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Disentangling f(R) Curvature from Magnetic Anisotropy in Super-Chandrasekhar White Dwarfs

Author: Harsha Adhikary · Indian Institute of Science, Bangalore · harshaa@iisc.ac.in


The Problem

The Chandrasekhar limit (~1.44 M☉) sets the classical maximum mass for a white dwarf. Yet a growing population of over-luminous Type Ia supernovae — SN 2006gz, SN 2007if, SN 2009dc — require progenitor masses of 2.0–2.8 M☉, firmly above this limit. Two theoretical mechanisms have been proposed to explain this:

  1. Bowers–Liang magnetic anisotropy (κ) — strong internal magnetic fields generate a tangential pressure excess that supplements degeneracy pressure, directly stiffening the equation of state.
  2. Starobinsky f(R) = R + αR² modified gravity (α) — geometric corrections to the TOV equations from higher-order curvature provide an effective extra pressure support.

Each mechanism has been studied in isolation (Das & Mukhopadhyay 2015; Deb, Mukhopadhyay & Weber 2022). But a critical set of questions was left unanswered:

Are κ and α genuinely distinct physical mechanisms, or are they just two parametrizations of the same effect? If they are distinct locally, can a single mass measurement tell them apart? And if not — what observable can?


The Gap in the Literature

Prior work established the following:

  • f(R) gravity alone can push M_max to 1.77–2.70 M☉ for large |α| (Das & Mukhopadhyay 2015)
  • Magnetic anisotropy alone can push M_max to ~2.51 M☉ (Deb et al. 2022)
  • Both were studied with a continuous Chandrasekhar EOS, never checking whether the discrete Landau-quantized microphysics changes the answer

What was missing:

  1. No analytic proof that f(R) curvature and Bowers–Liang anisotropy are structurally distinct (vs. being redundant parametrizations)
  2. No quantification of whether a mass measurement alone can disentangle the two — the degeneracy contour in (α, κ) space had not been mapped
  3. No degeneracy-breaking observable identified — the field knew the problem was degenerate but had no proposed discriminator
  4. No micro/macro consistency check — nobody had directly compared the continuous Chandrasekhar EOS against the discrete Landau EOS within the same unified solver

What This Paper Does

Result 1 — Local Distinguishability (analytic + numerical)

Using the Minimal Geometric Deformation (MGD) framework (Ovalle 2017), we prove analytically that the two force corrections scale differently near the stellar centre:

F_geom  ∝  r     (f(R) curvature force)
F_κ     ∝  r²    (Bowers–Liang anisotropic force)

We then verify numerically along the full solved radial profile of the fiducial star that this r vs r² scaling holds to within ~6% across the entire star — not merely in the r→0 limit used to derive it. This proves that including both κ and α is not double-counting: they are structurally distinct mechanisms.

Result 2 — Macroscopic Degeneracy (the bad news)

We ran a 12×12 grid of full stellar structure integrations over (α, κ) ∈ [-10¹³, -10¹²] cm² × [0, 0.4]. The resulting iso-mass contours are diagonal: a measurement of M_max alone cannot separately constrain α and κ. The posterior in (α, κ) space forms a ridge, not a point. This is a fundamental observational limitation — a new mechanism does not automatically give a new observable.

Result 3 — Degeneracy Breaking (the good news)

We computed the stellar radius R and dimensionless tidal deformability Λ for six configurations along the iso-M_max ≈ 2.55 M☉ contour. Despite masses fixed to within ΔM/M = 2.4%, the secondary observables vary dramatically:

Observable Min Max Variation
Radius R 1192 km 1429 km ΔR/R = 18%
Tidal Λ 1.08×10¹¹ 3.18×10¹¹ ΔΛ/Λ ≈ 100%

The dominant driver is the C⁻⁵ scaling of Λ: large-|α| configurations are more compact, large-κ configurations are more extended. A LISA measurement of Λ to within ~30% would be sufficient to select between the f(R)-dominated and anisotropy-dominated scenarios at this mass scale — even when the mass is only known to ±0.05 M☉.

Result 4 — Micro/Macro Consistency Check

We computed the discrete Landau-quantized EOS from first principles and fed it directly into the unified TOV solver alongside the continuous Chandrasekhar EOS. The two M_max values agree to 0.2% — confirming that the continuous approximation used throughout the macroscopic literature is valid even at B ~ 8.6 B_c where only ~18–20 Landau levels are populated. This check had not been performed in any prior work.


