Pith. sign in

REVIEW 2 major objections 5 minor 1 cited by

Pulse Profiles of Accreting Neutron Stars from GRMHD Simulations

T0 review · 2 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

Pith's one-line read Accreting millisecond pulsar hotspots are crescent- and band-shaped, not circular, and their simulated pulse profiles match observed amplitudes of 1-12% rms.

desk verdict Solid GRMHD-era pulse profile paper: the non-circular hotspot results will hold, but the quantitative amplitude claims rest on an emission model the authors themselves flag as approximate. read the letter →

arxiv 2411.16528 v2 pith:QNZPVNYY submitted 2024-11-25 astro-ph.HE

classification astro-ph.HE
keywords accretingmillisecondpulsarsneutronstarhotspotsGRMHDsimulationspulseprofilesraytracingelectronscatteringmagneticinclinationX-rayvariability
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper uses global three-dimensional general-relativistic magnetohydrodynamic simulations of a magnetized neutron star accreting from a disk to ask what shape the X-ray-emitting hotspots on the stellar surface really take, and what pulses those hotspots produce. It finds that the hotspots are not circular: at low magnetic inclination they are crescents around the magnetic axis, and at higher inclination they become elongated bands, with the morphology set entirely by the accretion columns. Ray-traced pulse profiles from these spots have fractional rms amplitudes of the fundamental and first harmonic mostly between 1 and 12 percent, matching the range seen in accreting millisecond pulsars. The paper argues this is strong evidence that pulse-profile modeling of accretion-powered pulsars must abandon the circular-spot assumption. It also shows that the turbulent accretion flow adds broadband variability and that electron-scattering absorption in the accretion column adds higher harmonics and additional variability.

What carries the argument

The machinery is a chain from simulation to synthetic observation: global three-dimensional general-relativistic magnetohydrodynamic simulations of a dipolar magnetosphere accreting from a turbulent disk produce surface matter-energy flux maps; the flux is converted to an effective blackbody temperature via $T_{\rm eff} = (F_m/\sigma_{\rm SB})^{1/4}$; and two independent general-relativistic ray-tracing codes, one forward in time and one backward, turn the surface temperature maps into bolometric pulse profiles, including stellar oblateness, Doppler boosting, light bending, and, in one code, radiative transfer of Thomson absorption through the accretion column. The spot shapes themselves come from the accretion columns: the star-disk magnetic interaction makes the columns, and thus the spots, non-axisymmetric crescents at low inclination and bands at high inclination. The pulse analysis fits $f(\phi) = A + B\sin(\phi+\phi_1) + C\sin(2\phi+\phi_2)$ and reports the fractional rms of the fundamental and first harmonic.

What would settle it

Compare a sample of accreting millisecond pulsars with independently known magnetic and observer inclinations against the simulated crescent and band hotspot family: if observed fractional rms amplitudes consistently fall outside the 1-12% range, or the observed harmonic ratios contradict the simulated trend with magnetic inclination, the central claim would be falsified.

Watch

Extended reading notes

Core claim

The central claim is that the accretion hotspots of accreting millisecond pulsars, as produced self-consistently by global GRMHD simulations of the star-disk system, form a family of crescent and elongated band shapes that depend on the stellar magnetic inclination, and that these non-circular geometries imprint characteristic pulse profiles. For magnetic inclinations of 30, 60, and 90 degrees, the time-averaged spots range from crescents near the magnetic axis to an equatorial belt, and the fractional rms amplitudes of the fundamental and first harmonic of the resulting pulses usually lie between 1 and 12 percent, consistent with observed accreting millisecond pulsars. The paper further claims that the turbulent accretion flow produces pulse-to-pulse variability on timescales comparable to the rotation period, and that electron scattering in the accretion column and disk obscures the antipodal hotspot, strengthens the fundamental, introduces higher harmonics, and increases overall variability. The conclusion drawn is that pulse-profile modeling for accretion-powered pulsars needs to move beyond circular spot shapes.

Load-bearing premise

The simulations assume that the hotspot radiates as an isotropic blackbody with temperature set by the matter-energy flux, ignoring the radiation-dominated shock, Comptonization, and anisotropic beaming that real accreting millisecond pulsars show, so the quantitative pulse amplitudes and shapes could shift if a more complete emission model were used.

