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 …

The rapid pace of development in quantum computing technology has sparked a
proliferation of benchmarks to assess the performance of quantum computing hardware and …

Quantum signal processing (QSP) is a powerful toolbox for the design of quantum
algorithms and can lead to asymptotically optimal computational costs. Its realization on …

Quantum signal processing (QSP) represents a real scalar polynomial of degree $ d $ using
a product of unitary matrices of size $2\times 2$, parameterized by $(d+ 1) $ real numbers …

This paper addresses the problem of solving nonlinear systems in the context of symmetric
quantum signal processing (QSP), a powerful technique for implementing matrix functions …

Elucidating a connection with nonlinear Fourier analysis (NLFA), we extend a well known
algorithm in quantum signal processing (QSP) to represent measurable signals by square …

We study the quantum simulation of mixed quantum-semiclassical (MQS) systems, of
fundamental interest in many areas of physics, such as molecular scattering and …

Pricing financial derivatives, in particular European-style options at different time-maturities
and strikes, means a relevant problem in finance. The dynamics describing the price of …

Demonstrations of quantum advantage for certain sampling problems has generated
considerable excitement for quantum computing and has further spurred the development of …

Analog quantum simulation allows for assessing static and dynamical properties of strongly
correlated quantum systems to high precision. To perform simulations outside the reach of …