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## PowerPoint Slideshow about 'np-complete problems and physical reality' - bernad

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Computer Science 101

Problem: “Given a graph, is it connected?”

Each particular graph 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

NP: Nondeterministic Polynomial Time

Does

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have a prime factor ending in 7?

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)?

Hamilton cycleSteiner treeGraph 3-coloringSatisfiabilityMaximum clique…

Matrix permanentHalting problem…

FactoringGraph isomorphismMinimum circuit size…

Graph connectivityPrimality testingMatrix determinantLinear programming…

NP-hard

NP-complete

NP

P

Does P=NP?

The (literally) $1,000,000 question

But what if P=NP, and the algorithm takes n10000 steps?

God will not be so cruel

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

Then why is it so hard to prove PNP?

Algorithms can be very clever

Gödel/Turing-style self-reference arguments don’t seem powerful enough

Combinatorial arguments face the “Razborov-Rudich barrier”

But maybe there’s some physical system that solves an NP-complete problem just by reaching its lowest energy state?

Dip two glass plates with pegs between them into soapy water

- Let the soap bubbles form a minimum Steiner tree connecting the pegs

Other Physical Systems

Spin glasses

Folding proteins

...

Well-known to admit “metastable” states

DNA computers: Just highly parallel ordinary computers

Analog Computing

Schönhage 1979: If we could compute

x+y, x-y, xy, x/y, x

for any real x,y in a single step, then we could solve NP-complete and even harder problems in polynomial time

Problem: The Planck scale!

Bennett, Bernstein, Brassard, Vazirani 1997: “Quantum magic” won’t be enough

~2n/2 queries are needed to search a list of size 2n for a single marked item

Quantum ComputingShor 1994: Quantum computers can factor in polynomial time

But can they solve NP-complete problems?

A. 2004: True even with “quantum advice”

Quantum Adiabatic Algorithm (Farhi et al. 2000)

Hi

Hf

Hamiltonian with easily-prepared ground state

Ground state encodes solution to NP-complete problem

Problem (van Dam, Mosca, Vazirani 2001): Eigenvalue gap can be exponentially small

Topological Quantum Field Theories (TQFT’s)

Freedman, Kitaev, Wang 2000: Equivalent to ordinary quantum computers

Nonlinear Quantum Mechanics (Weinberg 1989)

Abrams & Lloyd 1998: Could use to solve NP-complete and even harder problems in polynomial time

1 solution to NP-complete problem

No solutions

Time Travel Computing(Bacon 2003)

SupposePr[x=1] = p,Pr[y=1] = q

Then consistency requires p=q

So Pr[xy=1]= p(1-q) + q(1-p)= 2p(1-p)

x

xy

Causalloop

Chronology-respecting bit

x

y

Hidden Variables

Valentini 2001: “Subquantum” algorithm (violating ||2) to distinguish |0 from

Problem: Valentini’s algorithm still requires exponentially-precise measurements.But we probably could solve Graph Isomorphism subquantumly

A. 2002: Sampling the history of a hidden variable is another way to solve Graph Isomorphism in polynomial time—but again, probably not NP-complete problems!

“Anthropic Computing”

Guess a solution to an NP-complete problem. If it’s wrong, kill yourself.

Doomsday alternative:If solution is right, destroy human race.If wrong, cause human race to survive into far future.

“Transhuman Computing”

- Upload yourself onto a computer
- Start the computer working on a 10,000-year calculation
- Program the computer to make 50 copies of you after it’s done, then tell those copies the answer

Proposed Counterexamples

Proposed Counterexamples

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