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Jiangzhi Chen

Publications and source records attributed to Jiangzhi Chen.

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Complexity Powered Machine Intelligent Classification of Quantum Many-Body Dynamics

Identifying and classifying quantum phases from measurable time series in many-body dynamics have significant values, yet face formidable challenges, requiring profound knowledge of physicists. Here, to achieve a pure data-driven machine intelligent classification, we introduce a complexity boosted distance measure that captures the inherent complexity of dynamic evolution series in different quantum many-body phases. Significantly, the introduction of complexity-boosted distance leads to remarkable improvements of unsupervised manifold learning of quantum many-body dynamics, which are exemplified in discrete time crystal model, Aubry-André model, and quantum east model. Our method does not require any prior knowledge and exhibits effectiveness even in imperfect, disordered, and noisy situations that are challenging for human scientists. Successful classification of dynamic phases in many-body systems holds the potential to enable crucial applications, including identification of tsunamis, earthquakes, catastrophes and future trends in finance.

cond-mat.mes-hall

Machine Learning of Knot Topology in Non-Hermitian Band Braids

The deep connection among braids, knots and topological physics has provided valuable insights into studying topological states in various physical systems. However, identifying distinct braid groups and knot topology embedded in non-Hermitian systems is challenging and requires significant efforts. Here, we demonstrate that an unsupervised learning with the representation basis of $su(n)$ Lie algebra on $n$-fold extended non-Hermitian bands can fully classify braid group and knot topology therein, without requiring any prior mathematical knowledge or any pre-defined topological invariants. We demonstrate that the approach successfully identifies different topological elements, such as unlink, unknot, Hopf link, Solomon ring, trefoil, and so on, by employing generalized Gell-Mann matrices in non-Hermitian models with $n$=2 and $n$=3 energy bands. Moreover, since eigenstate information of non-Hermitian bands is incorporated in addition to eigenvalues, the approach distinguishes the different parity-time symmetry and breaking phases, recognizes the opposite chirality of braids and knots, and identifies out distinct topological phases that were overlooked before. Our study shows significant potential of machine learning in classification of knots, braid groups, and non-Hermitian topological phases.

cond-mat.mes-hall

Observation of Geometric Heat Pump Effect in Periodic Driven Thermal Diffusion

The concept of geometry works as an overarching framework underlying a wide range of transport phenomena. Particularly, the geometric phase effect in classical and quantum heat pump has been attracting much attention in microscopic systems. Here, we formulate theoretically the geometric heat pump effect in macroscopic driven diffusive systems. Upon modulation protocols, the nontrivial geometric curvature in the parameter space universally induces an additional pumped heat, beyond the constraint of hot-to-cold flowing. Furthermore, we set up a minimum experiment and indeed observe a non-vanishing directional heat flow across the driven system, despite keeping zero thermal bias between two time-dependent thermal reservoirs at every instant. We verify that in analogy to the geometric phase effect, the geometric pumped heat during each driving cycle is independent of driving periods in the adiabatic limit and coincides with theoretical predictions, thus validating its geometric origin. These results about geometric heat pump effect could have potential implications for designing and implementing nonreciprocal and topological thermal meta-devices under spatiotemporal modulations.

cond-mat.stat-mech

Geometric Heat Pump: Controlling Thermal Transport with Time-dependent Modulations

The second law of thermodynamics dictates that heat simultaneously flows from the hot to cold bath on average. To go beyond this picture, a range of works in the past decade show that, other than the average dynamical heat flux determined by instantaneous thermal bias, a non-trivial flux contribution of intrinsic geometric origin is generally present in temporally driven systems. This additional heat flux provides a free lunch for the pumped heat and could even drive heat against the bias. We review here the emergence and development of this so called ``geometric heat pump'', originating from the topological geometric phase effect, and cover various quantum and classical transport systems with different internal dynamics. The generalization from the adiabatic to the non-adiabatic regime and the application of control theory are also discussed. Then, we briefly discuss the symmetry restriction on the heat pump effect, such as duality, supersymmetry and time-reversal symmetry. Finally, we examine open problems concerning the geometric heat pump process and elucidate their prospective significance in devising thermal machines with high performance.

cond-mat.stat-mech

From the seep to the surface: the ascent and dissolution of methane bubbles in the ocean

Methane, as a strong greenhouse gas, has 21-25 times the warming potential per unit mass than carbon dioxide, and the methane from the oceans can contribute to ~4% of the annual atmosphere methane budget. Large methane bubble plumes have been observed in seep sites globally on shallow continental shelves, and emerging industry of methane hydrates mining causes growing environmental concern on possible disastrous blowout which destabilizes the methane hydrate and releases huge amount of methane gas. To better estimate how much methane in gaseous phase leaked from the seeps can reach the atmosphere, a simplified model is developed to simulate the ascent of a methane bubble from a shallow ocean methane seep, and the methane transfer with the surrounding water. The breakup and coalescence of bubbles are neglected, and the bubble is assumed to remain spherical following a vertical path during the whole rising process. We calculated the survival distance of bubbles with varying initial sizes and depths and the remaining percentage of methane reaching the sea surface, and applied the results to the seep sites in the Shenhu area in the South China Sea. The study can provide insight into the relative significance of different water bodies in contributing to the atmosphere greenhouse gas.

physics.geo-ph