Bringing the stars to the people

University of Delaware

Department of Physics and Astronomy

Biden School of Public Policy and Administration

Data Science Institute

Rubin Legacy Survey of Space and Time

Deputy Project Scientist for Construction

LSST Survey Scientist

federica b. bianco

she/her

slides available at

https://slides.com/federicabianco/includivedspedagogy

This is a living land acknowledgement developed in consultation with tribal leadership of Poutaxet, what is now known as the “Delaware Bay,” including: the Lenape Indian Tribe of Delaware, the Nanticoke Indian Tribe, and the Nanticoke Lenni-Lenape Tribal Nation in 2021. We thank these leaders for their generosity.

The University of Delaware occupies lands vital to the web of life for Lenni Lenape and Nanticoke, who share their ancestry, history, and future in this region. UD has financially benefited from this regional occupation as well as from Indigenous territories that were expropriated through the United States land grant system. European colonizers and later the United States forced Nanticoke and Lenni Lenape westward and northward, where they formed nations in present-day Oklahoma, Wisconsin, and Ontario, Canada. Others never left their homelands or returned from exile when they could. We express our appreciation for ongoing Indigenous stewardship of the ecologies and traditions of this region. While the harms to Indigenous people and their homelands are beyond repair, we commit to building right relationships going forward by collaborating with tribal leadership on actionable institutional steps.

The Vera C. Rubin Observatory LSST

A new, transformational observatory is about to start building a legacy for humanity vith a movie of the night sky

just as human-made satellites are changing it forever

A new, transformational observatory is about to start building a legacy for humanity vith a movie of the night sky

what's in a name?

The first ground-based national US observatory named after a woman, Dr. Vera C. Rubin

what's in a name?

what's in a name?

The first ground-based national US observatory named after a woman, Dr. Vera C. Rubin

“The most important feature of any telescope is the imagination with which it is used.”

LSST:

The Vera C. Rubin Observatory Legacy Survey of Space and Time

20Tb of data every night. That is equivalent to

8,000 high definition movies

4,000 hours of tiktok videos

every night for 10 years

A legacy dataset that belongs to all people in the USA giving access to never before seen corners of the Universe to all

LSST:

The Vera C. Rubin Observatory Legacy Survey of Space and Time

20Tb of data every night.

Probing Dark Energy and Dark Matter

image credit ESO-Gaia

Mapping the Milky Way and Local Volume

17Billion stars in the milky way: color, position, motion, and variability

An unprecedented inventory of the Solar System

from threatening asteroids to the distant Oort Cloud

image credit: ESA-Justyn R. Maund

Exploring the Transients and Variable Universe

10M alerts every night shared with the world

60 seconds after observation

The immutable skies

Bartolomeu Velho, 1568 (Bibliothèque Nationale, Paris)

1549 Oronce Fine, France

From Flammarion's Astronomie Populaire (1880): in Scania, Denmark

Henry III, Tivoli, SN 1054, unknown artist, ca.1450

TED talk - Andrew Connely

←Dimmer Brighter →

0.01 0.1 1 10 100

stellar sexplosions

stellar eruptions

stellar variability

←Dimmer Brighter →

0.01 0.1 1 10 100

To accomplish this, we need:

Objective: to provide a science-ready dataset to transform the 4 key science area

To accomplish this, we need:

1) Dark skies - Cerro Pachon Chile

Objective: to provide a science-ready dataset to transform the 4 key science area

To accomplish this, we need:

1) Dark skies - Cerro Pachon Chile

2) a large telescope mirror to be sensitive - 8m (6.7m)

Objective: to provide a science-ready dataset to transform the 4 key science area

May 2022 - Telescope Mount Assembly

3.2 Gigapixels:

We built the largest (declassified) camera ever built

to look farther and wider into the sky than ever before

In 2026 we will begin observing the sky with 1000 images every night for 10 years

1996-1998 Tony Tyson, Roger Angel

How it started

with Zhoran Mandami,

Astronaut Reid Wiseman,

Activist Zabib Musa Loro,

Pope Leo XIV,

Olympic medalist Alysa Liu,

Benicio Del Toro.......

2008

2017

Are We There YET????!!!!

Eye to the sky…on-sky engineering tests have begun at @nsfgov–@energy Rubin Observatory using the world’s largest digital camera!🔭

April 17 2025

Eye to the sky…on-sky engineering tests have begun at

Rubin Observatory using the world’s largest digital camera!

