The post Chiral Gauge Field and Topological Magnetoelectric Response in Fully Spin-Polarized Magnetic Weyl Semimetal Co3Sn2S2 first appeared on JPS Hot Topics.

]]>Weyl semimetals are a class of materials characterized by the presence of Weyl points where the valence and conduction bands touch linearly. Electrons near these points behave as relativistic fermions called Weyl fermions, contributing to topological magnetoelectric responses, such as the anomalous Hall effect. The concept of chiral gauge field was introduced to understand these topological effects. This fictitious gauge field describes the shifts in the Weyl points in the momentum space. Previous studies have shown that a chiral gauge field can be generated by external perturbations, such as light and lattice strain. This enables one to understand their effects, similar to ordinary electromagnetic fields appearing in Maxwell’s equations.

In magnetic Weyl semimetals, the interplay between the magnetic ordering and the topological magnetoelectric responses is of particular interest. When spin–momentum locking is present, where the spin and momentum of Weyl fermions are parallel or antiparallel, the magnetization can be directly mapped to the chiral gauge field. This correspondence has led to the development of various magnetoelectric responses with potential spintronic functionalities. However, the spin–momentum locking structure depends on both spin–orbit coupling and spin polarization. This hinders the understanding of the topological magnetoelectric responses in realistic magnetic Weyl semimetals based on a chiral gauge field.

This study investigated the chiral gauge field in relation to the magnetization in the Weyl ferromagnet Co_{3}Sn_{2}S_{2}. The electrons in Co_{3}Sn_{2}S_{2} are nearly fully spin-polarized, leading to the absence of spin–momentum locking around the Weyl points. The effective model calculations in this study demonstrated that the positions of the Weyl points are significantly influenced by magnetization modulation, which can be described by the chiral gauge field. This result attributes the temporal and spatial variations in the magnetization within Co_{3}Sn_{2}S_{2} to the chiral electric and magnetic fields. The calculations demonstrated that a magnetic domain wall with a width of 10 nm generates a large chiral magnetic field of 260 T, leading to topological magnetoelectric responses. One consequence is the charge pumping driven by domain wall dynamics, which is analogous to the quantum Hall effect induced by chiral electromagnetic fields. This effect results in an electric voltage up to 800 times higher than the spin motive force observed in conventional ferromagnetic metals. This makes Co_{3}Sn_{2}S_{2} a promising material for detecting domain wall dynamics in spintronic devices, such as magnetic memories.

The insights gained from this study on the chiral gauge field in magnetic Weyl semimetals are expected to stimulate further exploration of novel topological magnetoelectric responses associated with magnetic textures and dynamics.

(Written by A. Ozawa and Y. Araki on behalf of all the authors)

The post Chiral Gauge Field and Topological Magnetoelectric Response in Fully Spin-Polarized Magnetic Weyl Semimetal Co3Sn2S2 first appeared on JPS Hot Topics.

]]>The post Fermi Machine — Quantum Many-Body Solver Derived from Mapping between Noninteracting and Strongly Correlated Fermions first appeared on JPS Hot Topics.

]]>When attempting to reach the exact ground states of interacting quantum systems, the computational cost increases exponentially with the system size in most cases and is thus intractable, which is known as an NP-hard problem. Unless accurate quantum computers become available, approximate but sufficiently accurate algorithms that are applicable to conventional computers need to be developed. This demand is particularly strong in research fields, such as condensed matter, high-energy physics, and chemistry.

Various methods have been developed to achieve these objectives. Recently, artificial neural networks based on machine learning have demonstrated promising performances. For instance, they contribute to establish the existence of a quantum spin liquid that embodies strong long-range quantum entanglement, which is expected to be useful in quantum computers and information transmission.

However, the existing neural networks employ classical variables, such as Ising spins for hidden variables in Boltzmann machines, to represent the interaction and entanglement effects. As quantum entanglement is not efficiently handled by classical operations, hidden quantum variables that efficiently handle long-range quantum entanglement are desired to be incorporated.