Editorial extensions

If this is right

  • Pulse-profile models for accretion-powered pulsars should use non-circular hotspot shapes, because fitting circular spots may bias inferred mass, radius, and geometry.
  • Simulated fractional rms amplitudes of 1-12% for the fundamental and first harmonic match observed accreting millisecond pulsars, supporting accretion-column-determined hotspots as the origin of their pulsations.
  • The turbulent accretion flow produces significant broadband variability that exceeds the pulsed variability by a factor of 1.3-3.3, so observed light-curve variability should be treated as partly accretion noise.
  • Electron scattering in the accretion column and disk obscures the antipodal hotspot at higher accretion rates, increasing the fundamental amplitude and generating higher harmonics, so pulse shape should evolve with mass accretion rate.
  • Time-variable spot shapes on rotation-period timescales cause pulse-to-pulse variability with larger scatter in the fundamental amplitude and phase than in the first harmonic.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the simulated spot family is representative, current circular-spot pulse-profile fits to accreting millisecond pulsars may be underestimating geometric systematics in inferred neutron-star masses and radii; a natural next step is to fit the crescent and band family to archival data.
  • The predicted trend that the first harmonic strengthens and the fundamental weakens as magnetic inclination increases toward 90 degrees gives a population-level test: sources with independently inferred high magnetic obliquity should show stronger harmonic content.
  • The absorption-driven growth of the fundamental with rising mass accretion rate implies that an individual pulsar should show systematic pulse-shape evolution across an outburst, with higher harmonics appearing at the bright end; this could be checked with existing long monitoring campaigns.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. This paper uses global 3D GRMHD simulations (BHAC) of an accreting neutron star with a dipolar magnetic field for three magnetic inclinations (30, 60, and 90 degrees) to extract surface hotspot morphologies, convert the matter-energy flux to an effective temperature via Eq. (12), and compute X-ray pulse profiles with two independent general-relativistic ray-tracing codes (RAPTOR and X-PSI). The main claims are that the hotspots are crescent-shaped at low inclination and elongated bands/bars at higher inclination; that the simulated fractional rms amplitudes of the fundamental and first harmonic usually lie in the 1–12% range, consistent with observed accreting millisecond pulsars; that turbulent accretion flow adds broadband variability on timescales comparable to the spin period; and that electron scattering absorption in the accretion column and disk modifies pulse shapes and introduces additional variability and higher harmonics.

Significance. If the results hold, the paper provides a strong, physically motivated argument that pulse-profile modeling of accretion-powered pulsars should move beyond circular hotspot geometries, a step that is currently missing from standard AMXP pulse-profile analyses. The study is technically careful in several respects: the two ray-tracing codes agree to within about 1%, the camera convergence is checked at the 0.25% level, the harmonic-fit residuals are within 1.2%, and time-dependent ray tracing of individual GRMHD snapshots is used to quantify variability. The authors are also transparent about the main simplifications. However, the quantitative pulse-amplitude predictions, which are the basis for the claimed consistency with observations, rest on an isotropic blackbody emission model with no shock or Comptonization, and the electron-scattering treatment is absorption-only. These are load-bearing assumptions for the numerical values, so the strength of the quantitative conclusions is conditional on them.

major comments (2)
  1. [Section 2.2.1 and Eq. (12); discussed in Section 4] The quantitative pulse-amplitude range (1–12% rms) is computed by assuming that the accretion energy is radiated locally as an isotropic blackbody with Teff = (Fm/σSB)^(1/4), with no radiation-dominated shock and no Comptonization. The authors state in Section 4 that the amplitudes may be slightly overestimated because of this assumption. This is load-bearing: pulse rms amplitudes and the fundamental-to-first-harmonic ratio depend sensitively on the angular pattern of surface emission and on the temperature structure of the emitting region. A Comptonized beaming pattern applied to the same non-circular hotspot footprints could shift the predicted amplitudes and harmonic hierarchy relative to the observed AMXP values. I request either a robustness test using a simple anisotropic beaming prescription (for example, a limb-darkening or Comptonized-beaming factor) or a visible softening of the abstract/conclusion statements so that the conditional nature of the amplitude comparison is explicit.
  2. [Section 3.3 and Eq. (8)] The electron-scattering calculation includes only Thomson absorption opacity (alpha_nu = 0.4 cm^2/g) and ignores line-of-sight scattering and energy exchange. The conclusions that the accretion column and disk introduce significant additional variability and higher harmonics are based on this absorption-only model. Pure absorption removes photons and can overproduce harmonic structure and variability compared with a scattering treatment that redistributes photons in angle and energy. Although the limitation is acknowledged in Section 4, the quantitative values quoted in Section 3.3 (for example, variability increasing from 0.18 to 0.213 at i_obs = 50 degrees and from 0.182 to 0.391 at i_obs = 70 degrees) should be presented more cautiously, for instance as upper limits or as estimates pending a scattering calculation, because they are used to support the harmonic and variability conclusions.
minor comments (5)
  1. [Section 3.3 and Eq. (14)] Equation (14) fits only the fundamental and first harmonic, but Section 3.3 quotes amplitudes for the second, third, and fourth harmonics. Please specify the extended fit function (and the number of harmonics) used for those cases, since the reported fundamental and first-harmonic amplitudes in the absorption runs could otherwise be biased by unmodeled higher harmonics.
  2. [Section 3.2.2 and Figure 7] The rms values quoted for the fundamental and first harmonic (rms_nu0 and rms_nu1) are obtained from Lorentzian fits to the PSDs, but the fitting procedure is not described in enough detail. Please state the Lorentzian width, the integration range, and how the broadband noise floor is estimated, because the quoted numbers depend on these choices.
  3. [Section 3.2.2] The coefficients of variation for phi2 are reported as negative values (c_phi2 = -0.279 and -0.344). Since c_x is defined as sigma_x/<x>, a negative value is possible when the mean phase is negative, but the sign is not physically informative. Consider reporting the absolute value or a circular dispersion measure instead.
  4. [Figure 2 caption] The labels 'Middle' and 'Top' in the caption are somewhat unclear; please clarify explicitly that the top and middle rows correspond to the upper and lower magnetic hemispheres, respectively.
  5. [Section 2.1] The plasma beta is defined as beta_t = 2p/b^2, but the text later refers simply to 'beta' transitioning smoothly outside the light cylinder. Please use a consistent definition of beta throughout, or clarify that the same definition is implied.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the pulse amplitudes and hotspot morphologies are simulation outputs compared with observations post hoc, not fitted inputs.

