arXiv subjects

Marco Baldi

Publications and source records attributed to Marco Baldi.

At least 37 records · Page 2Linked to original sources

arXiv2025

BF-Max: an Efficient Bit Flipping Decoder with Predictable Decoding Failure Rate

The Bit-Flipping (BF) decoder, thanks to its very low computational complexity, is widely employed in post-quantum cryptographic schemes based on Moderate Density Parity Check codes in which, ultimately, decryption boils down to syndrome decoding. In such a setting, for security concerns, one must guarantee that the Decoding Failure Rate (DFR) is negligible. Such a condition, however, is very difficult to guarantee, because simulations are of little help and the decoder performance is difficult to model theoretically. In this paper, we introduce a new version of the BF decoder, that we call BF-Max, characterized by the fact that in each iteration only one bit (the least reliable) is flipped. When the number of iterations is equal to the number of errors to be corrected, we are able to develop a theoretical characterization of the DFR that tightly matches with numerical simulations. We also show how BF-Max can be implemented efficiently, achieving low complexity and making it inherently constant time. With our modeling, we are able to accurately predict values of DFR that are remarkably lower than those estimated by applying other approaches.

cs.IT↗

arXiv2025

Probing massive neutrinos and modified gravity with redshift-space morphologies and anisotropies of large-scale structure

Strong degeneracy exists between some modified gravity (MG) models and massive neutrinos because the enhanced structure growth produced by modified gravity can be suppressed due to the free-streaming massive neutrinos. Previous works showed this degeneracy can be broken with non-Gaussian or velocity information. Therefore in this work, we focus on the large-scale structure (LSS) in redshift space and investigate for the first time the possibility of using the non-Gaussian information and velocity information captured by the 3D scalar Minkowski functionals (MFs) and the 3D Minkowski tensors (MTs) to break this degeneracy. Based on the Quijote and Quijote-MG simulations, we find the imprints on redshift space LSS left by the Hu-Sawicki $f(R)$ gravity can be discriminated from those left by massive neutrinos with these statistics. With the Fisher information formalism, we first show how the MTs extract information with their perpendicular and parallel elements for both low- and high-density regions; then we compare constraints from the power spectrum monopole and MFs in real space with those in redshift space, and investigate how the constraining power is further improved with anisotropies captured by the quadrupole and hexadecapole of the power spectrum and the MTs; finally, we combine the power spectrum multipoles with MFs plus MTs and find the constraints from the power spectrum multipoles on $Ω_{\mathrm{m}}, h, σ_8$, $M_ν$, and $f_{R_0}$ can be improved, because they are complemented with non-Gaussian information, by a factor of 3.4, 3.0, 3.3, 3.3, and 1.9 on small scales ($k_{\rm{max}}=0.5~h\rm{Mpc}^{-1},\ R_G=5~h^{-1}\rm{Mpc}$), and 2.8, 2.2, 3.4, 3.4, and 1.5 on large scales ($k_{\rm{max}}=0.25~h\rm{Mpc}^{-1},\ R_G=10~h^{-1}\rm{Mpc}$).

astro-ph.CO↗

arXiv2025

Leveraging Angle of Arrival Estimation against Impersonation Attacks in Physical Layer Authentication

In this paper, we investigate the utilization of the angle of arrival (AoA) as a feature for robust physical layer authentication (PLA). While most of the existing approaches to PLA focus on common features of the physical layer of communication channels, such as channel frequency response, channel impulse response or received signal strength, the use of AoA in this domain has not yet been studied in depth, particularly regarding the ability to thwart impersonation attacks. In this work, we demonstrate that an impersonation attack targeting AoA based PLA is only feasible under strict conditions on the attacker's location and hardware capabilities, which highlights the AoA's potential as a strong feature for PLA. We extend previous works considering a single-antenna attacker to the case of a multiple-antenna attacker, and we develop a theoretical characterization of the conditions in which a successful impersonation attack can be mounted. Furthermore, we leverage extensive simulations in support of theoretical analyses, to validate the robustness of AoA-based PLA.

