Verification of quantum computation
|
|
- Garey McDowell
- 5 years ago
- Views:
Transcription
1 Verification of quantum computation THOMAS VIDICK, CALIFORNIA INSTITUTE OF TECHNOLOGY Presentation based on the paper: Classical verification of quantum computation by U. Mahadev (IEEE symp. on Foundations of Comp. Science, 2018)
2 Part I: Statement of result
3 Turing machines Computation model: the Turing Machine (TM) Input tape, work tape, output tape Input x 0,1 is on input tape Executes elementary steps using work tape as memory Eventually writes halting symbol on output tape The output of the TM is the contents of the output tape A TM is polynomial-time if there is a polynomial P Z[X] such that for any input x, M halts in at most P(bit length(x)) steps A randomized TM has access to a randomness tape initialized with random bits An interactive TM has access to communication tapes
4 Languages A (promise) language is L = (L yes, L no ) 0,1 PRIMES: L yes = { binary representation of prime integers } L no = { binary representation of non-prime integers } 3COL: L yes = { binary representation of 3-colorable graph G} L no = { binary representation of not 3 colorable graph G } QCIRCUIT: L yes = { C: quantum circuit, returns 1 w.p. 2/3} L no = { C: quantum circuit, returns 1 w.p. 1/3} ZEROSUM: L yes = { (P, q) s.t. P multilinear polynomial, σ x P x = 0 mod q } L no = { (P, q) s.t. P multilinear polynomial, σ x P x 0 mod q }
5 Verification Given L = (L yes, L no ) and x L y L n, decide which? P: languages that can be decided by a poly-time TM PRIMES is in P. 3COL? NP: languages with efficiently verifiable proofs: L NP if there is a poly-time TM V such that for any x: If x L yes, there is a proof π s.t. V accepts π w.h.p. prover proof If x L no, for any π, V rejects π w.h.p. 3COL: proof is valid coloring ZEROSUM? verifier
6 Verification Given L = (L yes, L no ) and x L y L n, decide which? P: languages that can be decided by a poly-time TM PRIMES is in P NP: languages with efficiently verifiable proofs 3COL is in NP IP: languages with efficiently verifiable interactive proofs: L IP if there is a poly-time randomized interactive TM V and a (unbounded) TM P such that for any x prover proof If x L yes, V accepts P w.h.p. If x L no, for any P, V rejects P w.h.p. ZEROSUM is in IP verifier
7 QCIRCUIT L yes = { C: quantum circuit, returns 1 w.p. 2/3} L no = { C: quantum circuit, returns 1 w.p. 1/3} 0 b 0 0 (C 2 ) n has basis {e b = e b1 e bn, b 0,1 n } C = U T U 1 U (C 2 ) n Pr(C returns 1 ) = Π 1 C(e 0 e 0 ) 2 QCIRCUIT is strongly believed not to lie in P or in NP QCIRCUIT is in IP by reduction to ZEROSUM (Feynman path integral) Prover has to compute unphysical exponential sums Can quantum mechanics prove itself?
8
9
10
11
12 Testing quantum mechanics in the high-complexity regime Google Intel IONQ Tangle Bristlecone IBM 160 IBM Lake qubits Q5(49Q) Q16 (72Q) Exponential state space + uncertainty principle prevent direct simulation or even benchmarking Quantum mechanics untested at large scales What if there is a limit to the exponential scaling of quantum devices?
13 Main Result [Mahadev 18] Theorem (Mahadev 2018) There is a classical randomized polynomial-time verifier V and a quantum polynomial-time prover P such that, given as input a quantum circuit C, If Pr C returns "1" 2/3, then Pr V accepts P 1 If Pr C returns "1" 1/3, then for any P, Pr V accepts P 0 *** Under the LWE assumption ***
14 The LWE assumption [Regev 05] Learning with Errors (LWE) : noisy linear equations are hard! Let n and q n 2 be integer, and s 0,1 n. Given polynomially many samples a i, a i s + e i mod q such that a i U Z q n, e i U { q,, 0,, q } it is hard to recover s LWE is leading candidate for post-quantum cryptography standard (NIST) Believed hard even for quantum computers A quantum device that defeats Mahadev s protocol can be used to break LWE
15 Part II Proof ideas
16 Main Result [Mahadev 18] Theorem (Mahadev 2018) There is a classical randomized polynomial-time verifier V and a quantum polynomial-time prover P such that, given as input a quantum circuit C, If Pr C returns "1" 2/3, then Pr V accepts P 1 If Pr C returns "1" 1/3, then for any P, Pr V accepts P 0 *** Under the LWE assumption ***
17 Verifying classical circuits x 0,1 x 0,2 x 0,3 x 0,4 x 1,1 x 1,2 x 1,3 x 1,4 x 2,1 x 2,2 x 2,3 x 2,4 x 3,1 x 3,2 x 3,3 x 3,4 x 4,1 x 4,2 x 4,3 x 4,4 b = 1? x 0,1 = x 0,2 = x 0,3 = x 0,4 = 0 x 1,1 = 1 x 0,1, x 1,2 = x 0,2, x 2,3 = x 1,3 x 1,4, x 4,1 = 1 Verifying computation of C reduces to verifying existence of solution to system of local equations
