Papers

Bogomolny, Bohigas and Schmit (BBS) found that the spectrum of the pairwise distance matrix on N points sampled from a smooth d-dimensional manifold encodes a signature of the underlying geometry. We develop I-BBS (Inference-BBS), a coordinate-free method that identifies a low-dimensional latent sub-manifold embedded in a high-dimensional ambient distance matrix alone, without accessing an ambient high-dimensional vector space. It therefore applies even when that space is only partly observable or undefined. We model the ambient embedding by two classes of generative noise, model-based and model-free. The noise mixes the latent signal with off-manifold components, so the eigenvalues reorganise collectively and the latent geometry cannot be read off eigenvalue by eigenvalue. We recover it instead from two integer-stable signatures that survive the noise: the multiplicity of the top non-Perron multiplet, which fixes $d$, and a parameter-free law for how the multiplet positions shrink as the noise grows. On synthetic spheres $S^1$, $S^2$ and $S^3$ these integer signatures are far more stable under noise than the continuous spectral slope, and a blind test recovers both the manifold and the noise model from a single distance matrix. Applications to neural-network representations and to the dynamic training regime are developed in two companion papers.

The materials science literature encodes decades of experimental knowledge in figures, yet this visual record remains locked away and inaccessible to AI at scale. The core difficulty is structural: most scientific figures are compound, with a single caption describing multiple sub-panels simultaneously, making direct image-text pairing unreliable. We present MatMMExtract, an end-to-end open-source pipeline that resolves this by decomposing compound figures into individual sub-panels and generating structured, grounded annotations using a large language model guided by a curated materials science taxonomy. Applied to 14,810 open-access articles, MatMMExtract produces MatSciFig; 391,606 panel-level image-text pairs from 180,571 figures, each annotated with a sub-caption, a two-level visualisation category spanning 19 classes and over 100 subtypes, and a scientific summary. To enable accurate panel localisation, we introduce MaterialScope, a domain-specific detection dataset of 2,811 manually annotated materials science figures, on which a fine-tuned YOLO12-m detector achieves mAP_50 of 0.9227. Among six benchmarked language models, Gemini 3.1 Flash Lite delivers the best cost-quality trade-off for annotation generation, with 82% of outputs rated good and a hallucination rate of 4.8%. A dual-encoder retrieval baseline on MatSciFig achieves a 4.4 times improvement in R@1 over zero-shot CLIP, demonstrating the dataset's immediate utility for vision-language learning. All resources are released openly to the community.

Nonlinear transport has emerged as a sensitive probe of quantum geometry beyond the Berry-curvature physics of linear response. However, the intrinsic second-order dc response remains conceptually subtle: different quantum and semiclassical formulations can appear to give different static limits, with different assignments of Fermi sea and Fermi surface contributions. Here we resolve this ambiguity by developing a gauge-consistent density-matrix theory of intrinsic nonlinear conductivity in both the length gauge, where the electric field couples through the position operator, and the velocity gauge, where it enters through the vector potential. We show that the two gauges give the same adiabatic dc response when the same retarded continuation is used for all external frequencies and when the velocity gauge current includes all field-dependent vertices. The apparent Fermi sea terms cancel in the full expression, leaving a Fermi surface quantum geometric contribution determined by the band-normalized quantum metric. This result implies that a fully gapped insulator has no residual dc nonlinear Hall current in the adiabatic clean limit. The reactive part of the Fermi surface term agrees with the original semiclassical Berry-connection-polarizability response, while the dissipative Ohmic sector requires a more careful treatment of relaxation and impurity scattering. Our work establishes the length-velocity gauge equivalence for quantum geometric nonlinear response and provides a foundation for using nonlinear transport to probe magnetic quantum geometry, especially in PT-symmetric antiferromagnets.

