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Abstract Variational quantum eigensolvers (VQEs) are leading candidates to demonstrate near-term quantum advantage. Here, we conduct density-matrix simulations of leading gate-based VQEs for a range of molecules. We numerically quantify their level of tolerable depolarizing gate-errors. We find that: (i) The best-performing VQEs require gate-error probabilities between 10−6 and 10−4 (10−4 and 10−2 with error mitigation) to predict, within chemical accuracy, ground-state energies of small molecules with 4 − 14 orbitals. (ii) ADAPT-VQEs that construct ansatz circuits iteratively outperform fixed-circuit VQEs. (iii) ADAPT-VQEs perform better with circuits constructed from gate-efficient rather than physically-motivated elements. (iv) The maximally-allowed gate-error probability, p c , for any VQE to achieve chemical accuracy decreases with the number N II of noisy two-qubit gates as $${p}_{c}\mathop{\propto }\limits_{\displaystyle{ \sim }}{N}_{{{{\rm{II}}}}}^{-1}$$ p c ∝ ~ N II − 1 . Additionally, p c decreases with system size, even with error mitigation, implying that larger molecules require even lower gate-errors. Thus, quantum advantage via gate-based VQEs is unlikely unless gate-error probabilities are decreased by orders of magnitude.

Abstract We present a numerically-optimized multipulse framework for the quantum control of a single-electron double quantum dot qubit. Our framework defines a set of pulse sequences, necessary for the manipulation of the ideal qubit basis, that avoids errors associated with excitations outside the computational subspace. A novel control scheme manipulates the qubit adiabatically, while also retaining high speed and ability to perform a general single-qubit rotation. This basis generates spatially localized logical qubit states, making readout straightforward. We consider experimentally realistic semiconductor qubits with finite pulse rise and fall times and determine the fastest pulse sequence yielding the highest fidelity. We show that our protocol leads to improved control of a qubit. We present simulations of a double quantum dot in a semiconductor device to visualize and verify our protocol. These results can be generalized to other physical systems since they depend only on pulse rise and fall times and the energy gap between the two lowest eigenstates.

This paper describes the new open-source framework PyFLEXTRKR (Python FLEXible object TRacKeR), a flexible atmospheric feature tracking software package with specific capabilities to track convective clouds from a variety of observations and model simulations. This software can track any atmospheric 2D objects and handle merging and splitting explicitly. The package has a collection of multi-object identification algorithms, scalable parallelization options, and has been optimized for large datasets including global high-resolution data. We demonstrate applications of PyFLEXTRKR on tracking individual deep convective cells and mesoscale convective systems from observations and model simulations ranging from large-eddy resolving (∼100s m) to mesoscale (∼10s km) resolutions. Visualization, post-processing, and statistical analysis tools are included in the package. New Lagrangian analyses of convective clouds produced by PyFLEXTRKR applicable to a wide range of datasets and scales facilitate advanced model evaluation and development efforts as well as scientific discovery.

Summary: Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest types of cancer and has a 5-year survival of less than 8% owing to its complex biology. As PDAC is refractory to immunotherapy, we need to understand the functional dynamics of T cells in the PDAC microenvironment to develop alternative therapeutic strategies. In this study, we performed RNA velocity-based pseudotime analysis on a scRNA-seq dataset from surgically resected human PDAC specimens to gain insight into temporal gene expression patterns that best characterize the cell fates. The tumor microenvironment was seen to encompass a range of terminal states for the T cell trajectories with suppressive and non-tumor-responsive T cells dominating them. However, the results also reveal the existence of a functional branch of the T cell population that was not transitioning to exhausted and senescent states. These findings reveal various microenvironmental signals driving T cell patterns which can be useful in identifying new therapeutic avenues.

Existing methods for molecular simulations with quantum computers use ansatz constructed as series of fermionic excitation evolution. Here, qubit excitation evolutions are employed instead, in combination with the ADAPT-VQE protocol, to construct short and accurate ansatz suitable for noisy and imperfect quantum computers.

Accurate detection and quantification of regional vegetation trends are essential for understanding the dynamics of landscape ecology and vegetation distribution. We applied a comprehensive trend analysis to satellite data to describe geospatial changes in vegetation along the Pacific slope of Peru and northern Chile, from sea level to the continental divide, a region characterised by biologically unique and highly sensitive arid and semi-arid environments. Our statistical analyses show broad regional patterns of positive trends in EVI, called “greening”, alongside patterns of “browning”, where trends are negative between 2000 and 2020. The coastal plain and foothills, up 1000 m, contain notable greening of the coastal Lomas and newly irrigated agricultural lands occurring alongside browning trends related to changes in land use practices and urban development. Strikingly, the precordilleras show a distinct ‘greening strip’, which extends from approximately 6°S to 22°S, with an altitudinal trend, ascending from the tropical lowlands (170–780 m) in northern Peru to the subtropics (1000–2800 m) in central Peru and temperate zone (2600–4300 m) in southern Peru and northern Chile. We find that the geographical characteristics of the greening strip do not match climate zones previously established by Köppen and Geiger. Greening and browning trends in the coastal deserts and the high Andes lie within well defined climatic and life zones, producing variable but identifiable trends. However, the distinct Pacific slope greening presents an unexpected distribution with respect to the regional Köppen–Geiger climate and life zones. This work provides insights on understanding the effects of climate change on Peru’s diverse ecosystems in highly sensitive, biologically unique arid and semi-arid environments on the Pacific slope.

Southern pine lumber is often treated with preservatives, but issues related to initial kiln-drying conditions and geographic source across the wide southern pine growth range have been suspected to negatively affect subsequent permeability and treatability. These effects remain poorly understood. In this series of exploratory studies, southern pine from across part of the growing range subjected to different kiln-drying regimes was evaluated in three phases exploring the effects of geographic source and initial kiln-drying conditions on permeability, pit structure and eventual preservative treatment of southern pine lumber. The results suggest that elevated temperatures coupled with poor humidity control at the start of the kiln drying process may negatively influence permeability and preservative penetration, but had only negligible effects on several other wood properties.

In quantum metrology (as well as computing) it is not easy to pinpoint the specific source of quantum advantage. Here, the authors reveal a link between postselection and the unusually high rates of information per final measurement in general quantum parameter-estimation scenarios.

Abstract Background Olfactory receptor (OR) genes are the largest multi-gene family in the mammalian genome, with 874 in human and 1483 loci in mouse (including pseudogenes). The expansion of the OR gene repertoire has occurred through numerous duplication events followed by diversification, resulting in a large number of highly similar paralogous genes. These characteristics have made the annotation of the complete OR gene repertoire a complex task. Most OR genes have been predicted in silico and are typically annotated as intronless coding sequences. Results Here we have developed an expert curation pipeline to analyse and annotate every OR gene in the human and mouse reference genomes. By combining evidence from structural features, evolutionary conservation and experimental data, we have unified the annotation of these gene families, and have systematically determined the protein-coding potential of each locus. We have defined the non-coding regions of many OR genes, enabling us to generate full-length transcript models. We found that 13 human and 41 mouse OR loci have coding sequences that are split across two exons. These split OR genes are conserved across mammals, and are expressed at the same level as protein-coding OR genes with an intronless coding region. Our findings challenge the long-standing and widespread notion that the coding region of a vertebrate OR gene is contained within a single exon. Conclusions This work provides the most comprehensive curation effort of the human and mouse OR gene repertoires to date. The complete annotation has been integrated into the GENCODE reference gene set, for immediate availability to the research community.