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By: Larisse D. Voufo On: November 28 th , 2006 lvoufo@cs.indiana.edu. Quantum Complexity Classes. http://www.quantiki.org/wiki/images/4/46/PhotonIdentityCartoon.gif. Introduction. 1982 (Trend toward miniaturization and microcircuitry) , Paul Benioff & Richard Feynman :
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By: Larisse D. Voufo On: November 28th, 2006 lvoufo@cs.indiana.edu Quantum Complexity Classes http://www.quantiki.org/wiki/images/4/46/PhotonIdentityCartoon.gif
Introduction • 1982 (Trend toward miniaturization and microcircuitry), Paul Benioff & Richard Feynman: Quantum Systems could perform computation. • 1985, David Deutch. Quantum Computer Turing Machine possibility of new Complexity of algorithms • Later On, Universality of Quantum Circuits Machine independent notion of quantum complexity.
Key quantum property for quantum complexity studies: Randomness of quantum measurement process Algorithm performed by a quantum computer is probabilistic. (== multiple runs, different results)
Probabilistic Computation vs. Quantum Computation. • Nondeterministic Computation (NC) = tree of configurations of NTM • Probabilistic Computation = NC where probabilities <--> edges and nodes. Rules of Classical Probability. • Quantum Computation = NC where amplitudes <--> edges and nodes. Rules of Quantum Probability.
From Classical Complexity classes… • P – “easy”: languages decided by polynomial-time TMs • NP: languages decided by polynomial-time NTMs. • Guess an answer, verify in polynomial time. Is answer YES? • NP-hard: Every hard problem can be polynomially reduced to a problem in this class. • NP-complete: NPC = NP-hard NP NP-hard P {} => P = NP
From Classical Complexity classes… • NPI: Problems in NP of intermediate difficulty • NPI = NP – P – NPC = NP – P – NP-hard • Co-NP: Like NP, but Answer is NO (counter-example based) NP Co-NP No proof for: P NP.
From Classical Complexity classes… • AWPP: languages decided by Almost-Wide Probabilistic Polynomial-timeNTMs • PP: languages decided by polynomial-time NTMs where the majority of paths gives the correct answer. • P#P: functions that count the number of accepting paths through an NP machine. P NP AWPP PP P#P.
From Classical Complexity classes… • IP: Problems solvable by an Interactive Proof System. • MA: languages decided by a bounded-error probabilistic Merlin-Arthur protocol. • BPP: Bounded-error Probabilistic Polynomial Time. “Problems that admit a probabilistic circuit family of polynomial size that always gives the right answer with prob > ½ + ”. • PSPACE: DPs that can be solved in polynomial-space, but may require exponential time.
… toQuantum Complexity Classes: • BQP: Bounded-error Quantum Polynomial Time. “DPs that can be solved, with high probability, by polynomial-size quantum circuits”. • EQP (QP): Exact version of BQP
… toQuantum Complexity Classes: P BPP BQP PSPACE • IP = PSPACE • NP MA • BPP MA IP • BQP P#P PSPACE • No firm proof for: BPP BQP (in general) • If P = PSPACE, then P = AWPP “relative to oracle” • NP = AWPP “relative to oracle” • NP PSPACE (checking if C(x(n), y(n)) = 1 for each y(m)) • NP BQP ?
… toQuantum Complexicity Classes: • BQNP ( = QMA) • QMA-complete • QIP • EQP BQP QMA QIP
Interactive Proof System: IP BPP ?, r, … Polynomial Number of Messages Proof (x L)
Merlin-Arthur Protocol: NP Deterministic Polynomial-time TM ?, r, … Constant Number of Messages
Merlin-Arthur Protocol: MA BPP ?, r, … Constant Number of Messages
Merlin-Arthur Protocol: QMA(C) • QMA-Completeness: ground state energy problem: (5-local hamiltonian). BQP ?, r, … Constant Number of Messages
Merlin-Arthur Protocol: QIP BQP Q- ?, r, … Polynomial Number of Messages Q- Proof (x L)
A model for quantum circuits: Facts: • Quantum gate: unitary transformation reversible gate. • Classical Reversible Computer = special case of Quantum Computer. • x(n) y(n) = f(x(n)) <==> U: |xi> |yi> • |00…0> Deterministic final measurement
3 Issues with this model: • Universality • Complete Model <==> There exists no transformation in U(2n) that we cannot reach. • Simulation of a Q-computer using another Q-computer • complexity classes do not depend on the details of the hardware. • Simulating a quantum computer on a classical computer: Better characterize the resources needed. • A Classical Computer can still simulate a Q-Computer, despite a polynomial limit on memory space available.
