Many-body localization in a quantum simulator with programmable random disorder

When a system thermalizes it loses all local memory of its initial conditions. This is a general feature of open systems and is well described by equilibrium statistical mechanics. Even within a closed (or reversible) quantum system, where unitary time evolution retains all information about its initial state, subsystems can still thermalize using the rest of the system as an effective heat bath. Exceptions to quantum thermalization have been predicted and observed, but typically require inherent symmetries or noninteracting particles in the presence of static disorder. The prediction of many-body localization (MBL), in which disordered quantum systems can fail to thermalize in spite of strong interactions and high excitation energy, was therefore surprising and has attracted considerable theoretical attention. Here we experimentally generate MBL states by applying an Ising Hamiltonian with long-range interactions and programmably random disorder to ten spins initialized far from equilibrium. We observe the essential signatures of MBL: memory retention of the initial state, a Poissonian distribution of energy level spacings, and entanglement growth in the system at long times. Our platform can be scaled to higher numbers of spins, where detailed modeling of MBL becomes impossible due to the complexity of representing such entangled quantum states. Moreover, the high degree of control in our experiment may guide the use of MBL states as potential quantum memories in naturally disordered quantum systems.Comment: 9 pages, 9 figure

Evolutionary optimisation of neural network models for fish collective behaviours in mixed groups of robots and zebrafish

Animal and robot social interactions are interesting both for ethological studies and robotics. On the one hand, the robots can be tools and models to analyse animal collective behaviours, on the other hand, the robots and their artificial intelligence are directly confronted and compared to the natural animal collective intelligence. The first step is to design robots and their behavioural controllers that are capable of socially interact with animals. Designing such behavioural bio-mimetic controllers remains an important challenge as they have to reproduce the animal behaviours and have to be calibrated on experimental data. Most animal collective behavioural models are designed by modellers based on experimental data. This process is long and costly because it is difficult to identify the relevant behavioural features that are then used as a priori knowledge in model building. Here, we want to model the fish individual and collective behaviours in order to develop robot controllers. We explore the use of optimised black-box models based on artificial neural networks (ANN) to model fish behaviours. While the ANN may not be biomimetic but rather bio-inspired, they can be used to link perception to motor responses. These models are designed to be implementable as robot controllers to form mixed-groups of fish and robots, using few a priori knowledge of the fish behaviours. We present a methodology with multilayer perceptron or echo state networks that are optimised through evolutionary algorithms to model accurately the fish individual and collective behaviours in a bounded rectangular arena. We assess the biomimetism of the generated models and compare them to the fish experimental behaviours.Comment: 10 pages, 4 figure

Classical and quantum: a conflict of interest

We highlight three conflicts between quantum theory and classical general relativity, which make it implausible that a quantum theory of gravity can be arrived at by quantising classical gravity. These conflicts are: quantum nonlocality and space-time structure; the problem of time in quantum theory; and the quantum measurement problem. We explain how these three aspects bear on each other, and how they point towards an underlying noncommutative geometry of space-time.Comment: 15 pages. Published in `Gravity and the quantum' [Essays in honour of Thanu Padmanabhan on the occasion of his sixtieth birthday] Eds. Jasjeet Singh Bagla and Sunu Engineer (Springer, 2017

