---
title: 'X-CIGALE: Modular SED Fitting'
url: https://www.emergentmind.com/topics/x-cigale
type: topic
---

# X-CIGALE: Modular SED Fitting

X-CIGALE is an advanced spectral energy distribution (SED) fitting framework extending the CIGALE platform to self-consistently model the emission of galaxies and active galactic nuclei (AGNs) from X-ray to radio wavelengths. By integrating physically-motivated modules for AGN accretion, torus geometry, polar dust, and host-galaxy components—alongside the statistical machinery of Bayesian parameter estimation—X-CIGALE enables robust inference of physical parameters such as star formation rates (SFR), stellar mass, AGN luminosity, accretion rate, Eddington ratio, and dust properties for diverse extragalactic populations [2001.08263][2011.09220][2201.03718][2404.16938].

## 1. Architectural Principles and Core Framework

X-CIGALE adopts the modular and energy-balance based philosophy of CIGALE, incorporating distinct physical processes into separate modules, each parameterized through grids sampled in the likelihood calculation. The principal modules comprise:

- **Star formation history (SFH):** e.g. delayed SFR(t)∝t exp(−t/τ), with optional recent bursts.
- **Stellar populations:** Bruzual & Charlot (2003) or similar, Chabrier or Salpeter IMF, solar metallicity.
- **Dust attenuation:** Empirical (Calzetti), two-component (Charlot & Fall), or SMC-like laws.
- **Dust emission:** Dale et al. (2014) templates for reprocessing of UV/optical into IR.
- **AGN emission:** Modern torus models (SKIRTOR; with density ρ∝r⁻ᵖ e^(−q|cosθ|)), viewing-angle parameterization, and a power-law/empirical disk spectrum.
- **Polar dust:** SMC-type extinction and greybody re-emission at characteristic T∼100 K, β∼1.6.
- **X-ray emission:** Power-law AGN corona (Γ configurable) and (optionally) host X-ray binaries.
- **Radio:** Addition of AGN radio jets/loudness; star-formation radio emission.

Modules interact through global energy balance, with the UV/optical extinction matched to IR emission. For AGN, X-ray, disk, and torus emission are treated consistently, with key physical relations (notably the αₒₓ relation, L_X–L_2500Å or L_X–L_12μm) constraining the normalization across bands [2001.08263][2201.03718][2404.16938].

## 2. X-ray and AGN Modules: Physical Methods and Innovations

Early X-CIGALE incarnations imposed the ultraviolet–X-ray correlation via the empirical $\alpha_{ox} = -0.3838\log[L_\nu(2\,\mathrm{keV})/L_\nu(2500\mathrm{\AA})]$ and the Just et al. (2007) relation, discarding SED models whose AGN disk and X-ray fluxes violated $\Delta\alpha_{ox}$ bounds of typically ±0.2 [2001.08263][2011.09220]. This enables consistent anchoring of the AGN corona and UV disk emission, breaking degeneracies between AGN and host-star contributions.

Subsequent developments extended the module capabilities:

- **AGN X-ray anisotropy:** X-CIGALE now allows $L_X(\theta)/L_X(0^\circ) = a_1\cos\theta + a_2\cos^2\theta + (1-a_1-a_2)$, capturing different geometries (isotropic, thin-disk, or custom), where θ is the viewing angle [2201.03718].
- **X-ray binaries and host-galaxy emission:** Models for high-mass XRBs (HMXB), low-mass XRBs (LMXB), and hot gas, with scaling following Fragos et al. (2013b) and Mezcua et al. (2018), enable decomposition of galaxy X-ray emission [2201.03718][2001.08263].
- **Bolometric corrections and LLAGN regime:** Low-luminosity AGN require an alternate prior, using the empirical L_X–L_12μm relation (Asmus et al. 2015) via $\alpha_{IRX}$ and explicit ADAF+disk engine mixing (δ_AGN): 
  $$
  \lambda L_\lambda^\text{total} \propto \delta_{AGN}\,\lambda L_\lambda^{ADAF} + (1-\delta_{AGN})\lambda L_\lambda^{Disk}
  $$
  yielding self-consistent bolometric corrections across $L_{Bol} \sim10^{39}$–$10^{46}$ erg s⁻¹ [2404.16938].

## 3. SED Fitting Workflow and Statistical Framework

Parameter inference in X-CIGALE proceeds via grid sampling. For each parameter set and observation:

- Model SEDs are synthesized, convolved with the filter set (including X-ray and IR boxcar bands).
- $\chi^2=\sum_i[(F_{obs,i} - F_{model,i})/\sigma_i]^2$ is computed, incorporating upper limits via likelihood integration for censored data [2001.08263].
- Bayesian-posteriors are constructed: $P(\theta) \propto \sum_{models} \exp(-\chi^2/2)\, \delta(\theta-\theta_{model})$.
- Physical parameters are reported as the marginal mean/1σ of the posterior, alongside best-fit single-model values.
- Model selection or complexity control leverages the Bayesian Information Criterion (BIC) or Akaike (AIC, ΔAIC).

This architecture delivers robust host-galaxy and AGN decompositions. Systematic uncertainties and degeneracies are evaluated through mock-catalog recovery tests, exploring the impact of parameter grid density and photometric coverage [2201.03718][2011.09220].

