Phonon density of states and compression behavior in iron sulfide under pressure

We report the partial phonon densities of states (DOS) of iron sulfide, a possible component of the rocky planet's core, measured by the Fe-57 nuclear resonant inelastic x-ray scattering and calculate the total phonon DOS under pressure. From the phonon DOS, we drive thermodynamic parameters. A comparison of the observed and estimated compressibilities makes it clear that there is a large pure electronic contribution in the observed compressibility in the metallic state. Our results present the observation of thermodynamic parameters of iron sulfide with the low-spin state of an Fe2+ ion at the high density, which is similar to the condition of the Martian core

Reentrant valence transition in EuO at high pressures: beyond the bond-valence model

The pressure-dependent relation between Eu valence and lattice structure in model compound EuO is studied with synchrotron-based x-ray spectroscopic and diffraction techniques. Contrary to expectation, a 7% volume collapse at $\approx$ 45 GPa is accompanied by a reentrant Eu valence transition into a \emph{lower} valence state. In addition to highlighting the need for probing both structure and electronic states directly when valence information is sought in mixed-valent systems, the results also show that widely used bond-valence methods fail to quantitatively describe the complex electronic valence behavior of EuO under pressure.Comment: 5 pages, 4 figure

Magneto-x-ray effects in transition-metal alloys

We present a theory that combines the relativistic spin-polarized version of the Koringa-Kohn-Rostoker coherent-potential approximation theory and the macroscopic theory of magneto-optical effects enabling us to calculate magneto-x-ray effects from first principles. The theory is illustrated by calculation of Faraday and Kerr rotations and ellipticities for transition-metal alloys

A general moment NRIXS approach to the determination of equilibrium Fe isotopic fractionation factors: application to goethite and jarosite

We measured the reduced partition function ratios for iron isotopes in goethite FeO(OH), potassium-jarosite KFe3(SO4)2(OH)6, and hydronium-jarosite (H3O)Fe3(SO4)2(OH)6, by Nuclear Resonant Inelastic X-Ray Scattering (NRIXS, also known as Nuclear Resonance Vibrational Spectroscopy -NRVS- or Nuclear Inelastic Scattering -NIS) at the Advanced Photon Source. These measurements were made on synthetic minerals enriched in 57Fe. A new method (i.e., the general moment approach) is presented to calculate {\beta}-factors from the moments of the NRIXS spectrum S(E). The first term in the moment expansion controls iron isotopic fractionation at high temperature and corresponds to the mean force constant of the iron bonds, a quantity that is readily measured and often reported in NRIXS studies.Comment: 38 pages, 2 tables, 8 figures. In press at Geochimica et Cosmochimica Acta. Appendix C contains new derivations relating the moments of the iron PDOS to the moments of the excitation probability function measured in Nuclear Resonant Inelastic X-ray Scatterin

Improved Bounds on Quantum Learning Algorithms

In this article we give several new results on the complexity of algorithms that learn Boolean functions from quantum queries and quantum examples. Hunziker et al. conjectured that for any class C of Boolean functions, the number of quantum black-box queries which are required to exactly identify an unknown function from C is $O(\frac{\log |C|}{\sqrt{{\hat{\gamma}}^{C}}})$, where $\hat{\gamma}^{C}$ is a combinatorial parameter of the class C. We essentially resolve this conjecture in the affirmative by giving a quantum algorithm that, for any class C, identifies any unknown function from C using $O(\frac{\log |C| \log \log |C|}{\sqrt{{\hat{\gamma}}^{C}}})$ quantum black-box queries. We consider a range of natural problems intermediate between the exact learning problem (in which the learner must obtain all bits of information about the black-box function) and the usual problem of computing a predicate (in which the learner must obtain only one bit of information about the black-box function). We give positive and negative results on when the quantum and classical query complexities of these intermediate problems are polynomially related to each other. Finally, we improve the known lower bounds on the number of quantum examples (as opposed to quantum black-box queries) required for $(\epsilon,\delta)$-PAC learning any concept class of Vapnik-Chervonenkis dimension d over the domain $\{0,1\}^n$ from $\Omega(\frac{d}{n})$ to $\Omega(\frac{1}{\epsilon}\log \frac{1}{\delta}+d+\frac{\sqrt{d}}{\epsilon})$. This new lower bound comes closer to matching known upper bounds for classical PAC learning.Comment: Minor corrections. 18 pages. To appear in Quantum Information Processing. Requires: algorithm.sty, algorithmic.sty to buil