Showing 1–50 of 844 results for author: Alves, A

Angular analysis of the decay ${\it Λ}_{\it b}^{0} \to {\it Λ}(1520){\it μ^{+}μ^{-}}$

Authors: LHCb collaboration, R. Aaij, M. Abdelfatah, A. S. W. Abdelmotteleb, C. Abellan Beteta, F. Abudinén, T. Ackernley, A. A. Adefisoye, B. Adeva, M. Adinolfi, P. Adlarson, C. Agapopoulou, C. A. Aidala, S. Akar, K. Akiba, H. Al Saleh, P. Albicocco, J. Albrecht, R. Aleksiejunas, F. Alessio, P. Alvarez Cartelle, A. A. Alves Jr, S. Amato, J. L. Amey, Y. Amhis , et al. (1167 additional authors not shown)

Abstract: The first angular analysis of ${\it Λ}_{\it b}^{0} \to {\it Λ}(1520){\it μ^{+}μ^{-}}$ decays is presented, using proton-proton collision data collected with the LHCb detector between 2011 and 2018, corresponding to an integrated luminosity of 9 fb$^{-1}$. The leptonic forward-backward asymmetry, $A_\text{FB, 3/2}^\ell$, and the $CP$-averaged angular observable, $S_{1cc}$, are determined by fitting… ▽ More The first angular analysis of ${\it Λ}_{\it b}^{0} \to {\it Λ}(1520){\it μ^{+}μ^{-}}$ decays is presented, using proton-proton collision data collected with the LHCb detector between 2011 and 2018, corresponding to an integrated luminosity of 9 fb$^{-1}$. The leptonic forward-backward asymmetry, $A_\text{FB, 3/2}^\ell$, and the $CP$-averaged angular observable, $S_{1cc}$, are determined by fitting projections of the angular distributions in four intervals of the square of the dimuon invariant mass between 0.1 and 12.5 GeV$^2/c^4$. The results are in good agreement with predictions based on the Standard Model of particle physics. △ Less

Submitted 21 August, 2026; originally announced August 2026.

Comments: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lhcb-glance.cern.ch/alcm/public/analysis/full-details/6206/ (LHCb public pages)

Report number: LHCb-PAPER-2026-037, CERN-EP-2026-240

Integrated Framework for Long-term Elective Surgery Management under Uncertainty: From Strategic to Tactical Planning

Authors: Joao P. F. da Silva, Lucas Bortoletto, Rafael C. S. Schouery, Edilson F. Arruda, Fabricio F. Santos, Ana Paula C. I. Alves

Abstract: In public healthcare systems, elective surgery waiting lists are a persistent management challenge, as hospitals must balance limited operating theatre capacity with uncertain and evolving demand. Long-term planning for these lists requires more than assigning operating theatre (OT) time to medical specialities, as isolated allocation decisions may fail to stabilise waiting lists over time. Such p… ▽ More In public healthcare systems, elective surgery waiting lists are a persistent management challenge, as hospitals must balance limited operating theatre capacity with uncertain and evolving demand. Long-term planning for these lists requires more than assigning operating theatre (OT) time to medical specialities, as isolated allocation decisions may fail to stabilise waiting lists over time. Such planning must account for uncertainty in patient arrivals in the queue and surgery durations, which are often neglected in OT scheduling models. In this context, we propose a novel integrated framework for elective surgery management under uncertainty, linking strategic queue-control decisions with tactical OT scheduling. The framework combines three components: (i) a closed-loop control policy that determines the number of patients to schedule in each planning cycle; (ii) a model to account for overtime-related cancellation risks; and (iii) a mixed-integer linear programming formulation, informed by the previous components, to solve an OT Scheduling Problem. The resulting tactical schedules are therefore guided by the long-term evolution of speciality-specific queues and by cancellation-risk considerations. We evaluate the proposed framework through a case study at University Hospital Unicamp, a large Brazilian public referral hospital. The results show that integrating strategic and tactical decisions stabilises waiting lists, controls cancellation risks, and supports more transparent theatre-allocation decisions, while remaining computationally efficient for practical implementation. △ Less

Submitted 28 July, 2026; originally announced July 2026.

MSC Class: 60; 90 ACM Class: G.2; G.3; J.3

Harnessing Machine Learning for Hybrid Constitutive Modelling of Viscoelastic Fluid Flows in Computational Rheology

Authors: J. L. Cummings, C. Fernandes, F. Dong, M. A. Alves, M. S. N. Oliveira

Abstract: Recent advances in data-driven modelling have highlighted the potential of hybrid approaches which combine Tensor Basis Neural Networks (TBNN) with Universal Differential Equations (UDE) to discover frame-invariant, non-linear viscoelastic constitutive models. These hybrid models enable the creation of digital twins for complex viscoelastic fluids, offering direct transferability to computational… ▽ More Recent advances in data-driven modelling have highlighted the potential of hybrid approaches which combine Tensor Basis Neural Networks (TBNN) with Universal Differential Equations (UDE) to discover frame-invariant, non-linear viscoelastic constitutive models. These hybrid models enable the creation of digital twins for complex viscoelastic fluids, offering direct transferability to computational fluid dynamics simulations. In this work, we introduce a reduced dimensional tensor basis formulation that enhances both the physical consistency of the learned representations with respect to the training data and the numerical stability of subsequent simulations. The UDE architecture is embedded into an open-source finite volume solver in which the constitutive response is generated dynamically at runtime based on local fluid flow conditions. Training on synthetic datasets generated using a range of well established viscoelastic models in oscillatory shear flows alone, the performance of the resulting UDEs is evaluated under extrapolation to unseen conditions and flow-types. These include deploying the UDEs in viscometric extensional flows as well as 2D and 3D benchmark flows, such as the 4:1 sudden contraction and cross-slot, providing a quantitative analysis of their capabilities, limitations and failure modes. The proposed reduced-basis framework enables data-efficient discovery of frame-invariant constitutive models that generalise beyond their training regime, capturing key flow features such as the onset and growth of flow-induced elastic instabilities in strong extensional flows even though trained solely on shear data. Quantitative accuracy decreases as extrapolation increases, but incorporating first normal stress difference information further improves quantitative accuracy and extends predictive fidelity to higher Deborah numbers. △ Less

Submitted 16 July, 2026; originally announced July 2026.

Comments: 33 pages

Biological Sex Determination in Cadavers Using Deep Learning Algorithms from Computed Tomography Images of Pelvis and Skull

Authors: Giovanna Herculano Tormena, Davi Nascimento Araújo, Germano Coimbra Soares de Carvalho, Gustavo Bruno Centenaro, Rafael Janowski Pozzer, Rodrigo Akira Azevedo Kurosawa, Danilo Aires Alves, Filipe Thiago Xavier de Campos, Pedro Henrique Macedo dos Santos, Pedro Augusto Prado Mota, Ricardo V. Godoy, João Manoel Herrera Pinheiro, Marcelo Becker

Abstract: Sexual identification of decomposed cadavers challenges traditional methods dependent on visual anthropological analysis. This study evaluates state-of-the-art deep learning (including YOLO26, YOLO11, ConvNeXt-Tiny, EfficientNetV2, ViT-B16, VGG16, and ResNet50) with transfer learning to automatically determine biological sex from forensic computed tomography (CT) scans. We analyzed 141 autopsied c… ▽ More Sexual identification of decomposed cadavers challenges traditional methods dependent on visual anthropological analysis. This study evaluates state-of-the-art deep learning (including YOLO26, YOLO11, ConvNeXt-Tiny, EfficientNetV2, ViT-B16, VGG16, and ResNet50) with transfer learning to automatically determine biological sex from forensic computed tomography (CT) scans. We analyzed 141 autopsied cadavers from the Forensic Medical Institute of Goiânia-GO, including a broad age range and varying conditions of preservation. The three-dimensional reconstructions of the pelvis and skull were converted into standardized two-dimensional profile projections, contributing to the study of this new technical approach. Data augmentation techniques compensated for sample limitations. Two scenarios were validated: binary and quaternary classification (one class per sex vs. one class per anatomical region of each sex). The best-performing model achieved highly consistent results on the pelvis region and still satisfactory performance on the skull region, reaching an overall patient-level accuracy of 95.65%, recall of 92.86%, F1- score of 94.36%, and precision of 97.22%, maintaining consistent performance across the evaluated cases, including those with trauma-related artifacts. Results indicate the technical feasibility of the methodology, demonstrating that deep learning models can provide objective, high-speed skeletal analysis. Since the study was conducted using data from a single institution and a single computed tomography scanner, further validation across multiple centers and scanners is required to assess the generalizability of the proposed approach △ Less

Submitted 21 June, 2026; originally announced June 2026.

Comments: 16 pages

A Research Agenda on Agents and Software Engineering: Outcomes from the Rio A2SE Seminar

Authors: Davide Taibi, Henry Muccini, Karthik Vaidhyanathan, Marcos Kalinowski, Michele Albano, Antonio Pedro Santos Alves, Renato Cerqueira, Mateus Devino, Matteo Esposito, Rodrigo Falcão, Vinicius Henning, Foutse Khomh, Valentina Lenarduzzi, Qinghua Lu, Matías Martínez, Henrique Mello, Daniel Mendez, Lucas Romao

Abstract: The rise of agentic AI is reshaping software engineering in two intertwined directions: agents are increasingly applied to support software engineering tasks, and Agentic AI systems themselves are complex systems that require re-thinking currently established software engineering practices. To chart a coherent research agenda covering the two directions, we organized the A2SE seminar in Rio de Jan… ▽ More The rise of agentic AI is reshaping software engineering in two intertwined directions: agents are increasingly applied to support software engineering tasks, and Agentic AI systems themselves are complex systems that require re-thinking currently established software engineering practices. To chart a coherent research agenda covering the two directions, we organized the A2SE seminar in Rio de Janeiro, bringing together 18 experts from academia and industry. Through structured presentations, collaborative topic clustering, and focused group discussions, participants identified six thematic areas: Governance, Software Engineering for Agents, Agents for Software Architecture, Quality and Evaluation, Sustainability, and Code, and they prioritized short-term and long-term research directions for each. This paper presents the resulting community-driven, opinionated research agenda, offering the SE community a structured foundation for coordinating efforts at this critical juncture. △ Less

Submitted 12 May, 2026; originally announced May 2026.

