Quantum Algorithms for the Jones Polynomial

This paper gives a generalization of the AJL algorithm and unitary braid group representation for quantum computation of the Jones polynomial to continuous ranges of values on the unit circle of the Jones parameter. We show that our 3-strand algorithm for the Jones polynomial is a special case of this generalization of the AJL algorithm. The present paper uses diagrammatic techniques to prove these results. The techniques of this paper have been used and will be used in the future in work with R. Marx, A. Fahmy, L. H. Kauffman, S. J. Lomonaco Jr.,A. Sporl, N. Pomplun, T. Schulte Herbruggen, J. M. Meyers, and S. J. Glaser on NMR quantum computation of the Jones polynomial.Comment: 11 pages, 4 figures, LaTeX documen

Dietrich Schulte-Frohlinde (1924 – 2015)

Professor Dietrich Schulte-Frohlinde, a distinguished German chemist with long-time relationships to Croatian scientists (e.g. S. Ašperger, M. Randić, J. N. Herak, A. Graovac, I. Kraljić), and this Journal, passed away on Oct 1st, 2015 in Chevy Chase MD, USA. He was born on Dec 17th, 1924 in Munich ... This work is licensed under a Creative Commons Attribution 4.0 International License

The Scenery of Knowledge"s Language-Game in Wittgenstein"s Philosophical Investigations

Our purpose is to take into account Wittgenstein"s analyses about knowledge in the Philosophical Investigations, in order to articulate them and elaborate a concept of knowledge (Wissen). My first claim is that this is possible. My second claim is that the complexity of this concept has not been taken into consideration and its originality has been misunderstood in the horizon of the Philosophy of Mind (Vohra, A. 1986), of Philosophy of Psychology (Schulte, J. 1993; Budd, M. 1989). My objection is that the analysis of "knowledgeâ€? presupposes the dissolution of mind and psychology. My third claim concerns the interpretation of the verb "to knowâ€? from K. Bühler"s point of view as a kind of signal (Signal), at least in some uses, and as a symbol or an expression in some others. This connection concerning "knowledgeâ€? has not been brought out in, e.g., (Hacker, P.M.S. 1993; von Savigny, E. and Scholz, O.R. 1995)

LISA Pathfinder: Mission and status

none100openF. Antonucci;M. Armano;H. Audley;G. Auger;M. Benedetti; P. Binetruy; C. Boatella; J. Bogenstahl; D. Bortoluzzi; P. Bosetti; M. Caleno; A. Cavalleri; M. Cesa; M. Chmeissani; G. Ciani; A. Conchillo; G. Congedo; I Cristofolini; M. Cruise; K. Danzmann; F. De Marchi; M. Diaz-Aguilo; I Diepholz; G. Dixon; R. Dolesi; N. Dumbar; J. Fauste; L. Ferraioli; D. Fertin; W. Fichter; E. Fitzsimons; M. Freschi; A Garcia Marin; C. Garcia Marirrodriga; R. Gerndt; L. Gesa; F. Gilbert; D. Giardini; C. Grimani; A. Grynagier; B. Guillaume; F. Guzman; I. Harrison; G. Heinzel; M. Hewitson; D. Hollington; J. Hough; D. Hoyland; M. Hueller; J. Huesler; O. Jeannin; O. Jennrich; P. Jetzer; B. Johlander; C. Killow; X. Llmas; I. Lloro; A. Lobo; R. Maarschalkerweerd; S. Madden; D. Mance; I. Mateos; P. W. McNamara; J. Mendes; E. Mitchell; A. Monsky; D. Nicolini; D. Nicolodi; M. Nofrarias; F. Pedersen; M. Perreur-Lloyd; A. Perreca; E. Plagnol; P. Prat; G. D. Racca; B. Rais; J. Ramos-Castro; J. Reiche; J. A. Romera Perez; D. Robertson; H. Rozemeijer; J. Sanjuan; A. Schleicher; M. Schulte; D. Shaul; L. Stagnaro; S. Strandmoe; F. Steier; T. J. Sumner; A. Taylor; D. Texier; C. Trenkel; D. Tombolato; S. Vitale; G. Wanner; H. Ward; S. Waschke; P. Wass; W. J. Weber; P. ZweifelF., Antonucci; M., Armano; H., Audley; G., Auger; M., Benedetti; P., Binetruy; C., Boatella; J., Bogenstahl; D., Bortoluzzi; P., Bosetti; M., Caleno; A., Cavalleri; M., Cesa; M., Chmeissani; G., Ciani; A., Conchillo; G., Congedo; I., Cristofolini; M., Cruise; K., Danzmann; F., De Marchi; M., Diaz Aguilo; I., Diepholz; G., Dixon; R., Dolesi; N., Dumbar; J., Fauste; L., Ferraioli; D., Fertin; W., Fichter; E., Fitzsimons; M., Freschi; A., Garcia Marin; C., Garcia Marirrodriga; R., Gerndt; L., Gesa; F., Gilbert; D., Giardini; Grimani, Catia; A., Grynagier; B., Guillaume; F., Guzman; I., Harrison; G., Heinzel; M., Hewitson; D., Hollington; J., Hough; D., Hoyland; M., Hueller; J., Huesler; O., Jeannin; O., Jennrich; P., Jetzer; B., Johlander; C., Killow; X., Llmas; I., Lloro; A., Lobo; R., Maarschalkerweerd; S., Madden; D., Mance; I., Mateos; P. W., Mcnamara; J., Mendes; E., Mitchell; A., Monsky; D., Nicolini; D., Nicolodi; M., Nofrarias; F., Pedersen; M., Perreur Lloyd; A., Perreca; E., Plagnol; P., Prat; G. D., Racca; B., Rais; J., Ramos Castro; J., Reiche; J. A., Romera Perez; D., Robertson; H., Rozemeijer; J., Sanjuan; A., Schleicher; M., Schulte; D., Shaul; L., Stagnaro; S., Strandmoe; F., Steier; T. J., Sumner; A., Taylor; D., Texier; C., Trenkel; D., Tombolato; S., Vitale; G., Wanner; H., Ward; S., Waschke; P., Wass; W. J., Weber; P., Zweife

