Model of a microtoroidal magnetometer

We present a model of a cavity optomechanical magnetic field sensor based on a microtoroidal resonator. The magnetic field induced expansion of a magnetostrictive material is transduced onto the physical structure of a highly compliant optical microresonator. The resulting motion is read out optically with ultra-high sensitivity. According to our theoretical model sensitivities of up to 750 fT/√ Hz may be possible. The simultaneous presence of high-quality mechanical and optical resonances in microtoroids greatly enhances both the response to the magnetic field and the measurement sensitivity

Cavity Optomechanical Magnetometer

A cavity optomechanical magnetometer is demonstrated where the magnetic field induced expansion of a magnetostrictive material is transduced onto the physical structure of a highly compliant optical microresonator. The resulting motion is read out optically with ultra-high sensitivity. Detecting the magnetostrictive deformation of Terfenol-D with a toroidal whispering gallery mode (TWGM) resonator a peak sensitivity of 400 nT/Hz^.5 was achieved with theoretical modelling predicting that sensitivities of up to 500 fT/Hz^.5 may be possible. This chip-based magnetometer combines high-sensitivity and large dynamic range with small size and room temperature operation

Sensitivity of cavity optomechanical field sensors

This article presents a technique for modeling cavity optomechanical field sensors. A magnetic or electric field induces a spatially varying strain across the sensor. The effect of this strain is accounted for by separating the mechanical motion of the sensor into eigenmodes, each modeled by a simple harmonic oscillator. The force induced on each oscillator can then be determined from an overlap integral between strain and the corresponding eigenmode, with the optomechanical coupling strength determining the ultimate resolution with which this force can be detected

Curvature-coupling dependence of membrane protein diffusion coefficients

We consider the lateral diffusion of a protein interacting with the curvature of the membrane. The interaction energy is minimized if the particle is at a membrane position with a certain curvature that agrees with the spontaneous curvature of the particle. We employ stochastic simulations that take into account both the thermal fluctuations of the membrane and the diffusive behavior of the particle. In this study we neglect the influence of the particle on the membrane dynamics, thus the membrane dynamics agrees with that of a freely fluctuating membrane. Overall, we find that this curvature-coupling substantially enhances the diffusion coefficient. We compare the ratio of the projected or measured diffusion coefficient and the free intramembrane diffusion coefficient, which is a parameter of the simulations, with analytical results that rely on several approximations. We find that the simulations always lead to a somewhat smaller diffusion coefficient than our analytical approach. A detailed study of the correlations of the forces acting on the particle indicates that the diffusing inclusion tries to follow favorable positions on the membrane, such that forces along the trajectory are on average smaller than they would be for random particle positions.Comment: 16 pages, 8 figure

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Volumetric rheology of polymers

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