full rationale

The derivation chain is self-contained: hotspot shapes and temperatures are produced by GRMHD simulations (with setup cited to Das & Porth 2024 and unit scaling to Das et al. 2022), converted to surface emission via Eq. (12), and ray-traced with RAPTOR and X-PSI. The fractional rms amplitudes in the abstract and Section 4 are read off from the simulated pulse profiles (Figures 5 and 7) and then compared with observed AMXP ranges; the observed values are not used to tune any parameter. Likewise, the electron-scattering absorption results are generated by solving the radiative transfer equation along the simulated geodesics, not by matching observed harmonic content. The self-citations provide simulation infrastructure and physical scaling, but neither is adjusted to reproduce the 1-12% rms range or the harmonic hierarchy, so they are inputs rather than circular supports. The paper's own stated limitations, e.g., isotropic blackbody emission and neglect of the shock/Comptonization component, are accuracy caveats rather than circularity: they change the quantitative predictions but do not make any equation reduce to its own output. No fitted parameter is renamed as a prediction, and no uniqueness claim or ansatz is imported solely from the authors' prior work. The central qualitative conclusion, that global GRMHD simulations produce non-circular crescent and elongated-band hotspots and that such geometries affect pulse profiles, follows from the simulation data and ray tracing rather than from the observed pulse properties. Therefore no circular step is identifiable.

Assumptions & free parameters 5 free parameters · 6 assumptions · 0 invented entities

The paper does not introduce new physics entities; it combines existing GRMHD simulations, ray-tracing codes, and scaling relations. The central claims rest on: (i) the simulation setup inherited from Das & Porth 2024, including ideal MHD and the chosen stellar parameters; (ii) the conversion of simulated flux into blackbody surface emission; (iii) the physical scaling of Mdot and magnetic field; and (iv) the radiative transfer treatment of electron scattering as monochromatic absorption. These are modeling choices, not fitted parameters tuned to reproduce observed pulse profiles.

free parameters (5)
  • Stellar magnetic dipole moment mu = 20 mu_cgs (code units); physical B ~ 3.78e7 to 3.78e8 G via Mdot scaling
    Chosen to place the magnetospheric radius in the AMXP range; no independent fit to pulse data. Section 2.1.
  • Stellar rotation frequency Omega_star = 0.03 c/rg -> 572.56 Hz
    Fixed for all runs; corresponds to a fast AMXP. Section 2.1.
  • Physical mass and radius scaling = R* = 10 km, M = 1.69 Msun, Req = 10.75 km
    Derived from R* = 4 rg and the choice of a 10 km radius; compactness is a modeling input, not a fit to pulse profiles. Section 2.1.
  • Eddington-scaled mass accretion rate = 1% Mdot_Edd for main runs; 0.01-1% for absorption study
    Sets the physical density normalization (rho = 1.27e-5 g cm^-3) and hence hotspot temperatures and pulse amplitudes. A free normalization of the model. Sections 2.1 and 3.3.
  • Temperature contour threshold for spot morphology = 2.5e7 K (2.15 keV)
    Chosen arbitrarily to guide the eye in Figure 3, as stated in footnote 4; not load-bearing for the main claims.
assumptions (6)
  • domain assumption Ideal GRMHD equations with no explicit resistivity or viscosity; MRI drives angular momentum transport
    The simulations solve Eqs. (1)-(3) with an ideal magneto-fluid; turbulent angular momentum transport relies on MRI resolved by the grid. This is standard for this class of simulations.
  • domain assumption Neutron star is modeled as a rigidly rotating excised sphere with a dipole magnetic field; stellar interior is not evolved
    Section 2.1: the star is a boundary with Rstar = 4 rg and a dipole field according to Wasserman & Shapiro (1983); the code excises the interior. Real stellar structure and field evolution are ignored.
  • ad hoc to paper The matter-energy flux at the extraction radius is radiated locally as a blackbody (Eq. 12), with no accretion shock or Comptonization
    Equation (12) sets Teff = (Fm/sigma_SB)^(1/4); Section 2.2.1 states the shock and Comptonization are not modeled. This is a simplifying assumption specific to this paper that directly shapes the predicted pulses.
  • standard math Photons follow Schwarzschild geodesics and the fast-light approximation is used in RAPTOR
    Ray tracing uses Eqs. (4)-(9) in Schwarzschild spacetime; time delays are ignored in RAPTOR, with differences below 5% in test cases (Figure 1).
  • ad hoc to paper Electron scattering is represented by Thomson absorption opacity only, with no line-of-sight scattering or energy exchange
    Section 2.2.1 sets the absorption coefficient to Thomson opacity for pure hydrogen; the authors explicitly note in Section 4 that scattering into the line of sight is not included and will affect the dips of the first harmonic.
  • domain assumption The Das et al. (2022) scaling relations keep the magnetospheric radius fixed when Mdot and magnetic field are rescaled
    Section 3.3 varies Mdot from 0.01% to 1% Eddington and adjusts B accordingly so the magnetospheric radius is constant; this assumes the scale-free GRMHD solution maps to physical units along a one-parameter family.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Pulse Profiles of Accreting Neutron Stars from GRMHD Simulations." pith.science (2026). https://pith.science/paper/QNZPVNYY

