Quantum Computers, Explained With Quantum Physics

Summary

The script explores the concept of quantum computing, introduced by Richard Feynman, which uses quantum elements to simulate quantum systems. It delves into the principles of quantum mechanics, such as amplitudes and superposition, and how qubits differ from classical bits. The potential of quantum computing in solving complex problems and its challenges in measurement and algorithm design are highlighted, with an emphasis on its exciting prospects in physics.

Takeaways

• ❄️ Quantum computers operate at temperatures just above absolute zero, isolated from the rest of the universe.
• 🚀 Quantum computers promise revolutionary advancements in computation, distinct from classical supercomputers.
• 🔬 Understanding quantum computing requires a grasp of quantum mechanics, particularly the concept of amplitudes.
• 🧠 Richard Feynman proposed quantum computers to simulate quantum systems that classical computers couldn't handle.
• 🌊 Amplitudes, complex numbers different from probabilities, govern the behavior of quantum systems.
• ⚛️ Qubits, the basic units of quantum computing, exist in superposition, holding both 0 and 1 states simultaneously.
• 🔗 Quantum entanglement links qubits, creating correlations that vastly increase computational potential.
• 🎲 Measuring a quantum system collapses it into a classical state, turning amplitudes into probabilities.
• 🌐 Interference, where amplitudes add constructively, is key to designing effective quantum algorithms.
• 🔍 Despite theoretical advancements, the most impactful applications of quantum computing remain unknown and await future discovery.

Q & A

What is the primary promise of quantum computing according to the script?

Quantum computing embodies the promise of the future with its potential to revolutionize our lives through turbo-charged computation.

How does quantum computing differ from classical computing?

Quantum computers aren’t just the next generation of supercomputers; they operate according to the laws of quantum physics and use qubits, which can be in a state of superposition, unlike classical bits that are strictly 0 or 1.

Who first proposed the idea of a quantum computer, and why?

Richard Feynman proposed the idea of a quantum computer because classical computers couldn't scale up to simulate quantum systems due to the exponential rise in computation cost with added particles.

What are amplitudes in quantum mechanics?

Amplitudes in quantum mechanics are complex numbers that describe the probabilities of different outcomes. They differ from classical probabilities in that they can interfere with each other, leading to phenomena such as cancellation.

What is superposition in the context of quantum computing?

Superposition is a state where a qubit can simultaneously hold a combination of 0 and 1, allowing quantum computers to process a vast amount of data compared to classical computers.

What is quantum entanglement?

Quantum entanglement is a phenomenon where qubits in a superposition state are mathematically related, such that the state of one qubit is directly connected to the state of another, regardless of the distance between them.

Why is it challenging to simulate highly entangled states with classical computers?

Simulating highly entangled states with classical computers is extremely expensive because the amount of classical bits needed grows exponentially. For instance, a 500-qubit system would require more classical bits than there are atoms in the known universe.

What happens to a quantum system when it is measured?

When a quantum system is measured, it collapses into a classical state, meaning that the qubits lose their superposition and become either 0 or 1.

How do scientists harness interference in quantum computing?

Scientists harness interference by creating a deterministic sequence of qubit gates that cause amplitudes to add up constructively, thereby boosting the probability of obtaining the correct answer.

What are some potential applications of quantum computing mentioned in the script?

Potential applications of quantum computing include fields such as cybersecurity and search optimization, but its most significant use is expected to be in exploring and understanding the deep structure of our world.

Why is designing quantum algorithms considered difficult?

Designing quantum algorithms is difficult because it requires ensuring that amplitudes add up constructively to increase the probability of the correct answer, which is challenging without knowing the right answer in advance.

Outlines

00:00

🌌 Quantum Computing: The Future of Computation

This paragraph introduces the concept of quantum computing, highlighting its potential to revolutionize computation beyond traditional supercomputers. It delves into the fundamental physics behind quantum computing, emphasizing the need to understand quantum mechanics. Richard Feynman's quest to simulate quantum systems and his realization that classical computers are inadequate for such tasks are discussed. The idea of a quantum computer, operating on quantum elements and laws, is introduced. The paragraph also touches on the concept of amplitudes in quantum physics, which differ from classical probabilities and are crucial for understanding quantum computing. The qubit, as the basic computational unit in quantum computing, is explained, contrasting it with classical bits and detailing its ability to exist in a superposition of states, which is key to quantum computing's power.

