arXiv subjects

David Sanchez

Publications and source records attributed to David Sanchez.

At least 19 recordsLinked to original sources

arXiv2026

Detecting Historical Turning Points in Italian Media: A Complex Systems Approach to a Diachronic News Corpus

The increasing availability of large-scale textual corpora has opened new possibilities for data-driven, quantitative approaches to historical analysis using Natural Language Processing (NLP). However, diachronic corpora with historical relevance from the pre-digital era remain scarce and often incomplete. We present a quantitative approach to historical analysis based on the reconstruction and exploration of a diachronic corpus of around 600,000 articles from the Italian newspaper "La Repubblica", covering all the articles published from the 1st of January 1985 to the 31st of December 2000 - a period of major political, social, and geopolitical change in Italy and globally. Using NLP techniques, we analyze the text at both lexical and semantic levels; we then apply tools from complex systems and statistical physics to trace shifts in media discourse over time. This allows us to detect key transition periods, such as the transition from the First Republic to the Second Republic in Italy, or major international conflicts like the Gulf War or the Kosovo War, without relying on prior labeling. The results show how combining computational linguistics with ideas from complex systems can offer new quantitative insight into historical changes, opening up new paths for studying the dynamics of media and society through large-scale textual data.

physics.soc-ph↗

arXiv2026

Phonological distances for linguistic typology and the origin of Indo-European languages

We show that short-range phoneme dependencies encode large-scale patterns of linguistic relatedness, with direct implications for quantitative typology and evolutionary linguistics. Specifically, using an information-theoretic framework, we argue that phoneme sequences modeled as second-order Markov chains essentially capture the statistical correlations of a phonological system. This finding enables us to quantify distances among 67 modern languages from a multilingual parallel corpus employing a distance metric that incorporates articulatory features of phonemes. The resulting phonological distance matrix recovers major language families and reveals signatures of contact-induced convergence. Remarkably, we obtain a clear correlation with geographic distance, allowing us to constrain a plausible homeland region for the Indo-European family, consistent with the Steppe hypothesis.

cs.CL↗

arXiv2026

Initial Performance of a Long Axial FOV PET with TOF and DOI capabilities: IMAS system

This work summarizes the design, construction, initial performance evaluation and pilot clinical results of the IMAS system, a long axial field of view (FOV), also known as total-body (TB-), positron emission tomography (PET) prototype scanner. This PET enables for the first time in TB-PET imaging, simultaneously time-of-flight (TOF) and depth-of-interaction (DOI) capabilities. The IMAS detector block is based on LYSO semi monolithic scintillators, with individual slab sizes of 3 mm x 25 mm x 20 mm each. Arrays of 1x8 slabs are coupled to 8x8 Silicon Photomultiplier arrays. A proprietary readout reduces the 64 signals to only 16 outputs, preserving both 3D photon impact positioning and timing accuracy. IMAS has a total of 30,720 channels. PETsys electronics is used for data acquisition. The IMAS geometry is based on 5 rings of 10 cm each, with a 5 cm gap between them. It defines an axial FOV of 71 cm with a bore aperture of 82 cm. We report in this work the pilot tests of the system performance and the first clinical results. We found that the system spatial resolution remained below 4 mm across the entire FOV, even at the off-radial position of 30 cm. A coincidence time resolution with a small size 22Na source of 560 ps FWHM was measured. A sensitivity of 56.54 cps/kBq is in good agreement with previous simulation studies; however, the noise equivalent count rates performance (79 kcps at 3.26 kBq/mL) was significantly lower than expected, likely due to a data transfer bottleneck between the system and the acquisition workstation. Finally, a comparison of one of the imaged patients with a commercial TOF PET/CT scanner is also provided, pinpointing an improved tumor identification for IMAS, and the advantages of TOF and especially DOI capabilities.

