Papers

We demonstrate the parametric modulation of a double quantum dot charge dipole coupled to a cavity, at the cavity frequency, achieving an amplified readout signal compared to conventional dispersive protocols. Our findings show that the observed cavity field displacement originates from dipole radiation within the cavity, rather than from a longitudinal coupling mechanism, yet exhibits the same signatures while relying on a transverse coupling. By carefully tuning the phase and amplitude of the intra-cavity field, we achieve a $\pi$-phase shift between two dipole states, resulting in a substantial enhancement of the signal-to-noise ratio. In addition to its applications in quantum dot based qubits in cQED architectures, this protocol could serve as a new promising tool for probing exotic electronic states in mesoscopic circuits embedded in cavities.

Dielectric metasurfaces can achieve strong light-matter interaction based on several types of collective (nonlocal) resonances, such as surface lattice resonances (SLRs) and quasi bound states in the continuum (quasi-BICs). Spectral selectivity, field enhancement, and high and controllable Q-factors make these resonances appealing for technological applications in lasing, sensing, nonlinear optics, and quantum photon sources. An emerging challenge focuses on tailoring light-matter interaction via mode coupling and hybridization between the fundamental resonances of a metasurface. While strong coupling phenomena have been demonstrated between various resonant modes, the interplay between collective resonances of different natures has not been observed to date. Here, we theoretically, numerically, and experimentally demonstrate the onset of coupling and hybridization between symmetry-protected quasi-BICs and SLRs in a dielectric metasurface. We show the emergence of anticrossing (or Rabi splitting) in the strong coupling regime with suppression of reflection, observed under TE-polarised excitation, and the manifestation of an accidental BIC under TM-polarised illumination as a result of energy exchange between the participating collective resonances in the weak coupling regime. The first effect is accompanied by hybridized near fields of the modes. The observed coupling mechanisms can be controlled by modifying the angle of incidence, polarisation, and surrounding environment. This foundational study on the coupling and hybridization of collective resonances offers insights that can be leveraged for the design of metasurfaces with targeted quasi-aBIC and collective hybridized resonances. It could also open new possibilities to control the near fields associated with such resonances, with promising applications in tunable nanophotonics and light manipulation.

High magnetic fields can increase the occurrence of vacuum arcing, suggesting that both electric and magnetic fields can play a role in the vacuum arcing process. The mechanism of vacuum arcing in high magnetic fields is believed to involve both the cathode and the anode, with the cathode serving as the originator of field-emitting nanoprotrusions or tips, while the anode serves a secondary role. Significant heating of the anode surface can be achieved by magnetic focusing of the emitted electron beam, leading to increased heat flux due to greater current density. We simulated the emitted electron beam in different configurations of the electric and magnetic fields using the particle-in-cell (PIC) and finite element methods (FEM). The heating caused by the impacting electron beam was simulated for magnetic fields ranging from 0 T to 30 T. The directions of the electric and magnetic fields were found to play a major role in the focusing of the electron beam. We found that a sufficient temperature increase on the anode surface for evaporation can be reached at magnetic fields on the order of 10-30 T, suggesting the possibility of plasma initiation on the anode side.

Ferrofluids, colloidal dispersions of magnetic nanoparticles, are renowned for pattern formation like few other materials. The Rosensweig instability of a horizontal ferrofluid-air interface in perpendicular magnetic field is especially well known classically, this instability sets the air-ferrofluid interface into an array of spikes that correspond to a new free energy minimum of the system. However, once the pattern is formed, it does not exhibit any notable thermal or non-equilibrium fluctuations, i.e., it is passive. In this work, we present an active version of the Rosensweig patterns. We realize them experimentally by driving a dispersion of magnetic nanoparticles with an electric field into a non-equilibrium gradient state and by inducing the instability using a magnetic field. The coupling of electric and magnetic forcing leads to patterns that can be adjusted from quiescent classic Rosensweig-like behavior (at low activity) to highly dynamic ones displaying peak and defect dynamics, as well as tunability of structure periodicities beyond what is possible in the classic systems (at high activity). We analyze the results using an active agent-based approach as well as a continuum perspective. We construct a simple equilibrium-like effective Rosensweig model to describe the onset of the patterns and propose a minimal Swift-Hohenberg type model capturing the essential active pattern dynamics. Our results suggest that classic continuum systems exhibiting pattern formation can be activated to display life-inspired non-equilibrium phenomena.