Large scale analysis of positional effects of single-base mismatches on microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Affymetrix GeneChips utilize 25-mer oligonucleotides probes linked to a silica surface to detect targets in solution. Mismatches due to single nucleotide polymorphisms (SNPs) can affect the hybridization between probes and targets. Previous research has indicated that binding between probes and targets strongly depends on the positions of these mismatches. However, there has been substantial variability in the effect of mismatch type across studies.</p> <p>Methods</p> <p>By taking advantage of naturally occurring mismatches between rhesus macaque transcripts and human probes from the Affymetrix U133 Plus 2 GeneChip, we collected the largest 25-mer probes dataset with single-base mismatches at each of the 25 positions on the probe ever used in this type of analysis.</p> <p>Results</p> <p>A mismatch at the center of a probe led to a greater loss in signal intensity than a mismatch at the ends of the probe, regardless of the mismatch type. There was a slight asymmetry between the ends of a probe: effects of mismatches at the 3' end of a probe were greater than those at the 5' end. A cross study comparison of the effect of mismatch types revealed that results were not in good agreement among different reports. However, if the mismatch types were consolidated to purine or pyrimidine mismatches, cross study conclusions could be generated.</p> <p>Conclusion</p> <p>The comprehensive assessment of the effects of single-base mismatches on microarrays provided in this report can be useful for improving future versions of microarray platform design and the corresponding data analysis algorithms.</p

A Survey on Continuous Time Computations

We provide an overview of theories of continuous time computation. These theories allow us to understand both the hardness of questions related to continuous time dynamical systems and the computational power of continuous time analog models. We survey the existing models, summarizing results, and point to relevant references in the literature

Social representations and the politics of participation

Recent work has called for the integration of different perspectives into the field of political psychology (Haste, 2012). This chapter suggests that one possible direction that such efforts can take is studying the role that social representations theory (SRT) can play in understanding political participation and social change. Social representations are systems of common-sense knowledge and social practice; they provide the lens through which to view and create social and political realities, mediate people's relations with these sociopolitical worlds and defend cultural and political identities. Social representations are therefore key for conceptualising participation as the activity that locates individuals and social groups in their sociopolitical world. Political participation is generally seen as conditional to membership of sociopolitical groups and therefore is often linked to citizenship. To be a citizen of a society or a member of any social group one has to participate as such. Often political participation is defined as the ability to communicate one's views to the political elite or to the political establishment (Uhlaner, 2001), or simply explicit involvement in politics and electoral processes (Milbrath, 1965). However, following scholars on ideology (Eagleton, 1991; Thompson, 1990) and social knowledge (Jovchelovitch, 2007), we extend our understanding of political participation to all social relations and also develop a more agentic model where individuals and groups construct, develop and resist their own views, ideas and beliefs. We thus adopt a broader approach to participation in comparison to other political-psychological approaches, such as personality approaches (e.g. Mondak and Halperin, 2008) and cognitive approaches or, more recently, neuropsychological approaches (Hatemi and McDermott, 2012). We move away from a focus on the individual's political behaviour and its antecedents and outline an approach that focuses on the interaction between psychological and political phenomena (Deutsch and Kinnvall, 2002) through examining the politics of social knowledge

Computability and dynamical systems

In this paper we explore results that establish a link between dynamical systems and computability theory (not numerical analysis). In the last few decades, computers have increasingly been used as simulation tools for gaining insight into dynamical behavior. However, due to the presence of errors inherent in such numerical simulations, with few exceptions, computers have not been used for the nobler task of proving mathematical results. Nevertheless, there have been some recent developments in the latter direction. Here we introduce some of the ideas and techniques used so far, and suggest some lines of research for further work on this fascinating topic

Copper-catalysed selective hydroamination reactions of alkynes

The development of selective reactions that utilize easily available and abundant precursors for the efficient synthesis of amines is a long-standing goal of chemical research. Despite the centrality of amines in a number of important research areas, including medicinal chemistry, total synthesis and materials science, a general, selective and step-efficient synthesis of amines is still needed. Here, we describe a set of mild catalytic conditions utilizing a single copper-based catalyst that enables the direct preparation of three distinct and important amine classes (enamines, α-chiral branched alkylamines and linear alkylamines) from readily available alkyne starting materials with high levels of chemo-, regio- and stereoselectivity. This methodology was applied to the asymmetric synthesis of ​rivastigmine and the formal synthesis of several other pharmaceutical agents, including ​duloxetine, ​atomoxetine, ​fluoxetine and ​tolterodine.National Institutes of Health (U.S.) (GM58160