Using angle-resolved photoemission spectroscopy (ARPES), we study the electronic structure and electron-phonon coupling in a Li-doped graphene monolayer decoupled from the Co(0001) substrate by intercalation of silicon. Based on the photoelectron diffraction measurements, we disclose the structural properties of the Si/Co interface. Our density functional theory calculations demonstrate that in the studied Li/graphene/Si/Co system the magnetism of Co substrate induces notable magnetic moments on Li and Si atoms. At the same time graphene remains almost nonmagnetic and clamped between two magnetically active atomic layers with antiparallel magnetizations. ARPES maps of the graphene Fermi surface reveal strong electron doping, which may lead to superconductivity mediated by electron-phonon coupling (EPC). Analysis of the spectral function of photoelectrons reveals apparent anisotropy of EPC in the $k$ space. These properties make the studied system tempting for studying the relation between superconductivity and magnetism in two-dimensional materials.

We have determined the temperature evolution of the spin and orbital moments in the zero-magnetization ferromagnet ${\mathrm{Sm}}_{1-x}{\mathrm{Gd}}_x{\mathrm{Al}}_2$ ($x$ = 0.024) by combining polarized and unpolarized single crystal neutron diffraction data. The sensitivity of the polarized neutron technique has allowed the moment values to be determined with a precision of $\approx 0.1{\mu }_{\mathrm{B}}$. Our results clearly demonstrate that, when magnetized by a field of 8 T, the spin and orbital moments in ${\mathrm{Sm}}_{1-x}{\mathrm{Gd}}_x{\mathrm{Al}}_2$ are oppositely directed, so that the net magnetization is very small. Below 60 K the contributions from spin and orbital motions are both about $2{\mu }_{\mathrm{B}}$, with that due to orbital motion being slightly larger than that due to spin. Between 60 and 65 K the contributions of each to the magnetization fall rapidly and change sign at $T_{\mathrm{comp}} \approx 67\mathrm{K}$, above which the aligned moments recover but with the orbital magnetization still slightly higher than the spin one. These results imply that above $T_{\mathrm{comp}}$ the small resultant magnetization of the ${\mathrm{Sm}}^{3+}$ ion is oppositely directed to the magnetizing field. It is suggested that this anomaly is due to polarization of conduction electron spin associated with the doping ${\mathrm{Gd}}^{3+}$ ions.

We numerically study the effect of disorder on the stability of the many-body zero mode in a Kitaev chain with local interactions. Our numerical procedure allows us to resolve the position space and multiparticle structure of the zero modes, as well as providing estimates for the mean energy splitting between pairs of states of opposite fermion parity, over the full many-body spectrum. We find that the parameter space of a clean system can be divided into regions where interaction induced decay transitions are suppressed (region I) and where they are not (region II). In region I we observe that disorder has an adverse effect on the zero mode, which extends further into the bulk and is accompanied by an increased energy splitting between pairs of states of opposite parity. Conversely region II sees a more intricate effect of disorder, showing an enhancement of localization at the system's end accompanied by a reduction in the mean pairwise energy splitting. We discuss our results in the context of the many-body localization (MBL). We show that while the mechanism that drives the MBL transition also contributes to the fock-space localization of the many-body zero modes, measures that characterize the degree of MBL do not necessarily correlate with an enhancement of the zero mode or an improved stability of the topological region.

The Ising spin glass in two dimensions exhibits rich behavior with subtle differences in the scaling for different coupling distributions. We use recently developed mappings to graph-theoretic problems together with highly efficient implementations of combinatorial optimization algorithms to determine exact ground states for systems on square lattices with up to $10000\times 10000$ spins. While these mappings only work for planar graphs, for example for systems with periodic boundary conditions in at most one direction, we suggest here an iterative windowing technique that allows one to determine ground states for fully periodic samples up to sizes similar to those for the open-periodic case. Based on these techniques, a large number of disorder samples are used together with a careful finite-size scaling analysis to determine the stiffness exponents and domain-wall fractal dimensions with unprecedented accuracy, our best estimates being $\theta =-0.2793\left(3\right)$ and $d_{\mathrm{f}}=1.27319\left(9\right)$ for Gaussian couplings. For bimodal disorder, a new uniform sampling algorithm allows us to study the domain-wall fractal dimension, finding $d_{\mathrm{f}}=1.279\left(2\right)$. Additionally, we also investigate the distributions of ground-state energies, of domain-wall energies, and domain-wall lengths.

We measure many-body interactions in isolated quantum dot states using double-quantum multidimensional coherent spectroscopy. Few states are probed in a diffraction limited spot, which is enabled by a collinear scheme in which radiated four-wave-mixing signals are measured with phase resolution. Many-body interactions are enhanced by an additional prepulse tuned to the delocalized quasicontinuum states. We propose this as a method for controlling coupling between quantum states.