18 Qubits e 1 ψ = α 0 e 0 + α 1 e 1 C 2 In general, the state of n qubits is represented by a unit vector ψ = α b e b1 e bn C 2 C 2 = C 2n b 0,1 n Dimension of state space grows exponentially with number of qubits Quantum circuit is unitary C = U T U 2 U 1 on C 2n Each U i acts as identity on all but constant number of qubits Pr C returns 1 = Π 1 C(e 0 e 0 ) 2, where Π 1 : projection on {αe 1 v} e 0
19 Hamiltonians A n-qubit Hamiltonian is a Hermitian H of norm H 1 acting on C 2 C 2 Z = and X = are 1-qubit Hamiltonians The energy of ψ with respect to H is ψ Hψ Toy example: H = 1 2 (X + Z) = λ min H = 2 2 ψ = α 0 e 0 + α 1 e 1 To evaluate the energy of ψ with respect to H: 1) Select W {X, Z} at random 2) Measure ψ in eigenbasis of W to obtain w 1,1 s.t. E w = ψ Wψ Repeat multiple times to get x 1, x k, z 1,, z k. Return 1 2 (1 σx k k + 1 σz k k)
20 Circuit-to-Hamiltonian [Kitaev 99] 0 b 0 0 H = σ i h i acting on C 2n Theorem (Kitaev): There is a δ > 1/ C 3 and an efficient mapping circuit C Hamiltonian H such that Pr(C returns "1") 2/3 λ min H 0 Pr(C returns "1") 1/3 λ min H δ Verifying computation of C reduces to verifying existence of small eigenvalues of H
21 A prototype 0 b 0 0 Select W {X, Z} w Measure W w 2 Measure W Repeat multiple times to get w n x 1, Measure x k, z 1, W, z k. H = 1 (X + Z) 2 qubit 1 qubit 2 qubit n Prepare ψ s.t. ψ Hψ = λ min (H) Send qubits of ψ one at a time Accept if 1 2 (1 k σx k + 1 k σz k) is δ 2
22 A prototype 0 b 0 0 H = 1 (X + Z) 2 Select W {X, Z} Repeat multiple times to get x 1, x k, z 1,, z k. W? w Prepare ψ s.t. ψ Hψ = λ min (H) Measure ψ in eigenbasis of W to obtain w { 1,1} Accept if 1 2 (1 k σx k + 1 k σz k) is δ 2 Prover can pretend λ min H = 1, violating uncertainty principle!
23 Claw-free functions f 0, f 1 : 0,1 n 0,1 n a claw-free pair of functions: r 0 f 1 Both f 0 and f 1 are bijections f 0 c For every c in the range, there is a unique claw: a pair (r 0,r 1 ) such that f 0 r 0 = f 1 r 1 = c r 1 Claws are hard to find: no efficient procedure returns (r 0, r 1, c) LWE assumption: Let n and q n 2 be integer, and s 0,1 n. Given samples a i, a i s + e i mod q such that a i U Z n q, e i U { q,, 0,, q } it is hard to recover s Public information: LWE samples a i, y i = a i s + e i Function evaluation: f b x i = a i x + e i + b y i mod q
24 Committing to a bit (f 0, f 1 ): 0,1 n 0,1 n a claw-free pair c = f b (r) (b, r) b {0,1} r R 0,1 n Check: f b r = c Hiding: c reveals no information about b (every c has exactly two preimages) Binding: Given c, computationally bounded device can reveal at most one b b = 0 b = 1 is easy, but given any fixed c, 0, r 0 (1, r 1 ) is hard
25 Committing to a qubit c = com(ψ) Compute w 1,1 s.t. E w = ψ Wψ Commit by encoding information in unknown two-dimensional space e 0 e r0, e 1 e r1 Classical outcome c commits quantum device to operate in that space W? d W = Meas W (ψ) e 1 ψ = α 0 e 0 + α 1 e 1 ψ c = α 0 e 0 e r0 + α 1 e 1 e r1 Measure all qubits in W eigenbasis ψ e 0 Can obtain measurement outcomes distributed as measurements in X or Z eigenbasis directly on ψ c Binding condition: must exist a single quantum state underlying both W
26 Commit & Reveal protocol [Mahadev 18] 0 0 b H = 1 (X + Z) 2 Prepare ψ = Σ α b e b s.t. 0 ψ Hψ = λ min (H) c = com(ψ) e 1 ψ Select W {X, Z} W? e 0 Compute outcome w from d w Repeat multiple times to get x 1, x k, z 1,, z k. d W = Meas W (ψ) Measure all qubits of ψ c in W eigenbasis Accept if 1 2 (1 k σx k + 1 k σz k) is δ 2
27 Commit & Reveal protocol [Mahadev 18] Theorem (Mahadev 2018) There is a classical randomized polynomial-time verifier V and a quantum polynomial-time prover P such that, given as input a quantum circuit C, If Pr C returns "1" 2/3, then Pr V accepts P 1 If Pr C returns "1" 1/3, then for any P, Pr V accepts P 0 Protocol can be implemented using small quantum computer Overhead due to crypto ~200 qubits For any behavior of the device, either the verifier rejects, or the device breaks the LWE assumption, or there exists a state ψ that underlies the verifier s energy estimation procedure, for all choices of measurement
28 Open: information-theoretic security IBM quantum experience (17 qubit) Can we remove the post-quantum crypto assumption? IP protocol requires device to perform unphysical computations Can a quantum computer prove the validity of its computation to a classical verifier?
