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Number of books at home and student achievement: new insights from two assessment methods and their interplay with the home literacy environment
(Springer, 2026) Heppt, Birgit; Volodina, Anna; Iglesias Muñoz, Patricia Andrea; Revilla, Melanie
Considering the widespread use of the books-at-home index in empirical educational and social research, the goal of the present study is twofold: First, by considering two common variants of the books-at-home index (i.e., number of books for adults and number of books for children) and their relations to the home literacy environment (HLE), we aim to provide further insight into the mechanisms underlying the relation between the number of books and student achievement. Second, the use of two different assessment methods of the number of books (i.e., open-ended questions and photos of the number of books) allows for an initial evaluation of the reliability and validity of the use of questions. Analyses are based on cross-sectional data of 332 parents of elementary school students from Grades 1, 3, and 5 who participated in a web survey in Spain. Multiple linear regression models revealed that, when assessed via open-ended questions, the number of children's books - but not the number of books for adults - contributed to explaining grades in Spanish and math beyond child gender and parental education. The number of children's books was also a significant predictor of the HLE, which was unrelated to students' grades. Comparing results of the two assessment methods revealed high correlations among the number of books collected through open-ended questions vs. photos and a much higher response rate for the questions. Results point to the use of (open-ended) questions as a viable approach for collecting the number of books in empirical research.
Does the background of the regulator matter? The role of expertise and diversity on the perceived competence of regulatory bodies
(Wiley, 2025) Pérez Durán, Ixchel; Papadopoulos, Yannis; Redert, Bastiaan; Triviño Salazar, Juan Carlos
This paper examines expertise and professional diversity within new (agencies and central banks) and traditional (ministries) regulatory bodies (RBs) and assesses their effect on the perceived competence of RBs. In particular, we address the following research questions: To what extent do members of RBs have expertise and display diversity in terms of their professional trajectories? How do expertise and professional diversity affect the perceived competence of RBs? By using two empirical sources of data, this article provides core information on the educational and professional profiles of RBs staff. In addition, the paper provides evidence that both professional diversity and expertise among RBs do not have a significant effect on their perceived competence by regime actors. However, the study also suggests that regime actors that are more closely aligned to the professional trajectory of RB members (i.e., other regulators and members of the executive branch) tend to have a more positive perception of the competence of RBs. Conversely, societal actors tend to be more critical toward RBs, suggesting that a lack of a shared language creates a greater distance from the regulators.
Restoring oscillatory dynamics in Alzheimer's disease: a laminar whole-brain model of serotonergic psychedelic effects
(MIT Press, 2026) Gendra, Jan C.; Lopez-Sola, Edmundo; Castaldo, Francesca; Lleal-Custey, Èlia; Sanchez Todo, Roser; Vohryzek, Jakub; Salvador, Ricardo; Andrzejak, Ralph Gregor; Ruffini, Giulio
Classical serotonergic psychedelics show promise in addressing neurodegenerative disorders such as Alzheimer's disease by modulating pathological brain dynamics. However, the precise neurobiological mechanisms underlying their effects remain elusive. This study introduces a personalized whole-brain model built upon a laminar neural mass framework to elucidate these effects. Using multimodal neuroimaging data from 30 subjects diagnosed with mild to moderate Alzheimer's disease, we simulate the impact of serotonin 2A receptor activation, characteristic of psychedelics, on cortical dynamics. By modulating the excitability of layer 5 pyramidal neurons, our models reproduce hallmark changes in EEG power spectra observed under psychedelics, including alpha power suppression and gamma power enhancement. These spectral shifts are shown to correlate strongly with the regional distribution of serotonin 2A receptors. Furthermore, simulated EEG reveals increased complexity and entropy, suggesting restored network function. These findings underscore the potential of serotonergic psychedelics to reestablish healthy oscillatory dynamics in the prodromal and early phases of Alzheimer's disease and offer mechanistic insights into their potential therapeutic effects in neurodegenerative disorders.
