Point defect qubits in semiconductors have demonstrated their outstanding capabilities for high spatial resolution sensing generating broad multidisciplinary *** boron nitride(hBN)hosting point defect qubits have rece...
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Point defect qubits in semiconductors have demonstrated their outstanding capabilities for high spatial resolution sensing generating broad multidisciplinary *** boron nitride(hBN)hosting point defect qubits have recently opened up new horizons for quantum sensing by implementing sensing *** sensitivity of point defect sensors in hBN is currently limited by the linewidth of the magnetic resonance signal,which is broadened due to strong hyperfine couplings.
Quenching of oscillations, namely, amplitude and oscillations death, is an emerging phenomenon exhibited by many real-world complexsystems. Here, we introduce a scheme that combines dissimilar couplings and repulsive...
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Quenching of oscillations, namely, amplitude and oscillations death, is an emerging phenomenon exhibited by many real-world complexsystems. Here, we introduce a scheme that combines dissimilar couplings and repulsive feedback links for the interactions of Stuart-Landau oscillators and analytically derive the conditions required for the amplitude death. Importantly, this analysis is independent of the network size, presents a generalized approach to calculate the stability conditions for various different coupling schemes, and befits nonidentical oscillators as well. Last, we discuss the similarities of the quenching of oscillations phenomenon with the postictal generalized Electroencephalogram (EEG) suppression in convulsive seizures.
Metagenomics has opened new avenues for exploring the genetic potential of uncultured microorganisms,which may serve as promising sources of enzymes and natural products for industrial *** enzymes with improved cataly...
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Metagenomics has opened new avenues for exploring the genetic potential of uncultured microorganisms,which may serve as promising sources of enzymes and natural products for industrial *** enzymes with improved catalytic properties from the vast amount of available metagenomic data poses a significant challenge that demands the development of novel computational and functional screening *** catalytic properties of all enzymes are primarily dictated by their structures,which are predominantly determined by their amino acid ***,this aspect has not been fully considered in the enzyme bioprospecting *** the accumulating number of available enzyme sequences and the increasing demand for discovering novel biocatalysts,structural and functional modeling can be employed to identify potential enzymes with novel catalytic *** efforts to discover new polysaccharide-degrading enzymes from rumen metagenome data using homology-based searches and machine learning-based models have shown significant ***,we will explore various computational approaches that can be employed to screen and shortlist metagenome-derived enzymes as potential biocatalyst candidates,in conjunction with the wet lab analytical methods traditionally used for enzyme characterization.
Computer simulations are an important tool for studying the mechanics of biological evolution. In particular, agent-based approaches provide an opportunity to collect high-quality records of ancestry relationships. Su...
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ISBN:
(数字)9798331508371
ISBN:
(纸本)9798331508388
Computer simulations are an important tool for studying the mechanics of biological evolution. In particular, agent-based approaches provide an opportunity to collect high-quality records of ancestry relationships. Such phylogenies can provide insight into evolutionary dynamics within these simulations. Previous work generally tracks lineages directly, yielding an exact phylogenetic record of evolutionary history. However, challenges exist in scaling direct ancestrytracking approaches to highly-distributed, many-processor evolution in silico. An alternative approach is to estimate phylogenetic history via noncoding annotations on digital genomes, akin to how bioinformaticians build phylogenies by assessing genetic similarities between organisms. Recent work has extended this “hereditary stratigraphy” approach to support powerful hardware accelerator platforms, such as the Cerebras Wafer-Scale Engine. Although these second-generation “surface”-based hereditary stratigraphy algorithms have demonstrated order-ofmagnitude speedups over first-generation “column”-based algorithms, it remains unknown how they impact the accuracy of reconstructed phylogenies. To address this question, we assessed reconstruction accuracy under alternative configurations across a matrix of evolutionary conditions varying in selection pressure, spatial structure, and ecological dynamics. Encouragingly, we find that the second-generation approaches provide higher reconstruction quality across most surveyed conditions.
Continuing improvements in computing hardware are poised to transform capabilities for in silico modeling of cross-scale phenomena underlying major open questions in evolutionary biology and artificial life, such as t...
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Computer simulations are an important tool for studying the mechanics of biological evolution. In particular, in silico work with agent-based models provides an opportunity to collect high-quality records of ancestry ...
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Evolutionary dynamics are shaped by a variety of fundamental, generic drivers, including spatial structure, ecology, and selection pressure. These drivers impact the trajectory of evolution, and have been hypothesized...