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arXiv2024

On the evolution of Betti curves in the Cosmic web

In this work, we study the evolution of Betti curves obtained by persistent-homological analysis of point clouds formed by halos in different cosmological $N$-body simulations. We show that they can be approximated with a scaled log-normal distribution function with reasonable precision. Our analysis shows that the shapes and maximums of Betti curves exhibit dependence on the mass range of the selected subpopulation of halos. Still, at the same time, the resolution of a simulation does not play any significant role, provided that the mass distribution of simulated halos is complete down to a given mass scale. Besides, we study how Betti curves change with the evolution of the Universe, i.e., their dependence on redshift. Sampling subpopulations of halos within certain mass ranges up to redshift $z=2.5$ yields a surprisingly small difference between corresponding Betti curves. We propose that this may be an indicator of the existence of a new specific topological invariant in the structure of the Universe.

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arXiv2024

The constraining power of the Marked Power Spectrum: an analytical study

The marked power spectrum - a two-point correlation function of a transformed density field - has emerged as a promising tool for extracting cosmological information from the large-scale structure of the Universe. In this work, we present the first comprehensive analytical study of the marked power spectrum's sensitivity to primordial non-Gaussianity (PNG) of the non-local type. We extend previous effective field theory frameworks to incorporate PNG, developing a complete theoretical model that we validate against the Quijote simulation suite. Through a systematic Fisher analysis, we compare the constraining power of the marked power spectrum against traditional approaches combining the power spectrum and bispectrum (P+B). We explore different choices of mark parameters to evaluate their impact on parameter constraints, particularly focusing on equilateral and orthogonal PNG as well as neutrino masses. Our analysis shows that while marking up underdense regions yields optimal constraints in the low shot-noise regime, the marked power spectrum's performance for discrete tracers with BOSS-like number densities does not surpass that of P+B analysis at mildly non-linear scales ($k \lesssim 0.25 \,h/\text{Mpc}$). However, the marked approach offers several practical advantages, including simpler estimation procedures and potentially more manageable systematic effects. Our theoretical framework reveals how the marked power spectrum incorporates higher-order correlation information through terms resembling tree-level bispectra and power spectrum convolutions. This work establishes a robust foundation for applying marked statistics to future large-volume surveys.

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arXiv2024

Decentralized Biometric Authentication based on Fuzzy Commitments and Blockchain

Blockchain technology, which was introduced for supporting cryptocurrencies, today provides a decentralized infrastructure for general information storage and execution of algorithms, thus enabling the conversion of many applications and services from a centralized and intermediated model to a decentralized and disintermediated one. In this paper we focus on biometric authentication, which is classically performed using centralized systems, and could hence benefit from decentralization. For such a purpose, however, an inherent contradiction between biometric applications and blockchain technology must be overcome, as the former require keeping biometric features private, while blockchain is a public infrastructure. We propose a blockchain-based biometric authentication protocol that enables decentralization and resilience while protecting the privacy, personal data, and, in particular, biometric features of users. The protocol we propose leverages fuzzy commitment schemes to allow biometric authentication to be performed without disclosing biometric data. We also analyze the security of the protocol we propose by considering some relevant attacks.

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arXiv2024

The impact of constrained interacting dark energy on the bound-zone velocity profile

We numerically study the effects of constrained interacting dark energy (CIDER) on the bound-zone velocity profiles around massive dark matter halos. Analyzing the CIDER simulations performed by Baldi (2023) for three different cases of dark sector coupling ($β=0.03$, $0.05$ and $0.08$) as well as for the standard $Λ$CDM cosmology ($β=0$), we determine the mean peculiar velocity profiles in the bound zones around the friends-of-friends halos with masses larger than $M_{\rm cut}=3\times 10^{13}\,h^{-1}M_{\odot}$ at three redshifts, $z=0$, $0.5$ and $1$. It is found that the universal power-law formula proposed by Falco et al. (2024) originally for the $Λ$CDM case still describes well the bound-zone velocity profiles, $V(r)$, even in the CIDER models. The slope of $V(r)$, turns out to be significantly affected by the CIDER, progressively decreasing as $β$ increases. Meanwhile, the amplitude of $V(r)$ exhibits little dependence on $β$, which is ascribed to the identical Hubble parameters shared by the $Λ$CDM and CIDER models in the entire redshift range. Our results imply that the bound-zone velocity slope can break a degeneracy even between the $Λ$CDM and CIDER models with $β\le 0.03$, which the standard cosmological diagnostics fail to distinguish. We devise a simple analytic formula for the bound-zone slope as a function of $β$, and prove its validity at all of the three redshifts. It is concluded that the slope of the mean bound-zone peculiar velocity profile should be in principle a powerful probe of dark sector interaction.

