991 resultados para Sequential Monte Carlo
Resumo:
The solvent effects on the low-lying absorption spectrum and on the (15)N chemical shielding of pyrimidine in water are calculated using the combined and sequential Monte Carlo simulation and quantum mechanical calculations. Special attention is devoted to the solute polarization. This is included by an iterative procedure previously developed where the solute is electrostatically equilibrated with the solvent. In addition, we verify the simple yet unexplored alternative of combining the polarizable continuum model (PCM) and the hybrid QM/MM method. We use PCM to obtain the average solute polarization and include this in the MM part of the sequential QM/MM methodology, PCM-MM/QM. These procedures are compared and further used in the discrete and the explicit solvent models. The use of the PCM polarization implemented in the MM part seems to generate a very good description of the average solute polarization leading to very good results for the n-pi* excitation energy and the (15)N nuclear chemical shield of pyrimidine in aqueous environment. The best results obtained here using the solute pyrimidine surrounded by 28 explicit water molecules embedded in the electrostatic field of the remaining 472 molecules give the statistically converged values for the low lying n-pi* absorption transition in water of 36 900 +/- 100 (PCM polarization) and 36 950 +/- 100 cm(-1) (iterative polarization), in excellent agreement among one another and with the experimental value observed with a band maximum at 36 900 cm(-1). For the nuclear shielding (15)N the corresponding gas-water chemical shift obtained using the solute pyrimidine surrounded by 9 explicit water molecules embedded in the electrostatic field of the remaining 491 molecules give the statistically converged values of 24.4 +/- 0.8 and 28.5 +/- 0.8 ppm, compared with the inferred experimental value of 19 +/- 2 ppm. Considering the simplicity of the PCM over the iterative polarization this is an important aspect and the computational savings point to the possibility of dealing with larger solute molecules. This PCM-MM/QM approach reconciles the simplicity of the PCM model with the reliability of the combined QM/MM approaches.
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Hydrogen bond interactions between acetone and supercritical water are investigated using a combined and sequential Monte Carlo/quantum mechanics (S-MC/QM) approach. Simulation results show a dominant presence of con. gurations with one hydrogen bond for different supercritical states, indicating that this specific interaction plays an important role on the solvation properties of acetone in supercritical water. Using QM MP2/aug-cc-pVDZ the calculated average interaction energy reveals that the hydrogen-bonded acetone-water complex is energetically more stable under supercritical conditions than ambient conditions and its stability is little affected by variations of temperature and/or pressure. All average results reported here are statistically converged.
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The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.
Resumo:
Statistical methods of inference typically require the likelihood function to be computable in a reasonable amount of time. The class of “likelihood-free” methods termed Approximate Bayesian Computation (ABC) is able to eliminate this requirement, replacing the evaluation of the likelihood with simulation from it. Likelihood-free methods have gained in efficiency and popularity in the past few years, following their integration with Markov Chain Monte Carlo (MCMC) and Sequential Monte Carlo (SMC) in order to better explore the parameter space. They have been applied primarily to estimating the parameters of a given model, but can also be used to compare models. Here we present novel likelihood-free approaches to model comparison, based upon the independent estimation of the evidence of each model under study. Key advantages of these approaches over previous techniques are that they allow the exploitation of MCMC or SMC algorithms for exploring the parameter space, and that they do not require a sampler able to mix between models. We validate the proposed methods using a simple exponential family problem before providing a realistic problem from human population genetics: the comparison of different demographic models based upon genetic data from the Y chromosome.
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The nonlinearity of high-power amplifiers (HPAs) has a crucial effect on the performance of multiple-input-multiple-output (MIMO) systems. In this paper, we investigate the performance of MIMO orthogonal space-time block coding (OSTBC) systems in the presence of nonlinear HPAs. Specifically, we propose a constellation-based compensation method for HPA nonlinearity in the case with knowledge of the HPA parameters at the transmitter and receiver, where the constellation and decision regions of the distorted transmitted signal are derived in advance. Furthermore, in the scenario without knowledge of the HPA parameters, a sequential Monte Carlo (SMC)-based compensation method for the HPA nonlinearity is proposed, which first estimates the channel-gain matrix by means of the SMC method and then uses the SMC-based algorithm to detect the desired signal. The performance of the MIMO-OSTBC system under study is evaluated in terms of average symbol error probability (SEP), total degradation (TD) and system capacity, in uncorrelated Nakagami-m fading channels. Numerical and simulation results are provided and show the effects on performance of several system parameters, such as the parameters of the HPA model, output back-off (OBO) of nonlinear HPA, numbers of transmit and receive antennas, modulation order of quadrature amplitude modulation (QAM), and number of SMC samples. In particular, it is shown that the constellation-based compensation method can efficiently mitigate the effect of HPA nonlinearity with low complexity and that the SMC-based detection scheme is efficient to compensate for HPA nonlinearity in the case without knowledge of the HPA parameters.
