Short-range Correlations Research Articles

Understanding the superconductivity and charge density wave interaction through quasi-static lattice fluctuations

In unconventional superconductors, coupled charge and lattice degrees of freedom can manifest in ordered phases of matter that are intertwined. In the cuprate family, fluctuating short-range charge correlations can coalesce into a longer-range charge density wave (CDW) order which is thought to intertwine with superconductivity, yet the nature of the interaction is still poorly understood. Here, by measuring subtle lattice fluctuations in underdoped YBa2Cu3O6+y on quasi-static timescales (thousands of seconds) through X-ray photon correlation spectroscopy, we report sensitivity to both superconductivity and CDW. The atomic lattice shows remarkably faster relaxational dynamics upon approaching the superconducting transition at Tc ≈ 65 K. By tracking the momentum dependence, we show that the intermediate scattering function almost monotonically scales with the relaxation distance of atoms away from their average positions above Tc and in the presence of the CDW state, while this peculiar trend is reversed for other temperatures. These observations are consistent with an incipient CDW stabilized by local strain. This work provides insights into the crucial role of relaxational atomic fluctuations for understanding the electronic physics cuprates, which are inherently disordered due to carrier doping.

Interplay between the charge density wave phase and a pseudogap under antiferromagnetic correlations

In this study, we explore the impact of short-range antiferromagnetic correlations on the charge density wave (CDW) phase in strongly correlated electron systems exhibiting the pseudogap phenomenon. Our investigation employs an n-pole approximation to consider the repulsive Coulomb interaction (U) and antiferromagnetic correlations. Considering an one-band Hubbard model to account for the Coulomb interaction and a BCS-like model for the CDW order parameter, we observed that an increase in U enhances antiferromagnetic fluctuations, resulting in a flattened re-normalized band around the antinodal point (π,0). The pseudogap manifests itself in the band structure and density of states, prompting exploration of various U and occupation number values. Our findings indicate that antiferromagnetic correlations significantly influence the CDW state, as the Fermi surface is reconstructed within the ordered phase. Furthermore, we found a Lifshitz transition inside both the CDW phase and the normal state, with the latter preceding the onset of the pseudogap.

Embedded multi-boson exchange: A step beyond quantum cluster theories

We introduce a diagrammatic multi-scale approach to the Hubbard model based on the interaction-irreducible (multi-boson) vertex of a small cluster embedded in a self-consistent medium. The vertex captures short-range correlations up to the length scale of the cluster, while long-range correlations are recovered from a set of diagrammatic equations for the Hedin three-leg vertex. By virtue of the crossing symmetry, the Fierz decoupling ambiguity of the Hubbard interaction is resolved exactly. Our benchmarks for the half-filled Hubbard model on the square lattice are in very good agreement with numerically exact diagrammatic Monte Carlo simulations. Published by the American Physical Society 2024

HNet: A deep learning based hybrid network for speaker dependent visual speech recognition

Visual Speech Recognition (VSR) is a popular area in computer vision research, attracting interest for its ability to precisely analyze lip motion and seamlessly convert them into textual representation. VSR systems leverage visual features to augment the understanding of automated speech and predict text. VSR finds various applications, including enhancing speech recognition in scenarios with degraded acoustic signals, aiding individuals with hearing impairments, bolstering security by reducing reliance on text based passwords, facilitating biometric authentication for liveness detection, and enabling underwater communications. Despite the various techniques proposed for improving the resilience and precision of automatic speech recognition, VSR still has challenges like homophones of words, gradient descent issues with varying sequence lengths, and lip reading demands accounting for short and long range correlations between consecutive video frames. We have proposed a hybrid network (HNet) with multilayered three dimensional dilated convolution neural network (3D-CNN). The spatio-temporal feature extraction process will be facilitated by dilated 3D-CNN. HNet integrates two bidirectional recurrent neural networks (BiGRU and BiLSTM) to process the feature sequences bidirectionally to establish the temporal relationship. The fusion of BiGRU-BiLSTM capabilities allows the model to process feature sequences more comprehensively and effectively. The proposed work focuses on face based biometric authentication for liveness detection using the VSR model to boost security against face spoofing. The existing face based biometric systems are widely used for individual authentication and verification but are still vulnerable to 3D masks and adversarial attacks. The VSR system can be added to existing face based verification systems as a second level authentication technique to identify a person with liveness. The working ideology of the VSR system will be based on the challenge response technique, where a person has to pronounce the passcode silently displayed on the screen. The VSR model assesses its effectiveness using word error rate (WER), which matches the pronounced passcode to the one presented on the screen. Overall, the proposed work aims to enhance the accuracy of VSR so that it can be combined with existing face based authentication systems. The proposed system outperforms the existing VSR system and obtained 1.3% WER. The significance of the proposed hybrid model is that it efficiently captures temporal dependencies, enhancing context embedding, improving robustness to input variability, reducing information loss, and enhancing performance and accuracy in modeling and analyzing passcode pronunciation patterns.

