The Experts below are selected from a list of 107394 Experts worldwide ranked by ideXlab platform

F. Prindle - One of the best experts on this subject based on the ideXlab platform.

Kazunori Ueda - One of the best experts on this subject based on the ideXlab platform.

  • logic constraint programming and concurrency the hard won lessons of the fifth Generation Computer project
    Science of Computer Programming, 2017
    Co-Authors: Kazunori Ueda
    Abstract:

    Abstract The technical goal of the Fifth Generation Computer Systems (FGCS) project (1982–1993) was to develop Parallel Inference technologies, namely systematized technologies for realizing knowledge information processing on top of parallel Computer architecture. The Logic Programming paradigm was adopted as the central working hypothesis of the project. At the same time, building a large-scale Parallel Inference Machine (PIM) meant to develop a novel form of general-purpose computing technologies that are powerful enough to express various parallel algorithms and to describe a full operating system of PIM. Accordingly, the research goal of the Kernel Language was set to designing a concurrent and parallel programming language under the working hypothesis of Logic Programming. The aim of this article is to describe the design process of the Kernel Language (KL1) in the context of related programming models in the 1980s, the essence of Concurrent Logic Programming and Constraint-Based Concurrency, and how the technologies we developed in those days evolved after their conception.

  • logic constraint programming and concurrency the hard won lessons of the fifth Generation Computer project
    International Symposium on Functional and Logic Programming, 2016
    Co-Authors: Kazunori Ueda
    Abstract:

    The technical goal of the Fifth Generation Computer Systems (FGCS) project (1982–1993) was to develop Parallel Inference technologies, namely systematized technologies for realizing knowledge information processing on top of parallel Computer architecture [8].

Warwick P. Bowen - One of the best experts on this subject based on the ideXlab platform.

  • free spectral range electrical tuning of a high quality on chip microcavity
    Optics Express, 2018
    Co-Authors: Christiaan Bekker, Christopher G. Baker, Rachpon Kalra, Han-hao Cheng, Varun Prakash, Warwick P. Bowen
    Abstract:

    Reconfigurable photonic circuits have applications ranging from next-Generation Computer architectures to quantum networks, coherent radar and optical metamaterials. Here, we demonstrate an on-chip high quality microcavity with resonances that can be electrically tuned across a full free spectral range (FSR). FSR tuning allows resonance with any source or emitter, or between any number of networked microcavities. We achieve it by integrating nanoelectronic actuation with strong optomechanical interactions that create a highly geometry-dependent effective refractive index. This allows low voltages and sub-nanowatt power consumption. We demonstrate a basic reconfigurable photonic network, bringing the microcavity into resonance with an arbitrary mode of a microtoroidal optical cavity across a telecommunications fibre link. Our results have applications beyond photonic circuits, including widely tuneable integrated lasers, reconfigurable optical filters for telecommunications and astronomy, and on-chip sensor networks.

  • free spectral range electrical tuning of a high quality on chip microcavity
    arXiv: Applied Physics, 2018
    Co-Authors: Christiaan Bekker, Christopher G. Baker, Rachpon Kalra, Han-hao Cheng, Varun Prakash, Warwick P. Bowen
    Abstract:

    Reconfigurable photonic circuits have applications ranging from next-Generation Computer architectures to quantum networks, coherent radar and optical metamaterials. However, complete reconfigurability is only currently practical on millimetre-scale device footprints. Here, we overcome this barrier by developing an on-chip high quality microcavity with resonances that can be electrically tuned across a full free spectral range (FSR). FSR tuning allows resonance with any source or emitter, or between any number of networked microcavities. We achieve it by integrating nanoelectronic actuation with strong optomechanical interactions that create a highly strain-dependent effective refractive index. This allows low voltages and sub-nanowatt power consumption. We demonstrate a basic reconfigurable photonic network, bringing the microcavity into resonance with an arbitrary mode of a microtoroidal optical cavity across a telecommunications fibre link. Our results have applications beyond photonic circuits, including widely tuneable integrated lasers, reconfigurable optical filters for telecommunications and astronomy, and on-chip sensor networks.

Von Zuben F.j. - One of the best experts on this subject based on the ideXlab platform.

