Complex Scaling Methods for the Study of Light Unstable Nuclei

2000 ◽  
pp. 118-124 ◽  
Author(s):  
K. Katō ◽  
S. Aoyama ◽  
T. Myo ◽  
H. Masui ◽  
T. Yamada ◽  
...  
Keyword(s):  
Complex Scaling ◽  
Unstable Nuclei ◽  
Scaling Methods

scholarly journals Complex scaling: Physics of unbound light nuclei and perspective

2020 ◽  
Vol 2020 (12) ◽  
Author(s):  
Takayuki Myo ◽  
Kiyoshi Katō
Keyword(s):  
Level Density ◽  
Scattering Problem ◽  
Light Nuclei ◽  
Transition Strength ◽  
Complex Scaling ◽  
Many Body ◽  
Complex Scaling Method ◽  
Continuum States ◽  
Unstable Nuclei ◽  
Strength Functions

Abstract The complex scaling method (CSM) is one of the most powerful methods of describing the resonances with complex energy eigenstates based on non-Hermitian quantum mechanics. We present the basic application of CSM to the properties of the unbound phenomena of light nuclei. In particular, we focus on many-body resonant and non-resonant continuum states observed in unstable nuclei. We also investigate the continuum level density (CLD) in the scattering problem in terms of the Green’s function with CSM. We discuss the explicit effects of resonant and non-resonant contributions in CLD and transition strength functions.

scholarly journals Hybrid method (JM-ECS) combining theJ-matrix and exterior complex scaling methods for scattering calculations

2010 ◽  
Vol 82 (6) ◽  
Author(s):  
Y. Bidasyuk ◽  
W. Vanroose ◽  
J. Broeckhove ◽  
F. Arickx ◽  
V. Vasilevsky
Keyword(s):  
Hybrid Method ◽  
Complex Scaling ◽  
Scaling Methods ◽  
Exterior Complex Scaling

Magnitude Estimation and Cross-Modal Matching of Lingual Vibrotactile and Auditory Sensation

1989 ◽  
Vol 32 (3) ◽  
pp. 698-702 ◽  
Author(s):  
Daniel Harris ◽  
Donald Fucci ◽  
Linda Petrosino
Keyword(s):  
Auditory Stimulus ◽  
Magnitude Estimation ◽  
Sensory Processing ◽  
Test Site ◽  
Systematic Investigation ◽  
Thenar Eminence ◽  
Stimulus Range ◽  
Psychophysical Scaling ◽  
Scaling Methods ◽  
Response Biases

The present experiment was a preliminary attempt to use the psychophysical scaling methods of magnitude estimation and cross-modal matching to investigate suprathreshold judgments of lingual vibrotactile and auditory sensation magnitudes for 20 normal young adult subjects. A 250-Hz lingual vibrotactile stimulus and a 1000-Hz binaural auditory stimulus were employed. To obtain judgments for nonoral vibrotactile sensory magnitudes, the thenar eminence of the hand was also employed as a test site for 5 additional subjects. Eight stimulus intensities were presented during all experimental tasks. The results showed that the slopes of the log-log vibrotactile magnitude estimation functions decreased at higher stimulus intensity levels for both test sites. Auditory magnitude estimation functions were relatively constant throughout the stimulus range. Cross-modal matching functions for the two stimuli generally agreed with functions predicted from the magnitude estimation data, except when subjects adjusted vibration on the tongue to match auditory stimulus intensities. The results suggested that the methods of magnitude estimation and cross-modal matching may be useful for studying sensory processing in the speech production system. However, systematic investigation of response biases associated with vibrotactile-auditory psychophysical scaling tasks appears to be a prerequisite.

Optical pumping and unstable nuclei

1985 ◽  
Vol 10 (6) ◽  
pp. 659-674 ◽  
Author(s):  
E.W. Otten
Keyword(s):  
Optical Pumping ◽  
Unstable Nuclei

A Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Ligand-Target Predictions

2020 ◽  
Author(s):  
Lewis Mervin ◽  
Avid M. Afzal ◽  
Ola Engkvist ◽  
Andreas Bender
Keyword(s):  
Target Prediction ◽  
Support Vector ◽  
Machine Learning Method ◽  
Learning Method ◽  
Protein Target ◽  
Bioactivity Prediction ◽  
Vector Machines ◽  
Scaling Methods ◽  
Data Points ◽  
Compound Target

In the context of bioactivity prediction, the question of how to calibrate a score produced by a machine learning method into reliable probability of binding to a protein target is not yet satisfactorily addressed. In this study, we compared the performance of three such methods, namely Platt Scaling, Isotonic Regression and Venn-ABERS in calibrating prediction scores for ligand-target prediction comprising the Naïve Bayes, Support Vector Machines and Random Forest algorithms with bioactivity data available at AstraZeneca (40 million data points (compound-target pairs) across 2112 targets). Performance was assessed using Stratified Shuffle Split (SSS) and Leave 20% of Scaffolds Out (L20SO) validation.

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