The question then is how to build an architecture that incorporates hidden quantum variables. A hint was provided by a recent understanding of strongly correlated electrons, particularly achieved by machine-learning analyses of spectroscopic experimental data and *ab initio* calculations of cuprate high-*T*_{c} superconductors. The key understanding is that electrons in the cuprates behave as if the original single electron is splintered into two noninteracting fermions, dubbed “electron fractionalization”, a remarkable but ubiquitous feature if bistability exists, as in examples near the first-order transitions.

A striking idea from this fractionalization is that strongly correlated fermions may be mapped to noninteracting systems, where the fractionalization is embodied by mutually hybridizing multiple components of fermions. As treating strong interaction and many-body entanglement is a widely recognized grand challenge, it would be astonishing if it is mapped to tractable noninteracting systems. One might be suspicious about this “free lunch”.

In this study, by taking the Hubbard model, known as a simple but challenging model of strongly correlated electrons, the exact mapping of the full Hilbert space of one- and two-site Hubbard models, to a two-component noninteracting fermion model (TCFM) is established. An extension of the mapping to larger systems and the architecture of the noninteracting multicomponent fermion model (MCFM) are proposed to simulate an any-sized Hubbard model, which enables a new quantum many-body solver called the Fermi machine. The Fermi machine easily treats quantum entanglement through the hybridization of hidden fermions and physical electrons, and easily reproduces the Mott insulator as well as the pseudogap states in cuprate superconductors by hybridization gaps.

The algorithm was tested for the four-site Hubbard model, and it easily reproduced the exact ground state by the MCFM. The Fermi machine has significant potential for accurate and functional quantum many-body solvers by utilizing the nature and structure of strongly correlated real electrons. The concept of mapping between strongly interacting quantum particles and tractable noninteracting quantum systems will provide the basis for a deeper understanding of the interacting quantum world.

(Written by Masatoshi Imada)

The post Fermi Machine — Quantum Many-Body Solver Derived from Mapping between Noninteracting and Strongly Correlated Fermions first appeared on JPS Hot Topics.

]]>The post Electricity Provides Cooling first appeared on JPS Hot Topics.

]]>Increasing temperatures to higher than the surrounding temperature is easier compared with decreasing temperatures to lower than the surrounding temperature. Many refrigerators and air conditioners use latent heat when liquid evaporates. Additionally, the Joule-Thomson effect and thermoelectric effect, termed the Peltier effect, have been used for cooling. Aligning magnetic moments using an external magnetic field is another useful method for controlling entropy. This magnetocaloric effect is useful in magnetic refrigeration, which is the most important technology for achieving extremely low temperatures.

In principle, an electric field can be used directly for cooling as the magnetic refrigeration. However, to date, no practical electric refrigerators exist, because the reported electrocaloric effect is much weaker than the magnetocaloric effect.

The strong correlation between different degrees of freedom in condensed matter allows an external field, such as a magnetic field, an electric field, and stress, to modulate the states in multiple degrees of freedom. For example, magnetism and electricity are tightly coupled in ferromagnetic ferroelectric materials, also known as multiferroics. Magnetic moments and atomic displacements are simultaneously controlled by an electric field, thus resulting in significant entropy change.

In this study, the electrocaloric effect of GdFeO_{3} is investigated. The Fe moments are aligned to host weak ferromagnetism below 661 K. Addition, antiferromagnetic ordering of Gd moments emerges below 2.5 K. The coupling between Fe and Gd moments induces parasitic ferroelectric polarization. In other words, the Gd moments and ferroelectric polarization are strongly coupled. Therefore, if an external electric field is applied (removed) under adiabatic conditions, then the ordering of the Gd magnetic moments is expected to be enhanced (weakened). Hence, the Gd moment system loses (gains) some entropy, as shown in the lower-left panel. Entropy must be transferred to (from) lattice vibrations, thus resulting in an increase (decrease) in temperature.

This effect was successfully observed using the measurement system shown schematically in the top-right panel. A typical experimental result is shown in the lower middle panel. As shown, the temperature of GdFeO_{3} increased and decreased owing to the application and removal of an external electric field, respectively, as predicted. The magnitude of the temperature change was determined by the initial temperature and external magnetic field, as shown in the two-dimensional color plot (bottom right panel). Furthermore, the energy efficiency was higher than that of typical magnetic caloric effects and adiabatic nuclear demagnetization.

