Página 1 dos resultados de 18 itens digitais encontrados em 0.020 segundos

## Statistical physics of equilibrium and nonequilibrium models : a computational approach

Gonçalves, Norberto Jorge Alves Parente
ENG
Relevância na Pesquisa
16.03%

## Illumination pattern optimization for fluorescence tomography: theory and simulation studies

Dutta, Joyita; Ahn, Sangtae; Joshi, Anand A; Leahy, Richard M
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
15.71%
Fluorescence molecular tomography is a powerful tool for 3D visualization of molecular targets and pathways in vivo in small animals. Owing to the high degrees of absorption and scattering of light through tissue, the fluorescence tomographic inverse problem is inherently ill-posed. In order to improve source localization and the conditioning of the light propagation model, multiple sets of data are acquired by illuminating the animal surface with different spatial patterns of near-infrared light. However, the choice of these patterns in most experimental setups is ad hoc and suboptimal. This paper presents a systematic approach for designing efficient illumination patterns for fluorescence tomography. Our objective here is to determine how to optimally illuminate the animal surface so as to maximize the information content in the acquired data. We achieve this by improving the conditioning of the Fisher information matrix. We parameterize the spatial illumination patterns and formulate our problem as a constrained optimization problem that, for a fixed number of illumination patterns, yields the optimal set of patterns. For geometric insight, we used our method to generate a set of three optimal patterns for an optically homogeneous...

## The Nearly Neutral and Selection Theories of Molecular Evolution Under the Fisher Geometrical Framework: Substitution Rate, Population Size, and Complexity

Razeto-Barry, Pablo; Díaz, Javier; Vásquez, Rodrigo A.
Fonte: Genetics Society of America Publicador: Genetics Society of America
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
56.02%
The general theories of molecular evolution depend on relatively arbitrary assumptions about the relative distribution and rate of advantageous, deleterious, neutral, and nearly neutral mutations. The Fisher geometrical model (FGM) has been used to make distributions of mutations biologically interpretable. We explored an FGM-based molecular model to represent molecular evolutionary processes typically studied by nearly neutral and selection models, but in which distributions and relative rates of mutations with different selection coefficients are a consequence of biologically interpretable parameters, such as the average size of the phenotypic effect of mutations and the number of traits (complexity) of organisms. A variant of the FGM-based model that we called the static regime (SR) represents evolution as a nearly neutral process in which substitution rates are determined by a dynamic substitution process in which the population’s phenotype remains around a suboptimum equilibrium fitness produced by a balance between slightly deleterious and slightly advantageous compensatory substitutions. As in previous nearly neutral models, the SR predicts a negative relationship between molecular evolutionary rate and population size; however...

## MR Measurement of Alloy Magnetic Susceptibility: Towards Developing Tissue-Susceptibility Matched Metals

Astary, Garrett W.; Peprah, Marcus K.; Fisher, Charles R.; Stewart, Rachel L.; Carney, Paul R.; Sarntinoranont, Malisa; Meisel, Mark W.; Manuel, Michele V.; Mareci, Thomas H.
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
25.71%
Magnetic resonance imaging (MRI) can be used to relate structure to function mapped with high-temporal resolution electrophysiological recordings using metal electrodes. Additionally, MRI may be used to guide the placement of electrodes or conductive cannula in the brain. However, the magnetic susceptibility mismatch between implanted metals and surrounding brain tissue can severely distort MR images and spectra, particularly in high magnetic fields. In this study, we present a modified MR method of characterizing the magnetic susceptibility of materials that can be used to develop biocompatible, metal alloys that match the susceptibility of host tissue in order to eliminate MR distortions proximal to the implant. This method was applied at 4.7 T and 11.1 T to measure the susceptibility of a model solid-solution alloy of Cu and Sn, which is inexpensive but not biocompatible. MR-derived relative susceptibility values of four different compositions of Cu-Sn alloy deviated by less than 3.1% from SQUID magnetometry absolute susceptibility measurements performed up to 7 T. These results demonstrate that the magnetic susceptibility varies linearly with atomic percentage in these solid-solution alloys, but are not simply the weighted average of Cu and Sn magnetic susceptibilities. Therefore susceptibility measurements are necessary when developing susceptibility-matched...

