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jense_2023_cmb_camb_mnu_neff.yaml
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jense_2023_cmb_camb_mnu_neff.yaml
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network_name: jense_2023_camb_mnu_neff
path: jense_2023_camb_mnu_neff
emulated_code:
name: camb
version: "1.5.2"
inputs: [ ombh2, omch2, As, ns, H0, tau, mnu, nnu ]
extra_args:
lens_potential_accuracy: 8
kmax: 10.0
k_per_logint: 130
lens_margin: 2050
AccuracyBoost: 1.0
lAccuracyBoost: 1.2
lSampleBoost: 1.0
DoLateRadTruncation: false
min_l_logl_sampling: 6000
recombination_model: CosmoRec
samples:
Ntraining: 120000
parameters:
ombh2: [0.015,0.030]
omch2: [0.09,0.15]
logA: [2.5,3.5]
tau: [0.02, 0.20]
ns: [0.85, 1.05]
h: [0.4,1.0]
H0: "lambda h: h * 100.0"
As: "lambda logA: 1.e-10 * np.exp(logA)"
# derived parameters
thetastar:
sigma8:
YHe:
zrei:
taurend:
zstar:
rstar:
zdrag:
rdrag:
N_eff:
nnu: [1.0,5.0]
networks:
- quantity: "derived"
type: NN
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
patience_values: 100
max_epochs: 1000
- quantity: "Cl/tt"
type: NN
log: True
modes:
label: l
range: [2,10000]
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
gradient_accumulation_steps: [ 1, 1, 1, 1, 1, 1 ]
patience_values: [ 100, 100, 100, 100, 100, 100 ]
max_epochs: [ 1000, 1000, 1000, 1000, 1000, 1000 ]
- quantity: "Cl/te"
type: PCAplusNN
modes:
label: l
range: [2,10000]
p_traits:
n_pcas: 512
n_batches: 10
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
patience_values: 100
max_epochs: 1000
- quantity: "Cl/ee"
type: NN
log: True
modes:
label: l
range: [2,10000]
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
patience_values: 100
max_epochs: 1000
- quantity: "Cl/bb"
type: NN
log: True
modes:
label: l
range: [2,10000]
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
patience_values: 100
max_epochs: 1000
- quantity: "Cl/pp"
inputs: [ ombh2, omch2, logA, ns, h, nnu ]
type: PCAplusNN
log: True
modes:
label: l
range: [2,10000]
p_traits:
n_pcas: 64
n_batches: 10
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
patience_values: 100
max_epochs: 1000
- quantity: "Hubble"
type: NN
log: True
modes:
label: z
range: [0,20]
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
patience_values: 100
max_epochs: 1000
- quantity: "angular_diameter_distance"
type: NN
log: True
modes:
label: z
range: [0,20]
n_traits:
n_hidden: [ 512, 512, 512, 512 ]
training:
validation_split: 0.1
learning_rates: [ 1.e-2, 1.e-3, 1.e-4, 1.e-5, 1.e-6, 1.e-7 ]
batch_sizes: [ 1000, 2000, 5000, 10000, 20000, 50000 ]
patience_values: 100
max_epochs: 1000