1,011 research outputs found
Free Energy Methods for Bayesian Inference: Efficient Exploration of Univariate Gaussian Mixture Posteriors
Because of their multimodality, mixture posterior distributions are difficult
to sample with standard Markov chain Monte Carlo (MCMC) methods. We propose a
strategy to enhance the sampling of MCMC in this context, using a biasing
procedure which originates from computational Statistical Physics. The
principle is first to choose a "reaction coordinate", that is, a "direction" in
which the target distribution is multimodal. In a second step, the marginal
log-density of the reaction coordinate with respect to the posterior
distribution is estimated; minus this quantity is called "free energy" in the
computational Statistical Physics literature. To this end, we use adaptive
biasing Markov chain algorithms which adapt their targeted invariant
distribution on the fly, in order to overcome sampling barriers along the
chosen reaction coordinate. Finally, we perform an importance sampling step in
order to remove the bias and recover the true posterior. The efficiency factor
of the importance sampling step can easily be estimated \emph{a priori} once
the bias is known, and appears to be rather large for the test cases we
considered. A crucial point is the choice of the reaction coordinate. One
standard choice (used for example in the classical Wang-Landau algorithm) is
minus the log-posterior density. We discuss other choices. We show in
particular that the hyper-parameter that determines the order of magnitude of
the variance of each component is both a convenient and an efficient reaction
coordinate. We also show how to adapt the method to compute the evidence
(marginal likelihood) of a mixture model. We illustrate our approach by
analyzing two real data sets
Long-time convergence of an Adaptive Biasing Force method
We propose a proof of convergence of an adaptive method used in molecular
dynamics to compute free energy profiles. Mathematically, it amounts to
studying the long-time behavior of a stochastic process which satisfies a
non-linear stochastic differential equation, where the drift depends on
conditional expectations of some functionals of the process. We use entropy
techniques to prove exponential convergence to the stationary state
Derivation of Langevin Dynamics in a Nonzero Background Flow Field
We propose a derivation of a nonequilibrium Langevin dynamics for a large
particle immersed in a background flow field. A single large particle is placed
in an ideal gas heat bath composed of point particles that are distributed
consistently with the background flow field and that interact with the large
particle through elastic collisions. In the limit of small bath atom mass, the
large particle dynamics converges in law to a stochastic dynamics. This
derivation follows the ideas of [D. D\"urr, S. Goldstein, and J. L. Lebowitz,
1981 and 1983; P. Calderoni, D. D\"urr, and S. Kusuoka, 1989] and provides
extensions to handle the nonzero background flow. The derived nonequilibrium
Langevin dynamics is similar to the dynamics in [M. McPhie, et al., 2001]. Some
numerical experiments illustrate the use of the obtained dynamic to simulate
homogeneous liquid materials under flow.Comment: Minor revisions, refined discussion of the laminar bath approach and
non-Hamiltonian dynamics approach in Section 2. 41 pages, 8 figure
Computation of free energy profiles with parallel adaptive dynamics
We propose a formulation of adaptive computation of free energy differences,
in the ABF or nonequilibrium metadynamics spirit, using conditional
distributions of samples of configurations which evolve in time. This allows to
present a truly unifying framework for these methods, and to prove convergence
results for certain classes of algorithms. From a numerical viewpoint, a
parallel implementation of these methods is very natural, the replicas
interacting through the reconstructed free energy. We show how to improve this
parallel implementation by resorting to some selection mechanism on the
replicas. This is illustrated by computations on a model system of
conformational changes.Comment: 4 pages, 1 Figur
An efficient sampling algorithm for Variational Monte Carlo
We propose a new algorithm for sampling the -body density in the Variational Monte Carlo (VMC)
framework. This algorithm is based upon a modified Ricci-Ciccotti
discretization of the Langevin dynamics in the phase space
improved by a Metropolis acceptation/rejection step. We show through some
representative numerical examples (Lithium, Fluorine and Copper atoms, and
phenol molecule), that this algorithm is superior to the standard sampling
algorithm based on the biased random walk (importance sampling).Comment: 23 page
Concurrent Geometric Multicasting
We present MCFR, a multicasting concurrent face routing algorithm that uses
geometric routing to deliver a message from source to multiple targets. We
describe the algorithm's operation, prove it correct, estimate its performance
bounds and evaluate its performance using simulation. Our estimate shows that
MCFR is the first geometric multicast routing algorithm whose message delivery
latency is independent of network size and only proportional to the distance
between the source and the targets. Our simulation indicates that MCFR has
significantly better reliability than existing algorithms
Immune Reactivity and Pseudoprogression or Tumor Flare in a Serially Biopsied Neuroendocrine Patient Treated with the Epigenetic Agent RRx-001.
Neuroendocrine tumors (NETs) are grouped together as a single class on the basis of histologic appearance, immunoreactivity for the neuroendocrine markers chromogranin A and synaptophysin, and potential secretion of hormones, neurotransmitters, neuromodulators and neuropeptides. Nevertheless, despite these common characteristics, NETs differ widely in terms of their natural histories: high-grade NETs are clinically aggressive and, like small cell lung cancer, which they most closely resemble, tend to respond to cisplatin and etoposide. In contrast, low-grade NETs, which as a rule progress and behave indolently, do not. In either case, the treatment strategy, apart from potentially curative surgical resection, is very poorly defined. This report describes the case of a 28-year-old white male with a diagnosis of high-grade NET of undetermined primary site metastatic to the lymph nodes, skin and paraspinal soft tissues, treated with the experimental anticancer agent RRx-001, in the context of a phase II clinical trial called TRIPLE THREAT (NCT02489903); serial sampling of tumor material through repeat biopsies demonstrated an intratumoral inflammatory response, including the amplification of infiltrating T cells, which correlated with clinical and symptomatic benefit. This case suggests that pseudoprogression or RRx-001-induced enlargement of tumor lesions, which has been previously described for several RRx-001-treated patients, is the result of tumoral lymphocyte infiltration
An objective frequency domain method for quantifying confined aquifer compressible storage using Earth and atmospheric tides
The groundwater hydraulic head response to the worldwide and ubiquitous atmospheric
tide at 2 cycles per day (cpd) is a direct function of confined aquifer compressible storage. The ratio of
the responses of hydraulic head to the atmospheric pressure change is a measure of aquifer barometric
efficiency, from which formation compressibility and aquifer specific storage can be determined in situ
rather than resorting to laboratory or aquifer pumping tests. The Earth tide also impacts the hydraulic head
response at the same frequency, and a method is developed here to quantify and remove this interference.
As a result, the barometric efficiency can be routinely calculated from 6-hourly hydraulic head, atmospheric
pressure, and modeled Earth tide records where available for a minimum of 15 days duration. This new
approach will be of critical importance in assessing worldwide problems of land subsidence or groundwater
resource evaluation that both occur due to groundwater abstractio
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