3 Issues with this model: 3. Accuracy == growth of error in measurement as the quantum circuit size increases. • NO Polynomial-size circuit family (hard problems) w/ gates of exponential accuracy. • An idealized T-gate q-circuit (acceptable accuracy): Error Prob / gate 1/T. • Quantum Algorithm w/ prob > ½ + (in the ideal case) Gates w/ accuracy T < O(). • BQP can really solve hard problems <==> linear improvement of the accuracy of the gates (computation size T).
More on Relationships between Complexity classes • P BPP BQP AWPP PP PSPACE. • Bernstein and Vazirani: BQP PSPACE • Adelman, Demarrais and Huang: BQP PP • Fortnow and Rogers: BQP AWPP
Other Complexity Classes Vary from one literature to another… • UP, QPSV, NPSV, UPSV, etc… Elham Kashefi’s PhD thesis (Imperial College London) • NQP, C=P, coC=P, etc… Tarsem S. Purewal Jr (University of Georgia)
Analyzing Quantum Algorithm Performances Over Classical Ones: • Non-exponential speedup: Eg: Grover’s Quantum Speed-up of the Search of an unsorted database. • “Relativized” Exponential Speed-up Oracles BPP BQP “relative to oracle”. Eg: Simon’s exponential quantum speedup for finding the period of 2 to 1 function. Deutch’s algorithm. • Exponential Speed-up for “apparently” hard problems Eg: Shor’s factoring algorithm.
References: • Tarsem S. Purewal Jr. “Revisiting a Limit on Efficient Quantum Computation”. ACM Southeastern Conference 2006, Melbourne, FL. March 10, 2006. Slides at http://www.cs.uga.edu/~purewal/slides/BQPinPPTalk.pdf • John Preskill. “Lecture Notes on Physics 229: Quantum Information and Computation”. Sept. 1998. California Institute of Technology. • Tarsem S. Purewal Jr. “Nondeterministic Quantum Query Complexity”. Combinatorics, Algorithms, and Theory Seminar (CATS), University of Georgia, Athens, GA. May 1, 2006. • Tarsem S. Purewal Jr. “5-local Hamiltonian is QMA-Complete”. Quantum Computing Journal Club, University of Georgia, Athens, GA. June 6, 2005. • Prof. Tony Hey. “Quantum Computing: an introduction”. Quantum Technology Center. http://www.qtc.ecs.soton.ac.uk/flecture.html • Artur Ekert, Patrick Hayden, Hitoshi Inamori. “Basic concepts in quantum computation”. converted to wiki format by Burgarth 22:37, 8 Jun 2005 (BST). http://www.quantiki.org/wiki/index.php/Basic_concepts_in_quantum_computation • Qbit.com. “Introduction to Quantum Theory”. http://www.quantiki.org/wiki/index.php/Introduction_to_Quantum_Theory • Elham Kashefi. “Complexity Analysis and Semantics for Quantum Computation”. November 26, 2003. http://web.comlab.ox.ac.uk/oucl/work/elham.kashefi/papers/phdelham.pdf • Tarsem S. Purewal Jr. http://www.cs.uga.edu/~purewal/vita.html • Lance Fortnow. “One Complexity Theorist's View of Quantum Computing”. http://people.cs.uchicago.edu/~fortnow/papers/quantview.pdf
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