Diffusion models are increasingly utilized for modeling molecular structures and conformational ensembles, yet the thermodynamic meaning of their learned representations and scores remains elusive. To resolve this ambiguity, we introduce a mathematically consistent action-operator framework natively compatible with diffusion models. By defining a fixed molecular environment as a base action $S_0(x)$ and an alchemical perturbation as an operator $O(x)$, standard diffusion noising induces effective noised actions and operators whose gradients and alchemical derivatives are directly represented by the model's learned fields. This rigorous self-consistency enables a “noisy operator bridge” capable of reading out free-energy differences ($\Delta F$) from endpoint ensembles and per-frame evaluations. In controlled experiments on alanine dipeptide systems, we show that incorporating physical inductive biases enables partial recovery of the base action and perturbation operator. When applied to a challenging C6-H to C6-F ligand-pocket nonbonded perturbation (185L/IND) with negligible phase-space overlap, our supervised bridge estimates the alchemical $\Delta F$ within approximately $1\ k_\mathrm{B}T$ of a stable 19-state MBAR reference. Finally, we demonstrate that endpoint coordinates and binary labels alone are sufficient to partially recover the operator shape and a centered free-energy scale without any force or action supervision. This work provides a rigorous path toward transforming generative molecular diffusion models from black-box coordinate samplers into auditable thermodynamic estimators.

A central premise of autonomous scientific imaging is that smarter navigation, whether Bayesian, RL-based, or otherwise adaptive, is the principal lever for sample-efficient acquisition. We present evidence to the contrary in scanning transmission electron microscopy (STEM), an atomic-resolution imaging modality whose every measurement deposits damaging electron dose. We introduce STEMGym, an open-source Gymnasium benchmark of 15 physics-simulated STEM worlds spanning five materials, three difficulty levels, and four characterisation tasks, scored by the Dose-Efficiency Curve area (DEC-AUC), a single scalar capturing the information-vs-dose Pareto frontier. Across 33 agent configurations under realistic dose budgets, the dominant determinant of dose efficiency is the analyst (perception) pipeline, not the navigator: pairing a trained CNN analyst with naïve raster scanning raises DEC-AUC by 5.5x over a CNN-free raster baseline (0.287 vs.\ 0.052), while substituting Bayesian or adaptive finite-state-machine navigation for raster yields no statistically significant further gain. Production-tier vision-language models further underperform task-specific CNNs by {\sim}13x on crystallographic defect analysis. By decoupling perception, navigation, and planning under a unified dose budget, STEMGym reframes where ML effort should be invested in autonomous electron microscopy and provides the measurement infrastructure to test it.

$\mathrm{Cl}(3,0)$ interatomic potentials, despite their algebraic elegance, predict force magnitudes accurately but force directions poorly. Across ten rMD17 molecules, every $L \leq 1$ baseline in our twelve-model study attains aggregate force-cosine similarity below $0.25$. The cause is structural. The geometric product of two vectors in $\mathbb{R}^3$ realises only the $L=0$ and $L=1$ components of its irreducible representation content, leaving the symmetric-traceless rank-2 component absent from the per-edge bilinear that drives each message-passing layer. We address this with CliffordSTF, which couples the Clifford multivector to closed-form symmetric-traceless tensor tracks at ranks two and three through bilinear cross-track contractions, using a single learned bilinear and no Clebsch–Gordan tables, Wigner-$D$ matrices, or e3nn calls. On rMD17, CliffordSTF raises aggregate force-cosine similarity from $0.055$ (base Clifford) to $0.551$, an order-of-magnitude relative directional gain, alongside improved magnitude accuracy (force MAE $15.8\%$ lower; energy MAE $10.9\%$ lower). It outperforms all CG-free or body-ordered baselines in our study (all $\leq 0.17$). On catalysis benchmarks, CliffordSTF achieves the best out-of-distribution S2EF energy MAE on OC22 in our experiments, and the best in-distribution energy MAE among $L \geq 2$ methods on OC22 IS2RE. An eleven-variant ablation shows the two tracks are complementary: neither alone matches the combined model.

