Continuous-time quantum walks can be used to solve the spatial search problem, which is an essential component for many quantum algorithms that run quadratically faster than their classical counterpart, in O(sqrt[n]) time for n entries. However, the capability of models found in nature is largely unexplored-e.g., in one dimension only nearest-neighbor Hamiltonians have been considered so far, for which the quadratic speedup does not exist. Here, we prove that optimal spatial search, namely with O(sqrt[n]) run time and high fidelity, is possible in one-dimensional spin chains with long-range interactions that decay as 1/r^{α} with distance r. In particular, near unit fidelity is achieved for α≈1 and, in the limit n→∞, we find a continuous transition from a region where optimal spatial search does exist (α<1.5) to where it does not (α>1.5). Numerically, we show that spatial search is robust to dephasing noise and that, for reasonable chain lengths, α≲1.2 should be sufficient to demonstrate optimal spatial search experimentally with near unit fidelity.
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http://dx.doi.org/10.1103/PhysRevLett.126.240502 | DOI Listing |
Trans R Soc Trop Med Hyg
January 2025
Centre for Snakebite Research and Interventions, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK.
Background: Snakebite is a priority neglected tropical disease, but incidence data are lacking; current estimates rely upon incomplete health facility reports or ad hoc surveys. Spatial analysis methods harness statistical associations between case incidence and spatially varying factors to improve estimates. This systematic review aimed to identify variables associated with snakebite risk in spatial and temporal analyses for inclusion in geospatial studies to improve risk estimation accuracy.
View Article and Find Full Text PDFAn intelligent controlled spatiotemporal mode-locked (STML) fiber laser based on a photonic lantern (PL) is proposed and experimentally demonstrated. A pair of in-house developed PLs is spliced into the cavity in a back-to-back structure. This PL-based structure functions as a mode multiplexer/demultiplexer to generate higher-order spatial modes.
View Article and Find Full Text PDFPLoS One
January 2025
Division of Biological Sciences, US Fish and Wildlife Southwest Regional Office, Albuquerque, New Mexico, United States of America.
There is growing interest in using deep learning models to automate wildlife detection in aerial imaging surveys to increase efficiency, but human-generated annotations remain necessary for model training. However, even skilled observers may diverge in interpreting aerial imagery of complex environments, which may result in downstream instability of models. In this study, we present a framework for assessing annotation reliability by calculating agreement metrics for individual observers against an aggregated set of annotations generated by clustering multiple observers' observations and selecting the mode classification.
View Article and Find Full Text PDFEur J Med Res
January 2025
Clinical Research and Big Data Center, South China Research Center for Acupuncture and Moxibustion, Medical College of Acu-Moxi and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.
Objectives: Poststroke dysphagia (PSD) is a common complication after stroke but there is limited information on its global prevalence and influencing factors, such as spatial, temporal, demographic characteristics, and stroke-related factors. Our study seeks to fill this knowledge gap by exploring the overall prevalence of PSD and its influencing factors.
Methods: A search of English-language literature from database inception from 2005 until May 2022 was performed using PubMed, Embase, Web of Science, Cochrane Library, and Scopus.
Lancet Reg Health West Pac
January 2025
State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, PR China.
Background: As natural reservoirs of diverse pathogens, small mammals are considered a key interface for guarding public health due to their wide geographic distribution, high density and frequent interaction with humans.
Methods: All formally recorded natural occurrences of small mammals (Order: Rodentia, Eulipotyphla, Lagomorpha, and Scandentia) and their associated microbial infections in China were searched in the English and Chinese literature spanning from 1950 to 2021 and geolocated. Machine learning models were applied to determine ecological drivers for the distributions of 45 major small mammal species and two common rodent-borne diseases (RBDs), and model-predicted potential risk locations were mapped.
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