Part I. Fundamental Concepts: 1. Introduction and overview 2. Introduction to quantum mechanics 3. Introduction to computer science Part II. Quantum Computation: 4. Quantum circuits 5. The quantum Fourier transform and its application 6. Quantum search algorithms 7. Quantum computers: physical realization Part III. Quantum Information: 8. Quantum noise and quantum operations 9. Distance measures for quantum information 10. Quantum error-correction 11. Entropy and information 12. Quantum information theory Appendices References Index.

Quantum Computation and Quantum Information

In 1978 it was discovered, largely through the work of Fleischmann, Van Duyne, Creighton, and their coworkers that molecules adsorbed on specially prepared silver surfaces produce a Raman spectrum that is at times a millionfold more intense than expected. This effect was dubbed surface-enhanced Raman scattering (SERS). Since then the effect has been demonstrated with many molecules and with a number of metals, including Cu, Ag, Au, Li, Na, K, In, Pt, and Rh. In addition, related phenomena such as surface-enhanced second-harmonic generation, four-wave mixing, absorption, and fluorescence have been observed. Although not all fine points of the enhancement mechanism have been clarified, the majority view is that the largest contributor to the intensity amplification results from the electric field enhancement that occurs in the vicinity of small, interacting metal particles that are illuminated with light resonant or near resonant with the localized surface-plasmon frequency of the metal structure. Small in this context is gauged in relation to the wavelength of light. The special preparations required to produce the effect, which include among other techniques electrochemical oxidation-reduction cycling, deposition of metal on very cold substrates, and the generation of metal-island films and colloids, is now understood to be necessary as a means of producing surfaces with appropriate electromagnetic resonances that may couple to electromagnetic fields either by generating rough films (as in the case of the former two examples) or by placing small metal particles in close proximity to one another (as in the case of the latter two). For molecules chemisorbed on SERS-active surface there exists a "chemical enhancement" in addition to the electromagnetic effect. Although difficult to measure accurately, the magnitude of this effect rarely exceeds a factor of 10 and is best thought to arise from the modification of the Raman polarizability tensor of the adsorbate resulting from the formation of a complex between the adsorbate and the metal. Rather than an enhancement mechanism, the chemical effect is more logically to be regarded as a change in the nature and identity of the adsorbate.

Surface-enhanced spectroscopy

https://easyspin.org/pubs/easyspin_jmr06.pdf

EasySpin, a comprehensive software package for spectral simulation and analysis in EPR.

A new general technique for the investigation of exchange processes in molecular systems is proposed and demonstrated. Applications comprise the study of chemical exchange, of magnetization transfer by inter‐ and intramolecular relaxation in liquids, and of spin diffusion and cross‐relaxation processes in solids.

Investigation of exchange processes by two‐dimensional NMR spectroscopy

THE determination of macromolecular structure by crystallography involves fitting atomic models to the observed diffraction data1. The traditional measure of the quality of this fit, and presumably the accuracy of the model, is theR value. Despite stereochemical restraints2, it is possible to overfit or 'misfit' the diffraction data: an incorrect model can be refined to fairly good R values as several recent examples have shown3. Here I propose a reliable and unbiased indicator of the accuracy of such models. By analogy with the cross-validation method4,5 of testing statistical models I define a statistical quantity (RfreeT) that measures the agreement between observed and computed structure factor amplitudes for a 'test' set of reflections that is omitted in the modelling and refinement process. As examples show, there is a high correlation between RfreeT and the accuracy of the atomic model phases. This is useful because experimental phase information is usually inaccurate, incomplete or unavailable. I expect that RfreeT will provide a measure of the information content of recently proposed models of thermal motion and disorder6–8, time-averaging9 and bulk solvent10.

Free R value: a novel statistical quantity for assessing the accuracy of crystal structures.

List of notation Introduction The dynamics of nuclear spin systems Manipulation of nuclear spin Hamiltonians One-dimensional Fourier spectroscopy Multiple-quantum transitions Two-dimensional Fourier spectroscopy Two-dimensional separation of interactions Two-dimensional correlation methods based on coherence transfer Dynamic processes studied by two-dimensional exchange spectroscopy Nuclear magnetic resonance imaging References Index.

/pdf/principles-of-nuclear-magnetic-resonance-in-one-and-two-4fuu9qo6xv.pdf

Principles of nuclear magnetic resonance in one and two dimensions

The possibilities for the extension of spectroscopy to two dimensions are discussed. Applications to nuclear magnetic resonance are described. The basic theory of two‐dimensional spectroscopy is developed. Numerous possible applications are mentioned and some of them treated in detail, including the elucidation of energy level diagrams, the observation of multiple quantum transitions, and the recording of high‐resolution spectra in inhomogenous magnetic fields. Experimental results are presented for some simple spin systems.

Richard R. Ernst

Papers

Principles of nuclear magnetic resonance in one and two dimensions

Investigation of exchange processes by two‐dimensional NMR spectroscopy

Two‐dimensional spectroscopy. Application to nuclear magnetic resonance

Coherence transfer by isotropic mixing: Application to proton correlation spectroscopy

Improved spectral resolution in cosy 1H NMR spectra of proteins via double quantum filtering.