The quantum geometric phase intrinsically dictates the geometry, topology, and many-body correlations of electronic wave functions. While quantum geometric phases are conventionally inferred through momentum-space probes or macroscopic transport measurements, their direct visualization and quantification in real space have historically been restricted by the spatial averaging of bulk techniques. Scanning tunneling microscopy and spectroscopy (STM/STS) circumvent this limitation, leveraging atomic-scale spatial resolution and high energy sensitivity to resolve local electronic phase profiles directly. This review highlights recent progress across four representative methodologies: probing the Aharonov-Bohm (AB) geometric phase via nanoscale real space interferometry; extracting the Berry phase from defect-induced quasiparticle interference and wavefront dislocations; reconstructing the complex phase structure in symmetric systems, such as magic-angle graphene, using order parameter decomposition; and mapping the phase textures and topological defects of pair density wave (PDW) and charge density wave (CDW) in unconventional superconductors utilizing the numerical 2D lock-in technique. Together, these developments show how quantum phases can be translated onto real space and locally resolvable observables. Phase-resolved STM imaging provides stringent constraints on topological states of matter, symmetry-breaking patterns, and strong electronic correlations, outlining a robust framework for in situ phase engineering in quantum materials.

We discuss the algebraic structure of observables in Schrödinger CFTs. These operators have zero mass (or particle number) and generically transform in staggered ”pyramid representations” built from ”alien operators,” as we explain with the doubled state-operator correspondence. We comment on implications for the space of non-relativistic CFTs, thermal physics, and generalize the exceptional symmetry conservation laws of Bekaert, Meunier, and Moroz, and Golkar and Son. We show that alien operators are analogous to double-twist operators in Lorentzian CFT, with systematic cross-channel corrections from massless particles when they exist.

The low-pressure phase diagram of La$_3$Ni$_2$O$_7$ provides an important reference for understanding its pressure-induced high-temperature superconductivity. While the spin-density-wave transition at $T_{\text{SDW}}\approx150$ K is increasingly well established, the origin of the second density-wave transition at $T_{\text{DW}}\approx130$ K has remained unresolved. Here, we perform unrestricted Hartree-Fock calculations to investigate the potential origin of the second transition. {Within the orthorhombic phase, the degeneracy between possible ordering wavevectors at $\boldsymbol{Q}_{Y}=(0,\pi)$ and at $\boldsymbol{Q}_{X}=(\pi,0)$ is lifted and the electronic system} develops a double-stripe spin-density wave with ordering vector $\boldsymbol{Q}_{Y}=(0,\pi)$. We identify that the pure double stripe spin state is unstable in La$_3$Ni$_2$O$_7$ towards a commensurate charge-density wave instability, which favors a spin-modulated double stripe order with intertwined charge and spin instabilities and establish the hierarchy of ordered states in La$_3$Ni$_2$O$_7$. We further discuss our results in the context of available experimental literature and propose further experimental tests to elucidate the origin of the SDW/DW states in this system.

We introduce a scheme to generate NOON states of few-body bosonic vortices and demonstrate their application as high-precision rotation sensors. Our approach is based on cold atoms in a weakly anisotropic two-dimensional harmonic trap, where the single-particle p orbitals define an effective two-mode Bose-Hubbard model with vortex modes $(\mathrm{p}_x\pm\mathrm{i}\mathrm{p}_y)$ carrying opposite circulation. In the self-trapping regime, we show that the NOON manifold becomes spectrally isolated, and collective tunneling processes give rise to highly entangled vortex NOON states. However, these states emerge on prohibitively long timescales. To overcome this limitation, we develop two complementary acceleration strategies: geodesic counterdiabatic driving for small particle numbers, and resonance- and chaos-assisted tunneling in the semiclassical regime at larger particle numbers. Both approaches enable the generation of NOON states on experimentally relevant timescales while preserving near-unit fidelities. Finally, we quantify the metrological advantage of vortex NOON states by introducing an interferometric protocol that exploits their intrinsic sensitivity to rotation, enabling the detection of infinitesimal external rotations at the Heisenberg limit. Our work opens the door to rotation sensors based on atomic NOON states, generically realizable in bosonic Josephson junctions with vortex-type orbitals.