It was recently discovered that supercurrents flowing through thin superconducting nanowires can be quenched by a gate voltage. This gate control of supercurrents, known as the GCS effect, could enable superconducting transistor logic. Here, we report that the GCS also manifests in a suppression of Meissner screening, establishing the phenomenon as a genuine feature of superconductivity that is not restricted to transport. Using a scanning nitrogen-vacancy magnetometer at sub-Kelvin temperatures, we image the nanoscale spatial region of GCS suppression in micron-size niobium islands. Our observations are compatible with a microscopic hot-spot model of quasiparticle generation and diffusion, and in conflict with other candidate mechanisms such as Joule heating or an electric field effect. Our work introduces an alternative means for studying quasiparticle dynamics in superconducting nanostructures, and showcases the power of local imaging techniques for understanding emergent condensed matter phenomena.

Crystalline semiconductors with intrinsically low lattice thermal conductivity ($\mathcal{K}$) are vital for device applications such as barrier coatings and thermoelectrics. Quaternary chalcogenide semiconductors such as CuCd$_2$InTe$_4$ and CuZn$_2$InTe$_4$ are experimentally shown to exhibit low $\mathcal{K}$, yet its microscopic origin remains poorly understood. Here, we analyse their thermal transport mechanisms using a unified first-principles framework that captures both the Peierls (particle-like propagation, $\mathcal{K}_P$) and coherence (wave-like tunneling, $\mathcal{K}_C$) mechanisms of phonon transport. We show that extended antibonding states below the Fermi level lead to enhanced phonon anharmonicity and strong scattering of heat-carrying phonon modes, suppressing $\mathcal{K}$ in these chalcogenides. We show that $\mathcal{K}_P$ dominates the total thermal conductivity, while $\mathcal{K}_C$ remains negligible even under strong anharmonicity of the phonon modes. The heavier Cd ions in CuCd$_2$InTe$_4$ induce greater acoustic-optical phonon overlap and scattering compared to CuZn$_2$InTe$_4$, further lowering thermal conductivity of the former. Additionally, grain boundary scattering in realistic samples contributes to further suppression of thermal transport. Our findings establish the atomistic origins of low $\mathcal{K}$ in quaternary chalcogenides and offer guiding principles for designing low-thermal-conductivity semiconductors.

Novel antiferromagnets with broken time reversal symmetry (TRS) have launched a new direction in spintronics research, combining the advantageous dynamical properties of conventional antiferromagnets with the controllability typically associated with ferromagnets. However, antiferromagnetic domains are notoriously challenging to image in real-space. X-ray magnetic circular dichroism (XMCD) offers a route to overcome this difficulty: XMCD contrast may be finite in TRS-breaking antiferromagnets with an appropriate magnetic space group. Here, we exploit this to image the octupole domains in a focused ion beam-fabricated device of the non-collinear antiferromagnet Mn$_3$Sn. Using scanning transmission x-ray microscopy, we spatially resolve the weak pre-edge XMCD contrast (of 0.2%) that is sensitive to $T_z$, achieving a contrast resolution better than 0.02%. We observe hysteretic switching of the octupole order through both the XMCD contrast and the corresponding anomalous Hall effect within the same device. These results confirm the bulk nature of this contrast, and establish XMCD-based microscopy as a powerful real space imaging method for TRS-breaking antiferromagnets, including altermagnets, enabling future studies of their dynamics, switching, and symmetry-tunable phenomena.

Crystallization, a fundamental phase transition process governing material formation in natural and industrial contexts, involves the spontaneous emergence of long-range structural order from disordered phases. This long-range periodicity involves spatial and molecular orientation order. Molecular dynamics (MD) simulations of crystallization require collective variables (CVs) that accurately distinguish this long-\range periodicity. Existing CVs based on local descriptors (e.g., bond-orientational order) often lack transferability across crystal structures. To address this, we propose a unified CV framework derived from the multipole expansion of Ewald summation: a mathematical formalism bridging X-ray diffraction (XRD) principles and electrostatic energy computation in MD. By projecting atomic configurations onto a basis of spherical harmonics (complete for angular function representation), our CV achieves high-fidelity encoding of both translational and orientational order. Metadynamics simulations demonstrate that this CV drives efficient sampling of polymorphic pathways for known crystals and predicts stable phases even without crystal structures. This approach shows potential as a transferable platform for ab initio crystal structure prediction.

