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Sourin Chatterjee

Publications and source records attributed to Sourin Chatterjee.

10 recordsLinked to original sources

Semi-Dirac spin liquids and frustrated quantum magnetism on the trellis lattice

Geometrical frustration in quantum magnets provides a fertile setting for unconventional phases of matter, including quantum spin liquids (QSLs). The trellis lattice, with its complex site arrangements and edge-sharing triangular motifs, presents a promising platform for such physics. In this work, we undertake a comprehensive classification of all fully symmetric QSLs on the trellis lattice using the projective symmetry group approach within the Abrikosov-fermion representation. We find 7 U(1) and 25 $Z_2$ short-ranged Ans\"atze and analyze the phase diagram in the mean-field parameter space, uncovering both gapped and Dirac QSLs as well as a semi-Dirac spin liquid that emerges at the level of projective symmetry group classification and mean-field band structure, in which the spinon dispersion is linear along one momentum direction but quadratic along the orthogonal one. We demonstrate that such dispersions can occur only at high-symmetry points in the Brillouin zone with $C_{2v}$ little groups and analyze their characteristic correlation signatures. Moreover, by optimizing over all symmetry-allowed mean-field states, we map out a phase diagram -- featuring six distinct phases -- of the nearest-neighbor Heisenberg Hamiltonian on the trellis lattice. Among these, we find four quasi-one-dimensional QSL phases, one dimer phase, and one Dirac QSL phase. Going beyond mean field, we also assess equal-time and dynamical spin structure factors of these phases using density-matrix renormalization group and Keldysh pseudofermion functional renormalization group calculations and compare qualitative momentum-space features of these spectra with those obtained at the mean-field level. Finally, we identify four cuprate and vanadate compounds as promising experimental realizations and provide spectroscopic predictions, based on first-principles Hamiltonians, as a guide for neutron-scattering studies.

cond-mat.str-el

Topological phase transition in anti-symmetric Lotka-Volterra doublet chain

We present the emergence of topological phase transition in the minimal model of two dimensional rock-paper-scissors cycle in the form of a doublet chain. The evolutionary dynamics of the doublet chain is obtained by solving the anti-symmetric Lotka-Volterra equation. We show that the mass decays exponentially towards edges and robust against small perturbation in the rate of change of mass transfer, a signature of a topological phase. For one of the configuration of our doublet chain, the mass is transferred towards both edges and the bulk is gaped. Further, we confirm this phase transition within the framework of topological band theory. For this we calculate the winding number which change from zero to one for trivial and a non-trivial topological phases respectively.

cond-mat.stat-mech

Fairness, not Emotion, Drives Socioeconomic Decision Making

Emotion and fairness play a key role in mediating socioeconomic decisions in humans; however, the underlying neurocognitive mechanism remains largely unknown. This exploratory study unraveled the interplay between agents' emotions and the fairness of their monetary proposal in rational decision-making, backed by ERP analyses at a group as well as a strategic level. In a time-bound ultimatum-game paradigm, 40 participants were exposed to three distinct proposers' emotions (Happy, Neutral, Disgusted) followed by one of the three offer ranges (Low, Intermediate, High). Our findings show a robust influence of economic fairness on acceptance rates. A multilevel generalized linear model showed offer as the dominant predictor of trial-specific responses. Subsequent clustering grouped participants into five clusters, which the Drift Diffusion Model corroborates. Pertinent neural markers demonstrated the recognition of facial expressions; however, they had minimal effect during socioeconomic decision-making. Our study explores individualistic decision-making processes revealing different cognitive strategies.

q-bio.NC

How Combined Pairwise and Higher-Order Interactions Shape Transient Dynamics

Understanding how species interactions shape biodiversity is a core challenge in ecology. While much focus has been on long-term stability, there is rising interest in transient dynamics-the short-lived periods when ecosystems respond to disturbances and adjust toward stability. These transitions are crucial for predicting ecosystem reactions and guiding effective conservation. Our study introduces a model that uses convex combinations to blend pairwise and higher-order interactions, offering a more realistic view of natural ecosystems. We find pairwise interactions slow the journey to stability, while higher-order interactions speed it up. Employing global stability analysis and numerical simulations, we establish that as the proportion of higher-order interactions (HOIs) increases, mean transient times exhibit a significant reduction, thereby underscoring the essential role of HOIs in enhancing biodiversity stabilization. Our results reveal a robust correlation between the most negative real part of the eigenvalues of the Jacobian matrix associated with the linearized system at the coexistence equilibrium and the mean transient times. This indicates that a more negative leading eigenvalue correlates with accelerated convergence to stable coexistence abundances. This insight is vital for comprehending ecosystem resilience and recovery, emphasizing the key role of HOIs in promoting stabilization. Amid growing interest in transient dynamics and its implications for biodiversity and ecological stability, our study enhances the understanding of how species interactions affect both transient and long-term ecosystem behavior. By addressing a critical gap in ecological theory and offering a practical framework for ecosystem management, our work advances knowledge of transient dynamics, ultimately informing effective conservation strategies.