Strengthening trust by design: a QCA study of design choices in regulatory regimes
(Wiley, 2026) Verhoest, Koen; Maggetti, Martino; Redert, Bastiaan; Latusek, Dominika; Jordana, Jacint
How can the design of regulatory regimes foster trust in those regimes? In food safety, finance, and data protection regulation, regulatory frameworks have been reformed to restore trust after regulatory failures. Using fuzzy-set qualitative comparative analysis, this paper seeks to identify how key design choices-centralization of competencies in one versus multiple regulatory agencies, agency independence, mandated interactions, and rules perceived as appropriate-combine in fostering both trust in the regime itself and between its actors. Rule appropriateness is found to be a necessary condition for trust, while the combination of centralized regulatory competencies with dense information sharing is particularly effective in building regime trust. Alternatively, trust can emerge in regimes with multiple independent agencies under specific configurations. By integrating diverse data sources and adopting a cross-sectoral, cross-national approach, this paper provides a fine-grained understanding of how design elements shape trust, offering lessons to scholars and policymakers on crafting resilient and trusted regulatory frameworks.
Intent-based service provisioning and closed-loop automation for cobot service migration in a multi-stakeholder environment
(Institute of Electrical and Electronics Engineers (IEEE), 2025) Pires Orozco, Rafael; Malinen, Jere; Porambage, Pawani; Alemany Prats, Pol; Adanza Dopazo, Daniel; Muñoz, Raul; Vilalta, Ricard; Giardina, Pietro G.; De Angelis, Michael; Landi, Giada
This paper presents a Proof-of-Concept (PoC) focused on intent-based service provisioning and closed-loop automation for collaborative robot (cobot) use case. The PoC demonstrates the integration of two key IBN enablers: the Intent-Based Network Intent Management Entity (IBN-IME) and CL Automation and Coordination, both aligned with 3GPP and ETSI Zero-Touch Service and Network Management (ZSM) standards. These enablers support the seamless interpretation of user intents, service deployment, and migration. The testbed, designed to emulate certain functionalities present in a 6G end-to-end system, highlights the potential for automation in future networks. The work addresses the need for an ecosystem that allows for the interaction of multiple stakeholders in a secure platform. The PoC presented can adapt to increasingly complex use cases, laying the groundwork for future improvements and broader deployments.
Escape from an attractor generated by recurrent exit
(American Physical Society, 2021) Zonca, Lou; Holcman, David
Kramer's theory of activation over a potential barrier consists in computing the mean exit time from the boundary of a basin of attraction of a randomly perturbed dynamical system. Here we report that for some systems, crossing the boundary is not enough, because stochastic trajectories return inside the basin with a high probability a certain number of times before escaping far away. This situation is due to a shallow potential. We compute the mean and distribution of escape times and show how this result explains the large distribution of interburst durations in neuronal networks.
Astroglial gap junctions strengthen hippocampal network activity by sustaining afterhyperpolarization via KCNQ channels
(Cell Press, 2024) Dossi, Elena; Zonca, Lou; Pivonkova, Helena; Milior, Giampaolo; Moulard, Julien; Vargova, Lydia; Chever, Oana; Holcman, David; Rouach, Nathalie
Throughout the brain, astrocytes form networks mediated by gap junction channels that promote the activity of neuronal ensembles. Although their inputs on neuronal information processing are well established, how molecular gap junction channels shape neuronal network patterns remains unclear. Here, using astroglial connexin-deficient mice, in which astrocytes are disconnected and neuronal bursting patterns are abnormal, we show that astrocyte networks strengthen bursting activity via dynamic regulation of extracellular potassium levels, independently of glutamate homeostasis or metabolic support. Using a facilitation-depression model, we identify neuronal afterhyperpolarization as the key parameter underlying bursting pattern regulation by extracellular potassium in mice with disconnected astrocytes. We confirm this prediction experimentally and reveal that astroglial network control of extracellular potassium sustains neuronal afterhyperpolarization via KCNQ voltage-gated K channels. Altogether, these data delineate how astroglial gap junctions mechanistically strengthen neuronal population bursts and point to approaches for controlling aberrant activity in neurological diseases.