We investigate how gravity influences negative differential thermal resistance (NDTR) in fluids modeled by multiparticle collision dynamics. In the integrable case, we derive the heat flux formula for the system exhibiting the NDTR effect, and show that by introducing a gravity along the direction of the thermodynamic force, the temperature difference required for the occurrence of NDTR can be greatly reduced. Meanwhile, we also demonstrate that the heat-bath-induced NDTR mechanism – originally found to be applicable only to weakly interacting systems – can now operate in systems with stronger interactions due to the presence of gravity, and further remains robust even in mixed fluids. These results provide new insights into heat transport and establish a theoretical foundation for designing fluidic thermal devices that harness the NDTR effect under gravity.

Two-dimensional (2D) kagome materials have drawn extensive research interest due to their unique electronic properties, like flat bands, magnetic frustration, and topological quantum states, which enable precise quantum state control and novel device innovation. Yet, simultaneously achieving high stability, tunability, and multifunctionality in 2D kagome systems remains a key material design challenge. In this study, we innovatively propose a new paradigm for constructing two-dimensional multi-kagome-layer materials based on the "1+3" design concept. By seamlessly integrating high-throughput screening techniques, we have successfully identified 6,379 novel 2D multilayer kagome candidates from a vast pool of candidates. These materials exhibit a rich diversity of types, encompassing 173 metals, 27 semimetals, 166 ferromagnetic semiconductors, and as many as 6,013 semiconductors. Furthermore, based on the 2D flat-band scoring criteria, we conducted a detailed analysis of the flat-band characteristics of the energy bands near the Fermi level in the predicted systems. Our findings reveal that approximately two-thirds of the systems meet the 2D flat-band scoring criteria, and notably, several systems exhibit nearly perfect flat-band characteristics. Our work provides an excellent paradigm for the design and research of 2D multilayer kagome materials

Ferroelectricity is a cornerstone of functional materials research, enabling diverse technologies from non-volatile memory to optoelectronics. Recently, type-I integer quantum ferroelectricity (IQFE), unconstrained by symmetry, has been proposed and experimentally demonstrated; however, as it arises from ionic displacements of an integer lattice vector, the initial and final states are macroscopically indistinguishable, rendering the physical properties unchanged. Here, we propose for the first time the nontrivial counterpart (i.e., type-II IQFE) where the polarization difference between the initial and final states is quantized but the macroscopical properties differ. We further demonstrate the existence of type-II IQFE in bulk chiral tellurium. In few-layer tellurium, the total polarization remains nearly quantized, composed of a bulk-inherited quantum component and a small surface-induced contribution. Molecular dynamics simulations reveal surface-initiated, layer-by-layer switching driven by reduced energy barriers, explaining why ferroelectricity was observed experimentally in few-layer tellurium, but not in bulk tellurium yet. Interestingly, the chirality of the initial and final states in bulk tellurium is opposite, suggesting a novel way to control structural chirality with electric field in chiral photonics and nonvolatile ferroelectric memory devices.

Patchy particles have proven to be a prominent model for studying the self-assembly behavior of various systems, ranging from finite clusters to bulk crystal assemblies, and from synthetic colloidal particles to viruses. The patchy particle model is flexible, but it also comes with its own pitfalls – the potential design space is infinite. Many efforts have been put into building inverse-design frameworks that efficiently design patchy particles for targeted assembly behaviors. In contrast, little work has been done on investigating the interplay between different types of parameters that can be optimized for patchy particles, such as patch location, patch size, and patch binding energies. Here, by utilizing molecular dynamics with automatic differentiation, we elucidate the relationships between different potential optimization parameters and provide general guidelines on how to approach patchy particle design for various types of finite clusters. Specifically, we find that the design parameter landscape is highly dependent on the floppiness of the target structure, and we can identify stiff and sloppy parameters by computing the Hessians of all optimization parameters.