We investigate the emergence of flagellar beating in chains of magnetic self–propelled particles (MSPPs) built from centimeter–scale vibrating robots (Hexbugs) with embedded neodymium dipoles. When one end of the chain is anchored and self–propulsion is activated, longitudinal stress accumulates along the chain until it overcomes the magnetic bending stiffness, triggering a buckling instability that drives sustained flagellar beating. Using a combination of experiments and numerical simulations, we identify three distinct dynamical regimes straight chain, stable flagellar beating, and fission governed by the competition between active force, chain length, and magnetic bending stiffness. The onset of beating requires a seed misalignment set by the balance between magnetic torques and rotational noise, and we show that the transition corresponds to a supercritical Hopf bifurcation. A kinematic model reproduces the observed orientation dynamics with excellent agreement. The magnetic bending stiffness, which arises directly from dipole–dipole interactions, is fully tunable via dipole strength and chain length, offering independent experimental control over both activity and rigidity. Our results establish a macroscopic platform for studying force-induced buckling and self–oscillations in active filaments, with direct connections to flagellar motion in biological and synthetic microswimmers.

This paper presents the derivation of closed-form expressions of the single-point statistical moments of a solution to a nonhomogeneous stochastic advection equation with a linear relaxation. While analytical solutions exist for homogeneous systems, nonhomogeneous cases have traditionally relied on intensive numerical simulations. Here, we provide an analytical framework for calculating single-point statistical moments by first obtaining the solution to the stochastic advection equation via the method of characteristics, from which the moments are derived. Explicit, closed-form expressions for the first four moments are derived as functions of the characteristic length scale of the stochastic velocity field and the spatial derivatives of time-mean profile of the field. The analytical results are validated against numerical simulations, demonstrating excellent agreement across a range of physical parameters. The resulting theory acts as a generalized “equation-of-state" style approach for predicting variability and non-Gaussian statistical behavior directly from the macroscopic mean state, providing applicability across transport systems with a wide range of time and length scales, including geology, hydrology, and atmospheric sciences.

Recent angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM) measurements on bilayer nickelate La$_3$Ni$_2$O$_7$ reveal a nearly isotropic, nodeless superconducting gap. We show that these single-particle spectra provide a symmetry-enforced test of the pairing nature. Mirror symmetry forces the hybridization between $d_{z^2}$ and $d_{x^2-y^2}$ orbitals to vanish along the Brillouin-zone (BZ) diagonal. Consequently, the gaps on the diagonal portions of the $\alpha/\beta$ and $\gamma$ Fermi pockets separately probe the intrinsic pairing strengths of the $d_{x^2-y^2}$ and $d_{z^2}$ sectors. A pairing state with pure or dominant intrinsic $d_{z^2}$-orbital pairing component produces nodes or near-nodes on the BZ diagonal of the $\alpha/\beta$ pockets and is thus challenged by ARPES and STM, whereas the pairing state with dominant intrinsic $d_{x^2-y^2}$-orbital pairing component has a nearly isotropic, nodeless gap on all pockets which well fits ARPES and STM data. The dominant $d_{x^2-y^2}$-orbital pairing is compatible with Hund's-rule-driven pairing mechanisms.

Inverse design of metal-organic frameworks (MOFs) requires navigating combinatorial spaces with costly property labels and opaque machine-learning models. We introduce LLM4MOF, a closed-loop multi-agent framework that converts a natural-language target into chemical hypotheses, constraints, diagnostic tests, and feedback. One agent proposes interpretable hypotheses over metal nodes, linkers, pore geometry, and functionality. Another converts them into constraints selecting MOFs defined by a node, linker, and topology. The Matchmaker forms four beams to attribute gains to geometry, chemistry, or metal choice: full hypothesis, chemistry, metal only, and random baseline. Blind to database landscapes, LLM4MOF enriches top performers across six adsorption, separation, and electronic-structure tasks within 400 evaluations. It also designs and live-simulates de novo MOFs spanning H2 storage, SF6 capture, and C2H6/C2H4 separation, deriving a distinct design rule for each objective. Under an identical nominal evaluation budget it consistently outperforms random search, Bayesian optimization, and genetic algorithms, and the outcome is insensitive to the language-model backend. All of this uses not a single property-labeled training structure, whereas generative alternatives train on thousands to hundreds of thousands. A new objective requires only a natural-language request: interpretable inverse design at a fraction of the data cost of existing approaches.