Comments: 6 pages, 1 table, A2SE meeting, https://sites.google.com/view/a2se2026/home

A UEFI System with SPDM to Protect Against Unauthorized Device Connections

Authors: Ágatha de Freitas, Marcos A. Simplicio Jr, Bruno C. Albertini, Renan C. A. Alves

Abstract: Attackers willing to compromise computing systems can use malicious peripherals as an attack vector, threatening users that cannot verify the hardware's authenticity. To address this problem, our work uses the Security Protocol and Data Model to propose a UEFI system capable of authenticating PCIe and USB devices trying to connect with it. We also develop an open source proof-of-concept using emul… ▽ More Attackers willing to compromise computing systems can use malicious peripherals as an attack vector, threatening users that cannot verify the hardware's authenticity. To address this problem, our work uses the Security Protocol and Data Model to propose a UEFI system capable of authenticating PCIe and USB devices trying to connect with it. We also develop an open source proof-of-concept using emulation to evaluate and illustrate our proposal, which is capable of restricting the devices' connections to only those allowed, thus protecting the system against malicious peripherals. Then, using kernel virtualization features to evaluate the emulation, we collect the number of instructions and CPU cycles during boot. Our experiments reveal that, during firmware execution, the number of instructions and the number of CPU cycles increased respectively 13% and 8% on average. This processing overhead is acceptable in view of enhanced security. Institutions requiring high security levels can leverage our proof-of-concept to tailor their own system based on their own requirements. △ Less

Submitted 7 May, 2026; originally announced May 2026.

Comments: 11 pages, 4 figures

Taking a Pulse on How Generative AI is Reshaping the Software Engineering Research Landscape

Authors: Bianca Trinkenreich, Fabio Calefato, Kelly Blincoe, Viggo Tellefsen Wivestad, Antonio Pedro Santos Alves, Júlia Condé Araújo, Marina Condé Araújo, Paolo Tell, Marcos Kalinowski, Thomas Zimmermann, Margaret-Anne Storey

Abstract: Context: Software engineering (SE) researchers increasingly study Generative AI (GenAI) while also incorporating it into their own research practices. Despite rapid adoption, there is limited empirical evidence on how GenAI is used in SE research and its implications for research practices and governance. Aims: We conduct a large-scale survey of 457 SE researchers publishing in top venues between… ▽ More Context: Software engineering (SE) researchers increasingly study Generative AI (GenAI) while also incorporating it into their own research practices. Despite rapid adoption, there is limited empirical evidence on how GenAI is used in SE research and its implications for research practices and governance. Aims: We conduct a large-scale survey of 457 SE researchers publishing in top venues between 2023 and 2025. Method: Using quantitative and qualitative analyses, we examine who uses GenAI and why, where it is used across research activities, and how researchers perceive its benefits, opportunities, challenges, risks, and governance. Results: GenAI use is widespread, with many researchers reporting pressure to adopt and align their work with it. Usage is concentrated in writing and early-stage activities, while methodological and analytical tasks remain largely human-driven. Although productivity gains are widely perceived, concerns about trust, correctness, and regulatory uncertainty persist. Researchers highlight risks such as inaccuracies and bias, emphasize mitigation through human oversight and verification, and call for clearer governance, including guidance on responsible use and peer review. Conclusion: We provide a fine-grained, SE-specific characterization of GenAI use across research activities, along with taxonomies of GenAI use cases for research and peer review, opportunities, risks, mitigation strategies, and governance needs. These findings establish an empirical baseline for the responsible integration of GenAI into academic practice. △ Less

Submitted 13 April, 2026; originally announced April 2026.

CORSIKA 8: A General Framework for Particle Cascade Simulations

Authors: J. M. Alameddine, J. Albrecht, A. A Alves Jr., J. Ammerman-Yebra, L. Arrabito, D. Baack, A. Coleman, C. Deaconu, H. Dembinski, D. Elsässer, R. Engel, A. Faure, A. Ferrari, C. Gaudu, C. Glaser, M. Gottowik, D. Heck, T. Huege, K. H. Kampert, N. Karastathis, J. Lazar, L. Nellen, D. Parello, T Pierog, R. Prechelt , et al. (12 additional authors not shown)

Abstract: The simulation of extensive air showers and particle cascades in general is a cornerstone of modern astroparticle physics. For more than two decades, CORSIKA, currently in version 7, has been one of the most widely used tools for this purpose. However, its architecture reflects design constraints of an earlier computing era, as well as increasingly limiting extensibility, maintainability, and adap… ▽ More The simulation of extensive air showers and particle cascades in general is a cornerstone of modern astroparticle physics. For more than two decades, CORSIKA, currently in version 7, has been one of the most widely used tools for this purpose. However, its architecture reflects design constraints of an earlier computing era, as well as increasingly limiting extensibility, maintainability, and adaptability to modern experimental requirements. CORSIKA 8 is a complete redesign of the original CORSIKA code, implemented in modern C++ and based on contemporary software engineering principles. It introduces a modular and extensible simulation framework with explicit handling of units, flexible geometry, and environment descriptions. In this paper, we present the design philosophy and core architecture of CORSIKA 8, describe the implementation of electromagnetic and hadronic shower physics, and validate air shower simulations against CORSIKA 7. The results demonstrate good agreement at the few-percent level for key observables, confirming the physics fidelity of CORSIKA 8. We also showcase new use cases that were beyond the capabilities of version 7, such as the simulation of cross-media showers and particle cascades in ice, including radio-signal propagation △ Less

Submitted 8 July, 2026; v1 submitted 2 April, 2026; originally announced April 2026.

Comments: 29 pages, 21 figures

Journal ref: Astroparticle Physics 182 (2026) 103265

A chaotic flux cipher based on the random cubic family $f_{c_n}(z)=z^3+c_n z$

Authors: Pouya Mehdipour, Alexandre Miranda Alves, Gerardo Honorato, Mostafa Salarinoghabi

Abstract: This paper presents a symmetric stream cipher that utilizes the dynamic properties of random cubic mappings in the complex plane to generate pseudo-random key streams. The system is based on the iterations of the random cubic polynomial $f_n(z)=z^3+c_n z$, where the parameters $c_n$ are chosen randomly from a disc of radius $δ$ and with center at the origin, aiming to improve the chaotic behaviour… ▽ More This paper presents a symmetric stream cipher that utilizes the dynamic properties of random cubic mappings in the complex plane to generate pseudo-random key streams. The system is based on the iterations of the random cubic polynomial $f_n(z)=z^3+c_n z$, where the parameters $c_n$ are chosen randomly from a disc of radius $δ$ and with center at the origin, aiming to improve the chaotic behaviour and, consequently, the randomness of the generated sequence. The stability of the Julia set under small parameter perturbations, when $δ< δ_0\simeq 0.89$, is considered to ensure key consistency in noisy environments, such as 5G networks. On the other hand, for $δ> 3$, the system exhibits instability and chaos, ideal for generating ultra-secure keys. The Python implementation integrates secure key derivation, robust key stream generation via warmed-up iteration, and an authenticated encryption scheme using the modern cryptographic primitives (\texttt{HKDF} and\texttt{HMAC-SHA-256}), to ensure message integrity and authenticity. Statistical analyses, including chi-square test and entropy calculation, are performed on the output of the key stream generator to evaluate its randomness and distribution. In addition, a complete statistical validation, compliant with \texttt{NIST SP 800-22} standards in modern cryptography, was performed to enhance the proposed system's credibility. △ Less

Submitted 21 March, 2026; originally announced March 2026.

Random Dynamics of a Family of Cubic Polynomials

Authors: Alexandre Miranda Alves, Gerardo Andrés Honorato Gutiérrez, Mostafa Salarinoghabi

Abstract: In this work, we study the non-autonomous dynamics generated by random iterations of the cubic family of the form $z^3 + cz$. The parameter sequence is chosen randomly from a bounded Borel subset of $\mathbb{C}$. We investigate topological properties of the corresponding Julia sets, with particular emphasis on conditions leading to total disconnectedness. We prove that the set of parameter sequenc… ▽ More In this work, we study the non-autonomous dynamics generated by random iterations of the cubic family of the form $z^3 + cz$. The parameter sequence is chosen randomly from a bounded Borel subset of $\mathbb{C}$. We investigate topological properties of the corresponding Julia sets, with particular emphasis on conditions leading to total disconnectedness. We prove that the set of parameter sequences for which the Julia set is totally disconnected is dense in the parameter space. We also construct examples where the Julia set is totally disconnected but the associated non-autonomous system is not hyperbolic. Finally, under suitable probabilistic assumptions on the parameter distribution, we show that almost every sequence produces a totally disconnected Julia set. △ Less

Submitted 10 March, 2026; originally announced March 2026.

Comments: 24 pages, 3 figures

MSC Class: 30D05; 37F10; 37F12

Using thermodynamics to learn gravitational wave physics

Authors: Caio César Rodrigues Evangelista, Níckolas de Aguiar Alves

Abstract: Black holes are some of the most interesting objects in the universe. While they first arise in the complicated behavior of general relativity, the physical laws ruling their behavior are surprisingly simple. For example, one of the core facts about black holes is that their area never decreases, much like the entropy in thermodynamics. In this note directed at introductory physics students and th… ▽ More Black holes are some of the most interesting objects in the universe. While they first arise in the complicated behavior of general relativity, the physical laws ruling their behavior are surprisingly simple. For example, one of the core facts about black holes is that their area never decreases, much like the entropy in thermodynamics. In this note directed at introductory physics students and their instructors, we use this similarity to understand properties of black hole physics using standard techniques from an undergraduate course in thermal physics. We explore the never-decreasing nature of black hole area to obtain bounds on the energy emitted in a black hole merger (a calculation originally done by Hawking). We show how this allows us to think of black holes in manners very similar to heat engines, and how these ideas have been used in modern gravitational wave observatories to test general relativity. This allows a research-level topic to be discussed in introductory physics lectures. △ Less

Submitted 9 March, 2026; v1 submitted 23 February, 2026; originally announced February 2026.

Comments: 7 pages, 3 figures. To appear in European Journal of Physics. v2: updated bibliography, minor changes

Journal ref: Eur. J. Phys 47 (2), 025604 (2026)

Statistical Confidence in Functional Correctness: An Approach for AI Product Functional Correctness Evaluation

Authors: Wallace Albertini, Marina Condé Araújo, Júlia Condé Araújo, Antonio Pedro Santos Alves, Marcos Kalinowski

Abstract: The quality assessment of Artificial Intelligence (AI) systems is a fundamental challenge due to their inherently probabilistic nature. Standards such as ISO/IEC 25059 provide a quality model, but they lack practical and statistically robust methods for assessing functional correctness. This paper proposes and evaluates the Statistical Confidence in Functional Correctness (SCFC) approach, which se… ▽ More The quality assessment of Artificial Intelligence (AI) systems is a fundamental challenge due to their inherently probabilistic nature. Standards such as ISO/IEC 25059 provide a quality model, but they lack practical and statistically robust methods for assessing functional correctness. This paper proposes and evaluates the Statistical Confidence in Functional Correctness (SCFC) approach, which seeks to fill this gap by connecting business requirements to a measure of statistical confidence that considers both the model's average performance and its variability. The approach consists of four steps: defining quantitative specification limits, performing stratified and probabilistic sampling, applying bootstrapping to estimate a confidence interval for the performance metric, and calculating a capability index as a final indicator. The approach was evaluated through a case study on two real-world AI systems in industry involving interviews with AI experts. Valuable insights were collected from the experts regarding the utility, ease of use, and intention to adopt the methodology in practical scenarios. We conclude that the proposed approach is a feasible and valuable way to operationalize the assessment of functional correctness, moving the evaluation from a point estimate to a statement of statistical confidence. △ Less

Submitted 20 February, 2026; originally announced February 2026.

