We propose a novel clustering method that is an extension of ideas inherent to scale-space clustering and support-vector clustering. Like the latter, it associates every data poin...
—Continuum quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles. By solving the manybody Schr¨odinge...
Kenneth Esler, Jeongnim Kim, David M. Ceperley, Lu...
Quantum computer programming is emerging as a new subject domain from multidisciplinary research in quantum computing, computer science, mathematics (especially quantum logic, lamb...
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
We present the SQRAM architecture for quantum computing, which is based on Knill’s QRAM model. We detail a suitable instruction set, which implements a universal set of quantum ...
Rajagopal Nagarajan, Nikolaos Papanikolaou, David ...