Using the Landau-Ginsburg-Devonshire approach we show that the linear gradient-type coupling between the electric polarization vector and antiferrodistortive long-range order parameter pseudovector, that has the form of Lifshitz invariant and named "bilinear flexo-antiferrodistortive coupling", can emerge in all antiferrodistortive ferroelastics, since it is symmetry-allowed. Using the four sublattices model we reveal that the bilinear flexo-antiferrodistortive coupling can induce the sublattice-sensitive polarization at the twin walls and antiphase boundaries in antiferrodistortive ferroelastics without any ferroelectric or antiferroelectric ordering. Since the induced polarization is perpendicular to the antiferrodistortive long-range order parameter and counter-directed in neighboring sublattices with checkerboard-type direction of antiferrodistortive long-range order parameter, such structure of polarization may correspond to the alterelectric-type quadrupolar electric order. However, physical manifestations of the bilinear flexo-antiferrodistortive coupling are invisible in most nanostructured antiferrodistortive ferroelectrics and antiferroelectrics due to the domination of piezoelectric and/or omnipresent linear flexoelectric couplings.

We present a unified physical theory demonstrating that human subjective time perception does not track geometric coordinate time $t$, but instead emerges from a local metric mutation driven by macroscopic physical entropy production. By establishing the Nonextensive Troika – a closed, mutually dependent algebraic triplet linking the phase-space fractal dimension $D$, the conformable derivative order $\alpha$, and the Tsallis nonextensive parameter $q$ – we eliminate independent phenomenological fitting constants. We prove that the local time metric inherently scales as $t^{\alpha}$, deriving the conformable operator as a necessary kinetic consequence. Furthermore, we derive the $q$-index from the equiprobable monofractal Tsallis entropy $S_q$. This structural closure unifies anomalous neural dissipative transport within a deformed leaky integrate-and-fire framework and analytically predicts macroscopic psychophysical response transitions, providing a clear thermodynamic basis for time dilation in psychedelic states (the REBUS model) and temporal compression during cognitive aging.

Active fluids consisting of living cells or synthetic microswimmers display rich emergent behavior and nonequilibrium mechanical properties, which not only shed light on various biological processes but also inform the engineering of autonomous fluidics and self-driven materials. The individual behavior of microswimmers and their interaction with self-generated mesoscale solvent flows underlie the emergent properties of active fluids. Here we studied the microscopic dynamics in dense 3D bacterial active fluids by simultaneous imaging of cell body, flagella, and flow field. A surprising finding is that the polarity of cells was randomly distributed in mesoscale flow regimes, and yet the system displays mesoscale order in the self-generated solvent flows. Despite the apparent flow-polarity decoupling, the motion of cells relative to local solvent flows predominantly navigated upstream, with the self-advection speed universally enhanced by a flow-controlled constant. Numerical modeling with full hydrodynamic interactions reveals that the observed flow-polarity decoupling arises from the breakdown of the commonly held force-dipole assumption for anisotropic microswimmers: in the presence of flow gradient and near-field hydrodynamic interactions, the direction of total active forcing exerted by a swimming bacterium to the surrounding fluid no longer aligns with its polarity. The simulations suggest that near-field interactions serve as a new type of emergent, configuration-dependent active forcing, which profoundly impact self-organization and transport in dense bacterial suspensions. Taken together, our work establishes fundamental knowledge for faithfully understanding the collective behavior of dense polar active fluids.

