Related papers: Effective Action Method for Computing Next to Lead…
$N$-jettiness subtractions provide a general approach for performing fully-differential next-to-next-to-leading order (NNLO) calculations. Since they are based on the physical resolution variable $N$-jettiness, $\mathcal{T}_N$, subleading…
Single top production processes at hadron colliders provide information on the relation between the top quark and the electroweak sector of the standard model. We compute the next-to-leading order QCD corrections to the three main…
The post Gaussian effective potential in D=3 dimensions and the Gaussian effective potential in D=2+epsilon are evaluated for the Ginzburg-Landau theory of superconductivity. It is shown that, the next order correction to the Gaussian…
We compute the next-to-leading order strong interaction corrections to gluino-mediated Delta F=2 box diagrams in the Minimal Supersymmetric Standard Model. These corrections are given by two loop diagrams which we have calculated in three…
Using Operator Product Expansions and a graphical ansatz for the four-point function of the fundamental field \phi^{\alpha}(x) in the conformally invariant O(N) vector model, we calculate the next-to-leading order in 1/N values of the…
We derive optimal order a posteriori error estimates for fully discrete approximations of linear Schr\"odinger-type equations, in the $L^\infty(L^2)-$norm. For the discretization in time we use the Crank-Nicolson method, while for the space…
We compute the $O(1/N^2)$ correction to the critical exponent $2\lambda$ $=$ $-$ $\beta^\prime(g_c)$ for the chiral Gross Neveu model in arbitrary dimensions by substituting the corrections to the asymptotic scaling forms of the propagators…
In a companion paper (hep-th/0512317), we have presented an approximation scheme to solve the Non Perturbative Renormalization Group equations that allows the calculation of the $n$-point functions for arbitrary values of the external…
We apply the exact renormalization group formalism to compute the effective action and potential of the four dimensional O$(N)$ linear sigma model in large $N$. With a finite momentum cutoff in place, the model is well defined. In the naive…
Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration…
The coherent potential approximation (CPA) is extended to describe satisfactorily the motion of particles in a random potential which is spatially correlated and smoothly varying. In contrast to existing cluster-CPA methods, the present…
Using effective field theory (EFT) techniques we calculate the next-to-leading order (NLO) spin-orbit contributions to the gravitational potential of inspiralling compact binaries. We use the covariant spin supplementarity condition (SSC),…
We calculate the two-particle irreducible (2PI) effective potential of the O(N) linear sigma model in 1+1 dimensions. The approximations we use are the next-to-leading order of a 1/N expansion (for arbitrary N) and a kind of "resummed loop…
We compute the next-to-leading correction to the scaling dimension of large-charge operators in the $3d$ critical $O(N)$ model in a double scaling limit in which both $N$ and the operator charge $Q$ are taken to be large. When $Q \gg N$ our…
This dissertation addresses a topic that I have worked on over the past decade: the automation of next-to-leading order electroweak corrections in the Standard Model of particle physics. After introducing the basic concepts and techniques…
We apply the derivative expansion of the effective action in the exact renormalization group equation up to fourth order to the $Z_2$ and $O(N)$ symmetric scalar models in $d=3$ Euclidean dimensions. We compute the critical exponents $\nu$,…
Previous work on soft-gluon resummation for direct photon production is extended to include additional subleading logarithmic terms through O(alpha alpha_s^3) and some representative comparisons are made to experimental results from the…
Optimal sensor and actuator selection is a central challenge in high-dimensional estimation and control. Nearly all subsequent control decisions are affected by these sensor/actuator locations, and optimal placement amounts to an…
This paper focuses on finding approximate solutions to stochastic optimal control problems with control domains being not necessarily convex, where the state trajectory is subject to controlled stochastic differential equations. The…
In this paper, we propose a stochastic Gauss-Newton (SGN) algorithm to study the online principal component analysis (OPCA) problem, which is formulated by using the symmetric low-rank product (SLRP) model for dominant eigenspace…