The role of cardiovascular risk factors on educational and regional inequalities in mortality in Spain 2016-2022: an analysis using multiple causes of death
(Elsevier, 2026) Pérez-Miguel, Enrique; Trias Llimós, Sergi
Background Cardiovascular (CVD) mortality is a key component of life expectancy dynamics. CVD mortality is influenced by well-established risk factors and inequalities across and within sub-populations exist. This paper assesses the role of risk factors on educational and regional inequalities in CVD and all-cause mortality in Spain and its regions (2016-2022). Methods Using multiple cause-of-death mortality data, we examine two indicators of CVD mortality: 1) Deaths with CVDs as the underlying cause (CVD mortality); and 2) deaths with CVDs as the underlying cause and a mention in the death certificate of any of the following risk factors: diabetes, chronic kidney disease, obesity, lipidemias and hypertension (CVD mortality with risk factors). We use Poisson models to estimate Relative Index of Inequalities (RII) and counterfactual scenarios to estimate potential gains in life expectancy at age 35 resulting from eliminating educational and regional inequalities in risk factors associated with CVDs. Results CVD deaths with any mentions of risk factors contributed to approximately one-third of CVD deaths and were strongly associated with CVD mortality and CVD mortality inequalities, especially among females. Eliminating inequalities in risk factors associated with CVDs would yield gains in life expectancy (for Spain: 0.19 years among females, 0.14 years among males), with regional variation. These gains were higher than expected compared to its relative weight on CVD and all-cause mortality. Conclusions Our results suggest that targeting well-established risk factors is an effective strategy for regional health policies, to improve overall life expectancy and CVD mortality and to reduce socioeconomic inequalities.
The cost of training machine learning models over distributed data sources
(Institute of Electrical and Electronics Engineers (IEEE), 2023) Guerra, Elia; Wilhelmi Roca, Francesc; Miozzo, Marco; Dini, Paolo
Federated learning is one of the most appealing alternatives to the standard centralized learning paradigm, allowing a heterogeneous set of devices to train a machine learning model without sharing their raw data. However, it requires a central server to coordinate the learning process, thus introducing potential scalability and security issues. In the literature, server-less federated learning approaches like gossip federated learning and blockchain-enabled federated learning have been proposed to mitigate these issues. In this work, we propose a complete overview of these three techniques, proposing a comparison according to an integral set of performance indicators, including model accuracy, time complexity, communication overhead, convergence time, and energy consumption. An extensive simulation campaign permits to draw a quantitative analysis considering both feedforward and convolutional neural network models. Results show that gossip federated learning and standard federated solution are able to reach a similar level of accuracy, and their energy consumption is influenced by the machine learning model adopted, the software library, and the hardware used. Differently, blockchain-enabled federated learning represents a viable solution for implementing decentralized learning with a higher level of security, at the cost of an extra energy usage and data sharing. Finally, we identify open issues on the two decentralized federated learning implementations and provide insights on potential extensions and possible research directions on this new research field.
Centering inclusivity in the design of online conferences - An OHBM-Open Science perspective
(Oxford University Press, 2021) Levitis, Elizabeth; Vohryzek, Jakub; Maumet, Camille
As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.
Multiscale effects of excitatory-inhibitory homeostasis in lesioned cortical networks: a computational study
(Public Library of Science (PLoS), 2023) dos Santos, Francisco Páscoa; Vohryzek, Jakub; Verschure, Paul F. M. J.
Stroke-related disruptions in functional connectivity (FC) often spread beyond lesioned areas and, given the localized nature of lesions, it is unclear how the recovery of FC is orchestrated on a global scale. Since recovery is accompanied by long-term changes in excitability, we propose excitatory-inhibitory (E-I) homeostasis as a driving mechanism. We present a large-scale model of the neocortex, with synaptic scaling of local inhibition, showing how E-I homeostasis can drive the post-lesion restoration of FC and linking it to changes in excitability. We show that functional networks could reorganize to recover disrupted modularity and small-worldness, but not network dynamics, suggesting the need to consider forms of plasticity beyond synaptic scaling of inhibition. On average, we observed widespread increases in excitability, with the emergence of complex lesion-dependent patterns related to biomarkers of relevant side effects of stroke, such as epilepsy, depression and chronic pain. In summary, our results show that the effects of E-I homeostasis extend beyond local E-I balance, driving the restoration of global properties of FC, and relating to post-stroke symptomatology. Therefore, we suggest the framework of E-I homeostasis as a relevant theoretical foundation for the study of stroke recovery and for understanding the emergence of meaningful features of FC from local dynamics.