We theoretically investigate the ground-state properties and breathing-mode collective excitations of three-dimensional dipolar Bose gases in anisotropic harmonic traps incorporating quantum fluctuations. Combining a Gaussian variational ansatz with a non-perturbative sum-rule analysis, we derive explicit analytical expressions for both axial and radial breathing-mode frequencies, which are validated by numerical solutions of the time-dependent extended Gross-Pitaevskii equation. Our theoretical predictions show excellent agreement with existing experimental data for $^{166}$Er and $^{162}$Dy gases. By constructing comprehensive phase diagrams across the parameter space of the $s$-wave scattering length, atom number, and trap aspect ratio, we reveal both discontinuous first-order phase transitions and smooth crossovers between the dilute Bose-Einstein condensate and dense quantum droplet phases. We confirm that the enhanced incompressibility induced by quantum fluctuations significantly elevates the breathing-mode frequencies in the droplet phase compared to conventional weakly interacting Bose gases. Furthermore, the system undergoes a phase transition and a crossover over the scattering length under the quasi-two-dimensional and quasi-one-dimensional confinements, characterized by discontinuous jumps and continuous crossovers in peak density and atomic cloud sizes, respectively. Our work offers a rigorous and highly accurate framework to characterize collective excitations in dipolar quantum gases, providing quantitative insights for forthcoming ultracold atom experiments in lanthanide atoms and polar molecules.

To detect Josephson self-resonances, we used an original method, namely, studying the voltage Uy at the Hall contacts in the Nd2-xCexCuO4/SrTiO3 film, where the CuO2 planes are aligned along the longest side of the sample, perpendicular to the substrate. It is argued that the observed Uy(j) oscillations are a set of Fiske steps in a layered superconductor system, indicating the manifestation of the ac-Josephson effect in a multilayer superconductor Nd2-xCexCuO4 with a significant number of intrinsic Josephson junctions.

Local orbital magnetization is the field whose rotation generates the equilibrium current density. Unlike spin magnetization, a quantum-mechanical local formula consistent with both this current relation and the modern theory of bulk orbital magnetization has been missing. In this work, we derive a quantum-mechanical formula for the local orbital magnetization for non-interacting electrons by considering local-flux response of the grand potential. The local-flux response fixes the formula uniquely in two dimensions, whereas in three dimensions it selects a natural representative within a longitudinal ambiguity. Furthermore, coarse graining yields a natural local marker that generates the current to third-derivative order, and its site-position moment equals the orbital magnetic quadrupole moment of finite-size systems. We illustrate the obtained results with the Haldane model.

Physical reservoir computing offers an energy-efficient alternative to conventional neural networks, where the material-specific intrinsic memory capacity in a physical system plays an indispensable role. Substituting temporal memory with spatial degrees of freedom, we demonstrate that the memory capacity can be created extrinsically in systems with no intrinsic memory by exploiting the computational space-time tradeoff. Our approach utilizes multidimensional input nodes to function as a spatial memory axis, thereby replacing the dependency on intrinsic history-dependent dynamics in the reservoir. Our scheme is validated in a multi-terminal quantum dot system, whose discrete energy levels provide strong nonlinearity and complexity crucial for reservoir computing, while its short relaxation time leaves no room for intrinsic memory. Numerically, the quantum dot reservoir with a tunable extrinsic memory shows high performance on both chaotic future prediction and nonlinear transformation tasks. Furthermore, from the analysis of quantum state trajectory acquired from task operations, the geometric understanding of the extrinsic memory capacity, nonlinearity, and complexity is provided and their correlations are systematically investigated.

Relative motion between interacting systems can generate emergent energy scales that are absent in isolated systems. While uniform motion can be eliminated by a Galilean transformation, relative motion between interacting systems generally cannot. By coupling to an excitation's spatial structure, relative motion generates a Doppler frequency determined by its wavevector and the relative velocity, providing a mechanism for driving nonequilibrium phenomena. In this tutorial, we illustrate these ideas using magnonic systems as a concrete platform. We first discuss motion-induced magnon transport between relatively moving ferromagnets, in which the Doppler frequency serves as an effective nonequilibrium bias in the perturbative regime. This mechanism produces magnon currents even without conventional driving forces such as temperature gradients or chemical potential differences. We then introduce motion-induced parametric instabilities. When the emergent scale becomes sufficiently large to resonantly create magnon pairs, the perturbative description breaks down, and the magnonic vacuum becomes unstable. This instability occurs above a critical velocity threshold and leads to spontaneous magnon-pair creation. Connections to related phenomena, including quantum friction, Cherenkov emission, and Zel'dovich superradiance, are also highlighted. The concept of an emergent energy scale provides a unifying framework for understanding transport phenomena and instabilities in quantum systems with relative motion.

