scholarly journals Validation of entanglement purification by continuous variable polarization

2004 ◽  
Vol 6 (6) ◽  
pp. S473-S477 ◽  
Author(s):  
Francesca Alessandrini ◽  
Stefano Mancini ◽  
Paolo Tombesi
Keyword(s):  
Continuous Variable ◽  
Entanglement Purification

scholarly journals Continuous-variable entanglement purification with atomic systems

2010 ◽  
Vol 27 (6) ◽  
pp. A198 ◽  
Author(s):  
Stojan Rebic ◽  
Stefano Mancini ◽  
Giovanna Morigi ◽  
David Vitali
Keyword(s):  
Continuous Variable ◽  
Entanglement Purification ◽  
Atomic Systems

Continuous variable entanglement purification and its physical implementation

2000 ◽  
Vol 47 (14-15) ◽  
pp. 2529-2542 ◽  
Author(s):  
Lu-Ming Duan ◽  
G. Giedke ◽  
J. I. Cirac ◽  
P. Zoller
Keyword(s):  
Continuous Variable ◽  
Entanglement Purification ◽  
Physical Implementation

scholarly journals Photonic hybrid state entanglement swapping using cat state superpositions

2020 ◽  
Vol 476 (2243) ◽  
pp. 20200237
Author(s):  
Ryan C. Parker ◽  
Jaewoo Joo ◽  
Timothy P. Spiller
Keyword(s):  
Success Probability ◽  
Bell State ◽  
Continuous Variable ◽  
Entanglement Swapping ◽  
Entangled State ◽  
Entanglement Purification ◽  
Hybrid State ◽  
Fock State ◽  
Purification Scheme ◽  
Low Levels

We propose the use of hybrid entanglement in an entanglement swapping protocol, as means of distributing a Bell state with high fidelity to two parties. The hybrid entanglement used in this work is described as a discrete variable (Fock state) and a continuous variable (cat state super- position) entangled state. We model equal and unequal levels of photonic loss between the two propagating continuous variable modes, before detecting these states via a projective vacuum-one-photon measurement, and the other mode via balanced homodyne detection. We investigate homodyne measurement imperfections, and the associated success probability of the measurement schemes chosen in this protocol. We show that our entanglement swapping scheme is resilient to low levels of photonic losses, as well as low levels of averaged unequal losses between the two propagating modes, and show an improvement in this loss resilience over other hybrid entanglement schemes using coherent state superpositions as the propagating modes. Finally, we conclude that our protocol is suitable for potential quantum networking applications which require two nodes to share entanglement separated over a distance of 5 -- 10   km , when used with a suitable entanglement purification scheme.

scholarly journals Entanglement Purification of Gaussian Continuous Variable Quantum States

2000 ◽  
Vol 84 (17) ◽  
pp. 4002-4005 ◽  
Author(s):  
Lu-Ming Duan ◽  
G. Giedke ◽  
J. I. Cirac ◽  
P. Zoller
Keyword(s):  
Continuous Variable ◽  
Quantum States ◽  
Entanglement Purification

Constructing and model-fitting receiver operator characteristics using continuous data.

2018 ◽  
Author(s):  
Josephine Ann Urquhart ◽  
Akira O'Connor
Keyword(s):  
Signal Detection ◽  
Least Squares Method ◽  
Model Fitting ◽  
Simulated Data ◽  
Continuous Variable ◽  
Continuous Data ◽  
Model Parameters ◽  
Operating Characteristics ◽  
Unequal Variance ◽  
Discrete Discrimination

