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META TOPICPARENT |
name="CosmoTelecons" |
ZTF Ia Phone-con: 2021-Mar-17 |
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1. SNe of the week [Joel J] |
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< < | 2. The status of DESI [Suhail D] |
> > | 2. Spectroscopic Classifications [Young-Lo K] |
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< < | 3. Machine Learning with ZTF [Nicolas] |
> > | 3. Machine Learning with ZTF [Nicolas M] |
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< < | 4. Spectroscopic Classifications [Young-Lo K] |
> > | 4. The status of DESI [Suhail D] |
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5. AOB / Close |
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< < | Participants (XX):
- Mickael R, Mat S, Young-Lo K, Martin B (Lyon), Joel J, Ariel G, Suhail D, Mattia B, Ana S-C(Stockholm), Kate M, Jacco T, Luke H, Maxime D, Mark M (Trinity), Melissa A, Philippe R, Manu G (Cleremont), Bastien C, Benjamin R (Marseille), Nicolas R (Paris)
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> > | -
Participants (22):
- Mickael R, Mat S, Young-Lo K, Martin B (Lyon), Joel J, Ariel G, Suhail D, Mattia B, Ana S-C (Stockholm), Maxime D (Trinity), Melissa A, Philippe R, Manu G (Cleremont), Jakob N, Nicolas M, Simeon R, Valery B (Berlin), Nicolas R (Paris), Bastien C, Ben R, Julian B (Marseille), Eleni (!)
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| Notes:
Transients of the Week: |
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< < |
Suhail on DESI:
Nicolas on Machine Learning: |
> > |
- It snowed last week.
- Classifications are now getting routinely reported to TNS
- It's also annoyingly overwriting the redshifts
- ZTF21aantxma is a prime example of this
- Can we get a SEDm spectral series for objects caught early (e.g. ZTF21aaomuka): Joel to talk to Shri and Matthew G
- Can we do something with 2018 SNe that were actually in 2019. Pre-explosion epochs? These are likely poor subtractions
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| Young-Lo on Spectroscopy: |
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< < | |
> > |
- Looking at how well the SEDm pipeline is producing classifications.
- What is the effect of CR rejection and background removal?
- Looking at objects in 2018 and comparing with BCS. Has downloaded all data
- There are some issues with the contour-separation: the WCS solution is off so the wrong area is excluded. Need to fix this.
- Looking at two effects: CR rejection (byecr) and Background subtraction (contsep)
- Needs to quantify fit quality: considering SNID rlap, and fraction of templates.
- Breaking things down in to monthly segments.
- The cosmic ray removal is improving all of the fits (inferred through the mean rlap over all objects).
- The 'failure fraction' (fraction of unclassified spectra) is similar.
- Need to improve the contsep solutions.
- In comparing to BCS: compare all subtypes or just Ia's? Maybe also compare with snIascore?
- Could also add host galaxy information into the fits: combine with Jeremy's code.
- Questions include: how secure is the cosmic ray selection? 5sigma
- Drafting a paper
Nicolas on Machine Learning / Photo-typing:
- Working with Jakob N in Berlin
- Looking at Sequential Deep Learning and Early Detection for Spectroscopy.
- Sequential Deep Learning:
- How can we automatically categorize a transient? This is an ill-posed question: what's the classification metric?
- Looking at classification of bright sources (<18.5) into types; Ia/non-Ia for faint SNe (>19), and subtyping.
- Trained on alert photometry, with RCF 2018 sample + AGNs/CVs as truth.
- No host redshift considered.
- The dataset is heterogeneous.
- Fitting in flux-space with a 60 day light-curve.
- Looking into the RAPID software. Works on sims (Plasticc); not on ZTF data.
- Written a function to input the data formats, etc.
- Also adapting the hyperparameters.
- The training sample is highly unbalanced. Resampling helps.
- Bright transients are better classified. AGN seem to be well classified.
- Looking to classify faint objects. Developed a method to simulate faint SNe from bright ones.
- Can combine classifications to get an ensemble classification: works well, but of course ~40% of objects are then unclassified.
- All available on github!
- Thinking about retraining on full ZTF-I sample.
Suhail on DESI:
- Spoken to Maayanne about a Citizen Science project.
- The plan is to target the hosts of all transients in DESI-SV.
- Jakob: the objects are not in the DESI target list.... A change in policy with MOUs. They might get targeted, but we might not know!
- Need to find some clarity with this!
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| Closing Remarks: |