The future development of quantum technologies relies on creating and manipulating
quantum systems of increasing complexity, with key applications in computation, simulation …

In recent years the dramatic progress in machine learning has begun to impact many areas
of science and technology significantly. In the present perspective article, we explore how …

To explore the possibilities of a near-term intermediate-scale quantum algorithm and long-
term fault-tolerant quantum computing, a fast and versatile quantum circuit simulator is …

Advances and New Research Opportunities in Quantum Computing Technology by Integrating it
with Other ICCT Underlying Technologie Page 1 1 Advances and New Research Opportunities …

Variational quantum algorithms are currently the most promising class of algorithms for
deployment on near-term quantum computers. In contrast to classical algorithms, there are …

We develop computationally affordable and encoding independent gradient evaluation
procedures for unitary coupled-cluster type operators, applicable on quantum computers …

Quantum machine learning, which involves running machine learning algorithms on
quantum devices, has garnered significant attention in both academic and business circles …

Due to the limitations of present-day quantum hardware, it is especially critical to design
algorithms that make the best possible use of available resources. When simulating …

Science is rich in abstract concepts that capture complex processes in astonishingly simple
ways. A prominent example is the reduction of molecules to simple graphs. This work …

Natural evolutionary strategies (NES) are a family of gradient-free black-box optimization
algorithms. This study illustrates their use for the optimization of randomly initialized …