Comments: Author version of the paper accepted for publication at CAIN 2026

Four-point functions with fractional R-symmetry excitations in the D1-D5 CFT

Authors: V. A. Souza Alves, Andre Alves Lima, G. M. Sotkov, M. Stanishkov

Abstract: We study correlation functions with fractional-mode excitations of the R-symmetry currents in D1-D5 CFT. We show how fractional-mode excitations lift to the covering surface associated with correlation functions as a specific sum of integer-mode excitations, with coefficients that can be determined exactly from the covering map in terms of Bell polynomials. We consider the four-point functions of… ▽ More We study correlation functions with fractional-mode excitations of the R-symmetry currents in D1-D5 CFT. We show how fractional-mode excitations lift to the covering surface associated with correlation functions as a specific sum of integer-mode excitations, with coefficients that can be determined exactly from the covering map in terms of Bell polynomials. We consider the four-point functions of fractional excitations of two chiral/anti-chiral NS fields, Ramond ground states and the twist-two scalar modulus deformation operator that drives the CFT away from the free point. We derive explicit formulas for classes of these functions with twist structures $(n)$-$(2)$-$(2)$-$(n)$ and $(n_1)(n_2)$-$(2)$-$(2)$-$(n_1)(n_2)$, the latter involving double-cycle fields. The final answer for the four-point functions always depends only on the lift of the base-space cross-ratio. We discuss how this relates to Hurwitz blocks associated with different conjugacy classes of permutations, the corresponding OPE channels and fusion rules. △ Less

Submitted 9 February, 2026; originally announced February 2026.

Comments: 50 pages

Multiscale Mechanical Response of 3D-Printed Diamondiynes: From Movable Interlocked Lattices to Architected Metamaterials

Authors: Anitesh Kumar Singh, Rodrigo A. F. Alves, Tapas Pal, Sarmistha Bora, Hugo X. Rodrigues, Emanuel J. A. dos Santos, Camila de L. Ribeiro, Alysson M. A. Silva, Luiz A. Ribeiro Júnior, Douglas S. Galvão, Chandra Sekhar Tiwary

Abstract: Diamondynes are a recently synthesized three-dimensional carbon allotrope, with interlocked and movable sublattices that introduce deformation modes not present in standard architected materials. Here, we report the first multiscale mechanical assessment of Diamondiyne-derived architectures by combining quasi-static compression of 3D-printed specimens with reactive molecular dynamics simulations o… ▽ More Diamondynes are a recently synthesized three-dimensional carbon allotrope, with interlocked and movable sublattices that introduce deformation modes not present in standard architected materials. Here, we report the first multiscale mechanical assessment of Diamondiyne-derived architectures by combining quasi-static compression of 3D-printed specimens with reactive molecular dynamics simulations of the corresponding atomic-scale models. We generate four geometries (3F, 2F-SY, 4F, and 2F-USY). All structures resulted in lower density in the range of 0.20-0.38 g.cm^-3. Experiments indicate that the symmetric two-sublattice structure (2F-SY) delivers the best performance, reaching a specific yield strength of 5.91 MPa.g^-1cm^-3 and a specific energy absorption of 279 J.g^-1, whereas 2F-USY architecture yielded the lowest values, with 0.77 MPa.g^-1.cm^-3 and 16 J.g^-1. The 4F geometry provided a specific energy absorption of 254 J.g^-1. The structures deformed through geometric collapse and strut buckling, which was due to diagonal shear in 2F-USY and progressive compaction in 2F-SY and 3F. Molecular dynamics simulations also confirmed these experimental trends and revealed strong directional anisotropy due to the arrangement of interlocked sublattices, with a stiffness of 24.1 GPa along the z-direction in the case of 4F architecture. Overall, Diamondiyne-derived architectures display geometry-dominated mechanical behavior and serve as a promising platform for lightweight, energy-absorbing metamaterials. △ Less

Submitted 27 January, 2026; originally announced February 2026.

Comments: 25 pages, 11 figures

MSC Class: 00-XX ACM Class: I.2; J.6

TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest

Authors: Altino Alves, Andre Hora

Abstract: Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over tim… ▽ More Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be time-consuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy. △ Less

Submitted 4 February, 2026; originally announced February 2026.

Comments: Published at MSR 2025

Testing Framework Migration with Large Language Models

Authors: Altino Alves, João Eduardo Montandon, Andre Hora

Abstract: Python developers rely on two major testing frameworks: \texttt{unittest} and \texttt{Pytest}. While \texttt{Pytest} offers simpler assertions, reusable fixtures, and better interoperability, migrating existing suites from \texttt{unittest} remains a manual and time-consuming process. Automating this migration could substantially reduce effort and accelerate test modernization. In this paper, we i… ▽ More Python developers rely on two major testing frameworks: \texttt{unittest} and \texttt{Pytest}. While \texttt{Pytest} offers simpler assertions, reusable fixtures, and better interoperability, migrating existing suites from \texttt{unittest} remains a manual and time-consuming process. Automating this migration could substantially reduce effort and accelerate test modernization. In this paper, we investigate the capability of Large Language Models (LLMs) to automate test framework migrations from \texttt{unittest} to \texttt{Pytest}. We evaluate GPT 4o and Claude Sonnet 4 under three prompting strategies (Zero-shot, One-shot, and Chain-of-Thought) and two temperature settings (0.0 and 1.0). To support this analysis, we first introduce a curated dataset of real-world migrations extracted from the top 100 Python open-source projects. Next, we actually execute the LLM-generated test migrations in their respective test suites. Overall, we find that 51.5% of the LLM-generated test migrations failed, while 48.5% passed. The results suggest that LLMs can accelerate test migration, but there are often caveats. For example, Claude Sonnet 4 exhibited more conservative migrations (e.g., preserving class-based tests and legacy \texttt{unittest} references), while GPT-4o favored more transformations (e.g., to function-based tests). We conclude by discussing multiple implications for practitioners and researchers. △ Less

Submitted 2 February, 2026; originally announced February 2026.

Comments: Accepted for publication at AST 2026

Topic Modeling in New Physics Detection

Authors: Alexandre Alves, Eduardo da Silva Almeida, Douglas Roberto Pimentel

Abstract: In this work, we apply topic modeling to detect new physics in proton-proton collisions at the LHC in an unsupervised way. We investigate three new physics scenarios where fully leptonic $t\bar{t}\to b\bar{b}\ell^+\ell^-ν_\ell\barν_\ell$ is the main source of background without relying on jet substructure variables. We demonstrate that the algorithm remains effective even in this low-particle mult… ▽ More In this work, we apply topic modeling to detect new physics in proton-proton collisions at the LHC in an unsupervised way. We investigate three new physics scenarios where fully leptonic $t\bar{t}\to b\bar{b}\ell^+\ell^-ν_\ell\barν_\ell$ is the main source of background without relying on jet substructure variables. We demonstrate that the algorithm remains effective even in this low-particle multiplicity framework, complementing jet tagging studies, where it is typically employed. Moreover, we demonstrate that the performance of topic modeling is competitive or even better than well-known outlier detectors, such as isolation forest and variational autoencoders, with moderate and high background pollution in almost all new physics scenarios considered. △ Less

Submitted 15 January, 2026; originally announced January 2026.

Comments: 33 pages, 13 figures, 4 tables

Science Consultant Agent

Authors: Karthikeyan K, Philip Wu, Xin Tang, Alexandre Alves

Abstract: The Science Consultant Agent is a web-based Artificial Intelligence (AI) tool that helps practitioners select and implement the most effective modeling strategy for AI-based solutions. It operates through four core components: Questionnaire, Smart Fill, Research-Guided Recommendation, and Prototype Builder. By combining structured questionnaires, literature-backed solution recommendations, and pro… ▽ More The Science Consultant Agent is a web-based Artificial Intelligence (AI) tool that helps practitioners select and implement the most effective modeling strategy for AI-based solutions. It operates through four core components: Questionnaire, Smart Fill, Research-Guided Recommendation, and Prototype Builder. By combining structured questionnaires, literature-backed solution recommendations, and prototype generation, the Science Consultant Agent accelerates development for everyone from Product Managers and Software Developers to Researchers. The full pipeline is illustrated in Figure 1. △ Less

Submitted 17 December, 2025; originally announced December 2025.

Sound as a gauge theory and its infrared triangle

Authors: Níckolas de Aguiar Alves, André G. S. Landulfo

Abstract: Over the last few decades, a rich structure has been uncovered in the infrared sector of various field theories. This mostly comes through the connections between memory effects, asymptotic symmetries, and soft theorems (the ``infrared triangle''), which have been explored in much depth within high-energy physics. In this paper, we show how sound also admits an infrared triangle. We consider the l… ▽ More Over the last few decades, a rich structure has been uncovered in the infrared sector of various field theories. This mostly comes through the connections between memory effects, asymptotic symmetries, and soft theorems (the ``infrared triangle''), which have been explored in much depth within high-energy physics. In this paper, we show how sound also admits an infrared triangle. We consider the linear perturbations of the Euler equations for a barotropic and irrotational fluid. We then show how low-frequency changes in an acoustic source can lead to lasting displacements of fluid particles. We proceed to write these linear perturbations in terms of a two-form potential -- a Kalb--Ramond field, in the high-energy physics terminology. This phrases linear sound as a gauge theory. Standard techniques can then be used to probe the infrared structure of acoustics. We show how the memory effect relates to asymptotic symmetries in this dual formulation, and comment on how these notions can be connected to soft theorems. This exhibits an example of an infrared triangle in a condensed matter system and provides new pathways to the experimental detection of memory effects. △ Less

Submitted 24 June, 2026; v1 submitted 16 December, 2025; originally announced December 2025.

