arXiv subjects

Saikat Banerjee

Publications and source records attributed to Saikat Banerjee.

At least 19 recordsLinked to original sources

arXiv2026

Light-driven octupolar inverse Faraday effect and multipolar order in Mott insulators

Hidden multipolar orders in spin-orbit-coupled Mott insulators provide a promising setting for correlated quantum matter, yet their control and detection remain major challenges. Here, we demonstrate that circularly polarized light enables both in $4d^2/5d^2$ systems with edge-sharing octahedra. Using a Floquet Schrieffer-Wolff expansion of a driven Hubbard-Kanamori model, we derive a low-energy multipolar Hamiltonian with two qualitatively new light-driven terms. One is an effective static field that couples linearly to the magnetic octupole, realizing an octupolar inverse Faraday effect. The other is a bond-dependent anisotropic exchange interaction absent in equilibrium. These two couplings are the key result of this work: the first provides a direct optical handle on hidden octupolar order, while the second reorganizes the multipolar exchange landscape and opens an enlarged Kitaev-like multipolar liquid regime. Their interplay produces a nonequilibrium multipolar phase space inaccessible in equilibrium, enabling optical tuning among antiferro-octupolar, ferro-octupolar, partially polarized ferro-quadrupolar, Ising octupolar, and multipolar liquid phases. We further show that the induced multipolar order couples to the lattice, generating reversible trigonal and tetragonal distortions that provide structural fingerprints in pump-probe experiments. Our work establishes a general mechanism for the optical generation, control, and detection of hidden multipolar quantum states.

cond-mat.str-el↗

arXiv2026

Minimal spin-rotor model for Barnett and Einstein--de Haas physics

The Barnett effect is usually understood through an effective magnetic field generated by mechanical rotation, while its reciprocal Einstein--de Haas effect describes the transfer of spin angular momentum to mechanical motion. We show that this effective-field picture changes qualitatively once the mechanical degree of freedom itself is quantized. To demonstrate this, we introduce an exactly solvable minimal spin-rotor model in which a spin-$1/2$ is coupled to a quantum rotor. In a fixed angular-momentum sector, the model reproduces the conventional Barnett splitting and remains formally equivalent to a Zeeman problem. For a superposition of rotor sectors, however, the Barnett field becomes operator-valued and the resulting dynamics generates coherent spin-rotor entanglement. This is directly visible in the reduced spin purity, rotor coherence, and entanglement entropy. Our results identify a minimal quantum setting in which the Barnett effective-field picture departs from its classical form and acquires a reciprocal manifestation through spin-dependent rotor coherence.

quant-ph↗

arXiv2025

Axionic tunneling from a topological Kondo insulator

Discoveries over the past two decades have revealed the remarkable ability of quantum materials to emulate relativistic properties of the vacuum, from Dirac cones in graphene to the Weyl surface states of topological insulators. Yet the most elusive consequence of topology in quantum matter is the axionic $E\cdot B$ term in the electromagnetic response. Here we report a direct signature of axionic physics obtained through scanning tunneling microscopy (STM). Although recent STM experiments using SmB$_6$ nanowires have been interpreted as evidence for spin-polarized currents arising from topological surface states, we show that the observed spin polarization instead originates from axionic electrodynamics. Our analysis reveals a striking voltage-induced magnetization: extremely small voltages ($\sim$ 30 meV) generate tip moments of order 0.1 $\mu_B$ that reverse sign with the applied bias. The magnitude, tunability, and reversibility of this signal are consistent with an axionic $E \cdot B$ coupling, and fully account for the magnetic component of the tip density of states, ruling out static magnetism. Millivolt-scale control of spin polarization in a tunnel junction provides a new route for probing axionic electrodynamics and opens avenues for future STM and spintronics applications.

