Perspectives for quantum state engineering via high nonlinearity in a double-EIT regime

We analyse the possibilities for quantum state engineering offered by a model for Kerr-type nonlinearity enhanced by electromagnetically induced transparency (EIT), which was recently proposed by Petrosyan and Kurizki [2002, Phys. Rev. A, 65, 33833]. We go beyond the semiclassical treatment and derive a quantum version of the model with both a full Hamiltonian approach and an analysis in terms of dressed states. The preparation of an entangled coherent state via a cross-phase modulation effect is demonstrated. We briefly show that the violation of locality for such an entangled coherent state is robust against low detection efficiency. Finally, we investigate the possibility of a bi-chromatic photon blockade realized via the interaction of a low density beam of atoms with a bi-modal electromagnetic cavity which is externally driven. We show the effectiveness of the blockade effect even when more than a single atom is inside the cavity. The possibility to control two different cavity modes allows some insights into the generation of an entangled state of cavity modes.

IQ motif selectivity in human IQGAP1: binding of myosin essential light chain and S100B.

IQGAPs are cytoskeletal scaffolding proteins which link signalling pathways to the reorganisation of actin and microtubules. Human IQGAP1 has four IQ motifs each of which binds to calmodulin. The same region has been implicated in binding to two calmodulin-like proteins, the myosin essential light chain Mlc1sa and the calcium and zinc ion binding protein S100B. Using synthetic peptides corresponding to the four IQ motifs of human IQGAP1, we showed by native gel electrophoresis that only the first IQ motif interacts with Mlc1sa. This IQ motif, and also the fourth, interacts with the budding yeast myosin essential light chain Mlc1p. The first and second IQ motifs interact with S100B in the presence of calcium ions. This clearly establishes that S100B can interact with its targets through IQ motifs in addition to interacting via previously reported sequences. These results are discussed in terms of the function of IQGAP1 and IQ motif recognition.