physics.med-ph↗

arXiv2025

HEGS : Revisiting a decade of H.E.S.S. extragalactic observations

During its first phase, from 2004 up to the end of 2012, the H.E.S.S. (High Energy Stereoscopic System) experiment observed the extragalactic skies for more than 2700 hours. These data have been re-analysed in a single consistent framework, leading to the derivation of a catalog of 23 sources. In total, about 5.7% of the sky was observed, allowing for several additional studies to be conducted: source variability, extragalactic gamma-ray background light, and comparison with the Fermi-LAT catalogues. In this contribution, we discuss these results and present the high-level data (catalogs, maps) released to the astrophysical community.

astro-ph.HE↗

arXiv2025

Methods for statistical detection of GRBs in the context of the LST-CTAO

Gamma-Ray Bursts (GRBs) afterglows are rapidly decaying signals that pose significant detection challenges, requiring improved methods to track their temporal evolution. In this study, we systematically compare various techniques for detecting GRB-like transient emissions at very high energies (VHE, >100 GeV). Our analysis includes time-dependent extension of the standard method (i.e., Li & Ma 1983) and other previously developed methods in the literature, alongside a novel likelihood-based approach, which directly fits spectral and temporal decay features to IACT data. Through dedicated observation simulations, we evaluate the performance of these methods for the Large-Sized Telescope prototype (LST-1) of the Cherenkov Telescope Array Observatory (CTAO). We characterised the enhanced sensitivity found in some of these methods compared to the standard significance estimation. For GRBs simulated with very fast afterglow decay, an improvement of more than a factor of two is seen in detections for some of the methods presented here, compared to the standard Li&Ma approach.

astro-ph.HE↗

arXiv2025

Understanding and Controlling V-Doping and S-Vacancy Behavior in Two-Dimensional Semiconductors- Toward Predictive Design

Doping in transition metal dichalcogenide (TMD) monolayers provides a powerful method to precisely tailor their electronic, optical, and catalytic properties for advanced technological applications, including optoelectronics, catalysis, and quantum technologies. However, doping efficiency and outcomes in these materials are strongly influenced by the complex interactions between introduced dopants and intrinsic defects, particularly sulfur vacancies. This coupling between dopants and defects can lead to distinctly different behaviors depending on doping concentration, presenting significant challenges in the predictable and controlled design of TMD properties. For example, in this work we systematically varied the p-type vanadium (V) doping density in tungsten disulfide (WS2) monolayers and observed a transition in doping behavior. At low concentrations, V-dopants enhance the native optical properties of WS2, as evidenced by increased photoluminescence, without introducing new electronic states. However, at higher concentrations, V-dopants promote the formation of vanadium-sulfur vacancy complexes that generate mid-gap states, with energies that can be precisely tuned by controlling the vanadium concentration. Using a combination of excitation- and temperature-dependent photoluminescence microscopy, atomic-resolution scanning transmission electron microscopy, and first-principles calculations, we identify attractive interactions between p-type V-dopants and n-type monosulfur vacancies. Our results provide mechanistic understanding of how enthalpic dopant-defect interactions versus entropic effects govern the balance between property enhancement versus perturbation of transition metal dichalcogenides and suggest a pathway toward the rational design of doping strategies for next-generation optoelectronic, catalytic, and quantum devices.

cond-mat.mtrl-sci↗

arXiv2025

Nonlinear Transport in Carbon Quantum Dot Electronic Devices: Experiment and Theory

Carbon quantum dots (CQDs) are a promising material for electronic applications due to their easy fabrication and interesting semiconductor properties. Further, CQDs exhibit quantum confinement and charging effects, which may lead not only to improved performances but also to devices with novel functionalities. Here, we investigate the electronic transport of CQDs embedded on epoxy polymer. Our samples are coupled to interdigitated electrodes with individually addressable microelectrodes. Remarkably, the current-voltage characteristics show strongly nonlinear regimes at room temperature, ranging from Schottky diode to Coulomb blockade and even negative differential conductance behavior. We propose a master equation theoretical framework which allows us to compute current curves that agree well with the observations. This model emphasizes the importance of interacting dots and electron traps in generating a cohesive picture that encompasses all transport regimes. Overall, our results suggest that CQDs constitute a versatile materials platform for 3D integrated electronic purposes.

