Results 41 to 50 of about 4,238 (224)
The random Wigner distribution of Gaussian stochastic processes with covariance in S0(ℝ2d)
The paper treats time-frequency analysis of scalar-valued zero mean Gaussian stochastic processes on ℝd. We prove that if the covariance function belongs to the Feichtinger algebra S0(ℝ2d) then: (i) the Wigner distribution and the ambiguity function of ...
Patrik Wahlberg
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Probability Distributions Describing Qubit-State Superpositions
We discuss qubit-state superpositions in the probability representation of quantum mechanics. We study probability distributions describing separable qubit states.
Margarita A. Man’ko +1 more
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This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu +5 more
wiley +1 more source
We present a new experimental approach to determine the Wigner distribution function of non-separable laser beams. A rotatable toroidal mirror is employed to focus an IR laser beam at a wavelength of $1064\;{\rm nm}$ .
Tobias Mey, Bernd Schäfer, Klaus Mann
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Personal identification based on radar gait measurement is an important application of biometric technology because it enables remote and continuous identification of people, irrespective of the lighting conditions and subjects’ outfits.
Keitaro Shioiri, Kenshi Saho
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The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches
Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Bidhan Chandra Garain +3 more
wiley +1 more source
Noised Phase Unwrapping Based on the Adaptive Window of Wigner Distribution
A noised phase-unwrapping method is presented by using the Wigner distribution function to filter the phase noise and restore the gradient of the phase map. By using Poisson’s equation, the unwrapped phase map was obtained.
Junqiu Chu +4 more
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Molecular design reshapes the landscape of excited‐state relaxation. Nonadiabatic dynamics reveal how electronic structure guides population flow between competing pathways beyond static energetic arguments. ABSTRACT Nitrobenzochalcogenadiazole derivatives are emerging candidates for photodynamic therapy (PDT), yet the precise mechanisms governing ...
Vinícius N. da Rocha +2 more
wiley +1 more source
The quaternion Wigner-Ville distribution associated with linear canonical transform (QWVD-LCT) is a nontrivial generalization of the quaternion Wigner-Ville distribution to the linear canonical transform (LCT) domain. In the present paper, we establish a
Mawardi Bahri, Muh. Saleh Arif Fatimah
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