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arXiv2024

Towards unveiling the large-scale nature of gravity with the wavelet scattering transform

We present the first application of the Wavelet Scattering Transform (WST) in order to constrain the nature of gravity using the three-dimensional (3D) large-scale structure of the universe. Utilizing the Quijote-MG N-body simulations, we can reliably model the 3D matter overdensity field for the f(R) Hu-Sawicki modified gravity (MG) model down to $k_{\rm max}=0.5$ h/Mpc. Combining these simulations with the Quijote $ν$CDM collection, we then conduct a Fisher forecast of the marginalized constraints obtained on gravity using the WST coefficients and the matter power spectrum at redshift z=0. Our results demonstrate that the WST substantially improves upon the 1$σ$ error obtained on the parameter that captures deviations from standard General Relativity (GR), yielding a tenfold improvement compared to the corresponding matter power spectrum result. At the same time, the WST also enhances the precision on the $Λ$CDM parameters and the sum of neutrino masses, by factors of 1.2-3.4 compared to the matter power spectrum, respectively. Despite the overall reduction in the WST performance when we focus on larger scales, it still provides a relatively $4.5\times$ tighter 1$σ$ error for the MG parameter at $k_{\rm max}=0.2$ h/Mpc, highlighting its great sensitivity to the underlying gravity theory. This first proof-of-concept study reaffirms the constraining properties of the WST technique and paves the way for exciting future applications in order to perform precise large-scale tests of gravity with the new generation of cutting-edge cosmological data.

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arXiv2024

Telecommand Rejection Probability for CCSDS-compliant LDPC-Coded Transmissions with Tail Sequence

According to the Consultative Committee for Space Data Systems (CCSDS) recommendation for TeleCommand (TC) synchronization and coding, the Communications Link Transmission Unit (CLTU) consists of a start sequence, followed by coded data, and a tail sequence, which might be optional depending on the employed coding scheme. With regard to the latter, these transmissions traditionally use a modified Bose-Chaudhuri-Hocquenghem (BCH) code, to which two state-of-the-art Low-Density Parity-Check (LDPC) codes were later added. As a lightweight technique to detect the presence of the tail sequence, an approach based on decoding failure has traditionally been used, choosing a non-correctable string as the tail sequence. This works very well with the BCH code, for which bounded-distance decoders are employed. When the same approach is employed with LDPC codes, it is necessary to design the tail sequence as a non-correctable string for the case of iterative decoders based on belief propagation. Moreover, the tail sequence might be corrupted by noise, potentially converting it into a correctable pattern. It is therefore important that the tail sequence is chosen to be as much distant as possible, according to some metric, from any legitimate codeword. In this paper we study such problem, and analyze the TC rejection probability both theoretically and through simulations. Such a performance figure, being the rate at which the CLTU is discarded, should clearly be minimized. Our analysis is performed considering many different choices of the system parameters (e.g., length of the CLTU, decoding algorithm, maximum number of decoding iterations).

cs.IT↗

arXiv2024

Cosmological simulations of scale-dependent primordial non-Gaussianity

We present the results of a set of cosmological N-body simulations with standard $Λ$CDM cosmology but characterized by a scale-dependent primordial non-Gaussianity of the local type featuring a power-law dependence of the $f_{\rm NL}^{\rm loc}(k)$ at large scales followed by a saturation to a constant value at smaller scales where non-linear growth leads to the formation of collapsed cosmic structures. Such models are built to ensure consistency with current Cosmic Microwave Background bounds on primordial non-Gaussianity yet allowing for large effects of the non-Gaussian statistics on the properties of non-linear structure formation. We show the impact of such scale-dependent non-Gaussian scenarios on a wide range of properties of the resulting cosmic structures, such as the non-linear matter power spectrum, the halo and sub-halo mass functions, the concentration-mass relation, the halo and void density profiles, and we highlight for the first time that some of these models might mimic the effects of Warm Dark Matter for several of such observables

astro-ph.CO↗

arXiv2024

AoA-Based Physical Layer Authentication in Analog Arrays under Impersonation Attacks

We discuss the use of angle of arrival (AoA) as an authentication measure in analog array multiple-input multiple-output (MIMO) systems. A base station equipped with an analog array authenticates users based on the AoA estimated from certified pilot transmissions, while active attackers manipulate their transmitted signals to mount impersonation attacks. We study several attacks of increasing intensity (captured through the availability of side information at the attackers) and assess the performance of AoA-based authentication using one-class classifiers. Our results show that some attack techniques with knowledge of the combiners at the verifier are effective in falsifying the AoA and compromising the security of the considered type of physical layer authentication.

