Parameter estimation from an Ornstein-Uhlenbeck process with measurement noise

This article aims to investigate the impact of noise on parameter fitting for an Ornstein-Uhlenbeck process, focusing on the effects of multiplicative and thermal noise on the accuracy of signal separation. To address these issues, we propose algorithms and methods that can effectively distinguish between thermal and multiplicative noise and improve the precision of parameter estimation for optimal data analysis. Specifically, we explore the impact of both multiplicative and thermal noise on the obfuscation of the actual signal and propose methods to resolve them. Firstly, we present an algorithm that can effectively separate thermal noise with comparable performance to Hamilton Monte Carlo (HMC) but with significantly improved speed. Subsequently, we analyze multiplicative noise and demonstrate that HMC is insufficient for isolating thermal and multiplicative noise. However, we show that, with additional knowledge of the ratio between thermal and multiplicative noise, we can accurately distinguish between the two types of noise when provided with a sufficiently large sampling rate or an amplitude of multiplicative noise smaller than thermal noise. This finding results in a situation that initially seems counterintuitive. When multiplicative noise dominates the noise spectrum, we can successfully estimate the parameters for such systems after adding additional white noise to shift the noise balance.Comment: 16 pages, 4 figure

Bond Orientational Order, Molecular Motion and Free Energy of High Density DNA Mesophases

By equilibrating condensed DNA arrays against reservoirs of known osmotic stress and examining them with several structural probes, it has been possible to achieve a detailed thermodynamic and structural characterization of the change between two distinct regions on the liquid crystalline phase digram: a higher-density hexagonally packed region with long-range bond orientational order in the plane perpendicular to the average molecular direction; and a lower-density cholesteric region with fluid-like positional order. X-rays scattering on highly ordered DNA arrays at high density and with the helical axis oriented parallel to the incoming beam showed a six-fold azimuthal modulation of the first order diffraction peak that reflects the macroscopic bond-orientational order. Transition to the less-dense cholesteric phase through osmotically controlled swelling shows the loss of this bond orientational order that had been expected from the change in optical birefringence patterns and that is consistent with a rapid onset of molecular positional disorder. This change in motion was previously inferred from intermolecular force measurements and is now confirmed by $\rm ^{31}P$ NMR. Controlled reversible swelling and compaction under osmotic stress, spanning a range of densities between $\sim 120$ mg/ml to $\sim 600$ mg/ml, allows measurement of the free energy changes throughout each phase and at the phase transition, essential information for theories of liquid-crystalline states.Comment: 14 pages, 3 figures in gif format available at http://abulafia.mgsl.dcrt.nih.gov/pics.html E-mail: [email protected]

Positional, Reorientational and Bond Orientational Order in DNA Mesophases

We investigate the orientational order of transverse polarization vectors of long, stiff polymer molecules and their coupling to bond orientational and positional order in high density mesophases. Homogeneous ordering of transverse polarization vector promotes distortions in the hexatic phase, whereas inhomogeneous ordering precipitates crystalization of the 2D sections with different orientations of the transverse polarization vector on each molecule in the unit cell. We propose possible scenarios for going from the hexatic phase, through the distorted hexatic phase to the crystalline phase with an orthorhombic unit cell observed experimentally for the case of DNA.Comment: 4 pages, 2 figure

Second-Hand Stress: Neurobiological Evidence for a Human Alarm Pheromone

Alarm pheromones are airborne chemical signals, released by an individual into the environment, which transmit warning of danger to conspecifics via olfaction. Using fMRI, we provide the first neurobiological evidence for a human alarm pheromone. Individuals showed activation of the amygdala in response to sweat produced by others during emotional stress, with exercise sweat as a control; behavioral data suggest facilitated evaluation of ambiguous threat

H2O–D2O Condensation in A Supersonic Nozzle

We examined the condensation of H2O, D2O, and four intermediate mixtures (20, 40, 60, and 80 mol % D2O) in a supersonic nozzle. Because the physical and chemical properties of protonated and deuterated water are so similar, this system is ideal for studying the change in condensation behavior as a function of condensible composition. In our experiments dilute mixtures of condensible vapor in N2 are expanded from three different stagnation temperatures resulting in a broad range of onset temperatures (190–238 K) and pressures (27–787 kPa). For a fixed stagnation temperature, the partial pressure required to maintain the onset of condensation at a given location or temperature in the nozzle is consistently higher for H2O than for D2O. In contrast, the supersaturation at fixed onset temperature is usually higher for D2O than for H2O and this difference increases toward lower temperature. The partial pressure at onset for the intermediate mixtures varied linearly between the values observed for the pure components in this ideal system

