For quantum computers to successfully solve real-world problems, it is necessary to tackle
the challenge of noise: the errors that occur in elementary physical components due to …

Estimating expectation values is a key subroutine in quantum algorithms. Near-term
implementations face two major challenges: a limited number of samples required to learn a …

We propose to use wave function overlaps obtained from a quantum computer as inputs for
the classical split-amplitude techniques, tailored and externally corrected coupled cluster, to …

Efficiently estimating fermionic Hamiltonian expectation values is vital for simulating various
physical systems. Classical shadow (CS) algorithms offer a solution by reducing the number …

Randomized measurement protocols such as classical shadows represent powerful
resources for quantum technologies, with applications ranging from quantum state …

We present shadow spectroscopy as a simulator-agnostic quantum algorithm for estimating
energy gaps using very few circuit repetitions (shots) and no extra resources (ancilla qubits) …

The recent advances in quantum information processing, sensing, and communications are
surveyed with the objective of identifying the associated knowledge gaps and formulating a …

Quantum computing is an emerging technology with potentially far-reaching implications for
national prosperity and security. Understanding the timeframes over which economic …

Quantum computing requires a universal set of gate operations; regarding gates as
rotations, any rotation angle must be possible. However a real device may only be capable …

Efficiently measuring nonlinear properties, like the entanglement spectrum, is a significant
yet challenging task from quantum information processing to many-body physics. Current …