Publications

Order by: publication date number of citations

• High-precision muon decay predictions for ALP searches

  Pulak Banerjee, Antonio Coutinho, Tim Engel, Andrea Gurgone, Adrian Signer, Yannick Ulrich

  SciPost Phys. 15, 021 (2023) · published 21 July 2023 | Toggle abstract · pdf

  We present an improved theoretical prediction of the positron energy spectrum for the polarised Michel decay $\mu^+\to e^+ \nu_e\bar{\nu}_\mu$. In addition to the full next-to-next-to-leading order correction of order $\alpha^2$ in the electromagnetic coupling, we include logarithmically enhanced terms at even higher orders. Logarithms due to collinear emission are included at next-to-leading accuracy up to order $\alpha^4$. At the endpoint of the Michel spectrum, soft photon emission results in large logarithms that are resummed up to next-to-next-to-leading logarithmic accuracy. We apply our results in the context of the MEG II and Mu3e experiments to estimate the impact of the theory error on the branching ratio sensitivity for the lepton-flavour-violating decay $\mu^+\to e^+ X$ of a muon into an axion-like particle $X$.

  5 citations

• Analytic neutrino oscillation probabilities

  Chee Sheng Fong

  SciPost Phys. 15, 013 (2023) · published 18 July 2023 | Toggle abstract · pdf

  In the work, we derive exact analytic expressions for $(3+N)$-flavor neutrino oscillation probabilities in an arbitrary matter potential in term of matrix elements and eigenvalues of the Hamiltonian. With the analytic expressions, we demonstrate that nonunitary and nonstandard neutrino interaction scenarios are physically distinct: they satisfy different identities and can in principle be distinguished experimentally. The analytic expressions are implemented in a public code NuProbe, a tool for probing new physics through neutrino oscillations.

  1 citation

• A symbol and coaction for higher-loop sunrise integrals

  Andreas Forum, Matt von Hippel

  SciPost Phys. Core 6, 050 (2023) · published 12 July 2023 | Toggle abstract · pdf

  We construct a symbol and coaction for the $l$-loop sunrise family of integrals, both for equal-mass and generic-mass cases. These constitute the first concrete examples of symbols and coactions for integrals involving Calabi-Yau threefolds and higher. In order to achieve a symbol of finite length, we recast the differential equations satisfied by these integrals in a unipotent form. We augment the integrals in a natural way by including ratios of maximal cuts $\tau_i$. We discuss the relationship of this construction to constructions of symbols and coactions for multiple polylogarithms and elliptic multiple polylogarithms, and its connection to notions of transcendental weight.

  3 citations

• New machine learning techniques for simulation-based inference: InferoStatic nets, kernel score estimation, and kernel likelihood ratio estimation

  Kyoungchul Kong, Konstantin T. Matchev, Stephen Mrenna, Prasanth Shyamsundar

  SciPost Phys. Codebases 14 (2023) · published 7 July 2023 | Toggle abstract · pdf

  We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar function called the inferostatic potential $\varphi$. In addition, we introduce new strategies, respectively called Kernel Score Estimation (KSE) and Kernel Likelihood Ratio Estimation (KLRE), to learn the score and the likelihood ratio functions from simulated data. We illustrate the new techniques with some toy examples and compare to existing approaches in the literature. We mention en passant some new loss functions that optimally incorporate latent information from simulations into the training procedure.

  1 citation

• Codebase release 0.1 for infstat

  Kyoungchul Kong, Konstantin T. Matchev, Stephen Mrenna, Prasanth Shyamsundar

  SciPost Phys. Codebases 14-r0.1 (2023) · published 7 July 2023 | Toggle abstract · src

  We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar function called the inferostatic potential $\varphi$. In addition, we introduce new strategies, respectively called Kernel Score Estimation (KSE) and Kernel Likelihood Ratio Estimation (KLRE), to learn the score and the likelihood ratio functions from simulated data. We illustrate the new techniques with some toy examples and compare to existing approaches in the literature. We mention en passant some new loss functions that optimally incorporate latent information from simulations into the training procedure.