Comments: 24 pages, 1 figure. v2: improved exposition, updated bibliography

Resistive Plate Chambers and Gaseous Detector Activities in the Brazilian High Energy Physics Community

Authors: Sandro Fonseca de Souza, Gilvan Augusto Alves, Mapse Barroso, Helio Nogima, Felipe Silva, Joao Pedro Gomes Pinheiro, Katherine Maslova Defante, Dalmo Dalto, Mauricio Thiel, Luis Mendes

Abstract: This document presents an overview of the activities of Brazilian groups on gaseous detectors, with emphasis on resistive plate chambers (RPCs) for the CMS experiment at the CERN LHC and related applications. It summarises the design, performance, maintenance and upgrade of the CMS RPC system, including the installation of improved RPCs for the HL-LHC era and the development of alternative, lower-… ▽ More This document presents an overview of the activities of Brazilian groups on gaseous detectors, with emphasis on resistive plate chambers (RPCs) for the CMS experiment at the CERN LHC and related applications. It summarises the design, performance, maintenance and upgrade of the CMS RPC system, including the installation of improved RPCs for the HL-LHC era and the development of alternative, lower-GWP gas mixtures. It also describes local laboratory infrastructures in Brazil for RPC assembly, testing and gas studies, as well as spin-off projects such as the MARTA cosmic-ray detector and applications in medical imaging and muography. It is intended as a living reference to be periodically updated, documenting the contributions of the Brazilian community to RPC technology and its applications. △ Less

Submitted 5 December, 2025; v1 submitted 30 November, 2025; originally announced December 2025.

The PV performance ratio paradox: annual data from large-scale, real-world PV systems show negligible meteorological and technical impact and points to dominant human factors

Authors: Hugo FM Milan, Aline Q Alves, Thatiane AT Souza, Juliana M Galo, Alex SC Maia, Moisés AP Borges, Ciro J Egoavil

Abstract: Performance ratio (PR) is a established measure of efficiency of photovoltaic (PV) systems. While previous research demonstrated the effects of meteorological and technical variables on PR, a gap persists in the literature on which variables strongly influence PR in large-scale, real-world, heterogeneous PV systems. This paper aims to fill this gap, applying data-driven models to PV systems locate… ▽ More Performance ratio (PR) is a established measure of efficiency of photovoltaic (PV) systems. While previous research demonstrated the effects of meteorological and technical variables on PR, a gap persists in the literature on which variables strongly influence PR in large-scale, real-world, heterogeneous PV systems. This paper aims to fill this gap, applying data-driven models to PV systems located in Rondônia State, Brazil, to identify which variables strongly influence annual PR, and, hence, should be the target for optimization. Surprisingly, only negligible effects were found between meteorological and technical variables on annual PR, indicating that human-factors (such as installation, monitoring, and maintenance quality) might have a stronger effect. These findings indicates that, to improve performance of PV systems, policy makers could focus on creating educational programs to teach PV installers and technicians how to properly install, monitor, and maintain modern PV systems. Through estimating the probability density functions of PR, its peak value was found as 78.85% (mean 77.52%, 95% confidence interval of 76.12% to 78.84%, and 95% prediction interval of 58.83% to 92.70%). A map of annual final yield was developed for Rondônia State and can be used by entrepreneurs to quickly and cheaply estimate energy production. △ Less

Submitted 20 November, 2025; originally announced November 2025.

Comments: Paper and supplementary material in the same PDF

The number of spanning trees as an indicator of critical phenomena: When Kirchhoff meets Ising

Authors: Roberto da Silva, Henrique A. Fernandes, Paulo G. Freitas, Sebastian Gonçalves, E. V. Stock, A. Alves

Abstract: Visibility graphs are spatial interpretations of time series. When derived from the time evolution of physical systems, the graphs associated with such series may exhibit properties that can reflect aspects such as ergodicity, criticality, or other dynamical behaviors. It is important to describe how the criticality of a system is manifested in the structure of the corresponding graphs or, in a pa… ▽ More Visibility graphs are spatial interpretations of time series. When derived from the time evolution of physical systems, the graphs associated with such series may exhibit properties that can reflect aspects such as ergodicity, criticality, or other dynamical behaviors. It is important to describe how the criticality of a system is manifested in the structure of the corresponding graphs or, in a particular way, in the spectra of certain matrices constructed from them. In this paper, we show how the critical behavior of an Ising spin system manifests in the spectra of the adjacency and Laplacian matrices constructed from an ensemble of time evolutions simulated via Monte Carlo (MC) Markov Chains, even for small systems and short MC steps. In particular, we show that the number of spanning trees -- or its logarithm -- , which represents a kind of \emph{structural entropy} or \emph{topological complexity} here obtained from Kirchhoff's theorem, can, in an alternative way, describe the criticality of the spin system. These findings parallel those obtained from the spectra of correlation matrices, which similarly encode signatures of critical and chaotic behavior. △ Less

Submitted 10 November, 2025; v1 submitted 9 November, 2025; originally announced November 2025.

Comments: 7 pages, 4 figures

User Misconceptions of LLM-Based Conversational Programming Assistants

Authors: Gabrielle O'Brien, Antonio Pedro Santos Alves, Sebastian Baltes, Grischa Liebel, Mircea Lungu, Marcos Kalinowski

Abstract: Programming assistants powered by large language models (LLMs) have become widely available, with conversational assistants like ChatGPT particularly accessible to novice programmers. However, varied tool capabilities and inconsistent availability of extensions (web search, code execution, retrieval-augmented generation) create opportunities for user misconceptions that may lead to over-reliance,… ▽ More Programming assistants powered by large language models (LLMs) have become widely available, with conversational assistants like ChatGPT particularly accessible to novice programmers. However, varied tool capabilities and inconsistent availability of extensions (web search, code execution, retrieval-augmented generation) create opportunities for user misconceptions that may lead to over-reliance, unproductive practices, or insufficient quality control. We characterize misconceptions that users of conversational LLM-based assistants may have in programming contexts through a two-phase approach: first brainstorming and cataloging potential misconceptions, then conducting qualitative analysis of Python-programming conversations from the WildChat dataset. We find evidence that users have misplaced expectations about features like web access, code execution, and non-text outputs. We also note the potential for deeper conceptual issues around information requirements for debugging, validation, and optimization. Our findings reinforce the need for LLM-based tools to more clearly communicate their capabilities to users and empirically ground aspects that require clarification in programming contexts. △ Less

Submitted 26 February, 2026; v1 submitted 29 October, 2025; originally announced October 2025.

Comments: Accepted to the Journal Ahead Workshop at ICSE '26

Deep Learning of the Biswas-Chatterjee-Sen Model

Authors: J. F. Silva Neto, D. S. M. Alencar, L. T. Brito, G. A. Alves, F. W. S. Lima, A. Macedo-Filho, R. S. Ferreira, T. F. A. Alves

Abstract: We investigate the critical properties of kinetic continuous opinion dynamics using deep learning techniques. The system consists of $N$ continuous spin variables in the interval $[-1,1]$. Dense neural networks are trained on spin configuration data generated via kinetic Monte Carlo simulations, accurately identifying the critical point on both square and triangular lattices. Classical unsupervise… ▽ More We investigate the critical properties of kinetic continuous opinion dynamics using deep learning techniques. The system consists of $N$ continuous spin variables in the interval $[-1,1]$. Dense neural networks are trained on spin configuration data generated via kinetic Monte Carlo simulations, accurately identifying the critical point on both square and triangular lattices. Classical unsupervised learning with principal component analysis reproduces the magnetization and allows estimation of critical exponents. Additionally, variational autoencoders are implemented to study the phase transition through the loss function, which behaves as an order parameter. A correlation function between real and reconstructed data is defined and found to be universal at the critical point. △ Less

Submitted 23 October, 2025; v1 submitted 10 October, 2025; originally announced October 2025.

Comments: 11 pages, 8 figures. arXiv admin note: text overlap with arXiv:2509.14155

Supervised and Unsupervised Deep Learning Applied to the Majority Vote Model

Authors: J. F. Silva Neto, D. S. M. Alencar, L. T. Brito, G. A. Alves, F. W. S. Lima, A. Macedo-Filho, R. S. Ferreira, T. F. A. Alves

Abstract: We employ deep learning techniques to investigate the critical properties of the continuous phase transition in the majority vote model. In addition to deep learning, principal component analysis is utilized to analyze the transition. For supervised learning, dense neural networks are trained on spin configuration data generated via the kinetic Monte Carlo method. Using independently simulated con… ▽ More We employ deep learning techniques to investigate the critical properties of the continuous phase transition in the majority vote model. In addition to deep learning, principal component analysis is utilized to analyze the transition. For supervised learning, dense neural networks are trained on spin configuration data generated via the kinetic Monte Carlo method. Using independently simulated configuration data, the neural network accurately identifies the critical point on both square and triangular lattices. Classical unsupervised learning with principal component analysis reproduces the magnetization and enables estimation of critical exponents, typically obtained via Monte Carlo importance sampling. Furthermore, deep unsupervised learning is performed using variational autoencoders, which reconstruct input spin configurations and generate artificial outputs. The autoencoders detect the phase transition through the loss function, quantifying the preservation of essential data features. We define a correlation function between the real and reconstructed data, and find that this correlation function is universal at the critical point. Variational autoencoders also serve as generative models, producing artificial spin configurations. △ Less

Submitted 23 October, 2025; v1 submitted 17 September, 2025; originally announced September 2025.

Comments: 11 pages, 9 figures

Observing Double Higgs Production at the LHC via Neutrino Feature Engineering in $hh\to b\bar{b}\ell\ellνν$

Authors: Alexandre Alves, Eduardo da Silva Almeida, Diego S. V. Gonçalves

Abstract: Double Higgs production is challenging even at the High Luminosity LHC. The Standard Model (SM) $hh\to b\bar{b}WW(ZZ)\to b\bar{b}\ell\ellνν$ has a moderate cross section compared to other decay modes, but its backgrounds, mainly top quark pairs and Drell-Yan production, are overwhelming. In this work, we propose new kinematic features designed to improve the discrimination of double Higgs pairs, i… ▽ More Double Higgs production is challenging even at the High Luminosity LHC. The Standard Model (SM) $hh\to b\bar{b}WW(ZZ)\to b\bar{b}\ell\ellνν$ has a moderate cross section compared to other decay modes, but its backgrounds, mainly top quark pairs and Drell-Yan production, are overwhelming. In this work, we propose new kinematic features designed to improve the discrimination of double Higgs pairs, in the $b\bar{b}\ell\ellνν$ channel, with cut-based and multivariate analyses. The new features are built with the neutrinos' momenta solutions obtained from imposing mass constraints when calculating Higgsness and Topness variables. For the SM $hh$ production, we estimate a $3.7σ$ statistical significance from an optimized cut-based strategy, improving about 20% over the best estimates of the literature, and $5σ$ from a multivariate analysis if systematic uncertainties on the backgrounds are small. The new variables are constructed as ratios of kinematic functions of the particles' momenta, being less prone to systematic errors. We also demonstrate the usefulness of the solutions in reconstructing heavy scalar resonances and other variables of phenomenological importance. △ Less

Submitted 15 September, 2025; originally announced September 2025.

