scholarly journals Processes of Creation and Propagation of Correlations in Large Quantum Particle System

Author(s):  
Viktor I. Gerasimenko
2004 ◽  
Vol 18 (04n05) ◽  
pp. 643-654 ◽  
Author(s):  
GIANFAUSTO DELL'ANTONIO

Consider a quantum particle of mass M in R3, described at time 0 by a wave function ϕ(x) with dispersion Δ, interacting independently with a collection of N particles of mass m. Using only Schroedinger's Quantum Mechanics we prove that when N becomes large and m/M becomes small, and if the information at time t>0 about the N particles of small mass in negleted, the system admits a "classical" description, i.e. a description in which the coherence of the wave function over distances of the order of mM-1N-1Δ have disappeared. We consider this a first step towards proving that most "sufficiently large" quantum systems interacting with an uncontrolled environment admit a classical description at least for position measurements.


Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1683
Author(s):  
Yuri Suhov ◽  
Mark Kelbert ◽  
Izabella Stuhl

This paper focuses on infinite-volume bosonic states for a quantum particle system (a quantum gas) in Rd. The kinetic energy part of the Hamiltonian is the standard Laplacian (with a boundary condition at the border of a ‘box’). The particles interact with each other through a two-body finite-range potential depending on the distance between them and featuring a hard core of diameter a>0. We introduce a class of so-called FK-DLR functionals containing all limiting Gibbs states of the system. As a justification of this concept, we prove that for d=2, any FK-DLR functional is shift-invariant, regardless of whether it is unique or not. This yields a quantum analog of results previously achieved by Richthammer.


2009 ◽  
Vol 28 (12) ◽  
pp. 3007-3009
Author(s):  
Wang-gen WAN ◽  
Ji-cheng LIN ◽  
Xiao-qing YU ◽  
Huan DING ◽  
Xiao-hui TAN

2004 ◽  
Vol 4 (5-6) ◽  
pp. 223-231
Author(s):  
H.-H. Yeh ◽  
W.-H. Wang

The utilization of membrane processes for drinking water treatment has become more popular. However, fouling by source water probably is the major factor prohibits its widespread application. In this research, the fouling phenomena of a microfiltration (MF) membrane were studied. The interactions among colloidal particles, calcium ion, and dissolved organics, such as salicylic acid, humic acid, and alginic acid, on MF fouling were focused. A lab-scale single hollow fiber MF membrane, made of polyvinylidenefluoride (PVDF), module was used. The results show that, for single organic compound, the extent of fouling caused by humic acid was higher that of alginic acid. For the latter, the permeate flux decrease at lower pH was more significant than those at higher pH. For low MW salicylic acid, both rejection and flux decrease were minor. It seems that solubility have strong correlation with fouling rate. The higher the solubility is, the lower the fouling rate. For sole colloidal particle system, latex beads with diameter close to the pore size of MF membrane showed severe fouling. Adding Ca can aggregate the latex beads, and alleviate fouling. However, calcium ion also found to increase fouling of alginic acid on membrane under neutral or alkali pH condition, probably via charge neutralization and/or bridging. In conclusion, MF fouling seems to be strongly related to the type of organics, size of colloidal particles, and the existence of divalent ions, in the feed water.


Author(s):  
Jiatang Cheng ◽  
Yan Xiong

Background: The effective diagnosis of wind turbine gearbox fault is an important means to ensure the normal and stable operation and avoid unexpected accidents. Methods: To accurately identify the fault modes of the wind turbine gearbox, an intelligent diagnosis technology based on BP neural network trained by the Improved Quantum Particle Swarm Optimization Algorithm (IQPSOBP) is proposed. In IQPSO approach, the random adjustment scheme of contractionexpansion coefficient and the restarting strategy are employed, and the performance evaluation is executed on a set of benchmark test functions. Subsequently, the fault diagnosis model of the wind turbine gearbox is built by using IQPSO algorithm and BP neural network. Results: According to the evaluation results, IQPSO is superior to PSO and QPSO algorithms. Also, compared with BP network, BP network trained by Particle Swarm Optimization (PSOBP) and BP network trained by Quantum Particle Swarm Optimization (QPSOBP), IQPSOBP has the highest diagnostic accuracy. Conclusion: The presented method provides a new reference for the fault diagnosis of wind turbine gearbox.


2017 ◽  
Vol 36 (6) ◽  
pp. 1-13 ◽  
Author(s):  
Tao Yang ◽  
Jian Chang ◽  
Ming C. Lin ◽  
Ralph R. Martin ◽  
Jian J. Zhang ◽  
...  

2021 ◽  
Vol 40 (4) ◽  
pp. 1-14
Author(s):  
Bo Ren ◽  
Ben Xu ◽  
Chenfeng Li

2019 ◽  
Vol 2019 (11) ◽  
Author(s):  
Olalla A. Castro-Alvaredo ◽  
Cecilia De Fazio ◽  
Benjamin Doyon ◽  
István M. Szécsényi

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