Super-resolution imaging of a low frequency levitated oscillator

We describe the measurement of the secular motion of a levitated nanoparticle in a Paul trap with a CMOS camera. This simple method enables us to reach signal-to-noise ratios as good as 10$^{6}$ with a displacement sensitivity better than 10$^{-16}\,m^{2}$/Hz. This method can be used to extract trap parameters as well as the properties of the levitated particles. We demonstrate continuous monitoring of the particle dynamics on timescales of the order of weeks. We show that by using the improvement given by super-resolution imaging, a significant reduction in the noise floor can be attained, with an increase in the bandwidth of the force sensitivity. This approach represents a competitive alternative to standard optical detection for a range of low frequency oscillators where low optical powers are require

Optomechanics with an electrodynamically levitated oscillator

In this work I report on a hybrid trap platform for sensitive optomechanics experiments with applications in quantum physics, thermodynamics and material science. We characterise a miniature linear Paul trap which can be used in combination with an optical cavity. The low-frequency harmonic motion of a nanoparticle levitated in a Paul trap can be detected with competitive sensitivities using a super-resolution imaging technique. This same method can be applied to characterise trap stability and nanosphere parameters such as mass with a 3% uncertainty. Using this same method at room temperature and at pressure of 3×10⁻⁷ mbar, we were able to measure an ultra-narrow mechanical linewidth of ∼80 µHz with a novel phase sensitive scheme which removes slow drifts in the mechanical frequency. We used this measurement to place new bounds on dissipative versions of wavefunction collapse models. Using two optical cavity modes with different frequencies interacting with a nanoparticle levitated within a Paul trap realises a versatile optomechanical system, which can be operated in regimes dominated by either linear or quadratic optomechanical coupling. We demonstrated cooling of the centre-of-mass motion of the nano-oscillator exclusively provided by the quadratic coupling. This nonlinear interaction gives rise to a highly non-thermal state of motion which matches well with theoretical predictions. In the linear regime, we report cooling down to Teff=21±4 mK limited by Paul trap noise, demonstrating stable trapping in the cavity standing-wave down to pressures ∼10⁻⁶ mbar. Using the same technique, we show that in theory, near ground state cooling could be achieved with better electronics used in conjunction with the filtering cavity developed as part of this work

An ultra-narrow line width levitated nano-oscillator for testing dissipative wavefunction collapse

Levitated nano-oscillators are seen as promising platforms for testing fundamental physics and testing quantum mechanics in a new high mass regime. Levitation allows extreme isolation from the environment, reducing the decoherence processes that are crucial for these sensitive experiments. A fundamental property of any oscillator is its line width and mechanical quality factor, Q. Narrow line widths in the microHertz regime and mechanical Q's as high as $10^{12}$ have been predicted for levitated systems, but to date, the poor stability of these oscillators over long periods have prevented direct measurement in high vacuum. Here we report on the measurement of an ultra-narrow line width levitated nano-oscillator, whose line width of $81\pm\,23\,\mu$Hz is only limited by residual gas pressure at high vacuum. This narrow line width allows us to put new experimental bounds on dissipative models of wavefunction collapse including continuous spontaneous localisation and Di\'{o}si-Penrose and illustrates its utility for future precision experiments that aim to test the macroscopic limits of quantum mechanics

Role of lateral and feedback connections in primary visual cortex in the processing of spatiotemporal regularity: a TMS study

