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 …

At the intersection of machine learning and quantum computing, quantum machine learning
has the potential of accelerating data analysis, especially for quantum data, with …

Practical challenges in simulating quantum systems on classical computers have been
widely recognized in the quantum physics and quantum chemistry communities over the …

One of the most promising suggested applications of quantum computing is solving
classically intractable chemistry problems. This may help to answer unresolved questions …

As we begin to reach the limits of classical computing, quantum computing has emerged as
a technology that has captured the imagination of the scientific world. While for many years …

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 …

The Lie-Trotter formula, together with its higher-order generalizations, provides a direct
approach to decomposing the exponential of a sum of operators. Despite significant effort …

We present the problem of approximating the time-evolution operator $ e^{-i\hat {H} t} $ to
error $\epsilon $, where the Hamiltonian $\hat {H}=(\langle G|\otimes\hat {\mathcal {I}})\hat …

Quantum state preparation is an important subroutine for quantum computing. We show that
any n-qubit quantum state can be prepared with a Θ (n)-depth circuit using only single-and …

An n-qubit quantum circuit performs a unitary operation on an exponentially large, 2 n-
dimensional, Hilbert space, which is a major source of quantum speed-ups. We develop a …