(Written by T. Arima on behalf of all the authors)

The post Electricity Provides Cooling first appeared on JPS Hot Topics.

]]>The post A Promising Solution to Nucleon–Nucleon Inverse Scattering Problem first appeared on JPS Hot Topics.

]]>Linear or nonlinear dynamical models can explain various real-life phenomena. While linear approximations work well for some systems, others can only be explained by nonlinear models, which greatly complicates calculations. One such phenomenon is the elastic two-body quantum scattering of nucleons.

This scattering problem is described by the Variable Phase Approximation (VPA), a nonautonomous nonlinear differential equation. The inverse nuclear scattering problem, where the interaction potential is determined from the asymptotic phase shifts at different energies or angular momenta, is particularly difficult to solve due to its sensitivity and ill-conditioned nature.

While several approaches exist to solve this problem, none can perfectly identify the interaction potential without prior knowledge of the system and each approach gives slightly different results. In this study, researchers attempt to address this problem by utilizing the Volterra series expansion and incorporating neural networks to deal with the inverse scattering problem.

First, they describe the forward VPA problem using the Volterra expansion. Due to the nonautonomous nature of VPA, the original Volterra method had to be extended, resulting in a first-order Volterra model for s-wave scattering. This model offers a robust approximation over a wide operating range with potentials up to a few tens of Mega electronvolts (MeV).

However, in practical neutron scattering experiments where the potentials are larger, the first-order approximation alone is insufficient, necessitating higher-order terms to capture the remaining error. Instead of introducing higher-order terms, in this study, the researchers modeled the remaining error as a nonlinear noise term using radial basis function (RBF) neural networks. This allowed the system to still be described by the first-order Volterra model.

By expanding the interaction potential term with suitable polynomials containing unknown coefficients, the RBF-transformed model could be written as a system of linear equations, which can be easily solved. Finally, at the last stage, Spline basis functions were applied to weed out the remaining errors through small continuous changes in the potentials.

This model was applied to * ^{1}S_{0}* neutron-proton scattering at fixed angular momentum within the 1 to 200 MeV energy range, yielding accurate results with expected potentials and less than 1% averaged relative error in the phase shifts. This method is also versatile enough to be applied to nuclear scatterings at fixed energy.

In summary, this study represents a significant advancement in nonlinear modeling. Beyond physics, this method can also be applied in other fields, such as biology and aerospace engineering. Moreover, it offers a way to gain deeper insights into nonlinear problems in physics, both in theory and in experiments.

The post A Promising Solution to Nucleon–Nucleon Inverse Scattering Problem first appeared on JPS Hot Topics.

]]>The post A New Method for Finding Bound States in the Continuum first appeared on JPS Hot Topics.

]]>The bound state at positive energy or the bound state in the continuum (BIC) was first predicted by von Neumann and Wigner in 1929. Unlike conventional bound states, which can only exist at discrete negative energies below continuum spectra of scattering states with positive energies, BICs make use of nonlocality of potential to confine themselves in localized areas by preventing outgoing waves from escaping.

BICs have diverse applications in many fields, including photonics and acoustics. However, despite extensive research, they have not yet been observed in quantum systems.

Addressing this gap, a new study published in *Progress of Theoretical and Experimental Physics* presents a general theory of constructing potentials that support BICs. The theory shows that BICs can be found only in nonlocal potentials among all possible potentials localized in coordinate space. Interestingly, the study reveals that within this set, mostly consisting of non-local potentials, BICs are as common as negative-energy bound states.

The study introduces a method for constructing all possible Hermitian potentials supporting BICs, which through a process called SB-decomposition, can be expressed in terms of potentials *V*_{s} and *V*_{B} that operate on scattering and bound state spaces, respectively.

Through numerical examples, the study illustrates that for a given Hermitian potential *V*, through SB-decomposition followed by analyzing the potential of bound states *<k’|V _{B}|k*>, we can determine whether it supports a BIC. Additionally, through coordinate representation, the study shows that any potential that supports a BIC is necessarily non-local in coordinate space.

Furthermore, the study outlines methods for searching BICs in real systems with possible nonlocal potentials.

