Pennylane: Automatic differentiation of hybrid quantum-classical computations
PennyLane is a Python 3 software framework for differentiable programming of quantum
computers. The library provides a unified architecture for near-term quantum computing …
computers. The library provides a unified architecture for near-term quantum computing …
Recent progress in the JARVIS infrastructure for next-generation data-driven materials design
The joint automated repository for various integrated simulations (JARVIS) infrastructure at
the National Institute of Standards and Technology is a large-scale collection of curated …
the National Institute of Standards and Technology is a large-scale collection of curated …
A perspective on sustainable computational chemistry software development and integration
The power of quantum chemistry to predict the ground and excited state properties of
complex chemical systems has driven the development of computational quantum chemistry …
complex chemical systems has driven the development of computational quantum chemistry …
Universal quantum circuits for quantum chemistry
Universal gate sets for quantum computing have been known for decades, yet no universal
gate set has been proposed for particle-conserving unitaries, which are the operations of …
gate set has been proposed for particle-conserving unitaries, which are the operations of …
Supercomputing leverages quantum machine learning and Grover's algorithm
The complexity of searching algorithms in classical computing is a classic problem and a
research area. Quantum computers and quantum algorithms can efficiently compute some …
research area. Quantum computers and quantum algorithms can efficiently compute some …
Differentiable quantum chemistry with PySCF for molecules and materials at the mean-field level and beyond
We introduce an extension to the PYSCF package, which makes it automatically
differentiable. The implementation strategy is discussed, and example applications are …
differentiable. The implementation strategy is discussed, and example applications are …
JARVIS-Leaderboard: a large scale benchmark of materials design methods
Lack of rigorous reproducibility and validation are significant hurdles for scientific
development across many fields. Materials science, in particular, encompasses a variety of …
development across many fields. Materials science, in particular, encompasses a variety of …
Prediction of the neutron drip line in oxygen isotopes using quantum computation
In the noisy intermediate-scale quantum era, variational algorithms have become a standard
approach to solving quantum many-body problems. Here, we present variational quantum …
approach to solving quantum many-body problems. Here, we present variational quantum …
Finite-volume pionless effective field theory for few-nucleon systems with differentiable programming
Finite-volume pionless effective field theory provides an efficient framework for the
extrapolation of nuclear spectra and matrix elements calculated at finite volume in lattice …
extrapolation of nuclear spectra and matrix elements calculated at finite volume in lattice …
Generating approximate ground states of molecules using quantum machine learning
The potential energy surface (PES) of molecules with respect to their nuclear positions is a
primary tool in understanding chemical reactions from first principles. However, obtaining …
primary tool in understanding chemical reactions from first principles. However, obtaining …