.. _supernova_models: Supernova Models ================ POSYDON supports different supernova models for the formation of compact objects. The supernova model can be set in the configuration file of the population synthesis model. Overview -------- The supernova treatment in POSYDON is determined by two key aspects: 1. **Core-collapse mechanism**: The physical prescription for computing remnant properties 2. **Computational approach**: How and when the collapse outcome is calculated Core-Collapse Mechanisms ------------------------ POSYDON supports the following core-collapse mechanisms: .. list-table:: Core-collapse mechanisms :header-rows: 1 :widths: 20 10 70 * - Mechanism - Engine - Description * - **Fryer+12-delayed** - ``None`` - Classical rapid and delayed supernova engines from Fryer et al. (2012) * - **Fryer+12-rapid** - ``None`` - Classical rapid and delayed supernova engines from Fryer et al. (2012) * - **Sukhbold+16-engine** - ``N20``, ``W20``, ``S19.8``, ``W15``, ``W18`` - Uses pre-computed results from Sukhbold et al. (2016) based on neutrino-powered explosions * - **Patton&Sukhbold20-engine** - ``N20``, ``W20``, ``S19.8``, ``W15``, ``W18`` - Advanced engine combining Patton & Sukhbold (2020) results for realistic explosion landscapes * - **Maltsev+25-engine** - ``M16`` - Maltsev et al. (2025) with updated explodability criteria and neutrino-driven physics. **Only valid M_CO < 10 Msun!** * - **Couch+20-engine** - ``"1.0", "1.2", "1.23", "1.25", "1.27", "1.3", "1.4"`` - Simulations of turbulence-aided neutrino-driven core-collapse supernovae from Couch et al. (2020) * - **direct** - ``None`` - Simplified prescriptions that directly collapse the pre-supernova to the baryonic mass * - **direct_he_core** - ``None`` - Simplified prescriptions that directly collapse the pre-supernova to the baryonic mass of the helium core Pulsational pair-instability supernova prescriptions ---------------------------------------------------- POSYDON also supports pulsational pair-instability supernova (PPISN) prescriptions, which can be set in the configuration file: .. list-table:: (P)PISN prescriptions :header-rows: 1 :widths: 20 10 70 * - Prescription - Parameters - Description * - **Marchant+19** - ``None`` - Marchant et al. (2019) prescription for PPISN and PISN mass loss from | Breivik et al. (2020). * - **Hendriks+23** - ``PISN_CO_shift`` and ``PPI_extra_mass_loss`` - Hendriks et al. (2023) prescription for PPISN and PISN mass loss. | ``PISN_CO_shift`` shifts the CO core mass threshold for PPI onset | and ``PPI_extra_mass_loss`` adds extra mass loss during PPISN events. | PISN occurs if the remnant mass after PPI mass loss is less than 10 Msun. Computational Approaches ------------------------ The outcome of core collapse can be computed using three different approaches, controlled by configuration flags: Pre-Trained Interpolators ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. code-block:: use_interp_values = True use_profiles = True use_core_masses = True This is the **default and recommended approach** for population synthesis. The pre-trained interpolators use outcomes that were computed offline from the detailed MESA stellar profiles. Because the on-the-fly calculations use the down-sampled profiles, the interpolators are generally more accurate and faster. On-the-Fly Calculations with Downsampled Profiles ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. code-block:: use_interp_values = False use_profiles = True use_core_masses = False This approach recalculates the core-collapse outcome during the simulation using stellar profiles. However, unlike the detailed profiles used to train the interpolators, these profiles