05:05

🔬 Exploring Quantum Entanglement and Measurement

This paragraph further explores the intricacies of quantum computing, focusing on the phenomena of superposition and entanglement. Superposition allows qubits to exist in multiple states simultaneously, enabling quantum computers to process vast amounts of data more efficiently than classical computers. Entanglement, described as the correlation among parts of a quantum system, is highlighted as a critical aspect of quantum computing. The paragraph explains how entanglement makes the description of highly entangled states with classical bits extremely costly. The challenge of measuring quantum systems without collapsing their quantum states into classical states is discussed, along with the use of interference to extract meaningful answers from quantum systems. The concept of quantum algorithms is introduced, explaining how they harness interference to boost the probability of obtaining correct answers. The paragraph concludes by acknowledging the difficulty in designing quantum algorithms and the potential of quantum computing to yield applications that are currently unforeseen.

Keywords

💡Quantum Computer

A quantum computer is a type of computer that uses quantum bits (qubits) to perform computations. Unlike classical computers that use bits (0 or 1), qubits can be in a state of 0, 1, or both simultaneously (superposition). This allows quantum computers to handle complex computations much faster than classical computers. In the video, the quantum computer is described as a revolutionary technology with the potential to vastly improve computational power.

💡Qubit

A qubit is the basic unit of information in a quantum computer, analogous to a bit in a classical computer. Qubits can exist in multiple states simultaneously due to the principle of superposition, allowing them to store and process much more information. The video explains that qubits are what enable quantum computers to perform complex calculations more efficiently than classical computers.

💡Superposition

Superposition is a fundamental principle of quantum mechanics where a quantum system can exist in multiple states at once. For qubits, this means they can be both 0 and 1 simultaneously. This principle is key to the enhanced computational power of quantum computers, as discussed in the video, where it allows for the manipulation of vast amounts of data.

💡Entanglement

Entanglement is a quantum phenomenon where two or more particles become linked, and the state of one particle directly influences the state of the other, no matter the distance between them. In the video, entanglement is described as a crucial feature of qubits, enabling the complex correlations necessary for quantum computing's superior processing capabilities.

💡Amplitude

In quantum mechanics, amplitude refers to the complex numbers associated with the likelihood of a quantum system being in a particular state. Amplitudes are not probabilities but are used to calculate probabilities. The video highlights that understanding amplitudes is essential to grasp the functioning of quantum computers and how they differ from classical computers.

💡Interference

Interference in quantum mechanics is the phenomenon where the amplitudes of different quantum states combine, leading to the enhancement or cancellation of probabilities. The video uses the analogy of waves in a pool to explain how interference helps in designing quantum algorithms, ensuring that the correct outcomes are more likely to occur.

💡Quantum Algorithm

A quantum algorithm is a set of instructions for a quantum computer to solve a problem using quantum principles like superposition, entanglement, and interference. The video discusses how quantum algorithms are challenging to design but have the potential to solve problems much more efficiently than classical algorithms, particularly in fields like cryptography and optimization.

💡Richard Feynman

Richard Feynman was a renowned physicist who proposed the concept of quantum computing in the 1980s. He recognized that classical computers could not efficiently simulate quantum systems and suggested that a computer based on quantum principles would be capable of such simulations. The video credits Feynman with laying the foundation for the field of quantum computing.

💡Classical Computer

A classical computer is a traditional computer that processes information using bits that are either 0 or 1. The video contrasts classical computers with quantum computers, highlighting that classical computers are not scalable for simulating quantum mechanics due to their exponential increase in computational cost with added complexity.

💡Simulation

In the context of quantum computing, simulation refers to the use of a quantum computer to model and study quantum systems. The video explains how Richard Feynman envisioned using quantum computers for simulations to gain insights into the quantum universe, something classical computers struggle with due to their limited scalability.

Highlights

Quantum computers are not the next generation of supercomputers but represent a fundamentally different technology.

The potential of quantum computing lies in its ability to revolutionize computation with its turbo-charged capabilities.

Understanding quantum computing requires delving into the subatomic world governed by quantum mechanics.

Richard Feynman envisioned a computer that could simulate quantum systems, leading to the concept of the quantum computer.

Classical computers are inadequate for simulating quantum mechanics due to the exponential increase in computational cost.

