In quantum state filtering one wants to determine whether an unknown quantum state, which is chosen from a known set of states, [|psi(1)>, em leader,|psi(N)>], is either a specific state, say |psi(1)>, or one of the remaining states, [|psi(2)>, em leader,|psi(N)>]. We present the optimal solution to this problem, in terms of generalized measurements, for the case that the filtering is required to be unambiguous. As an application, we propose an efficient, probabilistic quantum algorithm for distinguishing between sets of Boolean functions, which is a generalization of the Deutsch-Jozsa algorithm.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1103/PhysRevLett.90.257901 | DOI Listing |
PNAS Nexus
January 2025
Biocomplexity Institute, University of Virginia, Charlottesville, VA, USA.
This paper describes Epihiper, a state-of-the-art, high performance computational modeling framework for epidemic science. The Epihiper modeling framework supports custom disease models, and can simulate epidemics over dynamic, large-scale networks while supporting modulation of the epidemic evolution through a set of user-programmable interventions. The nodes and edges of the social-contact network have customizable sets of static and dynamic attributes which allow the user to specify intervention target sets at a very fine-grained level; these also permit the network to be updated in response to nonpharmaceutical interventions, such as school closures.
View Article and Find Full Text PDFNucleic Acids Res
December 2024
School of Computer Science and Cyber Engineering, GuangZhou University, 230 Wai Huan Xi Road, Guangzhou Higher Education Mega Center, Guangzhou, 510006, China.
DNA nanotechnology has created a wide variety of nanostructures that provide a reliable platform for nanofabrication and DNA computing. However, constructing programmable finite arrays that allow for easy pre-functionalization remains challenge. We aim to create more standardized and controllable DNA origami components, which could be assembled into finite-scale and more diverse superstructures driven by instruction sets.
View Article and Find Full Text PDFLife (Basel)
October 2024
Institute of Biochemistry and Biophysics, Polish Academy of Sciences, 02-106 Warszawa, Poland.
This study showed that the predictor in logistic regression can be applied to estimating the Gibbs free energy of tRNAs' recognition of and binding to their aminoacyl-tRNA synthetases. Then, 24 linear logistic regression models predicting different classes of tRNAs loaded with a corresponding amino acid were trained in a machine learning classification method, reducing the misclassification error to zero. The models were based on minimal subsets of Boolean explanatory variables describing the favorite presence of nucleotides or nucleosides localized in the different parts of the tRNA.
View Article and Find Full Text PDFCell
September 2024
Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Medicine and School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; School of Engineering, Westlake University, Hangzhou, Zhejiang 310030, China. Electronic address:
Math Biosci
August 2024
Montana State University, Bozeman, 59717, MT, USA. Electronic address:
We consider two types of models of regulatory network dynamics: Boolean maps and systems of switching ordinary differential equations. Our goal is to construct all models in each category that are compatible with the directed signed graph that describe the network interactions. This leads to consideration of lattice of monotone Boolean functions (MBF), poset of non-degenerate MBFs, and a lattice of chains in these sets.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!