June 23 2025

First Look party here at UD with 213 people signed up!

678 separate images taken in just over seven hours of observing time. Trifid nebula (top right) and the Lagoon nebula, which are several thousand light-years away from Earth. | NSF-DOE Vera C. Rubin Observatory

Ok, but what about teaching physics??

https://rubinobservatory.org/education

RUBIN GOT YOU!!

Ardis Herrold
Senior Education Specialist
Rubin Observatory
Email: ardis.herrold@noirlab.edu

Why do we study stellar explosions?

we are made of stars

The nitrogen in our DNA, the calcium in our teeth, the iron in our blood, the carbon in our apple pies were made in the interiors of collapsing stars.

We are made of starstuff.

― Carl Sagan, Cosmos

Farthest: 10.5 billion years ago

3 billion years after the Big Bang

redshift 4

Why do we study stellar explosions?

they are the best tool to "measure" the Universe

largest explosion on earth 10,000,000 erg

typical supernova....

Why do we study stellar explosions?

a unique opportunity to study extreme energy events

who'sploded?

How do we study stellar explosions?

with this much data we need Artificial Intelligence

To accomplish this, we need:

1) Dark skies - Cerro Pachon

2) a large telescope mirror to be sensitive - 8m (6.7m)

3) a large field-of-view for sky-scanning speed - 10 deg2

4) high spatial resolution, high quality images - 0.2''/pixels

5) process images in realtime to produce 10M nightly alerts and offline to produce and catalogs of all 37B objects

Objective: to provide a science-ready dataset to transform the 4 key science area

10 stars explode in the universe every second

Until the 1900s we would see 1 in a century

Until the 1980s we would see 1 in a decade

Until the 2010s we would see 1 in a month

With the Vera C. Rubin Observatory we will see 1000 every night !

+ ~40 other authors

17B Stars (x10) Ivezic+19

20B Galaxies (x10) Ivezic+19

>1M supernovae (stellar explosions)

~50 kilonovae (today 2) Setzer+19, Andreoni+19

>= 10 Interstellar Objects (today 2....

3 !)

in 60 seconds:

Difference Image Analysis

template

in 60 seconds:

Difference Image Analysis

template

difference image

in 60 seconds:

Difference Image Analysis

template

difference image

Rubin Observatory Data Management Team

federica bianco - fbianco@udel.edu

with this much data we need Artificial Intelligence

Improving the efficiency of transient detections with Neural Networks

search

template

difference

-

=

Saliency maps: what pixels matter?

search

template

difference

95% accurate

Acero-Cuellar et al. DESC submitted

Tatiana Acero-Cuellar

UNIDEL fellow,

LSST Data Science Fellow

Scanning the sky repeatedly in 6 colors

Boone 2017

visualizatoin and concept credit: Alex Razim

Neural processes replaces the imposed kernel with a learned model: an artificial neural network

AI approaches to sparse sampling

Siddharth Chaini

NASA FINESST fellow

k(x_i, x_j) = \frac{1}{\Gamma(\nu)2^{\nu-1}}\left( \frac{\sqrt{2\nu}}{l} d(x_i , x_j ) \right)^\nu K_\nu\left( \frac{\sqrt{2\nu}}{l} d(x_i , x_j )\right)\\ \nu=5/2

Can we study unusual SNe with Rubin data alone?

Data Driven Templates for rare classes of supernovae arising from massive stars: can we tell them apart from sparse LSST data lightcurves?

Creating templates from over 1000 photometry of "Stripped Envelope" Supernovae

Text

Khakpash+ 2024

Dr. Somayeh Khakpash

Catalyst Fellow

Data Science / AI

is a required tool in the modern physicists toolset

Providing career opportunities for our physics students in and outside of physics

Data Science provides an opportunity for inclusion in STEM

Including students from population traditionally withheld from STEM

Including STEM newcomers

Introducing students to research methods

Validating Student's Background, Experience, Domain knowledge, Creativity and Providing Career Paths

Most barriers to AI are due to gate keeping - methods are not that different from traditional analysis

Demystifying AI to grow informed and responsible citizens

Data Science for Physical Scientists

undergrad+grad - Physics and Natural Sciences

DS

PS

Award #2123264: to develop accessible and equitable data science pedagogical programs and build capacity for Data Science education at HBCUs

Machine Learning for Natural Scientists

Grads - Physics and Math students

Machine Learning for Time Series Analysis

grad - Natural Sciences

Foundations of Data Science for Everyone

Undergrads - Jointly tought at UD and Lincoln University (first degree granting HBCU )

