scholarly journals Testing the Quantum Coherent Behavior of Gravity

2018 ◽  
Author(s):  
Sougato Bose
Keyword(s):  
Coherent Behavior

scholarly journals Assessing the quantumness of the annealing dynamics via Leggett Garg’s inequalities: a weak measurement approach

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
V. Vitale ◽  
G. De Filippis ◽  
A. de Candia ◽  
A. Tagliacozzo ◽  
V. Cataudella ◽  
...  
Keyword(s):  
Quantum Computation ◽  
Quantum Computers ◽  
Quantum Annealing ◽  
Adiabatic Quantum Computation ◽  
Universal Quantum ◽  
Full Quantum ◽  
Measurement Approach ◽  
Coherent Behavior ◽  
Sizable Number

Abstract Adiabatic quantum computation (AQC) is a promising counterpart of universal quantum computation, based on the key concept of quantum annealing (QA). QA is claimed to be at the basis of commercial quantum computers and benefits from the fact that the detrimental role of decoherence and dephasing seems to have poor impact on the annealing towards the ground state. While many papers show interesting optimization results with a sizable number of qubits, a clear evidence of a full quantum coherent behavior during the whole annealing procedure is still lacking. In this paper we show that quantum non-demolition (weak) measurements of Leggett Garg inequalities can be used to efficiently assess the quantumness of the QA procedure. Numerical simulations based on a weak coupling Lindblad approach are compared with classical Langevin simulations to support our statements.

COOPERATIVE PHASE DYNAMICS IN COUPLED NEPHRONS

2001 ◽  
Vol 15 (23) ◽  
pp. 3079-3098 ◽  
Author(s):  
D. E. POSTNOV ◽  
O. V. SOSNOVTSEVA ◽  
E. MOSEKILDE ◽  
N.-H. HOLSTEIN-RATHLOU
Keyword(s):  
Chaotic Dynamics ◽  
Phase Synchronization ◽  
Functional Unit ◽  
Flow Regulation ◽  
Tubuloglomerular Feedback ◽  
Phase Dynamics ◽  
The Individual ◽  
Fast Oscillations ◽  
Coherent Behavior ◽  
Different Time Scales

The individual functional unit of the kidney (the nephron) displays oscillations in its pressure and flow regulation at two different time scales: Relatively fast oscillations associated with the myogenic dynamics of the afferent arteriole, and slower oscillations related with a delay in the tubuloglomerular feedback. Neighboring nephrons interact via vascularly propagated signals. We study the appearance of various forms of coherent behavior in a model of two such interacting nephrons. Among the observed phenomena are in-phase and anti-phase synchronization of chaotic dynamics, multistability, and partial phase synchronization in which the nephrons attain a state of chaotic phase synchronization with respect to their slow dynamics, but the fast dynamics remains desynchronized.

scholarly journals Coherent behavior in noncooperative games

1990 ◽  
Vol 50 (2) ◽  
pp. 424-444 ◽  
Author(s):  
Robert F Nau ◽  
Kevin F McCardle
Keyword(s):  
Noncooperative Games ◽  
Coherent Behavior

scholarly journals Finding biologically significant biclusters: a new function for co-expression evaluation

2017 ◽  
Author(s):  
Jorge E. Luna-Taylor ◽  
Carlos A. Brizuela ◽  
Ivan N. Alvarado
Keyword(s):  
Real Data ◽  
Biological Processes ◽  
Experimental Conditions ◽  
Dna Microarray Data ◽  
Biological Interest ◽  
Key Factor ◽  
Coherence Patterns ◽  
Expression Evaluation ◽  
Coherent Behavior