Our human visual system exploits spatiotemporal regularity to interpret incoming visual signals. With a dynamic stimulus sequence of four collinear bars (predictors) appearing consecutively toward the fovea, followed by a target bar with varying contrasts, we have previously found that this predictable spatiotemporal stimulus structure enhances target detection performance and its underlying neural process starts in the primary visual cortex (area V1). However, the relative contribution of V1 lateral and feedback connections in the processing of spatiotemporal regularity remains unclear. In this study we measured human contrast detection of a briefly presented foveal target that was embedded in a dynamic collinear predictor-target sequence. Transcranial magnetic stimulation (TMS) was used to selectively disrupt V1 horizontal and feedback connections in the processing of predictors. The coil was positioned over a cortical location corresponding to the location of the last predictor prior to target onset. Single-pulse TMS at an intensity of 10% below phosphene threshold was delivered at 20 or 90ms after the predictor onset. Our analysis revealed that the delivery of TMS at both time windows equally reduced, but did not abolish, the facilitation effect of the predictors on target detection. Furthermore, if the predictors’ ordination was randomized to suppress V1 lateral connections, the TMS disruption was significantly more evident at 20ms than at 90ms time window. We suggest that both lateral and feedback connections contribute to the encoding of spatiotemporal regularity in V1. These findings develop understanding of how our visual system exploits spatiotemporal regularity to facilitate the efficiency of visual perception

Parametric study of EEG sensitivity to phase noise during face processing

<b>Background: </b> The present paper examines the visual processing speed of complex objects, here faces, by mapping the relationship between object physical properties and single-trial brain responses. Measuring visual processing speed is challenging because uncontrolled physical differences that co-vary with object categories might affect brain measurements, thus biasing our speed estimates. Recently, we demonstrated that early event-related potential (ERP) differences between faces and objects are preserved even when images differ only in phase information, and amplitude spectra are equated across image categories. Here, we use a parametric design to study how early ERP to faces are shaped by phase information. Subjects performed a two-alternative force choice discrimination between two faces (Experiment 1) or textures (two control experiments). All stimuli had the same amplitude spectrum and were presented at 11 phase noise levels, varying from 0% to 100% in 10% increments, using a linear phase interpolation technique. Single-trial ERP data from each subject were analysed using a multiple linear regression model. <b>Results: </b> Our results show that sensitivity to phase noise in faces emerges progressively in a short time window between the P1 and the N170 ERP visual components. The sensitivity to phase noise starts at about 120–130 ms after stimulus onset and continues for another 25–40 ms. This result was robust both within and across subjects. A control experiment using pink noise textures, which had the same second-order statistics as the faces used in Experiment 1, demonstrated that the sensitivity to phase noise observed for faces cannot be explained by the presence of global image structure alone. A second control experiment used wavelet textures that were matched to the face stimuli in terms of second- and higher-order image statistics. Results from this experiment suggest that higher-order statistics of faces are necessary but not sufficient to obtain the sensitivity to phase noise function observed in response to faces. <b>Conclusion: </b> Our results constitute the first quantitative assessment of the time course of phase information processing by the human visual brain. We interpret our results in a framework that focuses on image statistics and single-trial analyses

Age-related delay in information accrual for faces: Evidence from a parametric, single-trial EEG approach

Background: In this study, we quantified age-related changes in the time-course of face processing by means of an innovative single-trial ERP approach. Unlike analyses used in previous studies, our approach does not rely on peak measurements and can provide a more sensitive measure of processing delays. Young and old adults (mean ages 22 and 70 years) performed a non-speeded discrimination task between two faces. The phase spectrum of these faces was manipulated parametrically to create pictures that ranged between pure noise (0% phase information) and the undistorted signal (100% phase information), with five intermediate steps. Results: Behavioural 75% correct thresholds were on average lower, and maximum accuracy was higher, in younger than older observers. ERPs from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The earliest age-related ERP differences occurred in the time window of the N170. Older observers had a significantly stronger N170 in response to noise, but this age difference decreased with increasing phase information. Overall, manipulating image phase information had a greater effect on ERPs from younger observers, which was quantified using a hierarchical modelling approach. Importantly, visual activity was modulated by the same stimulus parameters in younger and older subjects. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed a significantly slower processing in older observers starting around 120 ms after stimulus onset. This age-related delay increased over time to reach a maximum around 190 ms, at which latency younger observers had around 50 ms time lead over older observers. Conclusion: Using a component-free ERP analysis that provides a precise timing of the visual system sensitivity to image structure, the current study demonstrates that older observers accumulate face information more slowly than younger subjects. Additionally, the N170 appears to be less face-sensitive in older observers