5 papers
Quantum-Enhanced Neural Exchange-Correlation Functionals
Igor O. Sokolov, Gert-Jan Both, Art D. Bochevarov +6
Kohn-Sham Density Functional Theory (KS-DFT) provides the exact ground state energy and electron density of a molecule, contingent on the as-yet-unknown universal exchange-correlat…
Experimental differentiation and extremization with analog quantum circuits
Evan Philip, Julius de Hond, Vytautas Abramavicius +8
Solving and optimizing differential equations (DEs) is ubiquitous in both engineering and fundamental science. The promise of quantum architectures to accelerate scientific computi…
Evaluation of derivatives using approximate generalized parameter shift rule
Vytautas Abramavicius, Evan Philip, Kaonan Micadei +5
Parameter shift rules are instrumental for derivatives estimation in a wide range of quantum algorithms, especially in the context of Quantum Machine Learning. Application of singl…
PulserDiff: a pulse differentiable extension for Pulser
Vytautas Abramavicius, Melvin Mathé, Gergana V. Velikova +6
Programming analog quantum processing units (QPUs), such as those produced by Pasqal, can be achieved using specialized low-level pulse libraries like Pulser. However, few currentl…
What can we learn from quantum convolutional neural networks?
Chukwudubem Umeano, Annie E. Paine, Vincent E. Elfving +1
Quantum machine learning (QML) shows promise for analyzing quantum data. A notable example is the use of quantum convolutional neural networks (QCNNs), implemented as specific type…