Magnetometry of random AC magnetic fields using a single Nitrogen-Vacancy center

We report on the use of a single NV center to probe fluctuating AC magnetic fields. Using engineered currents to induce random changes in the field amplitude and phase, we show that stochastic fluctuations reduce the NV center sensitivity and, in general, make the NV response field-dependent. We also introduce two modalities to determine the field spectral composition, unknown a priori in a practical application. One strategy capitalizes on the generation of AC-field-induced coherence 'revivals', while the other approach uses the time-tagged fluorescence intensity record from successive NV observations to reconstruct the AC field spectral density. These studies are relevant for magnetic sensing in scenarios where the field of interest has a non-trivial, stochastic behavior, such as sensing unpolarized nuclear spin ensembles at low static magnetic fields.Comment: 11 pages, 3 figure

Evolution at the edge of expanding populations

Predicting evolution of expanding populations is critical to control biological threats such as invasive species and cancer metastasis. Expansion is primarily driven by reproduction and dispersal, but nature abounds with examples of evolution where organisms pay a reproductive cost to disperse faster. When does selection favor this 'survival of the fastest?' We searched for a simple rule, motivated by evolution experiments where swarming bacteria evolved into an hyperswarmer mutant which disperses $\sim 100\%$ faster but pays a growth cost of $\sim 10 \%$ to make many copies of its flagellum. We analyzed a two-species model based on the Fisher equation to explain this observation: the population expansion rate ($v$) results from an interplay of growth ($r$) and dispersal ($D$) and is independent of the carrying capacity: $v=2\sqrt{rD}$. A mutant can take over the edge only if its expansion rate ($v_2$) exceeds the expansion rate of the established species ($v_1$); this simple condition ($v_2 > v_1$) determines the maximum cost in slower growth that a faster mutant can pay and still be able to take over. Numerical simulations and time-course experiments where we tracked evolution by imaging bacteria suggest that our findings are general: less favorable conditions delay but do not entirely prevent the success of the fastest. Thus, the expansion rate defines a traveling wave fitness, which could be combined with trade-offs to predict evolution of expanding populations

A simple rule for the evolution of fast dispersal at the edge of expanding populations

Evolution by natural selection is commonly perceived as a process that favors those that replicate faster to leave more offspring; nature, however, seem to abound with examples where organisms forgo some replicative potential to disperse faster. When does selection favor invasion of the fastest? Motivated by evolution experiments with swarming bacteria we searched for a simple rule. In experiments, a fast hyperswarmer mutant that pays a reproductive cost to make many copies of its flagellum invades a population of mono-flagellated bacteria by reaching the expanding population edge; a two-species mathematical model explains that invasion of the edge occurs only if the invasive species' expansion rate, v₂, which results from the combination of the species growth rate and its dispersal speed (but not its carrying capacity), exceeds the established species', v₁. The simple rule that we derive, v₂ > v₁, appears to be general: less favorable initial conditions, such as smaller initial sizes and longer distances to the population edge, delay but do not entirely prevent invasion. Despite intricacies of the swarming system, experimental tests agree well with model predictions suggesting that the general theory should apply to other expanding populations with trade-offs between growth and dispersal, including non-native invasive species and cancer metastases.First author draf

Role of cross helicity in magnetohydrodynamic turbulence

Strong incompressible three-dimensional magnetohydrodynamic turbulence is investigated by means of high resolution direct numerical simulations. The simulations show that the configuration space is characterized by regions of positive and negative cross-helicity, corresponding to highly aligned or anti-aligned velocity and magnetic field fluctuations, even when the average cross-helicity is zero. To elucidate the role of cross-helicity, the spectra and structure of turbulence are obtained in imbalanced regions where cross-helicity is non-zero. When averaged over regions of positive and negative cross-helicity, the result is consistent with the simulations of balanced turbulence. An analytical explanation for the obtained results is proposed.Comment: 4 pages, 4 figure

Eye-CU: Sleep Pose Classification for Healthcare using Multimodal Multiview Data

Manual analysis of body poses of bed-ridden patients requires staff to continuously track and record patient poses. Two limitations in the dissemination of pose-related therapies are scarce human resources and unreliable automated systems. This work addresses these issues by introducing a new method and a new system for robust automated classification of sleep poses in an Intensive Care Unit (ICU) environment. The new method, coupled-constrained Least-Squares (cc-LS), uses multimodal and multiview (MM) data and finds the set of modality trust values that minimizes the difference between expected and estimated labels. The new system, Eye-CU, is an affordable multi-sensor modular system for unobtrusive data collection and analysis in healthcare. Experimental results indicate that the performance of cc-LS matches the performance of existing methods in ideal scenarios. This method outperforms the latest techniques in challenging scenarios by 13% for those with poor illumination and by 70% for those with both poor illumination and occlusions. Results also show that a reduced Eye-CU configuration can classify poses without pressure information with only a slight drop in its performance.Comment: Ten-page manuscript including references and ten figure

Velocities from Cross-Correlation: A Guide for Self-Improvement

The measurement of Doppler velocity shifts in spectra is a ubiquitous theme in astronomy, usually handled by computing the cross-correlation of the signals, and finding the location of its maximum. This paper addresses the problem of the determination of wavelength or velocity shifts among multiple spectra of the same, or very similar, objects. We implement the classical cross-correlation method and experiment with several simple models to determine the location of the maximum of the cross-correlation function. We propose a new technique, 'self-improvement', to refine the derived solutions by requiring that the relative velocity for any given pair of spectra is consistent with all others. By exploiting all available information, spectroscopic surveys involving large numbers of similar objects may improve their precision significantly. As an example, we simulate the analysis of a survey of G-type stars with the SDSS instrumentation. Applying 'self-improvement' refines relative radial velocities by more than 50% at low signal-to-noise ratio. The concept is equally applicable to the problem of combining a series of spectroscopic observations of the same object, each with a different Doppler velocity or instrument-related offset, into a single spectrum with an enhanced signal-to-noise ratio.Comment: 7 pages, 3 figures, uses emulateapj.cls; to appear in the Astronomical Journal; see http://hebe.as.utexas.edu/stools/ to obtain the companion softwar