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Showing 1 to 7 of 7 for “"invariant polynomials"”.

  1. Invariant polynomials and machine learning

    … the necessary tools from commutative algebra and invariant theory, we construct systematic methods to obtain sets of invariant variables that describe two such systems: particle physics and physical chemistry. In both cases, our systems are described by a collection of vectors. In the former, …

    cambridge Repository record for Invariant polynomials and machine learning (opens in a new tab)

  2. On the Ring of Invariant Polynomials for Representations of Lie Groups

    Made available in DSpace on 2014-12-09T22:17:57Z (GMT). No. of bitstreams: 1 7021071.pdf: 2562623 bytes, checksum: 095b94414a55b60df438b8bf1894fba0 (MD5) Previous issue date: 1970

    uiuc Repository record for On the Ring of Invariant Polynomials for Representations of Lie Groups (opens in a new tab)

  3. On semi-invariants of filtered representations of quivers and the cotangent bundle of the enhanced Grothendieck-Springer resolution

    … this notion in mind, we describe the ring of invariant polynomials for interesting families of quivers, namely, finite $ADE$-Dynkin quivers and affine type $\widetilde{A}$-Dynkin quivers. We then study their relation to an important and fundamental object in representation theory called the …

    uiuc Repository record for On semi-invariants of filtered representations of quivers and the cotangent bundle of the enhanced Grothendieck-Springer resolution (opens in a new tab)

  4. On representations of quantum groups and Cherednik algebras

    … and W the Weyl group of g, the restriction of g-invariant polynomials on g to [ is an isomorphism onto the W-invariant polynomials on , Res: C[g]1 -+ C[]w. A recent generalization of [36] to the case when the target space C of the polynomial maps is replaced by a finite-dimensional representation …

    mit Repository record for On representations of quantum groups and Cherednik algebras (opens in a new tab)

  5. Data-driven linear interatomic potentials

    … two novel frameworks, namely 'atomic permutation invariant polynomials' and 'atomic cluster expansion'. Both frameworks are linear models that can be used to create computationally efficient potentials that approximate the potential energy surface for materials and molecules with first-principles …

    cambridge Repository record for Data-driven linear interatomic potentials (opens in a new tab)

  6. Data-driven models of water and methane

    … Potentials (GAP) [1, 2] and the permutationally invariant polynomials (PIP) [3] methods, the latter applied in collaboration. The long-range electrostatic interactions are calculated using a classical force field, the modified TTM4F [4]. The resulting models are validated against quantum …

    cambridge Repository record for Data-driven models of water and methane (opens in a new tab)

  7. Interpretation of Infrared and Raman Spectra Using Driven Molecular Dynamics Method

    … tensor surface (PTS) done via permutationally invariant polynomials developed by our collaborator at Emory University. This new PTS method has advantages in describing polarizability with increased computational effectiveness and sufficient accuracy. The PTS functional form is used to describe …

    kennesaw Repository record for Interpretation of Infrared and Raman Spectra Using Driven Molecular Dynamics Method (opens in a new tab)