We report in this paper the temperature evolution of the magnetic structure of ${\mathrm{GdMn}}_2{\mathrm{O}}_5$, in the range 2–40 K, studied by neutron diffraction on an isotope-enriched powder. We detail a thorough analysis of the microscopic mechanisms needed to release the different magnetic frustrations that are at the origin of the polarization. In addition to the usual exchange-striction term, known to be at the origin of the polarization in this family, an additional exchange-striction effect between the ${\mathrm{Gd}}^{3+}$ and ${\mathrm{Mn}}^{3+}$ spins is found to be responsible for the very large polarization in the Gd compound.

We investigate the electron and nuclear spin coherence properties of ytterbium (${\mathrm{Yb}}^{3+}$) ions with nonzero nuclear spin, within an yttrium orthosilicate (${\mathrm{Y}}_2{\mathrm{SiO}}_5$) crystal, with a view to their potential application in quantum memories or repeaters. We find electron spin-lattice relaxation times are maximized at low magnetic field ($<100$ mT), where $g\sim 6$, reaching 5 s at 2.5 K, while coherence times are maximized when addressing ESR transitions at higher fields where $g\sim 0.7$, where a Hahn echo measurement yields $T_2$ up to 73 $\mu \mathrm{s}$. Dynamical decoupling can be used to suppress spectral diffusion and extend the coherence lifetime to over 0.5 ms, close to the limit of instantaneous diffusion. Using Davies electron-nuclear double resonance, we performed coherent control of the ${}^{173}\mathrm{Yb}^{3+}$ nuclear spin and studied its relaxation dynamics. At around 4.5 K we measure nuclear spins $T_1$ and $T_2$ of 4 and 0.35 ms, respectively, about 4 and 14 times longer than the corresponding times for the electron spin.

We discuss the Heisenberg model and its chiral extension in an extended truncation with the help of functional methods. Employing computer algebra to derive the beta functions, and pseudo-spectral methods to solve them, we are able to go significantly beyond earlier approximations, and provide new estimates on the critical quantities of both models. The fixed point of the Heisenberg model is mostly understood, and our results are in agreement with estimates from various other approaches, including Monte Carlo and conformal bootstrap studies. By contrast, in the chiral case, the formerly known disagreement with lattice studies persists, raising the question whether actually the same universality class is described.

We provide a systematic study of non-Hermitian topologically charged systems. Starting from a Hermitian Hamiltonian supporting Weyl points with arbitrary topological charge, adding a non-Hermitian perturbation transforms the Weyl points to one-dimensional exceptional contours. We analytically prove that the topological charge is preserved on the exceptional contours. In contrast to Hermitian systems, the addition of gain and loss allows for a new class of topological phase transition: when two oppositely charged exceptional contours touch, the topological charge can dissipate without opening a gap. These effects can be demonstrated in realistic photonics and acoustics systems.

We study the stabilization of an isolated magnetic skyrmion in a magnetic monolayer on a nonmagnetic conducting substrate via the Ruderman-Kittel-Kasuya-Yosida (RKKY) exchange interaction. Two different types of the substrate are considered, usual normal metal and single-layer graphene. While the full stability analysis for skyrmions in the presence of the RKKY coupling requires a separate effort that is outside the scope of this work, we are able to study the radial stability (stability of a skyrmion against collapse) using variational energy estimates obtained within first-order perturbation theory, with the unperturbed Hamiltonian describing the isotropic Heisenberg magnet, and the two perturbations being the RKKY exchange and the easy-axis anisotropy. We show that a proper treatment of the long-range nature of the RKKY interaction leads to a qualitatively different stabilization scenario compared to previous studies, where solitons were stabilized by the frustrated exchange coupling (leading to terms with the fourth power of the magnetization gradients) or by the Dzyaloshinskii-Moriya interaction (described by terms linear in the magnetization gradients). In the case of a metallic substrate, the skyrmion stabilization is possible under restrictive conditions on the Fermi surface parameters, while in the case of a graphene substrate the stabilization is naturally achieved in several geometries with a lattice-matching of graphene and magnetic layer.

Angle-resolved secondary electron emission (ARSEE) spectra were analyzed for two-dimensional atomic sheets using a time-dependent first-principles simulation of electron scattering. We demonstrate that the calculated ARSEE spectra capture the unoccupied band structure of the atomic sheets. The excitation dynamics that lead to SEE have also been revealed by the time-dependent Kohn-Sham decomposition scheme. In the present study, the mechanism for the experimentally observed ARSEE from atomic sheets is elucidated with respect to both energetics and the dynamical aspects of SEE.