Receiver operating characteristics (ROCs) are plots which provide a visual summary of a classifier’s decision response accuracy at varying discrimination thresholds. Typical practice, particularly within psychological studies, involves plotting an ROC from a limited number of discrete thresholds before fitting signal detection parameters to the plot. We propose that additional insight into decision-making could be gained through increasing ROC resolution, using trial-by-trial measurements derived from a continuous variable, in place of discrete discrimination thresholds. Such continuous ROCs are not yet routinely used in behavioural research, which we attribute to issues of practicality (i.e. the difficulty of applying standard ROC model-fitting methodologies to continuous data). Consequently, the purpose of the current article is to provide a documented method of fitting signal detection parameters to continuous ROCs. This method reliably produces model fits equivalent to the unequal variance least squares method of model-fitting (Yonelinas et al., 1998), irrespective of the number of data points used in ROC construction. We present the suggested method in three main stages: I) building continuous ROCs, II) model-fitting to continuous ROCs and III) extracting model parameters from continuous ROCs. Throughout the article, procedures are demonstrated in Microsoft Excel, using an example continuous variable: reaction time, taken from a single-item recognition memory. Supplementary MATLAB code used for automating our procedures is also presented in Appendix B, with a validation of the procedure using simulated data shown in Appendix C.

Prediction of Haemoglobin Level by Some Probability Distribution

2020 ◽  
Vol 9 (1) ◽  
pp. 84-88
Author(s):  
Govinda Prasad Dhungana ◽  
Laxmi Prasad Sapkota
Keyword(s):  
Probability Distribution ◽  
Normal Distribution ◽  
Goodness Of Fit ◽  
Continuous Variable ◽  
Hemoglobin Level ◽  
Chi Square ◽  
Chi Square Test ◽  
Log Normal ◽  
Two Parameters ◽  
Best Fit

 Hemoglobin level is a continuous variable. So, it follows some theoretical probability distribution Normal, Log-normal, Gamma and Weibull distribution having two parameters. There is low variation in observed and expected frequency of Normal distribution in bar diagram. Similarly, calculated value of chi-square test (goodness of fit) is observed which is lower in Normal distribution. Furthermore, plot of PDFof Normal distribution covers larger area of histogram than all of other distribution. Hence Normal distribution is the best fit to predict the hemoglobin level in future.

scholarly journals Aortic Valve Calcification is Associated with Future Cognitive Impairment

2021 ◽  
pp. 1-7
Author(s):  
Hojune E. Chung ◽  
Jessica Chen ◽  
Dhairyasheel Ghosalkar ◽  
Jared L. Christensen ◽  
Alice J. Chu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Aortic Valve ◽  
Lung Cancer Screening ◽  
Continuous Variable ◽  
Smoking History ◽  
Event Analysis ◽  
Aortic Valve Calcification ◽  
Valve Calcification ◽  
Ckd Stage ◽  
New Diagnosis

Background: While an association between atherosclerosis and dementia has been identified, few studies have assessed the longitudinal relationship between aortic valve calcification (AVC) and cognitive impairment (CI). Objective: We sought to determine whether AVC derived from lung cancer screening CT (LCSCT) was associated with CI in a moderate-to-high atherosclerotic risk cohort. Methods: This was a single site, retrospective analysis of 1401 U.S. veterans (65 years [IQI: 61, 68] years; 97%male) who underwent quantification of AVC from LCSCT indicated for smoking history. The primary outcome was new diagnosis of CI identified by objective testing (Mini-Mental Status Exam or Montreal Cognitive Assessment) or by ICD coding. Time-to-event analysis was carried out using AVC as a continuous variable. Results: Over 5 years, 110 patients (8%) were diagnosed with CI. AVC was associated with new diagnosis of CI using 3 Models for adjustment: 1) age (HR: 1.104; CI: 1.023–1.191; p = 0.011); 2) Model 1 plus hypertension, hyperlipidemia, diabetes, CKD stage 3 or higher (glomerular filtration rate <  60 mL/min) and CAD (HR: 1.097; CI: 1.014–1.186; p = 0.020); and 3) Model 2 plus CVA (HR: 1.094; CI: 1.011–1.182; p = 0.024). Sensitivity analysis demonstrated that the association between AVC and new diagnosis of CI remained significant upon exclusion of severe AVC (HR: 1.100 [1.013–1.194]; p = 0.023). Subgroup analysis demonstrated that this association remained significant when including education in the multivariate analysis (HR: 1.127 [1.030–1.233]; p = 0.009). Conclusion: This is the first study demonstrating that among mostly male individuals who underwent LCSCT, quantified aortic valve calcification is associated with new diagnosis of CI.

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