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DES
Generated by Researchly AI·June 14, 2026·6 sources
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TL;DR
The retrieved papers only partially address the topic of DES (Dark Energy Survey). One paper directly reports DES results, while the others concern photometric…
The retrieved papers only partially address the topic of DES (Dark Energy Survey).122
Diagram
One paper directly reports DES results, while the others concern photometric redshift methods relevant to surveys like DES.
The Dark Energy Survey (DES) final dataset was used to measure the Baryon Acoustic Oscillation (BAO) feature, yielding a 2.1% precision measurement of the angular diameter distance.1This measurement represents the most precise BAO result from purely photometric data, and the most precise from any Stage-III experiment at such high redshift.12
- Baryon Acoustic Oscillation (BAO) — A standard ruler in cosmology used to measure angular diameter distances; DES measured the ratio D_M(z_eff)/r_d = 19.51 ± 0.41 at an effective redshift of z_eff = 0.85.
- Photometric Redshift (photo-z) — Redshift estimates derived from multiband imaging magnitudes/colours, producing probability density functions (PDFs) for each galaxy rather than precise spectroscopic measurements.
- Photo-z PDF — Using the full redshift PDF rather than a single-point estimate reduces measurement bias in angular clustering from ~5% to ~3% when using narrow redshift bins of width z = 0.1.
- Machine-Learning Photo-z — Neural-network-based techniques such as ANNz2 and MLPQNA can provide photo-z quality comparable to or better than Bayesian methods up to z_phot ≲ 0.9 and r ≲ 23.5.
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Diagram
DES Photometric Survey Pipeline ──────────────────────────────────────────────────────── Multi-band Imaging │ ▼ Galaxy Catalogue (magnitudes, colours, sizes) │ ▼ Photo-z Estimation ┌─────────────────────────────────────┐ │ ML methods (ANNz2, MLPQNA) │ │ Template-fitting (BPZ) │ │ Deep Learning (CNN + MDN) │ └─────────────────────────────────────┘ │ ▼ Redshift PDFs per galaxy │ ▼ Galaxy Sample Selection (e.g. 0.6 < z < 1.2 for BAO) │ ▼ BAO Feature Measurement │ ▼ Angular Diameter Distance D_M(z_eff)/r_d │ ▼ Cosmological Constraints
Table
| Property | DES BAO Result |
|---|---|
| Redshift range | 0.6 < z < 1.2 |
| Effective redshift | z_eff = 0.85 |
| Measurement | D_M(z_eff)/r_d = 19.51 ± 0.41 |
| Precision | 2.13% (most precise from photometric data) |
| Tension with Planck | 2.13σ below Planck prediction |
| Analysis | Blinded to BAO position |
The DES galaxy sample used for BAO science was optimized for the redshift range 0.6 < z < 1.2, and the analysis was shown to be robust against analysis choices, data removal, redshift calibrations, and observational systematics.1For photometric surveys generally, twelve photo-z algorithms applied to LSST mock data revealed systematic biases and overall over/under-breadth in photo-z PDFs across many popular codes.23
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- DES achieved the most precise BAO measurement from purely photometric data, constraining D_M(z_eff)/r_d = 19.51 ± 0.41 at z_eff = 0.85.
- The DES result sits 2.13σ below the Planck-predicted BAO scale, representing a notable tension.
- Using full photo-z PDFs rather than single-point estimates reduces angular clustering measurement bias from ~5% to ~3% in narrow redshift bins.
- Machine-learning photo-z methods can match or surpass Bayesian template-fitting codes at r ≲ 23.5 and z_phot ≲ 0.9.
- Systematic biases in photo-z PDFs remain a challenge across many popular codes, even under idealised conditions.
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