cond-mat.mes-hall↗

arXiv2025

DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs

Large language models (LLMs) have recently revolutionized language processing tasks but have also brought ethical and legal issues. LLMs have a tendency to memorize potentially private or copyrighted information present in the training data, which might then be delivered to end users at inference time. When this happens, a naive solution is to retrain the model from scratch after excluding the undesired data. Although this guarantees that the target data have been forgotten, it is also prohibitively expensive for LLMs. Approximate unlearning offers a more efficient alternative, as it consists of ex post modifications of the trained model itself to prevent undesirable results, but it lacks forgetting guarantees because it relies solely on empirical evidence. In this work, we present DP2Unlearning, a novel LLM unlearning framework that offers formal forgetting guarantees at a significantly lower cost than retraining from scratch on the data to be retained. DP2Unlearning involves training LLMs on textual data protected using {\epsilon}-differential privacy (DP), which later enables efficient unlearning with the guarantees against disclosure associated with the chosen {\epsilon}. Our experiments demonstrate that DP2Unlearning achieves similar model performance post-unlearning, compared to an LLM retraining from scratch on retained data -- the gold standard exact unlearning -- but at approximately half the unlearning cost. In addition, with a reasonable computational cost, it outperforms approximate unlearning methods at both preserving the utility of the model post-unlearning and effectively forgetting the targeted information.

cs.LG↗

arXiv2024

Entropy and type-token ratio in gigaword corpora

There are different ways of measuring diversity in complex systems. In particular, in language, lexical diversity is characterized in terms of the type-token ratio and the word entropy. We here investigate both diversity metrics in six massive linguistic datasets in English, Spanish, and Turkish, consisting of books, news articles, and tweets. These gigaword corpora correspond to languages with distinct morphological features and differ in registers and genres, thus constituting a varied testbed for a quantitative approach to lexical diversity. We unveil an empirical functional relation between entropy and type-token ratio of texts of a given corpus and language, which is a consequence of the statistical laws observed in natural language. Further, in the limit of large text lengths we find an analytical expression for this relation relying on both Zipf and Heaps laws that agrees with our empirical findings.

cs.CL↗

arXiv2024

Computational lexical analysis of Flamenco genres

Flamenco, recognized by UNESCO as part of the Intangible Cultural Heritage of Humanity, is a profound expression of cultural identity rooted in Andalusia, Spain. However, there is a lack of quantitative studies that help identify characteristic patterns in this long-lived music tradition. In this work, we present a computational analysis of Flamenco lyrics, employing natural language processing and machine learning to categorize over 2000 lyrics into their respective Flamenco genres, termed as $\textit{palos}$. Using a Multinomial Naive Bayes classifier, we find that lexical variation across styles enables to accurately identify distinct $\textit{palos}$. More importantly, from an automatic method of word usage, we obtain the semantic fields that characterize each style. Further, applying a metric that quantifies the inter-genre distance we perform a network analysis that sheds light on the relationship between Flamenco styles. Remarkably, our results suggest historical connections and $\textit{palo}$ evolutions. Overall, our work illuminates the intricate relationships and cultural significance embedded within Flamenco lyrics, complementing previous qualitative discussions with quantitative analyses and sparking new discussions on the origin and development of traditional music genres.

cs.CL↗

arXiv2024

Vanadium-Doped Molybdenum Disulfide Monolayers with Tunable Electronic and Magnetic Properties: Do Vanadium-Vacancy Pairs Matter?