Comments: 21 pages, 10 figures, 2 tables

Comparing Calculations of Seasonal Variations of Atmospheric Muons in Deep Underground Detectors

Authors: Amanda Alves, Lilly Pyras, Dennis Soldin, Stef Verpoest

Abstract: Cosmic rays interact with nuclei in the Earth's atmosphere to produce extensive air showers, which give rise to the atmospheric muon flux. Temperature fluctuations in the atmosphere influence the rate of muons measured in deep underground experiments. This contribution presents predictions of the daily muon flux at a depth of 2000 m.w.e., calculated using MUTE, a software tool which combines MCEq,… ▽ More Cosmic rays interact with nuclei in the Earth's atmosphere to produce extensive air showers, which give rise to the atmospheric muon flux. Temperature fluctuations in the atmosphere influence the rate of muons measured in deep underground experiments. This contribution presents predictions of the daily muon flux at a depth of 2000 m.w.e., calculated using MUTE, a software tool which combines MCEq, a numerical solver of the matrix cascade equations in the atmosphere, with PROPOSAL, a propagation code for leptons in matter. The flux estimates are obtained assuming different cosmic-ray flux and hadronic interaction models. The results are compared to previous approaches, based on different methods, to calculate seasonal variations of atmospheric muons in deep underground detectors. △ Less

Submitted 25 August, 2025; originally announced August 2025.

Comments: Presented at the 39th International Cosmic Ray Conference (ICRC2025) Presented at the 39th International Cosmic Ray Conference (ICRC2025) Presented at the 39th International Cosmic Ray Conference (ICRC2025)

Report number: PoS-ICRC2025-399

Physics-Informed Neural Network for Elastic Wave-Mode Separation

Authors: E. A. B. Alves, P. D. S. de Lima, D. H. G. Duarte, M. S. Ferreira, J. M. de Araújo, C. G. Bezerra

Abstract: Mode conversion in non-homogeneous elastic media makes it challenging to interpret physical properties accurately. Decomposing these modes correctly is crucial across various scientific areas. Recent machine learning approaches have been proposed to address this problem, utilizing the Helmholtz decomposition technique. In this paper, we investigate the capabilities of a physics-informed neural net… ▽ More Mode conversion in non-homogeneous elastic media makes it challenging to interpret physical properties accurately. Decomposing these modes correctly is crucial across various scientific areas. Recent machine learning approaches have been proposed to address this problem, utilizing the Helmholtz decomposition technique. In this paper, we investigate the capabilities of a physics-informed neural network (PINN) in separating P and S modes by solving a scalar Poisson equation. This scalar formulation offers a dimensionally scalable reduction in computational cost compared to the traditional vector formulation. We verify the proposed method in both homogeneous and realistic non-homogeneous elastic models as showcases. The obtained separated modes closely match those from conventional numerical techniques, while exhibiting reduced transverse wave leakage. △ Less

Submitted 6 August, 2025; originally announced August 2025.

Comments: 8 pages, 6 figures. Submitted to PRE

Journal ref: Phys. Rev. E 113, 025503 (2026)

Define-ML: An Approach to Ideate Machine Learning-Enabled Systems

Authors: Silvio Alonso, Antonio Pedro Santos Alves, Lucas Romao, Hélio Lopes, Marcos Kalinowski

Abstract: [Context] The increasing adoption of machine learning (ML) in software systems demands specialized ideation approaches that address ML-specific challenges, including data dependencies, technical feasibility, and alignment between business objectives and probabilistic system behavior. Traditional ideation methods like Lean Inception lack structured support for these ML considerations, which can res… ▽ More [Context] The increasing adoption of machine learning (ML) in software systems demands specialized ideation approaches that address ML-specific challenges, including data dependencies, technical feasibility, and alignment between business objectives and probabilistic system behavior. Traditional ideation methods like Lean Inception lack structured support for these ML considerations, which can result in misaligned product visions and unrealistic expectations. [Goal] This paper presents Define-ML, a framework that extends Lean Inception with tailored activities - Data Source Mapping, Feature-to-Data Source Mapping, and ML Mapping - to systematically integrate data and technical constraints into early-stage ML product ideation. [Method] We developed and validated Define-ML following the Technology Transfer Model, conducting both static validation (with a toy problem) and dynamic validation (in a real-world industrial case study). The analysis combined quantitative surveys with qualitative feedback, assessing utility, ease of use, and intent of adoption. [Results] Participants found Define-ML effective for clarifying data concerns, aligning ML capabilities with business goals, and fostering cross-functional collaboration. The approach's structured activities reduced ideation ambiguity, though some noted a learning curve for ML-specific components, which can be mitigated by expert facilitation. All participants expressed the intention to adopt Define-ML. [Conclusion] Define-ML provides an openly available, validated approach for ML product ideation, building on Lean Inception's agility while aligning features with available data and increasing awareness of technical feasibility. △ Less

Submitted 25 June, 2025; originally announced June 2025.

Comments: Accepted for publication at the 51st Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA) 2025

Entangled Interlocked Diamond-like (Diamondiynes) Lattices

Authors: C. M. O. Bastos, E. J. A. dos Santos, R. A. F. Alves, Alexandre C. Dias, L. A. Ribeiro Junior, D. S. Galvão

Abstract: Diamondynes, a new class of diamond-like carbon allotropes composed of carbon with sp$^2$/sp$^3$-hybridized carbon networks, exhibit unique structural motifs that have not been previously reported in carbon materials. These architectures feature sublattices that are both interlocked and capable of relative movement. Using ab initio simulations, we have conducted an extensive investigation into the… ▽ More Diamondynes, a new class of diamond-like carbon allotropes composed of carbon with sp$^2$/sp$^3$-hybridized carbon networks, exhibit unique structural motifs that have not been previously reported in carbon materials. These architectures feature sublattices that are both interlocked and capable of relative movement. Using ab initio simulations, we have conducted an extensive investigation into the structural and electronic properties of five diamondyne structures. Our results show that diamondiynes are thermodynamically stable and exhibit wide electronic band gaps, from 2.2 eV to 4.0 eV. They are flexible yet highly resistant compared to other diamond-like structures. They have relatively small cohesive energy values, consistent with the fact that one diamondyne structure (2f-unsym) has already been experimentally realized. Our results provide new physical insights into diamond-like carbon networks and suggest promising directions for the development of porous, tunable frameworks with potential applications in energy storage and conversion. △ Less

Submitted 11 June, 2025; originally announced June 2025.

Comments: 6 pages

MSC Class: 00-XX ACM Class: I.2; J.6

Kinetic Flat-Histogram Simulations of Non-Equilibrium Stochastic Processes with Continuous and Discontinuous Phase Transitions

Authors: L. M. C. Alencar, T. F. A. Alves, G. A. Alves, F. W. S. Lima, A. Macedo-Filho, R. S. Ferreira

Abstract: As far as we know, there is no flat-histogram algorithm to sample the stationary distribution of non-equilibrium stochastic processes. The present work addresses this gap by introducing a generalization of the Wang-Landau algorithm, applied to non-equilibrium stochastic processes with local transitions. The main idea is to sample macroscopic states using a kinetic Monte Carlo algorithm to generate… ▽ More As far as we know, there is no flat-histogram algorithm to sample the stationary distribution of non-equilibrium stochastic processes. The present work addresses this gap by introducing a generalization of the Wang-Landau algorithm, applied to non-equilibrium stochastic processes with local transitions. The main idea is to sample macroscopic states using a kinetic Monte Carlo algorithm to generate trial moves, which are accepted or rejected with a probability that depends inversely on the stationary distribution. The stationary distribution is refined through the simulation by a modification factor, leading to convergence toward the true stationary distribution. A visitation histogram is also accumulated, and the modification factor is updated when the histogram satisfies a flatness condition. The stationary distribution is obtained in the limit where the modification factor reaches a threshold value close to unity. To test the algorithm, we compare simulation results for several stochastic processes with theoretically known behavior. In addition, results from the kinetic flat-histogram algorithm are compared with standard exact stochastic simulations. We show that the kinetic flat-histogram algorithm can be applied to phase transitions in stochastic processes with bistability, which describe a wide range of phenomena such as epidemic spreading, population growth, chemical reactions, and consensus formation. With some adaptations, the kinetic flat-histogram algorithm can also be applied to stochastic models on lattices and complex networks. △ Less

Submitted 26 February, 2026; v1 submitted 26 May, 2025; originally announced May 2025.

Comments: 10 pages, 13 figures, 90 references

The invisible threat: assessing the collisional hazard posed by the undiscovered Venus co-orbital asteroids

Authors: V. Carruba, R. Sfair, R. A. Araujo, O. C. Winter, D. C. Mourão, S. Di Ruzza, S. Aljbaae, G. Caritá, R. C. Domingos, A. A. Alves

Abstract: Currently, 20 co-orbital asteroids of Venus are known, with only one with an eccentricity below 0.38. This is most likely caused by observational biases since asteroids with larger eccentricities may approach the Earth and are easier to detect. We aim to assess the possible threat that the yet undetected population of Venus co-orbitals may pose to Earth, and investigate their detectability from Ea… ▽ More Currently, 20 co-orbital asteroids of Venus are known, with only one with an eccentricity below 0.38. This is most likely caused by observational biases since asteroids with larger eccentricities may approach the Earth and are easier to detect. We aim to assess the possible threat that the yet undetected population of Venus co-orbitals may pose to Earth, and investigate their detectability from Earth and space observatories. We used semi-analytical models of the 1:1 mean-motion resonance with Venus and numerical simulations to monitor close encounters with Earth on several co-orbital cycles. We analyzed observability windows and brightness variations for potential Venus co-orbitals as viewed from ground-based telescopes to assess their future detection feasibility with next-generation survey capabilities. There is a range of orbits with e < 0.38, larger at lower inclinations, for which Venus' co-orbitals can pose a collisional hazard to Earth. Current ground-based observations are constrained by periodic observing windows and solar elongation limitations, though the Rubin Observatory may detect some of these objects during favorable configurations. Space missions based on Venus' orbits may be instrumental in detecting Venus' co-orbitals at low eccentricities. △ Less

Submitted 21 May, 2025; originally announced May 2025.

