Quantum random sampling is the leading proposal for demonstrating a computational
advantage of quantum computers over classical computers. Recently the first large-scale …

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 analyze the complexity of learning $ n $-qubit quantum phase states. A degree-$ d $
phase state is defined as a superposition of all $2^ n $ basis vectors $ x $ with amplitudes …

The spectral-density operator ρ ̂ (ω)= δ (ω− H ̂) plays a central role in linear response
theory as its expectation value, the dynamical response function, can be used to compute …

Parametrized quantum evolution is the main ingredient in variational quantum algorithms for
near-term quantum devices. In digital quantum computing, it has been shown that random …

Over the last few decades, nonlinear optics has become significantly more nonlinear,
traversing nearly a billionfold improvement in energy efficiency, with ultrafast nonlinear …

The field of quantum Hamiltonian complexity lies at the intersection of quantum many-body
physics and computational complexity theory, with deep implications to both fields. The main …

Several classes of quantum circuits have been shown to provide a quantum computational
advantage under certain assumptions. The study of ever more restricted classes of quantum …

Randomness is an intrinsic feature of quantum theory. The outcome of any quantum
measurement will be random, sampled from a probability distribution that is defined by the …

Dynamics of atom–field correlations and single-mode nonclassicalities present in the
resonant Jaynes–Cummings model are investigated using negativity and entanglement …