Monolayers of molybdenum disulfide (MoS2) are the most studied two-dimensional (2D) transition-metal dichalcogenides (TMDs), due to its exceptional optical, electronic, and opto-electronic properties. Recent studies have shown the possibility of incorporating a small amount of magnetic transition metals (e.g., Fe, Co, Mn, V) into MoS2 to form a 2D dilute magnetic semiconductor (2D-DMS). However, the origin of the observed ferromagnetism has remained elusive, due to the presence of randomly generated sulfur vacancies during synthesis that can pair with magnetic dopants to form complex dopant-vacancy configurations altering the magnetic order induced by the dopants. By combining high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) imaging with first-principles density functional theory (DFT) calculations and magnetometry data, we demonstrate the critical effects of sulfur vacancies and their pairings with vanadium atoms on the magnetic ordering in V-doped MoS2 (V-MoS2) monolayers. Additionally, we fabricated a series of field effect transistors on these V-MoS2 monolayers and observed the emergence of p-type behavior as the vanadium concentration increased. Our study sheds light on the origin of ferromagnetism in V-MoS2 monolayers and provides a foundation for future research on defect engineering to tune the electronic and magnetic properties of atomically thin TMD-based DMSs.

cond-mat.mtrl-sci↗

arXiv2024

Large-population asymptotics for the maximum of diffusive particles with mean-field interaction in the noises

We study the $N \to \infty$ limit of the normalized largest component in some systems of $N$ diffusive particles with mean-field interaction. By applying a universal time change, the interaction in noises is transferred to the drift terms, and the asymptotic behavior of the maximum becomes well-understood due to existing results in the literature. We expect that the normalized maximum in the original setting has the same limiting distribution as that of i.i.d copies of a solution to the corresponding McKean-Vlasov SDE and we present some results and numerical simulations that support this conjecture.

math.PR↗

arXiv2023

Entropy estimators for Markovian sequences: A comparative analysis

Entropy estimation is a fundamental problem in information theory that has applications in various fields, including physics, biology, and computer science. Estimating the entropy of discrete sequences can be challenging due to limited data and the lack of unbiased estimators. Most existing entropy estimators are designed for sequences of independent events and their performance vary depending on the system being studied and the available data size. In this work we compare different entropy estimators and their performance when applied to Markovian sequences. Specifically, we analyze both binary Markovian sequences and Markovian systems in the undersampled regime. We calculate the bias, standard deviation and mean squared error for some of the most widely employed estimators. We discuss the limitations of entropy estimation as a function of the transition probabilities of the Markov processes and the sample size. Overall, this paper provides a comprehensive comparison of entropy estimators and their performance in estimating entropy for systems with memory, which can be useful for researchers and practitioners in various fields.

cond-mat.stat-mech↗

arXiv2023

Characterizing and Mitigating Timing Noise-Induced Decoherence in Single Electron Sources

Identifying and controlling decoherence in single electron sources (SES) is important for their applications in quantum information processing. The recent experiments with ultrashort electron pulses [J. D. Fletcher et al., Nat. Commun. 10, 5298 (2019)] demonstrate strong decoherence that cannot be caused by traditional mechanisms such as electron-electron or electron-phonon interactions. Here we propose timing noise as a universal model, consistent with existing experimental data, to explain strong decoherence of ultrafast SES pulses, without resorting to any specific microscopic mechanism for such decoherence. We also propose a protocol to filter out timing noise which works even in the presence of other decoherence effects, such as those present in, e.g., low-energy SESs.

cond-mat.mes-hall↗

arXiv2023

Language dynamics within adaptive networks: An agent-based approach of nodes and links coevolution

Motivated by the dramatic disappearance of endangered languages observed in recent years, a great deal of attention has been given to the modeling of language competition in order to understand the factors that promote the disappearance of a language and its unfolding dynamics. With this in mind, we build on existing network models of language competition in bilingual societies. These models deal with the interplay between the usage of a language (link state) and the preference or attitude of the speakers towards the language (node state). In this work, we allow for the case where agents have the freedom to adapt their local interactions in accordance with their language preference. This is modeled by introducing a local rewiring mechanism triggered by the dissatisfaction of an agent with its usage of a given language. Our numerical simulations show that permitting this freedom to agents likely results in linguistically segregated communities for small network sizes. However, for networks of sufficiently large size, the extinction of one of the languages is the most probable scenario. Furthermore, we analyze how the fraction of minority speakers changes with the system size and we find that this fraction grows as the total population increases, which is consistent with existing data. Overall, the results of this work help us understand the impact of speakers' preferences and choices in the complex language landscape of bilingual societies.

