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One striking feature of the contemporary modelling practice is its interdisciplinary nature. The same equation forms, and mathematical and computational methods, are used across different disciplines, as well as within the same discipline. Are there, then, differences between intra- and interdisciplinary transfer, and can the comparison between the two provide more insight on the challenges of interdisciplinary theoretical work? We will study the development and various uses of the Ising model within physics, contrasting them to its applications to socio-economic systems. While the renormalization group (RG) methods justify the transfer of the Ising model within physics – by ascribing them to the same universality class – its application to socio-economic phenomena has no such theoretical grounding. As a result, the insights gained by modelling socio-economic phenomena by the Ising model may remain limited.

We present a numerical study of a neural network model with a low level of activity. Our findings confirm a previous replica-symmetric mean-field analysis which predicts a much higher storage capacity compared with the standard Hopfield model. Indeed our estimate of the critical storage ratio of the model lies above that yielded analytically. We also obtain good agreement with an analytical investigation of the dynamics of the model.

We present first results for the Renner-Teller-induced predissociation of HCO(à 2A′) using new ab initio potential energy surfaces for the à (2A′) and the X̃(2A') states. The quantum mechanical dynamics calculations are performed in the time-dependent representation with the CO bond distance being fixed. The linewidths and final rotational state distribution of CO following the decay of various highly excited bending states of HCO (à 2A′) agree with recent experimental data. The dissociation mechanism is discussed in terms of the topology of the X̃ (2A')-state potential energy surface.

One of the most conspicuous features of contemporary modeling practices is the dissemination of mathematical and computational methods across disciplinary boundaries. We study this process through two applications of the Ising model: the Sherrington-Kirkpatrick model of spin glasses and the Hopfield model of associative memory. The Hopfield model successfully transferred some basic ideas and mathematical methods originally developed within the study of magnetic systems to the field of neuroscience. As an analytical resource we use Paul Humphreys's discussion of computational and theoretical templates. We argue that model templates are crucial for the intra- and interdisciplinary theoretical transfer. A model template is an abstract conceptual idea associated with particular mathematical forms and computationalmethods.