Universal Spreading of Conditional Mutual Information in Noisy Random Circuits.

We study the evolution of conditional mutual information (CMI) in generic open quantum systems, focusing on one-dimensional random circuits with interspersed local noise. Unlike in noiseless circuits, where CMI spreads linearly while being bounded by the light cone, we find that noisy random circuits with an error rate p exhibit superlinear propagation of CMI, which diverges far beyond the light cone at a critical circuit depth t_{c}∝p^{-1}. We demonstrate that the underlying mechanism for such rapid spreading is the combined effect of local noise and a scrambling unitary, which selectively removes short-range correlations while preserving long-range correlations. To analytically capture the dynamics of CMI in noisy random circuits, we introduce a coarse-graining method, and we validate our theoretical results through numerical simulations. Furthermore, we identify a universal scaling law governing the spreading of CMI.

Nuclear norm regularized loop optimization for tensor network

We propose a loop optimization algorithm based on nuclear norm regularization for the tensor network. The key ingredient of this scheme is to introduce a rank penalty term proposed in the context of data processing. Compared to the standard variational periodic matrix product states method, this algorithm can circumvent the local minima related to short-ranged correlation in a simpler fashion. We demonstrate its performance when used as a part of the tensor network renormalization algorithms [S. Yang, Z.-C. Gu, and X.-G. Wen, ] for the critical two-dimensional Ising model. The scale invariance of the renormalized tensors is attained with higher accuracy while the higher parts of the scaling dimension spectrum are obtained in a more stable fashion. Published by the American Physical Society 2024

A Frustrated Antipolar Phase Analogous to Classical Spin Liquids.

The study of magnetic frustration in classical spin systems is motivated by the prediction and discovery of classical spin liquid states. These uncommon magnetic phases are characterized by a massive degeneracy of their ground state implying a finite magnetic entropy at zero temperature. While the classical spin liquid state is originally predicted in the Ising triangular lattice antiferromagnet in 1950, this state has never been experimentally observed in any triangular magnets. The discovery of an electric analogue of classical spin liquids on a triangular lattice of uniaxial electric dipoles in EuAl12O19 is reported here. This new type of frustrated antipolar phase is characterized by a highly-degenerate state at low temperature implying an absence of long-range antiferroelectric order, despite short-range antipolar correlations. Its dynamics are governed by a thermally activated process, slowing down upon cooling toward a complete freezing at zerotemperature.

Short-Range Correlations and Urca Process in Neutron Stars.

Recent measurements of high-momentum correlated neutron-proton pairs at JLab suggest that the dense nucleonic component of the compact stars contains a fraction of high-momentum neutron-proton pairs that is not accounted for in the familiar Fermi-liquid theory of the neutron-proton fluid mixture. We compute the rate of the Urca process in compact stars taking into account the non-Fermi liquid contributions to the proton's spectral widths induced by short-range correlations. The Urca rate differs strongly from the Fermi-liquid prediction at low temperatures; in particular, the high threshold on the proton fraction precluding the Urca process in neutron stars is replaced by a smooth increase with the proton fraction. This observation may have a profound impact on the theories of cooling of compact stars.