cond-mat.mes-hall↗

arXiv2025

Eight-fold classification of superconducting orders

We present a symmetry-based classification for superconducting pairing states, organized by the exchange properties of the anomalous correlation function rather than by a specific microscopic pairing mechanism. The classification is built from the pairwise permutation of spin, orbital, spatial, and temporal indices, leading to the fermionic constraint ${\cal S} {\cal P}^\ast {\cal O} {\cal T}^\ast = -1$, and is further organized by separating relative and center-of-mass space-time coordinates. This construction defines what we call the Berezinskii--Abrahams hypercube, in which conventional Bardeen--Cooper--Schrieffer superconductivity, unconventional $p$- and $d$-wave pairing, odd-frequency superconductivity, Fulde--Ferrell--Larkin--Ovchinnikov states, pair-density-wave states, and time-modulated superconducting orders appear as different sectors of a unified framework. Beyond organizing known phases, the Berezinskii--Abrahams hypercube identifies symmetry-allowed hybrid orders that have received comparatively little attention, including odd-frequency Fulde--Ferrell--Larkin--Ovchinnikov or pair-density-wave states and odd-frequency time-modulated superconducting states. We discuss microscopic routes, candidate platforms, experimental signatures, and stability constraints for these sectors, emphasizing the distinction between symmetry allowance and physical realizability. We also present the proximity induced odd-frequency pair-density-wave state, and its driven analog as the two new examples of the states that naturally emerge in the Berezinskii--Abrahams hypercube. The resulting framework provides a guide for connecting established superconducting phenomena with unexplored symmetry-allowed forms of order.

cond-mat.supr-con↗

arXiv2025

Correlated Electrons and Magnetism in Double Perovskites

This paper is an overview of some recent work done on the double perovskites. We discuss the physics of selected double perovskite compounds emphasizing the relevant interactions and resulting observable phenomena such as the magnetic order using different theoretical approaches. Spin-Orbit interaction, which is comparable to other relevant interaction strengths, plays a central role in determining the physics of such 4d-5d perovskites.

cond-mat.str-el↗

arXiv2025

Interacting Dirac magnons in the van der Waals ferromagnet CrBr$_3$

We study the effects of magnon-magnon interactions in the two-dimensional van der Waals ferromagnet CrBr$_3$ focusing on its honeycomb lattice structure. Motivated by earlier theoretical predictions of temperature-induced spectral shifts and van Hove singularities in the magnon dispersion~[S. S. Pershoguba \textit{et al}., Dirac Magnons in Honeycomb Ferromagnets, \href{https://journals.aps.org/prx/abstract/10.1103/PhysRevX.8.011010}{Phys. Rev. X {\textbf{8}}, 011010 (2018)}], we go beyond the commonly used thermal magnon approximation by applying second-order perturbation theory in a fully numerical framework. Our analysis uncovers significant deviations from previous analysis: in particular, the predicted singularities are absent, consistent with recent inelastic neutron scattering measurements~[S. E. Nikitin \textit{et al}., Thermal Evolution of Dirac Magnons in the Honeycomb Ferromagnet CrBr$_3$, \href{https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.129.127201}{Phys. Rev. Lett. {\textbf{129}}, 127201 (2022)}]. Moreover, we find that the temperature dependence of the renormalized magnon spectrum exhibits a distinct $T^3$ behavior for the optical magnon branch, while retaining $T^2$ behavior for the acoustic or down magnon band. This feature sheds new light on the collective dynamics of Dirac magnons and their interactions. We further compare the honeycomb case with a triangular Bravais lattice, relevant for ferromagnetic monolayer MnBi$_2$Te$_4$, and show that both systems lack singular features while displaying quite distinct thermal trends.

cond-mat.mtrl-sci↗

arXiv2025

Resolving the Thermal Paradox: Many-body localization or fractionalization?