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Many applications, such as intermittent data assimilation, lead to a recursive application of Bayesian inference within a Monte Carlo context. Popular data assimilation algorithms include sequential Monte Carlo methods and ensemble Kalman filters (EnKFs). These methods differ in the way Bayesian inference is implemented. Sequential Monte Carlo methods rely on importance sampling combined with a resampling step, while EnKFs utilize a linear transformation of Monte Carlo samples based on the classic Kalman filter. While EnKFs have proven to be quite robust even for small ensemble sizes, they are not consistent since their derivation relies on a linear regression ansatz. In this paper, we propose another transform method, which does not rely on any a priori assumptions on the underlying prior and posterior distributions. The new method is based on solving an optimal transportation problem for discrete random variables. © 2013, Society for Industrial and Applied Mathematics
Resumo:
Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood functions. Several methods that permit exact, or close to exact, simulation from the posterior distribution have recently been developed. However, estimating the evidence and Bayes’ factors for these models remains challenging in general. This paper describes new random weight importance sampling and sequential Monte Carlo methods for estimating BFs that use simulation to circumvent the evaluation of the intractable likelihood, and compares them to existing methods. In some cases we observe an advantage in the use of biased weight estimates. An initial investigation into the theoretical and empirical properties of this class of methods is presented. Some support for the use of biased estimates is presented, but we advocate caution in the use of such estimates.
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The absorption spectrum of the acid form of pterin in water was investigated theoretically. Different procedures using continuum, discrete, and explicit models were used to include the solvation effect on the absorption spectrum, characterized by two bands. The discrete and explicit models used Monte Carlo simulation to generate the liquid structure and time-dependent density functional theory (B3LYP/6-31G+(d)) to obtain the excitation energies. The discrete model failed to give the correct qualitative effect on the second absorption band. The continuum model, in turn, has given a correct qualitative picture and a semiquantitative description. The explicit use of 29 solvent molecules, forming a hydration shell of 6 angstrom, embedded in the electrostatic field of the remaining solvent molecules, gives absorption transitions at 3.67 and 4.59 eV in excellent agreement with the S(0)-S(1) and S(0)-S(2) absorption bands at of 3.66 and 4.59 eV, respectively, that characterize the experimental spectrum of pterin in water environment. (C) 2010 Wiley Periodicals, Inc. Int J Quantum Chem 110: 2371-2377, 2010
Resumo:
A combined and sequential Monte Carlo-quantum mechanics methodology is used to describe the electronic absorption spectrum of the fluorescein dianion in water. Different sets of 100 statistically relevant configurations composed of the solute and several solvent molecules are sampled from the Monte Carlo simulation for a posteriori quantum mechanical calculations of the spectra. In the largest case the configurations are composed of fluorescein and 90 explicit water molecules embedded in the electrostatic field of all remaining water molecules within a distance of 11.3 angstrom. These configurations include 305 atoms and 842 valence electrons, justifying the use of a semi-empirical approach. The electronic spectrum is then calculated using the INDO/CIS method. The solvatochromic shift of fluorescein in water, compared with in isolation, is calculated using the discrete and explicit solvent models. The use of electrostatically embedded explicit water molecules, in INDO/CIS calculations, gives a good description of the spectral shift of the fluorescein dianion in aqueous environment. The results are verified to converge both statistically and with respect to the number of explicit solvent molecules used.
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Monte Carlo simulation and quantum mechanics calculations based on the INDO/CIS and TD-DFT methods were utilized to study the solvatochromic shift of benzophenone when changing the environment from normal water to supercritical (P = 340.2 atm and T = 673 K) condition. Solute polarization increases the dipole moment of benzophenone, compared to gas phase, by 88 and 35% in normal and supercritical conditions, giving the in-solvent dipole value of 5.8 and 4.2 D, respectively. The average number of solute-solvent hydrogen bonds was analyzed, and a large decrease of 2.3 in normal water to only 0.8 in the supercritical environment was found. By using these polarized models of benzophenone in the two different conditions of water, we performed MC simulations to generate statistically uncorrelated configurations of the solute surrounded by the solvent molecules and subsequent quantum mechanics calculations on these configurations. When changing from normal to supercritical water environment, INDO/CIS calculations explicitly considering all valence electrons of the 235 solvent water molecules resulted in a solvatochromic shift of 1425 cm(-1) for the most intense transition of benzophenone, that is, slightly underestimated in comparison with the experimentally inferred result of 1700 cm(-1). TD-B3LYP/6-311+G(2d,p) calculations on the same configurations but with benzophenone electrostatically embedded in the 320 water molecules resulted in a solvatochromic shift of 1715 cm(-1) for this transition, in very good agreement with the experimental result. When using the unpolarized model of the benzophenone, this calculated solvatochromic shift was only 640 cm(-1). Additional calculations were also made by using BHandHLYP/6-311+G(2d,p) to analyze the effect of the asymptotic decay of the exchange functional. This study indicates that, contrary to the general expectation, there is a sizable solute polarization even in the low-density regime of supercritical condition and that the inclusion of this polarization is important for a reliable description of the spectral shifts considered here.