Learning quantum properties from short-range correlations using multi-task networks

Characterizing multipartite quantum systems is crucial for quantum computing and many-body physics. The problem, however, becomes challenging when the system size is large and the properties of interest involve correlations among a large number of particles. Here we introduce a neural network model that can predict various quantum properties of many-body quantum states with constant correlation length, using only measurement data from a small number of neighboring sites. The model is based on the technique of multi-task learning, which we show to offer several advantages over traditional single-task approaches. Through numerical experiments, we show that multi-task learning can be applied to sufficiently regular states to predict global properties, like string order parameters, from the observation of short-range correlations, and to distinguish between quantum phases that cannot be distinguished by single-task networks. Remarkably, our model appears to be able to transfer information learnt from lower dimensional quantum systems to higher dimensional ones, and to make accurate predictions for Hamiltonians that were not seen in the training.

Unveiling short-range magnetic correlations: The development of magnetic pair distribution function method at CSNS

Recent advancements in the magnetic pair distribution function (mPDF) analysis of neutron total scattering data provide a powerful approach to investigate local magnetic correlations in materials. This technique is promising for revealing short-range magnetic correlations at the sub-nanometer length scale directly in real space. It is particularly suitable for strongly correlated electron systems and geometrically frustrated magnets. In this study, the mPDF experiment is conducted at the multi-physics instrument (MPI) of the China Spallation Neutron Source, one of the latest neutron total scattering diffractometers in the world. We systematically benchmarked a series of important parameters related to the experimental setup and data processing for mPDF experiments at the MPI and similar instruments. This method not only advances the magnetic structure determination of fundamental materials but also opens the door for extending mPDF studies to more complicated and frontier magnetic systems that are challenging for conventional diffraction methods.

Universality of quantum phase transitions in the integer and fractional quantum Hall regimes

Fractional quantum Hall (FQH) phases emerge due to strong electronic interactions and are characterized by anyonic quasiparticles, each distinguished by unique topological parameters, fractional charge, and statistics. In contrast, the integer quantum Hall (IQH) effects can be understood from the band topology of non-interacting electrons. We report a surprising super-universality of the critical behavior across all FQH and IQH transitions. Contrary to the anticipated state-dependent critical exponents, our findings reveal the same critical scaling exponent κ = 0.41 ± 0.02 and localization length exponent γ = 2.4 ± 0.2 for fractional and integer quantum Hall transitions. From these, we extract the value of the dynamical exponent z ≈ 1. We have achieved this in ultra-high mobility trilayer graphene devices with a metallic screening layer close to the conduction channels. The observation of these global critical exponents across various quantum Hall phase transitions was masked in previous studies by significant sample-to-sample variation in the measured values of κ in conventional semiconductor heterostructures, where long-range correlated disorder dominates. We show that the robust scaling exponents are valid in the limit of short-range disorder correlations.

Novel structures and collapse of solitons in nonminimally gravitating dark matter halos

Ultralight dark matter simulations predict condensates with short-range correlation, known as solitons or boson stars, at the centers of dark matter halos. This paper investigates the formation and collapse of dark matter solitons influenced by nonminimal gravitational effects, characterized by gradient-dependent self-interactions of dark matter and an additional source in Poisson's equation for gravity. Our simulations suggest that the initial evolution of dark matter resembles that without nonminimal gravitational effects. However, regions with negative potential curvature may develop, and solitons will collapse when their densities reach certain critical values for both positive and negative coupling constants. With strong nonminimal gravitational effects, we verify that linear density perturbations could grow on both large and small scales, potentially enhancing structure formation.

