Variational quantum circuit are among the most promising methods for dealing with optimization problems, combinatorial optimization and quantum machine learning. However, despite their popularity, many of the ansatze upon which such circuit relies su...
Linear systems of equations lie at the heart of many scientific and engineering problems, from machine learning to optimization and physics simulations. Classical methods like Gaussian elimination or iterative methods are powerful but can be ineffici...
Variational Quantum Algorithms (VQAs) are regarded as one of the most promising approaches for leveraging near-term quantum devices as they combine the power of quantum circuits with classical optimization to solve problems in chemistry, material sci...
Quantum Boltzmann Machines (QBMs) are at the cutting edge of quantum machine learning, offering a novel extension of classical Boltzmann machines through the lens of quantum mechanics. These models take advantage of quantum principles to push the bou...
In the landscape of technological innovation, two disruptive forces stand out: quantum computing and blockchain. While each has made significant strides independently, their convergence holds the promise of revolutionizing cryptography and reshaping ...
