A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

Applications such as simulating complicated quantum systems or solving large-scale linear
algebra problems are very challenging for classical computers, owing to the extremely high …

We propose a quantum algorithm to solve systems of nonlinear differential equations. Using
a quantum feature map encoding, we define functions as expectation values of parametrized …

We show that nonlinear problems including nonlinear partial differential equations can be
efficiently solved by variational quantum computing. We achieve this by utilizing multiple …

Conspectus Simulating molecular dynamics (MD) within a comprehensive quantum
framework has been a long-standing challenge in computational chemistry. An exponential …

Quantum computing is a game-changing technology for global academia, research centers
and industries including computational science, mathematics, finance, pharmaceutical …

Variational algorithms are a promising paradigm for utilizing near-term quantum devices for
modeling electronic states of molecular systems. However, previous bounds on the …

Quantum neural networks (QNNs) offer a powerful paradigm for programming near-term
quantum computers and have the potential to speed up applications ranging from data …

DIRAC is a freely distributed general-purpose program system for one-, two-, and four-
component relativistic molecular calculations at the level of Hartree–Fock, Kohn–Sham …

The promised industrial applications of quantum computers often rest on their anticipated
ability to perform accurate, efficient quantum chemical calculations. Computational drug …