@misc{pith2026241116528,
  author       = {Pith},
  title        = {Pith review of: Pulse Profiles of Accreting Neutron Stars from GRMHD Simulations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/QNZPVNYY}},
  note         = {Machine review of arXiv:2411.16528}
}
abstract

The pulsed X-ray emission from the neutron star surface acts as a window to study the state of matter in the neutron star interior. For accreting millisecond pulsars, the surface X-ray emission is generated from the `hotspots' formed due to the magnetically channeled accretion flow hitting the stellar surface. The emission from these hotspots is modulated by stellar rotation giving rise to pulsations. Using global three-dimensional general relativistic magnetohydrodynamic (GRMHD) simulations of the star-disk system, we investigate the accretion hotspots and the corresponding X-ray pulse properties of accreting millisecond pulsars with dipolar magnetic fields. The accretion spot morphologies in our simulations are entirely determined by the accretion columns and vary as a function of the stellar magnetic inclination. For lower magnetic inclinations, the hotspots are shaped like crescents around the magnetic axis and are transformed into elongated bars for higher inclinations. We model the X-ray pulses resulting from the simulated hotspots using general-relativistic ray tracing calculations and quantify the variability of the pulsed signal. The pulse amplitudes in our simulations usually range between $1 - 12 \%$ rms and are consistent with the observed values. We find that the turbulent accretion flow in the GRMHD simulations introduces significant broadband variability on a timescale similar to the stellar rotational period. We also explore the impact of electron scattering absorption and show that along with being a key factor in determining the pulse characteristics, this also introduces significant additional variability and higher harmonics in the bolometric light curve of the accreting sources.

Figures

Figures reproduced from arXiv: 2411.16528 by the authors.

Figure 1
Figure 1. Bolometric flux for RAPTOR and X-PSI with a uniform temperature spot (kTeff = 0.35 keV). The center of the hotspot for all the tests is at θc = 50◦ . The two columns show the bolometric pulse profiles for two different spot sizes (∆θ), 50◦ and 5◦ respectively. The first row (a, b) shows the tests for a spherical star rotating at 1 Hz and 400 Hz. The second row (c,d) shows the bolometric profiles for an oblate star r… view at source ↗
Figure 2
Figure 2. Averaged hotspot shapes at the stellar surface (r = 4.3 rg) for (a) χstar = 30◦ , (b) χstar = 60◦ and (c) χstar = 90◦ with the magnetic axis in the z − x plane. The top and the middle panels show the spot structures in the upper and lower magnetic hemispheres respectively. All the shells are averaged over t ∈ [15000, 25000] rg/c ≈ 48 stellar periods. The color bar shows temperature in Kelvin (converted to physical u… view at source ↗
Figure 3
Figure 3. Variability of temperature profiles and spot shapes for χstar = 60◦ around 1200rg/c (≈ 10 ms) apart. The variation in the high-temperature regions (Teff > 2.5 × 107 K) is outlined with the green contours. An animated version of the figure, illustrating the temperature evolution over 83 ms with a cadence of 0.17 ms, is available at: https://youtu.be/7QD3z1SKESE. 0.75 0.80 0.85 0.90 0.95 1.00 (a) 0.70 0.75 0.80 0.85 0… view at source ↗
Figures from the paper (9 more)
Figure 5
Figure 5. Figure 5: Fractional rms amplitude of the fundamental and the first harmonic of the averaged pulse profiles ( [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 4
Figure 4. Figure 4: Normalized bolometric pulse profiles of averaged hotspot shapes ( [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 6
Figure 6. Figure 6: Time evolution of (a) bolometric luminosity (L), (b) mass accretion rate (M˙ ), and (c) M˙ normalized bolometric luminosity for different stellar magnetic inclinations. The observer inclination is set to 70◦ . The stellar periods are highlighted by the grey dashed line…
Figure 7
Figure 7. Figure 7: shows the rms-normalized power spectrum densities (PSDs) of the observed bolometric luminosity and M˙ time series shown in [PITH_FULL_IMAGE:figures/full_fig_p009_7.png]
Figure 8
Figure 8. Figure 8: Pulse variability for χstar = 60◦ with iobs = 70◦ . Panel (a) shows the variation between the pulse obtained from the averaged spots using X-PSI and the phase-folded light curve from ( [PITH_FULL_IMAGE:figures/full_fig_p010_8.png]
Figure 9
Figure 9. Figure 9: Variation in the pulses as a function of M˙ for χstar = 60◦ at iobs= 50◦ using RAPTOR. Here, different col￾ors represent the normalized bolometric flux for different mass accretion rates, and the black dashed line represents the pulse shape from the stellar black body …
Figure 10
Figure 10. Figure 10: shows the variation in the pulses as a func￾tion of observer inclination angle in the presence of ac￾cretion column and the disk at 1%M˙ Edd. Similar to the pulses shown in [PITH_FULL_IMAGE:figures/full_fig_p011_10.png]
Figure 11
Figure 11. Figure 11: Volume rendering of density for χstar = 60◦ (left panel) and χstar = 90◦ (right panel). The solid lines show the corresponding stellar magnetic fieldlines for each case [PITH_FULL_IMAGE:figures/full_fig_p017_11.png]
Figure 12
Figure 12. Figure 12: RMS-normalized PSDs of the bolometric luminosity with electron scattering absorption for different observer inclinations, iobs = 50◦ (left) and iobs = 70◦ (right) for χstar = 60◦ at 1%M˙ Edd. The blue and orange curves represent the PSDs resulting from the surface hot…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Modelling polarized X-ray pulses from accreting millisecond pulsars with X-PSI, using different hot spot locations and shapes