  • Synthesis Of Spatio-temporal Models By The Evolution Of Non-uniform Cellular Automata
    Springer Verlag, 2015
    Co-Authors: Romano A.l., Villanueva W.j., Zanetti M.s., Von Zuben F.j.
    Abstract:

    Non-uniform or inhomogeneous cellular automata (NunCA) [28] are spatio-temporal models for dynamical systems in which space and time are discrete, and there is a distinct transition rule for each cell, with a finite number of states. The cells are in a regular lattice and the transition from one state to another is performed synchronously. The next state of a given cell will then be provided by a local and fixed transition rule that associates its current state and the current state of the neighbouring cells with the next state. The neighbourhood could also be specific for each cell, but will be considered the same, except for the cells at the frontiers of the regular lattice. So, the only distinct feature between NunCA and the traditional uniform cellular automata (CA) [29,34] is the adoption of a specific transition rule for each cell instead of a single transition rule for all the cells in the lattice. © 2009 Springer-Verlag Berlin Heidelberg.20485104Bäck, T., Hoffmeister, F., Schwefel, H.-P., Survey of Evolution Strategies (1991) Proceedings of the 4th International Conference on Genetic Algorithms, pp. 2-9Basanta, D., Miodownik, M.A., Bentley, P.J., Holm, E.A., Investigating the Evolvability of Biologically Inspired CA (2004) Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems, ALIFE9Beyer, H., Schwefel, H., (2002) Evolution strategies: A comprehensive introduction, , Natural ComputingCamazine, S., Deneubourg, J.-L., Franks, N.R., Sneyd, J., Theraulaz, G., Bonabeau, E., (2001) Self-Organization in Biological Systems, , Princeton University Press, PrincetonChua, L.O., Yang, L., Cellular Neural Networks: Theory (1988) IEEE Transactions on Circuits and Systems, 35 (10), pp. 1257-1272Chopard, B., (1998) Cellular automata modeling of physical systems, , Cambridge University Press, CambridgeCollasanti, R.L., Grime, J.P., Resource dynamics and vegetation process: A deterministic model using two-dimensional cellular automata (1993) Functional Ecology, 7, pp. 169-176Frisch, U., Hasslacher, B., Pomeau, Y., Lattice-gas automata for the Navier-Stokes equation (1986) Physical Review Letters, 56, pp. 1505-1508Golberg, D.E., (1989) Genetic Algorithms in Search, Optimization & Machine Learning, , Addison-Wesley, ReadingGregorio, S.D., Serra, R., An empirical method for modelling and simulating some complex macroscopic phenomena by cellular automata (1999) Future Generation Computer Systems, 16, pp. 259-271Gutowitz, H., Langton, C., (1988) Methods for Designing 'Interesting' Cellular Automata, , CNLS News LetterHillman, D., (1995) Combinatorial Spacetimes, , Ph.D. Thesis, University of PittsburghIlachinski, H.P., Structurally dynamic cellular automata (1987) Complex Systems, 1, pp. 503-527Jai, A.E., (1999) Nouvelle approche pour la modélisation des systèmes en expansion spatiale: Dynamique de végétation, Tendences nouvelles en modélisation pour l'environnement, pp. 439-445. , Elsevier, AmsterdamKagaris, D., Tragoudas, S., Von Neumann Hybrid Cellular Automata for Generating Deterministic Test Sequences (2001) ACM Trans. On Design Automation of Electronic Systems, 6 (3), pp. 308-321(1993) Theory and Applications of Coupled Map Lattices, , Kaneko, K, ed, Wiley, ChichesterLi, W., (1991) Phenomenology of Non-Local Cellular Automata, , Santa Fe Institute Working Paper 91-01-001Maji, P., Ganguly, N., Saha, S., Roy, A.K., Chaudhuri, P.P.: Cellular Automata Machine for Pattern Recognition. In: Bandini, S., Chopard, B., Tomassini, M. (eds.) ACRI 2002. LNCS, 2493, pp. 270-281. Springer, Heidelberg (2002)Mitchell, M., Hraber, P., Crutchfiled, J., Revisiting the edge of chaos: Evolving cellular automata to perform computations (1993) Complex Systems, 7, pp. 89-130Mitchell, M., Crutchfield, J.P., Das, R., Evolving Cellular Automata with Genetic Algorithms: A Review of Recent Work (1996) Proceedings of the First International Conference on Evolutionary Computation and Its ApplicationsNagel, K., Herrmann, H.J., Deterministic models for traffic jams (1993) Physica A, 199, pp. 254-269Nicolis, G., Prigogine, I., (1977) Self-organization in non-equilibrium systems, , Wiley, ChichesterOliveira, G.M.B., de Oliveira, P.P.B., Omar, N., Definition and Application of a Five-Parameter Characterization of Unidimensional Cellular Automata Rule Space (2001) Artificial Life, 7, pp. 277-301Rabino, G.A., Laghi, A.: Urban Cellular Automata: The Inverse Problem. In: Bandini, S., Chopard, B., Tomassini, M. (eds.) ACRI 2002. LNCS, 2493, pp. 349-356. Springer, Heidelberg (2002)Romano, A.L.T., Gomes, L., Gomes, G., Puma-Villanueva, W., Zanetti, M., Von Zuben, C.J., Von Zuben, F.J., Evolutionary Modeling of Larval Dispersal in Blowflies Using Non-Uniform Cellular Automata (2006) IEEE Congress on Evolutionary Computation, pp. 3872-3879Schönfisch, B., de Roos, A., Synchronous and asynchronous updating in cellular automata (1999) Biosystems, 51 (3), pp. 123-143Schwefel, H.-P., (1981) Numerical Optimization of Computer Models, , Wiley, ChichesterSipper, M., Non-Uniform Cellular Automata: Evolution in Rule Space and Formation of Complex Structures (1994) Artificial Life IV, pp. 394-399. , MIT Press, CambridgeToffoli, T., Margolus, N., (1987) Cellular automata machines - A new environment for modeling, , MIT Press, CambridgeTomassini, M., Perrenoud, M., Cryptography with cellular automata (2001) Applied Soft Computing, 1 (2), pp. 151-160Tomassini, M., Sipper, M., Zolla, M., Perrenould, M., Generating high-quality random numbers in parallel by cellular automata (1999) Future Generation Computer Systems, 16, pp. 291-305Tsalides, P., Cellular automata based build-in self test structures for VLSI systems (1990) IEE-Electronics Letters, 26 (17), pp. 1350-1352Vassilev, V.K., Miller, J.F., Fogarty, T.C., The Evolution of computation in coevolving demes of non-uniform cellular automata for global synchronization (1999) Proceedings of the 5th European Conference on Artificial Life, , BerlinVon Neumann, J., The General and Logical Theory of Automata, John von Neumann: Collected Works (1961) Design of Computer, Theory of Automata and Numerical Analysis, 5. , Taub, A.H, ed, Pergamon Press, OxfordWolfram, S., (1994), Cellular Automata and Complexity, Collected Papers. Addison-Wesley Publishing Company, Readin