29 Thank you Presentation based on the paper: Classical verification of quantum computation by U. Mahadev (IEEE conf. on Foundations of Comp. Science, 2018)
30 Interactive proofs for quantum computations Feynman path integral: Pr(C returns "1") = σ x:x1 =1 e x Ce 0 2 is (square of) summation of amplitude over exponentially many paths S = Σ P(x 1,, x T ) z T p 0 = P( z 1,, z T ) Any language that can be decided on a quantum computer can be classically verified. by querying an exponentially powerful prover!
31 Hamiltonians A n-qubit Hamiltonian is a Hermitian H of norm H 1 acting on C 2 C 2 Z = and X = are 1-qubit Hamiltonians The energy of ψ with respect to H is ψ Hψ ψ = α 0 e 0 + α 1 e 1 ψ Zψ = α 0 2 α 1 2 ψ Xψ = α 0 2 α 1 2 Estimate energy wrt Z: measure Estimate energy wrt X: Hadamard + measure X More generally, i : I 2 X I 2 I 2 H = σ ij α ij 2 (X ix j + Z i Z j ) is an n qubit Hamiltonian (provided Σ ij α ij 1)
32 Measurements e 1 e 0 Measurement rule: for b {0,1}, Pr b ψ = e b ψ 2 = α b 2 e 1 ψ = α 0 e 0 + α 1 e 1 C 2 Fourier transform: e 0 H: e 0 e 0, e 1 e 1 Generally: ψ = Measure i-th qubit: α x (e x1 e xn ) x 0,1 n H n α t = 2 n/2 α t (e t1 e tn ) t 0,1 n x 1 x t α x Pr b ψ, i = α x 2 Pr b ψ, i = α t 2 x:x i =b t:t i =b
33 Interactive proof for ZEROSUM Input is multilinear polynomial P F q [X 1,, X T ]. Goal: Σ x Fq T P x = 0? S = Σ P(x 1,, x T ) Σ z p T z = S? z T R F q Σ z p T 1 z = p T (z T )? z T 1 R F q p T (z) = Σ P(x 1,, x T 1, z) z T p T 1 (z) = Σ P(x 1,, z, z T ) z T 1 p 0 = P z 1,, z T? p 0 = P( z 1,, z T ) This protocol shows ZEROSUM IP
34 An example 0 H Z H b = 1 description of circuit C I got b = 1 Oh? Is this right?
Classical Verification of Quantum Computations
Classical Verification of Quantum Computations Urmila Mahadev UC Berkeley September 12, 2018 Classical versus Quantum Computers Can a classical computer verify a quantum computation? Classical output (decision
More informationVerification of quantum computation
Verification of quantum computation THOMAS VIDICK CALIFORNIA INSTITUTE OF TECHNOLOGY Slides: http://users.cms.caltech.edu/~vidick/verification.{ppsx,pdf} 1. Problem formulation 2. Overview of existing
More informationDoubly Efficient Interactive Proofs. Ron Rothblum
Doubly Efficient Interactive Proofs Ron Rothblum Outsourcing Computation Weak client outsources computation to the cloud. x y = f(x) Outsourcing Computation We do not want to blindly trust the cloud. x
More informationLecture 20: conp and Friends, Oracles in Complexity Theory
6.045 Lecture 20: conp and Friends, Oracles in Complexity Theory 1 Definition: conp = { L L NP } What does a conp computation look like? In NP algorithms, we can use a guess instruction in pseudocode:
More informationVERIFYING QUANTUM COMPUTATIONS AT SCALE: A CRYPTOGRAPHIC LEASH ON QUANTUM DEVICES
VERIFYING QUANTUM COMPUTATIONS AT SCALE: A CRYPTOGRAPHIC LEASH ON QUANTUM DEVICES THOMAS VIDICK Abstract. Rapid technological advances point to a near future where engineered devices based on the laws
More informationShor s Algorithm. Polynomial-time Prime Factorization with Quantum Computing. Sourabh Kulkarni October 13th, 2017
Shor s Algorithm Polynomial-time Prime Factorization with Quantum Computing Sourabh Kulkarni October 13th, 2017 Content Church Thesis Prime Numbers and Cryptography Overview of Shor s Algorithm Implementation
More informationChallenges in Quantum Information Science. Umesh V. Vazirani U. C. Berkeley
Challenges in Quantum Information Science Umesh V. Vazirani U. C. Berkeley 1 st quantum revolution - Understanding physical world: periodic table, chemical reactions electronic wavefunctions underlying
More informationLecture 15 - Zero Knowledge Proofs
Lecture 15 - Zero Knowledge Proofs Boaz Barak November 21, 2007 Zero knowledge for 3-coloring. We gave a ZK proof for the language QR of (x, n) such that x QR n. We ll now give a ZK proof (due to Goldreich,
More informationQuantum Computing Lecture 8. Quantum Automata and Complexity
Quantum Computing Lecture 8 Quantum Automata and Complexity Maris Ozols Computational models and complexity Shor s algorithm solves, in polynomial time, a problem for which no classical polynomial time
More informationLecture Notes 20: Zero-Knowledge Proofs
CS 127/CSCI E-127: Introduction to Cryptography Prof. Salil Vadhan Fall 2013 Lecture Notes 20: Zero-Knowledge Proofs Reading. Katz-Lindell Ÿ14.6.0-14.6.4,14.7 1 Interactive Proofs Motivation: how can parties
More informationLecture 2: From Classical to Quantum Model of Computation
