Under suitable assumptions, some recently developed quantum algorithms can estimate the
ground-state energy and prepare the ground state of a quantum Hamiltonian with near …

We develop a phase-estimation method with a distinct feature: its maximal run time (which
determines the circuit depth) is δ/ϵ, where ϵ is the target precision, and the preconstant δ …

A milestone in the field of quantum computing will be solving problems in quantum chemistry
and materials faster than state-of-the-art classical methods. The current understanding is …

In recent years, research in quantum computing has largely focused on two approaches:
near-term intermediate-scale quantum (NISQ) computing and future fault-tolerant quantum …

Quantum phase estimation is one of the critical building blocks of quantum computing. For
early fault-tolerant quantum devices, it is desirable for a quantum phase estimation algorithm …

Predicting observables in equilibrium states is a central yet notoriously hard question in
quantum many-body systems. In the physically relevant thermodynamic limit, certain …

We develop three new methods to implement any Linear Combination of Unitaries (LCU), a
powerful quantum algorithmic tool with diverse applications. While the standard LCU …

Quantum computing is believed to be particularly useful for the simulation of chemistry and
materials, among the various applications. In recent years, there have been significant …

We propose a class of randomized quantum algorithms for the task of sampling from matrix
functions, without the use of quantum block encodings or any other coherent oracle access …

Topological invariants of a dataset, such as the number of holes that survive from one length
scale to another (persistent Betti numbers) can be used to analyse and classify data in …