This groundbreaking research, by serving as a guide for harnessing BICs in real quantum systems, opens the door to new technologies with far-reaching implications.

The post A New Method for Finding Bound States in the Continuum first appeared on JPS Hot Topics.

]]>The post Understanding Non-Invertible Symmetries in Higher Dimensions Using Topological Defects first appeared on JPS Hot Topics.

]]>Symmetry is a fundamental concept of physics that describes how the laws of physics remain unchanged under certain transformations. Generalized symmetries are an extension of this concept, which, in recent times, has been applied to the analysis of quantum field theories. Among these are non-invertible symmetries which do not have inverse elements and cannot be undone, unlike traditional symmetries. However, they are less understood in higher dimensions than in two dimensions.

Generalized symmetries have been discovered by identifying the relations between symmetries and topological defects. These defects are like disruptions or “wrinkles” in the fabric of a physical system. They cannot be removed or smoothed out easily without creating a defect elsewhere. An interesting approach to understanding non-invertible symmetries is to construct topological defects.

Now, in a new study published in the *Progress of Theoretical and Experimental Physics*, researchers have, for the first time, presented concrete examples of non-invertible symmetries in four dimensions (4D) using this approach.

Specifically, the researchers constructed topological defects associated with the Kramers-Wannier-Wegner (KWW) duality in the 4D pure Z_{2} lattice gauge theory, similar to those in the two-dimensional Ising model. They discovered that these defects were non-invertible. Additionally, they constructed Z_{2} symmetry defects as well as defect junctions between these defects and the KWW duality defects. They derived the crossing relations and using these, calculated the expectation values for some of the defects.

Having accelerated the study of non-invertible symmetries in four-dimensional theories, this study was honored with the Outstanding Paper Award by the Physical Society of Japan. It marks a significant step towards understanding higher-dimensional non-invertible symmetries and the fundamental nature of the universe.

The post Understanding Non-Invertible Symmetries in Higher Dimensions Using Topological Defects first appeared on JPS Hot Topics.

]]>The post A Neural Thermometer for Predicting Phase Transitions of Unknown Systems first appeared on JPS Hot Topics.

]]>Machine learning has revolutionized research in fields hindered by experimental limitations. One notable application is identifying phases of matter that are classified by order parameters, which measure the degree of order within a system and signal phase transitions. These transitions can range from simple solid-liquid transformations to complex changes in magnetization or superconductivity. Identifying order parameters requires precise measurements that are often challenging with current technology. Additionally, some phases, like topological phases, lack clear order parameters, making them difficult to analyze.

Convolutional neural network (CNN)-based machine learning techniques have successfully classified phases in two- and three-dimensional systems. However, these techniques require labeled data, such as known phases or critical temperatures where phase transitions occur, to identify patterns and train the model. This limitation restricts their use for studying unknown systems, where information is not readily available.

In our study, we developed a novel CNN to determine phase transition temperatures directly from spin configurations of the system. The CNN consists of a convolutional layer that extracts patterns from the spin configurations, a single hidden layer, and a fully connected layer for (inverse) temperature prediction. We trained the CNN on data generated from the 2D Ising model, a simplified model of a magnetic system where spins are aligned either up or down on a 2D grid or lattice. In such a system, the spins tend to align below the critical temperature (the phase transition temperature), resulting in a magnetized phase. Using data generated through Monte Carlo simulations of the Ising model, the weights in the trained neural network captured features of the various spin configurations that signal phase transitions, enabling accurate prediction of critical temperatures.

Our model’s predictions of ferromagnetic phase transition temperatures closely matched the exact solutions. Although we used data generated by the Monte Carlo method for training, the model can also be applied to real data. The model is unique in that even though it was trained to just predict the (discretized) inverse temperatures of the inputs, it acquired the notion of phase transition coincidentally. This makes it particularly useful for studying completely unknown systems and statistical models in condensed matter physics. Additionally, unlike many neural networks that operate as black boxes and do not explain their predictions, this model provides insight into how it reaches its decisions in predicting critical temperatures, making it valuable for system analysis. For these contributions, our study received the Outstanding Paper Award from the Physical Society of Japan.