Analysis of DNA microarray data has been very useful for experimental molecular biology, as it provides unprecedented opportunities to study a wide variety of biological processes. As a part of this analysis, biclustering has been consolidated as one of the first steps in the discovery of new knowledge. Biclustering consists in identifying clusters of genes that present coherent behavior patterns for a subset of experimental conditions. The measure to assess this consistency is a key factor in the quality of discovered biclusters. In this paper, we propose a new function (VF) to evaluate the coherence of biclusters. This function recognizes shifting, and positive and negative scaling patterns, more efficiently than well-known reported functions with a similar purpose. Also, the VF function identifies positive and negative scaling subpatterns, which may be of biological interest and have not previously been discussed in the literature. To assess the performance of the VF function, a biclustering genetic algorithm (BGA_VF) was also designed, and tested on both synthetic and real data. The results show that the BGA_VF algorithm obtains high percentages of significant biclusters and recognizes all the analyzed combinations of coherence patterns.

scholarly journals Finding biologically significant biclusters: a new function for co-expression evaluation

2017 ◽  
Author(s):  
Jorge E. Luna-Taylor ◽  
Carlos A. Brizuela ◽  
Ivan N. Alvarado
Keyword(s):  
Real Data ◽  
Biological Processes ◽  
Experimental Conditions ◽  
Dna Microarray Data ◽  
Biological Interest ◽  
Key Factor ◽  
Coherence Patterns ◽  
Expression Evaluation ◽  
Coherent Behavior

Analysis of DNA microarray data has been very useful for experimental molecular biology, as it provides unprecedented opportunities to study a wide variety of biological processes. As a part of this analysis, biclustering has been consolidated as one of the first steps in the discovery of new knowledge. Biclustering consists in identifying clusters of genes that present coherent behavior patterns for a subset of experimental conditions. The measure to assess this consistency is a key factor in the quality of discovered biclusters. In this paper, we propose a new function (VF) to evaluate the coherence of biclusters. This function recognizes shifting, and positive and negative scaling patterns, more efficiently than well-known reported functions with a similar purpose. Also, the VF function identifies positive and negative scaling subpatterns, which may be of biological interest and have not previously been discussed in the literature. To assess the performance of the VF function, a biclustering genetic algorithm (BGA VF) was also designed, and tested on both synthetic and real data. The results show that the BGA VF algorithm obtains high percentages of significant biclusters and recognizes all the analyzed combinations of coherence patterns.

COHERENT BEHAVIOR OF EEC ACTIVITY AND HEART RATE VARIABILITY IN PREMATURE INFANTS

2003 ◽  
Vol 48 (s1) ◽  
pp. 36-37
Author(s):  
K. Pfurtscheller ◽  
G. R. Müller. ◽  
K. Pallasmann ◽  
C. Guger ◽  
G. Pfurtscheller
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Premature Infants ◽  
Coherent Behavior

scholarly journals Detection of Representative Variables in Complex Systems with Interpretable Rules Using Core-Clusters

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 66
Author(s):  
Camille Champion ◽  
Anne-Claire Brunet ◽  
Rémy Burcelin ◽  
Jean-Michel Loubes ◽  
Laurent Risser
Keyword(s):  
Real Data ◽  
High Dimensional ◽  
Robust Detection ◽  
The Core ◽  
Core Cluster ◽  
Minimal Dimension ◽  
Observed Behaviour ◽  
Regularization Strategy ◽  
Coherent Behavior ◽  
New Framework

In this paper, we present a new framework dedicated to the robust detection of representative variables in high dimensional spaces with a potentially limited number of observations. Representative variables are selected by using an original regularization strategy: they are the center of specific variable clusters, denoted CORE-clusters, which respect fully interpretable constraints. Each CORE-cluster indeed contains more than a predefined amount of variables and each pair of its variables has a coherent behavior in the observed data. The key advantage of our regularization strategy is therefore that it only requires to tune two intuitive parameters: the minimal dimension of the CORE-clusters and the minimum level of similarity which gathers their variables. Interpreting the role played by a selected representative variable is additionally obvious as it has a similar observed behaviour as a controlled number of other variables. After introducing and justifying this variable selection formalism, we propose two algorithmic strategies to detect the CORE-clusters, one of them scaling particularly well to high-dimensional data. Results obtained on synthetic as well as real data are finally presented.

Sign in / Sign up

Export Citation Format

Share Document