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arXiv2024

When Does Your Brain Know You? Segment Length and Its Impact on EEG-based Biometric Authentication Accuracy

In the quest for optimal EEG-based biometric authentication, this study investigates the pivotal balance for accurate identification without sacrificing performance or adding unnecessary computational complexity. Through a methodical exploration of segment durations, and employing a variety of sophisticated machine learning models, the research seeks to pinpoint a threshold where EEG data provides maximum informational yield for authentication purposes. The findings are set to advance the field of non-invasive biometric technologies, proposing a practical approach to secure and user-friendly identity verification systems while also raising considerations for the real-world application of EEG-based biometric authentication beyond controlled environments.

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arXiv2024

Quijote-PNG: Optimizing the summary statistics to measure Primordial non-Gaussianity

We apply a suite of different estimators to the Quijote-PNG halo catalogues to find the best approach to constrain Primordial non-Gaussianity (PNG) at non-linear cosmological scales, up to $k_{\rm max} = 0.5 \, h\,{\rm Mpc}^{-1}$. The set of summary statistics considered in our analysis includes the power spectrum, bispectrum, halo mass function, marked power spectrum, and marked modal bispectrum. Marked statistics are used here for the first time in the context of PNG study. We perform a Fisher analysis to estimate their cosmological information content, showing substantial improvements when marked observables are added to the analysis. Starting from these summaries, we train deep neural networks (NN) to perform likelihood-free inference of cosmological and PNG parameters. We assess the performance of different subsets of summary statistics; in the case of $f_\mathrm{NL}^\mathrm{equil}$, we find that a combination of the power spectrum and a suitable marked power spectrum outperforms the combination of power spectrum and bispectrum, the baseline statistics usually employed in PNG analysis. A minimal pipeline to analyse the statistics we identified can be implemented either with our ML algorithm or via more traditional estimators, if these are deemed more reliable.

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arXiv2024

Using Graph Theory for Improving Machine Learning-based Detection of Cyber Attacks

Early detection of network intrusions and cyber threats is one of the main pillars of cybersecurity. One of the most effective approaches for this purpose is to analyze network traffic with the help of artificial intelligence algorithms, with the aim of detecting the possible presence of an attacker by distinguishing it from a legitimate user. This is commonly done by collecting the traffic exchanged between terminals in a network and analyzing it on a per-packet or per-connection basis. In this paper, we propose instead to perform pre-processing of network traffic under analysis with the aim of extracting some new metrics on which we can perform more efficient detection and overcome some limitations of classical approaches. These new metrics are based on graph theory, and consider the network as a whole, rather than focusing on individual packets or connections. Our approach is validated through experiments performed on publicly available data sets, from which it results that it can not only overcome some of the limitations of classical approaches, but also achieve a better detection capability of cyber threats.

cs.CR↗

arXiv2024

The perspective of voids on rising cosmology tensions

We investigate the main tensions within the current standard model of cosmology from the perspective of the main statistics of cosmic voids, using the final BOSS DR12 data set. For this purpose, we present the first estimate of the $S_8\equiv σ_8\sqrt{Ω_{\rm m}/0.3}$ and $H_0$ parameters obtained from void number counts and shape distortions. To analyze void counts we relied on an extension of the popular volume-conserving model for the void size function, tailored to the application on data, including geometric and dynamic distortions. We calibrated the two nuisance parameters of this model with the official BOSS collaboration mock catalogs and propagated their uncertainty through the statistical analysis of the BOSS void number counts. The constraints from void shapes come from the study of the geometric distortions of the stacked void-galaxy cross-correlation function. In this work we focus our analysis on the $Ω_{\rm m}$-$σ_8$ and $Ω_{\rm m}$-$H_0$ parameter planes and derive the marginalized constraints $S_8 = 0.813^{+0.093}_{-0.068}$ and $H_0 = 67.3^{+10.0}_{-9.1} \ \mathrm{km} \ \mathrm{s}^{-1} \ \mathrm{Mpc}^{-1}$, which are fully compatible with constraints from the literature. These results are expected to notably improve in precision when analyzed jointly with independent probes and will open a new viewing angle on the rising cosmological tensions in the near future.