CS 880: Quantum Information Processing 9/7/10 Lecture : From Classical to Quantum Model of Computation Instructor: Dieter van Melkebeek Scribe: Tyson Williams Last class we introduced two models for deterministic
More informationCS154, Lecture 17: conp, Oracles again, Space Complexity
CS154, Lecture 17: conp, Oracles again, Space Complexity Definition: conp = { L L NP } What does a conp computation look like? In NP algorithms, we can use a guess instruction in pseudocode: Guess string
More informationLecture 19: Finish NP-Completeness, conp and Friends
6.045 Lecture 19: Finish NP-Completeness, conp and Friends 1 Polynomial Time Reducibility f : Σ* Σ* is a polynomial time computable function if there is a poly-time Turing machine M that on every input
More informationClassical Verification of Quantum Computations
2018 IEEE 59th Annual Symposium on Foundations of Computer Science Classical Verification of Quantum Computations Urmila Mahadev Department of Computer Science, UC Berkeley mahadev@berkeley.edu Abstract
More informationLecture 1: Introduction to Quantum Computing
Lecture : Introduction to Quantum Computing Rajat Mittal IIT Kanpur What is quantum computing? This course is about the theory of quantum computation, i.e., to do computation using quantum systems. These
More informationCMPT307: Complexity Classes: P and N P Week 13-1
CMPT307: Complexity Classes: P and N P Week 13-1 Xian Qiu Simon Fraser University xianq@sfu.ca Strings and Languages an alphabet Σ is a finite set of symbols {0, 1}, {T, F}, {a, b,..., z}, N a string x
More informationThe Class NP. NP is the problems that can be solved in polynomial time by a nondeterministic machine.
The Class NP NP is the problems that can be solved in polynomial time by a nondeterministic machine. NP The time taken by nondeterministic TM is the length of the longest branch. The collection of all
More informationQuantum Supremacy and its Applications
Quantum Supremacy and its Applications HELLO HILBERT SPACE Scott Aaronson (University of Texas at Austin) USC, October 11, 2018 Based on joint work with Lijie Chen (CCC 2017, arxiv:1612.05903) and on forthcoming
More informationQuantum algorithms (CO 781, Winter 2008) Prof. Andrew Childs, University of Waterloo LECTURE 1: Quantum circuits and the abelian QFT
Quantum algorithms (CO 78, Winter 008) Prof. Andrew Childs, University of Waterloo LECTURE : Quantum circuits and the abelian QFT This is a course on quantum algorithms. It is intended for graduate students
More informationCS151 Complexity Theory. Lecture 13 May 15, 2017
CS151 Complexity Theory Lecture 13 May 15, 2017 Relationship to other classes To compare to classes of decision problems, usually consider P #P which is a decision class easy: NP, conp P #P easy: P #P
More informationQ = Set of states, IE661: Scheduling Theory (Fall 2003) Primer to Complexity Theory Satyaki Ghosh Dastidar
IE661: Scheduling Theory (Fall 2003) Primer to Complexity Theory Satyaki Ghosh Dastidar Turing Machine A Turing machine is an abstract representation of a computing device. It consists of a read/write
More informationconp, Oracles, Space Complexity
conp, Oracles, Space Complexity 1 What s next? A few possibilities CS161 Design and Analysis of Algorithms CS254 Complexity Theory (next year) CS354 Topics in Circuit Complexity For your favorite course
More informationCS151 Complexity Theory. Lecture 1 April 3, 2017
CS151 Complexity Theory Lecture 1 April 3, 2017 Complexity Theory Classify problems according to the computational resources required running time storage space parallelism randomness rounds of interaction,
More informationAdvanced Cryptography Quantum Algorithms Christophe Petit
The threat of quantum computers Advanced Cryptography Quantum Algorithms Christophe Petit University of Oxford Christophe Petit -Advanced Cryptography 1 Christophe Petit -Advanced Cryptography 2 The threat
More informationTheory of Computation Chapter 12: Cryptography
Theory of Computation Chapter 12: Cryptography Guan-Shieng Huang Dec. 20, 2006 0-0 Introduction Alice wants to communicate with Bob secretely. x Alice Bob John Alice y=e(e,x) y Bob y??? John Assumption
More informationComplexity Theory VU , SS The Polynomial Hierarchy. Reinhard Pichler
Complexity Theory Complexity Theory VU 181.142, SS 2018 6. The Polynomial Hierarchy Reinhard Pichler Institut für Informationssysteme Arbeitsbereich DBAI Technische Universität Wien 15 May, 2018 Reinhard
More informationOutline. Complexity Theory EXACT TSP. The Class DP. Definition. Problem EXACT TSP. Complexity of EXACT TSP. Proposition VU 181.
