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Simone Ferrari

Publications and source records attributed to Simone Ferrari.

At least 19 recordsLinked to original sources
arXiv2026

Breaking Time: A Fully Gaussian Framework for Distributed and Continuous-Time SLAM

Continuous-time SLAM provides a principled framework for fusing heterogeneous sensors while estimating smooth trajectories, and is particularly well-suited for handling heterogeneous, asynchronous sensor streams with non-uniform readout patterns, such as rolling shutter cameras, LiDAR scanners, radar sweeps, or event-based sensors. In this work, we introduce G-solver, a fully Gaussian and distributed framework that combines Gaussian Belief Propagation (GBP) with Gaussian Process (GP) motion priors for continuous-time trajectory estimation. Our GP model provides a probabilistic representation of the trajectory, enabling consistent interpolation and the use of data-driven hyperparameters, while GBP offers a scalable message-passing formulation well-suited for decentralized settings. The resulting solver naturally extends to multi-camera scenarios without specialized synchronization or engineering effort. We evaluate the approach on synthetic and real data, including rolling shutter and distributed multi-camera optimization, demonstrating accurate and stable estimation with runtimes comparable to existing continuous-time methods. An open-source implementation is released.

cs.RO↗
arXiv2026

Hypercontractivity type property for generalized Mehler semigroups

We investigate the hypercontractivity property of generalized Mehler semigroups on the $L^p$-scale with respect to invariant measures. This property is first obtained in the purely theoretical setting of skew operators and, subsequently, deduced for generalized Mehler semigroups arising from linear stochastic differential equations perturbed by L\'evy noise. When the associated invariant measure $\mu$ lacks a purely Gaussian structure, jump components may prevent the validity of Nelson's classical $L^p$-$L^q$ estimates. However, a summability-improving property can be obtained in the setting of mixed-norm spaces $\mathcal{X}_{p,q}(E;\gamma,\pi)$ related to the factorization of the invariant measure $\mu = \gamma * \pi$ into a Gaussian part $\gamma$ and an infinitely divisible non-Gaussian part $\pi$. As in the classical Gaussian case, some modified logarithmic Sobolev inequalities with respect to invariant measures can be inferred.

math.AP↗
arXiv2025

MAD-BA: 3D LiDAR Bundle Adjustment -- from Uncertainty Modelling to Structure Optimization

The joint optimization of sensor poses and 3D structure is fundamental for state estimation in robotics and related fields. Current LiDAR systems often prioritize pose optimization, with structure refinement either omitted or treated separately using implicit representations. This paper introduces a framework for simultaneous optimization of sensor poses and 3D map, represented as surfels. A generalized LiDAR uncertainty model is proposed to address less reliable measurements in varying scenarios. Experimental results on public datasets demonstrate improved performance over most comparable state-of-the-art methods. The system is provided as open-source software to support further research.

cs.RO↗
arXiv2024

Regularity results for elliptic and parabolic systems of partial differential equations

We study Cauchy problems associated to elliptic operators acting on vector-valued functions and coupled up to the first-order. We prove pointwise estimates for the spatial derivatives of the semigroup associated to these problems in the space of bounded and continuous functions over $\R^d$. Consequently, we deduce relevant regularity results both in H\"older and Zygmund spaces and in Sobolev and Besov spaces.

math.AP↗
arXiv2024

Kinetic Inductance and Jitter Dependence of the Intrinsic Photon Number Resolution in Superconducting Nanowire Single-Photon Detectors

The ability to resolve photon numbers is crucial in quantum information science and technology, driving the development of detectors with intrinsic photon-number resolving (PNR) capabilities. Although transition edge sensors represent the state-of-the-art in PNR performance, superconducting nanowire single-photon detectors (SNSPDs) offer superior efficiency, speed, noise reduction, and timing precision. Directly inferring photon numbers, however, has only recently become feasible due to advances in readout technology. Despite this, photon-number discrimination remains constrained by the nanowire's electrical properties and readout jitter. In this work, we employ waveguide-integrated SNSPDs and time-resolved measurements to explore how the nanowire kinetic inductance and system jitter affect PNR capabilities. By analyzing the latency time of the photon detection, we can resolve changes in the rising edge of the detection pulse. We find that lower jitter as well as increased kinetic inductance enhances the pulse separation for different photon numbers and improves the PNR capability. Enhancing the kinetic inductance from 165 nH to 872 nH improves PNR quality by 12%, 31% and 23% over the first three photon numbers, though at the cost of reducing the detector's count rate from 165 Mcps to 19 Mcps. Our findings highlight the trade-off between PNR resolution and detector speed.