    astro-ph.HE 2025-01 accept novelty 5.0 of 10

    Polarized X-ray pulse simulations show IXPE can constrain pulsar inclination and spot colatitude to a few degrees only for bright, small hot spots, and cannot distinguish circular from ring-like spot shapes.

Reference graph

Works this paper leans on

83 extracted references · 12 canonical work pages · cited by 1 Pith paper

  1. [1]

    2024, A&A, 682, A60, doi: 10.1051/0004-6361/202348153

    Ahlberg, V., Poutanen, J., & Salmi, T. 2024, A&A, 682, A60, doi: 10.1051/0004-6361/202348153

  2. [2]

    AlGendy, M., & Morsink, S. M. 2014, ApJ, 791, 78, doi: 10.1088/0004-637X/791/2/78

  3. [3]

    2008, ApJL, 674, L45, doi: 10.1086/528983

    Altamirano, D., Casella, P., Patruno, A., Wijnands, R., & van der Klis, M. 2008, ApJL, 674, L45, doi: 10.1086/528983

  4. [4]

    O., et al

    Altamirano, D., Patruno, A., Heinke, C. O., et al. 2010, ApJL, 712, L58, doi: 10.1088/2041-8205/712/1/L58

  5. [5]

    2011, ApJL, 727, L18, doi: 10.1088/2041-8205/727/1/L18

    Altamirano, D., Cavecchi, Y., Patruno, A., et al. 2011, ApJL, 727, L18, doi: 10.1088/2041-8205/727/1/L18

  6. [6]

    M., Kulkarni, A., Burderi, L., & di Salvo, T

    Bachetti, M., Romanova, M. M., Kulkarni, A., Burderi, L., & di Salvo, T. 2010, MNRAS, 403, 1193, doi: 10.1111/j.1365-2966.2010.16203.x

  7. [7]

    A., & Hawley, J

    Balbus, S. A., & Hawley, J. F. 1991, ApJ, 376, 214, doi: 10.1086/170270

  8. [8]

    M., & Sunyaev, R

    Basko, M. M., & Sunyaev, R. A. 1976, MNRAS, 175, 395, doi: 10.1093/mnras/175.2.395

Show all 83 references
  1. [9]

    V., Watts, A

    Bilous, A. V., Watts, A. L., Harding, A. K., et al. 2019, ApJL, 887, L23, doi: 10.3847/2041-8213/ab53e7

  2. [10]

    2023, A&A, 678, A99, doi: 10.1051/0004-6361/202346833

    Bobrikova, A., Loktev, V., Salmi, T., & Poutanen, J. 2023, A&A, 678, A99, doi: 10.1051/0004-6361/202346833

  3. [11]

    K., Mahmoodifar, S., et al

    Bogdanov, S., Lamb, F. K., Mahmoodifar, S., et al. 2019, ApJL, 887, L26, doi: 10.3847/2041-8213/ab5968

  4. [12]

    2018, A&A, 613, A2, doi: 10.1051/0004-6361/201732149

    Bronzwaer, T., Davelaar, J., Younsi, Z., et al. 2018, A&A, 613, A2, doi: 10.1051/0004-6361/201732149

  5. [13]

    2020, A&A, 641, A126, doi: 10.1051/0004-6361/202038573

    Bronzwaer, T., Younsi, Z., Davelaar, J., & Falcke, H. 2020, A&A, 641, A126, doi: 10.1051/0004-6361/202038573

  6. [14]

    2018, ApJ, 864, 14, doi: 10.3847/1538-4357/aad5e5

    Bult, P., Altamirano, D., Arzoumanian, Z., et al. 2018, ApJ, 864, 14, doi: 10.3847/1538-4357/aad5e5

  7. [15]

    B., Altamirano, D., et al

    Bult, P., Markwardt, C. B., Altamirano, D., et al. 2019, ApJ, 877, 70, doi: 10.3847/1538-4357/ab1b26

  8. [16]

