Quantum computing aims to leverage the properties of superposition and interference to perform certain computations much faster than classical computers.
Quantum supremacy represents a milestone that demonstrates the superior computational power of quantum computers compared to classical ones.
Building error-corrected quantum computers, where qubits maintain their quantum state reliably, is the ultimate goal in the field.
Deep dives
Introduction to Quantum Computing
Quantum computing is a new approach to computation that utilizes the principles of quantum mechanics. It uses qubits, which are quantum bits that can exist in a superposition of both 0 and 1 states. Quantum computing aims to leverage the properties of superposition and interference to perform certain computations much faster than classical computers. Despite being in the early stages, there is significant potential for quantum computing to revolutionize various fields. However, one of the main challenges is achieving and maintaining the required level of error correction and qubit reliability.
The Concept of Quantum Supremacy
Quantum supremacy refers to the point in history when a quantum computer can perform a well-defined task significantly faster than any known classical computer. The task does not necessarily have to be useful, but it must have clearly defined right and wrong answers. Quantum supremacy represents a milestone that demonstrates the superior computational power of quantum computers compared to classical ones. Achieving quantum supremacy serves as strong evidence that quantum computers possess computational capabilities that cannot be replicated by classical systems. This landmark achievement lays the foundation for further advancements in quantum computing.
Google's Quantum Supremacy Announcement
Google recently made headlines by announcing their achievement of quantum supremacy. Their research involved a quantum computer that demonstrated the ability to solve a specific problem much faster than classical computers. This momentous achievement has stirred excitement in the field as it provides tangible evidence that quantum computing can outperform conventional computing, at least in certain tasks. While quantum supremacy is still in the early stages and there are challenges to overcome, this breakthrough paves the way for future advancements in quantum computing and opens up new possibilities for solving complex problems.
The Path to Error-Corrected Quantum Computers
Building error-corrected quantum computers, where qubits maintain their quantum state reliably, is the ultimate goal in the field. Currently, quantum computers face the challenge of decoherence, where unwanted interactions between qubits and the environment lead to loss of quantum states. Overcoming this challenge requires significant engineering efforts and innovations. Researchers are working towards reducing noise and improving qubit reliability to enable error correction. Theoretical breakthroughs and insights are also necessary to reduce the overhead of error correction and make error-corrected quantum computers practical. Achieving error-corrected quantum computers would unlock their full potential and revolutionize various domains of technology and science.
Advantages of Quantum Computing: Sampling Problems
One of the main realizations in quantum computing is that solving sampling problems, where the goal is to output a sample from a probability distribution, can be more advantageous than focusing on problems with a single right answer like factoring numbers. With a quantum computer, a randomly chosen sequence of operations can be applied to generate samples from the desired probability distribution. Although all outputs are exponentially unlikely, some are more likely than others due to constructive and destructive interference in their amplitudes.
Verifying Quantum Supremacy and Computational Complexity
Verifying that a quantum computer has achieved quantum supremacy, or outperforming classical computers, is a crucial aspect. Google's experiment used a statistical test called the linear cross entropy benchmark to test the outputs. However, verifying the results computationally is challenging, as it requires an exponentially costly classical calculation. While it is difficult to definitively rule out the possibility of fast classical algorithms for simulating quantum mechanics, evidence from complexity theory suggests that such algorithms are highly unlikely.
Scott Aaronson is a professor at UT Austin, director of its Quantum Information Center, and previously a professor at MIT. His research interests center around the capabilities and limits of quantum computers and computational complexity theory more generally.
This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.
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Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.
00:00 – Introduction
05:07 – Role of philosophy in science
29:27 – What is a quantum computer?
41:12 – Quantum decoherence (noise in quantum information)
49:22 – Quantum computer engineering challenges
51:00 – Moore’s Law
56:33 – Quantum supremacy
1:12:18 – Using quantum computers to break cryptography
1:17:11 – Practical application of quantum computers
1:22:18 – Quantum machine learning, questionable claims, and cautious optimism
1:30:53 – Meaning of life
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