Related papers: Using Principal Component Analysis to Distinguish …
Recent studies have shown a number of surprising vortex dynamics phenomena both in low and high temperature superconductors, which include: low frequency noise, slow voltage oscillations, history dependent dynamic response, memory of the…
Principal Component Analysis (PCA) is a transform for finding the principal components (PCs) that represent features of random data. PCA also provides a reconstruction of the PCs to the original data. We consider an extension of PCA which…
We study nonequilibrium quantum dynamics of spin chains by employing principal component analysis (PCA) on data sets of wave function snapshots and examine how information propagates within these data sets. The quantities we employ are…
Two-dimensional superconductors offer an excellent platform for the study of vortex matter due to their low superfluid stiffness and inability to effectively screen applied magnetic fields. Here we explore vortices in a two-dimensional…
Principal component analysis (PCA) is a widely employed statistical tool used primarily for dimensionality reduction. However, it is known to be adversely affected by the presence of outlying observations in the sample, which is quite…
We present simulations of the dynamic critical state for a 2D superconductor with strong pinning centers, corresponding to a matching field twice the applied magnetic field. The sharp crossover between the plastic regime, at low current…
Quantized magnetic vortices driven by electric current determine key electromagnetic properties of superconductors. While the dynamic behavior of slow vortices has been thoroughly investigated, the physics of ultrafast vortices under strong…
In order to characterize flux flow through disordered type-II superconductors, we investigate the effects of columnar and point defects on the vortex velocity / voltage power spectrum in the driven non-equilibrium steady state. We employ…
Two-band superconductors host vortices from superfluid condensates of different electron bands. These vortices carry a fractional flux quantum and attract each other, coalescing to form a composite vortex with the whole flux quantum…
We introduce a model describing vortices in strongly disordered three-dimensional superconductors. The model focuses on the topological defects, i.e., dislocation lines, in an elastic description of the vortex lattice. The model is studied…
The work reported in my doctoral thesis is an experimental study of vortex dynamics and phase transitions in thin films of type II superconductors using scanning tunneling spectroscopy, low frequency ac susceptibility measurements and…
Principal Component Analysis (PCA) is applied to a variety of blazars to examine X-ray spectral variability. Data from nine different objects are analysed in two ways: long-term, which examines variability trends across years or decades,…
The finite temperature dynamical phases of vortices in films driven by a uniform force and interacting with the periodic pinning potential of a square lattice of columnar defects are investigated by Langevin dynamics simulations of a London…
Superconductors often contain quantized microscopic whirlpools of electrons, called vortices, that can be modeled as one-dimensional elastic objects. Vortices are a diverse playground for condensed matter because of the interplay between…
Order-disorder transitions between glassy phases are quite common in nature and yet a comprehensive survey of the microscopic structural changes remains elusive since the scale of the constituents is tiny and in most cases few of them take…
Using molecular dynamics simulations, we report a study of the dynamics of two-dimensional vortex lattices driven over a disordered medium. In strong disorder, when topological order is lost, we show that the depinning transition is…
Principal Component Analysis (PCA) is one of the most commonly used statistical methods for data exploration, and for dimensionality reduction wherein the first few principal components account for an appreciable proportion of the…
We present new results of numerical simulations for driven vortex lattices in presence of random disorder at zero temperature. We show that the plastic dynamics of vortices display dissipative chaos. Intermittency "routes to chaos" have…
A new class of artificial atoms, such as synthetic nanocrystals or vortices in superconductors, naturally self-assemble into ordered arrays. This property makes them applicable to the design of novel solids, and devices whose properties…
Superconductors have two key characteristics. They expel magnetic field and they conduct electrical current with zero resistance. However, both properties are compromised in high magnetic fields which can penetrate the material and create a…