In this work, I explore the creation of new methods that optimize simulations of the gravitational N-body problem. Specifically, I take advantage of the recent popularity of Machine Learning methods to find tools that can suit this problem.

The first direct detection of gravitational waves opened the possibility of mapping the Universe via this new and independent messenger.

Promotor: K. Kuijken, Co-Promotor: H. Hoekstra

We explored the Universe using weak gravitational lensing, a phenomenon that occurs when light from distant galaxies is bent by the gravitational fields of closer cosmic objects, much like how a lens distorts light.

One of the most important correlation functions in physics, especially in cosmology, is the energy density, which describes how much energy is present at each point in spacetime due to matter fields. A key contribution to the energy density of the primordial universe comes from gravitational waves (GWs),…

Of all the mass in our Universe, 80% is thought to consist of a hypothetical and invisible substance called dark matter (DM).

In astronomy, the interpration of observations and measurements plays a crucial role: we rely purely and fundamentally on the information that reaches us as observers. And 80% of all matter in the universe is undetectable directly.

Promotor: Prof.dr. S. Portegies Zwart

In this thesis we study the landscape of gravitational models which modify GR by introducing an additional scalar degree of freedom (d.o.f.) to source Cosmic Acceleration.

At the largest scales, two ingredients dictate the distribution of matter in the Universe. The first is dark matter, acting as an invisible scaffolding held together by gravitational forces.

It's one of the big cosmology debates: the universe is expanding, but how fast exactly? Two available measurements yield different results. Leiden physicist David Harvey adapted an independent third measurement method, using the light warping properties of galaxies predicted by Einstein. He published…

This thesis investigates the structural evolution and assembly of galaxies since the first few billions years after the big bang.

For centuries astronomers studied the Universe by collecting light. Nowadays, we are living in times of great technological advancements, which allow us to explore our Universe in a new way - though gravitational wave radiation.

Three major research projects involving Leiden scientists have been awarded a grant from NWO’s Gravitation Programme. The projects are on innovation processes, organs-on-chips and quantum software.

Leiden University is involved in five new NWO Gravitation projects. Two relate to mental disorder and the remaining three to a healthy lifestyle, the combination of human and artificial intelligence, and the special relationship between plants and microbes.

The ultimate goal of cosmologists is to find a cosmological model able to explain the current observational data.

The physical origin of the dozens of stellar-mass binaries, the mergers of which have been detected by the LIGO-Virgo-KAGRA collaboration via gravitational waves, is still unknown.

The Advanced Nano-electrochemistry Institute Of the Netherlands (ANION) consortium will receive 23.6m euros in Gravitation funding for research on important electrochemical processes for energy transition. An additional four consortia with members from Leiden have also been awarded funding.

How do secondary school teachers’ professional learning preferences relate to teaching experience and the school context?

Galaxy intrinsic alignments induce a major astrophysical contamination to weak gravitational lensing measurements and need to be modelled and mitigated when extracting cosmological information from such measurements.

Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

In this dissertation (titled: Exploring the Synergies between Transfer in Reinforcement Learning and Procedural Content Generation) we explore how the two research fields named in the title, namely Transfer in Reinforcement Learning (TRL) and Procedural Content Generation (PCG) can synergize togethe…

Promotor: J. N. Kok, Co-promotor: A. J. Knobbe

Promotor: Koen Kuijken Co-promotor: Henk Hoekstra

Music profession requires strong reflective, collaborative, creative and improvisational skills, yet prevailing one-to-one tuition in conservatoire education focuses mainly on transmission of craft skills. Examining effects of students' collaborative and experiential learning, as in learning labs, creates…

With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.

The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.

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The aim of this study was to provide insight into how teachers in higher education can be supported in the design, implementation and evaluation of group assignments by developing a theoretical and evidence-based framework for the design of group assignments.

Galaxies form and live inside dark matter haloes. As a consequence, they are exposed to the tidal fields generated by the surrounding matter distribution: this imprints a preferential direction to the galaxy shapes, which leads to a coherent alignment on physically close galaxies, called intrinsic a…

In this thesis, the research focuses on the properties of dark matter and dark matter haloes and how they connect with the galaxies we can observe in the Universe.

This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.

The aim of this thesis was to examine what teachers want to learn themselves. The main research question was: what, how and why teachers want to learn? And does this depend on their years of teaching experience and the school at which they work?

This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.

Heightened activation of the striatum that adolescents show in response to reward is often associated with risk-taking and negative health consequences. This article in Nature Communications investigates a potential positive side of this heightened activation. It shows that the activity peak in late…

The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.

The programme is also offered in a blended learning version: this is a combination of distance learning and face-to-face learning. Read more information

Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…