Complexity Theory Complexity Theory Outline Complexity Theory VU 181.142, SS 2018 6. The Polynomial Hierarchy Reinhard Pichler Institut für Informationssysteme Arbeitsbereich DBAI Technische Universität
More informationZero-Knowledge Against Quantum Attacks
Zero-Knowledge Against Quantum Attacks John Watrous Department of Computer Science University of Calgary January 16, 2006 John Watrous (University of Calgary) Zero-Knowledge Against Quantum Attacks QIP
More informationTheory of Computation Time Complexity
Theory of Computation Time Complexity Bow-Yaw Wang Academia Sinica Spring 2012 Bow-Yaw Wang (Academia Sinica) Time Complexity Spring 2012 1 / 59 Time for Deciding a Language Let us consider A = {0 n 1
More informationDefinition: conp = { L L NP } What does a conp computation look like?
Space Complexity 28 Definition: conp = { L L NP } What does a conp computation look like? In NP algorithms, we can use a guess instruction in pseudocode: Guess string y of x k length and the machine accepts
More informationCS294: Pseudorandomness and Combinatorial Constructions September 13, Notes for Lecture 5
UC Berkeley Handout N5 CS94: Pseudorandomness and Combinatorial Constructions September 3, 005 Professor Luca Trevisan Scribe: Gatis Midrijanis Notes for Lecture 5 In the few lectures we are going to look
More informationThe Cook-Levin Theorem
An Exposition Sandip Sinha Anamay Chaturvedi Indian Institute of Science, Bangalore 14th November 14 Introduction Deciding a Language Let L {0, 1} be a language, and let M be a Turing machine. We say M
More informationIntroduction to Quantum Algorithms Part I: Quantum Gates and Simon s Algorithm
Part I: Quantum Gates and Simon s Algorithm Martin Rötteler NEC Laboratories America, Inc. 4 Independence Way, Suite 00 Princeton, NJ 08540, U.S.A. International Summer School on Quantum Information, Max-Planck-Institut
More informationLattice-Based Non-Interactive Arugment Systems
Lattice-Based Non-Interactive Arugment Systems David Wu Stanford University Based on joint works with Dan Boneh, Yuval Ishai, Sam Kim, and Amit Sahai Soundness: x L, P Pr P, V (x) = accept = 0 No prover
More informationCS5371 Theory of Computation. Lecture 18: Complexity III (Two Classes: P and NP)
CS5371 Theory of Computation Lecture 18: Complexity III (Two Classes: P and NP) Objectives Define what is the class P Examples of languages in P Define what is the class NP Examples of languages in NP
More informationGraph Non-Isomorphism Has a Succinct Quantum Certificate
Graph Non-Isomorphism Has a Succinct Quantum Certificate Tatsuaki Okamoto Keisuke Tanaka Summary This paper presents the first quantum computational characterization of the Graph Non-Isomorphism problem
More informationIntroduction to Quantum Computing
Introduction to Quantum Computing Petros Wallden Lecture 7: Complexity & Algorithms I 13th October 016 School of Informatics, University of Edinburgh Complexity - Computational Complexity: Classification
More informationGreat Theoretical Ideas in Computer Science
15-251 Great Theoretical Ideas in Computer Science Lecture 28: A Computational Lens on Proofs December 6th, 2016 Evolution of proof First there was GORM GORM = Good Old Regular Mathematics Pythagoras s
More information)j > Riley Tipton Perry University of New South Wales, Australia. World Scientific CHENNAI
Riley Tipton Perry University of New South Wales, Australia )j > World Scientific NEW JERSEY LONDON. SINGAPORE BEIJING SHANSHAI HONG K0N6 TAIPEI» CHENNAI Contents Acknowledgments xi 1. Introduction 1 1.1
More informationPh 219b/CS 219b. Exercises Due: Wednesday 4 December 2013
1 Ph 219b/CS 219b Exercises Due: Wednesday 4 December 2013 4.1 The peak in the Fourier transform In the period finding algorithm we prepared the periodic state A 1 1 x 0 + jr, (1) A j=0 where A is the
More information2 A Fourier Transform for Bivariate Functions
Stanford University CS59Q: Quantum Computing Handout 0 Luca Trevisan October 5, 0 Lecture 0 In which we present a polynomial time quantum algorithm for the discrete logarithm problem. The Discrete Log
More informationThe Quantum and Classical Complexity of Translationally Invariant Tiling and Hamiltonian Problems
The Quantum and Classical Complexity of Translationally Invariant Tiling and Hamiltonian Problems Daniel Gottesman Perimeter Institute for Theoretical Physics Waterloo, Ontario, Canada dgottesman@perimeterinstitute.ca
More informationIntroduction to Quantum Computing
Introduction to Quantum Computing The lecture notes were prepared according to Peter Shor s papers Quantum Computing and Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a
More informationA Complete Characterization of Unitary Quantum Space
A Complete Characterization of Unitary Quantum Space Bill Fefferman (QuICS, University of Maryland/NIST) Joint with Cedric Lin (QuICS) Based on arxiv:1604.01384 1. Basics Quantum space complexity Main
More informationCompute the Fourier transform on the first register to get x {0,1} n x 0.