  1 citation

• Exponential enhancement of dark matter freezeout abundance

  Bibhushan Shakya

  SciPost Phys. Proc. 12, 070 (2023) · published 5 July 2023 | Toggle abstract · pdf

  A novel paradigm for thermal dark matter (DM), termed "bouncing dark matter", is presented. In canonical thermal DM scenarios, the DM abundance falls exponentially as the temperature drops below the mass of DM, until thermal freezeout occurs. This note explores a broader class of thermal DM models that are exceptions to this rule, where the DM abundance can deviate from the exponentially falling curve, and even rise exponentially, while in thermal equilibrium. Such scenarios can feature present day DM annihilation cross sections much larger than the canonical thermal target, improving the prospects for indirect detection of DM annihilation signals.

• What charged cosmic rays tell us on dark matter

  Pierre Salati

  SciPost Phys. Proc. 12, 067 (2023) · published 5 July 2023 | Toggle abstract · pdf

  Dark matter particles could be the major component of the haloes of galaxies. Their mutual annihilations or decays would produce an indirect signature under the form of high-energy cosmic-rays. The focus of this presentation is on antimatter species, a component so rare that any excess over the background should be easily detected. After a recap on Galactic propagation, I will discuss positrons, antiprotons and anti-nuclei. For each of these species, anomalies have been reported. The antiproton excess, for instance, is currently a hot topic. Alas, it does not resist a correct treatment of theoretical and data errors.

• Disentangling sub-GeV dark matter from the diffuse supernova neutrino background using Hyper-Kamiokande

  Sandra Robles

  SciPost Phys. Proc. 12, 065 (2023) · published 5 July 2023 | Toggle abstract · pdf

  The upcoming Hyper-Kamiokande (HyperK) experiment is expected to detect the Diffuse Supernova Neutrino Background (DSNB). This requires to ponder all possible sources of background. Sub-GeV dark matter (DM) which annihilates into neutrinos is a potential background that has not been considered so far. We simulate DSNB and DM signals, as well as backgrounds in the HyperK detector. We find that DM-induced neutrinos could indeed alter the extraction of the correct values of the parameters of interest for DSNB physics. Since the DSNB is an isotropic signal, and DM originates primarily from the Galactic centre, we show that this effect could be alleviated with an on-off analysis.

  1 citation

• Impact of nuclear structure from shell model calculations on nuclear responses to WIMP elastic scattering for $^{19}$F and $^{nat}$Xe targets

  Raghda Abdel Khaleq, Cedric Simenel, Andrew E. Stuchbery

  SciPost Phys. Proc. 12, 062 (2023) · published 5 July 2023 | Toggle abstract · pdf

  Non-relativistic effective field theory (NREFT) is one approach used for describing the interaction of WIMPs with ordinary matter. Among other factors, these interactions are expected to be affected by the structure of the atomic nuclei in the target. The sensitivity of the nuclear response components of the WIMP-nucleus scattering amplitude is investigated using shell model calculations for $^{19}$F and $^{nat}$Xe. Resulting integrated nuclear response values are shown to be sensitive to some specifics of the nuclear structure calculations.

  1 citation

• Improved treatment of dark matter capture in compact stars

  Sandra Robles

  SciPost Phys. Proc. 12, 057 (2023) · published 5 July 2023 | Toggle abstract · pdf

  Compact stellar objects are promising cosmic laboratories to test the nature of dark matter (DM). DM captured by the strong gravitational field of these stellar remnants transfers kinetic energy to the star during the collision. This can have various effects such as anomalous heating of old compact stars. The proper calculation of the DM capture rate is key to derive bounds on DM interactions in any scenario involving DM accretion in a star. We improve former calculations, which rely on approximations, for both white dwarfs (WDs) and neutron stars (NSs). We account for the stellar structure, gravitational focusing, relativistic kinematics, Pauli blocking, realistic form factors, and strong interactions (NSs). Considering DM capture by scattering off either ions or degenerate electrons in WDs, we show that old WDs in DM-rich environments could probe the elusive sub-GeV mass regime for both DM-nucleon and DM-electron scattering. In NSs, DM can be captured via collisions with strongly interacting baryons or relativistic leptons. We project the NS sensitivity to DM-nucleon and DM-lepton scattering cross sections which greatly exceeds that of direct detection experiments, especially for low mass DM.