Gaussian Process Classification for Galaxy Blend Identification in LSST

A significant fraction of observed galaxies in the Rubin Observatory Legacy Survey of Space and Time (LSST) will overlap at least one other galaxy along the same line of sight, in a so-called “blend.” The current standard method of assessing blend likelihood in LSST images relies on counting up the number of intensity peaks in the smoothed image of a blend candidate, but the reliability of this procedure has not yet been comprehensively studied. Here we construct a realistic distribution of blended and unblended galaxies through high-fidelity simulations of LSST-like images, and from this we examine the blend classification accuracy of the standard peak-finding method. Furthermore, we develop a novel Gaussian process blend classifier model, and show that this classifier is competitive with both the peak finding method as well as with a convolutional neural network model. Finally, whereas the peak-finding method does not naturally assign probabilities to its classification estimates, the Gaussian process model does, and we show that the Gaussian process classification probabilities are generally reliable.

Unequal-mass mergers of dark matter haloes with rare and frequent self-interactions

Dark matter self-interactions have been proposed to solve problems on small length scales within the standard cold dark matter cosmology. Here we investigate the effects of dark matter self-interactions in merging systems of galaxies and galaxy clusters with equal and unequal mass ratios. We perform N-body dark matter-only simulations of idealised setups to study the effects of dark matter self-interactions that are elastic and velocity-independent. We go beyond the commonly adopted assumption of large-angle (rare) dark matter scatterings, paying attention to the impact of small-angle (frequent) scatterings on astrophysical observables and related quantities. Specifically, we focus on dark matter-galaxy offsets, galaxy-galaxy distances, halo shapes, morphology and the phase-space distribution. Moreover, we compare two methods to identify peaks: one based on the gravitational potential and one based on isodensity contours. We find that the results are sensitive to the peak finding method, which poses a challenge for the analysis of merging systems in simulations and observations, especially for minor mergers. Large dark matter-galaxy offsets can occur in minor mergers, especially with frequent self-interactions. The subhalo tends to dissolve quickly for these cases. While clusters in late merger phases lead to potentially large differences between rare and frequent scatterings, we believe that these differences are non-trivial to extract from observations. We therefore study the galaxy/star populations which remain distinct even after the dark matter haloes have coalesced. We find that these collisionless tracers behave differently for rare and frequent scatterings, potentially giving a handle to learn about the micro-physics of dark matter.

Informed Forms and Matters

After sufficient consideration for the proper balance between material and formal constraints, this chapter describes a pedagogical approach that transforms the education of future architects through a 'form-finding' method, allowing the material to accommodate itself to form and celebrate its own nature. To enhance pedagogical improvement of foundational studies in architecture and further explore this pedagogy based on form-finding in early design education, this chapter also presents the challenges to integrating materiality within the design process, as derived from the incorporation of experimental form-finding methods into early-stage design.

A Form-Finding Method for Branching Structures Based on Dynamic Relaxation

Branching structure is often used as a supporting structure of the grid shell due to its geometrical and force-transferring features, and the rationality of its shape is very important. The “physical” and “numerical” hanging models can be used for the joint form-finding of the branching structure and free-form grid shell. However, slack elements may exist in the equilibrium model which corresponds to the inefficient members in the form-found branching structure. To solve this problem, a form-finding method of branching structure based on dynamic relaxation is proposed in this study. The proposed method clusters the elements of the branching model and equalizes the axial forces of the elements in the same cluster, in other words, there are no slack elements in the equilibrium branching model. This method overcomes the defect that the equilibrium branching model may have slack elements and needs many manual adjustments during the procedure of determining the rational shape of a branching structure, and effectively prevents the inefficient members existing in the form-found structure. Numerical examples are provided to demonstrate the characteristics of the proposed method and its effectiveness is verified as well.