Quantum computers operate on the principles of quantum physics, making them ideal for probing the quantum realm.

Amplitudes, a core concept in quantum physics, differ from probabilities as they are complex numbers and not limited to 0 to 1.

The power of quantum computing stems from the unique rules of probability in the quantum universe.

Qubits, the basic unit of quantum computing, differ from classical bits by existing in superposition, allowing for 0, 1, or both states.

Superposition enables qubits to store and manipulate vast amounts of data, surpassing the capabilities of classical computers.

Entanglement is a phenomenon where qubits in superposition are mathematically related, affecting their outcomes upon measurement.

Quantum entanglement is characterized by correlations among parts of a quantum system that differ from classical correlations.

Describing highly entangled states with classical bits is impractical due to the exponential increase in required bits.

Quantum computers require measurement to extract information, but measurement collapses the quantum system into a classical state.

Interference, a phenomenon observed in waves, is harnessed in quantum computing to boost the probability of correct answers.

Quantum algorithms use a deterministic sequence of qubit gates to constructively add amplitudes, increasing the likelihood of correct outcomes.

Designing quantum algorithms is challenging due to the need to concentrate on the right answer without prior knowledge.

Quantum computing has had major breakthroughs since 1994, with theoretical applications in cybersecurity and search optimization.

The most significant application of quantum computers may be in exploring the deep structure of our world, as initially envisioned by physicists.

The true potential and applications of quantum computing are still largely unknown and may be discovered once quantum computers are more accessible.

Transcripts

Here, inside this refrigerator, at a temperature just a tick above absolute zero, isolated

from the rest of the universe... ...is a quantum computer.

If you believe the hype, this nascent technology embodies the promise of the future, and has

the potential to revolutionize our lives with its turbo-charged computation.

But quantum computers aren’t the next generation of supercomputers—they’re something else

entirely.

And before we can even begin to talk about their potential applications, we need to understand

the fundamental physics that drives the theory of quantum computing.

We’ll need to dive into another dimension, smaller and more alien than anything we intuitively

understand: the subatomic world of quantum mechanics.

Feynman’s Idea In the 1980s, one of the most important physicists

of the 20th century encountered a major roadblock.

Richard Feynman was hungry for a window into the quantum universe.

But quantum systems, by nature, are fragile, and the information they hold hides from us.

Because Feynman couldn’t directly observe quantum events, he wanted to design a simulation.

It quickly became clear that his computer wasn’t up to the task.

As he added particles to the quantum systems he was modeling, the cost of computation began

to rise exponentially.

Feynman concluded that classical computers just can't scale up fast enough

to keep pace with the growing complexity of quantum calculations.

Then he had a breakthrough.

What if he could design a tool made up of quantum elements itself?

This instrument would operate according to the laws of quantum physics, making it the

perfect way to probe the mysteries of the quantum realm.

The idea of the quantum computer was born.

And by dreaming it up, Feynman had started to build a bridge between quantum physics

and computer science.

To understand how quantum computing works, it’s essential to start by understanding

what makes it quantum in the first place.

This means that we need to talk about what’s at the heart of quantum physics: a concept

called amplitudes.

Here’s what the classical rules of probability tell us about getting tails if we toss a coin

20 times.

We add up the probabilities for all the possible outcomes resulting in tails.

That’s just common sense.

But common sense doesn’t govern the quantum universe.

Before you measure a subatomic particle, you can think about it as a wave of probability

that exists in a kind of black box—a quantum system with many different chances of being

in many different places.

Quantum mechanics, at its core, is a change to the rules of probability.

(02:05) This is also where the power of quantum computing comes from—from these different

rules of probability than the ones that we are used to.Amplitudes are closely related

to probabilities.

But they're not probabilities.

A key difference is probability is always a number from zero to one.

But amplitudes are complex numbers.

And what this means is that they obey different rules.

So, if I want to know the total amplitude for something to happen, I have to add up

the amplitudes for all the different ways that it could have happened.

But when I add up amplitudes, I see something new, which is that a particle might reach

a certain place one way with a positive amplitude and another way with a negative amplitude.

And if that happens, then those two amplitudes can cancel each other out so that the total

amplitude would be zero, and that would mean that that thing would never happen at all.

So the amplitudes are connected to the probability that you actually see something when you look

there.

This is sort of the central thing that quantum mechanics says about the world: that the way

that you describe a physical system is by a list of amplitudes.

