Advances in isolating, controlling and entangling quantum systems are transforming what
was once a curious feature of quantum mechanics into a vehicle for disruptive scientific and …

Digital quantum computers provide a computational framework for solving the Schrödinger
equation for a variety of many‐particle systems. Quantum computing algorithms for the …

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 …

Under suitable assumptions, the quantum-phase-estimation (QPE) algorithm is able to
achieve Heisenberg-limited precision scaling in estimating the ground-state energy …

Achieving near-term quantum advantage will require accurate estimation of quantum
observables despite significant hardware noise. For this purpose, we propose a novel …

We introduce a multireference selected quantum Krylov (MRSQK) algorithm suitable for
quantum simulation of many-body problems. MRSQK is a low-cost alternative to the …

Phase estimation is a quantum algorithm for measuring the eigenvalues of a Hamiltonian.
We propose and rigorously analyze a randomized phase estimation algorithm with two …

Quantum Krylov subspace diagonalization (QKSD) algorithms provide a low-cost alternative
to the conventional quantum phase estimation algorithm for estimating the ground-and …

Trotterization-based, iterative approaches to quantum simulation (QS) are restricted to
simulation times less than the coherence time of the quantum computer (QC), which limits …

We propose a quantum-classical hybrid algorithm of the power method, here dubbed as the
quantum power method, to evaluate H^ n| ψ⟩ with quantum computers, where n is a non …