Preparing to Discover the Unknown with Rubin LSST: Time Domain

Perhaps the most exciting promise of the Rubin Observatory Legacy Survey of Space and Time (LSST) is its capability to discover phenomena never before seen or predicted: true astrophysical novelties; but the ability of LSST to make these discoveries will depend on the survey strategy. Evaluating candidate strategies for true novelties is a challenge both practically and conceptually. Unlike traditional astrophysical tracers like supernovae or exoplanets, for anomalous objects, the template signal is by definition unknown. We approach this problem by assessing survey completeness in a phase space defined by object color and flux (and their evolution), and considering the volume explored by integrating metrics within this space with the observation depth, survey footprint, and stellar density. With these metrics, we explore recent simulations of the Rubin LSST observing strategy across the entire observed spatial footprint and in specific Local Volume regions: the Galactic Plane and Magellanic Clouds. Under our metrics, observing strategies with greater diversity of exposures and time gaps tend to be more sensitive to genuinely new transients, particularly over time-gap ranges left relatively unexplored by previous surveys. To assist the community, we have made all of the tools developed publicly available. While here we focus on transients, an extension of the scheme to include proper motions and the detection of associations or populations of interest will be communicated in Paper II of this series. This paper was written with the support of the Vera C. Rubin LSST Transients and Variable Stars and Stars, Milky Way, Local Volume Science Collaborations.

Structures of Dwarf Satellites of Milky Way-like Galaxies: Morphology, Scaling Relations, and Intrinsic Shapes

The structure of a dwarf galaxy is an important probe of the effects of stellar feedback and environment. Using an unprecedented sample of 223 low-mass satellites from the ongoing Exploration of Local Volume Satellites survey, we explore the structures of dwarf satellites in the mass range 105.5 < M ⋆ < 108.5 M ⊙. We survey satellites around 80% of the massive, M K < − 22.4 mag, hosts in the Local Volume (LV). Our sample of dwarf satellites is complete to luminosities of M V <−9 mag and surface brightness μ 0,V < 26.5 mag arcsec−2 within at least ∼200 projected kpc of the hosts. For this sample, we find a median satellite luminosity of M V = −12.4 mag, median size of r e = 560 pc, median ellipticity of ϵ = 0.30, and median Sérsic index of n = 0.72. We separate the satellites into late- and early-type (29.6% and 70.4%, respectively). The mass–size relations are very similar between them within ∼5%, which indicates that the quenching and transformation of a late-type dwarf into an early-type one involves only very mild size evolution. Considering the distribution of apparent ellipticities, we infer the intrinsic shapes of the early- and late-type samples. Combining with literature samples, we find that both types of dwarfs are described roughly as oblate spheroids that get more spherical at fainter luminosities, but early-types are always rounder at fixed luminosity. Finally, we compare the LV satellites with dwarf samples from the cores of the Virgo and Fornax clusters. We find that the cluster satellites show similar scaling relations to the LV early-type dwarfs but are roughly 10% larger at fixed mass, which we interpret as being due to tidal heating in the cluster environments. The dwarf structure results presented here are a useful reference for simulations of dwarf galaxy formation and the transformation of dwarf irregulars into spheroidals.

The Phantom Dark Matter Halos of the Local Volume in the Context of Modified Newtonian Dynamics

We explore the predictions of Milgromian gravity (MOND) in the local universe by considering the distribution of the “phantom” dark matter (PDM) that would source the MOND gravitational field in Newtonian gravity, allowing an easy comparison with the dark matter framework. For this, we specifically deal with the quasi-linear version of MOND (QUMOND). We compute the “stellar-to-(phantom)halo mass relation” (SHMR), a monotonically increasing power law resembling the SHMR observationally deduced from spiral galaxy rotation curves in the Newtonian context. We show that the gas-to-(phantom)halo mass relation is flat. We generate a map of the Local Volume in QUMOND, highlighting the important influence of distant galaxy clusters, in particular Virgo. This allows us to explore the scatter of the SHMR and the average density of PDM around galaxies in the Local Volume, ΩPDM ≈ 0.1, below the average cold dark matter density in a ΛCDM universe. We provide a model of the Milky Way in its external field in the MOND context, which we compare to an observational estimate of the escape velocity curve. Finally, we highlight the peculiar features related to the external field effect in the form of negative PDM density zones in the outskirts of each galaxy, and test a new analytic formula for computing galaxy rotation curves in the presence of an external field in QUMOND. While we show that the negative PDM density zones would be difficult to detect dynamically, we quantify the weak-lensing signal they could produce for lenses at z ∼ 0.3.

