arXiv subjects

Hidemaro Suwa

Publications and source records attributed to Hidemaro Suwa.

At least 19 recordsLinked to original sources

arXiv2026

Dynamical structure factor with a pumping approach on a trapped-ion quantum computer

Dynamical structure factors (DSF) measured with neutron-scattering experiments provide key insights into the structure of materials. Their computation requires both the preparation of an equilibrium state and the implementation of Hamiltonian dynamics. We demonstrate the feasibility of computing DSF on the Quantinuum Reimei trapped-ion quantum computer, comparing the DSF of 1D Heisenberg model on $20$ sites, and that of the copper sulfate crystal. To that end, we introduce a pumping approach for computing the DSF $S(q,\omega)$ on quantum computers that enables targeting specific arbitrary values of frequencies $\omega$. This method time-evolves the initial state using a time-dependent Hamiltonian perturbed by a source term oscillating at the target frequency $\omega$. When targeting only a few frequency values, this approach provides a significant reduction in shot overhead compared to previous methods.

quant-ph↗

arXiv2026

Semiclassical representation of the Hubbard model

By revisiting the path-integral formulation of the Hubbard model, we propose a theoretical approach based on a semiclassical approximation employing an unconventional coherent-state representation. Within this framework, a subset of the dynamical variables is treated as static, yielding a nonperturbative scheme that is applicable at finite temperature, incorporates intersite correlations, and can be naturally extended to multiorbital systems. We assess the validity of the approximation by comparing its results with exact solutions for one- and two-site systems, focusing in particular on the particle number, double occupancy, hopping amplitude, and spin correlations, and find that the present approach qualitatively reproduces the exact behavior. Quantitatively, deviations arise, which is associated with the continuum (non-discretized) character of the underlying density of states. Furthermore, we derive the exact transformation associated with the coherent-state construction, thereby providing additional insight into the representation of the Hubbard model.

cond-mat.str-el↗

arXiv2026

Unified Description of Spin-Lattice Coupling and Thermodynamics in the Pyrochlore Heisenberg Antiferromagnet

We study an extended model to describe the spin-lattice coupling, incorporating individual vibrations of bonds and atomic sites alongside distance-dependent exchange interactions. The proposed spin Hamiltonian can be effectively considered as an interpolation between two well-established minimum models, the bond-phonon model and the site-phonon model. The extended model, which treats bond phonons and site phonons on comparable footing, well reproduces successive field-induced phase transitions as well as the thermodynamic properties of a three-up-one-down state in the pyrochlore-lattice Heisenberg antiferromagnet, including negative thermal expansion, an enhanced magnetocaloric effect, and a sharp specific-heat peak. The present approach is broadly applicable to various spin models, providing a framework for identifying the primary phonon modes responsible for spin-lattice coupling and for understanding complex magnetic phase diagrams.

cond-mat.str-el↗

arXiv2025

Thermally quenched metastable phase in the Ising model with competing interactions

Thermal quenching has been used to find metastable materials such as hard steels and metallic glasses. More recently, quenching-based phase control has been applied to correlated electron systems that exhibit metal--insulator, magnetic or superconducting transitions. Despite the discovery of metastable electronic phases, however, how metastability is achieved through the degrees of freedom, which can vary even at low temperatures such as those of an electron, is unclear. Here, we show a thermally quenched metastable phase in the Ising model without conservation of magnetization by Monte Carlo simulations. When multiple types of interactions that stabilize different long-range orders are introduced, the ordering kinetics divergently slow toward low temperatures, meaning that the system will reach a low temperature without ordering if the cooling rate is high enough. Quantitative analysis of the divergent behavior suggests that the energy barrier for eliminating the local structure of competing orders is the origin of this metastability. Thus, the present simulations show that competing interactions play a key role in realizing metastability.

cond-mat.mtrl-sci↗

arXiv2024

Control of probability flow in Markov chain Monte Carlo -- Nonreversibility and lifting

