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The transport of conserved quantities like spin and charge is fundamental to characterizing the behavior of quantum many-body systems. Numerically simulating such dynamics is generically challenging, which motivates the consideration of quantum computing strategies. However, the relatively high gate errors and limited coherence times of today's quantum computers pose their own challenge, highlighting the need to be frugal with quantum resources. In this work we report simulations on quantum hardware of infinite-temperature energy transport in the mixed-field Ising chain, a paradigmatic many-body system that can exhibit a range of transport behaviors at intermediate times. We consider a chain with L=12 sites and find results broadly consistent with those from ideal circuit simulators over 90 Trotter steps, containing up to 990 entangling gates. To obtain these results, we use two key problem-tailored insights. First, we identify a convenient basis--the Pauli-Y basis--in which to sample the infinite-temperature trace and provide theoretical and numerical justifications for its efficiency relative to, e.g., the computational basis. Second, in addition to a variety of problem-agnostic error mitigation strategies, we employ a renormalization strategy that compensates for global nonconservation of energy due to device noise. We discuss the applicability of the proposed sampling approach beyond the mixed-field Ising chain and formulate a variational method to search for a sampling basis with small sample-to-sample fluctuations for an arbitrary Hamiltonian. This opens the door to applying these techniques in more general models. 

Dielectric mirrors based on Bragg reflection and photonic crystals have broad application in controlling light reflection with low optical losses. One key parameter in the design of these optical multilayers is the refractive index contrast, which controls the reflector performance. This work reports the demonstration of a high-reflectivity multilayer photonic reflector that consists of alternating layers of TiO₂films and nanolattices with low refractive index. The use of nanolattices enables high-index contrast between the high- and low-index layers, allowing high reflectivity with fewer layers. The broadband reflectance of the nanolattice reflectors with one to three layers has been characterized with peak reflectance of 91.9% at 527 nm and agrees well with theoretical optical models. The high-index contrast induced by the nanolattice layer enables a normalize reflectance band of Δλ/λ_oof 43.6%, the broadest demonstrated to date. The proposed nanolattice reflectors can find applications in nanophotonics, radiative cooling, and thermal insulation. 

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of aRhizosoleniasp. bloom, the initiation and complete bloom cycle ofChaetoceros socialis(8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms. 

Abstract The Gaia satellite is cataloging the astrometric properties of an unprecedented number of stars in the Milky Way with extraordinary precision. This provides a gateway for conducting extensive surveys of transient astrometric lensing events caused by dark compact objects. In this work, we establish a data analysis pipeline capable of searching for such events in the upcoming Gaia Data Release 4 (DR4). We use Gaia Early Data Release 3 (EDR3) and current dark matter and astrophysical black hole population models to create mock DR4 catalogs containing stellar trajectories perturbed by lensing. Our analysis of these mock catalogs suggests that Gaia DR4 will contain about 4 astrometric lensing events from astrophysical black holes at a 5 σ significance level. Furthermore, we project that our data analysis pipeline applied to Gaia DR4 will result in leading constraints on compact dark matter in the mass range 1–10 3   M ⊙ down to a dark matter fraction of about one percent. 

Abstract Understanding how climate affects trait composition within a biological assemblage is critical for assessing and eventually mitigating climate change impacts on the assemblage and its ecological functioning. While body size is a fundamental trait of animals as it affects many aspects of species' biology and ecology, it remains unclear through what mechanisms temperature and its variability influence within‐assemblage body size variation.This study aims to understand how temperature and its variability shape body size variations in animal assemblages and potentially affect assemblages' vulnerability to climate change. Using >5300 individuals of 680 macromoth species collected from 13 assemblages along a ca. 3000 m elevational gradient in Taiwan, we examined (1) the strength of environmental filtering and niche partitioning in determining the intra‐ and inter‐specific size variations within an assemblage, and (2) the effects of mean temperature and the daily and seasonal temperature variabilities on the strength of the two processes.We found that the body size composition was strongly affected by temperature and its seasonality via both processes. High temperature seasonality enhanced niche partitioning, causing within‐population size convergence. In contrast, low mean temperature and low seasonality both enhanced environmental filtering, causing within‐assemblage size convergence. However, while low temperature restricted the lower size limit within an assemblage, low seasonality restricted both lower and upper size limits.This study indicates an overlooked but important role of temperature seasonality in shaping intra‐ and inter‐specific size variations in moth assemblages through both environmental filtering and niche partitioning. With rising temperatures and amplifying seasonality around the globe, potentially weakened filtering forces may increase the size variation within assemblages, reinforcing the assemblage‐level resilience. Nevertheless, enhanced niche partitioning may limit size variation within populations, which may increase the population‐level vulnerability to environmental changes. This study improves the mechanistic understanding of the climatic effects on trait composition in animal assemblages and provides essential information for biodiversity conservation under climate change. Read the freePlain Language Summaryfor this article on the Journal blog. 

ABSTRACT We present six whole community shotgun metagenomic sequencing data sets of two types of biological soil crusts sampled at the ecotone of the Mojave Desert and Colorado Desert in California. These data will help us understand the diversity and function of biocrust microbial communities, which are essential for desert ecosystems.