  • Evolutionary Modeling Of Larval Dispersal In Blowflies Using Non-uniform Cellular Automata
    2015
    Co-Authors: Romano A.l.t., Von Zuben F.j., Gomes L., Gomes G., Puma-villanueva W., Zanetti M.
    Abstract:

    When the food supply flnishes, or when the larvae of blowflies complete their development and migrate prior to the total removal of the larval substrate, they disperse to find adequate places for pupation, a process known as post-feeding larval dispersal. Based on experimental data of the Initial and final configuration of the dispersion, the reproduction of such spatio-temporal behavior is achieved here by means of the evolutionary search for cellular automata with a distinct transition rule associated with each cell, also known as a nonuniform cellular automata, and with two states per cell in the lattice. Two-dimensional regular lattices and multivalued states will be considered and a practical question is the necessity of discovering a proper set of transition rules. Given that the number of rules is related to the number of cells in the lattice, the search space is very large and an evolution strategy is then considered to optimize the parameters of the transition rules, with two transition rules per cell. As the parameters to be optimized admit a physical interpretation, the obtained computational model can be analyzed to raise some hypothetical explanation of the observed spatiotemporal behavior. © 2006 IEEE.11271134Bäck, T., Hoffmeister, F., Schwefel, H.-P., A Survey of Evolution Strategies (1991) Proc. of the 4th Int. Conf. on GAs, pp. 2-9. , L. B. Belew and Booker, R. K, eds, San Diego, CABasanta, D., Miodownik, M.A., Bentley, P.J., Holm, E.A., Investigating the Evolvability of Biologically Inspired CABoldrini, J.L., Bassanezi, R.C., Moretti, A.C., Von Zuben, C.J., Godoy, W.A.C., Von Zuben, F.J., Reis, S.F., Non- local interactions and the dynamics of dispersal in immature insects (1997) Journal of Theoretical Biology, 185, pp. 523-531Camazine, S., Deneubourg, J.-L., Franks, N.R., Sneyd, J., Theraulaz, G., Bonabeau, E., (2001) Self-Organization in Biological Systems, , Princeton University PressChua, L.O., Yang, L., Cellular Neural Networks: Theory (1988) IEEE Trans, on Circuits and Systems, 35 (10), pp. 1257-1272. , OctoberChopard, B., (1998) Cellular automata modeling of physical systems, , Cambridge University PressCollasanti, R.L., Grime, J.P., Resource dynamics and vegetation process: A deterministic model using two-dimensional cellular automata (1993) Functional Ecology, 7, pp. 169-176De Jong, G., A model of competition for food. I. Frequencydependent viabilities (1976) American Naturalist, 110, pp. 1013-1027Dimou, L., Koutsikopoulus, A.P., Economopoulus, A.P., Lykakis, J., Depth of pupation of the olive fruit fly, Bactrocera (Dacus) oleae (Gmel.) (Dipt., Tephritidae), as affected by soil abiotic factors (2001) Journal of Applied Entomology, 127, pp. 12-17Frisch, U., Hasslacher, B., Pomeau, Y., Lattice-gas automata for the Navier-Stokes equation (1986) Phys. Rev. Lett, 56, pp. 1505-1508Gaines, S.D., Bertness, M., The dynamics of juvenile dispersal: Why field ecologiste must integrate (1993) Ecology, 74, pp. 2430-2435Gomes, L., Von Zuben, C.J., Postfeeding radial dispersal in larvae of Chrysomya albiceps (Díptera: Calliphoridae): implications for forensic entomology (2005) Forensic Science International, , in pressGoodbrod, J.R., Goff, M.L., Effects of larval population density on rates of development and interactions between two species of Chrysomya (Diptera: Calliphoridae) in laboratory culture (1990) Journal of Medical Entomology, 27, pp. 338-343Greenberg, B., Behavior of postfeeding