arXiv subjects

Andrea De Simone

Publications and source records attributed to Andrea De Simone.

At least 19 recordsLinked to original sources

arXiv2026

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↗

arXiv2025

Optimizing Uncertainty-Aware Deep Learning for On-the-Edge Murmur Detection in Low-Resource Settings

Early and reliable detection of heart murmurs is essential for the timely diagnosis of cardiovascular diseases, yet traditional auscultation remains subjective and dependent on expert interpretation. This work investigates artificial intelligence (AI)-based murmur detection using the CirCor Heart Sound dataset, with a focus on enabling uncertainty-aware, resource-efficient deployment on edge devices. Three convolutional neural network (CNN) architectures of increasing complexity (Light, Baseline, and Heavy) were compared in terms of classification performance, computational cost, and suitability for on-device inference. Additionally, Monte Carlo Dropout was applied for uncertainty estimation, providing confidence measures to improve prediction sensitivity. Results show that lightweight models can achieve accuracy comparable to deeper networks (91%) while requiring two orders of magnitude fewer parameters. Incorporating uncertainty-based selective classification further improved sensitivity by 3%, enhancing robustness and clinical reliability. The findings highlight the feasibility of developing computationally efficient, uncertainty-aware AI systems for heart murmur screening in low-resource and remote healthcare settings.

eess.SP↗

arXiv2025

Incremental Firmware Update Over-the-Air for Low-Power IoT Devices over LoRaWAN

Efficiently supporting remote firmware updates in Internet of Things (IoT) devices remains a significant challenge due to the limitations of many IoT communication protocols, which often make it impractical to transmit full firmware images. Techniques such as firmware partitioning have been introduced to mitigate this issue, but they frequently fall short, especially in battery-powered systems where time and energy constraints are critical. As a result, physical maintenance interventions are still commonly required, which is costly and inconvenient in large-scale deployments. In this work, we present a lightweight and innovative method that addresses this challenge by generating highly compact delta patches, enabling firmware reconstruction directly on the device. Our algorithm is specifically optimized for low-power devices, minimizing both memory usage and computational overhead. Compared to existing solutions, our approach significantly reduces the data volume needed for updates while maintaining performance comparable to more complex alternatives. Experimental evaluations confirm that our method yields substantial time and energy savings, making it particularly well-suited for battery-powered IoT nodes. Although our implementation targets the LoRaWAN protocol, the approach is flexible and can be adapted to other IoT communication technologies.

eess.SY↗

arXiv2020

Nonparametric Density Estimation from Markov Chains

We introduce a new nonparametric density estimator inspired by Markov Chains, and generalizing the well-known Kernel Density Estimator (KDE). Our estimator presents several benefits with respect to the usual ones and can be used straightforwardly as a foundation in all density-based algorithms. We prove the consistency of our estimator and we find it typically outperforms KDE in situations of large sample size and high dimensionality. We also employ our density estimator to build a local outlier detector, showing very promising results when applied to some realistic datasets.

stat.ME↗

arXiv2020

The impact of undetected cases on tracking epidemics: the case of COVID-19

One of the key indicators used in tracking the evolution of an infectious disease isthe reproduction number. This quantity is usually computed using the reportednumber of cases, but ignoring that many more individuals may be infected (e.g.asymptomatics). We propose a statistical procedure to quantify the impact of un-detected infectious cases on the determination of the effective reproduction number. Our approach is stochastic, data-driven and not relying on any compartmentalmodel. It is applied to the COVID-19 case in eight different countries and all Italianregions, showing that the effect of undetected cases leads to estimates of the effective reproduction numbers larger than those obtained only with the reported cases by factors ranging from two to ten. Our findings urge caution about deciding when and how to relax containment measures based on the value of the reproduction number.

q-bio.PE↗

arXiv2019

LHC Phenomenology of Dark Matter with a Color-Octet Partner

Colored dark sectors where the dark matter particle is accompanied by colored partners have recently attracted theoretical and phenomenological interest. We explore the possibility that the dark sector consists of the dark matter particle and a color-octet partner, where the interaction with the Standard Model is governed by an effective operator involving gluons. The resulting interactions resemble the color analogues of electric and magnetic dipole moments. Although many phenomenological features of this kind of model only depend on the group representation of the partner under SU(3)$_c$, we point out that interesting collider signatures such as $R$-hadrons are indeed controlled by the interaction operator between the dark and visible sector. We perform a study of the current constraints and future reach of LHC searches, where the complementarity between different possible signals is highlighted and exploited.

hep-ph↗

arXiv2019

Composite 2HDM with singlets: a viable dark matter scenario

We study the non-minimal composite Higgs model with global symmetry $\text{SO}(7)$ broken to $\text{SO}(5)\times \text{SO}(2)$. The model results in a composite Two-Higgs doublet model (2HDM) equipped with two extra singlets, the lightest of which can be a viable dark matter candidate. The model is able to reproduce the correct dark matter relic density both via the usual thermal freeze-out and through late time decay of the heavier singlet. In the case of thermal freeze-out, it is possible to evade current experimental constraints even with the minimum fine tuning allowed by electroweak precision tests.