## Fisher’s Geometrical Model Emerges as a Property of Complex Integrated Phenotypic Networks

Martin, Guillaume
Fonte: Genetics Society of America Publicador: Genetics Society of America
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
46.04%
Models relating phenotype space to fitness (phenotype–fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher’s geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model “from first principles” is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher’s model’s assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts.

## Integration of enzyme immobilised single-walled carbon nanotube arrays into microchannels for glucose detection

Yu, J.; Matthews, S.; Yunus, K.; Shapter, J.; Fisher, A.
Fonte: Electrochemical Science Group Publicador: Electrochemical Science Group
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
25.82%
Microfluidic devices for glucose detection have been constructed and developed by integration of covalently immobilised single-walled carbon nanotube arrays functionalised with glucose oxidase into a poly (dimethylsiloxane)-based microfluidic channel. With biocompatible ferrocenecarboxylic acid as electron transfer mediator, these microfluidic devices were tested systematically for electrochemical glucose detection by changing some geometrical parameters such as the width of detecting electrode as well as electrode gap between the enzyme electrode and the detecting electrode. Numerical simulations were also carried out using a finite difference model and used to further understand the concentration profiles in michochannels. The experimental results showed that glucose can be detected with a linear response up to a concentration of 5 mmol L⁻¹. Compared to reported glucose detection techniques, our microfluidic devices have some advantages such as simple design, repeated use and low cost.; Jingxian Yu, Sinéad M Matthews, Kamran Yunus, Joseph G Shapter and Adrian C Fisher

## Fisher information under decoherence in Bloch representation

Zhong, Wei; Sun, Zhe; Ma, Jian; Wang, Xiaoguang; Nori, Franco
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
25.88%
The dynamics of two variants of quantum Fisher information under decoherence are investigated from a geometrical point of view. We first derive the explicit formulas of these two quantities for a single qubit in terms of the Bloch vector. Moreover, we obtain analytical results for them under three different decoherence channels, which are expressed as affine transformation matrices. Using the hierarchy equation method, we numerically study the dynamics of both the two information in a dissipative model and compare the numerical results with the analytical ones obtained by applying the rotating-wave approximation. We further express the two information quantities in terms of the Bloch vector for a qudit, by expanding the density matrix and Hermitian operators in a common set of generators of the Lie algebra $\mathfrak{su}(d)$. By calculating the dynamical quantum Fisher information, we find that the collisional dephasing significantly diminishes the precision of phase parameter with the Ramsey interferometry.; Comment: 16 pages, 4 figures

## Asymptotic Accuracy of Bayes Estimation for Latent Variables with Redundancy

Yamazaki, Keisuke
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
15.95%
Hierarchical parametric models consisting of observable and latent variables are widely used for unsupervised learning tasks. For example, a mixture model is a representative hierarchical model for clustering. From the statistical point of view, the models can be regular or singular due to the distribution of data. In the regular case, the models have the identifiability; there is one-to-one relation between a probability density function for the model expression and the parameter. The Fisher information matrix is positive definite, and the estimation accuracy of both observable and latent variables has been studied. In the singular case, on the other hand, the models are not identifiable and the Fisher matrix is not positive definite. Conventional statistical analysis based on the inverse Fisher matrix is not applicable. Recently, an algebraic geometrical analysis has been developed and is used to elucidate the Bayes estimation of observable variables. The present paper applies this analysis to latent-variable estimation and determines its theoretical performance. Our results clarify behavior of the convergence of the posterior distribution. It is found that the posterior of the observable-variable estimation can be different from the one in the latent-variable estimation. Because of the difference...

## Geometrical Aspects on Parameter estimation of stochastic gravitational wave background: beyond the Fisher analysis

Seto, Naoki; Kyutoku, Koutarou
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
25.71%
The maximum likelihood method is often used for parameter estimation in gravitational wave astronomy. Recently, an interesting approach was proposed by Vallisneri to evaluate the distributions of parameter estimation errors expected for the method. This approach is to statistically analyze the local peaks of the likelihood surface, and works efficiently even for signals with low signal-to-noise ratios. Focusing special attention to geometric structure of the likelihood surface, we follow the proposed approach and derive formulae for a simplified model of data analysis where the target signal has only one intrinsic parameter, along with its overall amplitude. Then we apply our formulae to correlation analysis of stochastic gravitational wave background with a power-law spectrum. We report qualitative trends of the formulae using numerical results specifically obtained for correlation analysis with two Advanced-LIGO detectors.; Comment: 23 pages, to be published in PRD

