Quantum inference of states and processes

The maximum-likelihood principle unifies inference of quantum states and processes from experimental noisy data. Particularly, a generic quantum process may be estimated simultaneously with unknown quantum probe states provided that measurements on probe and transformed probe states are available. Drawbacks of various approximate treatments are considered.Comment: 7 pages, 4 figure

Measurement of qubits

We describe in detail the theory underpinning the measurement of density matrices of a pair of quantum two-level systems (qubits). Our particular emphasis is on qubits realized by the two polarization degrees of freedom of a pair of entangled photons generated in a down-conversion experiment; however, the discussion applies in general, regardless of the actual physical realization. Two techniques are discussed, namely, a tomographic reconstruction (in which the density matrix is linearly related to a set of measured quantities) and a maximum likelihood technique which requires numerical optimization (but has the advantage of producing density matrices that are always non-negative definite). In addition, a detailed error analysis is presented, allowing errors in quantities derived from the density matrix, such as the entropy or entanglement of formation, to be estimated. Examples based on down-conversion experiments are used to illustrate our results

Grain Surface Models and Data for Astrochemistry

AbstractThe cross-disciplinary field of astrochemistry exists to understand the formation, destruction, and survival of molecules in astrophysical environments. Molecules in space are synthesized via a large variety of gas-phase reactions, and reactions on dust-grain surfaces, where the surface acts as a catalyst. A broad consensus has been reached in the astrochemistry community on how to suitably treat gas-phase processes in models, and also on how to present the necessary reaction data in databases; however, no such consensus has yet been reached for grain-surface processes. A team of ∼25 experts covering observational, laboratory and theoretical (astro)chemistry met in summer of 2014 at the Lorentz Center in Leiden with the aim to provide solutions for this problem and to review the current state-of-the-art of grain surface models, both in terms of technical implementation into models as well as the most up-to-date information available from experiments and chemical computations. This review builds on the results of this workshop and gives an outlook for future directions

Kinetic studies on the inhibition of creatine kinase activity by branched‐chain α‐amino acids in the brain cortex of rats

Maple syrup urine disease (MSUD) is a metabolic disorder biochemically characterized by the accumulation of branched-chain α-amino acids (BCAA) and their branched-chain α-keto acids (BCKA) in blood and tissues. Neurological dysfunction is usually present in the patients, but the mechanisms of brain damage in this disease are far from be understood. The main objective of this study was to investigate the mechanisms by which BCAA inhibit creatine kinase activity, a key enzyme of energy homeostasis, in the brain cortex of 21-day-old Wistar rats. For the kinetic studies, Lineweaver–Burk and a modification of the Chevillard et al. plots were used to characterize the mechanisms of enzyme inhibition. The results indicated that BCAA inhibit creatine kinase by competition with the substrates phosphocreatine and ADP at the active site. Considering the crucial role creatine kinase plays in energy homeostasis in brain, if these effects also occur in the brain of MSUD patients, it is possible that inhibition of this enzyme activity may contribute to the brain damage found in this disease. In this case, it is possible that creatine supplementation to the diet might benefit MSUD patients