    2022, ApJL, 935, L32, doi: 10.3847/2041-8213/ac87f9

    Bult, P., Altamirano, D., Arzoumanian, Z., et al. 2022, ApJL, 935, L32, doi: 10.3847/2041-8213/ac87f9

  9. [17]

    2003, ApJL, 594, L39, doi: 10.1086/378258

    Belloni, T. 2003, ApJL, 594, L39, doi: 10.1086/378258

  10. [18]

    2008, ApJL, 674, L41, doi: 10.1086/528982 15

    Casella, P., Altamirano, D., Patruno, A., Wijnands, R., & van der Klis, M. 2008, ApJL, 674, L41, doi: 10.1086/528982 15

  11. [19]

    2024, ApJL, 971, L20, doi: 10.3847/2041-8213/ad5a6f

    Choudhury, D., Salmi, T., Vinciguerra, S., et al. 2024, ApJL, 971, L20, doi: 10.3847/2041-8213/ad5a6f

  12. [20]

    T., & Bardeen, J

    Cunningham, C. T., & Bardeen, J. M. 1972, ApJL, 173, L137, doi: 10.1086/180933 Dalc ´ ın, L., Paz, R., Storti, M., & D’El ´ ıa, J. 2008, Journal of Parallel and Distributed Computing, 68, 655, doi: 10.1016/j.jpdc.2007.09.005

  13. [21]

    2024, ApJL, 960, L12, doi: 10.3847/2041-8213/ad151f

    Das, P., & Porth, O. 2024, ApJL, 960, L12, doi: 10.3847/2041-8213/ad151f

  14. [22]

    Das, P., Porth, O., & Watts, A. L. 2022, MNRAS, 515, 3144, doi: 10.1093/mnras/stac1817

  15. [23]

    2022, PhRvD, 105, 103010, doi: 10.1103/PhysRevD.105.103010

    Davelaar, J., & Haiman, Z. 2022, PhRvD, 105, 103010, doi: 10.1103/PhysRevD.105.103010

  16. [24]

    J., Miller, M

    Dittmann, A. J., Miller, M. C., Lamb, F. K., et al. 2024, ApJ, 974, 295, doi: 10.3847/1538-4357/ad5f1e

  17. [25]

    L., et al

    Dorsman, B., Salmi, T., Watts, A. L., et al. 2025, MNRAS, 538, 2853, doi: 10.1093/mnras/staf438

  18. [26]

    A., Hunter, J., et al

    Droettboom, M., Caswell, T. A., Hunter, J., et al. 2018, matplotlib/matplotlib v2.2.2, Zenodo, doi: 10.5281/zenodo.1202077

  19. [27]

    2014, A&A, 567, A77, doi: 10.1051/0004-6361/201322904

    Ferrigno, C., Bozzo, E., Papitto, A., et al. 2014, A&A, 567, A77, doi: 10.1051/0004-6361/201322904

  20. [28]

    G., & Moncrief, V

    Fishbone, L. G., & Moncrief, V. 1976, ApJ, 207, 962, doi: 10.1086/154565

  21. [29]

    Remillard, R. A. 2002, ApJL, 576, L137, doi: 10.1086/343841

  22. [30]

    Chakrabarty, D., & Strohmayer, T. E. 2005, ApJL, 622, L45, doi: 10.1086/429563

  23. [31]

    C., Arzoumanian, Z., Adkins, P

    Gendreau, K. C., Arzoumanian, Z., Adkins, P. W., et al. 2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9905, Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray, ed. J.-W. A. den Herder, T. Takahashi, & M. Bautz, 9905...

  24. [32]

    M., Patruno, A., Chakrabarty, D., et al

    Hartman, J. M., Patruno, A., Chakrabarty, D., et al. 2008, ApJ, 675, 1468, doi: 10.1086/527461

  25. [33]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

  26. [34]

    2009, MNRAS, 400, 492, doi: 10.1111/j.1365-2966.2009.15477.x

    Ibragimov, A., & Poutanen, J. 2009, MNRAS, 400, 492, doi: 10.1111/j.1365-2966.2009.15477.x

  27. [35]

    Jones, E., Oliphant, T., & Peterson, P. 2001

  28. [36]

    H., Vanderspek, R., & Tomsick, J

    Kaaret, P., Morgan, E. H., Vanderspek, R., & Tomsick, J. A. 2006, ApJ, 638, 963, doi: 10.1086/498886

  29. [38]

    2021, ApJ, 907, 63, doi: 10.3847/1538-4357/abcec0

    Kazanas, D. 2021, ApJ, 907, 63, doi: 10.3847/1538-4357/abcec0

  30. [39]

    L., et al

    Kini, Y., Salmi, T., Watts, A. L., et al. 2023, MNRAS, 522, 3389, doi: 10.1093/mnras/stad1030

  31. [40]

    2024a, MNRAS, 527, 8118, doi: 10.1093/mnras/stad3595 —

    Kini, Y., Salmi, T., Vinciguerra, S., et al. 2024a, MNRAS, 527, 8118, doi: 10.1093/mnras/stad3595 —. 2024b, MNRAS, doi: 10.1093/mnras/stae2398

  32. [41]