## An information criterion for model selection with missing data via complete-data divergence

Shimodaira, Hidetoshi; Maeda, Haruyoshi
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
25.78%
We derive an information criterion for selecting a parametric model of complete-data distribution when only incomplete or partially observed data is available. Compared with AIC, the new criterion has an additional penalty term for missing data expressed by the Fisher information matrices of complete data and incomplete data. We prove that the new criterion is an asymptotically unbiased estimator of the complete-data divergence, namely, the expected Kullback-Leibler divergence between the true distribution and the estimated distribution for complete data, whereas AIC is that for the incomplete data. Information criteria PDIO (Shimodaira 1994) and AICcd (Cavanaugh and Shumway 1998) have been previously proposed for estimating the complete-data divergence, and these two criteria have the same penalty term. The additional penalty term of the new criterion for missing data turns out to be only the half of what is claimed in PDIO and AICcd. We observe in a simulation study that the new criterion is unbiased while the other two criteria are biased. Before starting the argument of model selection, we review the geometrical view of alternating minimizations of the EM algorithm, which plays an important role for the derivation of the new criterion.

## Effects of cosmological model assumptions on galaxy redshift survey measurements

Samushia, Lado; Percival, Will J.; Guzzo, Luigi; Wang, Yun; Cimatti, Andrea; Baugh, Carlton; Geach, James E.; Lacey, Cedric; Majerotto, Elisabetta; Mukherjee, Pia; Orsi, Alvaro
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
25.91%
The clustering of galaxies observed in future redshift surveys will provide a wealth of cosmological information. Matching the signal at different redshifts constrains the dark energy driving the acceleration of the expansion of the Universe. In tandem with these geometrical constraints, redshift-space distortions (RSD) depend on the build up of large-scale structure. As pointed out by many authors measurements of these effects are intrinsically coupled. We investigate this link, and argue that it strongly depends on the cosmological assumptions adopted when analysing data. Using representative assumptions for the parameters of the Euclid survey in order to provide a baseline future experiment, we show how the derived constraints change due to different model assumptions. We argue that even the assumption of a Friedman-Robertson-Walker (FRW) space-time is sufficient to reduce the importance of the coupling to a significant degree. Taking this idea further, we consider how the data would actually be analysed and argue that we should not expect to be able to simultaneously constrain multiple deviations from the standard $\Lambda$CDM model. We therefore consider different possible ways in which the Universe could deviate from the $\Lambda$CDM model...

## Information Geometry, One, Two, Three (and Four)

Johnston, D. A.; Janke, W.; Kenna, R.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
15.8%
Although the notion of entropy lies at the core of statistical mechanics, it is not often used in statistical mechanical models to characterize phase transitions, a role more usually played by quantities such as various order parameters, specific heats or suscept ibilities. The relative entropy induces a metric, the so-called information or Fisher-Rao m etric, on the space of parameters and the geometrical invariants of this metric carry information about the phase structure of the model. In various models the scalar curvature, ${\cal R}$, of the information metric has been found to diverge at the phase transition point and a plausible scaling relation postulated. For spin models the necessity of calculating in non-zero field has limited analytic consideration to one-dimensional, mean-field and Bethe lattice Ising models. We report on previous papers in which we extended the list somewhat in the current note by considering the {\it one}-dime nsional Potts model, the {\it two}-dimensional Ising model coupled to two-dimensional quantum gravity and the {\it three}-dimensional spherical model. We note that similar ideas have been ap plied to elucidate possible critical behaviour in families of black hole solutions in {\it four} space-time dimensions.

## A Widely Applicable Bayesian Information Criterion

Watanabe, Sumio
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
15.8%
A statistical model or a learning machine is called regular if the map taking a parameter to a probability distribution is one-to-one and if its Fisher information matrix is always positive definite. If otherwise, it is called singular. In regular statistical models, the Bayes free energy, which is defined by the minus logarithm of Bayes marginal likelihood, can be asymptotically approximated by the Schwarz Bayes information criterion (BIC), whereas in singular models such approximation does not hold. Recently, it was proved that the Bayes free energy of a singular model is asymptotically given by a generalized formula using a birational invariant, the real log canonical threshold (RLCT), instead of half the number of parameters in BIC. Theoretical values of RLCTs in several statistical models are now being discovered based on algebraic geometrical methodology. However, it has been difficult to estimate the Bayes free energy using only training samples, because an RLCT depends on an unknown true distribution. In the present paper, we define a widely applicable Bayesian information criterion (WBIC) by the average log likelihood function over the posterior distribution with the inverse temperature $1/\log n$, where $n$ is the number of training samples. We mathematically prove that WBIC has the same asymptotic expansion as the Bayes free energy...

