Home on Nico Schuster, Cosmologist

Frozen in Time: Voids as Pristine Laboratories of Physics

Fri, 01 May 2026 00:00:00 +0000

The history of the universe is a tug-of-war between the attractive force of gravity and the repulsive push of dark energy. While galaxies and clusters are defined by chaotic mergers and rapid gravitational growth, cosmic voids are the emptiest regions of space and the first places where gravity loses this battle. This makes them a unique window into exactly how and when cosmic expansion takes over.

To uncover this transition, we utilized state-of-the-art cosmological simulations to trace the life cycle and evolution of these underdense regions across 12.5 billion years of history. By categorizing voids based on their relative rank within their population rather than their absolute physical size, we successfully mitigated the selection biases introduced by galaxy formation that otherwise can lead to counterintuitive results. Through this relative framework, we discovered that void evolution is not a continuous process of emptying out. Instead, once the universe reaches a certain age, these structures settle into a calm and stable state, passively following the expansion of the cosmos.

SAIL: A Framework for Rigorous AI-Assisted Scientific Coding

Sun, 01 Mar 2026 00:00:00 +0000

The recent explosion in generative AI and Large Language Models (LLMs) offers a powerful opportunity to accelerate software development and create new tools, such as interactive scientific visualizations. Yet this also introduces a significant risk: the tendency for AI to “hallucinate” or simplify scientific laws to satisfy coding tasks or context limits. Moreover, these LLMs often lack the specialized intuition needed to distinguish between a functional script and a rigorously sound model, showcasing the need for expert guidance.

Predicting Cosmic Voids with AI

Thu, 01 Jan 2026 00:00:00 +0000

Cosmic voids are among the most powerful tools we have for mapping the universe, but they come with a high computational cost. To accurately predict their sizes and densities, researchers traditionally have to run massive, time-consuming simulations for every single variation of the universe’s physical parameters and laws.

To solve this, we developed a set of “emulators” based on neural networks. By training these algorithms on thousands of gravity-only simulations, we created an AI capable of predicting void statistics almost instantly by learning how these statistics depend on the physical parameters of the universe. This allows us to bypass the need for brute-force computation, enabling much faster and more reliable cosmological parameter estimation.

Do messy baryons spoil cosmic voids?

Thu, 01 Aug 2024 00:00:00 +0000

The visible universe is shaped by violent astrophysical processes, from star formation to supermassive black holes driving gas out of galaxies. However, when physicists model the universe on a computer, they often simulate only dark matter and its gravity, as these other baryonic processes are incredibly complex and computationally expensive. While this shortcut leads to inaccuracies when predicting the properties of densely packed galaxies, we wanted to know if and how much these messy baryonic effects also disrupt the quiet, vast expanses of cosmic voids.

Simple dynamics inside the emptiest places

Mon, 01 May 2023 00:00:00 +0000

While denser regions of the cosmic web, like massive galaxy clusters, are dominated by complex gravitational forces, gravity behaves more gently in the emptiest regions of space, offering cleaner physical environments. Cosmic voids are actively expanding, pushing matter outward in a highly organized way that avoids the messy physics found elsewhere in the universe.

Using state-of-the-art hydrodynamical simulations (which include additional physics alongside standard gravity) across a vast range of scales, we investigated exactly how matter and galaxies move around these underdense regions. Surprisingly, we discovered that these motions can be described exquisitely well by the simple equations of linear mass conservation.

Weighing neutrinos with cosmic emptiness

Sun, 01 Dec 2019 00:00:00 +0000

Neutrinos are the lightest massive particles that we know of, but their exact mass is still one of the biggest unknowns in particle physics. Unlike regular matter, neutrinos move too fast to be trapped by the gravitational pull of typical galaxies and their dark matter halos, meaning they naturally flow into the nearly empty regions of space, cosmic voids, potentially altering them in the process.

Through dedicated simulations, we investigated how these lightweight particles affect the properties of voids. By analyzing the clustering bias of these voids, a measure of how voids are distributed relative to the overall matter in the universe, we found that void properties are highly sensitive to the total sum of neutrino masses.