Structured dynamics in the algorithmic agent
(MDPI, 2025) Ruffini, Giulio; Castaldo, Francesca; Vohryzek, Jakub
In the Kolmogorov Theory of Consciousness, algorithmic agents utilize inferred compressive models to track coarse-grained data produced by simplified world models, capturing regularities that structure subjective experience and guide action planning. Here, we study the dynamical aspects of this framework by examining how the requirement of tracking natural data drives the structural and dynamical properties of the agent. We first formalize the notion of a generative model using the language of symmetry from group theory, specifically employing Lie pseudogroups to describe the continuous transformations that characterize invariance in natural data. Then, adopting a generic neural network as a proxy for the agent dynamical system and drawing parallels to Noether's theorem in physics, we demonstrate that data tracking forces the agent to mirror the symmetry properties of the generative world model. This dual constraint on the agent's constitutive parameters and dynamical repertoire enforces a hierarchical organization consistent with the manifold hypothesis in the neural network. Our findings bridge perspectives from algorithmic information theory (Kolmogorov complexity, compressive modeling), symmetry (group theory), and dynamics (conservation laws, reduced manifolds), offering insights into the neural correlates of agenthood and structured experience in natural systems, as well as the design of artificial intelligence and computational models of the brain.
N,N-dimethyltryptamine effects on connectome harmonics, subjective experience and comparative psychedelic experiences
(Nature Research, 2025) Vohryzek, Jakub; Luppi, Andrea I.; Atasoy, Selen; Deco, Gustavo; Carhart-Harris, Robin L.; Timmermann, Christopher; Kringelbach, Morten L.
Exploring the intricate relationship between brain's structure and function, and how this affects subjective experience is a fundamental pursuit in neuroscience. Psychedelic substances offer a unique insight into the influences of specific neurotransmitter systems on perception, cognition and consciousness. Specifically, their impact on brain function propagates across the structural connectome - a network of white matter pathways linking different regions. To comprehensively grasp the effects of psychedelic compounds on brain function, we used a theoretically rigorous framework known as connectome harmonic decomposition. This framework provides a robust method to characterize how brain function intricately depends on the organized network structure of the human connectome. We show that the connectome harmonic repertoire under N,N-dimethyltryptamine (DMT) is reshaped in line with other reported psychedelic compounds - psilocybin, lysergic acid diethylamide (LSD) and ketamine. Furthermore, we show that the repertoire entropy of connectome harmonics increases under DMT, as with those other psychedelics. Importantly, we demonstrate for the first time that measures of energy spectrum difference and repertoire entropy of connectome harmonics index the intensity of subjective experience of the participants in a time-resolved manner reflecting close coupling between connectome harmonics and subjective experience.
Connectome harmonic decomposition tracks the presence of disconnected consciousness during ketamine-induced unresponsiveness
(Elsevier, 2025) Van Maldegem, Milan; Vohryzek, Jakub; Atasoy, Selen; Alnagger, Naji; Cardone, Paolo; Bonhomme, Vincent; Vanhaudenhuyse, Audrey; Demertzi, Athena; Jaquet, Oceane; Bahri, Mohamed Ali; Nunez, Pablo; Kringelbach, Morten L.; Stamatakis, Emmanuel A.; Luppi, Andrea I.
Background: Ketamine, in doses suitable to induce anaesthesia in humans, gives rise to a unique state of unresponsiveness accompanied by vivid experiences and sensations, making it possible to disentangle the correlated but distinct concepts of conscious awareness and behavioural responsiveness. This distinction is often overlooked in the study of consciousness. Methods: The mathematical framework of connectome harmonic decomposition (CHD) was used to view functional magnetic resonance imaging (fMRI) signals during ketamine-induced unresponsiveness as distributed patterns across spatial scales. The connectome harmonic signature of this particular state was mapped onto signatures of other states of consciousness for comparison. Results: An increased prevalence of fine-grained connectome harmonics was found in fMRI signals obtained during ketamine-induced unresponsiveness, indicating higher granularity. After statistical assessment, the ketamine sedation harmonic signature showed alignment with signatures of LSD-induced (fixed effect =0.0113 [0.0099, 0.0127], P<0.001) or ketamine-induced (fixed effect =0.0087 [0.0071, 0.0103], P<0.001) psychedelic states, and misalignment with signatures seen in unconscious individuals owing to propofol sedation (fixed effect =–0.0213 [–0.0245, –0.0181], P<0.001) or brain injury (fixed effect =–0.0205 [–0.0234, –0.0178], P<0.001). Conclusions: The CHD framework, which only requires resting-state fMRI data and can be applied retrospectively, has the ability to track alterations in conscious awareness in the absence of behavioural responsiveness on a group level. This is possible because of ketamine's unique property of decoupling these two facets, and is important for consciousness and anaesthesia research.