are **downsampled** (reduced resolution) for computational efficiency. **Advantages**: More flexible, can handle evolutionary scenarios not covered by pre-computed grids, allows for model exploration **Disadvantages**: Slower than interpolators, potential accuracy loss due to profile downsampling **When to use**: For detailed model comparisons, sensitivity studies, or cases requiring custom physics Core-Masses Approach (Classical Population Synthesis) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. code-block:: use_interp_values = False use_profiles = False use_core_masses = True This classical approach uses only the core masses at carbon depletion, without requiring detailed stellar profiles. Pre-Defined Supernova Models ---------------------------- POSYDON provides a set of pre-defined supernova models (``SN_MODEL_v2_XX``) for which the initial-final interpolator has been trained. This requires the user to correctly set the supernova mechanism and engine in the configuration file of the population synthesis model. Model Overview ^^^^^^^^^^^^^^ The following table lists all pre-defined supernova models and their key characteristics: .. list-table:: Pre-defined SN Models :header-rows: 1 :widths: 12 25 8 18 18 * - Model - Mechanism - Engine - Conserve H-env - PPI Mass Loss * - SN_MODEL_v2_01 - Fryer+12-delayed - \- - No - -20.0 * - SN_MODEL_v2_02 - Fryer+12-delayed - \- - Yes - -20.0 * - SN_MODEL_v2_03 - Fryer+12-delayed - \- - No - 0.0 * - SN_MODEL_v2_04 - Fryer+12-delayed - \- - Yes - 0.0 * - SN_MODEL_v2_05 - Fryer+12-rapid - \- - No - -20.0 * - SN_MODEL_v2_06 - Fryer+12-rapid - \- - Yes - -20.0 * - SN_MODEL_v2_07 - Fryer+12-rapid - \- - No - 0.0 * - SN_MODEL_v2_08 - Fryer+12-rapid - \- - Yes - 0.0 * - SN_MODEL_v2_09 - Sukhbold+16-engine - N20 - No - -20.0 * - SN_MODEL_v2_10 - Sukhbold+16-engine - N20 - Yes - -20.0 * - SN_MODEL_v2_11 - Sukhbold+16-engine - N20 - No - 0.0 * - SN_MODEL_v2_12 - Sukhbold+16-engine - N20 - Yes - 0.0 * - SN_MODEL_v2_13 - Patton&Sukhbold20-engine - N20 - No - -20.0 * - SN_MODEL_v2_14 - Patton&Sukhbold20-engine - N20 - Yes - -20.0 * - SN_MODEL_v2_15 - Patton&Sukhbold20-engine - N20 - No - 0.0 * - SN_MODEL_v2_16 - Patton&Sukhbold20-engine - N20 - Yes - 0.0 * - SN_MODEL_v2_17 - Sukhbold+16-engine - W20 - No - -20.0 * - SN_MODEL_v2_18 - Sukhbold+16-engine - W20 - Yes - -20.0 * - SN_MODEL_v2_19 - Sukhbold+16-engine - W20 - No - 0.0 * - SN_MODEL_v2_20 - Sukhbold+16-engine - W20 - Yes - 0.0 * - SN_MODEL_v2_21 - Patton&Sukhbold20-engine - W20 - No - -20.0 * - SN_MODEL_v2_22 - Patton&Sukhbold20-engine - W20 - Yes - -20.0 * - SN_MODEL_v2_23 - Patton&Sukhbold20-engine - W20 - No - 0.0 * - SN_MODEL_v2_24 - Patton&Sukhbold20-engine - W20 - Yes - 0.0 * - SN_MODEL_v2_25 - Maltsev+25-engine - M16 - No - -20.0 * - SN_MODEL_v2_26 - Maltsev+25-engine - M16 - Yes - -20.0 * - SN_MODEL_v2_27 - Maltsev+25-engine - M16 - No - 0.0 * - SN_MODEL_v2_28 - Maltsev+25-engine - M16 - Yes - 0.0 All pre-defined models use: - ``use_interp_values = False`` (on-the-fly calculations, not pre-trained interpolators) - ``use_profiles = True`` (detailed MESA profiles, downsampled during calculation) - ``use_core_masses = False`` Configuration ^^^^^^^^^^^^^ To use a pre-defined model, specify it in your population synthesis configuration file: .. code-block:: ini [supernova] model = SN_MODEL_v2_13 This will automatically load all parameters for that model. Alternatively, you can customize individual parameters: .. code-block:: ini [supernova] mechanism = Patton&Sukhbold20-engine engine = N20 ECSN = Tauris+15 conserve_hydrogen_envelope = False PPI_extra_mass_loss = -20.0 use_interp_values = True use_profiles = False use_core_masses = False