Universal Momentum Distributions and Short-Range Nucleon Correlations

The problem of constructing universal two-nucleon momentum distributions for main NN-configurations and – used to describe short-range nucleon correlations in nuclei has been studied. A new method for calculating such distributions has been proposed, and their properties have been studied. As illustrations, calculations for several modern realistic NN potentials, including non-nucleon degrees of freedom, have been provided. A new characteristic that determines the ratio of the fractions of high-momentum components for spin-singlet and spin-triplet NN distributions at low energies, which can be useful for comparative evaluation of the isospin dependence of short-range correlations in calculations with different NN interaction potentials, has been proposed.

A Review on Study Short-Range Correlations and the Isospin Dependence

High-energy electron scattering can be considered a crucial tool for interpreting the function of high-momentum nucleons (and quarks) in nuclei and offers a clean, accurate probing for investigations of hadronic and nuclear organization. The intense repulsion of nuclear contact at small distances is the source of short-range interactions in nuclei and nuclear matter. These connections have been verified in several nuclear tests using hadronic and electroweak probes. Improved knowledge of the underlying structure of these high-momentum and short-range arrangements in nuclei will be crucial for a variety of high-energy observables. The short-range correlations also appear to be associated with changes in the quark distributions in nuclei. Over the past ten years, there has been a significant concentration on both theoretical and experimental efforts aimed at characterizing short-range correlations, namely their isospin dependence. In this review, it will employ a theoretical framework rooted in many-body Green's functions theory. Specifically, review focus on the one-body momentum distributions as a fundamental variable. The objective is to provide a concise overview of the latest research findings in the field.

Effects of nucleon-nucleon short-range correlation and symmetry energy on the evolution of newly born magnetars

Abstract Millisecond magnetars are widely suggested as the central engines powering hydrogen-poor superluminous supernovae (SLSNe). These magnetars primarily lose huge rotational energy through gravitational wave radiation (GWR) and magnetic dipole radiation (MDR), with MDR serving as an energy source for SLSNe. We study the evolution of the magnetar spin, magnetic inclination angle, and the resulting thermal radiative luminosity of the SLSNe, where the impacts of the nucleon-nucleon short-range correlation, the mass and initial spin of the magnetar, and the density-dependent symmetry energy of the dense nuclear matter on the evolution are discussed. The relativistic mean-field theory is employed to calculate the nuclear matter properties, and we particularly concentrate on the time- and space-dependent bulk viscosity which is crucial for the magnetic inclination angle evolution. It is found that the nucleon-nucleon short-range correlation weakens the damping of bulk viscosity of dense matter and therefore inhibits the growth of magnetic inclination angle, and it reduces the MDR (GWR) peak luminosity of a canonical magnetar by several times while it raises the peak thermal radiation luminosity of SLSNe by several times. For magnetars with nonrotating mass obviously lower than the $1.4 \, \rm M_\odot$ with slow initial rotation, the magnetic inclination angle is more likely to evolve towards 0 degrees quickly, and these magnetars are not suitable as the central engine for SLSNe. Within the ‘family’ of FSUGarnet interaction, a stiffer symmetry energy gives a lower threshold of direct Urca process and hence gives a much larger bulk viscosity coefficient, and thus it promotes the growth of the magnetic inclination angle and the GWR for canonical stars but reduces the peak brightness of SLSNe significantly.

Reconstruction of Bremsstrahlung γ-rays spectrum in heavy ion reactions with Richardson-Lucy algorithm

The high momentum tail (HMT) in the momentum distribution of nucleons above the Fermi surface has been regarded as an evidence of short-range correlations (SRCs) in atomic nuclei. It has been showcased recently that the np Bremsstrahlung radiation in heavy ion reactions can be used to extract HMT information. The Richardson-Lucy (RL) algorithm is introduced to the reconstruction of the original Bremsstrahlung γ-ray energy spectrum from experimental measurements. By solving the inverse problem of the detector response to the γ-rays, the original energy spectrum of the Bremsstrahlung γ in 25 MeV/u 86Kr + 124Sn has been reconstructed and compared to the isospin- and momentum-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) simulations. The analysis based on hypothesis test suggests the existence of the HMT of nucleons in nuclei, in accordance with the previous conclusions. With its effectiveness being demonstrated, it is feasible to apply the RL algorithm in future experiments of measuring the Bremsstrahlung γ-rays in heavy ion reactions.

