Quantum Computing since Democritus 1st Edition, Kindle Edition
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About the Author
- ASIN : B00B4V6IZK
- Publisher : Cambridge University Press; 1st edition (March 14, 2013)
- Publication date : March 14, 2013
- Language : English
- File size : 2198 KB
- Simultaneous device usage : Up to 4 simultaneous devices, per publisher limits
- Text-to-Speech : Enabled
- Enhanced typesetting : Enabled
- X-Ray : Not Enabled
- Word Wise : Enabled
- Print length : 406 pages
- Lending : Not Enabled
- Best Sellers Rank: #220,907 in Kindle Store (See Top 100 in Kindle Store)
- Customer Reviews:
Top reviews from the United States
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My Background: I have a layman's understanding of quantum mechanics, and took some Computational Complexity classes in college. I have a good understanding of the P vs NP complexity classes.
In this book, Aaronson discusses at least a dozen other complexity classes, including ZPP, BPP, AM, MA, IP, PSPACE, and many more. Each class is BRIEFLY discussed, but there's no way to understand them all without using other references, and by the time I was done with the book, I couldn't remember the definitions of most of them.
Aaronson's thesis is stated explicitly in the preface: "If quantum mechanics isn't physics in the usual sense - if it's not about matter, or energy, or waves, or particles -- then what is it about? From my perspective, it's about information and probabilities and observables, and how they relate to each other."
That's an interesting thesis, and I'd love to read the same book rewritten for laymen. Unfortunately, this book is too complex for a layman without putting in a LOT of outside reading, and though it had some fun puzzles and thought experiments, it just wasn't a fun read overall. It was a bit of a slog.
While he introduces complexity theory he does assume the reader is already familiar. He even explicitly states so several times. Be that as it may a hard working reader can certainly follow along.
The text is chock full of amazing and wonderful inisghts not only for the computationally inclined but also for the physicist. Aaronson has a unique view of physics and i found his perspective wildly illuminating.
I wish id have found and read this book in 2012 when it was published.
SImply amazing. IT is a book i will surely come back to and read again and again.
What it's got against it: Scott makes two terrible mistakes. First, he tries overhard to be conversational. Some of this is just offputting, like the many appearances of profanity in the book. (What possible purpose could this serve?) But in many cases, he simply fails to take advantage of print as a medium. You can explain things multiple times in multiple ways. More formal and less formal. Basic idea and then development. This is never done. Everything is said basically once, at some almost completely unpredictable level of detail and formality.
The second problem is that Aaronson makes no distinction -- and I mean *no* distinction -- between what he actually knows and what he only thinks about. In some cases, he's speculating on things that other people know well, but he just goes on as if his opinion were gospel. A case in point is where he supports the view -- still not mainstream, I don't think -- that something "weird" happens when you cross the event horizon of a black hole not for any physical reason, but because he simply felt that "it should be that way." I'm sorry. If I want to adopt someone's vague intuition on this as physically accurate, I'll ask a physicist.
In other cases, he's speculating on things that no one knows about. But he still presents his speculations as if they were fact.
It's really a pity. I would have been pretty happy reading those speculations if they had only been clearly identified as such.
To see how a book like this can be done, check out Tegmark's "Our Mathematical Universe." That book is considerably less technical than this one (and the subject matter is very different), but does a wonderful job of avoiding the pitfalls into which Aaronson has fallen.
Top reviews from other countries
We start with a tour of prerequisites. Chapter 2 covers axiomatic set theory (ZF); chapter 3 Gödel's Completeness and Incompleteness Theorems, and Turing Machines. In chapter 4 we apply some of these ideas to artificial intelligence, discuss Turing's Imitation Game and the state of the art in chatbots, and also Searle's Chinese Room puzzle. Aaronson invariably provides a fresh perspective on these familiar topics although already we see the `lecture note' character of this book, where details are hand-waved over (because the students already know this stuff, or they can go away and look it up).
Chapters 5 and 6 introduce us to the elementary computation complexity classes and explain the famous P not = NP conjecture. This is not a first introduction - you are assumed to already understand formal logic and concepts such as clauses, validity and unsatisfiability. Chapters 7 and 8 introduce, by way of a discussion on randomness and probabilistic computation, a slew of new complexity classes and the hypothesised relations between them, applying some of these ideas to cryptanalysis.
Chapter 9 brings us to quantum theory. Six pages in we're talking about qubits, norms and unitary matrices so a first course on quantum mechanics under your belt would help here. The author's computer science take on all this does bring in some refreshing new insights. We're now equipped, in chapter 10, to talk about quantum computing. Typically this is not architecture or engineering discussion; Aaronson is a theorist, and for his community, quantum computing means a new set of complexity classes with conjectural relationships to those of classical computation.
We now go off at a tangent as the author critiques Sir Roger Penrose's views on consciousness as a quantum gravity phenomenon. I think it's fair to say that no-one in AI takes this idea seriously, but the author has the intellectual resources to engage Penrose on his own ground here.
In chapter 12 we crank up the technical level to talk about decoherence and hidden variable theories. This is one of the most interesting chapters but is too discursive - really important concepts are touched on and then abandoned; for example the discussion of decoherence and the 2nd Law of Thermodynamics is set against a model of the multiverse, but it's never quite clear whether Aaronson is assuming the reality of the Everett Interpretation or whether he has some other, more purely mathematical model in mind.
Chapter 12 reminds us that a computational complexity theorist's idea of proof is a long way from that of a logician. We plunge into stochastic proofs, zero-knowledge proofs and probabilistically checkable proofs, all framed by a complexity analysis.
The next few chapters cover a series of topics in similar vein: quantum proofs (and their complexity classes), rebuttals of sceptical arguments against quantum computing (interesting and convincing), some technically demanding material on learning algorithms, and concepts of interactive proof.
The final few chapters are more philosophical: Aaronson applies his toolkit to topics such as the Anthropic Principle (via Bayesian reasoning); free will (he's in favour but has a highly-idiosyncratic view of what free will is); time travel (how closed timelike curves impact on classical and quantum computation); and cosmology (black holes, the information paradox, with firewalls bringing us up-to-date).
I have to say that I did finish this book - it didn't just sit on my coffee table, abandoned after the first few chapters, as the author rather fears in his preface. However, it has to be said that despite the author's undeniable enthusiasm, complexity theory remains a minority taste. There are plenty of insights and novel observations even for those of us less enthralled but I hope it's clear what kind of background the reader needs to get anything out of this volume.
To be fair, the book is already 362 pages long and to make the material less a write-up of post-graduate lecture notes and more a self-contained and smoothly-developed presentation of Aaronson's many original insights would seem to require an inordinate amount of time and effort, without substantially increasing the likely readership. I enjoyed it, but not without a degree of frustration.