PARALLEL ADAPTIVE QUANTUM TRAJECTORY METHOD FOR WAVEPACKET SIMULATIONS

2005 ◽  
Vol 15 (04) ◽  
pp. 415-422 ◽  
Author(s):  
RICOLINDO L. CARIÑO ◽  
IOANA BANICESCU ◽  
RAVI K. VADAPALLI ◽  
CHARLES A. WEATHERFORD ◽  
JIANPING ZHU
Keyword(s):  
Weighted Least Squares ◽  
Free Particle ◽  
Computation Time ◽  
Quantum Trajectory ◽  
Loop Scheduling ◽  
Load Imbalance ◽  
Wavepacket Dynamics ◽  
Trajectory Method ◽  
Linux Cluster ◽  
Computationally Intensive

Time-dependent wavepackets are widely used to model various phenomena in physics. One approach in simulating the wavepacket dynamics is the quantum trajectory method (QTM). Based on the hydrodynamic formulation of quantum mechanics, the QTM represents the wavepacket by an unstructured set of pseudoparticles whose trajectories are coupled by the quantum potential. The governing equations for the pseudoparticle trajectories are solved using a computationally-intensive moving weighted least squares (MWLS) algorithm, and the trajectories can be computed in parallel. This paper contributes a strategy for improving the performance of wavepacket simulations using the QTM. Specifically, adaptivity is incorporated into the MWLS algorithm, and loop scheduling techniques are employed to dynamically load balance the parallel computation of the trajectories. The adaptive MWLS algorithm reduces the amount of computations without sacrificing accuracy, while adaptive loop scheduling addresses the load imbalance introduced by the algorithm and the runtime system. Results of experiments on a Linux cluster are presented to confirm that the adaptive MWLS reduces the trajectory computation time by up to 24%, and adaptive loop scheduling achieves parallel efficiencies of up to 85% when simulating a free particle.

QUANTUM TRAJECTORY CALCULATIONS FOR BIPOLAR WAVEPACKET DYNAMICS IN ONE DIMENSION: SYNTHETIC SINGLE-WAVEPACKET PROPAGATION

2010 ◽  
Vol 09 (04) ◽  
pp. 711-734 ◽  
Author(s):  
KISAM PARK ◽  
BILL POIRIER
Keyword(s):  
Initial Conditions ◽  
Technical Difficulty ◽  
One Dimension ◽  
Quantum Trajectory ◽  
One Dimensional ◽  
Trajectory Calculations ◽  
Wave Packet Dynamics ◽  
Wavepacket Dynamics ◽  
Trajectory Method ◽  
The Given

In a previous paper [Park K, Poirier B, Parlant G, J Chem Phys129:194112, 2008], a synthetic quantum trajectory method (QTM) was successfully implemented for wave-packet dynamics in a one-dimensional (1D) symmetric Eckart barrier system, utilizing a "double-wavepacket" version of the bipolar decomposition, ψ = ψ+ + ψ- = (ψ1+ + ψ2+) + (ψ1- + ψ2-), to avoid a technical difficulty involving negligible initial ψ- density. In this paper, we develop a new synthetic algorithm which overcomes this difficulty directly, utilizing the original "single-wavepacket" version of the bipolar decomposition, ψ =ψ+ + ψ-, and also show that the initial propagation of ψ- is mainly governed by probability transfer from ψ+, rather than by the given initial conditions for ψ-. The new algorithm makes it possible to apply the synthetic bipolar QTM to asymptotically asymmetric as well as symmetric potential systems. Successful application results for both symmetric and asymmetric Eckart barrier systems in 1D are presented.

2‐D wavepath migration

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1528-1537 ◽  
Author(s):  
H. Sun ◽  
G. T. Schuster
Keyword(s):  
Fresnel Zone ◽  
Complex Structure ◽  
Computation Time ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Kirchhoff Migration ◽  
Time Sample ◽  
Grid Points ◽  
Computationally Intensive ◽  
Single Trace

Prestack Kirchhoff migration (KM) is computationally intensive for iterative velocity analysis. This is partly because each time sample in a trace must be smeared along a quasi‐ellipsoid in the model. As a less costly alternative, we use the stationary phase approximation to the KM integral so that the time sample is smeared along a small Fresnel zone portion of the quasi‐ellipsoid. This is equivalent to smearing the time samples in a trace over a 1.5‐D fat ray (i.e., wavepath), so we call this “wavepath migration” (WM). This compares to standard KM, which smears the energy in a trace along a 3‐D volume of quasi‐concentric ellipsoids. In principle, single trace migration with WM has a computational count of [Formula: see text] compared to KM, which has a computational count of [Formula: see text], where N is the number of grid points along one side of a cubic velocity model. Our results with poststack data show that WM produces an image that in some places contains fewer migration artifacts and is about as well resolved as the KM image. For a 2‐D poststack migration example, the computation time of WM is less than one‐third that of KM. Our results with prestack data show that WM images contain fewer migration artifacts and can define the complex structure more accurately. It is also shown that WM can be significantly faster than KM if a slant stack technique is used in the migration. The drawback with WM is that it is sometimes less robust than KM because of its sensitivity to errors in estimating the incidence angles of the reflections.

