arXiv subjects

P. -Y. Chen

Publications and source records attributed to P. -Y. Chen.

5 recordsLinked to original sources

arXiv2025

Complex magnetic phases and thermodynamics of CuB_2O_4

The copper metaborate CuB_2O_4(CBO) has been studied within the parametric space of magnetic field (B) and temperature (T), showing a series of distinct phases, including commensurate and incommensurate magnetic orders, as well as magnetic soliton phases. However, no single study has simultaneously demonstrated all these phases. moreover, the existence of additional phases below 2 K or above 2 T for B perpenducular to c has been scarcely explored. This work presents the first comprehensive construction of the complex B-T phase diagram for T = 0.1 to 25 K and B = 0 to 9 T (B perpenducular to c), utilizing thermodynamic probes, magnetic measurements, and neutron scattering on a single batch of CBO crystals. Our findings elucidate new magnetic phases and regimes. First-principles calculations help to gain a deeper understanding of this complex phase diagram. The emergence of various phases within such a narrow B and T regime is attributed to two primary mechanisms: the delicate competition between ferromagnetic and antiferromagnetic interactions, and the weak exchange and superexchange interactions within and between the Cu(A) and Cu(B) sublattices. This competition also leads to a magnetically frustrated ground state at absolute zero where the total magnetic entropy release from high to low temperatures is only 0.76 Rln2, lower than Rln2 expected for copper spin 1/2. Using CBO as a model system, the present work elucidates the intricate mechanisms underlying the formation of complex magnetic phases.

cond-mat.str-el↗

arXiv2025

Accurate prediction of macroscopic transport from microscopic imaging via critical fractals at the Mott transition

Vanadium dioxide (VO$_2$) exhibits hysteresis in resistance while undergoing a thermally driven insulator-metal transition (IMT). Understanding the nonequilibrium effects in resistance is of great interest, as VO$_2$ is a strong candidate for brain-inspired computing, which is more energy efficient for AI tasks compared to traditional computing. Accurate models of the connection between microscopic and macroscopic transport properties and microscopic imaging of VO$_2$ will allow us to better utilize VO$_2$ in future applications. However, predictions of macroscopic resistance of VO$_2$ that quantitatively match observations using spatially resolved data have not yet been achieved. Here, we demonstrate an accurate prediction of the macroscopic resistance of VO$_2$ throughout the entire temperature range of interest, by developing a multiscale resistor network model incorporating the assumption of fractal sub-pixel structure of the optical data, where the configuration of insulating and metallic domains within each pixel are drawn from the random field Ising model near criticality. This strongly indicates that the observed fractal, power law structure of metallic and insulating domains extends down to much smaller length scales than the current record for experimental resolution of this system, and that the two-dimensional random field Ising model near criticality is a suitable model for describing the metal and insulator patches of VO$_2$ down to scales that approach the unit cell.

cond-mat.str-el↗

arXiv2022

A Generative deep learning approach for shape recognition of arbitrary objects from phaseless acoustic scattering data

We propose and demonstrate a generative deep learning approach for the shape recognition of an arbitrary object from its acoustic scattering properties. The strategy exploits deep neural networks to learn the mapping between the latent space of a two-dimensional acoustic object and the far-field scattering amplitudes. A neural network is designed as an Adversarial autoencoder and trained via unsupervised learning to determine the latent space of the acoustic object. Important structural features of the object are embedded in lower-dimensional latent space which supports the modeling of a shape generator and accelerates the learning in the inverse design process.The proposed inverse design uses the variational inference approach with encoder and decoder-like architecture where the decoder is composed of two pretrained neural networks, the generator and the forward model. The data-driven framework finds an accurate solution to the ill-posed inverse scattering problem, where non-unique solution space is overcome by the multifrequency phaseless far-field patterns. This inverse method is a powerful design tool that does not require complex analytical calculation and opens up new avenues for practical realization, automatic recognition of arbitrary shaped submarines or large fish, and other underwater applications.

cs.SD↗

arXiv2021

Experimental observation of PT symmetry breaking near divergent exceptional points

Standard exceptional points (EPs) are non-Hermitian degeneracies that occur in open systems. At an EP, the Taylor series expansion becomes singular and fails to converge -- a feature that was exploited for several applications. Here, we theoretically introduce and experimentally demonstrate a new class of parity-time symmetric systems [implemented using radio frequency (rf) circuits] that combine EPs with another type of mathematical singularity associated with the poles of complex functions. These nearly divergent exceptional points can exhibit an unprecedentedly large eigenvalue bifurcation beyond those obtained by standard EPs. Our results pave the way for building a new generation of telemetering and sensing devices with superior performance.

physics.app-ph↗

arXiv2018

Scattering Cancellation based Cloaking for the Maxwell-Cattaneo Heat Waves

In this work we theoretically propose scattering cancellation-based cloaks for heat waves that obey the Maxwell-Cattaneo equation. The proposed cloaks possess carefully tailored diffusivity to cancel the dipole scattering from the object that they surround, and thus can render a small object invisible in the near and far fields, as demonstrated by full-wave finite-element simulations. Mantle heat cloaking is further analyzed and proposed to simplify the design and bring this cloaking technology one step closer to its practical implementation, with promising applications in nanoelectronics and defense related applications.

physics.optics↗