Comments: 10 pages, 10 figures, Under review in A&A

Journal ref: A&A 699, A86 (2025)

Brazilian Report on Dark Matter 2024

Authors: I. F. M. Albuquerque, J. Alcaniz, A. Alves, J. Amaral, C. Bonifazi, H. A. Borges, S. Carneiro, L. Casarini, D. Cogollo, A. G. Dias, G. C. Dorsch, A. Esmaili, G. Gil da Silveira, C. Gobel, V. P. Gonçalves, A. S. Jesus, D. Hadjimichef, P. C. de Holanda, R. F. L. Holanda, E. Kemp, A. Lessa, A. Machado, M. V T. Machado, M. Makler, V. Marra , et al. (29 additional authors not shown)

Abstract: One of the key scientific objectives for the next decade is to uncover the nature of dark matter (DM). We should continue prioritizing targets such as weakly-interacting massive particles (WIMPs), Axions, and other low-mass dark matter candidates to improve our chances of achieving it. A varied and ongoing portfolio of experiments spanning different scales and detection methods is essential to max… ▽ More One of the key scientific objectives for the next decade is to uncover the nature of dark matter (DM). We should continue prioritizing targets such as weakly-interacting massive particles (WIMPs), Axions, and other low-mass dark matter candidates to improve our chances of achieving it. A varied and ongoing portfolio of experiments spanning different scales and detection methods is essential to maximize our chances of discovering its composition. This report paper provides an updated overview of the Brazilian community's activities in dark matter and dark sector physics over the past years with a view for the future. It underscores the ongoing need for financial support for Brazilian groups actively engaged in experimental research to sustain the Brazilian involvement in the global search for dark matter particles △ Less

Submitted 8 May, 2025; v1 submitted 22 April, 2025; originally announced April 2025.

Comments: Editor-Convener: Farinaldo Queiroz. Report for the Latin American Association for High Energy, Cosmology and Astroparticle Physics

Lectures on the Bondi--Metzner--Sachs group and related topics in infrared physics

Authors: Níckolas de Aguiar Alves

Abstract: These are the extended lecture notes for a minicourse presented at the I São Paulo School on Gravitational Physics discussing the Bondi--Metzner--Sachs (BMS) group, the group of symmetries at null infinity on asymptotically flat spacetimes. The BMS group has found many applications in classical gravity, quantum field theory in flat and curved spacetimes, and quantum gravity. These notes build the… ▽ More These are the extended lecture notes for a minicourse presented at the I São Paulo School on Gravitational Physics discussing the Bondi--Metzner--Sachs (BMS) group, the group of symmetries at null infinity on asymptotically flat spacetimes. The BMS group has found many applications in classical gravity, quantum field theory in flat and curved spacetimes, and quantum gravity. These notes build the BMS group from its most basic prerequisites (such as group theory, symmetries in differential geometry, and asymptotic flatness) up to modern developments. These include its connections to the Weinberg soft graviton theorem, the memory effect, its use to construct Hadamard states in quantum field theory in curved spacetimes, and other ideas. Advanced sections briefly discuss the main concepts behind the infrared triangle in electrodynamics, superrotations, and the Dappiaggi--Moretti--Pinamonti group in expanding universes with cosmological horizons. New contributions by the author concerning asymptotic (conformal) Killing horizons are discussed at the end. △ Less

Submitted 11 May, 2026; v1 submitted 16 April, 2025; originally announced April 2025.

Comments: v4: 154 pages, 20 figures. Minor reference updates, matches published version

Journal ref: Eur. Phys. J. C 86.5, 507 (2026)

Null infinity as a Killing horizon

Authors: Níckolas de Aguiar Alves, Andre G. S. Landulfo

Abstract: Symmetries are ubiquitous in modern physics. They not only allow for a more simplified description of physical systems but also, from a more fundamental perspective, can be seen as determining a theory itself. In the present paper, we propose a new definition of asymptotic symmetries that unifies and generalizes the usual notions of symmetry considered in asymptotically flat spacetimes and expandi… ▽ More Symmetries are ubiquitous in modern physics. They not only allow for a more simplified description of physical systems but also, from a more fundamental perspective, can be seen as determining a theory itself. In the present paper, we propose a new definition of asymptotic symmetries that unifies and generalizes the usual notions of symmetry considered in asymptotically flat spacetimes and expanding universes with cosmological horizons. This is done by considering BMS-like symmetries for "asymptotic (conformal) Killing horizons", or A(C)KHs, here defined as null hypersurfaces that are tangent to a vector field satisfying the (conformal) Killing equation in a limiting sense. The construction is theory-agnostic and extremely general, for it makes no use of the Einstein equations and can be applied to a wide range of scenarios with different dimensions or hypersurface cross sections. While we reproduce the results by Dappiaggi, Moretti, and Pinamonti in the case of asymptotic Killing horizons, the conformal generalization does not yield only the BMS group, but a larger group. The enlargement is due to the presence of "superdilations". We speculate on many implications and possible continuations of this work, including the exploration of gravitational memory effects beyond general relativity, understanding antipodal matching conditions at spatial infinity in terms of bifurcate horizons, and the absence of superrotations in de Sitter spacetime and Killing horizons. △ Less

Submitted 20 August, 2025; v1 submitted 16 April, 2025; originally announced April 2025.

Comments: 18 pages, 4 figures. v3: change in title. Accepted for publication in Phys. Rev. D

Journal ref: Phys. Rev. D 112, 065017 (2025)

CMS RPC Non-Physics Event Data Automation Ideology

Authors: A. Dimitrov, M. Tytgat, K. Mota Amarilo, A. Samalan, K. Skovpen, G. A. Alves, E. Alves Coelho, F. Marujo da Silva, M. Barroso Ferreira Filho, E. M. Da Costa, D. De Jesus Damiao, S. Fonseca De Souza, R. Gomes De Souza, L. Mundim, H. Nogima, J. P. Pinheiro, A. Santoro, M. Thiel, A. Aleksandrov, R. Hadjiiska, P. Iaydjiev, M. Shopova, G. Sultanov, L. Litov, B. Pavlov , et al. (79 additional authors not shown)

Abstract: This paper presents a streamlined framework for real-time processing and analysis of condition data from the CMS experiment Resistive Plate Chambers (RPC). Leveraging data streaming, it uncovers correlations between RPC performance metrics, like currents and rates, and LHC luminosity or environmental conditions. The Java-based framework automates data handling and predictive modeling, integrating… ▽ More This paper presents a streamlined framework for real-time processing and analysis of condition data from the CMS experiment Resistive Plate Chambers (RPC). Leveraging data streaming, it uncovers correlations between RPC performance metrics, like currents and rates, and LHC luminosity or environmental conditions. The Java-based framework automates data handling and predictive modeling, integrating extensive datasets into synchronized, query-optimized tables. By segmenting LHC operations and analyzing larger virtual detector objects, the automation enhances monitoring precision, accelerates visualization, and provides predictive insights, revolutionizing RPC performance evaluation and future behavior modeling. △ Less

Submitted 11 April, 2025; originally announced April 2025.

Comments: CMS RPC Condition Data Automation, Java framework, 12 pages, 23 figures, CMS Condition database

The Measure of a Mass

Authors: Níckolas de Aguiar Alves, Bruno Arderucio Costa

Abstract: The concept of mass is central to any theory of gravity. Nevertheless, defining mass in general relativity is a difficult task, and even when it can be accomplished, we still need to investigate whether the typical properties of mass in Newtonian gravity are still true in Einsteinian gravity. In this essay, we discuss "the measure of a mass" in relativity by considering some of the many different… ▽ More The concept of mass is central to any theory of gravity. Nevertheless, defining mass in general relativity is a difficult task, and even when it can be accomplished, we still need to investigate whether the typical properties of mass in Newtonian gravity are still true in Einsteinian gravity. In this essay, we discuss "the measure of a mass" in relativity by considering some of the many different definitions (Komar, ADM, and Bondi) and how they are related. Finally, we discuss when and whether the mass is positive, as is usually expected, and which physical properties of matter and gravity can ensure this result. △ Less

Submitted 19 March, 2025; originally announced March 2025.

Comments: Essay written for the Gravity Research Foundation 2025 Awards for Essays on Gravitation

Physicochemical Characterization of a New 2D Semiconductor Carbon Allotrope, C16: An Investigation via Density Functional Theory and Machine Learning-based Molecular Dynamics

Authors: Kleuton A. L. Lima, Rodrigo A. F. Alves, Elie A. Moujaes, Alexandre C. Dias, Douglas S. Galvão, Marcelo L. Pereira Jr, Luiz A. Ribeiro Jr

Abstract: This study comprehensively characterizes, with suggested applications, a novel two-dimensional carbon allotrope, C$_{16}$, using Density Functional Theory and machine learning-based molecular dynamics. This nanomaterial is derived from naphthalene and bicyclopropylidene molecules, forming a planar configuration with sp$^2$ hybridization and featuring 3-, 4-, 6-, 8-, and 10-membered rings. Cohesive… ▽ More This study comprehensively characterizes, with suggested applications, a novel two-dimensional carbon allotrope, C$_{16}$, using Density Functional Theory and machine learning-based molecular dynamics. This nanomaterial is derived from naphthalene and bicyclopropylidene molecules, forming a planar configuration with sp$^2$ hybridization and featuring 3-, 4-, 6-, 8-, and 10-membered rings. Cohesive energy of \SI{-7.1}{\electronvolt/atom}, absence of imaginary frequencies in the phonon spectrum, and the retention of the system's topology after ab initio molecular dynamics simulations confirm the structural stability of C$_{16}$. The nanomaterial exhibits a semiconducting behavior with a direct band gap of \SI{0.59}{\electronvolt} and anisotropic optical absorption in the $y$ direction. Assuming a complete absorption of incident light, it registers a power conversion efficiency of \SI{13}{\percent}, demonstrating relatively good potential for applications in solar energy conversion. The thermoelectric figure of merit ($zT$) reaches 0.8 at elevated temperatures, indicating a reasonable ability to convert a temperature gradient into electrical power. Additionally, C$_{16}$ demonstrates high mechanical strength, with Young's modulus values of \SI{500}{\giga\pascal} and \SI{630}{\giga\pascal} in the $x$ and $y$ directions, respectively. Insights into the electronic, optical, thermoelectric, and mechanical properties of C$_{16}$ reveal its promising capability for energy conversion applications. △ Less

Submitted 14 March, 2025; originally announced March 2025.