Dynamic bonding is an essential feature of many soft materials. Molecular simulations have proven to be a powerful tool for modeling bonding kinetics and thermodynamics in these materials, providing insights into their properties that cannot be obtained by experiments alone. Here, we review recent advances in modeling dynamic bonding in soft matter via molecular dynamics, Monte Carlo, and hybrid simulation methods, highlighting outstanding challenges and future directions.

We have created an innovative natural thermostat algorithm to mimic the direct impact of temperature on interatomic distances in both a perfect crystal and a system containing a vacancy. Unlike previous research, our findings demonstrate that in a system with a defect, the radii of the initial ten coordination spheres increase almost linearly with temperature. However, the coefficients defining these dependencies, unlike those for interatomic distances farther from the vacancy, do not equal the linear thermal expansion coefficient of the perfect crystal. Knowing the atomic coordinates and their temperature evolution, we calculated the temperature dependence of the vacancy formation energy and the vacancy relaxation volume in bcc iron. The significance of these effects for the accurate calculation of atomic diffusion coefficients is analyzed and discussed.

This study demonstrates the control of neuronal survival and development using nitrogen-doped ultrananocrystalline diamond (N-UNCD). We highlight the role of N-UNCD in regulating neuronal activity via near-infrared illumination, demonstrating the generation of stable photocurrents that enhance neuronal survival and neurite outgrowth and foster a more active, synchronized neuronal network. Whole transcriptome RNA sequencing reveals that diamond substrates improve cellular-substrate interaction by upregulating extracellular matrix and gap junction-related genes. Our findings underscore the potential of conductive diamond as a robust and biocompatible platform for noninvasive and effective neural tissue engineering.

Attractive dipole interactions can be induced between equally charged soft nanoparticles under the influence of AC electric fields. The combination of charge repulsion and dipole attraction, along with different screening responses from an underlying electrolyte, lead to complex aggregations ranging from chain-like formation for linear polarizations to isotropic planar structures in the case of circular polarizations. In this work, we analyze the role of varying field anisotropies in these self-assembled structures. To this end, the formalism previously developed for the coarse-grained interactions of soft particles in the presence of linear [T.~Colla et al., ACS Nano 12, 4321-4337 (2018)] and circular [M.~Reich et al., Soft Matter 21, 1516-1528 (2025)] field polarizations is naturally extended to incorporate elliptical polarizations of arbitrary asymmetries. A rich variety of self-assembly formations is found at intermediate field anisotropies, thus bridging the gap between linear and circular field-induced self-assembly scenarios.

This study demonstrates the first realization of wireless strain, temperature and crack growth sensing within 3D-printed metallic structures using standard electromagnetic inspection hardware. This establishes a path toward need-based maintenance for parts operating in harsh environments driven by accurate, real-time damage assessments instead of relying on regularly scheduled maintenance teardowns. To this end, we encapsulate and embed magnetoelastic and thermomagnetic materials during additive manufacturing. Mechanical and thermal stimuli affect the magnetic permeability of the embedded materials, which modulates the flux through a coil placed on or near the part's surface. We demonstrate strain sensing accurate to +/-27x10-6 and temperature sensing accurate to +/-0.75 oC. We highlight these sensors' capabilities by detecting the onset of plasticity and fatigue-driven crack growth thousands of cycles before critical failure.

