Entanglement of indistinguishable particles in condensed-matter physics

The concept of entanglement in systems where the particles are indistinguishable has been the subject of much recent interest and controversy. In this paper we study the notion of entanglement of particles introduced by Wiseman and Vaccaro [Phys. Rev. Lett. 91, 097902 (2003)] in several specific physical systems, including some that occur in condensed-matter physics. The entanglement of particles is relevant when the identical particles are itinerant and so not distinguished by their position as in spin models. We show that entanglement of particles can behave differently than other approaches that have been used previously, such as entanglement of modes (occupation-number entanglement) and the entanglement in the two-spin reduced density matrix. We argue that the entanglement of particles is what could actually be measured in most experimental scenarios and thus its physical significance is clear. This suggests that entanglement of particles may be useful in connecting theoretical and experimental studies of entanglement in condensed-matter systems.

Towards a Realization of the Condensed-Matter-Gravity Correspondence in String Theory via Consistent Abelian Truncation of the Aharony-Bergman-Jafferis-Maldacena Model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Interacting fermionic atoms in optical lattices - A quantum simulator for condensed matter physics

This thesis reports on the creation and analysis of many-body states of interacting fermionic atoms in optical lattices. The realized system can be described by the Fermi-Hubbard hamiltonian, which is an important model for correlated electrons in modern condensed matter physics. In this way, ultra-cold atoms can be utilized as a quantum simulator to study solid state phenomena. The use of a Feshbach resonance in combination with a blue-detuned optical lattice and a red-detuned dipole trap enables an independent control over all relevant parameters in the many-body hamiltonian. By measuring the in-situ density distribution and doublon fraction it has been possible to identify both metallic and insulating phases in the repulsive Hubbard model, including the experimental observation of the fermionic Mott insulator. In the attractive case, the appearance of strong correlations has been detected via an anomalous expansion of the cloud that is caused by the formation of non-condensed pairs. By monitoring the in-situ density distribution of initially localized atoms during the free expansion in a homogeneous optical lattice, a strong influence of interactions on the out-of-equilibrium dynamics within the Hubbard model has been found. The reported experiments pave the way for future studies on magnetic order and fermionic superfluidity in a clean and well-controlled experimental system.

A deep learning model via thermodynamics and condensed matter physics

Deep Learning architectures give brilliant results in a large variety of fields, but a comprehensive theoretical description of their inner functioning is still lacking. In this work, we try to understand the behavior of neural networks by modelling in the frameworks of Thermodynamics and Condensed Matter Physics. We approach neural networks as in a real laboratory and we measure the frequency spectrum and the entropy of the weights of the trained model. The stochasticity of the training occupies a central role in the dynamics of the weights and makes it difficult to assimilate neural networks to simple physical systems. However, the analogy with Thermodynamics and the introduction of a well defined temperature leads us to an interesting result: if we eliminate from a CNN the "hottest" filters, the performance of the model remains the same, whereas, if we eliminate the "coldest" ones, the performance gets drastically worst. This result could be exploited in the realization of a training loop which eliminates the filters that do not contribute to loss reduction. In this way, the computational cost of the training will be lightened and more importantly this would be done by following a physical model. In any case, beside important practical applications, our analysis proves that a new and improved modeling of Deep Learning systems can pave the way to new and more efficient algorithms.

Characterization of the Biocompatible Magnetic Colloid on the Basis of Fe(3)O(4) Nanoparticles Coated with Dextran, Used as Contrast Agent in Magnetic Resonance Imaging

The magnetic resonance imaging contrast agent, the so-called Endorem (TM) colloidal suspension on the basis of superparamagnetic iron oxide nanoparticles (mean diameter of 5.5 nm) coated with dextran, were characterized on the basis of several measurement techniques to determine the parameters of their most important physical and chemical properties. It is assumed that each nanoparticle is consisted of Fe(3)O(4) monodomain and it was observed that its oxidation to gamma-Fe(2)O(3) occurs at 253.1 degrees C. The Mossbauer spectroscopy have shown a superparamagnetic behavior of the magnetic nanoparticles. The Magnetic Resonance results show an increase of the relaxation times T(1), T(2), and T(2)* with decreasing concentration of iron oxide nanoparticles. The relaxation effects of SPIONs contrast agents are influenced by their local concentration as well as the applied field strength and the environment in which these agents interact with surrounding protons. The proton relaxation rates presented a linear behavior with concentration. The measured values of thermooptic coefficient partial derivative n/partial derivative T, thermal conductivity K, optical birefringence Delta n(0), nonlinear refractive index n(2), nonlinear absorption beta` and third-order nonlinear susceptibility vertical bar chi((3))vertical bar are also reported.

Imaging the atomic structure of activated carbon

The precise atomic structure of activated carbon is unknown, despite its huge commercial importance in the purification of air and water. Diffraction methods have been extensively applied to the study of microporous carbons, but cannot provide an unequivocal identification of their structure. Here we show that the structure of a commercial activated carbon can be imaged directly using aberration-corrected transmission electron microscopy. Images are presented both of the as-produced carbon and of the carbon following heat treatment at 2000 degrees C. In the 2000 degrees C carbon clear evidence is found for the presence of pentagonal rings, suggesting that the carbons have a fullerene-related structure. Such a structure would help to explain the properties of activated carbon, and would also have important implications for the modelling of adsorption on microporous carbons.