Linking birth experience and perinatal depression symptoms to neuroanatomical changes in hippocampus and amygdala
(American Association for the Advancement of Science (AAAS), 2025) Ballesteros, Cristina; Paternina-Die, María; Martínez-García, Magdalena; López Montoya, Gonzalo; Noguero, Inés; Desco, Manuel; Vilarroya, Óscar; Martín de Blas, Daniel; Carmona, Susanna
Childbirth is a life-changing event in a mother's life. While the transition to motherhood has recently been recognized as one of the most neuroplastic periods in adulthood, no study has yet explored whether the hippocampus and amygdala change during the peripartum in relation to childbirth experience and perinatal depression symptoms. In this longitudinal neuroimaging study, we assessed 88 first-time gestational mothers in late pregnancy and early postpartum and 30 nulliparous control women. We used optimized high-resolution MRI scans to quantify volumetric changes in the hippocampus and amygdala, along with their substructures. We found that increases in depression symptoms during the peripartum were positively correlated with changes in the right amygdala. A more challenging birth experience was associated with bilateral increases in hippocampal volume. These findings show that studying the neuroanatomical changes during the transition to motherhood can inform not only about adaptive processes but also about potential vulnerabilities, highlighting the importance of tracking perinatal experiences to enhance women's health.
Dynamic legitimacy in territorial conflicts
(Taylor & Francis, 2026) Daniels, Lesley-Ann ; Sanjaume Calvet, Marc
Legitimacy plays a critical role in secessionist conflicts, which are per se a struggle about the territorial status of the people and its government alongside the degree of international recognition. This article examines how legitimacy is claimed by political actors during and after conflict, using the case study of Aceh secessionism. Taking a relational interpretation of legitimacy, we argue that rebels create it using different legitimacy resources and dependent on the audience and the context. During conflict, rebels use parallel narrow legitimation strategies that do not overlap. In the post-conflict period, rebels need to appeal to a broader audience but there is more competition for legitimacy. When rebels prioritise a restricted audience, this strategy requires trade-offs and carries substantial costs, and so stores up illegitimacy for the future. Our findings build on the previous literature on the dynamic nature of legitimacy changes in conflicts and suggest that legitimacy is more malleable and fluid than previously recognised. These findings have implications for international support for post-conflict groups in clashes on territorial status.
Early differentiation of mesenchymal stem cells is reflected in their dielectrophoretic behavior
(Nature Research, 2024) Tivig, Ioan; Vallet, Leslie; Moisescu, Mihaela G.; Fernandes, Romain; Andre, Franck M.; Mir, Lluis M.; Savopol, Tudor
The therapeutic use of mesenchymal stem cells (MSCs) becomes more and more important due to their potential for cell replacement procedures as well as due to their immunomodulatory properties. However, protocols for MSCs differentiation can be lengthy and may result in incomplete or asynchronous differentiation. To ensure homogeneous populations for therapeutic purposes, it is crucial to develop protocols for separation of the different cell types after differentiation. In this article we show that, when MSCs start to differentiate towards adipogenic or osteogenic progenies, their dielectrophoretic behavior changes. The values of cell electric parameters which can be obtained by dielectrophoretic measurements (membrane permittivity, conductivity, and cytoplasm conductivity) change before the morphological features of differentiation become microscopically visible. We further demonstrate, by simulation, that these electric modifications make possible to separate cells in their early stages of differentiation by using the dielectrophoretic separation technique. A label free method which allows obtaining cultures of homogenously differentiated cells is thus offered.
Calcium oscillations in mesenchymal stem cells, a control on cell cycle progression to influence cell fate towards proliferation or differentiation?
(Springer, 2025) Vallet, Leslie A.; Sánchez-Petidier, Marina; Fernandes, Romain; Naumova, Nataliia; Merla, Caterina; Consales, Claudia; Innamorati, Giorgia; André, Franck M.; Mir, Lluis M.
