Peter Elmer of Princeton explains how data is critical to understanding fundamental physics

Peter Elmer of Princeton explains how data is critical to understanding fundamental physics

Assessment

Interactive Video

Science, Physics

11th Grade - University

Hard

Created by

Quizizz Content

FREE Resource

The video discusses the importance of data science in physics, particularly in discovering the Higgs boson. It highlights CERN's role as a Higgs factory and the need for large data sets. Plans to upgrade the Large Hadron Collider to increase data size are mentioned, along with the challenges of exploring these data sets. The Software Institute's role in providing tools for data exploration is also covered.

Read more

5 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the significance of large data sets in fundamental physics?

They are used to create simulations of the universe.

They are primarily for educational purposes.

They help in discovering new particles like the Higgs boson.

They are used to store historical data.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the Large Hadron Collider at CERN currently known for?

Being a factory for producing Higgs bosons.

Creating new elements.

Developing new technologies.

Training physicists.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the planned upgrade for the Large Hadron Collider aimed at?

Improving safety measures.

Reducing energy consumption.

Enhancing the speed of particle collisions.

Increasing the data size by a factor of 100.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What challenge arises from the increased data size at the Large Hadron Collider?

How to share the data with the public.

How to store the data securely.

How to visualize the data in real-time.

How to effectively explore and analyze the data.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary focus of the Software Institute?

Training software engineers.

Developing new software languages.

Providing tools to explore large data sets.

Creating educational content.