Results 41 to 50 of about 199,961 (218)

Efficient Implementation of Randomized Quantum Algorithms With Dynamic Circuits

open access: yesIEEE Transactions on Quantum Engineering
Randomized algorithms are crucial subroutines in quantum computing, but the requirement to execute many types of circuits on a real quantum device has been challenging to their extensive implementation.
Shu Kanno   +4 more
doaj   +1 more source

Successive randomized compression: A randomized algorithm for the compressed MPO-MPS product [PDF]

open access: yesQuantum
Tensor networks like matrix product states (MPSs) and matrix product operators (MPOs) are powerful tools for representing exponentially large states and operators, with applications in quantum many-body physics, machine learning, numerical analysis, and ...
Chris Camaño   +2 more
doaj   +1 more source

Quantum online algorithms for a model of the request-answer game with a buffer

open access: yesУчёные записки Казанского университета: Серия Физико-математические науки, 2020
In this paper, we considered online algorithms as a request-answer game between two players: an adversary that generates input requests and an online algorithm that answers them.
K.R. Khadiev, D.I. Lin
doaj   +1 more source

p190A/ARHGAP35 and p190B/ARHGAP5 proteins in endometrial cancer: a novel cancer‐relevant paralog interplay

open access: yesMolecular Oncology, EarlyView.
This study identifies ARHGAP5, in addition to the frequently mutated ARHGAP35, as significantly mutated in endometrial cancer. Mutations in both genes co‐occur and are associated with their correlated downregulation. Functional CRISPR studies show that both paralogs regulate similar pathways, including actin cytoskeleton organization.
Mathilde Pinault   +12 more
wiley   +1 more source

Privacy-aware EV charging-station assignment: QoS–fairness optimization with traffic-analysis resistance [PDF]

open access: yesPeerJ Computer Science
The assignment of charging stations (CS) within urban electric vehicle (EV) networks necessitated a careful equilibrium among user quality of service (QoS), equitable station load distribution, and the mitigation of traffic-analysis inference from ...
Akram Y. Sarhan   +3 more
doaj   +2 more sources

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

open access: yesFEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill   +4 more
wiley   +1 more source

Streaming Histogram Publication over Weighted Sliding Windows Under Differential Privacy

open access: yesTsinghua Science and Technology
Continuously publishing histograms in data streams is crucial to many real-time applications, as it provides not only critical statistical information, but also reduces privacy leaking risk.
Xiujun Wang   +3 more
doaj   +1 more source

Leveraging randomized compiling for the quantum imaginary-time-evolution algorithm

open access: yesPhysical Review Research, 2022
Recent progress in noisy intermediate-scale quantum (NISQ) hardware shows that quantum devices may be able to tackle complex problems even without error correction.
Jean-Loup Ville   +15 more
doaj   +1 more source

Refinement of amino‐acid conformation vs. difference density maps in time‐resolved serial femtosecond crystallography data analysis

open access: yesFEBS Open Bio, EarlyView.
The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong   +3 more
wiley   +1 more source

A randomized block Krylov method for tensor train approximation

open access: yesFrontiers in Applied Mathematics and Statistics
Tensor train decomposition is a powerful tool to tackle high-dimensional large-scale tensor data and is not suffering from the curse of dimensionality. It relies on performing the singular value decomposition (SVD) of auxiliary unfolding matrices.
Gaohang Yu   +4 more
doaj   +1 more source

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