An Aggregation-Free Local Volume Fraction Formulation for Topological Design of Porous Structure

Cellular structure can possess superior mechanical properties and low density simultaneously. Additive manufacturing has experienced substantial progress in the past decades, which promotes the popularity of such bone-like structure. This paper proposes a methodology on the topological design of porous structure. For the typical technologies such as the p-norm aggregation and implicit porosity control, the violation of the maximum local volume constraint is inevitable. To this end, the primary optimization problem with bounds of local volume constraints is transformed into unconstrained programming by setting up a sequence of minimization sub-problems in terms of the augmented Lagrangian method. The approximation and algorithm using the concept of moving asymptotes is employed as the optimizer. Several numerical tests are provided to illustrate the effectiveness of the proposed approach in comparison with existing approaches. The effects of the global and local volume percentage, influence radius and mesh discretization on the final designs are investigated. In comparison to existing methods, the proposed method is capable of accurately limiting the upper bound of global and local volume fractions, which opens up new possibilities for additive manufacturing.

Topology optimization using PETSc: a Python wrapper and extended functionality

This paper presents a Python wrapper and extended functionality of the parallel topology optimization framework introduced by Aage et al. (Topology optimization using PETSc: an easy-to-use, fully parallel, open source topology optimization framework. Struct Multidiscip Optim 51(3):565–572, 2015). The Python interface, which simplifies the problem definition, is intended to expand the potential user base and to ease the use of large-scale topology optimization for educational purposes. The functionality of the topology optimization framework is extended to include passive domains and local volume constraints among others, which contributes to its usability to real-world design applications. The functionality is demonstrated via the cantilever beam, bracket and torsion ball examples. Several tests are provided which can be used to verify the proper installation and for evaluating the performance of the user’s system setup. The open-source code is available at https://github.com/thsmit/, repository $$\texttt {TopOpt\_in\_PETSc\_wrapped\_in\_Python}$$ TopOpt _ in _ PETSc _ wrapped _ in _ Python .

Thalamic morphology predicts the onset of freezing of gait in Parkinson’s disease

The onset of freezing of gait (FOG) in Parkinson’s disease (PD) is a critical milestone, marked by a higher risk of falls and reduced quality of life. FOG is associated with alterations in subcortical neural circuits, yet no study has assessed whether subcortical morphology can predict the onset of clinical FOG. In this prospective multimodal neuroimaging cohort study, we performed vertex-based analysis of grey matter morphology in fifty-seven individuals with PD at study entry and two years later. We also explored the behavioral correlates and resting-state functional connectivity related to these local volume differences. At study entry, we found that freezers (N = 12) and persons who developed FOG during the course of the study (converters) (N = 9) showed local inflations in bilateral thalamus in contrast to persons who did not (non-converters) (N = 36). Longitudinally, converters (N = 7) also showed local inflation in the left thalamus, as compared to non-converters (N = 36). A model including sex, daily levodopa equivalent dose, and local thalamic inflation predicted conversion with good accuracy (AUC: 0.87, sensitivity: 88.9%, specificity: 77.8%). Exploratory analyses showed that local thalamic inflations were associated with larger medial thalamic sub-nuclei volumes and better cognitive performance. Resting-state analyses further revealed that converters had stronger thalamo-cortical coupling with limbic and cognitive regions pre-conversion, with a marked reduction in coupling over the two years. Finally, validation using the PPMI cohort suggested FOG-specific non-linear evolution of thalamic local volume. These findings provide markers of, and deeper insights into conversion to FOG, which may foster earlier intervention and better mobility for persons with PD.