Visualizing the ac magnetic susceptibility of superconducting films via magneto-optical imaging

We have established a link between the global ac response and the local flux distribution of superconducting films by combining magnetic ac susceptibility, dc magnetization, and magneto-optical measurements. The investigated samples are three Nb films: a plain specimen, used as a reference sample, and other two films patterned with square arrays of antidots. At low temperatures and small ac amplitudes of the excitation field, the Meissner screening prevents penetration of flux into the sample. Above a certain ac drive threshold, flux avalanches are triggered during the first cycle of the ac excitation. The subsequent periodic removal, inversion, and rise of flux occurs essentially through the already-created dendrites, giving rise to an ac susceptibility signal weakly dependent on the applied field. The intradendrite flux oscillation is followed, at higher values of the excitation field, by a more drastic process consisting of creation of new dendrites and antidendrites. In this more invasive regime, the ac susceptibility shows a clear field dependence. At higher temperatures a smooth penetration occurs, and the flux profile is characteristic of a critical state. We have also shown that the regime dominated by vortex avalanches can be reliably identified by ac susceptibility measurements. © 2011 American Physical Society.

Synthesis of gadolinium-labeled shell-crosslinked nanoparticles for magnetic resonance imaging applications

Shell-crosslinked knedel-like nanoparticles (SCKs; knedel is a Polish term for dumplings) were derivatized with gadolinium Shell chelates and studied as robust magnetic-resonance-imaging-active structures with hydrodynamic diameters of 40 +/- 3 nm. SCKs possessing an amphiphilic core-shell morphology were produced from the aqueous assembly of diblock copolymers of poly(acrylic acid) (PAA) and poly(methyl acrylate) (PMA), PAA(52)-b-PMA(128), and subsequent covalent crosslinking by amidation upon reaction with 2,2'-(ethylenedioxy)bis(ethylamine) throughout the shell layer. The properties of these materials, including non-toxicity towards mammalian cells, non-immunogenicity within mice, and capability for polyvalent targeting, make them ideal candidates for utilization within biological systems. The synthesis of SCKs derivatized with Gd-III and designed for potential use as a unique nanometer-scale contrast agent for MRI applications is described herein. Utilization of an amino-functionalized diethylenetriaminepentaacetic acid-Gd analogue allowed for direct covalent conjugation throughout the hydrophilic shell layer of the SCKs and served to increase the rotational correlation lifetime of the Gd. In addition, the highly hydrated nature of the shell layer in which the Gd was located allowed for rapid water exchange; thus, the resulting material demonstrated large ionic relaxivities (39 s(-1) mM(-1)) in an applied magnetic field of 0.47 T at 40 degrees C and, as a result of the large loading capacity of the material, also demonstrated high molecular relaxivities (20 000 s(-1) mM(-1)).

Optical scatter imaging using digital Fourier microscopy

An approach reported recently by Alexandrov et al (2005 Int. J Imag. Syst. Technol. 14 253-8) on optical scatter imaging, termed digital Fourier microscopy (DFM), represents an adaptation of digital Fourier holography to selective imaging of biological matter. The holographic mode of the recording of the sample optical scatter enables reconstruction of the sample image. The form-factor of the sample constituents provides a basis for discrimination of these constituents implemented via flexible digital Fourier filtering at the post-processing stage. As in dark-field microscopy, the DFM image contrast appears to improve due to the suppressed optical scatter from extended sample structures. In this paper, we present the theoretical and experimental study of DFM using a biological phantom that contains polymorphic scatterers.

Characterization of Superparamagnetic Iron Oxide Coated with Silicone Used as Contrast Agent for Magnetic Resonance Image for the Gastrointestinal Tract

The present work is a report of the characterization of superparamagnetic iron oxide nanoparticles coated with silicone used as a contrast agent in magnetic resonance imaging of the gastrointestinal tract. The hydrodynamic size of the contrast agent is 281.2 rim, where it was determined by transmission electron microscopy and a Fe(3)O(4) crystalline structure was identified by X-ray diffraction, also confirmed by Mossbauer Spectroscopy. The blocking temperature of 190 K was determined from magnetic measurements based on the Zero Field Cooled and Field Cooled methods. The hysteresis loops were measured at different temperatures below and above the blocking temperature. Ferromagnetic resonance analysis indicated the superparamagnetic nature of the nanoparticles and a strong temperature dependence of the peak-to-peak linewidth Delta H(pp), giromagnetic factor g, number of spins N(S) and relaxation time T(2) were observed. This behavior can be attributed to an increase in the superexchange interaction.

Quantitative ferromagnetic resonance analysis of CD133 stem cells labeled with iron oxide nanoparticles

The aim of this work is to provide a quantitative method for analysis of the concentration of superparamagnetic iron oxide nanoparticles (SPION), determined by means of ferromagnetic resonance (FMR), with the nanoparticles coupled to a specific antibody (AC133), and thus to express the antigenic labeling evidence for the stem cells C D133(+). The FMR efficiency and sensitivity were proven adequate for detecting and quantifying the low amounts of iron content in the C D133(+) cells (similar to 6.16 x 10(5) pg in the volume of 2 mu l containing 4.5 x 1011 SPION). The quantitative method led to the result of 1.70 x 10(-13) mol of Fe (9.5 pg), or 7.0 x 10(6) nanoparticles per cell. For the quantification analysis via the FMR technique it was necessary to carry out a preliminary quantitative visualization of iron oxide-labeled cells in order to ensure that the nanoparticles coupled to the antibodies are indeed tied to the antigen at the stem cell surface and that the cellular morphology was conserved, as proof of the validity of this method. The quantitative analysis by means of FMR is necessary for determining the signal intensity for the study of molecular imaging by means of magnetic resonance imaging (MRI).