Headline Numbers

Pure f(R) alone  (α = -3×10¹² cm², conservative):    M_max ≈ 1.44 M☉
Pure magnetic    (B₀ = 3.79×10¹⁴ G):                 M_max ≈ 2.51 M☉
Unified combined (fiducial α, κ = 0.15):              M_max ≈ 2.60 M☉
Conservative B₀  (B₀ = 10¹³ G, stability window):    M     ≈ 1.56 M☉
Degeneracy break: ΔR/R = 18%,  ΔΛ/Λ ≈ 100%  at fixed M ≈ 2.55 M☉
Micro/macro gap:  0.2%  (Landau vs. Chandrasekhar EOS)

Repository Structure

ROOT/
├── constants.py                  # CGS physical constants
├── eos.py                        # Chandrasekhar + Landau + hybrid EOS
├── tov_solver.py                 # Unified TOV + f(R) + Riccati tidal solver
│
├── phase0_quick.py               # 12×12 grid scan → figure_phase0_quick.png
├── phase3_lambda.py              # Tidal Λ along iso-Mmax → Table 2, Figure 8
├── phase4_convergence_v2.py      # Convergence of ΔΛ/Λ signal → Figure 9
│
├── plot_fig1_mass_radius.py      # Figure 1: M–R relations
├── plot_fig2_contour.py          # Figure 2: (α, κ) degeneracy contour map
├── plot_fig3_landau_mr.py        # Figure 3: Landau M–R curve (quantum kinks)
├── plot_fig4_synthesis.py        # Figure 4: Full micro+macro synthesis
├── plot_fig5_neutronization.py   # Figure 5: ρ_c vs M (electron-capture cutoff)
├── plot_fig6_force_scaling.py    # Figure 6: F_geom vs F_κ radial profile
├── plot_fig7_conservative_b0.py  # Figure 7: Conservative B₀ companion case
│
├── table_phase3_lambda.txt       # Raw data for Table 2
├── table_phase4_convergence.txt  # Raw convergence data
└── README.md                     # This file

Running the Code

pip install numpy scipy matplotlib

# Reproduce Table 2 + Figure 8 (degeneracy breaking)
python phase3_lambda.py

# Reproduce convergence analysis + Figure 9
python phase4_convergence_v2.py

# Reproduce all paper figures
python plot_fig1_mass_radius.py
python plot_fig2_contour.py
python plot_fig3_landau_mr.py
python plot_fig4_synthesis.py
python plot_fig5_neutronization.py
python plot_fig6_force_scaling.py
python plot_fig7_conservative_b0.py

Expected runtimes: phase0 ~2 min · phase3 ~30 s · phase4 ~3 min · figure scripts ~10 s each


Key Design Decision: Decoupled Tidal Solver

The standard approach couples the tidal perturbation y(r) as a 5th ODE variable alongside the stiff TOV system. This causes repeated LSODA convergence failures in the f(R) + anisotropy regime due to the stiffness mismatch between the background fluid equations and the tidal perturbation.

This code uses a two-pass decoupled approach:

  1. Solve the 4-variable TOV background (compute_tidal=False) to get P(r), M(r)
  2. Fit cubic splines to the background profile
  3. Solve the Riccati ODE for y(r) as an independent post-processing step using DOP853

This is numerically stable, physically equivalent, and convergence-verified across four decades of ODE tolerance.


References

Reference Role in this work
Das & Mukhopadhyay (2015), JCAP 05, 045 f(R) TOV equations (perturbative strategy)
Deb, Mukhopadhyay & Weber (2022), ApJ 926, 66 Magnetic anisotropy + TO orientation
Hinderer (2008), ApJ 677, 1216 Tidal Love number ODE
Biswas & Bose (2019), PRD 99, 104002 Anisotropic Love number correction
Ovalle (2017), PRD 95, 104019 Minimal Geometric Deformation framework
Bowers & Liang (1974), ApJ 188, 657 Anisotropic pressure parametrization

License

MIT License — free to use and adapt with attribution.

Citation

If you use this code, please cite the associated paper. ArXiv preprint forthcoming.

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Python numerical solvers for macroscopic anisotropic and microscopic Landau-quantized Super-Chandrasekhar white dwarfs.

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