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Noson S. Yanofsky is Professor in the Department of Computer and Information Science at Brooklyn College and The Graduate Center of the City University of New York. He is a coauthor of Quantum Computing for Computer Scientists.

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Really enjoyed the 75% or so that I understood and I just skimmed the rest.
 
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steve02476 | 5 andere besprekingen | Jan 3, 2023 |
The Outer Limits of Reason is as far as I remember one of the best research essay that I have read so far. I definitely recommend the book to all inquiring minds around and to anyone who is too much confident about him/her-self knowledge.
Noson S. Yanofsky confirmed his knowledge page by page and with astonishing clarity explain hard topic such as Chaos, Relativity Theory and Quantum Mechanics. As a graduate student of Computer Science and Engineering I have found really well written explanations about theoretical computer science. Not for nothing Yanofsky is Professor in the Department of Computer and Information Science at Brooklyn College and The Graduate Center of the City University of New York.
Awards
Winner, 2013 American Publishers Award for Professional and Scholarly Excellence (PROSE Award) in Popular Science & Popular Mathematics, presented by the Professional and Scholarly Publishing Division of the Association of American Publishers
Quotes
Science is a human activity. It is created by finite, flawed human beings attempting to search for the ultimate truth.

The mathematics becomes abstract and about nothing in particular. Because these concepts are about nothing, they are about everything.

Rather than asking why the laws of physics follow mathematics, ask why there are any laws at all.

When we talk about the limits of scientific reasoning, we must keep in mind how we are observing the universe…the way we look at the universe is the way it will present itself to us.

Do not mistake the metaphor for reality.

SPOILER: Yanofsky conclusion thought
We human beings already live beyond reason. Real life has importance only when it includes ethics, values, and beauty. Reason is a powerful but nevertheless limited tool.
Table Of Contents

  • Introduction 1

  • Language Pradoxes 15

    • Liar! Liar! 15

    • Self-Referential Paradoxes 19

    • Naming Numbers 26


  • Philosophical Conundrums 31

    • Ships, People, and Other Objects 31

    • Hangin’ with Zeno and Gödel 41

    • Bald Men, Heaps, and Vagueness 50

    • Knowing about Knowing 57


  • Infinity puzzles 65

    • Sets and Sizes 66

    • Infinite Sets 69

    • Anything Larger? 76

    • Knowable and Unknowable 85


  • Computing Complexities 97

    • Some Easy Problems 98

    • Some Hard Problems 109

    • They’re All Connected 121

    • Almost Solving Hard Problems 129

    • Even Harder Problems 131


  • Computing Impossibilities 135

    • Algorithms, Computers, Machines, and Programs 136

    • To Halt or Not to Halt? 139

    • They’re All Connected 146

    • A Hierarchy of the Unknown 152

    • Minds, Brains, and Computers 157


  • Scientific Limitations 161

    • Chaos and Cosmos 161

    • Quantum Mechanics 175

    • Relativity Theory 214


  • Metascientific Perplexities 235

    • Philosophical Limitations of Science 235

    • Science and Methamatics 252

    • The Origin of Reason 272


  • Mathematical Obstructions 297

    • Classical limits 298

    • Galois Theory 304

    • Harder Than Halting 309

    • Logic 320

    • Axioms and Independence 331


  • Beyond Reason 339

    • Summing Up 339

    • Defining Reason 345

    • Peering Beyond 349


  • Notes 355

  • Bibliography 379

  • Index 393


… (meer)
 
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giacomomanta | 5 andere besprekingen | Aug 23, 2022 |
A wide and shallow review of various logical conundrums, language paradoxes, mathematical impossibilities, and quantum confusion. Yanovsky presents all this as representing the limits of ‘reason,’ but the kind of assumptions that he makes let you know that he is a computer scientist and not a philosopher.
 
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MusicalGlass | 5 andere besprekingen | Jan 16, 2021 |
I saw the IBM live demonstration of their five qubit machine. The problem I witnessed is that unless you make the initial set-up perfect, the accumulation of errors kills you. The Quantum Computer is really just another analogue device, not a digital one. In addition to all the other problems you get device-variability. What should ostensibly be two identical qubits when manufactured, turns out to be two qubits with slightly different properties. And then they told us that if the qubits were too far away from one another they didn't work properly, and that they didn't have full connectivity between qubits for larger machines. And of course the more error-correction you add to the system the more qubits you need.

Don't get me wrong, I think this stuff is great, but I'm dubious that the systems engineering required to turn it into an everyday reality is going to show up anytime soon.

The way they operate these devices at the moment is to cool everything to near absolute zero so that the state super-position doesn't decohere. And then run the same problem multiple times -- thousands of times in fact.

At the end you get a distribution of final states (i.e., in other words they decohere eventually). In the problem I saw being solved the correct solution occurred with probability circa 40%, but an incorrect one also showed up with a similar probability, when in fact a mathematically correct simulation of the quantum computation would give 0%.

In this case, I think the explanation was that this was a consequence of device variability.

The obvious way to build in error-correction would be to run the problem in parallel and then combine the results. So, I think, we need to triple the number of qubits, though there are probably better solutions.
… (meer)
 
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antao | Sep 24, 2020 |

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5
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259
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#88,671
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½ 3.7
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7
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19
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