Quantum computers are expected to surpass the computational capabilities of classical
computers and have a transformative impact on numerous industry sectors. We present a …

Quantum generative modeling is a growing area of interest for industry-relevant
applications. This work systematically compares a broad range of techniques to guide …

A bstract In this paper, we introduce a new quantity called SVD entanglement entropy. This
is a generalization of entanglement entropy in that it depends on two different states, as in …

The efficient preparation of quantum states is an important step in the execution of many
quantum algorithms. In the noisy intermediate-scale quantum (NISQ) computing era, this is a …

Loading classical data into quantum computers represents an essential stage in many
relevant quantum algorithms, especially in the field of quantum machine learning. Therefore …

An approximate quantum state preparation method is introduced, called the Walsh series
loader (WSL). The WSL approximates quantum states defined by real-value functions of …

Loading functions into quantum computers represents an essential step in several quantum
algorithms, such as quantum partial differential equation solvers. Therefore, the inefficiency …

We review the state of the art and recent advances in quantum computing applied to
derivative pricing and the computation of risk estimators like Value at Risk. After a brief …

We introduce an quantum-classical hybrid algorithm, named automatic quantum circuit
encoding (AQCE), that is designed to encode an arbitrary quantum state| Ψ〉 onto an …

Loading data efficiently from classical memories to quantum computers is a key challenge of
noisy intermediate-scale quantum computers. Such a problem can be addressed through …