Quantum Picturalism

The quantum mechanical formalism doesn't support our intuition, nor does it elucidate the key concepts that govern the behaviour of the entities that are subject to the laws of quantum physics. The arrays of complex numbers are kin to the arrays of 0s and 1s of the early days of computer programming practice. In this review we present steps towards a diagrammatic `high-level' alternative for the Hilbert space formalism, one which appeals to our intuition. It allows for intuitive reasoning about interacting quantum systems, and trivialises many otherwise involved and tedious computations. It clearly exposes limitations such as the no-cloning theorem, and phenomena such as quantum teleportation. As a logic, it supports `automation'. It allows for a wider variety of underlying theories, and can be easily modified, having the potential to provide the required step-stone towards a deeper conceptual understanding of quantum theory, as well as its unification with other physical theories. Specific applications discussed here are purely diagrammatic proofs of several quantum computational schemes, as well as an analysis of the structural origin of quantum non-locality. The underlying mathematical foundation of this high-level diagrammatic formalism relies on so-called monoidal categories, a product of a fairly recent development in mathematics. These monoidal categories do not only provide a natural foundation for physical theories, but also for proof theory, logic, programming languages, biology, cooking, ... The challenge is to discover the necessary additional pieces of structure that allow us to predict genuine quantum phenomena.Comment: Commissioned paper for Contemporary Physics, 31 pages, 84 pictures, some colo

Hidden measurements, hidden variables and the volume representation of transition probabilities

We construct, for any finite dimension $n$, a new hidden measurement model for quantum mechanics based on representing quantum transition probabilities by the volume of regions in projective Hilbert space. For $n=2$ our model is equivalent to the Aerts sphere model and serves as a generalization of it for dimensions $n \geq 3$. We also show how to construct a hidden variables scheme based on hidden measurements and we discuss how joint distributions arise in our hidden variables scheme and their relationship with the results of Fine.Comment: 23 pages, 1 figur

Three qubit entanglement within graphical Z/X-calculus

The compositional techniques of categorical quantum mechanics are applied to analyse 3-qubit quantum entanglement. In particular the graphical calculus of complementary observables and corresponding phases due to Duncan and one of the authors is used to construct representative members of the two genuinely tripartite SLOCC classes of 3-qubit entangled states, GHZ and W. This nicely illustrates the respectively pairwise and global tripartite entanglement found in the W- and GHZ-class states. A new concept of supplementarity allows us to characterise inhabitants of the W class within the abstract diagrammatic calculus; these method extends to more general multipartite qubit states.Comment: In Proceedings HPC 2010, arXiv:1103.226

The GHZ/W-calculus contains rational arithmetic

Graphical calculi for representing interacting quantum systems serve a number of purposes: compositionally, intuitive graphical reasoning, and a logical underpinning for automation. The power of these calculi stems from the fact that they embody generalized symmetries of the structure of quantum operations, which, for example, stretch well beyond the Choi-Jamiolkowski isomorphism. One such calculus takes the GHZ and W states as its basic generators. Here we show that this language allows one to encode standard rational calculus, with the GHZ state as multiplication, the W state as addition, the Pauli X gate as multiplicative inversion, and the Pauli Z gate as additive inversion.Comment: In Proceedings HPC 2010, arXiv:1103.226

Time-asymmetry of probabilities versus relativistic causal structure: an arrow of time

There is an incompatibility between the symmetries of causal structure in relativity theory and the signaling abilities of probabilistic devices with inputs and outputs: while time-reversal in relativity will not introduce the ability to signal between spacelike separated regions, this is not the case for probabilistic devices with space-like separated input-output pairs. We explicitly describe a non-signaling device which becomes a perfect signaling device under time-reversal, where time-reversal can be conceptualized as playing backwards a videotape of an agent manipulating the device. This leads to an arrow of time that is identifiable when studying the correlations of events for spacelike separated regions. Somewhat surprisingly, although time-reversal of Popuscu-Roerlich boxes also allows agents to signal, it does not yield a perfect signaling device. Finally, we realize time-reversal using post-selection, which could lead experimental implementation.Comment: 4 pages, some figures; replaces arXiv:1010.4572 [quant-ph