Thermal measurements of heat capacity and thermal conductivity in a wide range of insulators and superconductors exhibit a ``thermal paradox": a large linear specific heat reminiscent of neutral Fermi surfaces in samples that exhibit no corresponding linear temperature coefficient to the thermal conductivity. At first sight, these observations appear to support the formation of a continuum of thermally localized many-body excitations, a form of many-body localization that would be fascinating in its own right. Here, by mapping thermal conductivity measurements onto thermal RC circuits, we argue that the development of extremely long thermal relaxation times, a ``thermal bottleneck," is likely in systems with either many-body localization or neutral Fermi surfaces due to the large ratio between the electron and phonon specific heat capacities. We present a re-evaluation of thermal conductivity measurements in materials exhibiting a thermal paradox that can be used in future experiments to deliberate between these two exciting alternatives.

cond-mat.str-el↗

arXiv2024

Gradient-based optimization for variational empirical Bayes multiple regression

Variational empirical Bayes (VEB) methods provide a practically attractive approach to fitting large, sparse, multiple regression models. These methods usually use coordinate ascent to optimize the variational objective function, an approach known as coordinate ascent variational inference (CAVI). Here we propose alternative optimization approaches based on gradient-based (quasi-Newton) methods, which we call gradient-based variational inference (GradVI). GradVI exploits a recent result from Kim et. al. [arXiv:2208.10910] which writes the VEB regression objective function as a penalized regression. Unfortunately the penalty function is not available in closed form, and we present and compare two approaches to dealing with this problem. In simple situations where CAVI performs well, we show that GradVI produces similar predictive performance, and GradVI converges in fewer iterations when the predictors are highly correlated. Furthermore, unlike CAVI, the key computations in GradVI are simple matrix-vector products, and so GradVI is much faster than CAVI in settings where the design matrix admits fast matrix-vector products (e.g., as we show here, trendfiltering applications) and lends itself to parallelized implementations in ways that CAVI does not. GradVI is also very flexible, and could exploit automatic differentiation to easily implement different prior families. Our methods are implemented in an open-source Python software, GradVI (available from https://github.com/stephenslab/gradvi ).

stat.ME↗

arXiv2024

Multipolar multiferroics in $4d^2$/$5d^2$ Mott insulators

We extend the concept of conventional multiferroicity \ -- where ferroelectric and ferromagnetic orders coexist \ -- to include multipolar degrees of freedom. Specifically, we explore how this phenomenon emerges in $4d^2/5d^2$ Mott insulators with strong spin-orbit and Hund's couplings. Our study uncovers the origin of magnetic multipolar interactions in these systems and demonstrates that a combination of quadrupolar and octupolar magnetic order can simultaneously induce both electrical quadrupolar moments and ferroelectric polarization. By expanding the multiferroic framework to higher-order multipoles, we reveal the possibility of coexisting multipolar orders of different or same ranks, paving the way for new functional properties in a large class of strongly correlated materials.

cond-mat.str-el↗

arXiv2024

Higher-order topological corner and bond-localized modes in magnonic insulators

We theoretically investigate a two-dimensional decorated honeycomb lattice framework to realize a second-order topological magnon insulator (SOTMI) phase featuring distinct corner-localized modes. Our study emphasizes the pivotal role of spin-magnon mapping in characterizing bosonic topological properties, which exhibit differences from their fermionic counterparts. We employ a symmetry indicator topological invariant to identify and characterize this SOTMI phase, particularly for systems respecting time-reversal and ${\sf{C}}_6$ rotational symmetry. Using a spin model defined on a honeycomb lattice geometry, we demonstrate that introducing ``\textit{kekulé}'' type distortions yields a topological phase. In contrast, ``\textit{anti-kekulé}'' distortions result in a non-topological magnonic phase. The presence of kekulé distortions manifests in two distinct topologically protected bosonic corner modes - an \textit{intrinsic} and a \textit{pseudo}, based on the specific edge terminations. On the other hand, anti-kekulé distortions give rise to \SW{\textit{Tamm/Shockley}} type bond-localized boundary modes, which are non-topological and reliant on particular edge termination. We further investigate the effects of random out-of-plane exchange anisotropy disorder on the robustness of these bosonic corner modes. The distinction between SOTMIs and their fermionic counterparts arises due to the system-specific magnonic onsite energies, a crucial feature often overlooked in prior literature. Our study unveils exciting prospects for engineering higher-order topological phases in magnon systems and enhances our understanding of their unique behavior within decorated honeycomb lattices.

