1 / 26

What Google Won’t Find: The Ultimate Physical Limits of Search

Explore the theoretical limits of search algorithms and the possibility of solving NP-complete problems in physical systems such as quantum computing, analog computing, time travel computing, and anthropic computing.

jescobar
Download Presentation

What Google Won’t Find: The Ultimate Physical Limits of Search

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. What Google Won’t Find:The Ultimate Physical Limits of Search Scott Aaronson University of Waterloo

  2. “Is Google God?” —Thomas Friedman, NYT, 6/29/2003 Why Am I Speaking Here? My field—theoretical computer science—is directly concerned with the question of how to distinguish God from mortal impostors.

  3. CS Theory in One Slide Problem: “Given the Internet, are at least 50% of web pages all reachable from one another?” Each particular Internet is an instance The size of the instance, n, is the number of bits needed to specify it An algorithm is polynomial-time if it uses at most knc steps, for some constants k,c P is the class of all problems that have polynomial-time algorithms

  4. NP: Nondeterministic Polynomial Time Does 37976595177176695379702491479374117272627593301950462688996367493665078453699421776635920409229841590432339850906962896040417072096197880513650802416494821602885927126968629464313047353426395204881920475456129163305093846968119683912232405433688051567862303785337149184281196967743805800830815442679903720933 have a factor ending in 7?

  5. NP-hard: If you can solve it, you can solve everything in NP NP-complete: NP-hard and in NP Is there a Hamilton cycle (tour that visits each vertex exactly once)?

  6. Hamilton cycleGraph 3-coloringSatisfiabilityMaximum clique… Halting problemCounting problems… FactoringGraph isomorphism… Graph connectivityPrimality testingLinear programming… NP-hard NP-complete NP P

  7. Audience Exam Does P=NP? Answer: No. Extra credit: Prove it.(You’ll win at least $1,000,000 if you do)

  8. What could we do if we could solve NP-complete problems? If there actually were a machine with [running time] ~Kn (or even only with ~Kn2), this would have consequences of the greatest magnitude.—Gödel to von Neumann, 1956

  9. Then why is it so hard to prove PNP? Algorithms can be very clever Gödel/Turing-style diagonalization arguments don’t seem powerful enough Combinatorial arguments face the “Razborov-Rudich barrier”

  10. But maybe there’s somephysicalsystem that solves an NP-complete problem just by “relaxing” to its lowest energy state?

  11. Dip two glass plates with pegs between them into soapy water • Let the soap bubbles form a minimum Steiner tree connecting the pegs

  12. Other Physical Systems Spin glasses Folding proteins ... Well-known to admit “metastable” states DNA computers: Just highly parallel ordinary computers

  13. If we observe, we see |0 with probability ||2 |1 with probability ||2 Also, the object collapses to whichever outcome we see It’s Quantum Time If an object can be in two states |0 or |1, then it can also be in a superposition|0 + |1 Here  and  are complex amplitudes satisfying ||2+||2=1

  14. To modify a state we can multiply the vector of amplitudes by a unitary matrix—one that preserves

  15. We’re seeing interference between positive and negative amplitudes—the source of all “quantum weirdness”

  16. Quantum Computing A quantum state of n “qubits” takes 2n complex numbers to describe: The goal of quantum computing is to exploit this exponentiality in Nature.

  17. Interesting Bennett, Bernstein, Brassard, Vazirani 1994: “Quantum magic” won’t be enough Even a quantum computer would need ~2n/2 queries to search an unsorted array of size 2n for a single “marked” item Shor 1994: Quantum computers can factor integers in polynomial time But what about NP-complete problems?

  18. “Relativity Computing” DONE

  19. Problem: The Planck scale (10-33 cm, 10-43 sec) seems to impose a fundamental limit! Analog Computing Do the first step of a computation in 1 sec,the second in ½ sec, the third in ¼ sec, … Possible in “Malament-Hogarth spacetimes,” which have naked singularities

  20. Problem: Grandfather paradoxes Time Travel Computing Naïve idea: Do the first step of a computation, then go back in time and do the next step, etc. Resolution (Deutsch 1991): Use probability or quantum theory. E.g. you’re born with ½ probability, and if you’re born you go back and kill your grandfather, ergo you’re born with ½ probability, etc. Immediately suggests a model of computation, which can be shown to be exactly as powerful as the class PSPACE (A. 2005)

  21. Quantum Gravity Freedman, Kitaev, Wang 2000: “Topological quantum field theories,” a particular class of (2+1)-dimensional quantum gravity theories, yield no more power than ordinary quantum computers String theory? Loop quantum gravity? It’d help if the physicists themselves understood these things better!

  22. “Anthropic Computing” Guess a solution to an NP-complete problem. If it’s wrong, kill yourself. Suppose you could kill yourself in all universes where a quantum computer fails, then condition on remaining alive. What’s the class of problems you could then solve in polynomial time? A. 2005: It’s exactly the classical complexity class PP (Probabilistic Polynomial-Time), which is believed to be strictly larger than NP

  23. Second Law of Thermodynamics Proposed Counterexamples

  24. No Superluminal Signalling Proposed Counterexamples

  25. ? Intractability of NP-complete problems Proposed Counterexamples

  26. Concluding Remark I know this talk seemed pessimistic… But I’m an optimist

More Related