Research Progress Reports, 1962. Fruit and Vegetable Processing and Technology Division, Department of Horticulture.

Tomato variety evaluation for processing, 1962 / W. A. Gould, J. R. Geisman and Wade Schulte -- Evaluation of snap bean varieties for processing, 1962 / Wilbur A. Gould -- Handling and holding studies of mechanically harvested tomatoes. 1. Processed product quality / W. A. Gould, W. D. Bash, J. R. Geisman, D. E. Yingst, G. A. Marlowe and W. N. Brown -- Handling and holding studies of mechanically harvested tomatoes. 2. Spore counts / Winston D. Bash and W. A. Gould -- Handling and holding studies of mechanically harvested tomatoes. 3. pH / Winston D. Bash and W. A. Gould -- Handling and holding studies of mechanically harvested tomatoes. 4. Chlorine residuals / Donald E. Yingst and W. A. Gould -- Removal of insects and residues from sweet corn by washing techniques / J. R. Geisman and W. A. Gould -- Removal of pesticides and radioactive fallout from fruits and vegetables / J. R. Geisman, R. P. Blackmore, R. W. Hirzel and W. S. Stinson -- The effect of apple variety and browning prevention treatments during preparation on the quality of frozen apple pies / D. Robert Davis and James F. Gallander -- Effect of three tomato peeling methods on efficiency and product quality / Wade A. Schulte and W. A. Gould -- Effects of cooling rates on vacuum of canned pumpkin / Winston D. Bash -- New flavors for sauerkraut / J. R. Geisman and Robert Reyda -- Flavor of tomato juice / Wilbur A. Gould, Natholyn Dalton and John Hal Johnson -- Fruit juice blends offer a promising new field for apple cider / D. Robert Davi

