The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

The theory of entanglement provides a fundamentally new language for describing
interactions and correlations in many-body systems. Its vocabulary consists of qubits and …

Realizing quantum speedup for practically relevant, computationally hard problems is a
central challenge in quantum information science. Using Rydberg atom arrays with up to …

Quantum spin liquids, exotic phases of matter with topological order, have been a major
focus in physics for the past several decades. Such phases feature long-range quantum …

Motivated by far-reaching applications ranging from quantum simulations of complex
processes in physics and chemistry to quantum information processing, a broad effort is …

The developments of the open-source OpenMolcas chemistry software environment since
spring 2020 are described, with a focus on novel functionalities accessible in the stable …

Quantum simulation has emerged as a valuable arena for demonstrating and understanding
the capabilities of near-term quantum computers,–. Quantum annealing, has been …

Classical machine learning (ML) provides a potentially powerful approach to solving
challenging quantum many-body problems in physics and chemistry. However, the …

We study the performance of classical and quantum machine learning (ML) models in
predicting outcomes of physical experiments. The experiments depend on an input …

In this Article we describe the OpenMolcas environment and invite the computational
chemistry community to collaborate. The open-source project already includes a large …