## Statistical Geometry in Quantum Mechanics

Brody, Dorje C.; Hughston, Lane P.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
15.76%
A statistical model M is a family of probability distributions, characterised by a set of continuous parameters known as the parameter space. This possesses natural geometrical properties induced by the embedding of the family of probability distributions into the Hilbert space H. By consideration of the square-root density function we can regard M as a submanifold of the unit sphere in H. Therefore, H embodies the `state space' of the probability distributions, and the geometry of M can be described in terms of the embedding of in H. The geometry in question is characterised by a natural Riemannian metric (the Fisher-Rao metric), thus allowing us to formulate the principles of classical statistical inference in a natural geometric setting. In particular, we focus attention on the variance lower bounds for statistical estimation, and establish generalisations of the classical Cramer-Rao and Bhattacharyya inequalities. The statistical model M is then specialised to the case of a submanifold of the state space of a quantum mechanical system. This is pursued by introducing a compatible complex structure on the underlying real Hilbert space, which allows the operations of ordinary quantum mechanics to be reinterpreted in the language of real Hilbert space geometry. The application of generalised variance bounds in the case of quantum statistical estimation leads to a set of higher order corrections to the Heisenberg uncertainty relations for canonically conjugate observables.; Comment: 32 pages...

## On the Enlargement by Pr\"ufer Objects of the Cluster Category of type $A_\infty$

Fisher, Thomas A.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
25.71%
In a paper by Holm and Jorgensen, the cluster category $\mathscr{D}$ of type $A_\infty$, with Auslander-Reiten quiver $\mathbb{Z} A_\infty$, is introduced. Slices in the Auslander-Reiten quiver of $\mathscr{D}$ give rise to direct systems; the homotopy colimit of such direct systems can be computed and these "Pr\"ufer objects" can be adjoined to form a larger category. It is this larger category, $\overline{\mathscr{D}},$ which is the main object of study in this paper. We show that $\overline{\mathscr{D}}$ inherits a nice geometrical structure from $\mathscr{D}$; "arcs" between non-neighbouring integers on the number line correspond to indecomposable objects, and in the case of $\overline{\mathscr{D}}$ we also have arcs to infinity which correspond to the Pr\"ufer objects. During the course of this paper, we show that $\overline{\mathscr{D}}$ is triangulated, compute homs, investigate the geometric model, and we conclude by computing the cluster tilting subcategories of $\overline{\mathscr{D}}$.; Comment: 36 pages

## Critical behavior of the geometrical spin clusters and interfaces in the two-dimensional thermalized bond Ising model

Davatolhagh, S.; Moshfeghian, M.; Saberi, A. A.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.06%
The fractal dimensions and the percolation exponents of the geometrical spin clusters of like sign at criticality, are obtained numerically for an Ising model with temperature-dependent annealed bond dilution, also known as the thermalized bond Ising model (TBIM), in two dimensions. For this purpose, a modified Wolff single-cluster Monte Carlo simulation is used to generate equilibrium spin configurations on square lattices in the critical region. A tie-breaking rule is employed to identify non-intersecting spin cluster boundaries along the edges of the dual lattice. The values obtained for the fractal dimensions of the spanning geometrical clusters $D_{c}$, and their interfaces $D_{I}$, are in perfect agreement with those reported for the standard two-dimensional ferromagnetic Ising model. Furthermore, the variance of the winding angles, results in a diffusivity $\kappa=3$ for the two-dimensional thermalized bond Ising model, thus placing it in the universality class of the regular Ising model. A finite-size scaling analysis of the largest geometrical clusters, results in a reliable estimation of the critical percolation exponents for the geometrical clusters in the limit of an infinite lattice size. The percolation exponents thus obtained...

## Reaction-subdiffusion front propagation in a comblike model of spiny dendrites

Iomin, A.; Méndez López, Vicenç
Tipo: Artigo de Revista Científica Formato: application/pdf