Friday, 17th November 2023

Johannes Michel (UvA/Nikhef)

Elisa Chisari (UU)

Maximilian Becker (RU)

Ro Jefferson (UU)

Johannes Michel (UvA/Nikhef) – Transverse Momentum Distributions from TeV to MeV Scales
Abstract:
The LHC precision program critically relies on precise theory predictions for Standard-Model baseline cross sections to probe New Physics up to tens of TeV. In this talk, I will give a broad overview how the factorization of differential cross sections for the production of Higgs, Z, or W bosons in terms of transverse-momentum dependent (TMD) parton distribution functions enables theory to meet these precision demands. Tracing the frontier of current research in this area from a bird’s-eye view, I will discuss the role of three and four-loop QCD corrections, subleading-power TMD factorization, and our still limited knowledge of the nonperturbative structure of the proton. In the second part of my talk, I will turn to the closely related TMD fragmentation functions that describe how partons hadronize in 3D. Focussing on the 3D fragmentation of bottom and charm quarks, I will discuss how measurements at B factories, the LHC, and the future Electron-Ion Collider may help shed light on the elusive dynamics of QCD confinement at a scale of hundreds of MeV.

Elisa Chisari (UU) – Cosmology with the next generation of galaxy surveys: challenges and rewards
Abstract:
A new generation of galaxy surveys is at our doorstep. By mapping billions of galaxies over the sky, they will deliver precision constraints on the cosmological model. The significant gains in constraining power are accompanied by the need to develop more accurate models of the large-scale structure. Several physical effects will come into play that could be neglected or simplified in previous analyses. I will discuss the constraining power of upcoming surveys, focusing mostly on Rubin Observatory, and the modelling challenges they face.
Amongst the physical effects that need to be modelled, I will focus mostly on the “intrinsic alignments” of galaxies: alignments between their shapes that are likely to arise from tidal interactions between them. I will introduce a new modelling strategy based on the effective-field-theory description of intrinsic alignments and I will show tests of its robustness against numerical simulations. Finally, I will highlight new opportunities that will arise from modelling and constraining intrinsic alignments.

Maximilian Becker (RU) – Self-consistent quantization through N-type cutoffs: background independence and gravity coupled approximants
Abstract:
A key desideratum of a quantum theory in which gravity plays a non-trivial role is that any background structures involved must be self-consistently determined by the dynamics of the theory. In this talk I will present a recently proposed self-consistent quantization scheme for quantum field theories, in which background independence is promoted to the level of the regularized precursor of the QFT. This is implemented by constructing a sequence of “gravity-coupled approximants”, i.e. regularized quantum systems self-consistently coupled to a background metric, labeled by a dimensionless number N that designates “how many” quantum modes are allowed in the path integral. I will review the construction of such “N-cutoffs” for scalar and metric fluctuations on background Riemannian manifolds, focussing on the paradigmatic examples of the sphere (compact geometries) and the hyperboloid (non-compact geometries). It will be shown that demanding self-consistency of background structures already at the level of the regularized theory leads to novel behavior when the regulator is removed. In particular, without any fine-tuning of parameters, the zero-point fluctuations of these fields do not lead to the commonly expected cosmological constant problem of a cutoff sized background curvature. On the contrary, the inclusion of increasingly many field modes drives the curvature towards arbitrarily small values, vanishing when the cutoff N is taken to infinity.

Ro Jefferson (UU) – Physics ∩ Machine Learning
Abstract:
Machine learning has become both powerful and ubiquitous, but remains a black box whose internal workings are still largely unclear. In this talk, I will discuss some interesting connections between ideas in physics (in particular QFT and the renormalization group) and deep neural networks in particular, which collectively motivate a physics-based approach towards a theory of deep learning.

Z011 of CWI/Nikhef at the Science Park in Amsterdam

(A zoom connection is available for those that wish to join remotely: https://go.nikhef.nl/colloquium)

10:00  Coffee/tea
10:30   Johannes Michel (UvA/Nikhef)
11:15     Elisa Chisari (UU) –Nikhef colloquium–
12:15    Lunch
14:00  Maximilian Becker (RU)
14:45   Ro Jefferson (UU)
15:30   Borrel/drinks

For questions or suggestions, please contact one of the organizers:

Wouter Waalewijn (NIKHEF)
tel: +31 (0)20 5255773
e-mail: wouterw@nikhef.nl

Marieke Postma (Nikhef)
tel.: +31 (0)20 5925128
e-mail: mpostma@nikhef.nl

Timothy Budd (RU)
tel.: +31(0)24 3616161
e-mail: T.Budd@science.ru.nl