Abstract: Using the Fenchel-Eggleston theorem for convex hulls (an extension of the Caratheodory theorem), we prove that any likelihood can be maximized by either a dark matter 1-speed distribution F(v) in Earth's frame or 2-Galactic velocity distribution f(gal) ((u) over right arrow), consisting of a sum of delta functions. The former case applies only to time-averaged rate measurements and the maximum number of delta functions is (N-1), where N is the total number of data entries. The second case applies to any harmonic expansion coefficient of the time-dependent rate and the maximum number of terms is N. Using time-averaged rates, the aforementioned form of F(v) results in a piecewise constant unmodulated halo function (eta) over tilde (BF)-B-0 (v(min)) (which is an integral of the speed distribution) with at most (N-1) downward steps. The authors had previously proven this result for likelihoods comprised of at least one extended likelihood, and found the best-fit halo function to be unique. This uniqueness, however, cannot be guaranteed in the more general analysis applied to arbitrary likelihoods. Thus we introduce a method for determining whether there exists a unique best-fit halo function, and provide a procedure for constructing either a pointwise con fi dence band, if the best-fit halo function is unique, or a degeneracy band, if it is not. Using measurements of modulation amplitudes, the aforementioned form of f(gal) ((u) over right arrow), which is a sum of Galactic streams, yields a periodic time-dependent halo function (eta) over right arrow BF (v(min); t) which at any fixed time is a piecewise constant function of v(min) with at most N downward steps. In this case, we explain how to construct pointwise confidence and degeneracy bands from the time-averaged halo function. Finally, we show that requiring an isotropic Galactic velocity distribution leads to a Galactic speed distribution F(u)that is once again a sum of delta functions, and produces a time-dependent (eta) over tilde BF (v(min); t) function (and a time-averaged (eta) over tilde (0) BF (v(min))) that is piecewise linear, di ff ering significantly from best-fit halo functions obtained without the assumption of isotropy.

Abstract: The atmospheric neutrino passing fraction, or self-veto, is defined as the probability for an atmospheric neutrino not to be accompanied by a detectable muon from the same cosmic-ray air shower. Building upon previous work, we propose a redefinition of the passing fractions by unifying the treatment for muon and electron neutrinos. Several approximations have also been removed. This enables performing detailed estimations of the uncertainties in the passing fractions from several inputs: muon losses, cosmic-ray spectrum, hadronic-interaction models and atmosphere-density profiles. We also study the passing fractions under variations of the detector configuration: depth, surrounding medium and muon veto trigger probability. The calculation exhibits excellent agreement with passing fractions obtained from Monte Carlo simulations. Finally, we provide a general software framework to implement this veto technique for all large-scale neutrino observatories.

Abstract: Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of observables that exhibit the highest possible sensitivity to the underlying theory parameters. In this work we develop a flexible open source frame-work, ML4EFT, enabling the integration of unbinned multivariate observables into global SMEFT fits. As compared to traditional measurements, such observables enhance the sensitivity to the theory parameters by preventing the information loss incurred when binning in a subset of final-state kinematic variables. Our strategy combines machine learning regression and classification techniques to parameterize high-dimensional likelihood ratios, using the Monte Carlo replica method to estimate and propagate methodological uncertainties. As a proof of concept we construct unbinned multivariate observables for top-quark pair and Higgs+Z production at the LHC, demonstrate their impact on the SMEFT parameter space as compared to binned measurements, and study the improved constraints associated to multivariate inputs. Since the number of neural networks to be trained scales quadratically with the number of parameters and can be fully parallelized, the ML4EFT framework is well-suited to construct unbinned multivariate observables which depend on up to tens of EFT coefficients, as required in global fits.

Abstract: The Scotogenic model is a popular scenario that induces radiative Majorana neutrino masses and includes a weakly-interacting dark matter candidate. We classify all possible ultraviolet extensions of the Scotogenic model in which (i) the dark DOUBLE-STRUCK CAPITAL Z(2) parity emerges at low energies after the spontaneous breaking of a global U(1)(L) lepton number symmetry, and (ii) the low-energy effective theory contains a naturally small lepton number breaking parameter, suppressed by the mass of a heavy mediator integrated out at tree-level. We find 50 such models and discuss two of them in detail to illustrate our setup. We also discuss some general aspects of the phenomenology of the models in our classification, exploring possible lepton flavor violating signals, collider signatures and implications for dark matter. The phenomenological prospects of these scenarios are very rich due to the presence of additional scalar states, including a massless Goldstone boson.

Abstract: We investigate gravitational -wave backgrounds (GWBs) of primordial origin that would manifest only at ultrahigh frequencies, from kilohertz to 100 gigahertz, and leave no signal at LIGO, the Einstein Telescope, the Cosmic Explorer, LISA, or pulsar -timing arrays. We focus on GWBs produced by cosmic strings and make predictions for the GW spectra scanning over high-energy scale (beyond 10 10 GeV) particle physics parameters. Signals from local string networks can easily be as large as the big bang nucleosynthesis/ cosmic microwave background bounds, with a characteristic strain as high as 10 – 26 in the 10 kHz band, offering prospects to probe grand unification physics in the 10 14 -10 17 GeV energy range. In comparison, GWB from axionic strings is suppressed (with maximal characteristic strain similar to 10 – 31 ) due to the early matter era induced by the associated heavy axions. We estimate the needed reach of hypothetical futuristic GW detectors to probe such GWB and, therefore, the corresponding high-energy physics processes. Beyond the information of the symmetry -breaking scale, the high -frequency spectrum encodes the microscopic structure of the strings through the position of the UV cutoffs associated with cusps and kinks, as well as potential information about friction forces on the string. The IR slope, on the other hand, reflects the physics responsible for the decay of the string network. We discuss possible strategies for reconstructing the scalar potential, particularly the scalar self -coupling, from the measurement of the UV cutoff of the GW spectrum.