Little hierarchy, little higgses, and a little symmetry

By Hsin-Chia Cheng, I. Low. 2004

388 citations recorded by the source corpus.

Little Higgs theories are an attempt to address the ``little hierarchy problem,'' i.e., the tension between the naturalness of the electroweak scale and the precision electroweak measurements showing no evidence for new physics up to 5 – 10 TeV. In little Higgs theories, the Higgs mass-squareds are protected at one-loop order from the quadratic divergences. This allows the cutoff of the theory to be raised up to ~ 10 TeV, beyond the scales probed by the current precision data. However, strong constraints can still arise from the contributions of the new TeV scale particles which cancel the one-loop quadratic divergences from the standard model fields, and hence re-introduces the fine-tuning problem. In this paper we show that a new symmetry, denoted as T-parity, under which all heavy gauge bosons and scalar triplets are odd, can remove all the tree-level contributions to the electroweak observables and therefore makes the little Higgs theories completely natural. The T-parity can be manifestly implemented in a majority of little Higgs models by following the most general construction of the low energy effective theory a la Callan, Coleman, Wess and Zumino. In particular, we discuss in detail how to implement the T-parity in the littlest Higgs model based on SU(5)/SO(5). The symmetry breaking scale f can be even lower than 500 GeV if the contributions from the higher dimensional operators due to the unknown UV physics at the cutoff are somewhat small. The existence of T-parity has drastic impacts on the phenomenology of the little Higgs theories. The T-odd particles need to be pair-produced and will cascade down to the lightest T-odd particle (LTP) which is stable. A neutral LTP gives rise to missing energy signals at the colliders which can mimic supersymmetry. It can also serve as a good dark matter candidate.

Subfields: Artificial Intelligence, Nuclear and High Energy Physics, Political Science and International Relations

View Paper: https://www.semanticscholar.org/paper/939a6480e0a077a693e6e2031774497e613c40da

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

  1. David Tucker-Smith
  2. M. Schmaltz
  3. N. Arkani-Hamed
  4. Konstantin T. Matchev
  5. S. Dimopoulos
  6. Kyoungchul Kong
  7. S. Kachru
  8. I. Low

In Nuclear and High Energy Physics

  1. David Tucker-Smith
  2. S. Kachru
  3. S. Dimopoulos
  4. N. Arkani-Hamed
  5. Kyoungchul Kong
  6. M. Schmaltz
  7. AseshKrishna Datta
  8. Konstantin T. Matchev

In Political Science and International Relations

  1. S. Kachru
  2. S. Dimopoulos
  3. N. Arkani-Hamed
  4. David Tucker-Smith
  5. M. Schmaltz
  6. Cms Collaboration
  7. G. Villadoro
  8. G. Giudice

Citations in the corpus