About

Mon, 01 Jan 0001 00:00:00 +0000

I am Nico Schuster and I currently work as a Postdoctoral Researcher at the Centre de Physique des Particules de Marseille (CPPM) in Alice Pisani’s research group. I am active within several current and upcoming cosmological surveys: DESI, Euclid, the Vera C. Rubin Observatory (LSST), and the Wide-Field Spectroscopic Telescope (WST).

In my research, I explore the underlying properties of our Universe by using cosmic voids, the expansive, low-density regions between galaxies, to test fundamental physics. My research focuses on the theoretical modelling and interpretation of matter and galaxy distributions in and around voids, with the goal of sharpening cosmological constraints and establishing rigorous models for the next generation of galaxy surveys. In parallel, I study the imprints of dark energy, modified gravity, massive neutrinos, and other physical theories on cosmic voids, developing new observables tailored to disentangle their respective signatures.

CV

Mon, 01 Jan 0001 00:00:00 +0000

A short web CV. A more detailed publication list lives on the Publications page and on ORCID.

Research experience
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Postdoctoral Researcher — Centre de Physique des Particules de Marseille (CPPM), Oct 2024 – present.
Postdoctoral Researcher — Ludwig Maximilian University (LMU) of Munich, Oct 2023 – Sep 2024.

Education
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PhD in Physics — LMU Munich, 2020 – 2023. Thesis: Unique Characteristics of Voids in a Complex Universe. Supervisors: Nico Hamaus and Jochen Weller.
MSc in Physics — LMU Munich, 2015 – 2018. Thesis: Influence of massive neutrinos on cosmic voids.
BSc in Physics — LMU Munich, 2012 – 2015. Thesis: Der Blandford-Znajek Prozess.

Surveys & collaborations
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I am an active member of:

Legal & Privacy

Mon, 01 Jan 0001 00:00:00 +0000

Legal notice
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This is a personal, non-commercial website run by Nico Schuster. Published and maintained by Nico Schuster — schuster@cppm.in2p3.fr.

Hosting: Cloudflare, Inc. (Cloudflare Pages), 101 Townsend Street, San Francisco, CA 94107, USA — cloudflare.com.

Privacy
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This site is designed to respect your privacy. It sets no cookies and does not track you across the web.

Outreach & Media

Mon, 01 Jan 0001 00:00:00 +0000

Interactive Outreach Tools
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Beyond traditional outreach and both scientific and public writing, a major part of my science communication involves building interactive visualizations for the cosmology community to use.

My browser-based simulations of the cosmic web and gravitational lensing are publicly available and actively used by colleagues worldwide for teaching and public engagement. For more details on these tools and to explore them live, go here.

Tools & Visualizations

Mon, 01 Jan 0001 00:00:00 +0000

Three projects live here:

Cosmic Web Explorer — A real-time, interactive browser simulation of how the cosmic web of voids and filaments forms.
Gravitational Lensing Visualization — An interactive demo of how massive clusters and voids bend the light of background galaxies.
Void Profile Analysis Toolkit — A Python code for measuring density and velocity profiles around cosmic voids.

The two visualizations are fully interactable directly on this page. For a larger view on their own dedicated pages, use the Open in full window option below the embeds. Both were built using the SAIL framework (Scientist-AI-Loop). You can read more about this workflow on my publications page or directly in the paper.

Home on Nico Schuster, Cosmologist

Frozen in Time: Voids as Pristine Laboratories of Physics

SAIL: A Framework for Rigorous AI-Assisted Scientific Coding

Predicting Cosmic Voids with AI

Do messy baryons spoil cosmic voids?

Simple dynamics inside the emptiest places

Weighing neutrinos with cosmic emptiness

About

CV

Research experience #

Education #

Surveys & collaborations #

Legal & Privacy

Legal notice #

Privacy #

Outreach & Media

Interactive Outreach Tools #

Tools & Visualizations

Research experience
#

Education
#

Surveys & collaborations
#

Legal notice
#

Privacy
#

Interactive Outreach Tools
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