Institute for Nuclear and Particle Astrophysics (INPA) at LBNL
The INPA Seminar weekly talks are on Fridays, starting at 12:00 pm, unless informed otherwise. The seminar talk starts with a brief presentation of the weekly scientific news. Typically, the talks conclude by 1:00 pm. The seminars are held in the Sessler Conference Room, located in Bldg. 50A- 5132.
The committee members are:
The seminar schedule for the Institute for Nuclear and Particle Astrophysics (INPA) is tentative and becomes final a few days before the Friday talk.
Please send all suggestions for future INPA talks and speakers to the INPA Committee.
To be added to the INPA News Mailing List, please contact Erica Hall.
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Speaker: Eric Gawiser (Rutgers) Title: Improving Photometric Redshifts for 3x2pt Cosmology: Training Sample Augmentation, Optimal Binning, and Neural Network Classifiers
April 5 @ 12:00 pm - 1:00 pm
INPA SEMINAR TALK
Date: Friday, April 5, 2024
Time: 12:00 PM – 1:00 PM
Location: Sessler Conference Room–50A-5132 [Hybrid and In-Person]
Speaker: Eric Gawiser (Rutgers)
Title: Improving Photometric Redshifts for 3x2pt Cosmology: Training Sample Augmentation, Optimal Binning, and Neural Network Classifiers
Abstract: Large imaging surveys of galaxies rely on photometric redshifts (photo-z’s) and tomographic binning for 3 × 2 pt analyses that combine galaxy clustering and weak lensing. We divide simulated galaxy catalogs into training and application sets, where the spectroscopic training set is non-representative in a realistic way, and then estimate photometric redshifts for the application set. Spectroscopic training samples for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will be biased towards redder, brighter, lower-redshift galaxies, leading to photo-z estimates with outlier fractions nearly 4 times larger than for a representative training sample. Training sample augmentation allows us to add simulated galaxies possessing otherwise unrepresented features to our mock spectroscopic training sample, reducing the outlier fraction of the photo-z estimates by 50% and the scatter by 56%. We sort the galaxies into redshift bins chosen to maximize the 3x2pt signal using a novel generalized binning parameterization introduced by Moskowitz et al. (2023, ApJ 950, 49). Applying a neural network classifier trained to identify galaxies that are highly likely to be sorted into the correct redshift bin improves the figure of merit by ∼13%, equivalent to a 28% increase in data volume.
Join Zoom Meeting
https://lbnl.zoom.us/j/95016696011?pwd=Tk1XOW1Xd3RYRnlsc2tEYmRWZlVVZz09
Meeting ID: 950 1669 6011
Passcode: 247722
INPA guests from campus can now come to the lab early on Fridays. The INPA Common Room (50-5026) is reserved for our guests from 10:00 a.m. to 12:00 noon and from 1 p.m. to 5 p.m. Note that the seminars are now held in 50A-5132 to accommodate a more significant number of attendees.
CPTea Series (also known as INPA Tea Series)
The Physics Division CPTea Series invites you to an In-Person Tea Series 1st Friday of every month at 3:30 pm INPA Conference Room 50-5026.
Everyone is welcome to attend the open forum. Tea and light refreshments will be served.
INPA Common Room (50-5026)
Fridays
3:30 pm
Access to the Lab
For a shuttle pass, please email Erica Hall. The pass is only valid for the day of the seminar.