249 research outputs found
Weakly-Interacting Massive Particles in Non-supersymmetric SO(10) Grand Unified Models
Non-supersymmetric SO(10) grand unified theories provide a framework in which
the stability of dark matter is explained while gauge coupling unification is
realized. In this work, we systematically study this possibility by classifying
weakly interacting DM candidates in terms of their quantum numbers of
, , and . We
consider both scalar and fermion candidates. We show that the requirement of a
sufficiently high unification scale to ensure a proton lifetime compatible with
experimental constraints plays a strong role in selecting viable candidates.
Among the scalar candidates originating from either a 16 or 144 of SO(10), only
SU(2) singlets with zero hypercharge or doublets with satisfy all
constraints for
and intermediate scale gauge groups. Among fermion triplets with
zero hypercharge, only a triplet in the 45 with intermediate group
leads to
solutions with and a long proton lifetime. We find
three models with weak doublets and as dark matter candidates for the
and
intermediate
scale gauge groups assuming a minimal Higgs content. We also discuss how these
models may be tested at accelerators and in dark matter detection experiments.Comment: 43 pages, 3 figure
Implications of Gravitational Waves for Supersymmetric Grand Unification
Supersymmetric grand unification based on is one of the most
attractive paradigms in physics beyond the Standard Model. Inspired by the
recent NANOGrav signal, we discuss the implications of detecting a stochastic
gravitational wave background emitted by a network of cosmic strings for the
grand unification. Starting from a minimal model with multiple steps
of symmetry breaking, we show that it generally prefers a high intermediate
scale above that is favored by observable primordial
gravitational waves. The observed spectrum can potentially narrow the possible
range of the cosmic string scale and restricts the unified couplings and the
unification scale by requiring gauge coupling unification. As an indirect
consequence of the high cosmic string scale, the monopole abundance places
non-trivial constraints on the theory. These are complementary to the proton
decay constraints and probe different facets of supersymmetric
unification theories.Comment: 9 pages, 1 figure, 3 table
Dark Matter Models in Non-Supersymmetric SO(10) Unification Models
University of Minnesota Ph.D. dissertation. June 2017. Major: Physics. Advisor: Keith Olive. 1 computer file (PDF); viii, 107 pages.This thesis studies systematically non-supersymmetric models that contain dark matter candidates. The stability of the dark matter is guaranteed by a remnant Z 2 symmetry embedded naturally in SO(10). We build models base on various dark matter production mechanism, including the non-equilibrium thermal dark matter scenario, the weakly interactive massive particle scenario, and the asymmetric dark matter scenario. Although we start from very general assumptions on the choice of dark matter representation and the symmetry breaking pattern, the number of viable models is severely restricted by the requirement of gauge coupling unification. These models are then checked against several phenomenological constraints, such as the light neutrino masses, direct detection bounds on dark matter candidates and the proton decay lifetime. Finally, we demonstrate that the vacuum stability problem of the Standard Model can be evaded by one of our scalar dark matter models
Dark Matter and Gauge Coupling Unification in Non-supersymmetric SO(10) Grand Unified Models
Unlike minimal SU(5), SO(10) provides a straightforward path towards gauge
coupling unification by modifying the renormalization group evolution of the
gauge couplings above some intermediate scale which may also be related to the
seesaw mechanism for neutrino masses. Unification can be achieved for several
different choices of the intermediate gauge group below the SO(10) breaking
scale. In this work, we consider in detail the possibility that SO(10)
unification may also provide a natural dark matter candidate, stability being
guaranteed by a leftover symmetry. We systematically examine the possible
intermediate gauge groups which allow a non-degenerate, fermionic, Standard
Model singlet dark matter candidate while at the same time respecting gauge
coupling unification. Our analysis is done at the two-loop level. Surprisingly,
despite the richness of SO(10), we find that only two models survive the
analysis of phenomenological constraints, which include suitable neutrino
masses, proton decay, and reheating.Comment: 39 pages, 8 figures. Version accepted for publication in Physical
Review
Post-Inflationary Dark Matter Bremsstrahlung
Dark matter may only interact with the visible sector efficiently at energy
scales above the inflaton mass, such as the Planck scale or the grand
unification scale. In such a scenario, the dark matter is mainly produced out
of equilibrium during the period of reheating, often referred to as UV
freeze-in. We evaluate the abundance of the dark matter generated from
bremsstrahlung off the inflaton decay products assuming no direct coupling
between the inflaton and the dark matter. This process generally dominates the
production of dark matter for low reheating temperatures where the production
through the annihilations of particle in the thermal plasma becomes
inefficient. We find that the bremsstrahlung process dominates for reheating
temperatures GeV, and produces the requisite
density of dark matter for a UV scale GeV. As examples, we
calculate numerically the yield of the dark matter bremsstrahlung through
gravitation and dimension-6 vector portal effective interactions.Comment: 19 pages, 5 figure
Federated Unlearning via Active Forgetting
The increasing concerns regarding the privacy of machine learning models have
catalyzed the exploration of machine unlearning, i.e., a process that removes
the influence of training data on machine learning models. This concern also
arises in the realm of federated learning, prompting researchers to address the
federated unlearning problem. However, federated unlearning remains
challenging. Existing unlearning methods can be broadly categorized into two
approaches, i.e., exact unlearning and approximate unlearning. Firstly,
implementing exact unlearning, which typically relies on the
partition-aggregation framework, in a distributed manner does not improve time
efficiency theoretically. Secondly, existing federated (approximate) unlearning
methods suffer from imprecise data influence estimation, significant
computational burden, or both. To this end, we propose a novel federated
unlearning framework based on incremental learning, which is independent of
specific models and federated settings. Our framework differs from existing
federated unlearning methods that rely on approximate retraining or data
influence estimation. Instead, we leverage new memories to overwrite old ones,
imitating the process of \textit{active forgetting} in neurology. Specifically,
the model, intended to unlearn, serves as a student model that continuously
learns from randomly initiated teacher models. To preserve catastrophic
forgetting of non-target data, we utilize elastic weight consolidation to
elastically constrain weight change. Extensive experiments on three benchmark
datasets demonstrate the efficiency and effectiveness of our proposed method.
The result of backdoor attacks demonstrates that our proposed method achieves
satisfying completeness
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