Legal Issues for Space Based Solar Power

When Pacific Gas & Electric Co. (PG&E) entered into a May 2009 contract with Solaren Corp. to purchase power for 150,000 homes starting in 2016, public attention was abruptly focused on a potential major new source of energy: space based solar power (SBSP). First proposed in 1968 by Dr. Peter E. Glaser, Vice President for Advanced Technology at Arthur D. Little, SBSP is based on the simple facts that solar power, the most abundant source of energy on our planet, cannot be collected on the earth\u27s surface at night, and that the sun\u27s rays lose much of their energy while traveling through our atmosphere. As a result, the same solar collector located in a geosynchronous earth orbit (GEO) some 36,000 Km in space can produce between 5 and 10 times as much electric power as can be produced on the earth\u27s surface. Solaren\u27s innovative relationship with PG&E is based on a 40-year-old concept that a solar power satellite located in space can be designed to deliver a base load source of electrical power 24 hours of every day and night

On the dimension of subspaces with bounded Schmidt rank

We consider the question of how large a subspace of a given bipartite quantum system can be when the subspace contains only highly entangled states. This is motivated in part by results of Hayden et al., which show that in large d x d--dimensional systems there exist random subspaces of dimension almost d^2, all of whose states have entropy of entanglement at least log d - O(1). It is also related to results due to Parthasarathy on the dimension of completely entangled subspaces, which have connections with the construction of unextendible product bases. Here we take as entanglement measure the Schmidt rank, and determine, for every pair of local dimensions dA and dB, and every r, the largest dimension of a subspace consisting only of entangled states of Schmidt rank r or larger. This exact answer is a significant improvement on the best bounds that can be obtained using random subspace techniques. We also determine the converse: the largest dimension of a subspace with an upper bound on the Schmidt rank. Finally, we discuss the question of subspaces containing only states with Schmidt equal to r.Comment: 4 pages, REVTeX4 forma

Simple Space-Time Symmetries: Generalizing Conformal Field Theory

We study simple space-time symmetry groups G which act on a space-time manifold M=G/H which admits a G-invariant global causal structure. We classify pairs (G,M) which share the following additional properties of conformal field theory: 1) The stability subgroup H of a point in M is the identity component of a parabolic subgroup of G, implying factorization H=MAN, where M generalizes Lorentz transformations, A dilatations, and N special conformal transformations. 2) special conformal transformations in N act trivially on tangent vectors to the space-time manifold M. The allowed simple Lie groups G are the universal coverings of SU(m,m), SO(2,D), Sp(l,R), SO*(4n) and E_7(-25) and H are particular maximal parabolic subgroups. They coincide with the groups of fractional linear transformations of Euklidean Jordan algebras whose use as generalizations of Minkowski space time was advocated by Gunaydin. All these groups G admit positive energy representations. It will also be shown that the classical conformal groups SO(2,D) are the only allowed groups which possess a time reflection automorphism; in all other cases space-time has an intrinsic chiral structure.Comment: 37 pages, 4 Table

Constructing patch-based ligand-binding pocket database for predicting function of proteins

Background Many of solved tertiary structures of unknown functions do not have global sequence and structural similarities to proteins of known function. Often functional clues of unknown proteins can be obtained by predicting small ligand molecules that bind to the proteins. Methods In our previous work, we have developed an alignment free local surface-based pocket comparison method, named Patch-Surfer, which predicts ligand molecules that are likely to bind to a protein of interest. Given a query pocket in a protein, Patch-Surfer searches a database of known pockets and finds similar ones to the query. Here, we have extended the database of ligand binding pockets for Patch-Surfer to cover diverse types of binding ligands. Results and conclusion We selected 9393 representative pockets with 2707 different ligand types from the Protein Data Bank. We tested Patch-Surfer on the extended pocket database to predict binding ligand of 75 non-homologous proteins that bind one of seven different ligands. Patch-Surfer achieved the average enrichment factor at 0.1 percent of over 20.0. The results did not depend on the sequence similarity of the query protein to proteins in the database, indicating that Patch-Surfer can identify correct pockets even in the absence of known homologous structures in the database