No Arabic abstract
High energy cosmic neutrino observations provide a sensitive test of Lorentz invariance violation, which may be a consequence of quantum gravity theories. We consider a class of non-renormalizable, Lorentz invariance violating operators that arise in an effective field theory description of Lorentz invariance violation in the neutrino sector inspired by Planck-scale physics and quantum gravity models. We assume a conservative generic scenario for the redshift distribution of extragalactic neutrino sources and employ Monte Carlo techniques to describe superluminal neutrino propagation, treating kinematically allowed energy losses of superluminal neutrinos caused by both vacuum pair emission and neutrino splitting. We consider EFTs with both non-renormalizable CPT-odd and non-renormalizable CPT-even operator dominance. We then compare the spectra derived using our Monte Carlo calculations in both cases with the spectrum observed by IceCube in order to determine the implications of our results regarding Planck-scale physics. We find that if the drop off in the neutrino flux above ~2 PeV is caused by Planck scale physics, rather than by a limiting energy in the source emission, a potentially significant pileup effect would be produced just below the drop off energy in the case of CPT-even operator dominance. However, such a clear drop off effect would not be observed if the CPT-odd, CPT-violating term dominates.
Observations of high energy neutrinos, both in the laboratory and from cosmic sources, can be a useful probe in searching for new physics. Such observations can provide sensitive tests of Lorentz invariance violation (LIV), which may be a the result of quantum gravity physics (QG). We review some observationally testable consequences of LIV using effective field theory (EFT) formalism. To do this, one can postulate the existence of additional small LIV terms in free particle Lagrangians, suppressed by powers of the Planck mass. The observational consequences of such terms are then examined. In particular, one can place limits on a class of non-renormalizable, mass dimension five and six Lorentz invariance violating operators that may be the result of QG.
We study the prospects of detecting signals of a resonant scattering of high-energy cosmic neutrinos on electrons in the atmosphere. Such a process is possible through an s-channel exchange of a isotriplet scalar particle predicted by some particle physics theories. We estimate the event rates for a reference detector setup with plausible assumptions on the interaction strengths and energy resolutions. We find as the most promising process the resonance production of tau neutrinos whose signature would be a quiet (in contrast with a hadronic bang) production of the tau lepton followed by a more noisy decay in downstream.
Ultrahigh-energy photons up to 1.4 peta-electronvolts have been observed by new cosmic-ray telescope in China -- a hint that Lorentz invariance might break down at the Planck-scale level.
Flavor ratios of very high energy astrophysical neutrinos, which can be studied at the Earth by a neutrino telescope such as IceCube, can serve to diagnose their production mechanism at the astrophysical source. The flavor ratios for neutrinos and antineutrinos can be quite different as we do not know how they are produced in the astrophysical environment. Due to this uncertainty the neutrino and antineutrino flavor ratios at the Earth also could be quite different. Nonetheless, it is generally assumed that flavor ratios for neutrinos and antineutrinos are the same at the Earth, in fitting the high energy astrophysical neutrino data. This is a reasonable assumption for the limited statistics for the data we currently have. However, in the future the fit must be performed allowing for a possible discrepancy in these two fractions in order to be able to disentangle different production mechanisms at the source from new physics in the neutrino sector. To reinforce this issue, in this work we show that a wrong assumption about the distribution of neutrino flavor ratios at the Earth may indeed lead to misleading interpretations of IceCube results.
Collisions at high-energy particle colliders are a traditionally fruitful source of exotic particle discoveries. Finding these rare particles requires solving difficult signal-versus-background classification problems, hence machine learning approaches are often used. Standard approaches have relied on `shallow machine learning models that have a limited capacity to learn complex non-linear functions of the inputs, and rely on a pain-staking search through manually constructed non-linear features. Progress on this problem has slowed, as a variety of techniques have shown equivalent performance. Recent advances in the field of deep learning make it possible to learn more complex functions and better discriminate between signal and background classes. Using benchmark datasets, we show that deep learning methods need no manually constructed inputs and yet improve the classification metric by as much as 8% over the best current approaches. This demonstrates that deep learning approaches can improve the power of collider searches for exotic particles.