GAILAVERY

I am GAIL AVERY, a cosmologist and computational astrophysicist specializing in the detection, characterization, and cosmological implications of cosmic voids—vast underdense regions shaping the large-scale structure of the universe. With a Ph.D. in Observational Cosmology (Princeton University, 2021) and recipient of the 2024 American Astronomical Society’s Beatrice Tinsley Prize, I have pioneered novel methodologies to map and interpret cosmic voids as probes of dark energy, modified gravity, and primordial density fluctuations. As the Principal Investigator of the NSF-funded Cosmic Void Frontier Project and Lead Scientist at the Intergalactic Medium Dynamics Consortium, I synergize galaxy surveys, N-body simulations, and topological data analysis to decode the "emptiness" that defines cosmic voids. My 2023 algorithm VOID-NET, a deep learning framework achieving 98% accuracy in distinguishing noise from true voids in DESI and Euclid datasets, has become a cornerstone for next-generation void cosmology.

Research Motivation

Cosmic voids, occupying over 60% of the universe’s volume, are sensitive tracers of dark energy and gravitational collapse physics. However, their identification and utilization face three fundamental challenges:

1. Observational Noise: Contamination by foreground galaxies and redshift-space distortions in spectroscopic surveys.

2. Dynamic Boundaries: Ambiguity in defining void edges due to hierarchical structure formation.

3. Cosmological Model Dependence: Biases introduced by assuming specific dark energy equations of state during void detection.

My work reimagines cosmic voids as multi-messenger cosmological laboratories, leveraging their unique geometry, velocity fields, and thermal histories to test theories beyond ΛCDM.

Methodological Framework

My research integrates observational data, numerical simulations, and topological machine learning:

1. Multi-Tracer Void Identification

• Developed VOIDSPHERE:

  • A hybrid algorithm combining galaxy positions, weak lensing shear maps, and kinetic Sunyaev-Zel’dovich (kSZ) signals to detect voids across redshifts (0 < z < 2.5).

  • Uncovered the "Boomerang Void" in DESI Data Release 7, whose repulsive velocity profile challenges standard ΛCDM predictions.

  • Adopted by the European Southern Observatory for Euclid satellite void catalog production.

2. Void Dynamical Tomography

• Engineered DARKFLOW:

  • A Bayesian hierarchical model reconstructing void velocity fields from galaxy peculiar velocities and CMB dipole measurements.

  • Revealed coherent inflows toward the Local Void at 400 km/s, resolving the "Hubble tension" within 1σ confidence.

  • Integrated into NASA’s Nancy Grace Roman Telescope pipeline for high-z void studies.

3. Topological Persistence Analysis

• Launched COSMIC TOPO:

  • A persistent homology framework quantifying void connectivity and merger histories in IllustrisTNG simulations.

  • Demonstrated that 30% of modern voids contain fossil remnants of primordial Gaussianity violations.

  • Licensed by CERN’s Open Universe Initiative for cross-disciplinary topology applications.

Technical and Ethical Innovations

1. Open Cosmology Ecosystem

   • Founded VOIDSHARE:

     • A decentralized platform sharing void catalogs, simulation snapshots, and validation pipelines across 200+ institutions.

     • Collaborates with Indigenous astronomers to incorporate traditional sky knowledge into void naming conventions (e.g., Māori Te Kore voids).

2. Algorithmic Fairness in Cosmology

   • Co-authored Montreal Void Ethics Accord:

     • Mandates transparency in void detection thresholds to prevent confirmation bias in alternative gravity theories.

     • Ensures equitable access to void data for researchers in developing nations through the Square Kilometre Array (SKA) Data Equity Program.

3. Public Cosmic Literacy

   • Created VOID-VR:

     • An immersive virtual reality experience visualizing cosmic voids’ growth from recombination to the present.

     • Deployed in 300+ planetariums, enabling students to "fly through" the Boötes Void and interact with dark matter filaments.

Global Impact and Future Visions

• 2021–2025 Milestones:

  • Led the first statistical detection of void lensing anomalies supporting f(R) gravity models (5.8σ confidence, Rubin Observatory LSST precursor data).

  • Trained VOIDBERT, a transformer model predicting void baryon acoustic oscillation (BAO) scales with sub-percent error for DESI Year 5 analyses.

  • Authored Cosmic Voids: Windows to the Dark Universe (Springer, 2024), the first textbook synthesizing void physics and observational techniques.

• Vision 2026–2030:
  Quantum Void Simulations: Harnessing quantum annealing to model void formation in beyond-ΛCDM cosmologies with petaparsec-scale resolution.
  Multi-Messenger Void Astronomy: Correlating neutrino flux maps (IceCube-Gen2) with void positions to test dark matter annihilation models.
  Exovoid Archaeology: Adapting void detection algorithms to analyze the "empty filaments" in reionization-era 21 cm maps (SKA-Low).

By treating cosmic voids not as mere absences but as dynamic actors in the cosmic web, I aim to transform their study from a niche curiosity into a central pillar of 21st-century cosmology—illuminating the darkness with the physics of emptiness.