Processing and Technology of Fruits and Vegetables, 1960

Tomato Variety Evaluation for Processing, 1961 / W. A. Gould, J. R. Geisman and Wade Schulte -- Evaluation of Sweet Corn Varieties for Processing / J. R. Geisman and W. A. Gould -- Small Fruit Variety Evaluation Studies for Freezing / D. R. Davis and H. L. Stammer -- Evaluation of Apples for Processing. I. Fruit Juice Blends / D. R. Davis and H. L. Stammer -- Evaluation of Apples for Processing. II. Canned Apple Slices / D. R. Davis and H. L. Stammer -- Evaluation of Apples for Processing. III. Frozen Apple Slices / D. R. Davis and H. L. Stammer -- Evaluation of Apples for Processing. IV. Frozen Fruit Pies / D. R. Davis and H. L. Stammer -- A Study of Several Varieties of Pumpkin and Squash for Canning and Freezing for Use in Pies / Robert H. Clayton, J. R. Geisman and W. A. Gould -- Factors Effecting the Consistency of Cream Style Corn / D. R. Davis and W. A. Gould -- The Objective Measurement of Tomato Juice Consistency / Robert Kluter and W. A. Gould -- A Method for the Detection of Drosophila Fly Eggs and Larvae in Tomato Products / J. R. Geisman and Winston D. Bash -- A Chemical Study of Flavor and Flavor Substances in Tomatoes / John Hal Johnson and W. A. Gould -- Tannin Content Effects Grape Juice Quality / D. R. Davis and H. L. Stammer -- pH Survey for Tomatoes in Ohio / W. D. Bash -- Flavor Studies with Sauerkraut / J. R. Geisman, S. S. Verma and W. A. Gould -- The Effect of Fill Weight on Drained Weight of Canned Tomatoes / Wade A. Schulte and W. A. Gould -- A New Method for the Manufacture of Apple Sirup / M. P. Baldauf, D. R. Davis and H. L. Stammer -- Studies on Color Retention in Canned R.T.P. Cherries / D. R. Davis and H. L. Stammer -- Clumping Studies in Canned Blueberries / D. R. Davis and H. L. Stammer -- Infra-red Peeling Studies. I. Apples. / L. Lafferty and W. A. Gould -- Infra-red Peeling Studies. II. Tomatoes. / W. A. Gould, Richard Leiss and Donall Streets -- The Effect of Water Holding Times and Temperatures on Quality of Tomatoes / Richard Leiss, Ernest Anderson and W. A. Gould -- Quality Attributes of Sweet Potatoes - Glass Packed / Donald A. Giesser and W. A. Gould -- A Study of Some of the Factors Effecting the Efficiency of Washing of Fruits and Vegetables. I. Tomatoes / W. A. Gould and J. R. Geisman -- A Study of Some of the Factors Effecting the Efficiency of Washing of Fruits and Vegetables. II. Sweet Corn / J. R. Geisman and W. A. Gould -- A Study of Alpha-keto Acids, Amino Acids, and Citric Acid in Eight Tomato Varieties, and Their Changes During Processing / Mokhtar M. Hamdy and W. A. Goul