Correlating matched-filter model for analysis and optimisation of neural networks

A new formalism is described for modelling neural networks by means of which a clear physical understanding of the network behaviour can be gained. In essence, the neural net is represented by an equivalent network of matched filters which is then analysed by standard correlation techniques. The procedure is demonstrated on the synchronous Little-Hopfield network. It is shown how the ability of this network to discriminate between stored binary, bipolar codes is optimised if the stored codes are chosen to be orthogonal. However, such a choice will not often be possible and so a new neural network architecture is proposed which enables the same discrimination to be obtained for arbitrary stored codes. The most efficient convergence of the synchronous Little-Hopfield net is obtained when the neurons are connected to themselves with a weight equal to the number of stored codes. The processing gain is presented for this case. The paper goes on to show how this modelling technique can be extended to analyse the behaviour of both hard and soft neural threshold responses and a novel time-dependent threshold response is described

Causal categories: relativistically interacting processes

A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a `causal category'. We provide methods of constructing causal categories, and we study the consequences of these methods for the general framework of categorical quantum mechanics.Comment: 43 pages, lots of figure

A short-term intervention improved children's insights into causal processes

Understanding of causal mechanisms has largely been ignored in past work on science learning, with studies typically assessing multiple aspects of children’s knowledge or focusing on their explanations without differentiating between accounts of factors, variables and mechanisms. Recent evidence suggests that grasp of mechanisms is in fact a crucial predictor of children’s science achievement; and that spatial-temporal ability is a key driver of this grasp, helping children to envisage the transformations involved in the continuous causal processes they encounter in science lessons. The present research tested the impact of a short-term intervention designed to promote spatial-temporal thinking with regard to one such process, sinking. Children across Years one to three from a school in a disadvantaged area (5 to 8 year-olds, six classes, N=171) were taken through a three-stage classroom exercise: Making initial predictions and observations; engaging in an imaginative game to explore the interactions between objects and water; and then testing further predictions supported by the introduction of scientific terminology. These stages modelled on a scientific investigation, targeting five key steps: (1) perception; (2) representation; (3) analysis; (4) mental imagery; and (5) use of feedback. The exercise produced substantial improvements in children’s performance, regardless of age; better observation and more accurate prediction; more coordinated representations; greater incidence of imagery and mechanism-related analysis; better sensitivity to feedback and increased use of scientific terminology. The data suggest that the ability to utilise spatial-temporal elements in causal inference is highly malleable and that giving children space to think and talk imaginatively about mechanisms is central to their progress. At present, science lessons typically focus on the ‘what’ rather than the ‘why’, and do not actively support such thinking about causal processes

Nonverbal Ability and Scientific Vocabulary Predict Children's Causal Reasoning in Science Better than Generic Language

Verbal and nonverbal forms of thinking exhibit widespread dissociation at neural and behavioral level. The importance of this for children's causal thinking and its implications for school science are largely unknown. Assessing 5‐ to 10‐year‐olds' responses (N = 231), verbal ability predicted causal reasoning, but only at lower levels, while nonverbal ability was the strongest predictor at higher levels of causal inference. We also distinguished between generic and scientific vocabulary use (n = 101). The results showed that use of scientific vocabulary predicted causal reasoning beyond generic, and connected more to nonverbal thinking. The findings highlighted the importance of elementary school science activities supporting application of nonverbal ability in thinking about causal processes; the benefits of linking nonverbal imagery to scientific vocabulary; and shortcomings in understanding of the forms/sources of nonverbal ability and their role in learning

Environment and classical channels in categorical quantum mechanics

We present a both simple and comprehensive graphical calculus for quantum computing. In particular, we axiomatize the notion of an environment, which together with the earlier introduced axiomatic notion of classical structure enables us to define classical channels, quantum measurements and classical control. If we moreover adjoin the earlier introduced axiomatic notion of complementarity, we obtain sufficient structural power for constructive representation and correctness derivation of typical quantum informatic protocols.Comment: 26 pages, many pics; this third version has substantially more explanations than previous ones; Journal reference is of short 14 page version; Proceedings of the 19th EACSL Annual Conference on Computer Science Logic (CSL), Lecture Notes in Computer Science 6247, Springer-Verlag (2010