quant-ph↗
arXiv2024

Fast thermo-optic switching on silicon nitride platform through parity-time symmetry breaking

This work demonstrates a fast thermo-optic switching mechanism on silicon nitride on insulator platform leveraging parity-time symmetry breaking. The cladding-free design enables low-loss optical propagation in a partially metal-covered waveguide, with the same metal layer serving as an integrated heater for rapid phase tuning. The fabricated device exhibits an 8.5 {\mu}s rise time for a {\pi} phase shift, despite the weak thermo-optic coefficient in silicon nitride. Additionally, the impact of thermal cross-talk is investigated and an insertion loss as low as 0.39 dB for a 100-{\mu}m-long heater-waveguide section is demonstrated.

physics.optics↗
arXiv2024

MAD-ICP: It Is All About Matching Data -- Robust and Informed LiDAR Odometry

LiDAR odometry is the task of estimating the ego-motion of the sensor from sequential laser scans. This problem has been addressed by the community for more than two decades, and many effective solutions are available nowadays. Most of these systems implicitly rely on assumptions about the operating environment, the sensor used, and motion pattern. When these assumptions are violated, several well-known systems tend to perform poorly. This paper presents a LiDAR odometry system that can overcome these limitations and operate well under different operating conditions while achieving performance comparable with domain-specific methods. Our algorithm follows the well-known ICP paradigm that leverages a PCA-based kd-tree implementation that is used to extract structural information about the clouds being registered and to compute the minimization metric for the alignment. The drift is bound by managing the local map based on the estimated uncertainty of the tracked pose. To benefit the community, we release an open-source C++ anytime real-time implementation.

cs.RO↗
arXiv2024

VBR: A Vision Benchmark in Rome

This paper presents a vision and perception research dataset collected in Rome, featuring RGB data, 3D point clouds, IMU, and GPS data. We introduce a new benchmark targeting visual odometry and SLAM, to advance the research in autonomous robotics and computer vision. This work complements existing datasets by simultaneously addressing several issues, such as environment diversity, motion patterns, and sensor frequency. It uses up-to-date devices and presents effective procedures to accurately calibrate the intrinsic and extrinsic of the sensors while addressing temporal synchronization. During recording, we cover multi-floor buildings, gardens, urban and highway scenarios. Combining handheld and car-based data collections, our setup can simulate any robot (quadrupeds, quadrotors, autonomous vehicles). The dataset includes an accurate 6-dof ground truth based on a novel methodology that refines the RTK-GPS estimate with LiDAR point clouds through Bundle Adjustment. All sequences divided in training and testing are accessible through our website.

cs.CV↗
arXiv2023

$L^p$-$L^q$ estimates for transition semigroups associated to dissipative stochastic systems

In a separable Hilbert space, we study supercontractivity and ultracontractivity properties for a transition semigroups associated with a stochastic partial differential equations. This is done in terms of exponential integrability of Lipschitz functions and some logarithmic Sobolev-type inequalities with respect to invariant measures. The abstract characterization results concerning the improving of summability can be applied to transition semigroups associated to a stochastic reaction-diffusion equations.

math.PR↗
arXiv2022

Schauder regularity results in separable Hilbert spaces

We prove Schauder type estimates for solutions of stationary and evolution equations driven by weak generators of transition semigroups associated to a semilinear stochastic partial differential equations with values in a separable Hilbert space.

math.AP↗
arXiv2021

Single-photon detection and cryogenic reconfigurability in Lithium Niobate nanophotonic circuits