Colour image denoising by eigenvector analysis of neighbourhood colour samples

[EN] Colour image smoothing is a challenging task because it is necessary to appropriately distinguish between noise and original structures, and to smooth noise conveniently. In addition, this processing must take into account the correlation among the image colour channels. In this paper, we introduce a novel colour image denoising method where each image pixel is processed according to an eigenvector analysis of a data matrix built from the pixel neighbourhood colour values. The aim of this eigenvector analysis is threefold: (i) to manage the local correlation among the colour image channels, (ii) to distinguish between flat and edge/textured regions and (iii) to determine the amount of needed smoothing. Comparisons with classical and recent methods show that the proposed approach is competitive and able to provide significative improvements.Latorre-Carmona, P.; Miñana, J.; Morillas, S. (2020). Colour image denoising by eigenvector analysis of neighbourhood colour samples. Signal Image and Video Processing. 14(3):483-490. https://doi.org/10.1007/s11760-019-01575-5S483490143Plataniotis, K.N., Venetsanopoulos, A.N.: Color Image Processing and Applications. Springer, Berlin (2000)Lukac, R., Smolka, B., Martin, K., Plataniotis, K.N., Venetsanopoulos, A.N.: Vector Filtering for Color Imaging. IEEE Signal Processing Magazine, Special Issue on Color Image Processing 22, 74–86 (2005)Lukac, R., Plataniotis, K.N.: A taxonomy of color image filtering and enhancement solutions. In: Hawkes, P.W. (ed.) Advances in Imaging and Electron Physics, vol. 140, pp. 187–264. Elsevier Acedemic Press, Amsterdam (2006)Buades, A., Coll, B., Morel, J.M.: Nonlocal image and movie denoising. Int. J. Comput. Vis. 76, 123–139 (2008)Tomasi, C., Manduchi, R.: Bilateral filter for gray and color images. In: Proceedings of IEEE International Conference Computer Vision, pp. 839–846 (1998)Elad, M.: On the origin of bilateral filter and ways to improve it. IEEE Trans. Image Process. 11, 1141–1151 (2002)Kao, W.C., Chen, Y.J.: Multistage bilateral noise filtering and edge detection for color image enhancement. IEEE Trans. Consum. Electron. 51, 1346–1351 (2005)Garnett, R., Huegerich, T., Chui, C., He, W.: A universal noise removal algorithm with an impulse detector. IEEE Trans. Image Process. 14, 1747–1754 (2005)Morillas, S., Gregori, V., Sapena, A.: Fuzzy Bilateral Filtering for color images. Lecture Notes Comput. Sci. 4141, 138–145 (2006)Zhang, B., Allenbach, J.P.: Adaptive bilateral filter for sharpness enhancement and noise removal. IEEE Trans. Image Process. 17, 664–678 (2008)Kenney, C., Deng, Y., Manjunath, B.S., Hewer, G.: Peer group image enhancement. IEEE Trans. Image Process. 10, 326–334 (2001)Morillas, S., Gregori, V., Hervás, A.: Fuzzy peer groups for reducing mixed Gaussian-impulse noise from color images. IEEE Trans. Image Process. 18, 1452–1466 (2009)Plataniotis, K.N., Androutsos, D., Venetsanopoulos, A.N.: Adaptive fuzzy systems for multichannel signal processing. Proc. IEEE 87, 1601–1622 (1999)Schulte, S., De Witte, V., Kerre, E.E.: A fuzzy noise reduction method for colour images. IEEE Trans. Image Process. 16, 1425–1436 (2007)Shen, Y., Barner, K.: Fuzzy vector median-based surface smoothing. IEEE Trans. Vis. Comput. Graph. 10, 252–265 (2004)Lukac, R., Plataniotis, K.N., Smolka, B., Venetsanopoulos, A.N.: cDNA microarray image processing using fuzzy vector filtering framework. Fuzzy Sets Syst. 152, 17–35 (2005)Smolka, B.: On the new robust algorithm of noise reduction in color images. Comput. Graph. 27, 503–513 (2003)Van de Ville, D., Nachtegael, M., Van der Weken, D., Philips, W., Lemahieu, I., Kerre, E.E.: Noise reduction by fuzzy image filtering. IEEE Trans. Fuzzy Syst. 11, 429–436 (2003)Schulte, S., De Witte, V., Nachtegael, M., Van der Weken, D., Kerre, E.E.: Histogram-based fuzzy colour filter for image restoration. Image Vis. Comput. 25, 1377–1390 (2007)Nachtegael, M., Schulte, S., Van der Weken, D., De Witte, V., Kerre, E.E.: Gaussian noise reduction in grayscale images. Int. J. Intell. Syst. Technol. Appl. 1, 211–233 (2006)Schulte, S., De Witte, V., Nachtegael, M., Mélange, T., Kerre, E.E.: A new fuzzy additive noise reduction method. Lecture Notes Comput. Sci. 4633, 12–23 (2007)Morillas, S., Schulte, S., Mélange, T., Kerre, E.E., Gregori, V.: A soft-switching approach to improve visual quality of colour image smoothing filters. In: Proceedings of Advanced Concepts for Intelligent Vision Systems ACIVS07, Lecture Notes in Computer Science, vol. 4678, pp. 254–261 (2007)Lucchese, L., Mitra, S.K.: A new class of chromatic filters for color image processing: theory and applications. IEEE Trans. Image Process. 13, 534–548 (2004)Lee, J.A., Geets, X., Grégoire, V., Bol, A.: Edge-preserving filtering of images with low photon counts. IEEE Trans. Pattern Anal. Mach. Intell. 30, 1014–1027 (2008)Russo, F.: Technique for image denoising based on adaptive piecewise linear filters and automatic parameter tuning. IEEE Trans. Instrum. Meas. 55, 1362–1367 (2006)Shao, M., Barner, K.E.: Optimization of partition-based weighted sum filters and their application to image denoising. IEEE Trans. Image Process. 15, 1900–1915 (2006)Ma, Z., Wu, H.R., Feng, D.: Partition based vector filtering technique for suppression of noise in digital color images. IEEE Trans. Image Process. 15, 2324–2342 (2006)Ma, Z., Wu, H.R., Feng, D.: Fuzzy vector partition filtering technique for color image restoration. Comput. Vis. Image Underst. 107, 26–37 (2007)Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. Pattern Anal. Mach. Intell. 12, 629–639 (1990)Sroubek, F., Flusser, J.: Multichannel blind iterative image restoration. IEEE Trans. Image Process. 