High-fidelity simulations are essential for predicting material behavior under high-velocity impact (HVI), but their accuracy depends on material models and parameters that are often calibrated by manual fitting to multiple costly experiments. In this study, we develop an ensemble-based data assimilation framework for automatic calibration of selected plasticity, fracture, and equation-of-state (EOS) parameters in HVI simulations using data from a single HVI test. The framework combines Smoothed Particle Hydrodynamics, the ensemble Kalman filter (EnKF), and adaptive covariance inflation to mitigate variance collapse. A simple benchmark first shows that the framework is at least one order of magnitude more computationally efficient than Markov chain Monte Carlo at comparable identification accuracy. We then use synthetic back-face deflection data for an AZ31B magnesium plate to identify representative parameters in the Johnson-Cook plasticity and fracture models and the Mie-Gruneisen EOS. Results under under-biased, over-biased, and limited-observation cases show that parameters to which the data are sufficiently sensitive can be accurately recovered within about five iterations, with convergent ensemble standard deviations. In contrast, insensitive parameters tend to converge to incorrect values and retain large ensemble spreads. With fewer observations, convergence is still achieved for sensitive parameters but requires more iterations. Under extreme prior bias, a parameter rejuvenation strategy drives sensitive parameters toward the true values even when the truth lies outside the initial ensemble spread. These results show that ensemble standard deviation provides a practical diagnostic for parameter sensitivity, identifiability, and potential non-uniqueness. Overall, the proposed framework offers an efficient and robust approach for material model characterization in HVI problems.

The VQE algorithm is applied to the problem of finding the ground state of a lattice model with on-site Coulomb repulsion, nearest-neighbor hopping, and on-site sd-interaction. We compare the performance of several ansatze, including cluster and generic forms. Several modifications of the standard cluster ansatz implementation are proposed, which significantly reduce the number of two-qubit gates. Different classical optimizers are employed within the VQE algorithm. The performance of the algorithms is evaluated using both noiseless and noisy simulations.

Non-Hermiticity naturally arises in many physical systems that exchange energy with their environment. The presence of non-Hermiticity leads to many novel topological physics phenomena and device applications. In the non-Hermitian energy band theory, the foundation of these physics and applications, both energies and wavevectors can take complex values. The energy bands thus become a Riemann surface, and such an energy-band Riemann surface underlies all the important signatures of non-Hermitian topological physics phenomena. Despite a long history and recent theoretical interests, the energy-band Riemann surface has not been experimentally studied. Here we provide a photonic observation of the energy-band Riemann surface of a non-Hermitian system. This is achieved by applying a tunable imaginary gauge transformation on the platform of the photonic synthetic frequency dimension. From the measured topology of the Riemann surface, we reveal the complex-energy winding, the open-boundary-condition spectrum, the generalized Brillouin zone, and the branch points. Our findings demonstrate a unified framework in the studies of diverse effects in non-Hermitian topological physics through an experimental observation of energy-band Riemann surfaces.

We investigate the modulational instability of uniform wave packets governed by a discrete third-order nonlinear Schrödinger equation in finite square lattices, modeling light propagation in two-dimensional nonlinear waveguide arrays. We analyze how initially stable uniform distributions evolve into self-trapped (localized) regimes and the influence of a refractive index detuning selectively applied along the diagonal waveguides on this transition. This detuning effectively emulates the effect of on-site Hubbard-like interactions $U$ in photonic analogs of interacting particles in a one-dimensional lattice. While for $U = 0$ the system exhibits the known direct transition from stable uniform states to asymptotically localized profiles, we show that $U > 0$ induces an emergence of intermediate dynamical regimes. These regimes include coherent breathing modes that can be either confined along diagonal or off-diagonal waveguides, as well as chaotic-like propagation patterns. At higher nonlinearities, we identify distinct self-trapped regimes characterized by diagonal or off-diagonal localized modes, depending on the strength of $U$. The critical nonlinear strengths separating the existing regimes are shown in the phase diagram, underscoring the competing trends imposed by the Hubbard-like interaction on the optical field.

