Optimizing Geometry Compression using Quantum Annealing

The compression of geometry data is an important aspect of bandwidth-efficient data transfer for distributed 3d computer vision applications. We propose a quantum-enabled lossy 3d point cloud compression pipeline based on the constructive solid geometry (CSG) model representation. Key parts of the pipeline are mapped to NP-complete problems for which an efficient Ising formulation suitable for the execution on a Quantum Annealer exists. We describe existing Ising formulations for the maximum clique search problem and the smallest exact cover problem, both of which are important building blocks of the proposed compression pipeline. Additionally, we discuss the properties of the overall pipeline regarding result optimality and described Ising formulations.Comment: 6 pages, 3 figure

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

Coherent control of plasma dynamics

Coherent control of a system involves steering an interaction to a final coherent state by controlling the phase of an applied field. Plasmas support coherent wave structures that can be generated by intense laser fields. Here, we demonstrate the coherent control of plasma dynamics in a laser wakefield electron acceleration experiment. A genetic algorithm is implemented using a deformable mirror with the electron beam signal as feedback, which allows a heuristic search for the optimal wavefront under laser-plasma conditions that is not known a priori. We are able to improve both the electron beam charge and angular distribution by an order of magnitude. These improvements do not simply correlate with having the `best' focal spot, since the highest quality vacuum focal spot produces a greatly inferior electron beam, but instead correspond to the particular laser phase that steers the plasma wave to a final state with optimal accelerating fields

Magnetic fingerprint of individual Fe4 molecular magnets under compression by a scanning tunnelling microscope

Single-molecule magnets (SMMs) present a promising avenue to develop spintronic technologies. Addressing individual molecules with electrical leads in SMM-based spintronic devices remains a ubiquitous challenge: interactions with metallic electrodes can drastically modify the SMM\u2019s properties by charge transfer or through changes in the molecular structure. Here, we probe electrical transport through individual Fe4 SMMs using a scanning tunnelling microscope at 0.5 K. Correlation of topographic and spectroscopic information permits identification of the spin excitation fingerprint of intact Fe4 molecules. Building from this, we find that the exchange coupling strength within the molecule\u2019s magnetic core is significantly enhanced. First-principles calculations support the conclusion that this is the result of confinement of the molecule in the two-contact junction formed by the microscope tip and the sample surface

Predictions of melting, crystallization, and local atomic arrangements of aluminum clusters using a reactive force field

A parametrized reactive force field model for aluminum ReaxFFAl has been developed based on density functional theory (DFT) data. A comparison has been made between DFT and ReaxFFAl outputs to ascertain whether ReaxFFAl is properly parametrized and to check if the output of the latter has correlation with DFT results. Further checks include comparing the equations of state of condensed phases of Al as calculated from DFT and ReaxFFAl. There is a good match between the two results, again showing that ReaxFFAl is correctly parametrized as per the DFT input. Simulated annealing has been performed on aluminum clusters Aln using ReaxFFAl to find the stable isomers of the clusters. A plot of stability function versus cluster size shows the existence of highly stable clusters (magic clusters). Quantum mechanically these magic clusters arise due to the complete filling of the orbital shells. However, since force fields do not care about electrons but work on the assumption of validity of Born–Oppenheimer approximation, the magic clusters are therefore correlated with high structural symmetry. There is a rapid decline in surface energy contribution due to the triangulated nature of the surface atoms leading to higher coordination number. The bulk binding energy is computed to be 76.8 kcal/mol. This gives confidence in the suitability of ReaxFF for studying and understanding the underlying dynamics in aluminum clusters. In the quantification of the growth of cluster it is seen that as the size of the clusters increase there is preference for the coexistence of fcc/hcp orders at the expense of simple icosahedral ordering, although there is some contribution from distorted icosahedral ordering. It is found that even for aluminum clusters with 512 atoms distorted icosahedral ordering exists. For clusters with N≥256 atoms fcc ordering dominates, which implies that at this point we are already on the threshold of bulklike bonding

Detection of hidden structures on all scales in amorphous materials and complex physical systems: basic notions and applications to networks, lattice systems, and glasses

Recent decades have seen the discovery of numerous complex materials. At the root of the complexity underlying many of these materials lies a large number of possible contending atomic- and larger-scale configurations and the intricate correlations between their constituents. For a detailed understanding, there is a need for tools that enable the detection of pertinent structures on all spatial and temporal scales. Towards this end, we suggest a new method by invoking ideas from network analysis and information theory. Our method efficiently identifies basic unit cells and topological defects in systems with low disorder and may analyze general amorphous structures to identify candidate natural structures where a clear definition of order is lacking. This general unbiased detection of physical structure does not require a guess as to which of the system properties should be deemed as important and may constitute a natural point of departure for further analysis. The method applies to both static and dynamic systems.Comment: (23 pages, 9 figures

Cavity-enhanced second harmonic generation via nonlinear-overlap optimization

We describe an approach based on topology optimization that enables automatic discovery of wavelength-scale photonic structures for achieving high-efficiency second-harmonic generation (SHG). A key distinction from previous formulation and designs that seek to maximize Purcell factors at individual frequencies is that our method not only aims to achieve frequency matching (across an entire octave) and large radiative lifetimes, but also optimizes the equally important nonlinear--coupling figure of merit $\bar{\beta}$, involving a complicated spatial overlap-integral between modes. We apply this method to the particular problem of optimizing micropost and grating-slab cavities (one-dimensional multilayered structures) and demonstrate that a variety of material platforms can support modes with the requisite frequencies, large lifetimes $Q > 10^4$, small modal volumes $\sim (\lambda/n)^3$, and extremely large $\bar{\beta} \gtrsim 10^{-2}$, leading to orders of magnitude enhancements in SHG efficiency compared to state of the art photonic designs. Such giant $\bar{\beta}$ alleviate the need for ultra-narrow linewidths and thus pave the way for wavelength-scale SHG devices with faster operating timescales and higher tolerance to fabrication imperfections