Reentrant behavior in the nearest-neighbor Ising antiferromagnet in a magnetic field

2004 ◽  
Vol 70 (22) ◽  
Author(s):  
Minos A. Neto ◽  
J. Ricardo de Sousa
Keyword(s):  
Magnetic Field ◽  
Nearest Neighbor ◽  
Ising Antiferromagnet

SIMULATION OF A MULTICRITICAL FCC ISING ANTIFERROMAGNET

1996 ◽  
Vol 07 (06) ◽  
pp. 857-861
Author(s):  
D. RENNÉ
Keyword(s):  
Magnetic Field ◽  
Monte Carlo ◽  
External Magnetic Field ◽  
Triple Point ◽  
Nearest Neighbor ◽  
Neighbor Interaction ◽  
Multicritical Point ◽  
Fcc Lattice ◽  
Ising Antiferromagnet ◽  
Open Question

Inspired by the work by Kämmerer, Dünweg, Binder, and d'Onorio de Meo we investigated the spin-[Formula: see text] Ising antiferromagnet on a fcc lattice in a homogeneous external magnetic field H with uniform nearest-neighbor interaction J by Monte Carlo simulations. In order to answer the open question whether this system exhibits a triple point or a multicritical point for positive H, we mainly studied lattices with 4 · 323 and 4 · 723 spins. We found a multicritical point at (Hc, kBTc) = (3.49 ± 0.02, 1.02 ± 0.01) J in the thermodynamic limit.

scholarly journals Effective Hamiltonian for a half-filled asymmetric ionic Hubbard chain with alternating on-site interaction

2016 ◽  
Vol 30 (03) ◽  
pp. 1550260 ◽  
Author(s):  
I. Grusha ◽  
M. Menteshashvili ◽  
G. I. Japaridze
Keyword(s):  
Magnetic Field ◽  
Nearest Neighbor ◽  
Effective Hamiltonian ◽  
Heisenberg Chain ◽  
Spin Hamiltonian ◽  
Effective Spin ◽  
One Dimensional ◽  
The One ◽  
Strong Repulsion ◽  
Ionic Hubbard Model

We derive an effective spin Hamiltonian for the one-dimensional half-filled asymmetric ionic Hubbard model (IHM) with alternating on-site interaction in the limit of strong repulsion. It is shown that the effective Hamiltonian is that of a spin S = 1/2 anisotropic XXZ Heisenberg chain with alternating next-nearest-neighbor (NNN) and three-spin couplings in the presence of a uniform and a staggered magnetic field.

scholarly journals Thermal Robustness of Entanglement in a Dissipative Two-Dimensional Spin System in an Inhomogeneous Magnetic Field

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1066
Author(s):  
Gehad Sadiek ◽  
Samaher Almalki
Keyword(s):  
Magnetic Field ◽  
Steady State ◽  
Nearest Neighbor ◽  
Quantum Phase Transitions ◽  
Inhomogeneous Magnetic Field ◽  
Steady States ◽  
Inhomogeneous Field ◽  
Spin States ◽  
Two Dimensional ◽  
Spin Lattice

Recently new novel magnetic phases were shown to exist in the asymptotic steady states of spin systems coupled to dissipative environments at zero temperature. Tuning the different system parameters led to quantum phase transitions among those states. We study, here, a finite two-dimensional Heisenberg triangular spin lattice coupled to a dissipative Markovian Lindblad environment at finite temperature. We show how applying an inhomogeneous magnetic field to the system at different degrees of anisotropy may significantly affect the spin states, and the entanglement properties and distribution among the spins in the asymptotic steady state of the system. In particular, applying an inhomogeneous field with an inward (growing) gradient toward the central spin is found to considerably enhance the nearest neighbor entanglement and its robustness against the thermal dissipative decay effect in the completely anisotropic (Ising) system, whereas the beyond nearest neighbor ones vanish entirely. The spins of the system in this case reach different steady states depending on their positions in the lattice. However, the inhomogeneity of the field shows no effect on the entanglement in the completely isotropic (XXX) system, which vanishes asymptotically under any system configuration and the spins relax to a separable (disentangled) steady state with all the spins reaching a common spin state. Interestingly, applying the same field to a partially anisotropic (XYZ) system does not just enhance the nearest neighbor entanglements and their thermal robustness but all the long-range ones as well, while the spins relax asymptotically to very distinguished spin states, which is a sign of a critical behavior taking place at this combination of system anisotropy and field inhomogeneity.