CS 94 Recursive Fourier Sampling, Simon s Algorithm /5/009 Spring 009 Lecture 3 1 Review Recall that we can write any classical circuit x f(x) as a reversible circuit R f. We can view R f as a unitary
More informationLecture 3: Interactive Proofs and Zero-Knowledge
CS 355 Topics in Cryptography April 9, 2018 Lecture 3: Interactive Proofs and Zero-Knowledge Instructors: Henry Corrigan-Gibbs, Sam Kim, David J. Wu So far in the class, we have only covered basic cryptographic
More information1 Quantum Circuits. CS Quantum Complexity theory 1/31/07 Spring 2007 Lecture Class P - Polynomial Time
CS 94- Quantum Complexity theory 1/31/07 Spring 007 Lecture 5 1 Quantum Circuits A quantum circuit implements a unitary operator in a ilbert space, given as primitive a (usually finite) collection of gates
More informationNon-Interactive ZK:The Feige-Lapidot-Shamir protocol
Non-Interactive ZK: The Feige-Lapidot-Shamir protocol April 20, 2009 Remainders FLS protocol Definition (Interactive proof system) A pair of interactive machines (P, V ) is called an interactive proof
More informationQuantum Complexity Theory and Adiabatic Computation
Chapter 9 Quantum Complexity Theory and Adiabatic Computation 9.1 Defining Quantum Complexity We are familiar with complexity theory in classical computer science: how quickly can a computer (or Turing
More informationLecture 1: Introduction to Quantum Computing
Lecture 1: Introduction to Quantum Computing Rajat Mittal IIT Kanpur Whenever the word Quantum Computing is uttered in public, there are many reactions. The first one is of surprise, mostly pleasant, and
More informationComputational Complexity Theory
Computational Complexity Theory Marcus Hutter Canberra, ACT, 0200, Australia http://www.hutter1.net/ Assumed Background Preliminaries Turing Machine (TM) Deterministic Turing Machine (DTM) NonDeterministic
More informationThe quantum threat to cryptography
The quantum threat to cryptography Ashley Montanaro School of Mathematics, University of Bristol 20 October 2016 Quantum computers University of Bristol IBM UCSB / Google University of Oxford Experimental
More informationLecture 22: Quantum computational complexity
CPSC 519/619: Quantum Computation John Watrous, University of Calgary Lecture 22: Quantum computational complexity April 11, 2006 This will be the last lecture of the course I hope you have enjoyed the
More information. An introduction to Quantum Complexity. Peli Teloni
An introduction to Quantum Complexity Peli Teloni Advanced Topics on Algorithms and Complexity µπλ July 3, 2014 1 / 50 Outline 1 Motivation 2 Computational Model Quantum Circuits Quantum Turing Machine
More informationQMA(2) workshop Tutorial 1. Bill Fefferman (QuICS)
QMA(2) workshop Tutorial 1 Bill Fefferman (QuICS) Agenda I. Basics II. Known results III. Open questions/next tutorial overview I. Basics I.1 Classical Complexity Theory P Class of problems efficiently
More informationModels of Computation
Models of Computation Analysis of Algorithms Week 1, Lecture 2 Prepared by John Reif, Ph.D. Distinguished Professor of Computer Science Duke University Models of Computation (RAM) a) Random Access Machines
More information15.1 Proof of the Cook-Levin Theorem: SAT is NP-complete
CS125 Lecture 15 Fall 2016 15.1 Proof of the Cook-Levin Theorem: SAT is NP-complete Already know SAT NP, so only need to show SAT is NP-hard. Let L be any language in NP. Let M be a NTM that decides L
More informationComplete problems for classes in PH, The Polynomial-Time Hierarchy (PH) oracle is like a subroutine, or function in
Oracle Turing Machines Nondeterministic OTM defined in the same way (transition relation, rather than function) oracle is like a subroutine, or function in your favorite PL but each call counts as single
More informationIntroduction to Quantum Computing
Introduction to Quantum Computing Toni Bluher Math Research Group, NSA 2018 Women and Mathematics Program Disclaimer: The opinions expressed are those of the writer and not necessarily those of NSA/CSS,
More informationNP, polynomial-time mapping reductions, and NP-completeness
NP, polynomial-time mapping reductions, and NP-completeness In the previous lecture we discussed deterministic time complexity, along with the time-hierarchy theorem, and introduced two complexity classes:
More informationIntroduction to Interactive Proofs & The Sumcheck Protocol
CS294: Probabilistically Checkable and Interactive Proofs January 19, 2017 Introduction to Interactive Proofs & The Sumcheck Protocol Instructor: Alessandro Chiesa & Igor Shinkar Scribe: Pratyush Mishra
More information1500 AMD Opteron processor (2.2 GHz with 2 GB RAM)
NICT 2019 2019 2 7 1 RSA RSA 2 3 (1) exp $ 64/9 + *(1) (ln 0) 1/2 (ln ln 0) 3/2 (2) 2009 12 768 (232 ) 1500 AMD Opteron processor (2.2 GHz with 2 GB RAM) 4 (3) 18 2 (1) (2) (3) 5 CRYPTREC 1. 2. 3. 1024,
More informationQUANTUM ARTHUR MERLIN GAMES
comput. complex. 14 (2005), 122 152 1016-3328/05/020122 31 DOI 10.1007/s00037-005-0194-x c Birkhäuser Verlag, Basel 2005 computational complexity QUANTUM ARTHUR MERLIN GAMES Chris Marriott and John Watrous
