringdown template. Using a reference waveform composed of 13 modes, we establish a mode hierarchy and determine the minimum number of modes required to avoid parameter biases across a wide range of LISA sources. For typical systems with masses ∼106–107M⊙ at redshifts z ∼ 2–6, we find that at least 3–6 modes are needed for accurate parameter estimation, while high signal-to-noise ratio events may need at least 10 modes. Our results are a window-insensitive lower bound on the minimum number of modes, as more modes may be needed depending on the choice of time-domain windowing of the postmerger signal.
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PubblicazioneTransferable mechanism of perpendicular magnetic anisotropy switching by hole doping in in VX2 (X=Te, Se, S) monolayers( 2025)The ability to tune and switch magnetic anisotropy to a perpendicular orientation is a key challenge for implementing two-dimensional magnets in spintronic devices. H-phase vanadium dichalcogenides VX2 (X = Te, Se, S) are promising ferromagnetic semiconductors with large magnetic anisotropy energy (MAE). Recent work has shown that hole doping can switch their easy axis to out-of-plane, although the microscopic origin of this perpendicular magnetic anisotropy (PMA) remains unclear. Using density-functional-theory calculations, we demonstrate that the PMA enhancement arises from first-order spin-orbit coupling (SOC) acting on topmost degenerate valence states with nonzero orbital angular momentum projection (ml ≠ 0). In this case, the L̂_z Ŝ_z term dominates for perpendicular magnetization orientation, while in-plane orientations involve only weaker, second-order SOC contributions. The increased valence bandwidth leads to depletion of higher-energy states upon hole doping, stabilizing PMA. From this mechanism, we identify two transferable design principles for enhancing magnetic anisotropy under weak hole doping: (i) orbital degeneracy at the valence-band edge protected by point-group symmetry and (ii) finite SOC in the degenerate manifold. Notably, we identify multiple magnetic semiconductors that meet these criteria and display enhanced MAE under hole doping. Furthermore, we show that band engineering can strategically place these degenerate orbitals at the valence band edge, significantly boosting PMA when hole-doped. We also examine trends in VTe2, VSe2, and VS2 to determine the influence of crystal-field splitting, exchange interaction, and orbital hybridization on the valence band edges. These results provide both a fundamental understanding of PMA switching upon hole doping and a transferable strategy for tuning magnetic anisotropy, essential for designing high-performance spintronic materials.