Classical quantum emulators are key tools for algorithm design, error correction, and noise mitigation. They rely on a variety of simulation methods such as statevector, tensor networks, matrix product states, decision diagrams and others. Their performance depends not only on…
Classical simulation of molecular systems is limited by exponential scaling, a hurdle quantum algorithms like Variational Quantum Eigensolvers (VQEs) aim to overcome. Although ADAPT-VQE enhances VQEs by dynamically building ansätze, it can remain computationally intensive. This work presents K-ADAPT-VQE, which…
Evaluating quantum algorithms at utility-scale—involving more than 100 qubits—is a key step toward advancing real-world applications of quantum computing. In this study, we benchmark seven state-of-the-art quantum emulators employing techniques such as tensor networks, matrix product states (MPS), decision diagrams,…
The dynamics of many-body quantum states in open systems is commonly numerically simulated by unraveling the density matrix into pure-state trajectories. In this work, we introduce a new unraveling strategy that can adaptively minimize the averaged entanglement in the trajectory…
A key requirement for quantum technologies based on atoms, ions, and molecules is the ability to realize precise phase- and amplitude-controlled quantum operations via coherent laser pulses. However, for generating pulses on the submicrosecond timescale, the characteristics of the optical…