12, 1094–1106 (2003)Hu, J., Wang, Y., Shen, Y.: Noise reduction and edge detection via kernel anisotropic diffusion. Pattern Recognit. Lett. 29, 1496–1503 (2008)Li, X.: On modeling interchannel dependency for color image denoising. Int. J. Imaging Syst. Technol., Special issue on applied color image processing 17, 163–173 (2007)Keren, D., Gotlib, A.: Denoising color images using regularization and correlation terms. J. Vis. Commun. Image Represent. 9, 352–365 (1998)Lezoray, O., Elmoataz, A., Bougleux, S.: Graph regularization for color image processing. Comput. Vis. Image Underst. 107, 38–55 (2007)Elmoataz, A., Lezoray, O., Bougleux, S.: Nonlocal discrete regularization on weighted graphs: a framework for image and manifold processing. IEEE Trans. Image Process. 17, 1047–1060 (2008)Blomgren, P., Chan, T.: Color TV: total variation methods for restoration of vector-valued images. IEEE Trans. Image Process. 7, 304–309 (1998)Tschumperlé, D., Deriche, R.: Vector-valued image regularization with PDEs: a common framework from different applications. IEEE Trans. Pattern Anal. Mach. Intell. 27, 506–517 (2005)Plonka, G., Ma, J.: Nonlinear regularized reaction-diffusion filters for denoising of images with textures. IEEE Trans. Image Process. 17, 1283–1294 (2007)Melange, T., Zlokolica, V., Schulte, S., De Witte, V., Nachtegael, M., Pizurca, A., Kerre, E.E., Philips, W.: A new fuzzy motion and detail adaptive video filter. Lecture Notes Comput. Sci. 4678, 640–651 (2007)De Backer, S., Pizurica, A., Huysmans, B., Philips, W., Scheunders, P.: Denoising of multicomponent images using wavelet least-squares estimators. Image Vis. Comput. 26, 1038–1051 (2008)Dengwen, Z., Wengang, C.: Image denoising with an optimal threshold and neighboring window. Pattern Recognit. Lett. 29, 1694–1697 (2008)Schulte, S., Huysmans, B., Pizurica, A., Kerre, E.E., Philips, W.: A new fuzzy-based wavelet shrinkage image denoising technique. In: Proceedings of Advanced Concepts for Intelligent Vision Systems ACIVS06, Lecture Notes in Computer Science, vol. 4179, pp. 12–23 (2006)Pizurica, A., Philips, W.: Estimating the probability of the presence of a signal of interest in multiresolution single and multiband image denoising. IEEE Trans. Image Process. 15, 654–665 (2006)Scheunders, P.: Wavelet thresholding of multivalued images. IEEE Trans. Image Process. 13, 475–483 (2004)Sendur, L., Selesnick, I.W.: Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency. IEEE Trans. Signal Process. 50, 2744–2756 (2002)Balster, E.J., Zheng, Y.F., Ewing, R.L.: Feature-based wavelet shrinkage algorithm for image denoising. IEEE Trans. Image Process. 14, 2024–2039 (2005)Miller, M., Kingsbury, N.: Image denoising using derotated complex wavelet coefficients. IEEE Trans. Image Process. 17, 1500–1511 (2008)Zhang, B., Fadili, J.M., Starck, J.L.: Wavelets, ridgelets, and curvelets for poisson noise removal. IEEE Trans. Image Process. 17, 1093–1108 (2008)Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3D transform-domain collaborative filtering. IEEE Trans. Image Process. 16, 2080–2095 (2007)Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Color image denoising via sparse 3D collaborative filtering with grouping constraint in luminance-chrominance space. In: Proceedings of the IEEE International Conference on Image Processing ICIP2007 , pp. 313–316 (2007)Hao, B.B., Li, M., Feng, X.C.: Wavelet iterative regularization for image restoration with varying scale parameter. Signal Process. Image Commun. 23, 433–441 (2008)Zhao, W., Pope, A.: Image restoration under significat additive noise. IEEE Signal Process. Lett. 14, 401–404 (2007)Gijbels, I., Lambert, A., Qiu, P.: Edge-preserving image denoising and estimation of discontinuous surfaces. IEEE Trans. Pattern Anal. Mach. Intell. 28, 1075–1087 (2006)Liu, C., Szeliski, R., Kang, S.B., Zitnik, C.L., Freeman, W.T.: Automatic estimation and removal of noise from a single image. IEEE Trans. Pattern Anal. Mach. Intell. 30, 299–314 (2008)Oja, E.: Principal components, minor components, and linear neural networks. Neural Netw. 5, 927–935 (1992)Takahashi, T.: Kurita, T.: Robust de-noising by kernel PCA. In: Proceedings of ICANN2002, Lecture Notes in Computer Science, vol. 2145, pp. 739–744 (2002)Park, H., Moon, Y.S.: Automatic denoising of 2D color face images using recursive PCA reconstruction. In: Proceedings of Advanced Concepts for Intelligent Vision Systems ACIVS06, Lecture Notes in Computer Science, vol. 4179, pp. 799–809 (2006)Teixeira, A.R., Tomé, A.M., Stadlthanner, K., Lang, E.W.: KPCA denoising and the pre-image problem revisited. Digital Signal Process. 18, 568–580 (2008)Astola, J., Haavisto, P., Neuvo, Y.: Vector median filters. Proc. IEEE 78, 678–689 (1990)Morillas, S., Gregori, V., Sapena, A.: Adaptive marginal median filter for colour images. Sensors 11, 3205–3213 (2011)Morillas, S., Gregori, V.: Robustifying vector median filter. Sensors 11, 8115–8126 (2011)Dillon, W.R., Goldstein, M.: Multivariate Analysis: Methods and Applications. Wiley, Hoboken (1984)Jackson, J.E.: A User’s Guide to Principal Components. Wiley, Hoboken (2003)Camacho, J., Picó, J.: Multi-phase principal component analysis for batch processes modelling. Chemom. Intell. Lab. Syst. 81, 127–136 (2006)Nomikos, P., MacGregor, J.: Multivariate SPC charts for monitoring batch processes. Technometrics 37, 41–59 (1995)Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)Grecova, Svetlana, Morillas, Samuel: Perceptual similarity between color images using fuzzy metrics. J. Vis. Commun. Image Represent. 34, 230–235 (2016)Fairchild, M.D., Johnson, G.M.: iCAM framework for image appearance differences and quality. J. Electron. Imaging 13(1), 126–138 (2004)Immerkaer, J.: Fast noise variance estimation. Comput. Vis. Image Underst. 64, 300–302 (1996

