Delta-Vs and Design Reference Mission Scenarios for Mars Missions

Before setting out on any long journey, it is important to first have an idea about how to get there, how long it might take, and how much it will cost. Primarily, the answers depend upon where you are starting and where you wish to go. In the formulative stages of any mission to Mars, having quick estimates of answers to these basic questions will aid in the efficient exploration of the trade space. In this paper, we present a “mileage chart” of sorts illustrating the range of ΔV’s and times-of-flight (TOF) between various starting and stopping points between Earth and Mars. This paper expands upon a chart from a previous work by the authors. We discuss the methodologies used to calculate or estimate expected values and reasonable ranges, including some more detailed specific examples

Analyzing Prospects for Quantum Advantage in Topological Data Analysis

Lloyd et al. were first to demonstrate the promise of quantum algorithms for computing Betti numbers, a way to characterize topological features of data sets. Here, we propose, analyze, and optimize an improved quantum algorithm for topological data analysis (TDA) with reduced scaling, including a method for preparing Dicke states based on inequality testing, a more efficient amplitude estimation algorithm using Kaiser windows, and an optimal implementation of eigenvalue projectors based on Chebyshev polynomials. We compile our approach to a fault-tolerant gate set and estimate constant factors in the Toffoli complexity. Our analysis reveals that super-quadratic quantum speedups are only possible for this problem when targeting a multiplicative error approximation and the Betti number grows asymptotically. Further, we propose a dequantization of the quantum TDA algorithm that shows that having exponentially large dimension and Betti number are necessary, but insufficient conditions, for super-polynomial advantage. We then introduce and analyze specific problem examples which have parameters in the regime where super-polynomial advantages may be achieved, and argue that quantum circuits with tens of billions of Toffoli gates can solve seemingly classically intractable instances.Comment: 54 pages, 7 figures. Added a number of theorems and lemmas to clarify findings and also a discussion in the main text and new appendix about variants of our problems with high Betti numbers that are challenging for recent classical algorithm

Close companions around young stars

Multiplicity is a fundamental property that is set early during stellar lifetimes, and it is a stringent probe of the physics of star formation. The distribution of close companions around young stars is still poorly constrained by observations. We present an analysis of stellar multiplicity derived from APOGEE-2 spectra obtained in targeted observations of nearby star-forming regions. This is the largest homogeneously observed sample of high-resolution spectra of young stars. We developed an autonomous method to identify double lined spectroscopic binaries (SB2s). Out of 5007 sources spanning the mass range of $\sim$0.05--1.5 \msun, we find 399 binaries, including both RV variables and SB2s. The mass ratio distribution of SB2s is consistent with a uniform for $q0.95$. The period distribution is consistent with what has been observed in close binaries ($<10$ AU) in the evolved populations. Three systems are found to have $q\sim$0.1, with a companion located within the brown dwarf desert. There are not any strong trends in the multiplicity fraction (MF) as a function of cluster age from 1 to 100 Myr. There is a weak dependence on stellar density, with companions being most numerous at $\Sigma_*\sim30$ stars/pc$^{-2}$, and decreasing in more diffuse regions. Finally, disk-bearing sources are deficient in SB2s (but not RV variables) by a factor of $\sim$2; this deficit is recovered by the systems without disks. This may indicate a quick dispersal of disk material in short-period equal mass systems that is less effective in binaries with lower $q$.Comment: 25 pages, 20 figures. Accepted to A

Observing Mars from Areostationary Orbit: Benefits and Applications

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Mosaic: A Satellite Constellation to Enable Groundbreaking Mars Climate System Science and Prepare for Human Exploration

The Martian climate system has been revealed to rival the complexity of Earth\u27s. Over the last 20 yr, a fragmented and incomplete picture has emerged of its structure and variability; we remain largely ignorant of many of the physical processes driving matter and energy flow between and within Mars\u27 diverse climate domains. Mars Orbiters for Surface, Atmosphere, and Ionosphere Connections (MOSAIC) is a constellation of ten platforms focused on understanding these climate connections, with orbits and instruments tailored to observe the Martian climate system from three complementary perspectives. First, low-circular near-polar Sun-synchronous orbits (a large mothership and three smallsats spaced in local time) enable vertical profiling of wind, aerosols, water, and temperature, as well as mapping of surface and subsurface ice. Second, elliptical orbits sampling all of Mars\u27 plasma regions enable multipoint measurements necessary to understand mass/energy transport and ion-driven escape, also enabling, with the polar orbiters, dense radio occultation coverage. Last, longitudinally spaced areostationary orbits enable synoptic views of the lower atmosphere necessary to understand global and mesoscale dynamics, global views of the hydrogen and oxygen exospheres, and upstream measurements of space weather conditions. MOSAIC will characterize climate system variability diurnally and seasonally, on meso-, regional, and global scales, targeting the shallow subsurface all the way out to the solar wind, making many first-of-their-kind measurements. Importantly, these measurements will also prepare for human exploration and habitation of Mars by providing water resource prospecting, operational forecasting of dust and radiation hazards, and ionospheric communication/positioning disruptions

Low but contrasting neutral genetic differentiation shaped by winter temperature in European great tits

Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species – the great tit Parus major – at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), using 22 microsatellite markers. Overall we found a low but significant genetic differentiation among sites (FST = 0.008). Genetic differentiation was higher, and genetic diversity lower, in south-western Europe. These regional differences were statistically best explained by winter temperature. Overall, our results suggest that great tits form a single patchy metapopulation across Europe, in which genetic differentiation is independent of geographical distance and gene flow may be regulated by environmental factors via movements related to winter severity. This might have important implications for the evolutionary trajectories of sub-populations, especially in the context of climate change, and calls for future investigations of local differences in costs and benefits of philopatry at large scales

Interpretable surface-based detection of focal cortical dysplasias:a Multi-centre Epilepsy Lesion Detection study

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world