More informationQUANTUM COMPUTING. Part II. Jean V. Bellissard. Georgia Institute of Technology & Institut Universitaire de France
QUANTUM COMPUTING Part II Jean V. Bellissard Georgia Institute of Technology & Institut Universitaire de France QUANTUM GATES: a reminder Quantum gates: 1-qubit gates x> U U x> U is unitary in M 2 ( C
More informationDiscrete Quantum Theories
Discrete Quantum Theories Andrew J. Hanson 1 Gerardo Ortiz 2 Amr Sabry 1 Yu-Tsung Tai 3 (1) School of Informatics and Computing (2) Department of Physics (3) Mathematics Department Indiana University July
More informationQuantum Technologies for Cryptography
University of Sydney 11 July 2018 Quantum Technologies for Cryptography Mario Berta (Department of Computing) marioberta.info Quantum Information Science Understanding quantum systems (e.g., single atoms
More informationCS154, Lecture 13: P vs NP
CS154, Lecture 13: P vs NP The EXTENDED Church-Turing Thesis Everyone s Intuitive Notion of Efficient Algorithms Polynomial-Time Turing Machines More generally: TM can simulate every reasonable model of
More informationFrom Secure MPC to Efficient Zero-Knowledge
From Secure MPC to Efficient Zero-Knowledge David Wu March, 2017 The Complexity Class NP NP the class of problems that are efficiently verifiable a language L is in NP if there exists a polynomial-time
More informationShort Course in Quantum Information Lecture 5
Short Course in Quantum Information Lecture 5 Quantum Algorithms Prof. Andrew Landahl University of New Mexico Course Info All materials downloadable @ website http://info.phys.unm.edu/~deutschgroup/deutschclasses.html
More informationIntroduction to Machine Learning
Introduction to Machine Learning 236756 Prof. Nir Ailon Lecture 4: Computational Complexity of Learning & Surrogate Losses Efficient PAC Learning Until now we were mostly worried about sample complexity
More informationarxiv: v1 [quant-ph] 11 Apr 2016
Zero-knowledge proof systems for QMA Anne Broadbent Zhengfeng Ji 2,3 Fang Song 4 John Watrous 5,6 arxiv:604.02804v [quant-ph] Apr 206 Department of Mathematics and Statistics University of Ottawa, Canada
More informationTime to learn about NP-completeness!
Time to learn about NP-completeness! Harvey Mudd College March 19, 2007 Languages A language is a set of strings Examples The language of strings of all zeros with odd length The language of strings with
More informationCSCI 1590 Intro to Computational Complexity
CSCI 1590 Intro to Computational Complexity Randomized Computation John E. Savage Brown University April 15, 2009 John E. Savage (Brown University) CSCI 1590 Intro to Computational Complexity April 15,
More informationLecture 26: Arthur-Merlin Games
CS 710: Complexity Theory 12/09/2011 Lecture 26: Arthur-Merlin Games Instructor: Dieter van Melkebeek Scribe: Chetan Rao and Aaron Gorenstein Last time we compared counting versus alternation and showed
More informationLecture 23: Introduction to Quantum Complexity Theory 1 REVIEW: CLASSICAL COMPLEXITY THEORY
Quantum Computation (CMU 18-859BB, Fall 2015) Lecture 23: Introduction to Quantum Complexity Theory November 31, 2015 Lecturer: Ryan O Donnell Scribe: Will Griffin 1 REVIEW: CLASSICAL COMPLEXITY THEORY
More informationInput Decidable Language -- Program Halts on all Input Encoding of Input -- Natural Numbers Encoded in Binary or Decimal, Not Unary
Complexity Analysis Complexity Theory Input Decidable Language -- Program Halts on all Input Encoding of Input -- Natural Numbers Encoded in Binary or Decimal, Not Unary Output TRUE or FALSE Time and Space
More informationComputational and Statistical Learning Theory
Computational and Statistical Learning Theory TTIC 31120 Prof. Nati Srebro Lecture 6: Computational Complexity of Learning Proper vs Improper Learning Efficient PAC Learning Definition: A family H n of
More informationIntroduction to Quantum Computing
Introduction to Quantum Computing Part I Emma Strubell http://cs.umaine.edu/~ema/quantum_tutorial.pdf April 12, 2011 Overview Outline What is quantum computing? Background Caveats Fundamental differences
More informationZero-Knowledge Proofs and Protocols
Seminar: Algorithms of IT Security and Cryptography Zero-Knowledge Proofs and Protocols Nikolay Vyahhi June 8, 2005 Abstract A proof is whatever convinces me. Shimon Even, 1978. Zero-knowledge proof is
More informationComputability and Complexity
Computability and Complexity Lecture 10 More examples of problems in P Closure properties of the class P The class NP given by Jiri Srba Lecture 10 Computability and Complexity 1/12 Example: Relatively
More informationQuantum NP - Cont. Classical and Quantum Computation A.Yu Kitaev, A. Shen, M. N. Vyalyi 2002
Quantum NP - Cont. Classical and Quantum Computation A.Yu Kitaev, A. Shen, M. N. Vyalyi 2002 1 QMA - the quantum analog to MA (and NP). Definition 1 QMA. The complexity class QMA is the class of all languages
More informationAn Introduction to Quantum Information and Applications