astro-ph.CO↗

arXiv2024

Quijote-PNG: The Information Content of the Halo Mass Function

We study signatures of primordial non-Gaussianity (PNG) in the redshift-space halo field on non-linear scales, using a combination of three summary statistics, namely the halo mass function (HMF), power spectrum, and bispectrum. The choice of adding the HMF to our previous joint analysis of power spectrum and bispectrum is driven by a preliminary field-level analysis, in which we train graph neural networks on halo catalogues to infer the PNG $f_\mathrm{NL}$ parameter. The covariance matrix and the responses of our summaries to changes in model parameters are extracted from a suite of halo catalogues constructed from the Quijote-PNG N-body simulations. We consider the three main types of PNG: local, equilateral and orthogonal. Adding the HMF to our previous joint analysis of power spectrum and bispectrum produces two main effects. First, it reduces the equilateral $f_\mathrm{NL}$ predicted errors by roughly a factor $2$, while also producing notable, although smaller, improvements for orthogonal PNG. Second, it helps break the degeneracy between the local PNG amplitude, $f_\mathrm{NL}^\mathrm{local}$, and assembly bias, $b_ϕ$, without relying on any external prior assumption. Our final forecasts for PNG parameters are $Δf_\mathrm{NL}^\mathrm{local} = 40$, $Δf_\mathrm{NL}^\mathrm{equil} = 210$, $Δf_\mathrm{NL}^\mathrm{ortho} = 91$, on a cubic volume of $1 \left(h^{-1}{\rm Gpc}\right)^3$, with a halo number density of $\bar{n}\sim 5.1 \times 10^{-5}~h^3\mathrm{Mpc}^{-3}$, at $z = 1$, and considering scales up to $k_\mathrm{max} = 0.5~h\,\mathrm{Mpc}^{-1}$.

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arXiv2024

Taming assembly bias for primordial non-Gaussianity

Primordial non-Gaussianity of the local type induces a strong scale-dependent bias on the clustering of halos in the late-time Universe. This signature is particularly promising to provide constraints on the non-Gaussianity parameter $f_{\rm NL}$ from galaxy surveys, as the bias amplitude grows with scale and becomes important on large, linear scales. However, there is a well-known degeneracy between the real prize, the $f_{\rm NL}$ parameter, and the (non-Gaussian) assembly bias i.e., the halo formation history-dependent contribution to the amplitude of the signal, which could seriously compromise the ability of large-scale structure surveys to constrain $f_{\rm NL}$. We show how the assembly bias can be modeled and constrained, thus almost completely recovering the power of galaxy surveys to competitively constrain primordial non-Gaussianity. In particular, studying hydrodynamical simulations, we find that a proxy for the halo properties that determine assembly bias can be constructed from photometric properties of galaxies. Using a prior on the assembly bias guided by this proxy degrades the statistical errors on $f_{\rm NL}$ only mildly compared to an ideal case where the assembly bias is perfectly known. The systematic error on $f_{\rm NL}$ that the proxy induces can be safely kept under control.

astro-ph.CO↗

arXiv2023

No Catch-22 for Fuzzy Dark Matter: testing substructure counts and core sizes via high-resolution cosmological simulations

Fuzzy Dark Matter (FDM) has recently emerged as an interesting alternative model to the standard Cold Dark Matter (CDM). In this model, dark matter consists of very light bosonic particles with quantum mechanical effects on galactic scales. Using the N-body code AX-GADGET, we perform cosmological simulations of FDM that fully model the dynamical effects of the quantum potential throughout cosmic evolution. Through the combined analysis of FDM volume and high-resolution zoom-in simulations of different FDM particle masses ($m_χ$ $\sim$ $10^{-23} - 10^{-21}$ eV/c$^2$), we study how FDM impacts the abundance of substructure and the inner density profiles of dark matter haloes. For the first time, using our FDM volume simulations, we provide a fitting formula for the FDM-to-CDM subhalo abundance ratio as a function of the FDM mass. More importantly, our simulations clearly demonstrate that there exists an extended FDM particle mass interval able to reproduce the observed substructure counts and, at the same time, create substantial cores ($r_{c} \sim 1$ kpc) in the density profile of dwarf galaxies ($\approx 10^{9}-10^{10}$ M$_{\odot}$), which stands in stark contrast with CDM predictions even with baryonic effects taken into account. The dark matter distribution in the faintest galaxies offers then a clear way to discriminate between FDM and CDM.

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