cond-mat.mes-hall↗

arXiv2023

Superposed periodic kink and pulse solutions of coupled nonlinear equations

We present novel previously unexplored periodic solutions, expressed in terms of Jacobi elliptic functions, for both a coupled $ϕ^4$ model and a coupled nonlinear Schrödinger equation (NLS) model. Remarkably, these solutions can be elegantly reformulated as a linear combination of periodic kinks and antikinks, or as a combination of two periodic kinks or two periodic pulse solutions. However, we also find that for $m=0$ and a specific value of the periodicity (or at a nonzero value of the elliptic modulus $m$) this superposition does not hold. These results demonstrate that the notion of superposed solutions extends to the coupled nonlinear equations as well.

nlin.SI↗

arXiv2023

New static solutions of symmetric $ϕ^4$ equation

In this paper, we provide new exact solutions of nonlinear Klein-Gordon ($ϕ^4$) equation in $1+1$-dimension. For simplicity, we focus on the static equation and ignore the time-dependence. The symmetric $ϕ^4$ equation has played an important role in several areas of physics. We obtain several novel non-singular solutions of the symmetric $ϕ^4$ model in terms of the Jacobi elliptic functions and compare them with the well-known solutions. Finally, we categorize these solutions in terms of the potential parameters.

nlin.SI↗

arXiv2023

Electromagnetic signatures of chiral quantum spin liquid

Quantum spin liquid (QSL) has become an exciting topic in interacting spin systems that do not order magnetically down to the lowest experimentally accessible temperature; however, conclusive experimental evidence remains lacking. Motivated by the recent surge of theoretical and experimental interest in a half-filled Hubbard model on the triangular lattice, where chiral QSL can be stabilized, we investigate the electromagnetic signature of the chiral QSL to aid experimental detection. We systematically studied the electrical charge and orbital electrical current associated with a spinon excitation in the chiral QSL based on parton mean-field theory and unbiased density-matrix renormalization group calculations. We then calculated both longitudinal and transverse optical conductivities below the Mott gap. We also conduct quantum field theory analysis to unravel the connection between spinon excitation and emergent and physical gauge fields. Our results show that the chiral QSL phase has a clear electromagnetic response even in a Mott insulator regime, which can facilitate the experimental detection of this long-sought-after phase.

cond-mat.str-el↗

arXiv2023

Mesoscopic critical fluctuations

We investigate magnetic fluctuations of a mesoscopic critical region at the interface induced by smooth time-independent spacial changes of a control parameter across its critical value. Near the spatial critical point, the order parameter fluctuations are mesoscopic, i.e., much larger than the lattice constant but decaying away from the critical region. We propose a minimal model to describe this behavior and show that it leads to the integrable Painlevé-II equation for the local order parameter. We argue that known mathematical properties of this equation produce insight into the nonlinear susceptibilities of this region.

cond-mat.mes-hall↗

arXiv2023

Dependence of Physiochemical Features on Marine Chlorophyll Analysis with Learning Techniques

Marine chlorophyll which is present within phytoplankton are the basis of photosynthesis and they have a high significance in sustaining ecological balance as they highly contribute toward global primary productivity and comes under the food chain of many marine organisms. Imbalance in the concentrations of phytoplankton can disrupt the ecological balance. The growth of phytoplankton depends upon the optimum concentrations of physiochemical constituents like iron, nitrates, phosphates, pH level, salinity, etc. and deviations from an ideal concentration can affect the growth of phytoplankton which can ultimately disrupt the ecosystem at a large scale. Thus the analysis of such constituents has high significance to estimate the probable growth of marine phytoplankton. The advancements of remote sensing technologies have improved the scope to remotely study the physiochemical constituents on a global scale. The machine learning techniques have made it possible to predict the marine chlorophyll levels based on physiochemical properties and deep learning helped to do the same but in a more advanced manner simulating the working principle of a human brain. In this study, we have used machine learning and deep learning for the Bay of Bengal to establish a regression model of chlorophyll levels based on physiochemical features and discussed its reliability and performance for different regression models. This could help to estimate the amount of chlorophyll present in water bodies based on physiochemical features so we can plan early in case there arises a possibility of disruption in the ecosystem due to imbalance in marine phytoplankton.

