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526
Simulating Normalized Constants: From Importance Sampling to Bridge Sampling to Path Sampling
, 1998
"... Computing (ratios of) normalizing constants of probability models is a fundamental computational problem for many statistical and scientific studies. Monte Carlo simulation is an effective technique, especially with complex and highdimensional models. This paper aims to bring to the attention of ..."
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Cited by 229 (5 self)
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Computing (ratios of) normalizing constants of probability models is a fundamental computational problem for many statistical and scientific studies. Monte Carlo simulation is an effective technique, especially with complex and highdimensional models. This paper aims to bring to the attention of general statistical audiences of some effective methods originating from theoretical physics and at the same time to explore these methods from a more statistical perspective, through establishing theoretical connections and illustrating their uses with statistical problems. We show that the acceptance ratio method and thermodynamic integration are natural generalizations of importance sampling, which is most familiar to statistical audiences. The former generalizes importance sampling through the use of a single “bridge ” density and is thus a case of bridge sampling in the sense of Meng and Wong. Thermodynamic integration, which is also known in the numerical analysis literature as Ogata’s method for highdimensional integration, corresponds to the use of infinitely many and continuously connected bridges (and thus a “path”). Our path sampling formulation offers more flexibility and thus potential efficiency to thermodynamic integration, and the search of optimal paths turns out to have close connections with the Jeffreys prior density and the Rao and Hellinger distances between two densities. We provide an informative theoretical example as well as two empirical examples (involving 17 to 70dimensional integrations) to illustrate the potential and implementation of path sampling. We also discuss some open problems.
The NoséPoincaré Method for Constant Temperature Molecular Dynamics
 J. Comput. Phys
, 1999
"... We present a new extended phase space method for constant temperature (canonical ensemble) molecular dynamics. Our starting point is the Hamiltonian introduced by Nose' to generate trajectories corresponding to configurations in the canonical ensemble. Using a Poincare' timetransformation ..."
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Cited by 46 (6 self)
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We present a new extended phase space method for constant temperature (canonical ensemble) molecular dynamics. Our starting point is the Hamiltonian introduced by Nose' to generate trajectories corresponding to configurations in the canonical ensemble. Using a Poincare' timetransformation, we construct a Hamiltonian system with the correct intrinsic timescale and show that it generates trajectories in the canonical ensemble. Our approach corrects a serious deficiency of the standard change of variables (Nose'Hoover dynamics), which yields a timereversible system but simultaneously destroys the Hamiltonian structure. A symplectic discretization method is presented for solving the Nose'Poincare' equations. The method is explicit and preserves the timereversal symmetry. In numerical experiments, it is shown that the new method exhibits enhanced stability when the temperature fluctuation is large. Extensions are presented for Nose' chains, holonomic constraints, and rigid bodies.
Firstprinciples simulation: ideas, illustrations and the CASTEP code
 J
, 2002
"... Firstprinciples simulation, meaning densityfunctional theory calculations with plane waves and pseudopotentials, has become a prized technique in condensedmatter theory. Here I look at the basics of the suject, give a brief review of the theory, examining the strengths and weaknesses of its imple ..."
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Cited by 35 (2 self)
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Firstprinciples simulation, meaning densityfunctional theory calculations with plane waves and pseudopotentials, has become a prized technique in condensedmatter theory. Here I look at the basics of the suject, give a brief review of the theory, examining the strengths and weaknesses of its implementation, and illustrating some of the ways simulators approach problems through a small case study. I also discuss why and how modern software design methods have been used in writing a completely new modular version of the CASTEP code. 1. Overview The simulator builds a model of a real system and explores its behaviour. The model is a mathematical one and the exploration is done on a computer, and in many ways simulation studies share the same mentality as experimental ones. However, in a simulation there is absolute control and access to detail, the ability to compute almost any observable, and given enough computer muscle, exact answers for the model. These strengths have been exploited for
Effective interactions in soft condensed matter physics
 Physics Reports
"... 2. Soft matter 272 2.1. What is soft matter 272 2.2. Stabilization of colloidal suspensions 276 ..."
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Cited by 28 (1 self)
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2. Soft matter 272 2.1. What is soft matter 272 2.2. Stabilization of colloidal suspensions 276
Diffusion in Zeolites
"... We review the basic ideas underlying diffusion in microporous solids, and explore recent efforts over the last two decades to measure and model the dynamics of molecules sorbed in zeolites. We outline the many important insights that have emerged regarding diffusion in zeolites, while also unders ..."