The Markov chain Monte Carlo (MCMC) method is widely used in various fields as a powerful numerical integration technique for systems with many degrees of freedom. In MCMC methods, probabilistic state transitions can be considered as a random walk in state space, and random walks allow for sampling from complex distributions. However, paradoxically, it is necessary to carefully suppress the randomness of the random walk to improve computational efficiency. By breaking detailed balance, we can create a probability flow in the state space and perform more efficient sampling along this flow. Motivated by this idea, practical and efficient nonreversible MCMC methods have been developed over the past ten years. In particular, the lifting technique, which introduces probability flows in an extended state space, has been applied to various systems and has proven more efficient than conventional reversible updates. We review and discuss several practical approaches to implementing nonreversible MCMC methods, including the shift method in the cumulative distribution and the directed-worm algorithm.

cond-mat.stat-mech↗

arXiv2024

Electronic Raman scattering of antiferromagnetic excitonic insulators

The excitonic insulator, a quantum mechanical state arising from exciton condensation, was proposed theoretically many years ago but has yet to be experimentally confirmed. The discovery of correlated transition metal oxides based on $4d$ and $5d$ elements, where the on-site Coulomb repulsion is comparable to the dominant hopping amplitude, presents a unique opportunity to study exciton condensation. By constructing an effective mean field Raman operator for the Hubbard model, we derive the low-energy electronic Raman scattering cross section, demonstrating Raman spectroscopy as a powerful tool for detecting exciton condensation. Here, we demonstrate that Raman scattering directly reveals exciton condensation in the bilayer iridate Sr$_3$Ir$_2$O$_7$ under pressure.

cond-mat.str-el↗

arXiv2023

Extraordinary magnetic response of an anisotropic 2D antiferromagnet via site-dilution

A prominent character of two-dimensional magnetic systems is the enhanced spin fluctuations, which however reduce the ordering temperature. Here we report that a magnetic field of only one-thousandth of the Heisenberg superexchange interaction can induce a crossover, which for practical purposes is the effective ordering transition, at temperatures about 6 times of the Neel transition in a site-diluted two-dimensional anisotropic quantum antiferromagnet. Such a strong magnetic response is enabled because the system directly enters the antiferromagnetically ordered state from the isotropic disordered state skipping the intermediate anisotropic stage. The underlying mechanism is achieved on a pseudospin-half square lattice realized in the [(SrIrO3)1/(SrTiO3)2] superlattice thin film that is designed to linearly couple the staggered magnetization to external magnetic fields by virtue of the rotational symmetry-preserving Dzyaloshinskii Moriya interaction. Our model analysis shows that the skipping of the anisotropic regime despite the finite anisotropy is due to the enhanced isotropic fluctuations under moderate dilution.

cond-mat.str-el↗

arXiv2023

Reducing rejection exponentially improves Markov chain Monte Carlo sampling

The choice of transition kernel critically influences the performance of the Markov chain Monte Carlo method. Despite the importance of kernel choice, guiding principles for optimal kernels have not been established. Here, we propose a one-parameter rejection control transition kernel that can be applied to various Monte Carlo samplings and demonstrate that the rejection process plays a major role in determining the sampling efficiency. Varying the rejection probability, we examine the autocorrelation time of the order parameter in the two- and three-dimensional ferromagnetic Potts models. Our results reveal that reducing the rejection rate leads to an exponential decrease in autocorrelation time in sequential spin updates and an algebraic reduction in random spin updates. The autocorrelation times of conventional algorithms almost fall on a single curve as a function of the rejection rate. The present transition kernel with an optimal parameter provides one of the most efficient samplers for general cases of discrete variables.

cond-mat.stat-mech↗

arXiv2022

Matrix Product Renormalization Group: Potential Universal Quantum Many-Body Solver

The density matrix renormalization group (DMRG) is a celebrated tensor network algorithm, which computes the ground states of one-dimensional quantum many-body systems very efficiently. Here we propose an improved formulation of continuous tensor network algorithms, which we name a matrix product renormalization group (MPRG). MPRG is a universal quantum many-body solver, which potentially works at both zero and finite temperatures, in two and higher dimensions, and is even applicable to open quantum systems. Furthermore, MPRG does not rely on any variational principles and thus supports any kind of non-Hermitian systems in any dimension. As a demonstration, we present critical properties of the Yang-Lee edge singularity in one dimension as a representative non-Hermitian system.

