L4

Some recent applications of supertwistors to superparticle mechanics will be reviewed.
First: Supertwistors allow a simple quantization of the  N-extended 4D massless superparticle, and peculiarities of massless 4D supermultiplets can then be explained by considering the quantum fate of a classical ``worldline CPT'' symmetry. For N=1 there is a global CPT anomaly, which explains why there is no CPT self-conjugate supermultiplet. For N=2 there is no anomaly but a Kramers degeneracy explains the doubling of states in the CPT self-conjugate hypermultiplet.
Second: the bi-supertwistor formulation of the N-extended massive superparticle in 3D, 4D and 6D makes manifest a ``hidden’’ 2N-extended supersymmetry. It also has a simple expression in terms of hermitian 2x2 matrices over the associative division algebras R,C,H.
Third: omission of the mass-shell constraint in this 3D,4D,6D bi-supertwistor action yields, as suggested  by holography, the action for a supergraviton in 4D,5D,7D AdS. Application to the near horizon AdSxS geometries of the M2,D3 and M5 brane confirms that the graviton supermultiplet has 128+128 polarisation states. 

The talk will describe accelerated algorithms for computing full or partial matrix factorizations such as the eigenvalue decomposition, the QR factorization, etc. The key technical novelty is the use of  randomized projections to reduce the effective dimensionality of  intermediate steps in the computation. The resulting algorithms execute faster on modern hardware than traditional algorithms, and are particularly well suited for processing very large data sets.

The algorithms described are supported by a rigorous mathematical analysis that exploits recent work in random matrix theory. The talk will briefly review some representative theoretical results.

Abstract: We study nonuniform sampling in shift-invariant spaces whose generator is a totally positive function. For a subclass of such generators the sampling theorems can be formulated in analogy to the theorems of Beurling and Landau for bandlimited functions. These results are  optimal and validate  the  heuristic reasonings in the engineering literature. In contrast to the cardinal series, the reconstruction procedures for sampling in a shift-invariant space with a totally positive generator  are local and thus accessible to numerical linear algebra.

A subtle  connection between sampling in shift-invariant spaces and the theory of Gabor frames leads to new and optimal  results for Gabor frames.  We show that the set of phase-space shifts of  $g$ (totally positive with a Gaussian part) with respect to a rectangular lattice forms a frame, if and only if the density of the lattice  is strictly larger than 1. This solves an open problem going backto Daubechies in 1990 for the class of totally positive functions of Gaussian type.
 

Almost all real-world applications involve a degree of uncertainty. This may be the result of noisy measurements, restrictions on observability, or simply unforeseen events. Since many models in both engineering and the natural sciences make use of partial differential equations (PDEs), it is natural to consider PDEs with random inputs. In this context, passing from modelling and simulation to optimization or control results in stochastic PDE-constrained optimization problems. This leads to a number of theoretical, algorithmic, and numerical challenges.

 From a mathematical standpoint, the solution of the underlying PDE is a random field, which in turn makes the quantity of interest or the objective function an implicitly defined random variable. In order to minimize this distributed objective, one can use, e.g., stochastic order constraints, a distributionally robust approach, or risk measures. In this talk, we will make use of risk measures.

After motivating the approach via a model for the mitigation of an airborne pollutant, we build up an analytical framework and introduce some useful risk measures. This allows us to prove the existence of solutions and derive optimality conditions. We then present several approximation schemes for handling non-smooth risk measures in order to leverage existing numerical methods from PDE-constrained optimization. Finally, we discuss solutions techniques and illustrate our results with numerical examples.

In this talk, I discuss the positive geometry of the Wilson Loop Diagrams appearing in SYM N-4 theory. In particular, I define an algorithm for associating Wilson Loop diagrams to convex cells of the positive Grassmannians. Using combinatorics of these cells, I then consider the geometry of N^2MHV diagrams on 6 points.

With the purpose of examining some relevant geometric properties of the moduli space of sheaves over an algebraic surface, Le Potier conjectured some unexpected duality between the complete linear series of certain natural divisors, called Theta divisors, on the moduli space. Such conjecture is widely known as Strange Duality conjecture. After having motivated the problem by looking at certain instances of quantization in physics, we will work in the setting of surfaces. We will then sketch the proof in the case of abelian surfaces, giving an idea of the techniques that are used. In particular, we will show how the theory of discrete Heisenberg groups and fiber wise Fourier-Mukai transforms, which might be applied to other cases of interest, enter the picture. This is joint work with Alina Marian, Dragos Opera and Kota Yoshioka.

Heckman introduced N operators on the space of polynomials in N variables, such that these operators form a covariant set relative to permutations of the operators and variables, and such that Jack symmetric polynomials are eigenfunctions of the power sums of these operators. We introduce the analogues of these N operators for Macdonald symmetric polynomials, by using Cherednik operators. The latter operators pairwise commute, and Macdonald polynomials are eigenfunctions of their power sums. We compute the limits of our operators at N → ∞ . These limits yield a Lax operator for Macdonald symmetric functions. This is a joint work with Evgeny Sklyanin.

[[{"fid":"47873","view_mode":"default","fields":{"format":"default"},"type":"media","attributes":{"class":"file media-element file-default"},"link_text":"AD abstract.pdf"}]]

We  study  the  concept  of   financial  bubble  under model uncertainty.
We suppose the agent to be endowed with a family Q of local martingale measures for  the  underlying  discounted  asset  price. The priors are allowed to be mutually singular to each other.
One fundamental issue is the definition of a well-posed concept of robust fundamental value of a given  financial asset.
Since in this setting we have no linear pricing system, we choose to describe robust fundamental values through superreplication prices.
To this purpose, we investigate a dynamic version of robust superreplication, which we use
to  introduce  the  notions  of  bubble  and  robust  fundamental  value  in  a  consistent way with the existing literature in the classical case of one prior.

This talk is based on the works [1] and [2].

[1] Biagini, F. , Föllmer, H. and Nedelcu, S. Shifting martingale measures
and the slow birth of a bubble as a submartingale, Finance and
Stochastics: Volume 18, Issue 2, Page 297-326, 2014.

[2] Biagini, F., Mancin, J.,
Financial Asset Price Bubbles under Model 
Uncertainty, Preprint, 2016.