Background: Under regular culture conditions, mesenchymal stem cells (MSCs) exhibit cytosolic calcium concentration oscillations (Ca oscillations), that change, especially in frequency, after the differentiation of the MSCs. Ca oscillations are known to encode important information in frequency and amplitude, ultimately controlling many cellular processes such as proliferation and differentiation. Previous studies evidenced that decreasing the frequency of Ca oscillations by physical means can facilitate osteodifferentiation of MSCs. Understanding the relationships between Ca oscillations and MSCs proliferation or differentiation appears necessary in the attractive perspective of influencing cell fate by controlling Ca signaling. Methods: Using fluorescence microscopy we evaluated the evolution of Ca oscillations throughout the adipogenic and osteogenic differentiation processes. Then, using electrical stimulation with microsecond pulsed electric fields (µsPEFs), we manipulated the frequency of Ca oscillations in MSCs and measured its consequences on cell growth. Results: Although the evolution of the Ca oscillation frequencies differed between the adipogenic and osteogenic differentiation pathways in early stages of differentiation, we observed common features in the late stages: a progressive decrease in the Ca oscillations frequencies, before their complete arrest as the differentiations reached their term. It has been reported that most cells undergoing differentiation experience a concomitant commitment to terminal differentiation and cell cycle exit, and prior to this, lengthened G1 phases, where the molecular competition between mitogenic and differentiating signals occurs. A relationship between the frequency of Ca oscillations and the progression of the cell cycle, through some Ca sensitive molecular factors, could explain the evolutions of the frequencies of Ca oscillations observed during proliferation and differentiation. We hypothesized that increasing the frequency of Ca oscillations would promote proliferation, while decreasing it would promote differentiation under differentiating conditions. Using electrical stimulation with µsPEFs, we manipulated the frequency of Ca oscillations in MSCs and its increase actually promoted cell proliferation. Conclusions: Manipulating the frequency of Ca oscillations influences the cell fate of MSCs. We propose hypotheses on the actors that could link the Ca oscillation frequencies with proliferation and differentiation processes, based on data available in the literature.
Spin structure of heavy-quark hybrids
(American Physical Society, 2019) Brambilla, Nora; Lai, Wai Kin; Segovia, Jorge; Tarrús Castellà, Jaume; Vairo, Antonio
A unique feature of quantum chromodynamics (QCD), the theory of strong interactions, is the possibility for gluonic degrees of freedom to participate in the construction of physical hadrons, which are color singlets, in an analogous manner to valence quarks. Hadrons with no valence quarks are called glueballs, while hadrons where both gluons and valence quarks combine to form a color singlet are called hybrids. The unambiguous identification of such states among the experimental hadron spectrum has been thus far not possible. Glueballs are particularly difficult to establish experimentally since the lowest lying ones are expected to strongly mix with conventional mesons. On the other hand, hybrids should be easier to single out because the set of quantum numbers available to their lowest excitations may be exotic, i.e., not realized in conventional quark-antiquark systems. Particularly promising for discovery appear to be heavy hybrids, which are made of gluons and a heavy-quark-antiquark pair (charm or bottom). In the heavy-quark sector systematic tools can be used that are not available in the light-quark sector. In this paper we use a nonrelativistic effective field theory to uncover for the first time the full spin structure of heavy-quark hybrids up to 1/m2-terms in the heavy-quark-mass expansion. We show that such terms display novel characteristics at variance with our consolidated experience on the fine and hyperfine splittings in atomic, molecular and nuclear physics. We determine the nonperturbative contributions to the matching coefficients of the effective field theory by fitting our results to lattice-QCD determinations of the charmonium hybrid spectrum and extrapolate the results to the bottomonium hybrid sector where lattice-QCD determinations are still challenging.
QCD spin effects in the heavy hybrid potentials and spectra
(American Physical Society, 2020) Brambilla, Nora; Lai, Wai Kin; Segovia, Jorge; Tarrús Castellà, Jaume
The spin-dependent operators for heavy quarkonium hybrids have been recently obtained in a nonrelativistic effective field theory approach up to next-to-leading order in the heavy-quark mass expansion. In the effective field theory for hybrids several operators not found in standard quarkonia appear, including an operator suppressed by only one power of the heavy-quark mass. We compute the matching coefficients for these operators in the short heavy-quark-antiquark distance regime, r>>1/AQCD, by matching weakly coupled potential nonrelativistic QCD to the effective field theory for hybrids. In this regime the perturbative and nonperturbative contributions to the matching coefficients factorize, and the latter can be expressed in terms of purely gluonic correlators whose form we explicitly calculate with the aid of the transformation properties of the gluon fields under discrete symmetries. We detail our previous comparison with direct lattice computations of the charmonium hybrid spectrum, from which the unknown nonperturbative contributions can be obtained, and extend it to datasets with different light-quark masses.

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