Indium selenide is a phase-change chalcogenide whose polymorphism enables a variety of physical properties to be tuned. Here we directly quantify the evolution of the surface work function across the amorphous-to-crystalline transition in RF-sputtered In2Se3 thin films grown on c-plane Al2O3 (001). By varying deposition temperature (100-500 {\deg}C) and film thickness, we establish processing windows for a- In2Se3, {\alpha}-In2Se3, and {\gamma}-InSe, and correlate structure with electronic and morphological properties. X-ray diffraction shows films deposited at 100 to 200 {\deg}C are amorphous, 300 to 400 {\deg}C yields {\alpha}-In2Se3, whereas 500 {\deg}C yields {\gamma}-InSe. Kelvin probe force microscopy (KPFM) maps the surface potential and yields spatially averaged work functions spanning 5.26 to 6.64 eV across the amorphous-crystalline transformation; pronounced intra-film heterogeneity is observed, with select {\alpha}-phase and {\gamma}-InSe grains exhibiting work functions exceeding the local mean. Topographical distinctions are found between phases with hexagonally faceted grains in the crystalline state, whereas homogeneous nano-mounds are found in amorphous films. Analysis of Tauc plots revealed optical bandgaps in the range of 2.50 to 1.55 eV across the observed phases. X-ray fluorescence (XRF) measurements further indicated that the indium to selenium concentration ratio varied between 0.70 {\pm} 0.1 to 1.01 {\pm} 0.1 as the deposition temperature increased from 100 to 500 {\deg}C. These measurements provide direct, spatially resolved quantification of work-function evolution through the phase change, supplying parameters essential for contact engineering and device integration of In2Se3 and InSe.

We report dielectric and magnetoelectric studies of single-crystalline \ce{CeMgAl11O19}, a Kramers triangular magnet embedded in a polarizable hexaaluminate lattice. In zero magnetic field, the permittivity $\varepsilon'(T)$ follows the Barrett law of a quantum paraelectric down to 25 K, below which a broad minimum develops near 3 K without evidence of static ferroelectric or magnetic order. Application of magnetic fields up to \SI{9}{\tesla} shifts this minimum to higher temperatures and broadens it, evidencing a tunable magnetoelectric response.The magnetoelectric coupling was characterized using results from magnetization measurements. The anomaly temperature $T^*$, extracted from the local minimum of $\varepsilon'(T)$, exhibits a linear dependence on the squared magnetization $M^2$, consistent with the biquadratic magnetoelectric coupling allowed in centrosymmetric systems. This magnetoelectric effect, mediated by spin-orbit-entangled Kramers doublets interacting with a frustrated antipolar liquid, establishes \ce{CeMgAl11O19} as a prototype for exploring quantum magnetoelectricity in frustrated systems.

In this work, we show that suitably designed spatially varying linearly polarized light provides a versatile route to generate and control pseudo-magnetic fields in Weyl semimetals through Floquet engineering. Within a high-frequency expansion, we derive an effective axial gauge potential $\mathbf{A}_5(\mathbf{r})$ whose curl gives the pseudo-magnetic field $\mathbf{B}_5(\mathbf{r})$. By mapping the light profile to $\mathbf{A}_5(\mathbf{r})$, we establish design principles for pseudo-magnetic field textures that mimic strain-induced gauge fields while offering key advantages like dynamic control, full reversibility, spatial selectivity, and absence of material deformation. We compare the Landau-level spectra produced by uniform real and pseudo-magnetic fields and also analyze both their linear optical conductivity and the second-order dc responses. Our results enable real-time manipulation of pseudo-magnetic fields and predict clear experimental signatures for optically engineered gauge fields in topological semimetals.

We present an atomistic line graph neural network (ALIGNN) model for predicting dielectric functions directly from crystal structures. Trained on $\sim$7000 dielectric functions from the JARVIS-DFT database computed with a meta-GGA exchange-correlation functional, the model accurately reproduces spectral features, including peak intensities and overall line shapes, while enabling efficient high-throughput screening. Applied to the recently developed Alexandria materials database, containing over four hundred thousand insulating materials, we uncover a clear elemental trend, with vanadium emerging as a strong indicator of materials with high-spectroscopic limited maximum efficiency (SLME). In particular, vanadium-based perovskite materials show a substantially higher fraction of high-SLME compounds compared to the database average, underscoring their promise for optoelectronic applications.

We study extreme events of avalanche activities in finite-size two-dimensional self-organized critical (SOC) models, specifically the stochastic Manna model (SMM) and the Bak-Tang-Weisenfeld (BTW) sandpile model. Employing the approach of block maxima, the study numerically reveals that the distributions for extreme avalanche size and area follow the generalized extreme value (GEV) distribution. The extreme avalanche size follows the Gumbel distribution with shape parameter $\xi=0$ while in the case of the extreme avalanche area, we report $\xi>0$. We propose scaling functions for extreme avalanche activities that connect the activities on different length scales. With the help of data collapse, we estimate the precise values of these critical exponents. The scaling functions provide an understanding of the intricate dynamics for different variants of the sandpile model, shedding light on the relationship between system size and extreme event characteristics. Our findings give insight into the extreme behavior of SOC models and offer a framework to understand the statistical properties of extreme events.

