arXiv subjects

Xiangying Shen

Publications and source records attributed to Xiangying Shen.

6 recordsLinked to original sources

arXiv2026

Topological Lithography via External Field: Creating Topological States Anywhere Beyond the Edge

Topological insulators (TIs), recognized for their robust boundary states and unconventional phase transitions, have emerged as one of the most impactful discoveries in recent decades, attracting considerable interest across diverse fields. However, conventional TIs require topological contrasts between adjacent bulk regions, typically achieved by distinct symmetries, which limits their flexibility and broader applicability. In this work, we introduce a "lithography" approach to inducing topological states by applying external fields in time-reversal-symmetric systems. These states transcend the conventional bulk topology design paradigm and offer exceptional tunability: they can exist at geometric edges, within the bulk, or even be induced remotely. Because the external field is highly controllable, the induced states are programmable, reconfigurable, and can be easily tailored into desirable patterns. Theoretically, we demonstrate that the external field modifies the Jackiw-Rebbi mechanism, inducing a real-space topological transition characterized by a local topological marker (LTM). We further establish an extended valley bulk-edge correspondence, which explains both the conventional scenario and our findings. Our results, validated across mechanical, electronic, and acoustic platforms, highlight the broad applicability of this approach to various systems. This work not only advances the theory of topology but also enhances the diversity, tunability, and practical implementation of topological states and materials.

cond-mat.other↗

arXiv2026

Imaginary Gauge Field and Non-Hermitian Topological Transition Emerging Through Attenuation-Gauge Duality in Conservative Systems

Non-Hermitian physics traditionally relies on active gain--loss modulation or non-reciprocal couplings, which often introduce significant complexity, compromise stability, and offer very limited scalability in conservative systems. Here we propose an attenuation-gauge duality paradigm in which non-Hermitian topology emerges within fully passive, conservative systems through coupling to a structured reservoir. We derive that a spatially varying reservoir can establish an attenuation-gauge duality, where the spatial variation manifests as an emergent imaginary gauge field in the effective dynamics. It drives the boundary accumulation of skin modes while preserving energy conservation, analogous to Feshbach projection in quantum open systems. We validate this universal wave paradigm via macroscopic mechanical metamaterials, demonstrating that the direction of the skin effect can be reversed by tuning a single passive coupling parameter$t_\perp$, driven by a topological phase transition characterized by the spectral winding number. This framework also allows for a nonlinear extension, where amplitude-dependent coupling can induce intrinsic topological transitions.

cond-mat.other↗

arXiv2024

A cyclical route linking fundamental mechanism and AI algorithm: An example from tuning Poisson's ratio in amorphous networks

"AI for science" is widely recognized as a future trend in the development of scientific research. Currently, although machine learning algorithms have played a crucial role in scientific research with numerous successful cases, relatively few instances exist where AI assists researchers in uncovering the underlying physical mechanisms behind a certain phenomenon and subsequently using that mechanism to improve machine learning algorithms' efficiency. This article uses the investigation into the relationship between extreme Poisson's ratio values and the structure of amorphous networks as a case study to illustrate how machine learning methods can assist in revealing underlying physical mechanisms. Upon recognizing that the Poisson's ratio relies on the low-frequency vibrational modes of dynamical matrix, we can then employ a convolutional neural network, trained on the dynamical matrix instead of traditional image recognition, to predict the Poisson's ratio of amorphous networks with a much higher efficiency. Through this example, we aim to showcase the role that artificial intelligence can play in revealing fundamental physical mechanisms, which subsequently improves the machine learning algorithms significantly.

cond-mat.soft↗

arXiv2021

Achieving adjustable elasticity with non-affine to affine transition

For various engineering and industrial applications it is desirable to realize mechanical systems with broadly adjustable elasticity to respond flexibly to the external environment. Here we discover a topology-correlated transition between affine and non-affine regimes in elasticity in both two- and three-dimensional packing-derived networks. Based on this transition, we numerically design and experimentally realize multifunctional systems with adjustable elasticity. Within one system, we achieve solid-like affine response, liquid-like non-affine response and a continuous tunability in between. Moreover, the system also exhibits a broadly tunable Poisson's ratio from positive to negative values, which is of practical interest for energy absorption and for fracture-resistant materials. Our study reveals a fundamental connection between elasticity and network topology, and demonstrates its practical potential for designing mechanical systems and metamaterials.

cond-mat.mtrl-sci↗

arXiv2015

Temperature-dependent transformation thermotics: From switchable thermal cloaks to macroscopic thermal diodes

The macroscopic control of ubiquitous heat flow remains poorly explored due to the lack of a fundamental theoretical method. Here, by establishing temperature-dependent transformation thermotics for treating materials whose conductivity depends on temperature, we show analytical and simulation evidence for switchable thermal cloaking and a macroscopic thermal diode based on the cloaking. The latter allows heat flow in one direction but prohibits the flow in the opposite direction, which is also confirmed by our experiments. Our results suggest that the temperature-dependent transformation thermotics could be a fundamental theoretical method for achieving macroscopic heat rectification, and provide guidance both for macroscopic control of heat flow and for the design of the counterparts of switchable thermal cloaks or macroscopic thermal diodes in other fields like seismology, acoustics, electromagnetics, or matter waves.

cond-mat.mtrl-sci↗

arXiv2015

Intelligent thermal cloak-concentrators

How to macroscopically control the flow of heat at will is up to now a challenge, which, however, is very important for human life since heat flow is a ubiquitous phenomenon in nature. Inspired by intelligent electronic components or intelligent materials, here we demonstrate, analytically and numerically, a unique class of intelligent bifunctional thermal metamaterials called thermal cloak-concentrators, which can automatically change from a cloak (concentrator) to a concentrator (cloak) when the applied temperature field decreases (increases). For future experimental realization, the behavior is also confirmed by assembling homogeneous isotropic materials according to the effective medium theory. The underlying mechanism originates from the effect of nonlinearity in thermal conduction. This work not only makes it possible to achieve a switchable Seebeck effect, but also offers guidance both for macroscopic manipulation of heat flow at will and for the design of similar intelligent multifunctional metamaterials in optics, electromagnetics, acoustics, or elastodynamics.

cond-mat.mtrl-sci↗