Exclusion in junction geometries

Zhang, Keming; Krapivsky, P. L.; Redner, S.

doi:10.1103/physreve.99.052133

Cited by 8 publications

(10 citation statements)

References 48 publications

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“…(1) at ∆ = 0, where it reduces to the XY chain. The XY model is an archetypal model of quantum physics, encapsulating the physics underlying universal phenomena in equilibrium phase transition, much less looking for exotic phases through machine learning [49][50][51][52][53][54][55][56]. On one hand, the linear XY chain in the presence of transverse fields plays a central role in condensed matter theory [57,58] and is a good candidate for building blocks in quantum computers [59,60] and quantum information applications [61].…”

Section: The Information Measuresmentioning

confidence: 99%

Criticality and factorization in the Heisenberg chain with Dzyaloshinskii-Moriya interaction

You

et al. 2019

Phys. Rev. B

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In this work, we address the ground state properties of the anisotropic spin-1/2 Heisenberg XYZ chain under the interplay of magnetic fields and the Dzyaloshinskii-Moriya (DM) interaction which we interpret as an electric field. The identification of the regions of enhanced sensitivity determines criticality in this model. We calculate the Wigner-Yanase skew information (WYSI) as a coherence witness of an arbitrary two-qubit state under specific measurement bases. The WYSI is demonstrated to be a good indicator for detecting the quantum phase transitions. The finite-size scaling of coherence susceptibility is investigated. We find that the factorization line in the antiferromagnetic phase becomes the factorization volume in the gapless chiral phase induced by DM interactions, implied by the vanishing concurrence for a wide range of field. We also present the phase diagram of the model with three phases: antiferromagnetic, paramagnetic, and chiral, and point out a few common mistakes in deriving the correlation functions for the systems with broken reflection symmetry.

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Section: The Information Measuresmentioning

confidence: 99%

Criticality and factorization in the Heisenberg chain with Dzyaloshinskii-Moriya interaction

You

et al. 2019

Phys. Rev. B

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“…Thermal phase transitions of spin systems such as Ising and XY models as well as quantum phase transitions of frustrated spin systems have been detected successfully. 161,[169][170][171][172][173][174][175][176][177][178][179][180][181][182][183][184][185][186] Critical exponents of the Ising model 169,170,187,188) as well as the classical percolation transition 189,190) are also estimated by machine learning. Novel magnetic configurations such as the skyrmion are recognized using neural networks.…”

Section: Introductionmentioning

confidence: 99%

Drawing Phase Diagrams of Random Quantum Systems by Deep Learning the Wave Functions

Ohtsuki

Mano

2020

J. Phys. Soc. Jpn.

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Applications of neural networks to condensed matter physics are becoming popular and beginning to be well accepted. Obtaining and representing the ground and excited state wave functions are examples of such applications. Another application is analyzing the wave functions and determining their quantum phases. Here, we review the recent progress of using the multilayer convolutional neural network, so-called deep learning, to determine the quantum phases in random electron systems. After training the neural network by the supervised learning of wave functions in restricted parameter regions in known phases, the neural networks can determine the phases of the wave functions in wide parameter regions in unknown phases; hence, the phase diagrams are obtained. We demonstrate the validity and generality of this method by drawing the phase diagrams of two-and higher dimensional Anderson metal-insulator transitions and quantum percolations as well as disordered topological systems such as three-dimensional topological insulators and Weyl semimetals. Both real-space and Fourier space wave functions are analyzed. The advantages and disadvantages over conventional methods are discussed. * ohtsuki@sophia.ac.jp

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“…We now demonstrate numerically the theoretical critical radius of a drop on the solid surface with various contact angles varying from π/6 to π using the lattice Boltzmann method [20]. A uniform cartesian grid is used and all simulation parameters are expressed in lattice units.…”

mentioning

confidence: 99%

Spontaneous shrinkage of droplet on a wetting surface in the phase-field model

Zhang

Guo

2019

Phys. Rev. E

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Phase field theory is widely used to model multi-phase flows. A drop can shrink or grow spontaneously due to the redistribution of interface and bulk energies to minimize the system energy.In this paper, the spontaneous behaviour of a drop on a flat surface is investigated. It is found that there exists a critical radius dependent on the contact angle, the domain size and the interface width, below which the droplet will eventually disappear. In particular, the critical radius can be very large when the contact angle is hydrophilic. The theoretical prediction of the critical radius is verified numerically by simulating a drop on a surface with various contact angles, the domain sizes and the interface widths.

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Exclusion in junction geometries

Cited by 8 publications

References 48 publications

Criticality and factorization in the Heisenberg chain with Dzyaloshinskii-Moriya interaction

Criticality and factorization in the Heisenberg chain with Dzyaloshinskii-Moriya interaction

Drawing Phase Diagrams of Random Quantum Systems by Deep Learning the Wave Functions

Spontaneous shrinkage of droplet on a wetting surface in the phase-field model

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