cond-mat.str-el↗

arXiv2022

Lifted directed-worm algorithm

Nonreversible Markov chains can outperform reversible chains in the Markov chain Monte Carlo method. Lifting is a versatile approach to introducing net stochastic flow in state space and constructing a nonreversible Markov chain. We present here an application of the lifting technique to the directed-worm algorithm. The transition probability of the worm update is optimized using the geometric allocation approach; the worm backscattering probability is minimized, and the stochastic flow breaking the detailed balance is maximized. We demonstrate the performance improvement over the previous worm and cluster algorithms for the four-dimensional hypercubic lattice Ising model. The sampling efficiency of the present algorithm is approximately 80, 5, and 1.7 times as high as those of the standard worm algorithm, the Wolff cluster algorithm, and the previous lifted worm algorithm, respectively. We estimate the dynamic critical exponent of the hypercubic lattice Ising model to be $z \approx 0$ in the worm and the Wolff cluster updates. The lifted version of the directed-worm algorithm can be applied to a variety of quantum systems as well as classical systems.

cond-mat.stat-mech↗

arXiv2022

BCS-BEC Crossover of Triplet Exciton Condensation in Bilayer Systems

We study the BCS-BEC crossover phenomenon of triplet exciton condensation using a half-filled bilayer Hubbard model. We calculate the dynamical spin structure factor and the exciton wave function on the phase boundary between the antiferromagnetically ordered and disordered phases. In the BCS regime, the formation and condensation of particle-hole bound states, namely excitons, occur simultaneously at the phase transition point, and the exciton wave function is extended in real space. In the BEC regime, on the other hand, bound states are well defined over the whole Brillouin zone also in the disordered phase, and the size of particle-hole pairs is smaller than a lattice space. Quantum criticality of charge-spin-orbital entangled states can emerge from intermediate coupling materials in the crossover regime.

cond-mat.str-el↗

arXiv2022

Quasi-2D anomalous Hall Mott insulator of topologically engineered Jeff =1/2 electrons

We investigate an experimental toy-model system of a pseudospin-half square-lattice Hubbard Hamiltonian in [(SrIrO3)1/(CaTiO3)1] to include both nontrivial complex hopping and moderate electronic correlation. While the former induces electronic Berry phases as anticipated from the weak-coupling limit, the later stabilizes an antiferromagnetic (AFM) Mott insulator ground state in analogous to the strong-coupling limit. Their combined results in the real system are found to be an anomalous Hall effect with a non-monotonic temperature dependence due to the self-competition of the electron-hole pairing in the Mott state, and an exceptionally large Ising anisotropy that is captured as a giant magnon gap beyond the superexchange approach. The unusual phenomena highlight the rich interplay of electronic topology and electronic correlation in the intermediate-coupling regime that is largely unexplored and challenging in theoretical modelling.

cond-mat.str-el↗

arXiv2022

Nematicity and fractional magnetization plateaus induced by spin-lattice coupling in the classical kagome-lattice Heisenberg antiferromagnet

We investigate the effect of spin-lattice coupling (SLC) on the magnetic properties of the classical kagome-lattice Heisenberg antiferromagnet (KHAF) using improved Monte Carlo updates. The lattice modes are represented by Einstein site phonons, which introduce effective further-neighbor spin interactions in addition to the nearest-neighbor biquadratic interactions. In the weak SLC, the macroscopically degenerate coplanar ground state remains at zero field, while a $\sqrt{3} \times \sqrt{3}$ ordered phase accompanied by a 1/3-magnetization plateau appears in external magnetic fields. In the strong SLC, we find a nematic order at zero field and a 1/9-magnetization plateau associated with a $3 \times 3$ collinear order. Near the phase transition between the 1/9- and 1/3-plateau states, the ergodicity in the single spin flip is practically broken, and slow dynamics appear. We propose that relevant KHAFs with strong SLC would be realized in spinel-based materials.

cond-mat.str-el↗

arXiv2021

Neural Network Approach to Construction of Classical Integrable Systems

Integrable systems have provided various insights into physical phenomena and mathematics. The way of constructing many-body integrable systems is limited to few ansatzes for the Lax pair, except for highly inventive findings of conserved quantities. Machine learning techniques have recently been applied to broad physics fields and proven powerful for building non-trivial transformations and potential functions. We here propose a machine learning approach to a systematic construction of classical integrable systems. Given the Hamiltonian or samples in latent space, our neural network simultaneously learns the corresponding natural Hamiltonian in real space and the canonical transformation between the latent space and the real space variables. We also propose a loss function for building integrable systems and demonstrate successful unsupervised learning for the Toda lattice. Our approach enables exploring new integrable systems without any prior knowledge about the canonical transformation or any ansatz for the Lax pair.