scholarly journals Application of Deep Convolutional Neural Networks and Smartphone Sensors for Indoor Localization

2019 ◽  
Vol 9 (11) ◽  
pp. 2337 ◽  
Author(s):  
Imran Ashraf ◽  
Soojung Hur ◽  
Yongwan Park
Keyword(s):  
Magnetic Field ◽  
Nearest Neighbor ◽  
Indoor Localization ◽  
Scene Recognition ◽  
Localization Error ◽  
K Nearest Neighbor ◽  
Current Location ◽  
Smartphone Sensors ◽  
The Impact ◽  
Localization Systems

Indoor localization systems are susceptible to higher errors and do not meet the current standards of indoor localization. Moreover, the performance of such approaches is limited by device dependence. The use of Wi-Fi makes the localization process vulnerable to dynamic factors and energy hungry. A multi-sensor fusion based indoor localization approach is proposed to overcome these issues. The proposed approach predicts pedestrians’ current location with smartphone sensors data alone. The proposed approach aims at mitigating the impact of device dependency on the localization accuracy and lowering the localization error in the magnetic field based localization systems. We trained a deep learning based convolutional neural network to recognize the indoor scene which helps to lower the localization error. The recognized scene is used to identify a specific floor and narrow the search space. The database built of magnetic field patterns helps to lower the device dependence. A modified K nearest neighbor (mKNN) is presented to calculate the pedestrian’s current location. The data from pedestrian dead reckoning further refines this location and an extended Kalman filter is implemented to this end. The performance of the proposed approach is tested with experiments on Galaxy S8 and LG G6 smartphones. The experimental results demonstrate that the proposed approach can achieve an accuracy of 1.04 m at 50 percent, regardless of the smartphone used for localization. The proposed mKNN outperforms K nearest neighbor approach, and mean, variance, and maximum errors are lower than those of KNN. Moreover, the proposed approach does not use Wi-Fi for localization and is more energy efficient than those of Wi-Fi based approaches. Experiments reveal that localization without scene recognition leads to higher errors.

Nearest-neighbor Ising antiferromagnet on the fcc lattice: Evidence for multicritical behavior

1996 ◽  
Vol 53 (5) ◽  
pp. 2345-2351 ◽  
Author(s):  
S. Kämmerer ◽  
B. Dünweg ◽  
K. Binder ◽  
M. d’Onorio de Meo
Keyword(s):  
Nearest Neighbor ◽  
Fcc Lattice ◽  
Ising Antiferromagnet

scholarly journals Frustrations and phase transitions in magnets of various dimensionality

2018 ◽  
Vol 185 ◽  
pp. 11002
Author(s):  
Felix Kassan-Ogly ◽  
Alexey Proshkin
Keyword(s):  
Magnetic Field ◽  
Phase Transitions ◽  
External Magnetic Field ◽  
Specific Heat ◽  
Nearest Neighbor ◽  
Linear Chain ◽  
Exchange Interactions ◽  
Specific Model ◽  
Main Challenge ◽  
Transition Points

We studied magnetic orderings, phase transitions, and frustrations in the Ising, 3-state Potts and standard 4-state Potts models on 1D, 2D, and 3D lattices: linear chain, square, triangular, kagome, honeycomb, and body-centered cubic. The main challenge was to find out the causes of frustrations phenomena and those features that distinguish frustrated system from not frustrated ones. The spins may interrelate with one another via the nearest-neighbor, the next-nearest-neighbor or higher-neighbor exchange interactions and via an external magnetic field that may be either competing or not. For problem solving we mainly calculated the entropy and specific heat using the rigorous analytical solutions for Kramers-Wannier transfer-matrix and exploiting computer simulation, par excellence, by Wang-Landau algorithm. Whether a system is ordered or frustrated is depend on the signs and values of exchange interactions. An external magnetic field may both favor the ordering of a system and create frustrations. With the help of calculations of the entropy, the specific heat and magnetic parameters, we obtained the points and ranges of frustrations, the frustration fields and the phase transition points. The results obtained also show that the same exchange interactions my either be competing or noncompeting which depends on the specific model and the lattice topology.

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