Raman scattering is emerging as a surprising probe of electron topology in quantum materials. It has been used recently to detect and characterize a topological phase transition that accompanies the magnetic transition in Nd$_2$Ir$_2$O$_7$. Here we present a theory of Raman scattering from nodal electrons with Weyl and quadratic band touching spectra, which has to reach beyond the standard effective mass approximation. After reviewing and providing the details of our previous theory development, we discuss several new results. We show that the light-polarization dependence of Raman scattering is universal in the case of Weyl electrons and given by an analytic expression, while it contains symmetry-protected features in the case of quadratic band-touching nodes. We also analyze modifications of the Raman signal due to the ubiquitous tilting of the Weyl spectrum, and argue that universality is lost only in a finite frequency range that springs out of the threshold frequency for untilted nodes. Finally, we explore the frequency dependence of Raman scattering for the case of Dirac electrons coexisting with a flat band in the same region of the first Brillouin zone, which is inspired by the material V$_{1/3}$NbS$_2$.

We present a nonperturbative tensor-network approach to the excitation spectra of superconducting circuits based on Josephson junction arrays. These arrays provide the large lumped inductances required for qubit designs, yet their intrinsically many-body nature is typically reduced to effective single-mode descriptions. Perturbative treatments attempt to include the collective array modes neglected in these approximations, but a fully nonperturbative analysis is challenging due to the many-body structure and the collective character of these modes. We overcome this difficulty using the DMRG-X algorithm, which extends tensor-network methods to excited states. Our key advance is a construction of trial states from the linearized mode structure, enabling direct computation of excitations, even in degenerate manifolds, which was previously inaccessible. Our results reveal significant deviations from, and allow us to improve upon, previous perturbative treatments in the regime of low array junction impedance.

The field of coherent electronics aims to advance electronic functionalities by utilizing quantum coherence. Here, we demonstrate a viable and versatile methodology for controlling electron dynamics optically in graphene nanoribbons. In particular, we propose to flatten the band structure of armchair graphene nanoribbons via control electrodes, arranged periodically along the extended direction of the nanoribbon. This addresses a key mechanism for dephasing in solids, which derives from the momentum dependence of the energy gap between the valence and the conduction band. We design an optimal driving field pulse to produce collective Rabi oscillations between these bands, in their flattened configuration. As an example for coherent control, we show that these optimized pulses can be used to invert the entire electronic band population by a $\pi$ pulse in a reversible fashion, and to create a superposition state via a $\pi/2$ pulse, which generates an alternating photocurrent. Our proposal consists of a platform and methodological approach to optically control the electron dynamics of graphene nanoribbons, paving the way toward novel coherent electronic and quantum information processing devices in solid-state materials.

In this work, we investigate the use of spatio-temporalImplicit Neural Representations (INRs) for dynamic X-ray computed tomography (XCT) reconstruction under interlaced acquisition schemes. The proposed approach combines ADMM-based optimization with INCODE, a conditioning framework incorporating prior knowledge, to enable efficient convergence. We evaluate our method under diverse acquisition scenarios, varying the severity of global undersampling, spatial complexity (quantified via spatial information), and noise levels. Across all settings, our model achieves strong performance and outperforms Time-Interlaced Model-Based Iterative Reconstruction (TIMBIR), a state-of-the-art model-based iterative method. In particular, we show that the inductive bias of the INR provides good robustness to moderate noise levels, and that introducing explicit noise modeling through a weighted least squares data fidelity term significantly improves performance in more challenging regimes. The final part of this work explores extensions toward a practical reconstruction framework. We demonstrate the modularity of our approach by explicitly modeling detector non-idealities, incorporating ring artifact correction directly within the reconstruction process. Additionally, we present a proof-of-concept 4D volumetric reconstruction by jointly optimizing over batched axial slices, an approach which opens up the possibilities for massive parallelization, a critical feature for processing large-scale datasets.