Maximum Information and Quantum Prediction Algorithms
نویسنده
چکیده
This paper describes an algorithm for selecting a consistent set within the consistent histories approach to quantum mechanics and investigates its properties. The algorithm uses a maximum information principle to select from among the consistent sets formed by projections defined by the Schmidt decomposition. The algorithm unconditionally predicts the possible events in closed quantum systems and ascribes probabilities to these events. A simple spin model is described and a complete classification of all exactly consistent sets of histories formed from Schmidt projections in the model is proved. This result is used to show that for this example the algorithm selects a physically realistic set. Other tentative suggestions in the literature for set selection algorithms using ideas from information theory are discussed. Typeset using REVTEX ∗E-mail:[email protected] 1
منابع مشابه
Estimation of LPC coefficients using Evolutionary Algorithms
The vast use of Linear Prediction Coefficients (LPC) in speech processing systems has intensified the importance of their accurate computation. This paper is concerned with computing LPC coefficients using evolutionary algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Dif-ferential Evolution (DE) and Particle Swarm Optimization with Differentially perturbed Velocity (PSO-DV...
متن کاملPrediction of daily precipitation of Sardasht Station using lazy algorithms and tree models
Due to the heterogeneous distribution of precipitation, predicting its occurrence is one of the primary and basic solutions to prevent possible disasters and damages caused by them. Considering the high amount of precipitation in Sardasht County, the people of this city turning to agriculture in recent years and not using classification models in the studied station, it is necessary to predict ...
متن کاملEarly Prediction of Gestational Diabetes Using Decision Tree and Artificial Neural Network Algorithms
Introduction: Gestational diabetes is associated with many short-term and long-term complications in mothers and newborns; hence, the detection of its risk factors can contribute to the timely diagnosis and prevention of relevant complications. The present study aimed to design and compare Gestational diabetes mellitus (GDM) prediction models using artificial intelligence algorithms. Materials ...
متن کاملFemtosecond quantum control studies on vibrational quantum information processing
The role of phases and their interplay in molecular vibrational quantum computing with multiple qubits Chirp-driven vibrational distribution in transition metal carbonyl complexes Phys. Robustness of quantum gates operating on the high frequency modes of MnBr(CO) 5 Comment on " Anharmonic properties of the vibrational quantum computer " [J. Monotonic convergent optimal control theory with stric...
متن کاملPersonal Credit Score Prediction using Data Mining Algorithms (Case Study: Bank Customers)
Knowledge and information extraction from data is an age-old concept in scientific studies. In industrial decision-making processes, the application of this concept gives rise to data-mining opportunities. Personal credit scoring is an ever-vital tool for banking systems in order to manage and minimize the inherent risks of the financial sector, thus, the design and improvement of credit scorin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1996