Lithium-Niobate-On-Insulator (LNOI) is emerging as a promising platform for integrated quantum photonic technologies because of its high second-order nonlinearity and compact waveguide footprint. Importantly, LNOI allows for creating electro-optically reconfigurable circuits, which can be efficiently operated at cryogenic temperature. Their integration with superconducting nanowire single-photon detectors (SNSPDs) paves the way for realizing scalable photonic devices for active manipulation and detection of quantum states of light. Here we report the first demonstration of these two key components integrated in a low loss (0.2 dB/cm) LNOI waveguide network. As an experimental showcase of our technology, we demonstrate the combined operation of an electrically tunable Mach-Zehnder interferometer and two waveguide-integrated SNSPDs at its outputs. We show static reconfigurability of our system with a bias-drift-free operation over a time of 12 hours, as well as high-speed modulation at a frequency up to 1 GHz. Our results provide blueprints for implementing complex quantum photonic devices on the LNOI platform.

quant-ph↗
arXiv2020

On the Flow Past an Array of Two-Dimensional Street Canyons Between Slender Buildings

The flow above idealized, two-dimensional series of parallelepipedal buildings is examined with the aim of investigating how the building width to height aspect ratio affects the turbulence in the roughness sublayer and the ventilation of the underlying street canyons. We compare the case of buildings with a squared section with a configuration with slender buildings both in the case of unit canyon width to height aspect ratio and in the case of AR = 2. The former corresponds to skimming flow and the latter to wake-interference regime. Measurements are performed in a water channel, measuring velocity on a vertical mid-plane using a particle image velocimetry technique. The mean flow, its second-order turbulence statistics, the exchange fluxes, and the integral time scales investigated, with results showing that slender buildings enhance turbulence production and yield longer integral time scales in the region just above the building roof. The combined analysis of the turbulence production fields and the snapshots of the flow during sweep and ejection events demonstrate that the shear layer between the canyon and the external flow is significantly more unstable with slender buildings, mainly because the damping effect of the vertical velocity fluctuations from the flat roof of the upwind building is substantially missing. Consequently, a larger (downstream) portion of the interface is prone to the direct interaction of the external flow structures. The higher turbulence intensity promotes the ventilation at the canyon interface. In summary, the present experiments show that the effect of the reduced building aspect ratio is particularly significant when the urban canopy consists of narrow canyons. The result is of interest since narrow street canyons are typically bounded by slender buildings in the urban texture of the old European city centres.

physics.flu-dyn↗
arXiv2019

Superconducting nanowire single-photon spectrometer exploiting cascaded photonic crystal cavities

Superconducting nanowire single-photon detectors promise efficient (~100%) and fast (~Gcps) detection of light at the single-photon level. They constitute one of the building blocks to realize integrated quantum optical circuits in a waveguide architecture. The optical response of single-photon detectors, however, is limited to measure only the presence of photons. It misses the capability to resolve the spectrum of a possible broadband illumination. In this work, we propose the optical design for a superconducting nanowire single-photon spectrometer in an integrated optical platform. We exploit a cascade of cavities with different resonance wavelengths side-coupled to a photonic crystal bus waveguide. This allows to demultiplex different wavelengths into different spatial regions, where individual superconducting nanowires that measure the presence of single photons are placed next to these cavities. We employ temporal coupled-mode theory to derive the optimal conditions to achieve a high absorption efficiency in the nanowire with fine spectral resolution. It is shown that the use of a mirror at the end of the cascaded system that terminates the photonic crystal bus waveguide increases the absorption efficiency up to unity, in principle, in the absence of loss. The expected response is demonstrated by full-wave simulations for both two-dimensional and three-dimensional structures. Absorption efficiencies of about 80% are achieved both in two-dimensional structures for four cascaded cavities and in three-dimensional structures for two cascaded cavities. The achieved spectral resolution is about 1 nm. We expect that the proposed setup, both analytically studied and numerically demonstrated in this work, offers a great impetus for future quantum nanophotonic on-chip technologies.

physics.optics↗
arXiv2018

Gradient estimates for perturbed Ornstein-Uhlenbeck semigroups on infinite dimensional convex domains