Small Angle Neutron Scattering from D2O–H2O Nanodroplets and Binary Nucleation Rates in A Supersonic Nozzle

Small angle neutron scattering (SANS) experiments were used to characterize binary nanodroplets composed of D2O and H2O. The droplets were formed by expanding dilute mixtures of condensible vapor in a N2 carrier gas through a supersonic nozzle, while maintaining the onset of condensation at a fixed position in the nozzle. It is remarkable, given the small coherent scattering length density of light water, that even the pure H2O aerosol gave a scattering signal above background. The scattering spectra were analyzed assuming a log-normal distribution of droplets. On average, the geometric radius of the nanodroplets rg was rg=13 (±1) nm, the polydispersity ln σr was ln σr=0.19 (±0.07), and the number density N was N=(2±0.2)⋅1011 cm−3. The aerosol volume fractions derived from the SANS measurements are consistent with those derived from the pressure trace experiments, suggesting that the composition of the droplets was close to that of the initial condensible mixture. A quantitative analysis of the scattering spectra as a function of the isotopic composition gave further evidence that the binary droplets exhibit ideal mixing behavior. Because both the stagnation temperature T0 and the location of onset were fixed, the temperature corresponding to the maximum nucleation rate was constant at TJ max=229 (±1) K. Thus, the experiments let us estimate the isothermal peak nucleation rates as a function of the isotopic composition. The nucleation rates were found to be essentially constant with Jmax equal to (3.6±0.5)⋅1016 cm−3 s−1 at a mean supersaturation of 44 (±3)

The air pressure effect on the homogeneous nucleation of carbon dioxide by molecular simulation

Vapour-liquid equilibria (VLE) and the influence of an inert carrier gas on homogeneous vapour to liquid nucleation are investigated by molecular simulation for quaternary mixtures of carbon dioxide, nitrogen, oxygen, and argon. Canonical ensemble molecular dynamics simulation using the Yasuoka-Matsumoto method is applied to nucleation in supersaturated vapours that contain more carbon dioxide than in the saturated state at the dew line. Established molecular models are employed that are known to accurately reproduce the VLE of the pure fluids as well as their binary and ternary mixtures. On the basis of these models, also the quaternary VLE properties of the bulk fluid are determined with the Grand Equilibrium method. Simulation results for the carrier gas influence on the nucleation rate are compared with the classical nucleation theory (CNT) considering the "pressure effect" [Phys. Rev. Lett. 101: 125703 (2008)]. It is found that the presence of air as a carrier gas decreases the nucleation rate only slightly and, in particular, to a significantly lower extent than predicted by CNT. The nucleation rate of carbon dioxide is generally underestimated by CNT, leading to a deviation between one and two orders of magnitude for pure carbon dioxide in the vicinity of the spinodal line and up to three orders of magnitude in presence of air as a carrier gas. Furthermore, CNT predicts a temperature dependence of the nucleation rate in the spinodal limit, which cannot be confirmed by molecular simulation

FixFit: using parameter-compression to solve the inverse problem in overdetermined models

All fields of science depend on mathematical models. One of the fundamental problems with using complex nonlinear models is that data-driven parameter estimation often fails because interactions between model parameters lead to multiple parameter sets fitting the data equally well. Here, we develop a new method to address this problem, FixFit, which compresses a given mathematical model's parameters into a latent representation unique to model outputs. We acquire this representation by training a neural network with a bottleneck layer on data pairs of model parameters and model outputs. The bottleneck layer nodes correspond to the unique latent parameters, and their dimensionality indicates the information content of the model. The trained neural network can be split at the bottleneck layer into an encoder to characterize the redundancies and a decoder to uniquely infer latent parameters from measurements. We demonstrate FixFit in two use cases drawn from classical physics and neuroscience

Coupling between Smectic and Twist Modes in Polymer Intercalated Smectics

We analyse the elastic energy of an intercalated smectic where orientationally ordered polymers with an average orientation varying from layer to layer are intercalated between smectic planes. The lowest order terms in the coupling between polymer director and smectic layer curvature are added to the smectic elastic energy. Integration over the smectic degrees of freedom leaves an effective polymer twist energy that has to be included into the total polymer elastic energy leading to a fluctuational renormalization of the intercalated polymer twist modulus. If the polymers are chiral this in its turn leads to a renormalization of the cholesteric pitch.Comment: 8 pages, 1 fig in ps available from [email protected] Replaced version also contains title and abstract in the main tex