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Research Topic : statistical methods
Australian State/Territory : VIC
Field of Research : Mathematical Physics
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  • Funded Activity

    Discovery Projects - Grant ID: DP120101593

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Advanced numerical and analytical techniques for exact studies in combinatorics and statistical mechanics. Exactly solved models are of immense importance in all areas of the theoretical sciences and play important roles in our understanding of complex natural and social phenomena. This project aims to develop powerful new methods that will enable mathematicians and physicists to greatly expand the types of models for which we can find a solution.
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    Funded Activity

    Discovery Projects - Grant ID: DP110102317

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Characteristic polynomials in random matrix theory. Random matrix theory is the subject of an active international research effort, due to its broad range of applications including the statistical analysis of high-dimensional data sets, wireless communication, and the celebrated Riemann zeros in prime number theory. Characteristic polynomials will be used to focus an attack on these problems.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT100100494

    Funder
    Australian Research Council
    Funding Amount
    $556,623.00
    Summary
    Design, analysis and application of Monte Carlo methods in statistical mechanics. Statistical mechanics is a general framework for studying complex systems and Monte Carlo methods are an important computational tool in such studies. This project will develop new, vastly more efficient, Monte Carlo methods for problems in statistical mechanics, and will apply these methods to real-world problems such as urban traffic flow.
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    Funded Activity

    Discovery Projects - Grant ID: DP140102613

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    A synthesis of random matrix theory for applications in mathematics, physics and engineering. Random matrix theory, matrix theory where the elements are random, or the matrix chosen from an ensemble, is driven by its ever expanding range of applications, and the richness of the mathematics being uncovered. These applications include topics of acknowledged modern day importance, for example quantum information theory, wireless communication, data analysis, signal processing and the study of algor .... A synthesis of random matrix theory for applications in mathematics, physics and engineering. Random matrix theory, matrix theory where the elements are random, or the matrix chosen from an ensemble, is driven by its ever expanding range of applications, and the richness of the mathematics being uncovered. These applications include topics of acknowledged modern day importance, for example quantum information theory, wireless communication, data analysis, signal processing and the study of algorithms. Buoyed by promising preliminary investigations, this project aims to draw together seemingly disparate techniques to tackle problems from such topics. In addition to providing solutions to these problems, these methods are expected to provide inspiration for fellow researchers.
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    Funded Activity

    Discovery Projects - Grant ID: DP110101141

    Funder
    Australian Research Council
    Funding Amount
    $614,000.00
    Summary
    Design, analysis and application of Monte Carlo algorithms in statistical mechanics. Monte Carlo methods provide a powerful computational tool with an enormous range of applications. However when applied in statistical mechanics they typically suffer from severe critical slowing-down, so that their computational efficiency tends rapidly to zero as a critical point is approached. We will develop novel, more efficient Monte Carlo algorithms, to simulate a range of models in statistical mechanics a .... Design, analysis and application of Monte Carlo algorithms in statistical mechanics. Monte Carlo methods provide a powerful computational tool with an enormous range of applications. However when applied in statistical mechanics they typically suffer from severe critical slowing-down, so that their computational efficiency tends rapidly to zero as a critical point is approached. We will develop novel, more efficient Monte Carlo algorithms, to simulate a range of models in statistical mechanics and back this up with rigorous mathematical analysis proving that their results can be trusted.
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    Funded Activity

    Discovery Projects - Grant ID: DP120100939

    Funder
    Australian Research Council
    Funding Amount
    $690,000.00
    Summary
    Critical behaviour of lattice models of spin systems. A common feature of complex systems is that simple, short-range forces can produce long-range effects. Lattice spin systems are paradigms of this phenomenon, and this project proposes to solve a number of outstanding and significant problems in these systems. This will enhance our understanding of complex systems in general, and key models in particular.
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    Funded Activity