We describe a mechanism by which fermions in topologically trivial bands can form correlated states exhibiting a fractional quantum Hall (FQH) effect upon introduction of strong repulsive interactions. These states are solid-liquid composites, in which a FQH liquid is induced by the formation of charge order (CO), following a recently proposed paradigm of symmetry-breaking topological (SBT) order [Phys. Rev. Lett. 113, 216404 (2014)]. We devise a spinless fermion model on a triangular lattice, featuring a topologically trivial phase when interactions are omitted. Adding strong short-range repulsion, we first establish a repulsion-driven CO phase at density ${\rho }_{\mathrm{CO}}=2/3$ particles per site, then dope the model to higher densities $\rho ={\rho }_{\mathrm{CO}}+\nu /6$. At $\nu =1/3,2/5$ ($\rho =13/18,11/15$) we observe definitive signatures of both CO and the FQH effect—a sharply peaked static structure factor, gapped and degenerate energy spectrum, and fractionally quantized Hall conductivity ${\sigma }_{\mathrm{H}}=1/3,2/5$ in units of $e^2/h$—over a range of all model parameters. We thus obtain direct evidence for fermionic SBT order of FQH type in topologically trivial bands.

Ultrapure conductors may exhibit hydrodynamic transport where the collective motion of charge carriers resembles the flow of a viscous fluid. In a confined geometry (e.g., in ultra-high-quality nanostructures), the electronic fluid assumes a Poiseuille-type flow. Applying an external magnetic field tends to diminish viscous effects leading to large negative magnetoresistance. In two-component systems near charge neutrality, the hydrodynamic flow of charge carriers is strongly affected by the mutual friction between the two constituents. At low fields, the magnetoresistance is negative, however, at high fields the interplay between electron-hole scattering, recombination, and viscosity results in a dramatic change of the flow profile: the magnetoresistance changes its sign and eventually becomes linear in very high fields. This nonmonotonic magnetoresistance can be used as a fingerprint to detect viscous flow in two-component conducting systems.

The restricted Boltzmann machine (RBM) is one of the fundamental building blocks of deep learning. RBM finds wide applications in dimensional reduction, feature extraction, and recommender systems via modeling the probability distributions of a variety of input data including natural images, speech signals, and customer ratings, etc. We build a bridge between RBM and tensor network states (TNS) widely used in quantum many-body physics research. We devise efficient algorithms to translate an RBM into the commonly used TNS. Conversely, we give sufficient and necessary conditions to determine whether a TNS can be transformed into an RBM of given architectures. Revealing these general and constructive connections can cross fertilize both deep learning and quantum many-body physics. Notably, by exploiting the entanglement entropy bound of TNS, we can rigorously quantify the expressive power of RBM on complex data sets. Insights into TNS and its entanglement capacity can guide the design of more powerful deep learning architectures. On the other hand, RBM can represent quantum many-body states with fewer parameters compared to TNS, which may allow more efficient classical simulations.

We report that the sample miniaturization of first-order-phase-transition bulk systems causes a greater degree of supercooling. From a theoretical perspective, the size effects can be rationalized by considering two mechanisms: (i) the nucleation is a rare and stochastic event, and thus, its rate is correlated with the volume and/or surface area of a given sample; (ii) when the sample size decreases, the dominant heterogeneous nucleation sites that play a primary role for relatively large samples are annealed out. We experimentally verified the size effects on the supercooling phenomena for two different types of strongly correlated electron systems: the transition-metal dichalcogenide ${\mathrm{IrTe}}_2$ and the organic conductor $\theta \text{−}{\left(\mathrm{BEDT}\text{−}\mathrm{TTF}\right)}_2\mathrm{RbZn}{\left(\mathrm{SCN}\right)}_4$. The origin of the size effects considered in this study does not depend on microscopic details of the material; therefore, they may often be involved in the first-order-transition behavior of small-volume specimens.

Suspended metallic carbon nanotubes (m-CNTs) exhibit a remarkably large transport gap that can exceed 100 meV. Both experiment and theory suggest that strong electron-electron interactions play a crucial role in generating this electronic structure. To further understand this strongly interacting system, we have performed electronic measurements of suspended m-CNTs with known diameter and chiral angle. Spectrally resolved photocurrent microscopy was used to determine m-CNT structure. The room-temperature electrical characteristics of 18 individually contacted m-CNTs were compared to their respective diameter and chiral angle. At the charge neutrality point, we observe a peak in m-CNT resistance that scales exponentially with inverse diameter. Using a thermally activated transport model, we estimate that the transport gap is (450 meV nm)/$D$, where $D$ is CNT diameter. We find no correlation between the gap and the CNT chiral angle. Our results add important constraints to theories attempting to describe the electronic structure of m-CNTs.

