Quantum Machine Learning

Regular computing

100

Name one examples of machine learning used in real life.

Any generative AI (like ChatGPT), weather prediction, stock prediction, robotics, etc.

200

A piece of data that can either be 0 or 1

Bit

300

It is a branch of AI involving predictions and training with existing data.

Machine learning

400

Involves an input, many hidden layers and an output

Artificial neural networks

500

The main difference between neural network hidden layers and logic gates

Hidden layers account for and add weights/biases while logic gates do not

Quantum computing

100

The branch of physics relating to subatomic particles and their behavior

Quantum mechanics

200

The quantum equivalent of classical bits

Qubit

300

This theory says that a particle could have multiple states at once.

Superposition

Schrodinger's cat is not accepted

400

Quantum particles can be linked, regardless of the distance between them 

Quantum entanglement

500

How are qubits made? (no specifics)

Manipulating the spin of electrons in particles.

Quantum ML 1

100

Name a benefit of quantum ML

Faster, more accurate, more efficient

200

Name a drawback of quantum ML

Not very accessible, data needs to be converted

300

A fast algorithm to find prime factors

Shor's algorithm

400

Name the quantum mech. principle that explains higher precision in quantum ML

Quantum entanglement

500

Why can quantum neural networks be faster?

Qubits are processed through quantum logic gates and affect each other (entanglement), so there are fewer calculations.

Quantum ML 2

100

One field where Shor's algorithm can be used

Cryptography

200

Why can quantum machine learning be better for optimization problems?

Perform in reasonable time

300

Describe the main function of Shor's algorithm.

Prime factorization but in reasonable time (polynomial, not exponential)

400

Name two cases in which imaging within quantum machine learning is used 

Autonomous vehicles, detecting medical defects

500

Why is gradient descent faster in quantum neural networks than regular neural networks?

You can go in multiple directions and start at multiple points with gradient descent because of parallelism.

Random physics

100

The equation for work

Integral of F dot dr

200

This person combined four important equations which are fundamental for electromagnetism as a whole.

James Clerk Maxwell (or just Maxwell)

300

The rate of change of magnetic flux with respect to time.

electromotive force (emf) or induced voltage

400

The time constant for a circuit with an inductor and resistor(s).

L/R_eq

500

The type of function that solves a second order differential equation where x'' is directly proportional to -x. x is the original function.

x is a sine or cosine function