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Evolutionary dynamics are shaped by a variety of fundamental, generic drivers, including spatial structure, ecology, and selection pressure. These drivers impact the trajectory of evolution, and have been hypothesized to influence phylogenetic structure. For instance, they can help explain natural history, steer behavior of contemporary evolving populations, and influence efficacy of application-oriented evolutionary optimization. Likewise, in inquiry-oriented artificial life systems, these drivers constitute key building blocks for open-ended evolution. Here, we set out to assess (1) if spatial structure, ecology, and selection pressure leave detectable signatures in phylogenetic structure, (2) the extent, in particular, to which ecology can be detected and discerned in the presence of spatial structure, and (3) the extent to which these phylogenetic signatures generalize across evolutionary systems. To this end, we analyze phylogenies generated by manipulating spatial structure, ecology, and selection pressure within three computational models of varied scope and sophistication. We find that selection pressure, spatial structure, and ecology have characteristic effects on phylogenetic metrics, although these effects are complex and not always intuitive. Signatures have some consistency across systems when using equivalent taxonomic unit definitions (e.g., individual, genotype, species). Further, we find that sufficiently strong ecology can be detected in the presence of spatial structure. We also find that, while low-resolution phylogenetic reconstructions can bias some phylogenetic metrics, high-resolution reconstructions recapitulate them faithfully. Although our results suggest potential for evolutionary inference of spatial structure, ecology, and selection pressure through phylogenetic analysis, further methods development is needed to distinguish these drivers' phylometric signatures from each other and to appropriately normalize phylogenetic metrics. With s
Operations over data streams typically hinge on efficient mechanisms to aggregate or summarize history on a rolling basis. For high-volume data steams, it is critical to manage state in a manner that is fast and memor...
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Operations over data streams typically hinge on efficient mechanisms to aggregate or summarize history on a rolling basis. For high-volume data steams, it is critical to manage state in a manner that is fast and memory efficient - particularly in resource-constrained or real-time contexts. Here, we address the problem of extracting a fixed-capacity, rolling subsample from a data stream. Specifically, we explore "data stream curation" strategies to fulfill requirements on the composition of sample time points retained. Our "DStream" suite of algorithms targets three temporal coverage criteria: (1) steady coverage, where retained samples should spread evenly across elapsed data stream history;(2) stretched coverage, where early data items should be proportionally favored;and (3) tilted coverage, where recent data items should be proportionally favored. For each algorithm, we prove worst-case bounds on rolling coverage quality. In contrast to previous work by Moreno, Rodriguez Papa, and Dolson (2024), which dynamically scales memory use to guarantee a specified level of coverage quality, here we focus on the more practical, application-driven case of maximizing coverage quality given a fixed memory capacity. As a core simplifying assumption, we restrict algorithm design to a single update operation: writing from the data stream to a calculated buffer site - with data never being read back, no metadata stored (e.g., sample timestamps), and data eviction occurring only implicitly via overwrite. Drawing only on primitive, low-level operations and ensuring full, overhead-free use of available memory, this "DStream" framework ideally suits domains that are resource-constrained (e.g., embedded systems), performance-critical (e.g., real-time), and fine-grained (e.g., individual data items as small as single bits or bytes). In particular, proposed power-of-two-based buffer layout schemes support O(1) data ingestion via concise bit-level operations. To further practical applica
The quantitative understanding and precise control of complex dynamical systems can only be achieved by observing their internal states via measurement and/or estimation. In large-scale dynamical networks, it is often...
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The influence of measurement back action on electro-optic sampling of electromagnetic quantum fluctuations is investigated. Based on a cascaded treatment of the nonlinear interaction between a near-infrared coherent p...
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The influence of measurement back action on electro-optic sampling of electromagnetic quantum fluctuations is investigated. Based on a cascaded treatment of the nonlinear interaction between a near-infrared coherent probe and the mid-infrared vacuum, we account for the generated electric-field contributions that lead to detectable back action. Specifically, we theoretically address two realistic setups, exploiting one or two probe beams for the nonlinear interaction with the quantum vacuum, respectively. The setup parameters at which back action starts to considerably contaminate the measured noise profiles are determined. We find that back action starts to detrimentally affect the signal once the fluctuations due to the coupling to the mid-infrared vacuum become comparable to the base shot noise. Due to the vacuum fluctuations entering at the beam splitter, the shot noise of two incoming probe pulses in different channels is uncorrelated. Therefore, even when the base shot noise dominates the output of the experiment, it does not contribute to the correlation signal itself. However, we find that further contributions due to nonlinear shot-noise enhancement are still present. Ultimately, a regime in which electro-optic sampling of quantum fields can be considered as effectively back-action free is found.
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