    Discovery Projects - Grant ID: DP160103562

    Funder
    Australian Research Council
    Funding Amount
    $334,000.00
    Summary
    Interplay of Topology and Geometry in Polymeric Critical Phenomena. This project aims to develop new understanding of key topologically driven behaviour in complex polymers such as DNA. The mathematical modelling of the rich geometric behaviour of long-chain polymers and how they change their shape in response to the environment has provided a framework for our understanding of these ubiquitous molecules. Complex polymers such as ring polymers and DNA display topological properties such as knott .... Interplay of Topology and Geometry in Polymeric Critical Phenomena. This project aims to develop new understanding of key topologically driven behaviour in complex polymers such as DNA. The mathematical modelling of the rich geometric behaviour of long-chain polymers and how they change their shape in response to the environment has provided a framework for our understanding of these ubiquitous molecules. Complex polymers such as ring polymers and DNA display topological properties such as knotting and linking. Recent experiments twisting DNA demonstrate novel phenomena precipitated by the interplay of topological and geometric properties. Using advanced mathematical and computational techniques, the project aims to explain how topological constraints and changes disturb key polymer behaviour.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT130100972

    Funder
    Australian Research Council
    Funding Amount
    $583,999.00
    Summary
    Computational studies of soft matter. Soft matter systems such as colloidal suspensions and polymers are ubiquitous in nature, and industrially important. For colloidal systems, specifically hard spheres, this project will utilise new algorithms to attack long standing questions about the nature of the virial series. For self-avoiding walks and related models of polymers, research studies have recently developed radically improved Monte Carlo simulation algorithms. These algorithms will enable t .... Computational studies of soft matter. Soft matter systems such as colloidal suspensions and polymers are ubiquitous in nature, and industrially important. For colloidal systems, specifically hard spheres, this project will utilise new algorithms to attack long standing questions about the nature of the virial series. For self-avoiding walks and related models of polymers, research studies have recently developed radically improved Monte Carlo simulation algorithms. These algorithms will enable this project to simulate polymers which may be as long as DNA, and to calculate physical properties with unprecedented precision. The software developed for studying polymers will be released as an open source software library which will revolutionise the field of polymer simulation.
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    Funded Activity

    Discovery Projects - Grant ID: DP140101110

    Funder
    Australian Research Council
    Funding Amount
    $370,000.00
    Summary
    Advanced algorithms for statistical mechanical models. Polymer science, percolation theory and models of magnetism are at the forefront of lattice statistical mechanics and condensed matter theory. Numerical techniques to determine the behaviour of model systems in these areas are predominantly Monte Carlo methods, series generation and analysis, or based on partition function zeroes. New algorithms have been developed for all three methods that are vastly more efficient than their predecessors. .... Advanced algorithms for statistical mechanical models. Polymer science, percolation theory and models of magnetism are at the forefront of lattice statistical mechanics and condensed matter theory. Numerical techniques to determine the behaviour of model systems in these areas are predominantly Monte Carlo methods, series generation and analysis, or based on partition function zeroes. New algorithms have been developed for all three methods that are vastly more efficient than their predecessors. Coupled with the availability of dramatically increased computer power, this project takes advantage of a unique position to make dramatic advances in the afore-mentioned research areas. Furthermore, the methods have wider applicability than those mentioned.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT200100981

    Funder
    Australian Research Council
    Funding Amount
    $816,204.00
    Summary
    Solvability and universality in stochastic processes. Exactly solvable stochastic processes are an important area of mathematical research, with cross-disciplinary links to quantum physics, quantum algebras and probability theory. These processes can be used to model a variety of real-world phenomena such as crystal growth and polymers in random media. This project aims to significantly expand our knowledge of exactly solvable stochastic processes by extending them to new algebraic frameworks. A .... Solvability and universality in stochastic processes. Exactly solvable stochastic processes are an important area of mathematical research, with cross-disciplinary links to quantum physics, quantum algebras and probability theory. These processes can be used to model a variety of real-world phenomena such as crystal growth and polymers in random media. This project aims to significantly expand our knowledge of exactly solvable stochastic processes by extending them to new algebraic frameworks. Among the outcomes of the project, we expect to identify new probabilistic structures which go beyond the famous Gaussian universality class. These theoretical developments allow better prediction of randomly growing interfaces, which encompass a range of phenomena from tumour growth to forest fires.
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