Pr2_2Ir2_2O7_7: when Luttinger semimetal meets Melko-Hertog-Gingras spin ice state

We study the band structure topology and engineering from the interplay between local moments and itinerant electrons in the context of pyrochlore iridates. For the metallic iridate Pr$_2$Ir$_2$O$_7$, the Ir $5d$ conduction electrons interact with the Pr $4f$ local moments via the $f$-$d$ exchange. While the Ir electrons form a Luttinger semimetal, the Pr moments can be tuned into an ordered spin ice with a finite ordering wavevector, dubbed "Melko-Hertog-Gingras" state, by varying Ir and O contents. We point out that the ordered spin ice of the Pr local moments generates an internal magnetic field that reconstructs the band structure of the Luttinger semimetal. Besides the broad existence of Weyl nodes, we predict that the magnetic translation of the "Melko-Hertog-Gingras" state for the Pr moments protects the Dirac band touching at certain time reversal invariant momenta for the Ir conduction electrons. We propose the magnetic fields to control the Pr magnetic structure and thereby indirectly influence the topological and other properties of the Ir electrons. Our prediction may be immediately tested in the ordered Pr$_2$Ir$_2$O$_7$ samples. We expect our work to stimulate a detailed examination of the band structure, magneto-transport, and other properties of Pr$_2$Ir$_2$O$_7$.Comment: 10 pages, 7 figures, added more ref

Analysis of the role of poly(A) -binding protein (PAB1) in the mRNA degradation process in yeast

The mRNA deadenylation process influences multiple aspects of protein synthesis and is known to be the major factor controlling mRNA decay rates. My data demonstrates that yeast PAB1 plays both positive and negative roles in controlling deadenylation, and I have identified particular regions of PAB1 involved in controlling different aspects of the mRNA degradative process. I have found that yeast PAB1 does not play a simple, obstructionist role in regulating CCR4 deadenylation. Instead, PAB1-PAB1 protein interactions, as mediated by the PAB1 proline-rich region (P domain) and the RRM1 domain, are required for the CCR4 deadenylase activity. The P and RRM1 domains were shown to mediate PAB1-PAB1 binding, suggesting that enhancing CCR4 function entails the rearrangement of the PAB1-mRNP structure. I have also established that PAB1 contacts to the poly (A) tail made by the RRM2 domain are critical to stabilizing the CCR4-NOT complex and promoting deadenylation. The C-terminal globular domain of PAB1 through its contacts to eRF3 is also required for CCR4 deadenylation. In contrast, the RRM3 domain of PAB1 inhibits deadenylation and decapping. mRNP structures involving the terminal PAB1 bound to poly (A) are also affected by RRM3 and control the end to deadenylation and apparently the commencement of decapping. These results indicate that PAB1 integrates and controls the transition from deadenylation to decapping and from a translationally competent state to an mRNA degradative state

Least-squares reverse-time migration

Conventional migration methods, including reverse-time migration (RTM) have two weaknesses: first, they use the adjoint of forward-modelling operators, and second, they usually apply a crosscorrelation imaging condition to extract images from reconstructed wavefields. Adjoint operators, which are an approximation to inverse operators, can only correctly calculate traveltimes (phase), but not amplitudes. To preserve the true amplitudes of migration images, it is necessary to apply the inverse of the forward-modelling operator. Similarly, crosscorrelation imaging conditions also only correct traveltimes (phase) but do not preserve amplitudes. Besides, the examples show crosscorrelation imaging conditions produce strong sidelobes. Least-squares migration (LSM) uses both inverse operators and deconvolution imaging conditions. As a result, LSM resolves both problems in conventional migration methods and produces images with fewer artefacts, higher resolution and more accurate amplitudes. At the same time, RTM can accurately handle all dips, frequencies and any type of velocity variation. Combining RTM and LSM produces least-squares reverse-time migration (LSRTM), which in turn has all the advantages of RTM and LSM. In this thesis, we implement two types of LSRTM: matrix-based LSRTM (MLSRTM) and non-linear LSRTM (NLLSRTM). MLSRTM is a matrix formulation of LSRTM and is more stable than conventional LSRTM; it can be implemented with linear inversion algorithms but needs a large amount of computer memory. NLLSRTM, by contrast, directly expresses migration as an optimisation which minimises the 2 norm of the residual between the predicted and observed data. NLLSRTM can be implemented using non-linear gradient inversion algorithms, such as non-linear steepest descent and non-linear conjugated-gradient solvers. We demonstrate that both MLSRTM and NLLSRTM can achieve better images with fewer artefacts, higher resolution and more accurate amplitudes than RTM using three synthetic examples. The power of LSRTM is also further illustrated using a field dataset. Finally, a simple synthetic test demonstrates that the objective function used in LSRTM is sensitive to errors in the migration velocity. As a result, it may be possible to use NLLSRTM to both refine the migrated image and estimate the migration velocity.Open Acces