physics.soc-ph↗

arXiv2023

Sulfur Vacancy Related Optical Transitions in Graded Alloys of MoxW1-xS2 Monolayers

Engineering the electronic bandgap is of utmost importance in diverse domains ranging from information processing and communication technology to sensing and renewable energy applications. Transition metal dichalcogenides (TMDCs) provide an ideal platform for achieving this goal through techniques including alloying, doping, and creating in-plane or out-of-plane heterostructures. Here, we report on the synthesis and characterization of atomically controlled two-dimensional graded alloy of MoxW1-xS2, wherein the center region is Mo rich and gradually transitions towards a higher concentration of W atoms at the edges. This unique alloy structure leads to a continuously tunable bandgap, ranging from 1.85 eV in the center to 1.95 eV at the edges consistent with the larger band gap of WS2 relative to MoS2. Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy showed the presence of sulfur monovacancy, VS, whose concentration varied across the graded MoxW1-xS2 layer as a function of Mo content with the highest value in the Mo rich center region. Optical spectroscopy measurements supported by ab initio calculations reveal a doublet electronic state of VS, which was split due to the spin-orbit interaction, with energy levels close to the conduction band or deep in the band gap depending on whether the vacancy is surrounded by W atoms or Mo atoms. This unique electronic configuration of VS in the alloy gave rise to four spin-allowed optical transitions between the VS levels and the valence bands. Our work highlights the potential of simultaneous defect and optical engineering of novel devices based on these 2D monolayers.

cond-mat.mtrl-sci↗

arXiv2023

Modeling language ideologies for the dynamics of languages in contact

In multilingual societies, it is common to encounter different language varieties. Various approaches have been proposed to discuss different mechanisms of language shift. However, current models exploring language shift in languages in contact often overlook the influence of language ideologies. Language ideologies play a crucial role in understanding language usage within a cultural community, encompassing shared beliefs, assumptions, and feelings towards specific language forms. These ideologies shed light on the social perceptions of different language varieties expressed as language attitudes. In this study, we introduce an approach that incorporates language ideologies into a model for contact varieties by considering speaker preferences as a parameter. Our findings highlight the significance of preference in language shift, which can even outweigh the influence of language prestige associated, for example, with a standard variety. Furthermore, we investigate the impact of the degree of interaction between individuals holding opposing preferences on the language shift process. Quite expectedly, our results indicate that when communities with different preferences mix, the coexistence of language varieties becomes less likely. However, variations in the degree of interaction between individuals with contrary preferences notably lead to non-trivial transitions from states of coexistence of varieties to the extinction of a given variety, followed by a return to coexistence, ultimately culminating in the dominance of the previously extinct variety. By studying finite-size effects, we observe that the duration of coexistence states increases exponentially with network size. Ultimately, our work constitutes a quantitative approach to the study of language ideologies in sociolinguistics.

physics.soc-ph↗

arXiv2023

Superconductor-quantum dot hybrid coolers

We propose a refrigeration scheme in a mesoscopic superconductor-quantum dot hybrid device. The setup can significantly cool down a normal metal coupled to the device by applying a bias voltage across the system. We demonstrate that the cooling power can be as large as 0.05$\Delta_0^2/h$ where $\Delta_0$ is the absolute value of superconducting order parameter. In contrast to previous proposals, our device operates without any magnetic elements such as ferromagnetic reservoirs or Zeeman splittings. The refrigeration scheme works over a broad parameter range and can be optimized by tuning system parameters such as level position and bias voltage. Our theory self-consistently determines the temperature drop of the normal reservoir in the nonlinear transport regime including electron-electron interactions at the mean field level. Finally, we evaluate the refrigeration performance and find efficiencies as large as half of the Carnot bound for realistic values of the coupling strength.

cond-mat.mes-hall↗