larvae of some Calliphoridae and a muscid (Diptera) (1990) Annals of the Entomological Society of America, 83, pp. 1210-1214Gregorio, S.D., Serra, R., An empirical method for modelling and simulating some complex macroscopic phenomena by cellular automata (1999) Future Generation Computer Systems, 16, pp. 259-271Gutowitz, H., Langton, C., Methods for Designing 'Interesting' Cellular Automata (1988) CNLS News, , LetterJai, A.E., Nouvelle approche pour la modélisation des systèmes en expansion spatiale: Dynamique de végétation, Tendences nouvelles en modélisation pour l'environnement (1999) Elsevier, 439-445(1993) Theory and Applications of Coupled Map Lattices, , Kaneko, K, Ed, Wiley, New YorkLevot, G.W., Brown, K.R., Shipp, E., Larval growth of some calliphorid and sarcophagid Diptera (1979) Bulletin of Entomological Research, 69, pp. 469-475Lomnicki, A., (1988) Population ecology of individuals, , Princeton Press, 233 pMaji, P., Ganguly, N., Saha, S., Roy, A.K., Chaudhuri, P.P., Cellular Automata Machine for Pattern Recognition (2002) Lecture Notes In Computer Science, 2493, pp. 270-281. , Springer-Verlag, LondonMitchell, M., Hraber, P., Crutchfiled, J., Revisiting the edge of chaos: Evolving cellular automata to perform computations (1993) Complex Systems, 7, pp. 89-130Mueller, L.D., Density-dependent population growth and natural selection in food-limited environments: The Drosophila model (1988) American Naturalist, 132, pp. 786-809Nagel, K., Herrmann, H.J., Deterministic models for traffic jams (1993) Physica A, 199, pp. 254-269Nicolis, G., Prigogine, I., (1977) Self-organization in non-equilibrium systems, , WileyRabino, G. A., & Laghi, A. Urban Cellular Automata: The Inverse Problem. Bandini, S., & Chopard, B., & Tomassini, M. (Eds.): ACRI 2002, LNCS 2493, pp. 349-356, Springer-Verlag Berlin Heidelberg, 2002Reis, S.F., Stangenhaus, G., Godoy, W.A.C., Von Zuben, C.J., Ribeiro, O.B., Variação em caracteres bionômicos em função de densidade larval em Chrysomya megacepala e Chrysomya putoria (Diptera : Calliphoridae) (1994) Revista Brasileira de Entomologia, 38, pp. 33-34Schönfisch, B., de Roos, A., Synchronous and asynchronous updating in cellular automata (1999) Biosystems, 51 (3), pp. 123-143. , SeptemberSchwefel, H.-P., (1981) Numerical Optimization of Computer Models, , Wiley, ChichesterSipper, M., Non-Uniform Cellular Automata: Evolution in Rule Space and Formation of Complex Structures (1994) Artificial Life IV, pp. 394-399. , RA Brooks and P. Maes, editors, The MIT PressSmith K. G. V., A manual of forensic entomology. Ithaca, Cornell University Press, 1986Toffoli, T., Margolus, N., (1987) Cellular automata machines-A new environment for modeling, , The Mit PressTomassini, M., Perrenoud, M., Cryptography with cellular automata (2001) Applied Soft Computing, 1 (2), pp. 151-160. , AugustTomassini, M., Sipper, M., Zolla, M., Perrenould, M., Generating high-quality random numbers in parallel by cellular automata (1999) Future Generation Computer Systems, 16, pp. 291-305Turchin, P., Population consequences of aggregative movement (1998) Journal of Animal Ecology, 58, pp. 75-100Vassilev, V.K., Miller, J.F., Fogarty, T.C., The Evolution of computation in co-evolving demes of non-uniform cellular automata for global synchronization (1999) Proceedings of the 5 lh European Conference on Artificial Life, BerlinVon Neumann, J. The General and Logical Theory of Automata, John von Neumann: Collected Works, 5: Desing of Computer, Theory of Automata and Numerical Analysis, Taub, A.H.(ed), Oxford: Pergamon Press, 1961Wolfram, S., (1994), Cellular Automata and Complexity, Collected Papers. Addison-Wesley Publishing Compan