hep-ph↗

arXiv2019

Machine Learning in High Energy Physics Community White Paper

Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas for machine learning in particle physics. We detail a roadmap for their implementation, software and hardware resource requirements, collaborative initiatives with the data science community, academia and industry, and training the particle physics community in data science. The main objective of the document is to connect and motivate these areas of research and development with the physics drivers of the High-Luminosity Large Hadron Collider and future neutrino experiments and identify the resource needs for their implementation. Additionally we identify areas where collaboration with external communities will be of great benefit.

physics.comp-ph↗

arXiv2019

Guiding New Physics Searches with Unsupervised Learning

We propose a new scientific application of unsupervised learning techniques to boost our ability to search for new phenomena in data, by detecting discrepancies between two datasets. These could be, for example, a simulated standard-model background, and an observed dataset containing a potential hidden signal of New Physics. We build a statistical test upon a test statistic which measures deviations between two samples, using a Nearest Neighbors approach to estimate the local ratio of the density of points. The test is model-independent and non-parametric, requiring no knowledge of the shape of the underlying distributions, and it does not bin the data, thus retaining full information from the multidimensional feature space. As a proof-of-concept, we apply our method to synthetic Gaussian data, and to a simulated dark matter signal at the Large Hadron Collider. Even in the case where the background can not be simulated accurately enough to claim discovery, the technique is a powerful tool to identify regions of interest for further study.

hep-ph↗

arXiv2019

Searching for long-lived particles beyond the Standard Model at the Large Hadron Collider

Particles beyond the Standard Model (SM) can generically have lifetimes that are long compared to SM particles at the weak scale. When produced at experiments such as the Large Hadron Collider (LHC) at CERN, these long-lived particles (LLPs) can decay far from the interaction vertex of the primary proton-proton collision. Such LLP signatures are distinct from those of promptly decaying particles that are targeted by the majority of searches for new physics at the LHC, often requiring customized techniques to identify, for example, significantly displaced decay vertices, tracks with atypical properties, and short track segments. Given their non-standard nature, a comprehensive overview of LLP signatures at the LHC is beneficial to ensure that possible avenues of the discovery of new physics are not overlooked. Here we report on the joint work of a community of theorists and experimentalists with the ATLAS, CMS, and LHCb experiments --- as well as those working on dedicated experiments such as MoEDAL, milliQan, MATHUSLA, CODEX-b, and FASER --- to survey the current state of LLP searches at the LHC, and to chart a path for the development of LLP searches into the future, both in the upcoming Run 3 and at the High-Luminosity LHC. The work is organized around the current and future potential capabilities of LHC experiments to generally discover new LLPs, and takes a signature-based approach to surveying classes of models that give rise to LLPs rather than emphasizing any particular theory motivation. We develop a set of simplified models; assess the coverage of current searches; document known, often unexpected backgrounds; explore the capabilities of proposed detector upgrades; provide recommendations for the presentation of search results; and look towards the newest frontiers, namely high-multiplicity "dark showers", highlighting opportunities for expanding the LHC reach for these signals.

hep-ex↗

arXiv2018

Displaced Vertices from Pseudo-Dirac Dark Matter

Displaced vertices are relatively unusual signatures for dark matter searches at the LHC. We revisit the model of pseudo-Dirac dark matter (pDDM), which can accommodate the correct relic density, evade direct detection constraints, and generically provide observable collider signatures in the form of displaced vertices. We use this model as a benchmark to illustrate the general techniques involved in the analysis, the complementarity between monojet and displaced vertex searches, and provide a comprehensive study of the current bounds and prospective reach.

hep-ph↗

arXiv2017

Lyman-alpha Constraints on Ultralight Scalar Dark Matter: Implications for the Early and Late Universe

We investigate constraints on scalar dark matter (DM) by analyzing the Lyman-alpha forest, which probes structure formation at medium and small scales, and also by studying its cosmological consequences at high and low redshift. For scalar DM that constitutes more than 30% of the total DM density, we obtain a lower limit m >~ 10^{-21} eV for the mass of scalar DM. This implies an upper limit on the initial field displacement (or the decay constant for an axion-like field) of phi <~ 10^{16} GeV. We also derive limits on the energy scale of cosmic inflation and establish an upper bound on the tensor-to-scalar ratio of r < 10^{-3} in the presence of scalar DM. Furthermore, we show that there is very little room for ultralight scalar DM to solve the "small-scale crisis" of cold DM without spoiling the Lyman-alpha forest results. The constraints presented in this paper can be used for testing generic theories that contain light scalar fields.

astro-ph.CO↗

arXiv2017

Evaporation and scattering of momentum- and velocity-dependent dark matter in the Sun