Comments: 22 pages

MSC Class: 00-XX ACM Class: J.2; I.6

Investigating Issues that Lead to Code Technical Debt in Machine Learning Systems

Authors: Rodrigo Ximenes, Antonio Pedro Santos Alves, Tatiana Escovedo, Rodrigo Spinola, Marcos Kalinowski

Abstract: [Context] Technical debt (TD) in machine learning (ML) systems, much like its counterpart in software engineering (SE), holds the potential to lead to future rework, posing risks to productivity, quality, and team morale. Despite growing attention to TD in SE, the understanding of ML-specific code-related TD remains underexplored. [Objective] This paper aims to identify and discuss the relevance o… ▽ More [Context] Technical debt (TD) in machine learning (ML) systems, much like its counterpart in software engineering (SE), holds the potential to lead to future rework, posing risks to productivity, quality, and team morale. Despite growing attention to TD in SE, the understanding of ML-specific code-related TD remains underexplored. [Objective] This paper aims to identify and discuss the relevance of code-related issues that lead to TD in ML code throughout the ML workflow. [Method] The study first compiled a list of 34 potential issues contributing to TD in ML code by examining the phases of the ML workflow, their typical associated activities, and problem types. This list was refined through two focus group sessions involving nine experienced ML professionals, where each issue was assessed based on its occurrence contributing to TD in ML code and its relevance. [Results] The list of issues contributing to TD in the source code of ML systems was refined from 34 to 30, with 24 of these issues considered highly relevant. The data pre-processing phase was the most critical, with 14 issues considered highly relevant. Shortcuts in code related to typical pre-processing tasks (e.g., handling missing values, outliers, inconsistencies, scaling, rebalancing, and feature selection) often result in "patch fixes" rather than sustainable solutions, leading to the accumulation of TD and increasing maintenance costs. Relevant issues were also found in the data collection, model creation and training, and model evaluation phases. [Conclusion] We have made the final list of issues available to the community and believe it will help raise awareness about issues that need to be addressed throughout the ML workflow to reduce TD and improve the maintainability of ML code. △ Less

Submitted 18 February, 2025; originally announced February 2025.

Comments: To appear in the 2025 4th IEEE/ACM International Conference on AI Engineering - Software Engineering for AI, CAIN 2025

Exploring Novel 2D Analogues of Goldene: Electronic, Mechanical, and Optical Properties of Silverene and Copperene

Authors: Emanuel J. A. dos Santos, Rodrigo A. F. Alves, Alexandre C. Dias, Marcelo L. Pereira Junior, Douglas S. Galvão, Luiz A. Ribeiro Junior

Abstract: Two-dimensional (2D) materials have garnered significant attention due to their unique properties and broad application potential. Building on the success of goldene, a monolayer lattice of gold atoms, we explore its proposed silver and copper analogs, silverene and copperene, using density functional theory calculations. Our findings reveal that silverene and copperene are energetically stable, w… ▽ More Two-dimensional (2D) materials have garnered significant attention due to their unique properties and broad application potential. Building on the success of goldene, a monolayer lattice of gold atoms, we explore its proposed silver and copper analogs, silverene and copperene, using density functional theory calculations. Our findings reveal that silverene and copperene are energetically stable, with formation energies of -2.3 eV/atom and -3.1 eV/atom, closely matching goldene's -2.9 eV/atom. Phonon dispersion and ab initio molecular dynamics simulations confirm their structural and dynamical stability at room temperature, showing no bond breaking or structural reconfiguration. Mechanical analyses indicate isotropy, with Young's moduli of 73 N/m, 44 N/m, and 59 N/m for goldene, silverene, and copperene, respectively, alongside Poisson's ratios of 0.46, 0.42, and 0.41. These results suggest comparable rigidity and deformation characteristics. Electronic band structure analysis highlights their metallic nature, with variations in the band profiles at negative energy levels. Despite their metallic character, these materials exhibit optical properties akin to semiconductors, pointing to potential applications in optoelectronics. △ Less

Submitted 17 February, 2025; originally announced February 2025.

Comments: 24 pages and six figures

MSC Class: 00-xx ACM Class: J.2; I.6

SPARC4 control system

Authors: Denis Bernardes, Orlando Verducci Junior, Francisco Rodrigues, Claudia Vilega Rodrigues, Luciano Fraga, Eder Martioli, Clemens D. Gneiding, André Luiz de Moura Alves, Juliano Romão, Laerte Andrade, Leandro de Almeida, Ana Carolina Mattiuci, Flavio Felipe Ribeiro, Wagner Schlindwein, Jesulino Bispo dos Santos, Francisco Jose Jablonski, Julio Cesar Neves Campagnolo, Rene Laporte

Abstract: SPARC4 is a new astronomical instrument developed entirely by Brazilian institutions, currently installed on the 1.6-m Perkin-Elmer telescope of the Pico dos Dias Observatory. It allows the user to perform photometric or polarimetric observations simultaneously in the four SDSS bands (g, r, i, and z). In this paper, we describe the control system developed for SPARC4. This system is composed of S4… ▽ More SPARC4 is a new astronomical instrument developed entirely by Brazilian institutions, currently installed on the 1.6-m Perkin-Elmer telescope of the Pico dos Dias Observatory. It allows the user to perform photometric or polarimetric observations simultaneously in the four SDSS bands (g, r, i, and z). In this paper, we describe the control system developed for SPARC4. This system is composed of S4ACS, S4ICS, and S4GUI softwares and associated hardware. S4ACS is responsible for controlling the four EMCCD scientific cameras (one for each instrument band). S4ICS controls the sensors and motors responsible for the moving parts of SPARC4. Finally, S4GUI is the interface used to perform observations, which includes the choice of instrument configuration and image acquisition parameters. S4GUI communicates with the instrument subsystems and with some observatory facilities, needed during the observations. Bench tests were performed for the determination of the overheads added by SPARC4 control system in the acquisition of photometric and polarimetric series of images. In the photometric mode, SPARC4 allows the acquisition of a series of 1400 full-frame images, with a deadtime of 4.5 ms between images. Besides, several image series can be concatenated with a deadtime of 450 ms plus the readout time of the last image. For the polarimetric mode, measurements can be obtained with a deadtime of 1.41 s plus the image readout time between subsequent waveplate positions. For both photometric and polarimetric modes, the user can choose among operating modes with image readout times between 5.9 ms and 1.24 s, which ultimately defines the instrument temporal performance. △ Less

Submitted 24 December, 2024; originally announced December 2024.

Comments: 20 pages, 14 figures, peer-reviewed paper

Update of the Brazilian Participation in the Next-Generation Collider Experiments

Authors: W. L. Aldá Júnior, G. A. Alves, K. M. Amarilo, M. Barroso Ferreira Filho, C. A. Bernardes, E. M. da Costa, U. de Freitas Carneiro da Graça, D. de Jesus Damião, S. de Souza Fonseca, L. M. Domingues Mendes, M. Donadelli, G. Gil da Silveira, C. Hensel, C. Jahnke, H. Malbouisson, J . L. Marin, D. E. Martins, A. Massafferri, C. Mora Herrera, I. Nasteva, E. E. Purcino de Souza, F. S. Queiroz, M. Rangel, P. Rebello Teles, M. Thiel , et al. (2 additional authors not shown)

Abstract: This proposal outlines the future plans of the Brazilian High-Energy Physics (HEP) community for upcoming collider experiments. With the construction of new particle colliders on the horizon and the ongoing operation of the High-Luminosity LHC, several research groups in Brazil have put forward technical proposals, covering both hardware and software contributions, as part of the Brazilian contrib… ▽ More This proposal outlines the future plans of the Brazilian High-Energy Physics (HEP) community for upcoming collider experiments. With the construction of new particle colliders on the horizon and the ongoing operation of the High-Luminosity LHC, several research groups in Brazil have put forward technical proposals, covering both hardware and software contributions, as part of the Brazilian contribution to the global effort. The primary goal remains to foster a unified effort within the Brazilian HEP community, optimizing resources and expertise to deliver a high-impact contribution to the international HEP community. △ Less

Submitted 7 October, 2024; originally announced October 2024.

Comments: 24 pages, submitted to the Latin American Strategy Forum for Research Infrastructure

Simulating radio emission from particle cascades with CORSIKA 8

Authors: J. M. Alameddine, J. Albrecht, J. Ammerman-Yebra, L. Arrabito, A. A. Alves Jr., D. Baack, A. Coleman, H. Dembinski, D. Elsässer, R. Engel, A. Faure, A. Ferrari, C. Gaudu, C. Glaser, M. Gottowik, D. Heck, T. Huege, K. H. Kampert, N. Karastathis, L. Nellen, T. Pierog, R. Prechelt, M. Reininghaus, W. Rhode, F. Riehn , et al. (5 additional authors not shown)

Abstract: CORSIKA 8 is a new framework for simulations of particle cascades in air and dense media implemented in modern C++17, based on past experience with existing codes, in particular CORSIKA 7. The flexible and modular structure of the project allows the development of independent modules that can produce a fully customizable particle shower simulation. The radio module in particular is designed to tre… ▽ More CORSIKA 8 is a new framework for simulations of particle cascades in air and dense media implemented in modern C++17, based on past experience with existing codes, in particular CORSIKA 7. The flexible and modular structure of the project allows the development of independent modules that can produce a fully customizable particle shower simulation. The radio module in particular is designed to treat the electric field calculation and its propagation through complex media to each observer location in an autonomous and flexible way. It already allows for the simultaneous simulation of the radio emission calculated with two independent time-domain formalisms, the "Endpoint formalism" as previously implemented in CoREAS and the "ZHS" algorithm as ported from ZHAireS. The design acts as the baseline interface for current and future development for the simulation of radio emission from particle showers in standard and complex scenarios, such as cross-media showers penetrating from air into ice. In this work, we present the design and implementation of the radio module in CORSIKA 8, along with validation studies and a direct comparison of the radio emission from air showers simulated with CORSIKA 8, CORSIKA 7 and ZHAireS. We also present the impact of simulation details such as the step size of simulated particle tracks on radio-emission simulations and perform a direct comparison of the "Endpoints" and "ZHS" formalisms for the same underlying air showers. Finally, we present an in-depth comparison of CORSIKA 8 and CORSIKA 7 for optimum simulation settings and discuss the relevance of observed differences in light of reconstruction efforts for the energy and mass of cosmic rays. △ Less

Submitted 24 September, 2024; originally announced September 2024.