  • Multivariate Ant Colony Optimization In Continuous Search Spaces
    2015
    Co-Authors: De Franca F.o., Von Zuben F.j., Coelho G.p., De Faissol Attux R.r.
    Abstract:

    This work introduces an ant-inspired algorithm for optimization in continuous search spaces that is based on the Generation of random vectors with multivariate Gaussian pdf. The proposed approach is called MACACO - Multivariate Ant Colony Algorithm for Continuous Optimization - and is able to simultaneously adapt all the dimensions of the random distribution employed to generate the new individuals at each iteration. In order to analyze MACACO's search efficiency, the approach was compared to a pair of counterparts: the Continuous Ant Colony System (CACS) and the approach known as Ant Colony Optimization in Rn (ACOR). The comparative analysis, which involves wellknown benchmark problems from the literature, has indicated that MACACO outperforms CACS and ACOR in most cases as the quality of the final solution is concerned, and it is just about two times more costly than the least expensive contender. Copyright 2008 ACM.916Bilchev, G., Parmee, I.C., The ant colony metaphor for searching continuous design spaces (1995) Lecture Notes in Computer Science, 993, pp. 25-39. , T. C. Fogarty, editor, Evolutionary Computing, AISB Workshop, of, SpringerBox, G.E.P., Muller, M.A., A note on the Generation of random normal deviates (1958) Annals. Math. Stat, 29, pp. 610-611de França, F.O., Von Zuben, F.J., de Castro, L.N., Max min ant system and capacitated p-medians: Extensions and improved solutions (2005) Informatica (Slovenia), 29 (2), pp. 163-172Dorigo, M., (1992) Optimization, Learning and Natural Algorithms, , PhD thesis, Politecnico di Milano, ItalyDorigo, M., Di Caro, G., The ant colony optimization meta-heuristic (1999) New Ideas in Optimization, pp. 11-32. , D. Corne, M. Dorigo, and F. Glover, editors, McGraw-Hill, LondonDorigo, M., Stützle, T., The ant colony optimization metaheuristic: Algorithms, applications, and advances (2003) Handbook of Metaheuristics, pp. 251-286. , F. W. Glover and G. A. Kochenberger, editors, Kluwer Academic PressDréo, J., Siarry, P., A new ant colony algorithm using the heterarchical concept aimed at optimization of multiminima continuous functions (2002) Lecture Notes in Computer Science, 2463, pp. 216-221. , M. Dorigo, G. D. Caro, and M. Sampels, editors, Ant Algorithms, of, SpringerM. Guntsch and M. Middendorf. A population based approach for ACO. In S. Cagnoni, J. Gottlieb, E. Hart, M. Middendorf, and G. Raidl, editors, Applications of Evolutionary Computing, Proceedings of Evo Workshops2002: Evo COP, EvoIASP, EvoSTim, 2279 of LNCS, pages 72-81, Kinsale, Ireland, 3-4 2002. Springer-VerlagHernádvölgyi, I.T., Generating random vectors from the multivariate normal distribution (1998), Technical Report TR-98-07, University of Ottawa, Aug. 20Marsaglia, G., Tsang, W.W., The ziggurat method for generating random variables (2000) Journal of Statistical Software, 5 (8), pp. 1-7Monmarché, N., Venturini, G., Slimane, M., On how Pachycondyla apicalis ants suggest a new search algorithm (2000) Future Generation Computer Systems, 16 (8), pp. 937-946Pourtakdoust, S.H., Nobahari, H., An extension of ant colony system to continuous optimization problems (2004) Lecture Notes in Computer Science, 3172, pp. 294-301. , M. Dorigo, M. Birattari, C. Blum, L. M. Gambardella, F. Mondada, and T. Stützle, editors, ANTS Workshop, of, SpringerShang, Y.-W., Qiu, Y.-H., A note on the extended Rosenbrock function (2006) Evolutionary Computation, 14 (1), pp. 119-126. , MarchSocha, K., Dorigo, M., Ant colony optimization for continuous domains (2006) European Journal of Operational Research, In Press, Corrected ProofStützle, T., Dorigo, M., ACO algorithms for the quadratic assignment problem (1999) New Ideas in Optimization, pp. 33-50. , D. Corne, M. Dorigo, and F. Glover, editors, McGraw-Hill, Londo