Dark matter with momentum- or velocity-dependent interactions with nuclei has shown significant promise for explaining the so-called Solar Abundance Problem, a longstanding discrepancy between solar spectroscopy and helioseismology. The best-fit models are all rather light, typically with masses in the range of 3-5 GeV. This is exactly the mass range where dark matter evaporation from the Sun can be important, but to date no detailed calculation of the evaporation of such models has been performed. Here we carry out this calculation, for the first time including arbitrary velocity- and momentum-dependent interactions, thermal effects, and a completely general treatment valid from the optically thin limit all the way through to the optically thick regime. We find that depending on the dark matter mass, interaction strength and type, the mass below which evaporation is relevant can vary from 1 to 4 GeV. This has the effect of weakening some of the better-fitting solutions to the Solar Abundance Problem, but also improving a number of others. As a by-product, we also provide an improved derivation of the capture rate that takes into account thermal and optical depth effects, allowing the standard result to be smoothly matched to the well-known saturation limit.

hep-ph↗

arXiv2017

Geometric Baryogenesis from Shift Symmetry

We present a new scenario for generating the baryon asymmetry of the universe that is induced by a Nambu-Goldstone (NG) boson. The shift symmetry naturally controls the operators in the theory, while allowing the NG boson to couple to the spacetime geometry as well as to the baryons. The cosmological background thus sources a coherent motion of the NG boson, which leads to baryogenesis. Good candidates of the baryon-generating NG boson are the QCD axion and axion-like fields. In these cases the axion induces baryogenesis in the early universe, and can also serve as dark matter in the late universe.

hep-ph↗

arXiv2017

Towards the next generation of simplified Dark Matter models

This White Paper is an input to the ongoing discussion about the extension and refinement of simplified Dark Matter (DM) models. Based on two concrete examples, we show how existing simplified DM models (SDMM) can be extended to provide a more accurate and comprehensive framework to interpret and characterise collider searches. In the first example we extend the canonical SDMM with a scalar mediator to include mixing with the Higgs boson. We show that this approach not only provides a better description of the underlying kinematic properties that a complete model would possess, but also offers the option of using this more realistic class of scalar mixing models to compare and combine consistently searches based on different experimental signatures. The second example outlines how a new physics signal observed in a visible channel can be connected to DM by extending a simplified model including effective couplings. This discovery scenario uses the recently observed excess in the high-mass diphoton searches of ATLAS and CMS for a case study to show that such a pragmatic approach can aid the experimental search programme to verify/falsify a potential signal and to study its underlying nature. In the next part of the White Paper we outline other interesting options for SDMM that could be studied in more detail in the future. Finally, we discuss important aspects of supersymmetric models for DM and how these could help to develop of more complete SDMM.

hep-ex↗

arXiv2017

Spontaneous Baryogenesis without Baryon Isocurvature

We propose a new class of spontaneous baryogenesis models that does not produce baryon isocurvature perturbations. The baryon chemical potential in these models is independent of the field value of the baryon-generating scalar, hence the scalar field fluctuations are blocked from propagating into the baryon isocurvature. We demonstrate this mechanism in simple examples where spontaneous baryogenesis is driven by a non-canonical scalar field. The suppression of the baryon isocurvature allows spontaneous baryogenesis to be compatible even with high-scale inflation.

hep-ph↗

arXiv2016

Cosmological Aspects of Spontaneous Baryogenesis

We investigate cosmological aspects of spontaneous baryogenesis driven by a scalar field, and present general constraints that are independent of the particle physics model. The relevant constraints are obtained by studying the backreaction of the produced baryons on the scalar field, the cosmological expansion history after baryogenesis, and the baryon isocurvature perturbations. We show that cosmological considerations alone provide powerful constraints, especially for the minimal scenario with a quadratic scalar potential. Intriguingly, we find that for a given inflation scale, the other parameters including the reheat temperature, decoupling temperature of the baryon violating interactions, and the mass and decay constant of the scalar are restricted to lie within ranges of at most a few orders of magnitude. We also discuss possible extensions to the minimal setup, and propose two ideas for evading constraints on isocurvature perturbations: one is to suppress the baryon isocurvature with nonquadratic scalar potentials, another is to compensate the baryon isocurvature with cold dark matter isocurvature by making the scalar survive until the present.

hep-ph↗

arXiv2016

Simplified Models vs. Effective Field Theory Approaches in Dark Matter Searches

In this review we discuss and compare the usage of simplified models and Effective Field Theory (EFT) approaches in dark matter searches. We provide a state of the art description on the subject of EFTs and simplified models, especially in the context of collider searches for dark matter, but also with implications for direct and indirect detection searches, with the aim of constituting a common language for future comparisons between different strategies. The material is presented in a form that is as self-contained as possible, so that it may serve as an introductory review for the newcomer as well as a reference guide for the practitioner.

hep-ph↗