Electrically controlled quantum transition to an anomalous metal in 2D

The mechanism through which superconductivity is destroyed upon controlled disordering often holds the key to understanding the mechanism of emergence of superconductivity. Here we demonstrate an $in$-$situ$ mechanism to control the fraction of disorder in a 2D superconductor. By controlling an electric field V$_G$, we created an assembly of segregated superconducting nano-islands and varied the inter-island distance to accomplish a quantum phase transition from a superconducting phase to a strange quantum anomalous metallic (QAM) phase at LaVO$_3$/SrTiO$_3$ interfaces. In the QAM phase, the resistivity dropped below a critical temperature (T$_{CM}$) as if the system was approaching superconductivity, and then saturated, indicating the destruction of global phase coherence and the emergence of a phase where metal-like transport of Bosons (a Bose metal) becomes a possibility. The unprecedented control over the island size is obtained through the control of nanometer scale ferroelectric domains formed in the SrTiO$_3$ side of the interface due to a low-temperature structural phase transition.Comment: To be published in ACS Applied Electronic Material

A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization

The concept of particle swarms originated from the simulation of the social behavior commonly observed in animal kingdom and evolved into a very simple but efficient technique for optimization in recent past. Since its advent in 1995, the Particle Swarm Optimization (PSO) algorithm has attracted the attention of a lot of researchers all over the world resulting into a huge number of variants of the basic algorithm as well as many parameter selection/control strategies. PSO relies on the learning strategy of the individuals to guide its search direction. Traditionally, each particle utilizes its historical best experience as well as the global best experience of the whole swarm through linear summation. The Comprehensive Learning PSO (CLPSO) was proposed as a powerful variant of PSO that enhances the diversity of the population by encouraging each particle to learn from different particles on different dimensions, in the metaphor that the best particle, despite having the highest fitness, does not always offer a better value in every dimension. This paper presents a variant of single-objective PSO called Dynamic Neighborhood Learning Particle Swarm Optimizer (DNLPSO), which uses learning strategy whereby all other particles’ historical best information is used to update a particle’s velocity as in CLPSO. But in contrast to CLPSO, in DNLPSO, the exemplar particle is selected from a neighborhood. This strategy enables the learner particle to learn from the historical information of its neighborhood or sometimes from that of its own. Moreover, the neighborhoods are made dynamic in nature i.e. they are reformed after certain intervals. This helps the diversity of the swarm to be preserved in order to discourage premature convergence. Experiments were conducted on 16 numerical benchmarks in 10, 30 and 50 dimensions, a set of five constrained benchmarks and also on a practical engineering optimization problem concerning the spread-spectrum radar poly-phase code design. The results demonstrate very competitive performance of DNLPSO while locating the global optimum on complicated and multimodal fitness landscapes when compared with five other recent variants of PSO

Unconventional Superconductivity at LaVO₃/SrTiO₃ Interfaces

The conducting interfaces of perovskite oxides are fertile playgrounds of diverse quantum phenomena, and they are potentially important for applications in superconducting nanoelectronic devices. We discovered that the interfaces between the Mott-insulator LaVO3 and the band-insulator SrTiO3 host two-dimensional superconductivity below Tc ≈ 250 mK. Our band structure calculations indicate that for these interfaces, multiple bands (the V and the Ti d bands) cross the Fermi energy where the V d electrons also carry a magnetic moment, thereby raising the possibility of an unconventional order parameter (OP) of the superconducting phase. We have fabricated subsurface soft metallic point-contacts at the LaVO3/SrTiO3 interfaces to probe the OP symmetry spectroscopically through the measurement of Andreev reflection. The spectroscopic features strongly deviate from the expectations within the conventional Bardeen–Cooper–Schriefer framework and support the existence of an unconventional order parameter

Electrically Controlled Quantum Transition to an Anomalous Metal in 2D

The mechanism through which superconductivity is destroyed upon controlled disordering often holds the key to understanding the mechanism of the emergence of superconductivity. Here, we demonstrate an in-situ mechanism to control the fraction of disorder in a 2D superconductor. By controlling an electric field VG, we created an assembly of segregated superconducting nano-islands and varied the interisland distance to accomplish a quantum phase transition from a superconducting phase to a strange quantum anomalous metallic (QAM) phase at LaVO3/SrTiO3 interfaces. In the QAM phase, the resistivity dropped below a critical temperature (TCM) as if the system was approaching superconductivity and then saturated, indicating the destruction of global phase coherence and the emergence of a phase where metal-like transport of Bosons (a Bose metal) becomes a possibility. The unprecedented control over the island size is obtained through the control of nanometer-scale ferroelectric domains formed in the SrTiO3 side of the interface due to a low-temperature structural phase transition