By Tara Collins, Michelle Escobar, Kayla Rollins, and Logan White

When you hear the phrase computational dynamics, what comes to mind?

By Tara Collins, Michelle Escobar, Kayla Rollins, and Logan White

When you hear the phrase computational dynamics, what comes to mind?

Images of glasses-clad tech whizzes staring into screens?

Flowcharts, oceans of coffee, and lightbulb moments?

Utter computer-related confusion?

By: Kathryn Benedict, Kate Allen, Sarai Ross, Rosy Nuam

Girls Talk Math is an all girls camp that introduces new topics that students would not normally see in their everyday math class at school. This camp also brings together many young women to better explore a field that is male dominated. During this camp we were able to research many important women that we able to make their own legacy while facing much adversity along the way. The camp wants to show not only the campers but also other women going into the field of math and science to not be afraid due to the gender difference, but instead use it as motivation to carry on doing what you love and making your own legacy along the way.

Our group consisted of four young women. Kathryn is a rising sophomore at Cedar Ridge High School. Kate is a rising sophomore at Carrboro High School. Sarai is a rising junior at Northern Vance High School. Rosy is a rising senior at East Chapel Hill High School.

by Nya Batson, Monique Dacanay, Emily Gao, and Staci Tranquille.

Hello! And welcome to the realm of quantum mechanics! First off, what in the world is quantum mechanics? Let’s start with a brief introduction.

Quantum mechanics is one of the most important branches of physics. It focuses on the laws of nature at three different levels: molecular, atomic, and subatomic. Quantum mechanics has a variety of important concepts; the following are some that we learned through our problem set: Planck’s law, the photoelectric effect, and wave-particle duality. A crucial element of quantum mechanics is understanding that everything has characteristics of both waves and particles. We will touch on this and many other topics later on.

By: Michelle Chen, Cameron Farrar, Laura O’Sullivan, and Cat Bassett

**Introduction**

Everything we do in life has a chance. That chance may come from picking the right card, picking a certain marble out of a bag or maybe deciding to give the first person who walks through a random door $100. Essentially,each chance has a certain trade-off of benefits. Often times we think about the chances as something will happen over the chance of something else taking place as we weigh possible outcomes. This is called risk analysis. One of the ways we can determine risk is we can use Monte Carlo simulations to replicate real life situations a large number of times in order to observe the long-term patterns without having the complications (cost, labor, materials, etc.) of manual repetition.

By Divya Aikat, Helena Harrison, Annie Qin, and Quinn Shanahan

The definition of cryptography is the art of writing and solving code. However, over the last two weeks, we learned so much more than just this textbook explanation. While working together within our team, we explored many different aspects behind cryptography. By building off our individual strengths, we prepared ourselves for higher level mathematics. The following is a synopsis of the progress we’ve made over the past two weeks.

By Nethania Okyere, Rachel Rozansky, Ashleigh Taylor, and Sylvia Towey

**Knot Theory**

The knot theory are two mathematical branches of topology. Its simply a loop in 3 dimensional space( doesn’t intersect itself). Knots can be described in various ways. Given a method of description, however, there may be more than one description that represents the same knot. For example, a common method of describing a knot is using a knot diagram. Any given knot can be drawn in many different ways using a knot diagram.

By Noa Bearman, Kimberly Cruz Lopez, Tina Lin, Xintong Xiang, and Maria Neri Otero*

*Maria helped the group work through the problem set but was unfortunately unable to attend camp during the blog writing.

**Introduction**

Have you ever tried to send a secret message to a friend? Did it work? Was it secure? Well, one way to do so in a more secure way is by using Elliptic Curve Cryptography (ECC). Most people have never heard of ECC before, and two weeks ago, neither did we. However, in the past two weeks, we have been learning how to use this exciting application of the techniques of algebraic geometry and abstract algebra applied to the ancient art of keeping messages secure. ECC was first introduced by Victor Miller and Neal Koblitz in 1985. It was proposed as an alternative to other forms of cryptography with public-key systems such as DSA and RSA. Public-key systems involve the use of two different kinds of keys: a public key that is available to the public and a private key in which only the owner knows. The applications of ECC has been growing and has recently gained a lot of attention in industry and academia. The following information below will go more in-depth on what ECC is, how it works, its advantages, its disadvantages, and our progression throughout this course.

By Myla James, Shania Johnson, Maya Mukerjee, and Savitha Saminathan.

**Graph Theory**

Here’s some definitions to help you understand our assignment:

Nodes – vertex/point.

Edges – lines connecting vertices.

Adjacent – two nodes (vertices) are adjacent if they share an edge (line).

Degree – number of edges adjacent to a particular node.

We started this problem set with learning about the difference between connected and disconnected graphs.

Connected Graph – able to travel from one node to any other through its edges.

Disconnected graph – more complex; it has components.

Components – parts of the graphs that are connected.

By Camilla Fratta, Ananya Jain, Sydney Mason, Gabby Matejowsky, and Nevaeh Pinkney*.

*Nevaeh helped the group work through the problem set but was unfortunately unable to attend camp during the blog writing.

Mathematical Epidemiology explores the realm of mathematics applied to public health. It relies on modeling to use known information about certain scenarios regarding the spread of diseases and then uses it to predict future outcomes. By the end of the problem set, our group learned about the challenging process that comes with trying to predict population sizes in order to control the spreading of diseases. The equations that are faced in this branch of mathematics are at the heart of mathematical modeling.

**Mathematical Models and Modeling**

A mathematical model is an equation used to predict or model the most likely results to occur in a real-world situation. We used these types of equations to model the spread of a disease in a population, tracking the flow of populations from susceptible to infected to recovered. In real life scenarios, there are too many variables to fully account for, so we only were able to place a few in our equations. This made the models less accurate, but at the same time very useful to us in our problem set. They gave us a good idea of how things worked in an actual epidemic and helped us to understand what mathematical modeling really is.

By: Nia Beverly, Makayla McDaniel, Yuanyuan Matherly, and Tyler Deegan

**Cryptography** is defined as the art of writing and solving codes. Upon first thought, many people picture codes as an antiquated war time communication technique. However, the field of cryptography is alive and well, and it has become pervasive in our everyday lives. The world is becoming more and more connected through technology, and with this, there is a greater need to protect information. **Encryption** is probably the most widely used application of cryptography, and it is used to protect information by making it so only one person with a key can understand what is transmitted. In the following paragraphs we will walk through the steps to mathematically understanding one widely used type of encryption.