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Betaine dyes are known to show very large transition energy shifts in different solvents. The ortho-betaine molecule - a simple two-ring prototype of the E-T(30) Reichardt dye - has been investigated theoretically from a combined statistical and quantum mechanics approach. Using sequential Monte Carlo (MC) simulations and MP2/cc-pVDZ calculations the in-water dipole moment of ortho-betaine is obtained as 12.30 +/- 0.05 D. This result shows a considerable increase of 75% compared to the in-vacuum dipole moment. For comparison, the use of a polarizable continuum model using the same MP2/cc-pVDZ leads to an in-water dipole moment of 11.6 D, in good agreement. This large polarization is incorporated in the classical potential for another MC simulation to generate solute-solvent configurations and to obtain the contribution of the polarization effect in the solvatochromic shift. Using statistically uncorrelated configurations and supermolecular INDO/CIS calculations, including the solute and, explicitly, 230 solvent water molecules, the statistically converged calculated shift is obtained here as 6360 cm(-1), in good agreement with the experimental result of 7550 cm(-1). (c) 2007 Elsevier B.V. All rights reserved.
Resumo:
The solvatochromic shift of the lowest singlet it pi -> pi* electronic transition in the all-trans, cis-13, cis-11, cis-9, and cis-7 retinal isomers were computed under the influence of water, methanol, and benzene solvents. Excitation energies were calculated in gas phase and in solution. The calculations in solution were performed considering the sequential Monte Carlo (MC) /Quantum Mechanical approach. The MC simulations were performed considering the full retinal isomer molecules and 900 water molecules, 900 methanol, or 400 benzene ones. The OPLS/AA parametrization was chosen for retinal, methanol, and benzene molecules and the SPC model was used for water one. From the MC calculations 100 independent configurations were selected, with 100 solvent molecules in thermodynamical equilibrium at T = 298.15 K. Average point-charges were obtained from those independent configurations for water, methanol, and benzene solvent. TDDFT and CASSCF//CASPT2 methodologies were used to compute the vertical excitation energy of the retinal isomers in different environment. (C) 2010 Wiley Periodicals, Inc. Int J Quantum Chem 110: 2076-2087, 2010
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The sequential Monte Carlo/CASPT2 approach was employed to investigate deactivation and emission processes from the lowest-lying pi pi * and n pi * excited states of 9H-adenine in aqueous solution. It is found that conical intersections connecting the pi pi* and n pi* states with the ground state are also present in solution, whereas the barriers for the deactivation paths are significantly smaller on solvated conditions. The large destabilization of the n pi* state found in solution possibly prevents its involvement in the deactivation photophysics and explains the change from a bi- to a mono-exponential decay for the molecule in the gas phase and solution, respectively. (C) 2010 Elsevier B.V. All rights reserved.
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The minimum energy path along the lowest-lying pi pi* excited state of 2-aminopurine was calculated to elucidate the mechanisms of radiationless decay and emission in water. The sequential Monte Carlo quantum mechanics approach with a multiconfigurational and perturbative description of the wave function was employed to compute the minimum, transition state, and conical intersection. It was found that the barrier in the potential energy surface to access the conical intersection funnel increases in aqueous environment, making the system prone to enlarge the emission yield. These results rationalize the observed enhancement of emission in 2-aminopurine upon increasing of the solvent polarity. (c) 2008 Elsevier B.V. All rights reserved.
Resumo:
This thesis is composed of three articles with the subjects of macroeconomics and - nance. Each article corresponds to a chapter and is done in paper format. In the rst article, which was done with Axel Simonsen, we model and estimate a small open economy for the Canadian economy in a two country General Equilibrium (DSGE) framework. We show that it is important to account for the correlation between Domestic and Foreign shocks and for the Incomplete Pass-Through. In the second chapter-paper, which was done with Hedibert Freitas Lopes, we estimate a Regime-switching Macro-Finance model for the term-structure of interest rates to study the US post-World War II (WWII) joint behavior of macro-variables and the yield-curve. We show that our model tracks well the US NBER cycles, the addition of changes of regime are important to explain the Expectation Theory of the term structure, and macro-variables have increasing importance in recessions to explain the variability of the yield curve. We also present a novel sequential Monte-Carlo algorithm to learn about the parameters and the latent states of the Economy. In the third chapter, I present a Gaussian A ne Term Structure Model (ATSM) with latent jumps in order to address two questions: (1) what are the implications of incorporating jumps in an ATSM for Asian option pricing, in the particular case of the Brazilian DI Index (IDI) option, and (2) how jumps and options a ect the bond risk-premia dynamics. I show that jump risk-premia is negative in a scenario of decreasing interest rates (my sample period) and is important to explain the level of yields, and that gaussian models without jumps and with constant intensity jumps are good to price Asian options.