Comments: 17 pages

Journal ref: Astropart. Phys. 166, 103072 (2025)

A computational study of algebraic coarse spaces for two-level overlapping additive Schwarz preconditioners

Authors: Filipe A. C. S. Alves, Alexander Heinlein, Hadi Hajibeygi

Abstract: The two-level overlapping additive Schwarz method offers a robust and scalable preconditioner for various linear systems resulting from elliptic problems. One of the key to these properties is the construction of the coarse space used to solve a global coupling problem, which traditionally requires information about the underlying discretization. An algebraic formulation of the coarse space reduce… ▽ More The two-level overlapping additive Schwarz method offers a robust and scalable preconditioner for various linear systems resulting from elliptic problems. One of the key to these properties is the construction of the coarse space used to solve a global coupling problem, which traditionally requires information about the underlying discretization. An algebraic formulation of the coarse space reduces the complexity of its assembly. Furthermore, well-chosen coarse basis functions within this space can better represent changes in the problem's properties. Here we introduce an algebraic formulation of the multiscale finite element method (MsFEM) based on the algebraic multiscale solver (AMS) in the context of the two-level Schwarz method. We show how AMS is related to other energy-minimizing coarse spaces. Furthermore, we compare the AMS with other algebraic energy-minimizing spaces: the generalized Dryja-Smith-Widlund (GDSW), and the reduced dimension GDSW (RGDSW). △ Less

Submitted 15 August, 2024; originally announced August 2024.

Comments: Submitted to the proceedings of the 28th International Conference on Domain Decomposition Methods (DDM28)

Positive Mass in General Relativity Without Energy Conditions

Authors: Níckolas de Aguiar Alves, Andre G. S. Landulfo, Bruno Arderucio Costa

Abstract: A long-standing problem in physics is why observed masses are always positive. While energy conditions in quantum field theory can partly answer this problem, in this paper we find evidence that classical general relativity abhors negative masses, without the need for quantum theory or energy conditions. This is done by considering many different models of negative-mass "stars" and showing they ar… ▽ More A long-standing problem in physics is why observed masses are always positive. While energy conditions in quantum field theory can partly answer this problem, in this paper we find evidence that classical general relativity abhors negative masses, without the need for quantum theory or energy conditions. This is done by considering many different models of negative-mass "stars" and showing they are dynamically unstable. A fortiori, we show that any barotropic negative-mass star must be dynamically unstable. △ Less

Submitted 17 January, 2025; v1 submitted 31 July, 2024; originally announced August 2024.

Comments: 26 pages, 9 figures. v3 accepted for publication in Phys. Rev. D. Two extra appendices relative to the published version

Journal ref: Phys. Rev. D 111, 044027 (2025)

Industrial Practices of Requirements Engineering for ML-Enabled Systems in Brazil

Authors: Antonio Pedro Santos Alves, Marcos Kalinowski, Daniel Mendez, Hugo Villamizar, Kelly Azevedo, Tatiana Escovedo, Helio Lopes

Abstract: [Context] In Brazil, 41% of companies use machine learning (ML) to some extent. However, several challenges have been reported when engineering ML-enabled systems, including unrealistic customer expectations and vagueness in ML problem specifications. Literature suggests that Requirements Engineering (RE) practices and tools may help to alleviate these issues, yet there is insufficient understandi… ▽ More [Context] In Brazil, 41% of companies use machine learning (ML) to some extent. However, several challenges have been reported when engineering ML-enabled systems, including unrealistic customer expectations and vagueness in ML problem specifications. Literature suggests that Requirements Engineering (RE) practices and tools may help to alleviate these issues, yet there is insufficient understanding of RE's practical application and its perception among practitioners. [Goal] This study aims to investigate the application of RE in developing ML-enabled systems in Brazil, creating an overview of current practices, perceptions, and problems in the Brazilian industry. [Method] To this end, we extracted and analyzed data from an international survey focused on ML-enabled systems, concentrating specifically on responses from practitioners based in Brazil. We analyzed RE-related answers gathered from 72 practitioners involved in data-driven projects. We conducted quantitative statistical analyses on contemporary practices using bootstrapping with confidence intervals and qualitative studies on the reported problems involving open and axial coding procedures. [Results] Our findings highlight distinct RE implementation aspects in Brazil's ML projects. For instance, (i) RE-related tasks are predominantly conducted by data scientists; (ii) the most common techniques for eliciting requirements are interviews and workshop meetings; (iii) there is a prevalence of interactive notebooks in requirements documentation; (iv) practitioners report problems that include a poor understanding of the problem to solve and the business domain, low customer engagement, and difficulties managing stakeholders expectations. [Conclusion] These results provide an understanding of RE-related practices in the Brazilian ML industry, helping to guide research toward improving the maturity of RE for ML-enabled systems. △ Less

Submitted 22 July, 2024; originally announced July 2024.

Comments: arXiv admin note: substantial text overlap with arXiv:2310.06726

Exploring Top-Quark Signatures of Heavy Flavor-Violating Scalars at the LHC with Parametrized Neural Networks

Authors: Alexandre Alves, Eduardo da Silva Almeida, Alex G. Dias, Diego S. V. Gonçalves

Abstract: In this work, we study flavor-violating scalars (flavons) in a range of large masses that have not been explored previously. We model the interactions with an effective field theory formulation where the flavon is heavier than the top quark. In addition, we assume that the flavon only couples to fermions of the Standard Model in a flavor-changing way. As the flavon couples strongly to top quarks,… ▽ More In this work, we study flavor-violating scalars (flavons) in a range of large masses that have not been explored previously. We model the interactions with an effective field theory formulation where the flavon is heavier than the top quark. In addition, we assume that the flavon only couples to fermions of the Standard Model in a flavor-changing way. As the flavon couples strongly to top quarks, same-sign and opposite-sign top quark pair signals can be explored in the search for those particles. Using parametrized neural networks, we show that it is possible to probe flavons with masses in the 200-1600 GeV range through their interactions with a top quark plus up and charm quarks for effective couplings of order 10^-2 TeV^-1 at the 14 TeV High-Luminosity LHC. △ Less

Submitted 16 July, 2024; originally announced July 2024.

Comments: 15 pages, 6 figures

Social dilemmas, network reciprocity and the small-world property

Authors: F. B. Pereira, R. S. Ferreira, D. S. M. Alencar, T. F. A. Alves, G. A. Alves, F. W. S. Lima, A. Macedo-Filho

Abstract: We revisit two evolutionary game theory models, namely the Prisoner and the Snowdrift dilemmas, on top of small-world networks. These dynamics on networked populations (individuals occupying nodes of a graph) are mainly concerning on the competition between to cooperate or to defect, by allowing some process of revision of strategies. Cooperators avoid defectors by forming clusters in a process kn… ▽ More We revisit two evolutionary game theory models, namely the Prisoner and the Snowdrift dilemmas, on top of small-world networks. These dynamics on networked populations (individuals occupying nodes of a graph) are mainly concerning on the competition between to cooperate or to defect, by allowing some process of revision of strategies. Cooperators avoid defectors by forming clusters in a process known as network reciprocity. This defense strategy is based on the fact that any individual interact only with its nearest neighbors. The minimum cluster, in turn, is formed by a set of three completely connected nodes and the bulk of these triplets is associated with the transitivity property of a network. Particularly, we show that the transitivity increases eventually assuming a constant behavior when observed as a function of the number of contacts of an individual. We investigate the influence of the network reciprocity on that transitivity increasing regime on the promotion of a cooperative behavior. The dynamics on small-world networks are compared with those random regular, and annealed networks, the later typically studied as the well-mixed approach. We observe that the Snowdrift Game converge to an annealed scenario as randonness and coordination number increase, whereas the Prisoner's Dilemma becomes more severe against the cooperative behavior under the regime of an increasing network reciprocity. △ Less

Submitted 11 November, 2024; v1 submitted 11 July, 2024; originally announced July 2024.

Comments: 10 pages, 7 figures

Generalized Diffusive Epidemic Process with Permanent Immunity in Two Dimensions

Authors: V. R. Carvalho, T. F. A. Alves, G. A. Alves, D. S. M. Alencar, F. W. S. Lima, A. Macedo-Filho, R. S. Ferreira

Abstract: We introduce the generalized diffusive epidemic process, which is a metapopulation model for an epidemic outbreak where a non-sedentary population of walkers can jump along lattice edges with diffusion rates $D_S$ or $D_I$ if they are susceptible or infected, respectively, and recovered individuals possess permanent immunity. Individuals can be contaminated with rate $μ_c$ if they share the same l… ▽ More We introduce the generalized diffusive epidemic process, which is a metapopulation model for an epidemic outbreak where a non-sedentary population of walkers can jump along lattice edges with diffusion rates $D_S$ or $D_I$ if they are susceptible or infected, respectively, and recovered individuals possess permanent immunity. Individuals can be contaminated with rate $μ_c$ if they share the same lattice node with an infected individual and recover with rate $μ_r$, being removed from the dynamics. Therefore, the model does not have the conservation of the active particles composed of susceptible and infected individuals. The reaction-diffusion dynamics are separated into two stages: (i) Brownian diffusion, where the particles can jump to neighboring nodes, and (ii) contamination and recovery reactions. The dynamics are mapped into a growing process by activating lattice nodes with successful contaminations where activated nodes are interpreted as infection sources. In all simulations, the epidemic starts with one infected individual in a lattice filled with susceptibles. Our results indicate a phase transition in the dynamic percolation universality class controlled by the population size, irrespective of diffusion rates $D_S$ and $D_I$ and a subexponential growth of the epidemics in the percolation threshold. △ Less

Submitted 15 July, 2024; v1 submitted 11 July, 2024; originally announced July 2024.

Comments: 8 pages, 4 figures

Deep Dive into MRI: Exploring Deep Learning Applications in 0.55T and 7T MRI

Authors: Ana Carolina Alves, André Ferreira, Behrus Puladi, Jan Egger, Victor Alves

Abstract: The development of magnetic resonance imaging (MRI) for medical imaging has provided a leap forward in diagnosis, providing a safe, non-invasive alternative to techniques involving ionising radiation exposure for diagnostic purposes. It was described by Block and Purcel in 1946, and it was not until 1980 that the first clinical application of MRI became available. Since that time the MRI has gone… ▽ More The development of magnetic resonance imaging (MRI) for medical imaging has provided a leap forward in diagnosis, providing a safe, non-invasive alternative to techniques involving ionising radiation exposure for diagnostic purposes. It was described by Block and Purcel in 1946, and it was not until 1980 that the first clinical application of MRI became available. Since that time the MRI has gone through many advances and has altered the way diagnosing procedures are performed. Due to its ability to improve constantly, MRI has become a commonly used practice among several specialisations in medicine. Particularly starting 0.55T and 7T MRI technologies have pointed out enhanced preservation of image detail and advanced tissue characterisation. This review examines the integration of deep learning (DL) techniques into these MRI modalities, disseminating and exploring the study applications. It highlights how DL contributes to 0.55T and 7T MRI data, showcasing the potential of DL in improving and refining these technologies. The review ends with a brief overview of how MRI technology will evolve in the coming years. △ Less

Submitted 1 July, 2024; originally announced July 2024.