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Cited by 26 (4 self)
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We review the basic ideas underlying diffusion in microporous solids, and explore recent efforts over the last two decades to measure and model the dynamics of molecules sorbed in zeolites. We outline the many important insights that have emerged regarding diffusion in zeolites, while also underscoring the fact that much remains unknown. Particularly intriguing are the persistent discrepancies among different experimental probes of diffusion for certain zeoliteguest systems. Clarifying the origin of these discrepant diffusion measurements is undoubtedly one of the great challenges of future zeolite research. The eventual solution is intimately associated with progress in our understanding of real crystal structures and with our ability to synthesize sufficiently ideal zeolite crystallites.
Accelerating Molecular Dynamics Simulations With Configurable Circuits
 IEE Proc. on Computers and Digital Technology
, 2006
"... Molecular Dynamics (MD) is of central importance to computational chemistry. Here we show that MD can be implemented efficiently on a COTS FPGA board, and that speedups from to over a PC implementation can be obtained. Although the amount of speedup depends on the stability required, can ..."
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Cited by 25 (9 self)
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Molecular Dynamics (MD) is of central importance to computational chemistry. Here we show that MD can be implemented efficiently on a COTS FPGA board, and that speedups from to over a PC implementation can be obtained. Although the amount of speedup depends on the stability required, can be obtained with virtually no detriment, and the upper end of the range is apparently viable in many cases. We sketch our FPGA implementations and describe the effects of precision on the tradeoff between performance and quality of the MD simulation. 1.
Harvesting graphics power for MD simulations
 Molecular Simulation
"... We discuss an implementation of molecular dynamics (MD) simulations on a graphic processing unit (GPU) in the NVIDIA CUDA language. We tested our code on a modern GPU, the NVIDIA GeForce 8800 GTX. Results for two MD algorithms suitable for shortranged and longranged interactions, and a congruential ..."
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Cited by 20 (0 self)
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We discuss an implementation of molecular dynamics (MD) simulations on a graphic processing unit (GPU) in the NVIDIA CUDA language. We tested our code on a modern GPU, the NVIDIA GeForce 8800 GTX. Results for two MD algorithms suitable for shortranged and longranged interactions, and a congruential shift random number generator are presented. The performance of the GPU’s is compared to their main processor counterpart. We achieve speedups of up to 80, 40 and 150 fold, respectively. With newest generation of GPU’s one can run standard MD simulations at 10 7 flops/$. 1
Strict detailed balance is unnecessary in Monte Carlo simulations
 J. Chem Phys
, 1999
"... Detailed balance is an overly strict condition to ensure a valid Monte Carlo simulation. We show that, under fairly general assumptions, a Monte Carlo simulation need satisfy only the weaker balance condition. Not only does our proof show that sequential updating schemes are correct, but also it est ..."
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Cited by 19 (0 self)
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Detailed balance is an overly strict condition to ensure a valid Monte Carlo simulation. We show that, under fairly general assumptions, a Monte Carlo simulation need satisfy only the weaker balance condition. Not only does our proof show that sequential updating schemes are correct, but also it establishes the correctness of a whole class of new methods that simply leave the Boltzmann distribution invariant. 1 1
Blue Matter: Approaching the Limits of Concurrency for Classical Molecular Dynamics
 In SC ’06: Proceedings of the 2006 ACM/IEEE conference on Supercomputing
, 2006
"... been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be ..."
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Cited by 19 (0 self)
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been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). Copies may be requested from IBM T. J. Watson Research Center, P.
Mechanics and dynamics of actindriven thin membrane protrusions
 Biophysical Journal
, 2006
"... ABSTRACT Motile cells explore their surrounding milieu by extending thin dynamic protrusions, or filopodia. The growth of filopodia is driven by actin filament bundles that polymerize underneath the cell membrane. We compute the mechanical and dynamical features of the protrusion growth process by e ..."
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Cited by 15 (0 self)
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ABSTRACT Motile cells explore their surrounding milieu by extending thin dynamic protrusions, or filopodia. The growth of filopodia is driven by actin filament bundles that polymerize underneath the cell membrane. We compute the mechanical and dynamical features of the protrusion growth process by explicitly incorporating the flexible plasma membrane. We find that a critical number of filaments are needed to generate net filopodial growth. Without external influences, the filopodium can extend indefinitely up to the buckling length of the Factin bundle. Dynamical calculations show that the protrusion speed is enhanced by the thermal fluctuations of the membrane; a filament bundle encased in a flexible membrane grows much faster. The protrusion speed depends directly on the number and spatial arrangement of the filaments in the bundle and whether the filaments are tethered to the membrane. Filopodia also attract each other through distortions of the membrane. Spatially close filopodia will merge to form a larger one. Forcevelocity relationships mimicking micromanipulation experiments testing our predictions are computed.