An Introduction to Quantum Information and Applications Iordanis Kerenidis CNRS LIAFA-Univ Paris-Diderot Quantum information and computation Quantum information and computation How is information encoded
More informationCS154, Lecture 13: P vs NP
CS154, Lecture 13: P vs NP The EXTENDED Church-Turing Thesis Everyone s Intuitive Notion of Efficient Algorithms Polynomial-Time Turing Machines More generally: TM can simulate every reasonable model of
More informationQuantum Supremacy and its Applications
Quantum Supremacy and its Applications HELLO HILBERT SPACE Scott Aaronson (University of Texas, Austin) Simons Institute, Berkeley, June 12, 2018 Based on joint work with Lijie Chen (CCC 2017, arxiv: 1612.05903)
More informationarxiv:cs/ v1 [cs.cc] 15 Jun 2005
Quantum Arthur-Merlin Games arxiv:cs/0506068v1 [cs.cc] 15 Jun 2005 Chris Marriott John Watrous Department of Computer Science University of Calgary 2500 University Drive NW Calgary, Alberta, Canada T2N
More informationInteractive Proofs. Merlin-Arthur games (MA) [Babai] Decision problem: D;
Interactive Proofs n x: read-only input finite σ: random bits control Π: Proof work tape Merlin-Arthur games (MA) [Babai] Decision problem: D; input string: x Merlin Prover chooses the polynomial-length
More informationSecurity Implications of Quantum Technologies
Security Implications of Quantum Technologies Jim Alves-Foss Center for Secure and Dependable Software Department of Computer Science University of Idaho Moscow, ID 83844-1010 email: jimaf@cs.uidaho.edu
More informationNotes for Lecture 27
U.C. Berkeley CS276: Cryptography Handout N27 Luca Trevisan April 30, 2009 Notes for Lecture 27 Scribed by Madhur Tulsiani, posted May 16, 2009 Summary In this lecture we begin the construction and analysis
More informationSimulation of quantum computers with probabilistic models
Simulation of quantum computers with probabilistic models Vlad Gheorghiu Department of Physics Carnegie Mellon University Pittsburgh, PA 15213, U.S.A. April 6, 2010 Vlad Gheorghiu (CMU) Simulation of quantum
More informationLimits of Feasibility. Example. Complexity Relationships among Models. 1. Complexity Relationships among Models
Limits of Feasibility Wolfgang Schreiner Wolfgang.Schreiner@risc.jku.at Research Institute for Symbolic Computation (RISC) Johannes Kepler University, Linz, Austria http://www.risc.jku.at 1. Complexity
More informationLecture Notes 17. Randomness: The verifier can toss coins and is allowed to err with some (small) probability if it is unlucky in its coin tosses.
CS 221: Computational Complexity Prof. Salil Vadhan Lecture Notes 17 March 31, 2010 Scribe: Jonathan Ullman 1 Interactive Proofs ecall the definition of NP: L NP there exists a polynomial-time V and polynomial
More informationLecture 24: Randomized Complexity, Course Summary
6.045 Lecture 24: Randomized Complexity, Course Summary 1 1/4 1/16 1/4 1/4 1/32 1/16 1/32 Probabilistic TMs 1/16 A probabilistic TM M is a nondeterministic TM where: Each nondeterministic step is called
More informationOn the query complexity of counterfeiting quantum money
On the query complexity of counterfeiting quantum money Andrew Lutomirski December 14, 2010 Abstract Quantum money is a quantum cryptographic protocol in which a mint can produce a state (called a quantum
More informationCSCI3390-Lecture 14: The class NP
CSCI3390-Lecture 14: The class NP 1 Problems and Witnesses All of the decision problems described below have the form: Is there a solution to X? where X is the given problem instance. If the instance is
More informationLecture 17: Cook-Levin Theorem, NP-Complete Problems
6.045 Lecture 17: Cook-Levin Theorem, NP-Complete Problems 1 Is SAT solvable in O(n) time on a multitape TM? Logic circuits of 6n gates for SAT? If yes, then not only is P=NP, but there would be a dream
More informationChapter 10. Quantum algorithms
Chapter 10. Quantum algorithms Complex numbers: a quick review Definition: C = { a + b i : a, b R } where i = 1. Polar form of z = a + b i is z = re iθ, where r = z = a 2 + b 2 and θ = tan 1 y x Alternatively,
More informationPh 219b/CS 219b. Exercises Due: Wednesday 11 February 2009
1 Ph 219b/CS 219b Exercises Due: Wednesday 11 February 2009 5.1 The peak in the Fourier transform In the period finding algorithm we prepared the periodic state A 1 1 x 0 + jr, (1) A j=0 where A is the
More informationIntroduction to Quantum Computing
Introduction to Quantum Computing Part II Emma Strubell http://cs.umaine.edu/~ema/quantum_tutorial.pdf April 13, 2011 Overview Outline Grover s Algorithm Quantum search A worked example Simon s algorithm
More informationSimon s algorithm (1994)
Simon s algorithm (1994) Given a classical circuit C f (of polynomial size, in n) for an f : {0, 1} n {0, 1} n, such that for a certain s {0, 1} n \{0 n }: x, y {0, 1} n (x y) : f (x) = f (y) x y = s with
More informationCS151 Complexity Theory. Lecture 14 May 17, 2017
CS151 Complexity Theory Lecture 14 May 17, 2017 IP = PSPACE Theorem: (Shamir) IP = PSPACE Note: IP PSPACE enumerate all possible interactions, explicitly calculate acceptance probability interaction extremely
More information