Cooperative emission due to spontaneous build-up and rapid decay of macroscopic polarization in a strongly inverted gain medium is drastically different from the lasing dynamics. The medium polarization and not the cavity field drives the emission from a d ...
The spatial distribution of dwarf galaxies around their host galaxies is a critical test for the standard model of cosmology because it probes the dynamics of dark matter halos and is independent of the internal baryonic processes of galaxies. Comoving pla ...
This book introduces the mathematical ideas connecting Statistical Mechanics and Conformal Field Theory (CFT). Building advanced structures on top of more elementary ones, the authors map out a well-posed road from simple lattice models to CFTs.Structure ...
The task of learning a quantum circuit to prepare a given mixed state is a fundamental quantum subroutine. We present a variational quantum algorithm (VQA) to learn mixed states which is suitable for near-term hardware. Our algorithm represents a generaliz ...
Fields of technology as diverse as microwave filter construction, characterization of material interfaces with atomic precision, and detection of gravitational waves from astronomical sources employ mechanical resonators at their core. The utility of mecha ...
Quantum two-level systems, i.e., qubits, form the basis for most quantum machine learning approaches that have been proposed throughout the years. However, higher dimensional quantum systems constitute a promising alternative and are increasingly explored ...
Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, used with Markov chain Monte Carlo sampling, provide good approximations to s ...
The design of envelopes with complex geometries often leads to construction challenges. To overcome these difficulties, resorting to discrete differential geometry proved successful by establishing close links between mesh properties and the existence of g ...
Compressed sensing is provided a data-acquisition paradigm for sparse signals. Remarkably, it has been shown that the practical algorithms provide robust recovery from noisy linear measurements acquired at a near optimal sampling rate. In many real-world a ...