Motivated by the close relations of the renormalization group with both the holography duality and the deep learning, we propose that the holographic geometry can emerge from deep learning the entanglement feature of a quantum many-body state. We develop a concrete algorithm, call the entanglement feature learning (EFL), based on the random tensor network (RTN) model for the tensor network holography. We show that each RTN can be mapped to a Boltzmann machine, trained by the entanglement entropies over all subregions of a given quantum many-body state. The goal is to construct the optimal RTN that best reproduce the entanglement feature. The RTN geometry can then be interpreted as the emergent holographic geometry. We demonstrate the EFL algorithm on a 1D free fermion system and observe the emergence of the hyperbolic geometry (${\mathrm{AdS}}_3$ spatial geometry) as we tune the fermion system towards the gapless critical point (${\mathrm{CFT}}_2$ point).

The microscopic state of a magnetic material is characterized by its resonant magneto-optical response through the off-diagonal dielectric tensor component ${\epsilon }_{xy}$. However, the measurement of the full complex ${\epsilon }_{xy}$ in the extreme ultraviolet spectral region covering the $M$ absorption edges of $3d$ ferromagnets is challenging due to the need for either a careful polarization analysis, which is complicated by a lack of efficient polarization analyzers, or scanning the angle of incidence in fine steps. Here, we propose and demonstrate a technique to extract the complex resonant permittivity ${\epsilon }_{xy}$ simply by scanning the polarization angle of linearly polarized high harmonics to measure the magneto-optical asymmetry in reflection geometry. Because this technique is more practical and faster to experimentally implement than previous approaches, we can directly measure the full time evolution of ${\epsilon }_{xy}\left(t\right)$ during laser-induced demagnetization across the entire $M_{2,3}$ absorption edge of cobalt with femtosecond time resolution. We find that for polycrystalline Co films on an insulating substrate, the changes in ${\epsilon }_{xy}$ are uniform throughout the spectrum, to within our experimental precision. This result suggests that, in the regime of strong demagnetization, the ultrafast demagnetization response is primarily dominated by magnon generation. We estimate the contribution of exchange-splitting reduction to the ultrafast demagnetization process to be no more than 25%.

We use first-principles methods to investigate the energetics of oxygen-octahedra rotations in $AB{\mathrm{O}}_3$ perovskite oxides. We focus on the short-period, perfectly antiphase or in-phase, tilt patterns that characterize the structure of most compounds and control their physical (e.g., conductive, magnetic) properties. Based on an analytical form of the relevant potential energy surface, we discuss the conditions for the stability of various polymorphs presenting different rotation patterns, and obtain numerical results for a collection of thirty-five representative materials. Our results reveal the mechanisms responsible for the frequent occurrence of a particular structure that combines antiphase and in-phase rotations, i.e., the orthorhombic $Pbnm$ phase displayed by about half of all perovskite oxides, as well as by many nonoxidic perovskites. In essence, the $Pbnm$ phase benefits from the simultaneous occurrence of antiphase and in-phase tilt patterns that compete with each other, but not as strongly as to be mutually exclusive. We also find that secondary antipolar modes, involving the $A$ cations, contribute to weaken the competition between tilts of different types, and thus play a key role in the stabilization of the $Pbnm$ structure. Our results thus confirm and better explain previous observations for particular compounds in the literature. Interestingly, we also find that strain effects, which are known to be a major factor governing phase competition in related (e.g., ferroelectric) perovskite oxides, play no essential role as regards the relative stability of different rotational polymorphs. Further, we discuss why the $Pbnm$ structure stops being the ground state in two opposite limits—namely, for large and small $A$ cations—showing that very different effects become relevant in each case. Our work thus provides a comprehensive discussion and reference data on these all-important and abundant materials, which will be useful to better understand existing compounds as well as to identify new strategies for materials engineering.

Efficient and automated classification of phases from minimally processed data is one goal of machine learning in condensed-matter and statistical physics. Supervised algorithms trained on raw samples of microstates can successfully detect conventional phase transitions via learning a bulk feature such as an order parameter. In this paper, we investigate whether neural networks can learn to classify phases based on topological defects. We address this question on the two-dimensional classical XY model which exhibits a Kosterlitz-Thouless transition. We find significant feature engineering of the raw spin states is required to convincingly claim that features of the vortex configurations are responsible for learning the transition temperature. We further show a single-layer network does not correctly classify the phases of the XY model, while a convolutional network easily performs classification by learning the global magnetization. Finally, we design a deep network capable of learning vortices without feature engineering. We demonstrate the detection of vortices does not necessarily result in the best classification accuracy, especially for lattices of less than approximately 1000 spins. For larger systems, it remains a difficult task to learn vortices.