Entanglement entropy has proven to be a powerful probe of phenomena such as quantum chaos and phase transitions. Pseudo entropy is a recently proposed time-like generalization of an entanglement measure, motivated by de Sitter holography. In this work, we find that pseudo entropy can also serve as a novel probe for distinguishing topological phases of matter. For this, we consider the Su–Schrieffer–Heeger model as a representative example and investigate the averaged excess entropy $\Delta S_{12}$, defined as the difference between pseudo entropy and the average entanglement entropy, across the topological-to-trivial and trivial-to-topological phase transitions. When the two states are in the same phase, we find that $ \Delta S_{12}$ is non-positive under periodic boundary conditions, while for open boundary conditions, it is non-positive only when the system is sufficiently large. Moreover, we analyze ground-state quench protocols for topology-crossing quenches and find that the imaginary pseudo entropy tracks the critical times predicted by the Fisher zeros.

We reanalyze superconductivity in jellium model within the dielectric formalism developed by Kirzhnits, Maksimov, and Khomskii (KMK), which is probably the most reliable approach to this model. The linearized KMK integral equation for superconducting transition temperature is analyzed analytically and solved numerically by direct diagonalization to obtain $T_c$ dependence on Wigner - Seitz radius $r_s$. As a first systematic extension beyond random - phase approximation (RPA), static Hubbard local - field corrections are incorporated into the dielectric function. Our results in general narrow the interval of possible $T_c$ values in comparison with widely scattered results of some of the previous works. For the case of metallic hydrogen our calculations show $T_c(r_s)$ dependence with characteristic dome with maximum of $T_c$ at $r_s\sim$ 9.0 of the order of some fractions of Kelvin only, despite the naive expectations based on the high values of pairing Boson frequency. This is due to the weak - coupling regime of superconductivity in jellium model at all densities.

Based on a recent experiment in high-quality GaAs quantum wells [Phys. Rev. Lett. 127, 056801 (2021)], we present a microscopic study of the energy gap in two-dimensional electron gases at filling factor $\nu=1/3$, explicitly incorporating both finite layer thickness and disorder effects. The finite layer thickness is modeled by solving the Poisson-Schrödinger equations for the experimental devices, yielding the electron wave functions in the perpendicular direction. Using these and the disorder energy extracted from the experiment, we estimate the charge gap and the mobility gap at $\nu=1/3$ in the weakly disordered lowest Landau level. Remarkably, both gaps show good quantitative agreement with the activation gap measured from the experiment in narrow quantum wells. Our results also indicate the potential need of incorporating higher subbands to make accurate theoretical predictions of the energy gap in wide quantum wells.

Room-temperature, unshielded recording of cardiac magnetic signals has remained a significant challenge since the inception of magnetocardiography (MCG). In this work, we present an MCG system based on optically pumped magnetometers (OPMs) designed to operate in ambient magnetic environments and acquire adult human cardiac magnetic fields, without the need for active or passive shielding. The system operates in a gradiometer configuration, achieving background-noise cancellation with a common-mode rejection ratio (CMRR) of 31 dB and a gradient sensitivity of 314 $\mathrm{fT/cm/\sqrt{Hz}}$. MCG signals were acquired sequentially at 16 locations across the anterior thorax, and a comprehensive signal-analysis framework incorporating wavelet multiscale principal component analysis (WMSPCA) filtering and signal quality estimation (SQE) scoring was developed to enhance signal quality. This framework yielded a QRS complex signal-to-noise ratio (SNR) of $28.56 \pm 5.61$ dB across all measurement locations. These results demonstrate the feasibility of performing clinical-grade MCG in unshielded, real-world magnetic environments, with consistent morphological fidelity across the QRS complex and T-wave segments. This work represents a meaningful step toward the practical deployment of OPM-based MCG systems in hospital and point-of-care settings.

