Finite-resolution Deconvolution of Multiwavelength Imaging of 20,000 Galaxies in the COSMOS Field: The Evolution of Clumpy Galaxies over Cosmic Time

Compact star-forming clumps observed in distant galaxies are often suggested to play a crucial role in galaxy assembly. In this paper, we use a novel approach of applying finite-resolution deconvolution on ground-based images of the COSMOS field to resolve 20,185 star-forming galaxies (SFGs) at 0.5 < z < 2 to an angular resolution of 0.″3 and study their clump fractions. A comparison between the deconvolved images and HST images across four different filters shows good agreement and validates image deconvolution. We model spectral energy distributions using the deconvolved 14-band images to provide resolved surface brightness and stellar-mass density maps for these galaxies. We find that the fraction of clumpy galaxies decreases with increasing stellar masses and with increasing redshift: from ∼30% at z ∼ 0.7 to ∼50% at z ∼ 1.7. Using abundance matching, we also trace the progenitors for galaxies at z ∼ 0.7 and measure the fractional mass contribution of clumps toward their total mass budget. Clumps are observed to have a higher fractional mass contribution toward galaxies at higher redshift: increasing from ∼1% at z ∼ 0.7 to ∼5% at z ∼ 1.7. Finally, the majority of clumpy SFGs have higher specific star formation rates (sSFR) compared to the average SFGs at fixed stellar mass. We discuss the implication of this result for in situ clump formation due to disk instability.

Mathematical Principles of Object 3D Reconstruction by Shape-from-Focus Methods

Shape-from-Focus (SFF) methods have been developed for about twenty years. They able to obtain the shape of 3D objects from a series of partially focused images. The plane to which the microscope or camera is focused intersects the 3D object in a contour line. Due to wave properties of light and due to finite resolution of the output device, the image can be considered as sharp not only on this contour line, but also in a certain interval of height—the zone of sharpness. SSFs are able to identify these focused parts to compose a fully focused 2D image and to reconstruct a 3D profile of the surface to be observed.

Blockworlds 0.1.0: A demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models

Parametric geological models such as implicit or kinematic models provide low-dimensional, interpretable representations of 3-D geological structures. Combining these models with geophysical data in a probabilistic joint inversion framework provides an opportunity to directly quantify uncertainty in geological interpretations. For best results, the projection of the geological parameter space onto the finite-resolution discrete basis of the geophysical calculation must be faithful within the power of the data to discriminate. We show that naively exporting voxelised geology as done in commonly used geological modeling tools can easily produce a poor approximation to the true geophysical likelihood, degrading posterior inference for structural parameters. We then demonstrate a numerical forward-modeling scheme for calculating anti-aliased rock properties on regular meshes for use with gravity and magnetic sensors. Finally, we explore anti-aliasing in the context of a kinematic forward model for simple tectonic histories, showing its impact on the structure of the geophysical likelihood for gravity anomaly.

Lewis fry Richardson Medal Lecture – How many modes are neededto predict climate bifurcations?: Lessons from an experiment

According to everyone’s experience, predicting the weather reliably over more than 8 days seems an impossible taskfor our best weather agencies. At the same time, politicians and citizens are asking scientists for climate projections severaldecades into the future to guide economic and environmental policies, especially regarding the maximum admissible emissions of CO2. To what extent is this request scientifically admissible? In this lecture we will investigate this question, focusing on the topic of predictions of transitions between metastable statesof the atmospheric or oceanic circulations. Two relevant exemples are the switching between zonal and blocked atmosphericcirculation at midlatitudes and the alternance of El Niño and La Niña phases in the Pacific ocean. The main issue is whetherpresent climate models, that necessarily have a finite resolution and a smaller number of degrees of freedom than the actualterrestrial system, are able to reproduce such spontaneous or forced transitions. To do so, we will draw an analogy betweenclimate observations and results obtained in our group on a laboratory-scale, turbulent, von Kármán flow, in which spontaneoustransitions between different states of the circulation take place. We will detail the analogy, and investigate the nature of thetransitions, the number of degrees of freedom that characterizes the latter and discuss the effect of reducing the number ofdegrees of freedom in such systems. We will also discuss the role of fluctuations and their origin, and stress the importance ofdescribing very small scales to capture fluctuations of correct intensity and scale.

Theoretical and practical approaches to improve the performance of local correlation algorithms for volume data analysis and shape recognition

In this paper, several approaches to be used to accelerate algorithms for fitting an atomic structure into a given 3D density map determined by cryo-EM are discussed. Rotation and translation of the atomic structure to find similarity scores are used and implemented with discrete Fourier transforms. Several rotations can be combined into groups to accelerate processing. The finite resolution of experimental and simulated maps allows a reduction in the number of rotations and translations needed in order to estimate similarity-score values.

How many modes does it take to describe climate change?: The lessons from an experiment

&lt;p&gt;According to everyone's experience, predicting the weather reliably for more than 8 days seems an impossible task for our best weather agencies. At the same time, politicians and citizens are asking scientists for decades of climate predictions to help them make decisions, especially on CO2 emissions. To what extent is this request scientifically admissible?&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;In this lecture I will investigate this question, focusing on the topic of predictions of bifurcations of the atmospheric or oceanic circulations. In such case, the issue is whether present climate models, that have necessarily a finite resolution and a smaller number of degrees of freedom than the actual terrestrial systems, are able to reproduce spontaneous or forced bifurcations. For this, I will use recent results obtained by my group in a laboratory analog of such systems, so called von Karman flow, in which spontaneous bifurcations of the circulation take place. I will detail the analogy, and investigate the nature of bifurcations, the number of degrees of freedom that characterizes it and discuss what is the effect of reducing the number of degrees of freedom in such system.&lt;/p&gt;&lt;p&gt;I will also discuss the role of fluctuations and their origin, and stress the importance of describing very small scales to capture fluctuations of correct intensity and scale.&lt;/p&gt;