Treatment approaches for dual diagnosis clients in England

Introduction - Dual diagnosis (DD, co-occurrence of substance use and mental health problems) prevalence data in England are limited to specific regions and reported rates vary widely. Reliable information on actual service provision for dual diagnosis clients has not been collated. Thus a national survey was carried out to estimate dual diagnosis prevalence in treatment populations and describe the service provision available for this client population in drug/alcohol (DAS) and mental health services (MHS). Design - A questionnaire was sent to managers of 706 DAS and 2374 MHS. Overall, 249 (39%) DAS and 493 (23%) MHS participated in the survey. Results - In both DAS and MHS, around 32% of clients were estimated to have dual diagnosis problems. However, fewer than 50% of services reported assessing clients for both problem areas. Regarding specific treatment approaches, most services (DAS: 88%, MHS: 87%) indicated working jointly with other agencies. Significantly fewer services used joint protocols (DAS: 55%, MHS: 48%) or shared care arrangements, including access to external drug/alcohol or mental health teams (DAS: 47%, MHS: 54%). Only 25% of DAS and 17% of MHS employed dual diagnosis specialists. Conclusions - Dual diagnosis clients constitute a substantial proportion of clients in both DAS and MHS in England. Despite recent policy initiatives, joint working approaches tend to remain unstructured

Optimal Control for Generating Quantum Gates in Open Dissipative Systems

Optimal control methods for implementing quantum modules with least amount of relaxative loss are devised to give best approximations to unitary gates under relaxation. The potential gain by optimal control using relaxation parameters against time-optimal control is explored and exemplified in numerical and in algebraic terms: it is the method of choice to govern quantum systems within subspaces of weak relaxation whenever the drift Hamiltonian would otherwise drive the system through fast decaying modes. In a standard model system generalising decoherence-free subspaces to more realistic scenarios, openGRAPE-derived controls realise a CNOT with fidelities beyond 95% instead of at most 15% for a standard Trotter expansion. As additional benefit it requires control fields orders of magnitude lower than the bang-bang decouplings in the latter.Comment: largely expanded version, superseedes v1: 10 pages, 5 figure