The development of quantum computing across several technologies and platforms has
reached the point of having an advantage over classical computers for an artificial problem …

It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the
US decadal particle-physics community planning, and in fact until recently, this was not …

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

Neuromorphic computing uses brain-inspired principles to design circuits that can perform
computational tasks with superior power efficiency to conventional computers. Approaches …

Interacting many-electron problems pose some of the greatest computational challenges in
science, with essential applications across many fields. The solutions to these problems will …

Key static and dynamic properties of matter—from creation in the Big Bang to evolution into
subatomic and astrophysical environments—arise from the underlying fundamental …

The electronic Schrödinger equation can only be solved analytically for the hydrogen atom,
and the numerically exact full configuration-interaction method is exponentially expensive in …

Given access to accurate solutions of the many-electron Schrödinger equation, nearly all
chemistry could be derived from first principles. Exact wave functions of interesting chemical …

Non-Abelian gauge theories underlie our understanding of fundamental forces in nature,
and developing tailored quantum hardware and algorithms to simulate them is an …

Quantum annealing is a computing paradigm that has the ambitious goal of efficiently
solving large-scale combinatorial optimization problems of practical importance. However …