Inferring microscopic Hamiltonians from experimental data is a central challenge in quantum materials and quantum simulation. In low-dimensional spin systems, exchange interactions are often assumed to be spatially uniform, despite structural and environmental inhomogeneities that can locally modify the coupling. Here, we leverage a local, length-independent machine learning methodology to reconstruct spatially modulated exchange interactions directly from inelastic scanning tunneling spectroscopy maps. We demonstrate this approach with nanographene spin chains, identifying both near-uniform and inhomogeneous regimes across the synthesized magnets. The reconstructed models quantitatively reproduce the experimental spectra and recover the correct scaling of the excitation gap with system size. Our results establish a general strategy to bridge local spectroscopic measurements with effective many-body Hamiltonians.

We develop a time-local nonequilibrium Green's function formulation for real-time dynamics in quantum systems coupled to superconducting leads. The superconducting lead self-energy is a strongly frequency-dependent matrix in Nambu space, giving rise to nonlocal memory kernels in the time domain. This makes direct propagation of the Kadanoff-Baym (KB) equations computationally demanding. To overcome this difficulty, we extend the auxiliary-mode expansion, originally developed for normal-metal leads, to Nambu-space self-energies. This allows us to decompose the superconducting lead self-energy into a finite number of exponential modes and to transform the KB equations with memory integrals into a closed set of ordinary differential equations. The resulting time-local equations enable efficient real-time simulations under general time-dependent bias voltages, superconducting phases, and one-body Hamiltonians of the central system, while retaining the memory effects induced by superconducting leads. As an application, we analyze voltage-quench dynamics in a superconductor-quantum-dot-superconductor junction and show that, after a dc bias is suddenly applied, the system evolves through a transient regime and relaxes to an ac Josephson periodic steady state. The resulting periodic steady-state current agrees with the Floquet Green's function solution, validating the present real-time formulation.

Cooperative emission is a collective quantum optical process that requires macroscopic phase coherence among coupled emitters. Recent observations of cooperative emission in QD superlattices have renewed interest in how such coherence emerges in nanostructured solids. Meanwhile, theoretical studies have long discussed the relationship between electronic delocalization and coherence, particularly whether delocalized states necessarily give rise to cooperative emission. This study addresses this question through power-dependent steady-state PL and time-resolved PL decay measurements. The findings indicate that, although the quantum resonance peak exhibits delocalized excitonic characteristics, it shows no signatures of cooperative radiation. In particular, neither superlinear intensity scaling nor power-dependent emission delay was observed, indicating the absence of cooperative-radiation signatures. This can be understood from two disorder-related aspects. Temperature-dependent spectroscopy reveals pronounced inhomogeneous broadening and low-temperature dark-exciton participation, pointing to intra-domain static disorder and exciton-state mixing. These effects collectively hinder the establishment of macroscopic coherence. The temperature dependence of the quantum resonance peak decay lifetime is consistent with two-dimensional exciton dynamics. This work provides direct experimental evidence that electronic delocalization can be decoupled from cooperative coherence in CdSe quantum dot superlattices.

We derive an equation describing domain wall motion in antiferromagnets under the influence of normal strain. From this equation, we find that the domain wall moves towards positions where $\varepsilon_{xx}$ is high and $\varepsilon_{zz}$ is low. Furthermore, each strain component leads to a different terminal velocity for the same strain profile. This difference arises because both strains affect the domain wall width in opposite ways: $\varepsilon_{xx}$ reduces the width, whereas $\varepsilon_{zz}$ increases it. The model is then compared with mumax$^+$ simulations for various strain profiles, including a strain gradient, an oscillating strain, and a Rayleigh wave. The comparison shows good agreement between the analytical and numerical results. Finally, we demonstrate the potential of standing surface acoustic waves as an error correction method in racetrack memory.