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 …

We introduce an algorithm to compute expectation values of time-evolved observables on
digital quantum computers that requires only bounded average circuit depth to reach …

Simulating the dynamic evolution of physical and molecular systems in a quantum computer
is of fundamental interest in many applications. The implementation of dynamics simulation …

We study how parallelism can speed up quantum simulation. A parallel quantum algorithm
is proposed for simulating the dynamics of a large class of Hamiltonians with good sparse …

Hamiltonian simulation is a major application of quantum computing, for example, enabling
prediction of the properties of molecules. Prior work has used product formulas with …

The Linear Combination of Unitaries (LCU) method is a powerful scheme for the block
encoding of operators but suffers from high overheads. In this work, we discuss the …

Estimating the eigenstate properties of quantum many-body systems is a long-standing,
challenging problem for both classical and quantum computing. For the task of eigenstate …

The well-conditioned multi-product formula (MPF), proposed by [Low, Kliuchnikov, and
Wiebe, 2019], is a simple high-order time-independent Hamiltonian simulation algorithm that …

Time-dependent Hamiltonian simulation (TDHS) is a critical task in quantum computing.
Existing algorithms are generally biased with a small algorithmic error $\varepsilon $, and …

Discovering pragmatic and efficient approaches to synthesize $\varepsilon $-
approximations to quantum operators such as real (imaginary) time-evolution propagators in …