q-bio.PE

A First Principles Approach to Trust-Based Recommendation Systems in Social Networks

This paper explores recommender systems in social networks which leverage information such as item rating, intra-item similarities, and trust graph. We demonstrate that item-rating information is more influential than other information types in a collaborative filtering approach. The trust graph-based approaches were found to be more robust to network adversarial attacks due to hard-to-manipulate trust structures. Intra-item information, although sub-optimal in isolation, enhances the consistency of predictions and lower-end performance when fused with other information forms. Additionally, the Weighted Average framework is introduced, enabling the construction of recommendation systems around any user-to-user similarity metric. All the codes are publicly available on GitHub.

cs.IR

A Novel Room-Based Epidemic Model: Quarantine, Testing, and Vaccination Strategies

Epidemic outbreaks pose significant challenges to public health and socio-economic stability, necessitating a comprehensive understanding of disease transmission dynamics and effective control strategies. This article discusses the limitations of traditional compartmental and network-based models and, inspired by the opinion formation models, introduces a room-based model that incorporates social gatherings and intuitive quarantine measures. Through simulations and analysis, we examine the impact of various model parameters, and confinement measures like quarantine and preventive measures like testing, and vaccination on disease spread. Additionally, we explore centrality-based testing and immunization strategies, demonstrating their effectiveness in reducing the spread of diseases compared to a random approach. Finally, we propose a combined strategy, that outperforms the existing strategies. It takes both global and local properties of the network structure into account, highlighting the potential for integrated control measures in epidemic management. This research not only contributes to a deeper understanding of epidemic models, but also provides insights into devising successful intervention strategies, including quarantine measures, testing methodologies, and vaccine programs to combat emerging epidemics and pandemics

physics.soc-ph

Neighbour Sum Patterns : Chessboards to Toroidal Worlds

We say that a chessboard filled with integer entries satisfies the neighbour-sum property if the number appearing on each cell is the sum of entries in its neighbouring cells, where neighbours are cells sharing a common edge or vertex. We show that an $n\times n$ chessboard satisfies this property if and only if $n\equiv 5\pmod 6$. Existence of solutions is further investigated of rectangular, toroidal boards, as well as on Neumann neighbourhoods, including a nice connection to discrete harmonic functions. Construction of solutions on infinite boards are also presented. Finally, answers to three dimensional analogues of these boards are explored using properties of cyclotomic polynomials and relevant ideas conjectured.

math.NT

Effective Vaccination Strategies in Network-based SIR Model

Controlling and understanding epidemic outbreaks has recently drawn great interest in a large spectrum of research communities. Vaccination is one of the most well-established and effective strategies in order to contain an epidemic. In the present study, we investigate a network-based virus-spreading model building on the popular SIR model. Furthermore, we examine the efficacy of various vaccination strategies in preventing the spread of infectious diseases and maximizing the survival ratio. The experimented strategies exploit a wide range of approaches such as relying on network structure centrality measures, focusing on disease-spreading parameters, and a combination of both. Our proposed hybrid algorithm, which combines network centrality and illness factors, is found to perform better than previous strategies in terms of lowering the final death ratio in the community on various real-world networks and synthetic graph models. Our findings particularly emphasize the significance of taking both network structure properties and disease characteristics into account when devising effective vaccination strategies.

cs.SI

Characterising Solutions of Anomalous Cancellation

Anomalous cancellation of fractions is a mathematically inaccurate method where cancelling the common digits of the numerator and denominator correctly reduces it. While it appears to be accidentally successful, the property of anomalous cancellation is intricately connected to the number of digits of the denominator as well as the base in which the fraction is represented. Previous work have been mostly surrounding three digit solutions or specific properties of the same. This paper seeks to get general results regarding the structure of numbers that follow the cancellation property (denoted by $P^*_{\ell; k}$) and an estimate of the total number of solutions possible in a given base representation. In particular, interesting properties regarding the saturation of the number of solutions in general and $p^n$ bases (where $p$ is a prime) have been studied in detail.

math.HO

Controlling species densities in structurally perturbed intransitive cycles with higher-order interactions

The persistence of biodiversity of species is a challenging proposition in ecological communities in the face of Darwinian selection. The present article investigates beyond the pairwise competitive interactions and provides a novel perspective for understanding the influence of higher-order interactions on the evolution of social phenotypes. Our simple model yields a prosperous outlook to demonstrate the impact of perturbations on intransitive competitive higher-order interactions. Using a mathematical technique, we show how alone the perturbed interaction network can quickly determine the coexistence equilibrium of competing species instead of solving a large system of ordinary differential equations. It is possible to split the system into multiple feasible cluster states depending on the number of perturbations. Our analysis also reveals the ratio between the unperturbed and perturbed species is inversely proportional to the amount of employed perturbation. Our results suggest that nonlinear dynamical systems and interaction topologies can be interplayed to comprehend species' coexistence under adverse conditions. Particularly our findings signify that less competition between two species increases their abundance and outperforms others.

q-bio.PE