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A modified version of PQCD considered in previous works is further investigated in the case of a vanishing gluon condensate, by retaining only the quark one. In this case the Green functions generating functional is expressed in a simple form in which Dirac’s delta functions are now absent from the free propagators. The new expansion implements the dimensional transmutation effect through a single interaction vertex in addition to the standard ones in mass less QCD. The results of an ongoing two loop evaluation of the vacuum energy will be presented. The potential is parameterized as a function of the quark mass (defined by the pole of the first corrections to the quark propagator), the assumed finite zero momentum limit of the coupling constant g and the dimensional regularization parameter. The first condensate dependent corrections to the gluon and quark self-energies and propagators are evaluated. Assuming the possibility of fixing a minimum of the potential at the experimental value of the top quark mass =173 GeV, we evaluate the pole of the simplest correction to the propagator of the composite operator describing the quark condensate. Then, alter adopting the idea from the former top condensate models, in which the Higgs field corresponds to the quark condensate, the obtained pole gave a first rough estimate for the Higgs mass =168.2 GeV. Although being inside of the recently experimentally excluded region: 160-170 GeV, this mass value has the chance of being modified by a better approximation being currently considered for the gluon propagator entering its evaluation.

Solving linear systems of equations is a common problem that arises both on its own and as a subroutine in more complex problems: given a matrix A and a vector b, find a vector x such that Ax=b. Often, one does not need to know the solution x itself, but rather an approximation of the expectation value of some operator associated with x, e.g., x'Mx for some matrix M. In this case, when A is sparse and well-conditioned, with largest dimension N, the best known classical algorithms can find x and estimate x'Mx in O(N * poly(log(N))) time. In this talk I'll describe a quantum algorithm for solving linear sets of equations that runs in poly(log N) time, an exponential improvement over the best classical algorithm. This talk is based on my paper arXiv:0811.3171v2, which was written with Avinatan Hassidim and Seth Lloyd.