Christiaan Bekker - One of the best experts on this subject based on the ideXlab platform.

  • free spectral range electrical tuning of a high quality on chip microcavity
    Optics Express, 2018
    Co-Authors: Christiaan Bekker, Christopher G. Baker, Rachpon Kalra, Han-hao Cheng, Varun Prakash, Warwick P. Bowen
    Abstract:

    Reconfigurable photonic circuits have applications ranging from next-Generation Computer architectures to quantum networks, coherent radar and optical metamaterials. Here, we demonstrate an on-chip high quality microcavity with resonances that can be electrically tuned across a full free spectral range (FSR). FSR tuning allows resonance with any source or emitter, or between any number of networked microcavities. We achieve it by integrating nanoelectronic actuation with strong optomechanical interactions that create a highly geometry-dependent effective refractive index. This allows low voltages and sub-nanowatt power consumption. We demonstrate a basic reconfigurable photonic network, bringing the microcavity into resonance with an arbitrary mode of a microtoroidal optical cavity across a telecommunications fibre link. Our results have applications beyond photonic circuits, including widely tuneable integrated lasers, reconfigurable optical filters for telecommunications and astronomy, and on-chip sensor networks.

  • free spectral range electrical tuning of a high quality on chip microcavity
    arXiv: Applied Physics, 2018
    Co-Authors: Christiaan Bekker, Christopher G. Baker, Rachpon Kalra, Han-hao Cheng, Varun Prakash, Warwick P. Bowen
    Abstract:

    Reconfigurable photonic circuits have applications ranging from next-Generation Computer architectures to quantum networks, coherent radar and optical metamaterials. However, complete reconfigurability is only currently practical on millimetre-scale device footprints. Here, we overcome this barrier by developing an on-chip high quality microcavity with resonances that can be electrically tuned across a full free spectral range (FSR). FSR tuning allows resonance with any source or emitter, or between any number of networked microcavities. We achieve it by integrating nanoelectronic actuation with strong optomechanical interactions that create a highly strain-dependent effective refractive index. This allows low voltages and sub-nanowatt power consumption. We demonstrate a basic reconfigurable photonic network, bringing the microcavity into resonance with an arbitrary mode of a microtoroidal optical cavity across a telecommunications fibre link. Our results have applications beyond photonic circuits, including widely tuneable integrated lasers, reconfigurable optical filters for telecommunications and astronomy, and on-chip sensor networks.