Let $X$ be a separable Hilbert space endowed with a non-degenerate centred Gaussian measure $\gamma$ and let $\lambda_1$ be the maximum eigenvalue of the covariance operator associated with $\gamma$. The associated Cameron--Martin space is denoted by $H$. For a sufficiently regular convex function $U:X\to\mathbb{R}$ and a convex set $\Omega\subseteq X$, we set $\nu:=e^{-U}\gamma$ and we consider the semigroup $(T_\Omega(t))_{t\geq 0}$ generated by the self-adjoint operator defined via the quadratic form \[ (\varphi,\psi)\mapsto \int_\Omega\langle D_H\varphi,D_H\psi\rangle_Hd\nu, \] where $\varphi,\psi$ belong to $D^{1,2}(\Omega,\nu)$, the Sobolev space defined as the domain of the closure in $L^2(\Omega,\nu)$ of $D_H$, the gradient operator along the directions of $H$. A suitable approximation procedure allows us to prove some pointwise gradient estimates for $(T_\Omega(t))_{t\ge 0}$. In particular, we show that \[ |D_H T_\Omega(t)f|_H^p\le e^{- p \lambda_1^{-1} t}(T_\Omega(t)|D_H f|^p_H), \qquad\, t>0,\ \nu\textrm{ -a.e. in }\Omega, \] for any $p\in [1,+\infty)$ and $f\in D^{1,p}(\Omega ,\nu)$. We deduce some relevant consequences of the previous estimate, such as the logarithmic Sobolev inequality and the Poincar\'e inequality in $\Omega$ for the measure $\nu$ and some improving summability properties for $(T_\Omega(t))_{t\geq 0}$. In addition we prove that if $f$ belongs to $L^p(\Omega,\nu)$ for some $p\in(1,\infty)$, then \[|D_H T_\Omega(t)f|^p_H \leq K_p t^{-\frac{p}{2}} T_\Omega(t)|f|^p,\qquad \, t>0,\ \nu\text{-a.e. in }\Omega,\] where $K_p$ is a positive constant depending only on $p$. Finally we investigate on the asymptotic behaviour of the semigroup $(T_\Omega(t))_{t\geq 0}$ as $t$ goes to infinity.

math.AP↗
arXiv2016

Sub-Poisson-Binomial Light

We introduce the general parameter Q_PB that provides an experimentally accessible nonclassicality measure for light. The parameter is quantified by the click statistics obtained from on-off detectors in a general multiplexing detection setup. Sub-Poisson-binomial statistics, observed by Q_PB<0, indicates that a given state of light is nonclassical. Our new parameter replaces the binomial parameter Q_B for more general cases, where any unbalance among the multiplexed modes is allowed, thus enabling the use of arbitrary multiplexing schemes. The significance of the parameter Q_PB is theoretically examined in a measurement setup that only consists of a ring resonator and a single on-off detector. The proposed setup exploits minimal experimental resources and is geared towards a fully integrated quantum nanophotonic circuit. The results show that nonclassical features remain noticeable even in the presence of significant losses, rendering the new nonclassicality test more practical and flexible to be used in various nanophotonic platforms.

quant-ph↗
arXiv2016

Maximal Sobolev regularity for solutions of elliptic equations in infinite dimensional Banach spaces endowed with a weighted Gaussian measure

Let $X$ be a separable Banach space endowed with a non-degenerate centered Gaussian measure $\mu$. The associated Cameron-Martin space is denoted by $H$. Let $\nu=e^{-U}\mu$, where $e^{-U}$ is a sufficiently regular weight and $U:X\rightarrow\mathbb{R}$ is a convex and continuous function. In this paper we are interested in the $W^{2,2}$ regularity of the weak solutions of elliptic equations of the type \[\lambda u-L_\nu u=f,\] where $\lambda>0$, $f\in L^2(X,\nu)$ and $L_\nu$ is the self-adjoint operator associated with the quadratic form \[(\psi,\varphi)\mapsto \int_X\left\langle\nabla_H\psi,\nabla_H\varphi\right\rangle_Hd\nu\qquad\psi,\varphi\in W^{1,2}(X,\nu).\]

math.AP↗