Thermally assisted quantum annealing of a 16-qubit problem.

Efforts to develop useful quantum computers have been blocked primarily by environmental noise. Quantum annealing is a scheme of quantum computation that is predicted to be more robust against noise, because despite the thermal environment mixing the system's state in the energy basis, the system partially retains coherence in the computational basis, and hence is able to establish well-defined eigenstates. Here we examine the environment's effect on quantum annealing using 16 qubits of a superconducting quantum processor. For a problem instance with an isolated small-gap anticrossing between the lowest two energy levels, we experimentally demonstrate that, even with annealing times eight orders of magnitude longer than the predicted single-qubit decoherence time, the probabilities of performing a successful computation are similar to those expected for a fully coherent system. Moreover, for the problem studied, we show that quantum annealing can take advantage of a thermal environment to achieve a speedup factor of up to 1,000 over a closed system.

Quantum annealing with manufactured spins.

Many interesting but practically intractable problems can be reduced to that of finding the ground state of a system of interacting spins; however, finding such a ground state remains computationally difficult. It is believed that the ground state of some naturally occurring spin systems can be effectively attained through a process called quantum annealing. If it could be harnessed, quantum annealing might improve on known methods for solving certain types of problem. However, physical investigation of quantum annealing has been largely confined to microscopic spins in condensed-matter systems. Here we use quantum annealing to find the ground state of an artificial Ising spin system comprising an array of eight superconducting flux quantum bits with programmable spin-spin couplings. We observe a clear signature of quantum annealing, distinguishable from classical thermal annealing through the temperature dependence of the time at which the system dynamics freezes. Our implementation can be configured in situ to realize a wide variety of different spin networks, each of which can be monitored as it moves towards a low-energy configuration. This programmable artificial spin network bridges the gap between the theoretical study of ideal isolated spin networks and the experimental investigation of bulk magnetic samples. Moreover, with an increased number of spins, such a system may provide a practical physical means to implement a quantum algorithm, possibly allowing more-effective approaches to solving certain classes of hard combinatorial optimization problems.

A numerical investigation of the effect of vertex geometry on localized surface plasmon resonance of nanostructures.

Advances in nanofabrication and nano-scale measurement methods now allow for fabrication of highly detailed nanometer-scale topographic features. As geometric features greatly impact the formation of an electromagnetic field in response to incident light, this in turn calls for the study of the effects of new features of nanostructures on their performance in applications such as localized surface plasmon resonance (LSPR) sensing. This paper studies the effects of vertex features of a single nanostructure on its LSPR properties. A general relationship between the LSPR spectra and the vertex features of a nanoparticle is established. The results of electrodynamics calculations show that a delta-star with a relatively small vertex angle exhibits a bigger resonant wavelength than one with a large vertex angle. Moreover, the sensing performance initially increases, and then decreases as angular size of the vertices increases, with a turning point of 30 degrees. It is also shown that for nanostars with different numbers of vertices, the resonant wavelength undergoes a blue shift and the sensing performance grows poorer as the number of vertices increases. A regular vertex angle of 30 degrees displays the greatest figure of merit (FOM) value for LSPR applications, approximately 9.5 RIU(-1).

Effects of vertex truncation of polyhedral nanostructures on localized surface plasmon resonance.

Polyhedral nanostructures are widely used to enable localized surface plasmon resonance (LSPR). In practice, vertices of such structures are almost always truncated due to limitations of nanofabrication processes. This paper studies the effects of vertex truncation of polyhedral nanostructures on the characteristics of LSPR sensing. The optical properties and sensing performance of triangular nanoplates with truncated vertices are investigated using electrodynamics analysis and verified by experiment. The experimental results correlated with simulation analysis demonstrate that the fabricated triangular nanoplate array has a truncation ratio, defined as the length of truncation along an edge of the triangle over the edge length, of approximately 12.8%. This significantly influences optical properties of the nanostructures, resulting in poorer sensing performance. These insights can be used to guide the design and fabrication of nanostructures for high performance LSPR sensors.