## 4. Key Physical Parameters and Diagnostic Indices

X-CIGALE infers a suite of host and AGN properties. Principal parameters include:

- **AGN fraction ($\mathrm{frac_{AGN}}$):** The fraction of total 5–1000μm IR luminosity from the AGN torus [2011.09220].
- **$\alpha_{ox}$ index:** Measures X-ray/UV slope; crucial for constraining the energy budget in luminous AGN, but requiring modification (to $\alpha_{IRX}$) in the LLAGN regime [2404.16938].
- **Bolometric corrections ($k_X$):** Empirically calibrated for LLAGN as $k_X \sim 9$–11, lower than quasars, reflecting the different SED contributions.
- **SFR, $M_*$:** Derived from joint fitting of SFH, SSP, dust modules; parameter reliability spans typical σ≈0.1–0.3 dex [2108.10899][2111.02539].
- **AGN luminosity ($L_{AGN}$), BHAR, $\lambda_{Edd}$:** From AGN disk/torus normalization and X-ray constraints, with Eddington ratios recoverable and cross-checkable against proxies (e.g., $L_X/M_*$) [2302.01358].

For AGN type classification, X-CIGALE uses combinations of torus viewing angle (e.g., $i_{best}=30^\circ$ for type 1, $70^\circ$ for type 2), polar dust extinction, and $\mathrm{frac_{AGN}}$ thresholds, outperforming simple single-parameter cuts in completeness and reliability [2106.11579][2108.10899].

## 5. Impact on Observational Studies and Practical Methodology

X-CIGALE underpins multiwavelength SED analyses across large extragalactic surveys:

- **AGN/host decomposition:** Robustly separates AGN from star-formation even in the presence of degeneracy between young dust-enshrouded SF and red AGN tori [2011.09220][2106.11579].
- **Improved AGN detection:** X-ray and polar-dust modules increase detection efficiency for Compton-thin and heavily obscured AGN, revealing populations missed by classical mid-IR color criteria [2011.09220][2106.11579].
- **Type-1/type-2 classification:** The inclusion of inclination and polar dust recovers $\sim85$% of spectroscopic type-1 and $>95$% of type-2 AGN, provided adequate multiwavelength coverage [2106.11579][2108.10899].
- **Cosmic evolution and co-evolution:** Instantaneous SFR and BHAR derived from X-CIGALE enable forward modeling of $M_{BH}$–$M_*$ relations, supporting self-regulated AGN feedback scenarios [2302.01358].
- **LLAGN census:** Empirical L_X–L_12μm-based modules deliver meaningful AGN power estimates in LINERs, Seyferts, and other weakly accreting sources, extending SED modeling below $L_X <10^{42}$ erg s⁻¹ [2404.16938].

X-CIGALE efficiency depends critically on SED coverage (UV to FIR/radio), photometric calibration, and precise intrinsic X-ray fluxes (absorption-corrected via N_H or hardness ratios). For statistical robustness, quality cuts (e.g., $\chi^2_{red}<5$) and parameter consistency checks are recommended [2111.02539].

## 6. Software Distribution, Evolution, and Usage

All X-CIGALE functionality has been merged into the mainstream CIGALE codebase (v2022.0+), with continued enhancements for AGN anisotropy, radio, and LLAGN-specific modeling [2201.03718][2404.16938]. The package provides:

- Python-based modular design: Users specify a configuration file enumerating modules and parameter grids.
- Integrated statistical outputs: Full posteriors, best-fit SEDs, component fluxes, and diagnostics.
- Public codebase and documentation: Downloadable via pip or GitLab; full documentation and parameter file templates online.
- Example parameter file segments:
  ```
  [parameters]
  sfhdelayed     # SFH module
  population     # SSP
  dustatt_calzetti # Dust attenuation
  dustem_dale2014 # Dust emission
  skirtor2016    # AGN clumpy torus
  polar_dust     # Polar dust
  xray           # X-ray AGN/host
  radio          # AGN jet/radio module
  ```

## 7. Limitations, Systematics, and Future Prospects

Current limitations reflect boundaries in physical modeling and data quality:

- For heavily Compton-thick AGN, the SED modeling is limited by the accuracy of absorption corrections and photometric constraints [2302.01358][2011.09220].
- The classical $\alpha_{ox}$ prior is not universally applicable; ADAF+disk or $\alpha_{IRX}$ models are required in the low-luminosity regime [2404.16938].
- Degeneracies persist between torus inclination and polar dust for moderate $E(B-V)$, only partially mitigated by mock-catalog recovery techniques [2001.08263].
- Optimal performance requires full UV–radio photometric coverage plus robust X-ray measurements, which can be a limiting factor in highly obscured systems at $z>1.5$ [2108.10899].

Ongoing code development focuses on enhancing LLAGN sensitivity, refining AGN/star formation decomposition with machine-learning classification of outputs, and integrating direct adaptivity to instrument-specific data footprints [2201.03718][2404.16938].

X-CIGALE has become a community standard for disentangling AGN and host properties in cosmic evolution studies, AGN/galaxy feedback scenarios, and the optimization of legacy and future X-ray/IR/radio surveys (e.g., eROSITA, ATHENA) [2011.09220][2201.03718][2302.01358][2404.16938].

Source: https://www.emergentmind.com/topics/x-cigale