Self-Adapting Short-Range Correlation Functional for Complete Active Space-Based Approximations.

We propose a short-range correlation energy correction tailored for active space wave function models. The correction relies on a short-range multideterminant correlation functional computed with a local range-separation parameter that self-adapts to the underlying wave function. This approach is analogous to that of Giner et al. [J. Chem. Phys. 2018, 149, 194301] which addresses the basis set incompleteness error, with the vital distinction that in our protocol the range-separation parameter remains finite in the complete basis set limit, ensuring nonzero short-range correlation. The proposed correlation functional compensates for the missing short-range correlation via two mechanisms: (i) an automatically adapting short-range parameter, which gauges the missing correlation in the electron vicinity, and (ii) the functional's explicit dependence on the on-top pair density, which reduces short-range correlation in regions where electron correlation is mainly static. We integrate our method into the multireference adiabatic connection theory for CASSCF wave functions. The performance of the introduced CAS-AC0-(c,md) model is verified by calculating potential energy curves for alkaline-earth metal dimers (Be2, Mg2, Ca2) and for the chromium dimer, in all cases obtaining promising results.

Nuclear contacts of unstable nuclei

Nuclear contact is a key quantity to describe the nucleon-nucleon short-range correlations (SRCs). While they have been determined by electron scattering experiments for selected stable nuclei, nuclear contacts are largely unknown for unstable nuclei. In this work, we study nuclear contacts for a number of nuclei in the vicinity of the doubly magic 132Sn from the theoretical perspective, with special emphasis on unstable nuclei. We find that the proton-proton contact generally gets suppressed by the excess neutrons for the Sn isotopes, resembling the suppression of α-cluster formation reported recently for the same isotopic chain (J. Tanaka et al., 2021 [46]). This might suggest a hidden universal aspect of SRCs and α clustering, two different kinds of nuclear correlations. Moreover, we reveal a model-independent correlation between the proton-proton contact and the root-mean-square radius of proton density distributions for Sn isotopes. Meanwhile, a linear relation is found between the proton-proton contact and the proton number for the N=82 isotones. Our results can be helpful for future experimental studies of SRCs in unstable nuclei at advanced facilities worldwide.

Short-range expansion for the quantum many-body problem

In this work we derive a systematic short-range expansion of the many-body wave function. At leading order, the wave function is factorized to a zero-energy s-wave correlated pair and spectator particles, while terms that include energy derivatives and larger orbital angular momentum two-body functions appear at subleading orders. The validity of the expansion is tested for the two-body case, as well as the many-body case, where infinite neutron matter is considered. An accurate and consistent description of both coordinate-space two-body densities and the one-body momentum distribution is obtained. These results show the possibility to utilize such an expansion for describing different observables in strongly-interacting many-body systems, including nuclear, atomic and condensed-matter systems. This work also opens the path for a systematic description of large momentum transfer reactions in nuclear systems sensitive to short-range correlations, provides a link between such experiments and low-energy nuclear physics, and motivates measurement of new observables in these experiments.

Mechanism of overscreening breakdown by molecular-scale electrode surface morphology in asymmetric ionic liquids

The interfacial nature of the electric double layer (EDL) assumes that electrode surface morphology significantly impacts the EDL properties. Since molecular-scale roughness modifies the structure of EDL, it is expected to disturb the overscreening effect and alter differential capacitance (DC). In this paper, we present a model that describes EDL near atomically rough electrodes with account for short-range electrostatic correlations. We provide numerical and analytical solutions for the analysis of conditions for the overscreening breakdown and DC shift estimation. Our findings reveal that electrode surface structure leads to DC decrease and can both break or enhance overscreening depending on the relation of surface roughness to electrostatic correlation length and ion size asymmetry.