The post A Neural Thermometer for Predicting Phase Transitions of Unknown Systems first appeared on JPS Hot Topics.

]]>The post Pressure-Tuned Classical–Quantum Crossover in Magnetic Field-Induced Quantum Phase Transitions of a Triangular-Lattice Antiferromagnet first appeared on JPS Hot Topics.

]]>The high-pressure application is an experimental means to significantly alter the microscopic physical parameters of a material. At ambient pressure, these physical parameters generally do not change significantly, regardless of the temperature. Recently, the effects of high pressure have been studied across a broad area of condensed matter physics, including pressure-driven high-temperature superconductivity and topological phases. Frustrated quantum magnets are expected to be significantly affected by pressure because frustration due to competing interactions gives rise to many low-energy states with small energy differences. Additionally, small quantum fluctuations play an important role in manifesting unconventional physical phenomena, such as unconventional quantum phases. Therefore, applying external pressure to frustrated quantum materials enables the manipulation of quantum correlations across the classical and quantum mechanical regimes, facilitating the exploration of exotic phenomena along the crossover.

This study explores an exciting example of a frustrated antiferromagnet—triangular-lattice compound CsCuCl_{3}. To generate the phase diagram of magnetic field vs. pressure for this compound, we utilized our newly developed proximity detector oscillator system and high-pressure cell to measure magnetic susceptibility in pulsed magnetic fields exceeding the saturation field up to 55 T, under pressures of up to 2.08 GPa. We observed the field-induced quantum phase transitions from umbrella to up-up-down (UUD) and Y-coplanar phase immediately below the UUD phase above 0.90 and 1.7 GPa, respectively. Moreover, we calculated the pressure dependence of the transition fields, including the saturation field, and reliably determined the exchange interaction and easy-plane anisotropy parameters under pressure. With increasing pressure, the magnitude of the inter-chain antiferromagnetic exchange interaction increased linearly, whereas the magnitude of the intrachain ferromagnetic exchange interaction decreased significantly. Consequently, the ratio of the intra- to inter-chain exchange interactions decreased substantially with increasing pressure, indicating that the largely coupled ferromagnetic spins, regarded as semi-classical spins, became quantum spins. This suggests that the occurrence of the UUD and Y-coplanar phases is accompanied by a crossover from semiclassical to quantum spins in CsCuCl_{3}.

(Written by Masayuki Hagiwara on behalf of all authors)

The post Pressure-Tuned Classical–Quantum Crossover in Magnetic Field-Induced Quantum Phase Transitions of a Triangular-Lattice Antiferromagnet first appeared on JPS Hot Topics.

]]>The post Discovery of Light-Induced Mirror Symmetry Breaking first appeared on JPS Hot Topics.

]]>Light can break symmetries in time and space. For example, circularly polarized light can break the time-reversal symmetry. This time-reversal symmetry breaking can be used to generate the light-induced magnetization.

Despite several studies on the light-induced symmetry breaking, whether light can break mirror symmetries remains unclear.

Recently, we have demonstrated that circularly or linearly polarized light can break the mirror symmetries. We considered monolayer graphene periodically driven by circularly or linearly polarized light, and studied the effects of the light field on the mirror symmetries and charge transport. We demonstrated that the symmetries of the *xz *and *yz* mirror planes of monolayer graphene can be broken by circularly or linearly polarized light. We also observed that the mirror symmetry breaking can be characterized by the off-diagonal charge conductivity, which is the transport coefficient describing the charge current perpendicular to the applied electric field. The conductivity becomes antisymmetric or symmetric with respect to its indices when circularly or linearly polarized light, respectively, is applied. This difference is due to the difference in time-reversal symmetry.

This study discovered the light-induced mirror symmetry breaking, paving the way for the optical control of mirror symmetries and the realization of various phenomena utilizing the mirror symmetry breaking. This also indicates that the origin of the light-induced anomalous Hall effect, which is described by the antisymmetric off-diagonal charge conductivity, is not simply the light-induced time-reversal symmetry breaking, but a combination of this and the light-induced mirror symmetry breaking.

(Written by N. Arakawa on behalf of all authors.)

The post Discovery of Light-Induced Mirror Symmetry Breaking first appeared on JPS Hot Topics.

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