    K., & Romanova, M

    Kulkarni, A. K., & Romanova, M. M. 2005, ApJ, 633, 349, doi: 10.1086/444489 —. 2008, MNRAS, 386, 673, doi: 10.1111/j.1365-2966.2008.13094.x —. 2013, MNRAS, 433, 3048, doi: 10.1093/mnras/stt945

  33. [42]

    K., Boutloukos, S., Van Wassenhove, S., et al

    Lamb, F. K., Boutloukos, S., Van Wassenhove, S., et al. 2009, ApJ, 706, 417, doi: 10.1088/0004-637X/706/1/417

  34. [43]

    Lattimer, J. M. 2021, Annual Review of Nuclear and Particle Science, 71, 433, doi: 10.1146/annurev-nucl-102419-124827

  35. [44]

    Lindquist, R. W. 1966, Annals of Physics, 37, 487, doi: 10.1016/0003-4916(66)90207-7

  36. [45]

    Zand, J. J. M., & Marshall, F. E. 2002, ApJL, 575, L21, doi: 10.1086/342612

  37. [46]

    C., Tchekhovskoy, A., & Blandford, R

    McKinney, J. C., Tchekhovskoy, A., & Blandford, R. D. 2012, MNRAS, 423, 3083, doi: 10.1111/j.1365-2966.2012.21074.x

  38. [47]

    W., Thorne, K

    Misner, C. W., Thorne, K. S., & Wheeler, J. A. 1973, Gravitation (San Francisco: W.H. Freeman and Co.)

  39. [48]

    M., Leahy, D

    Morsink, S. M., Leahy, D. A., Cadeau, C., & Braga, J. 2007, ApJ, 663, 1244, doi: 10.1086/518648

  40. [49]

    2024, ApJL, 961, L20, doi: 10.3847/2041-8213/ad16eb

    Jacquemin-Ide, J. 2024, ApJL, 961, L20, doi: 10.3847/2041-8213/ad16eb

  41. [50]

    S., Bult, P., et al

    Ng, M., Ray, P. S., Bult, P., et al. 2021, ApJL, 908, L15, doi: 10.3847/2041-8213/abe1b4

  42. [51]

    Oliphant, T. E. 2007, Computing in Science Engineering, 9, 10, doi: 10.1109/MCSE.2007.58

  43. [52]

    2019, A&A, 629, A61, doi: 10.1051/0004-6361/201935559

    Olivares, H., Porth, O., Davelaar, J., et al. 2019, A&A, 629, A61, doi: 10.1051/0004-6361/201935559

  44. [53]

    M., et al

    Papitto, A., de Martino, D., Belloni, T. M., et al. 2015, MNRAS, 449, L26, doi: 10.1093/mnrasl/slv013

  45. [54]

    2011, A&A, 535, L4, doi: 10.1051/0004-6361/201117995

    Papitto, A., Bozzo, E., Ferrigno, C., et al. 2011, A&A, 535, L4, doi: 10.1051/0004-6361/201117995

  46. [55]

    2019, ApJ, 882, 104, doi: 10.3847/1538-4357/ab2fdf

    Papitto, A., Ambrosino, F., Stella, L., et al. 2019, ApJ, 882, 104, doi: 10.3847/1538-4357/ab2fdf

  47. [56]

    M., Wijnands, R., Chakrabarty, D., & van der Klis, M

    Patruno, A., Hartman, J. M., Wijnands, R., Chakrabarty, D., & van der Klis, M. 2010, ApJ, 717, 1253, doi: 10.1088/0004-637X/717/2/1253

  48. [57]

    2009a, MNRAS, 396, L51, doi: 10.1111/j.1745-3933.2009.00660.x 16

    Patruno, A., Rea, N., Altamirano, D., et al. 2009a, MNRAS, 396, L51, doi: 10.1111/j.1745-3933.2009.00660.x 16

  49. [58]

    Patruno, A., & Watts, A. L. 2021, Astrophysics and Space Science Library, 461, 143, doi: 10.1007/978-3-662-62110-3 4

  50. [59]

    2009b, ApJL, 698, L60, doi: 10.1088/0004-637X/698/1/L60

    Patruno, A., Wijnands, R., & van der Klis, M. 2009b, ApJL, 698, L60, doi: 10.1088/0004-637X/698/1/L60

  51. [60]

    R., Ftaclas, C., & Cohen, J

    Pechenick, K. R., Ftaclas, C., & Cohen, J. M. 1983, ApJ, 274, 846, doi: 10.1086/161498

  52. [61]

    Perez, F., & Granger, B. E. 2007, Computing in Science Engineering, 9, 21, doi: 10.1109/MCSE.2007.53

  53. [62]

    2017, Computational Astrophysics and Cosmology, 4, 1, doi: 10.1186/s40668-017-0020-2

    Porth, O., Olivares, H., Mizuno, Y., et al. 2017, Computational Astrophysics and Cosmology, 4, 1, doi: 10.1186/s40668-017-0020-2

  54. [63]

    Poutanen, J., & Beloborodov, A. M. 2006, MNRAS, 373, 836, doi: 10.1111/j.1365-2966.2006.11088.x

  55. [64]

