No Arabic abstract
Hidden valleys, hidden sectors with multi-particle dynamics and a mass gap, can produce striking and unusual final states at the LHC. Unparticle models, hidden-sectors with conformal dynamics and no (or a very small) mass gap, can result in unusual kinematic features that indirectly reflect the conformal dynamics. When sufficiently large mass gaps are added to unparticle models, they become hidden valley models. Predictions using unparticle propagators alone overlook the most striking signals, which are typically of hidden-valley type. Inclusive signatures often cannot be predicted from unparticle dimensions, and exclusive signatures are often visible and can be spectacular. Among possible signatures are: Higgs decays to pairs of particles that in turn decay to two quarks, leptons or gauge bosons, possibly with displaced vertices; Higgs, top, and neutralino decays to more than six particles; resonances below an ``unparticle continuum which produce multi-body final states; etc. The Stephanov model is deconstructed, reconstructed, and shown to be a hidden valley model. Some effects of strong dynamics on hidden valley observables, not predictable using unparticle methods, are discussed, including resonances, reduced flavor symmetry breaking, reduced supersymmetry breaking, and a strongly enhanced hidden parton shower.
We consider scale invariant theories of continuous mass fields, and show how interactions of these fields with the standard model can reproduce unparticle interactions. There is no fixed point or dimensional transmutation involved in this approach. We generalize interactions of the standard model to multiple unparticles in this formalism and explicitly work out some examples, in particular we show that the product of two scalar unparticles behaves as a normalized scalar unparticle with dimension equal to the sum of the two composite unparticle dimensions. Extending the formalism to scale invariant interactions of continuous mass fields, we calculate three point function of unparticles.
Fermionic unparticles are introduced and their basic properties are discussed. Some phenomenologies related are exploited, such as their effects on charged Higgs boson decays and anomalous magnetic moments of leptons. Also, it has been found that measurements of $B^0-bar B^0$ mixing could yield interesting constraints on couplings between unparticle operators and standard model fields.
While stochastic gradient descent (SGD) is still the emph{de facto} algorithm in deep learning, adaptive methods like Clipped SGD/Adam have been observed to outperform SGD across important tasks, such as attention models. The settings under which SGD performs poorly in comparison to adaptive methods are not well understood yet. In this paper, we provide empirical and theoretical evidence that a heavy-tailed distribution of the noise in stochastic gradients is one cause of SGDs poor performance. We provide the first tight upper and lower convergence bounds for adaptive gradient methods under heavy-tailed noise. Further, we demonstrate how gradient clipping plays a key role in addressing heavy-tailed gradient noise. Subsequently, we show how clipping can be applied in practice by developing an emph{adaptive} coordinate-wise clipping algorithm (ACClip) and demonstrate its superior performance on BERT pretraining and finetuning tasks.
We use semi-analytic models implemented in the Millennium Simulation to analyze the merging histories of dark matter haloes and of the galaxies that reside in them. We assume that supermassive black holes only exist in galaxies that have experienced at least one major merger. Only a few percent of galaxies with stellar masses less than $M_* < 10^{10} M_{odot}$ are predicted to have experienced a major merger and to contain a black hole. The fraction of galaxies with black holes increases very steeply at larger stellar masses. This agrees well with the observed strong mass dependence of the fraction of nearby galaxies that contain either low-luminosity (LINER-type) or higher-luminosity (Seyfert or composite-type) AGN. We then investigate when the major mergers that first create the black holes are predicted to occur. High mass galaxies are predicted to have formed their black holes at very early epochs. The majority of low mass galaxies never experience a major merger and hence do not contain a black hole, but a significant fraction of the supermassive black holes that do exist in low mass galaxies are predicted to have formed recently.
Some modern cosmological models predict the appearance of Boltzmann Brains: observers who randomly fluctuate out of a thermal bath rather than naturally evolving from a low-entropy Big Bang. A theory in which most observers are of the Boltzmann Brain type is generally thought to be unacceptable, although opinions differ. I argue that such theories are indeed unacceptable: the real problem is with fluctuations into observers who are locally identical to ordinary observers, and their existence cannot be swept under the rug by a choice of probability distributions over observers. The issue is not that the existence of such observers is ruled out by data, but that the theories that predict them are cognitively unstable: they cannot simultaneously be true and justifiably believed.