ML

PNS

undergraduate students from various disciplines:

different backgrounds

no functional coding

no experience with unstructured homework

advanced UG and Grad students:

domain experience

varying coding background

some experience w quantitative inference

varying experience with unstructured homework

Focus on questions, not on answers

DS

PS

Recipe:

Real Data from Real Problems
Collaborative project-based work
Free access, industry-ready tools
On-going discussions of DS ethics

Live coding by the students and instructur

equalizing technology access:

Slack (or discourse), GitHub, GoogleColab, tableau, google earth, Python

validating everyone's background

(in project ideation and by assigned roles: data steward, domain expert, methodology design lead)

real problems from the literature (scientific or public access work, including blogs, medium posts) that are relevant to students' lives

students unpack ethical aspects of each project

Data Ethics is a core course of the UD MSDS

Challenge:

Teach them to use AI to facilitate coding,

but not to skip over the understanding bit

demystify coding and Data Science concepts

Grading

Grading: while I talk a lot about coding practices, the grade is always only based on the analysis, not the code:

(1) are the figure telling the story and telling it correctly

(2) figure captions - are the figures interpreted correctly

(3) reproducibility: does the code run

Final required but not graded per se - 1-1 interview for final grade review the final and general understanding

@fedhere

We can make the scientific community a community of practice funded compassion and cooperation

is a word I am borrowing from Margaret Atwood to describe the fact that the future is us.

However loathsome or loving we are, so will we be.

Whereas utopias are the stuff of dream dystopias are the stuff of nightmares, ustopias are what we create together when we are wide awake

https://www.youtube.com/watch?v=QO3nY_u6hos

US-TOPIA

thank you!

University of Delaware

Department of Physics and Astronomy

Biden School of Public Policy and Administration

Data Science Institute

federica bianco

fbianco@udel.edu

Multi-city Urban Observatory Network

Studying cities as complex systems through imaging data

Multi-city Urban Observatory Network

Dobler, Bianco, et al 2021, in Remote Sensing

Studying cities as complex systems through imaging data

energy demand and consumption
ecology of flora and fauna
urban metabolism
circadiem rhythms

Multi-city Urban Observatory Network

Testing the performance of MetaAI SAM on astronomical objects

Instead of building our own specialized AI, can we adapt the models that the industry produces?

That would save a lot of computational resources and computational resources have an environmental footprint!

Award #2123264

Rodiat Ayinde and Tatiana Acero Cuellar are applying the computer vision models they developed for astronomy to geography

Tatiana Acero Cuellar

Why do we study the night sky?

NASA - Hubble Legacy Field Zoom-Out

Two things fill the mind with ever new and increasing admiration and awe, the more often and steadily we reflect upon them: the starry heavens above me and the moral law within me.

I see them before me and connect them immediately with the consciousness of my existence.

-Emmanuel Kant

https://baptistnews.com/article/we-do-not-know-all-the-names/

Training a single large model like a ResNet-50 on a standard GPU (e.g., NVIDIA V100) for a few epochs on ImageNet (1.2M images) can emit roughly ~100-150 kg CO₂or the CO₂ equivalent of a short flight.

But how many models are you training in development?

7 bands

sparse data

Award #2308016

Award #2123264

Rubin Rhapsodies:

a project to give access to LSST data through sound

7 bands

sparse data

Award #2308016

Award #2123264

Rubin Rhapsodies:

a project to give access to LSST data through sound

7 bands

sparse data

Award #2308016

Award #2123264

Rubin Rhapsodies:

a project to give access to LSST data through sound

What's even harder to study than stellar explosions?

Shar Daniels is a NSF Graduate Research Fellow.

They use telescopes and cameras in innovative ways to show the stars in their time evolution at milliseconds rate

and uses cutting edge AI (transformers) to discover new physical phenomena

NSF Graduate Research

Fellowship Program

time: 1 pixel = 3.0 milliseconds

space: 1 pixel = 1 arcsecond

What's even harder to study than stellar explosions?

Any phenomenon that changes rapidly, in less than hours, is a technological challenge in astronomy

What's even harder to study than stellar explosions?

Stellar flares are short lived (~minutes) brightening events caused by magnetic reconnections in stars' atmospheres. Stellar flare impact planetary habitability. Fast and unpredictable, they are hard to study and their physical properties, like temperature, are poorly constrained.