    2003, MNRAS, 343, 1301, doi: 10.1046/j.1365-8711.2003.06773.x

    Poutanen, J., & Gierli´ nski, M. 2003, MNRAS, 343, 1301, doi: 10.1046/j.1365-8711.2003.06773.x

  56. [65]

    2011, Computing in Science & Engineering, 13, 40

    Ramachandran, P., & Varoquaux, G. 2011, Computing in Science & Engineering, 13, 40

  57. [66]

    2011, A&A, 526, A95, doi: 10.1051/0004-6361/201014322

    Riggio, A., Papitto, A., Burderi, L., et al. 2011, A&A, 526, A95, doi: 10.1051/0004-6361/201014322

  58. [67]

    E., Watts, A

    Riley, T. E., Watts, A. L., Bogdanov, S., et al. 2019, ApJL, 887, L21, doi: 10.3847/2041-8213/ab481c

  59. [68]

    E., Choudhury, D., Salmi, T., et al

    Riley, T. E., Choudhury, D., Salmi, T., et al. 2023, Journal of Open Source Software, 8, 4977, doi: 10.21105/joss.04977

  60. [69]

    Koldoba, A. V. 2011, in Advances in Plasma Astrophysics, ed. A. Bonanno, E. de Gouveia Dal Pino, & A. G. Kosovichev, Vol. 274, 416–421, doi: 10.1017/S1743921311007393

  61. [70]

    Lovelace, R. V. E. 2004, ApJ, 610, 920, doi: 10.1086/421867 —. 2012, MNRAS, 421, 63, doi: 10.1111/j.1365-2966.2011.20055.x

  62. [71]

    B., & Lightman, A

    Rybicki, G. B., & Lightman, A. P. 1979, Radiative processes in astrophysics

  63. [72]

    2021, A&A, 646, A23, doi: 10.1051/0004-6361/202039470

    Salmi, T., Loktev, V., Korsman, K., et al. 2021, A&A, 646, A23, doi: 10.1051/0004-6361/202039470

  64. [73]

    2018, A&A, 618, A161, doi: 10.1051/0004-6361/201833348

    Salmi, T., N¨ attil¨ a, J., & Poutanen, J. 2018, A&A, 618, A161, doi: 10.1051/0004-6361/201833348

  65. [74]

    2024, ApJ, 974, 294, doi: 10.3847/1538-4357/ad5f1f

    Salmi, T., Choudhury, D., Kini, Y., et al. 2024, ApJ, 974, 294, doi: 10.3847/1538-4357/ad5f1f

  66. [75]

    S., et al

    Sanna, A., Ferrigno, C., Ray, P. S., et al. 2018a, A&A, 617, L8, doi: 10.1051/0004-6361/201834160

  67. [76]

    2018b, A&A, 610, L2, doi: 10.1051/0004-6361/201732262

    Sanna, A., Bahramian, A., Bozzo, E., et al. 2018b, A&A, 610, L2, doi: 10.1051/0004-6361/201732262

  68. [77]

    2022, MNRAS, 516, L76, doi: 10.1093/mnrasl/slac093

    Sanna, A., Bult, P., Ng, M., et al. 2022, MNRAS, 516, L76, doi: 10.1093/mnrasl/slac093

  69. [78]

    2017, ApJL, 836, L23, doi: 10.3847/2041-8213/aa5e51

    Strohmayer, T., & Keek, L. 2017, ApJL, 836, L23, doi: 10.3847/2041-8213/aa5e51

  70. [79]

    2003, ApJL, 596, L67, doi: 10.1086/379158 van der Walt, S., Colbert, S

    Zand, J. 2003, ApJL, 596, L67, doi: 10.1086/379158 van der Walt, S., Colbert, S. C., & Varoquaux, G. 2011, Computing in Science Engineering, 13, 22, doi: 10.1109/MCSE.2011.37

  71. [80]

    L., et al

    Vinciguerra, S., Salmi, T., Watts, A. L., et al. 2024, ApJ, 961, 62, doi: 10.3847/1538-4357/acfb83

  72. [81]

    Wasserman, I., & Shapiro, S. L. 1983, ApJ, 265, 1036, doi: 10.1086/160745

  73. [82]

    Watts, A. L. 2019, in American Institute of Physics Conference Series, Vol. 2127, Xiamen-CUSTIPEN Workshop on the Equation of State of Dense Neutron-Rich Matter in the Era of Gravitational Wave Astronomy, 020008, doi: 10.1063/1.5117798

  74. [83]

    L., Andersson, N., Chakrabarty, D., et al

    Watts, A. L., Andersson, N., Chakrabarty, D., et al. 2016, Rev. Mod. Phys., 88, 021001, doi: 10.1103/RevModPhys.88.021001

  75. [84]

    1998, Nature, 394, 344, doi: 10.1038/28557 17 χstar = 60◦ χstar = 90◦ Figure 11

    Wijnands, R., & van der Klis, M. 1998, Nature, 394, 344, doi: 10.1038/28557 17 χstar = 60◦ χstar = 90◦ Figure 11. Volume rendering of density for χstar = 60 ◦ (left panel) and χstar = 90 ◦ (right panel). The solid lines show the corresponding stellar magnetic fieldlines for ea...

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.