Increasing Performance of the Quantum Trajectory Method by Grouping Trajectories

2017 ◽  
pp. 136-150
Author(s):  
Alexey Liniov ◽  
Valentin Volokitin ◽  
Iosif Meyerov ◽  
Mikhail Ivanchenko ◽  
Sergey Denisov
Keyword(s):  
Quantum Trajectory ◽  
Trajectory Method

Quantum trajectory calculations for bipolar wavepacket dynamics in one dimension

2008 ◽  
Vol 129 (19) ◽  
pp. 194112 ◽  
Author(s):  
Kisam Park ◽  
Bill Poirier ◽  
Gérard Parlant
Keyword(s):  
One Dimension ◽  
Quantum Trajectory ◽  
Trajectory Calculations ◽  
Wavepacket Dynamics

scholarly journals Parallel Implementation of Katsevich's FBP Algorithm

2006 ◽  
Vol 2006 ◽  
pp. 1-8 ◽  
Author(s):  
Jiansheng Yang ◽  
Xiaohu Guo ◽  
Qiang Kong ◽  
Tie Zhou ◽  
Ming Jiang
Keyword(s):  
Numerical Experiments ◽  
Parallel Implementation ◽  
Cone Beam Ct ◽  
Computation Time ◽  
Cone Beam ◽  
Filtered Backprojection ◽  
Typical Experiment ◽  
Linux Cluster ◽  
Parallel Reconstruction ◽  
Reconstruction Time

For spiral cone-beam CT, parallel computing is an effective approach to resolving the problem of heavy computation burden. It is well known that the major computation time is spent in the backprojection step for either filtered-backprojection (FBP) or backprojected-filtration (BPF) algorithms. By the cone-beam cover method [1], the backprojection procedure is driven by cone-beam projections, and every cone-beam projection can be backprojected independently. Basing on this fact, we develop a parallel implementation of Katsevich's FBP algorithm. We do all the numerical experiments on a Linux cluster. In one typical experiment, the sequential reconstruction time is 781.3 seconds, while the parallel reconstruction time is 25.7 seconds with 32 processors.

scholarly journals Optimum feedback strategy for access control mechanism modelled as stochastic differential equation in computer network

2004 ◽  
Vol 2004 (3) ◽  
pp. 263-276 ◽  
Author(s):  
N. U. Ahmed ◽  
Cheng Li
Keyword(s):  
Access Control ◽  
Network Performance ◽  
Control Mechanism ◽  
Computer Network ◽  
Random Search ◽  
Computation Time ◽  
Control Law ◽  
Access Control Mechanism ◽  
Computationally Intensive ◽  
Computer Communication Network

We consider optimum feedback control strategy for computer communication network, in particular, the access control mechanism. The dynamic model representing the source and the access control system is described by a system of stochastic differential equations developed in our previous works. Simulated annealing (SA) was used to optimize the parameters of the control law based on neural network. This technique was found to be computationally intensive. In this paper, we have proposed to use a more powerful algorithm known as recursive random search (RRS). By using this technique, we have been able to reduce the computation time by a factor of five without compromising the optimality. This is very important for optimization of high-dimensional systems serving a large number of aggregate users. The results show that the proposed control law can improve the network performance by improving throughput, reducing multiplexor and TB losses, and relaxing, not avoiding, congestion.

scholarly journals Full versus decoupled constant matrices to speed up power system state estimation

2020 ◽  
Vol 11 (3) ◽  
pp. 1287
Author(s):  
Meriem Majdoub ◽  
Bouchra Cheddadi ◽  
Omar Sabri ◽  
Abdelaziz Belfqih ◽  
Jamal Boukherouaa
Keyword(s):  
Power System ◽  
State Estimation ◽  
Distribution Systems ◽  
Weighted Least Squares ◽  
Computation Time ◽  
System State ◽  
Transmission Systems ◽  
Power System State Estimation ◽  
Slowing Down ◽  
Speed Up

This paper presents a performance evaluation of two solutions to reduce computational burden of the traditional Weighted Least Squares Algorithm for power system state estimation: Simplified methods SWLS1 / SWLS2 based on full constant matrices and Fast decoupled FDWLS based on decoupled constant matrices. First, the algorithms were tested on IEEE 14 and 118 bus transmission systems. Second, the solutions were tested on a rural distribution feeder to evaluate the response of the algorithms to high R/X ratio. Results show that for transmission systems, FDWLS is the fastest method but more sensitive to erroneous measurements. Simplifications considered in FDWLS, are not valid in distribution systems with high R/X ratio this results in slowing down the algorithm convergence speed considerably compared to SWLS2 which performs well. SWLS2 algorithm presents a promising solution to reduce computation time for application in future smart grid.

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