q-bio.QM↗

arXiv2023

COVID-19 Spreading Prediction and Impact Analysis by Using Artificial Intelligence for Sustainable Global Health Assessment

The COVID-19 pandemic is considered as the most alarming global health calamity of this century. COVID-19 has been confirmed to be mutated from coronavirus family. As stated by the records of The World Health Organization (WHO at April 18 2020), the present epidemic of COVID-19, has influenced more than 2,164,111 persons and killed more than 146,198 folks in over 200 countries across the globe and billions had confronted impacts in lifestyle because of this virus outbreak. The ongoing overall outbreak of the COVID-19 opened up new difficulties to the research sectors. Artificial intelligence (AI) driven strategies can be valuable to predict the parameters, hazards, and impacts of such an epidemic in a cost-efficient manner. The fundamental difficulties of AI in this situation is the limited availability of information and the uncertain nature of the disease. Here in this article, we have tried to integrate AI to predict the infection outbreak and along with this, we have also tried to test whether AI with help deep learning can recognize COVID-19 infected chest X-Rays or not. The global outbreak of the virus posed enormous economic, ecological and societal challenges into the human population and with help of this paper, we have tried to give a message that AI can help us to identify certain features of the disease outbreak that could prove to be essential to protect the humanity from this deadly disease.

cs.AI↗

arXiv2023

Automatized marine vessel monitoring from sentinel-1 data using convolution neural network

The advancement of multi-channel synthetic aperture radar (SAR) system is considered as an upgraded technology for surveillance activities. SAR sensors onboard provide data for coastal ocean surveillance and a view of the oceanic surface features. Vessel monitoring has earlier been performed using Constant False Alarm Rate (CFAR) algorithm which is not a smart technique as it lacks decision-making capabilities, therefore we introduce wavelet transformation-based Convolution Neural Network approach to recognize objects from SAR images during the heavy naval traffic, which corresponds to the numerous object detection. The utilized information comprises Sentinel-1 SAR-C dual-polarization data acquisitions over the western coastal zones of India and with help of the proposed technique we have obtained 95.46% detection accuracy. Utilizing this model can automatize the monitoring of naval objects and recognition of foreign maritime intruders.

cs.CV↗

arXiv2023

Emergent orbital magnetization in Kitaev quantum magnets

Unambiguous identification of the Kitaev quantum spin liquid (QSL) in materials remains a huge challenge despite many encouraging signs from various measurements. To facilitate the experimental detection of the Kitaev QSL, here we propose to use remnant charge response in Mott insulators hosting QSL to identify the key signatures of QSL. We predict an emergent orbital magnetization in a Kitaev system in an external magnetic field. The direction of the orbital magnetization can be flipped by rotating the external magnetic field in the honeycomb plane. The orbital magnetization is demonstrated explicitly through a detailed microscopic analysis of the multiorbital Hubbard-Kanamori Hamiltonian and also supported by a phenomenological picture. We first derive the localized electrical loop current operator in terms of the spin degrees of freedom. Thereafter, utilizing the Majorana representation, we estimate the loop currents in the ground state of the chiral Kitaev QSL state, and obtain the consequent current textures, which are responsible for the emergent orbital magnetization. Finally, we discuss the possible experimental techniques to visualize the orbital magnetization which can be considered as the signatures of the underlying excitations.

cond-mat.str-el↗