And the way that a physical system changes over time is by a linear transformation of

these amplitudes—by some change to these amplitudes.

But how can quantum computers use amplitudes to store and manipulate information quantumly?

This is a qubit.

It’s the basic computational unit in quantum computing.

Qubits are like bits in a classical computer, but with a crucial difference.

A bit is binary—it stores information in strings of binary digits that can only be

0 or 1.

But qubits are made of subatomic particles, so they operate according to subatomic logic.

Qubits can be 0, 1, or what we call a linear combination of 0 and 1.

This fluid combination of amplitudes is at the core of quantum computing.

Before you measure a qubit, it exists in a state called superposition.

You can think about it as a quantum version of a probability distribution, where each

qubit has some amplitude for being 0, and some amplitude for being 1.

Superposition is the reason that quantum computers can store and manipulate vast amounts of data

compared to classical computers.

When two or more qubits are in this closed state of superposition, they relate to one

another through the phenomenon of entanglement.

This means that their final outcomes, when we measure them, are mathematically related.

Quantum entanglement is the word we use for the characteristic correlations among parts

of a quantum system, which are different from the correlations that we normally encounter

in the classical world, in ordinary experience.

You could think of it as like a book.

When you look at the pages one at a time, you don't see any information—you just see

random gibberish because the information isn't encoded in the individual pages, but in the

correlations among them.

And to read the book, you have to collectively observe many pages at once.

But if you want to describe very highly entangled states using ordinary bits, it's extremely

expensive.

Imagine that you had a primitive 10-qubit computer.

It could store 2^10 values in parallel.

To describe this entangled configuration with a classical computer, you’d need 16 kilobytes,

or 16 thousand bits.

Expand to a system with 500 entangled qubits, and you now require more classical bits than

there are atoms in the known universe.

This is exactly what Feynman meant when he said that classical computers weren’t scalable

for simulating quantum mechanics.

For a quantum computer to be of any use, you need to measure information from the qubits

to get an output.

The problem is, when a quantum system is measured, it collapses into a classical state.

If you look at a qubit, let's say to ask it whether it's zero or one, then you collapse

its state, right?

You force it to decide whether to be a zero or one.

Anything carries away information about whether that qubit is zero or one—so for example,

if that information gets recorded in some radiation that's escaping from the quantum

computer, then the effect on the qubit will be exactly as if someone had measured it to

see whether it was 0 or 1.

When you look at the system, then the amplitudes become probabilities.

To extract an answer from the quantum system that isn’t just a random outcome of probability,

like the flip of a coin, we have to use interference.

Interference can be seen in classical physics … when waves in a pool hit each other, and

one wave is above the surface, and the other wave is below the surface, and they cancel

each other.

Interference is just what amplitudes do when you add them up.

… If something can happen one way with an amplitude of a half and another way with an

amplitude of minus a half, then the total amplitude for it to happen would be zero.

This is what you do in the famous double slit experiment.

You close one of the paths, and then you see that now the thing that previously never happened,

can happen.

This is a quantum algorithm.

Scientists can harness interference by creating a deterministic sequence of qubit gates.

These qubit gates cause the amplitudes to add up constructively.

This means that they’re mathematically guaranteed to boost the probability of seeing one of

the right answers.

This is a quantum algorithm.

Scientists can harness interference by creating a deterministic sequence of qubit gates.

These qubit gates cause the amplitudes to add up constructively.

This means that they’re mathematically guaranteed to boost the probability of seeing one of

the right answers.

You might ask, how could you possibly concentrate all this on the right answer when you yourself

don't know in advance which answer is the right one?

This is exactly why designing quantum algorithms is so difficult and why we have a whole field

that's been studying it for decades.

Since 1994, there have been a few major breakthroughs in quantum algorithms, with theoretical applications

in fields such as cybersecurity and search optimization.

But according to most experts in the field, quantum computers are most likely to be useful

for what they were born to do—when a curious physicist wondered about the deep structure

of our world.

I find quantum computing exciting as a way to explore physics.

Now, whether that's going to make anybody any money—whether there'll be practical

applications in the near-term—that's still very much an open question.

But at least for physicists, it's an exciting time.

The truth is... that the most important application, I believe, of quantum computers is something

that we don't know yet.

I'm sure that once we have a quantum computer to play with, we'll find amazing applications

that we can't yet foresee.