nlin.SI↗

arXiv2021

Exciton condensation in bilayer spin-orbit insulator

We investigate the nature of the magnetic excitations of a bilayer single-orbital Hubbard model in the intermediate-coupling regime. This model exhibits a quantum phase transition (QPT) between a paramagnetic (PM) and an insulating antiferromagnetic (AFM) phase at a critical value of the coupling strength. By using the random phase approximation, we show that the QPT is continuous when the PM state is a band insulator and that the corresponding quantum critical point (QCP) arises from the condensation of preformed excitons. These low-energy excitons reemerge on the other side of the QCP as the transverse and longitudinal modes of the AFM state. In particular, the longitudinal mode remains sharp for the model parameters relevant to Sr$_{3}$Ir$_{2}$O$_{7}$ because of the strong easy-axis anisotropy of this material.

cond-mat.str-el↗

arXiv2021

Geometric allocation approach to accelerating directed worm algorithm

The worm algorithm is a versatile technique in the Markov chain Monte Carlo method for both classical and quantum systems. The algorithm substantially alleviates critical slowing down and reduces the dynamic critical exponents of various classical systems. It is crucial to improve the algorithm and push the boundary of the Monte Carlo method for physical systems. We here propose a directed worm algorithm that significantly improves computational efficiency. We use the geometric allocation approach to optimize the worm scattering process: worm backscattering is averted, and forward scattering is favored. Our approach successfully enhances the diffusivity of the worm head (kink), which is evident in the probability distribution of the relative position of the two kinks. Performance improvement is demonstrated for the Ising model at the critical temperature by measurement of exponential autocorrelation times and asymptotic variances. The present worm update is approximately 25 times as efficient as the conventional worm update for the simple cubic lattice model. Surprisingly, our algorithm is even more efficient than the Wolff cluster algorithm, which is one of the best update algorithms. We estimate the dynamic critical exponent of the simple cubic lattice Ising model to be $z \approx 0.27$ in the worm update. The worm and the Wolff algorithms produce different exponents of the integrated autocorrelation time of the magnetic susceptibility estimator but the same exponent of the asymptotic variance. We also discuss how to quantify the computational efficiency of the Markov chain Monte Carlo method. Our approach can be applied to a wide range of physical systems, such as the $| ϕ|^4$ model, the Potts model, the O($n$) loop model, and lattice QCD.

cond-mat.stat-mech↗

arXiv2019

Machine learning for molecular dynamics with strongly correlated electrons

We use machine learning to enable large-scale molecular dynamics (MD) of a correlated electron model under the Gutzwiller approximation scheme. This model exhibits a Mott transition as a function of on-site Coulomb repulsion $U$. The repeated solution of the Gutzwiller self-consistency equations would be prohibitively expensive for large-scale MD simulations. We show that machine learning models of the Gutzwiller potential energy can be remarkably accurate. The models, which are trained with $N=33$ atoms, enable highly accurate MD simulations at much larger scales ($N\gtrsim10^{3}$). We investigate the physics of the smooth Mott crossover in the fluid phase.

cond-mat.str-el↗

arXiv2018

Giant magnetic response of a two-dimensional antiferromagnet

A fundamental difference between antiferromagnets and ferromagnets is the lack of linear coupling to a uniform magnetic field due to the staggered order parameter. Such coupling is possible via the Dzyaloshinskii-Moriya (DM) interaction but at the expense of reduced antiferromagnetic (AFM) susceptibility due to the canting-induced spin anisotropy. We solve this long-standing problem with a top-down approach that utilizes spin-orbit coupling in the presence of a hidden SU(2) symmetry. We demonstrate giant AFM responses to sub-Tesla external fields by exploiting the extremely strong two-dimensional critical fluctuations preserved under a symmetry-invariant exchange anisotropy, which is built into a square-lattice artificially synthesized as a superlattice of SrIrO3 and SrTiO3. The observed field-induced logarithmic increase of the ordering temperature enables highly efficient control of the AFM order. As antiferromagnets promise to afford switching speed and storage security far beyond ferromagnets, our symmetry-invariant approach unleashes the great potential of functional antiferromagnets.

cond-mat.str-el↗