Optimal Parallel Quantum Query Algorithms
We study the complexity of quantum query algorithms that make p queries in parallel in each timestep. This model is in part motivated by the fact that decoherence times of qubits are typically small, so it makes sense to parallelize quantum algorithms as much as possible. We show tight bounds for a...
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| Vydané v: | Algorithmica Ročník 79; číslo 2; s. 509 - 529 |
|---|---|
| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
New York
Springer US
01.10.2017
Springer Nature B.V Springer Verlag |
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| ISSN: | 0178-4617, 1432-0541 |
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| Abstract | We study the complexity of quantum query algorithms that make
p
queries in parallel in each timestep. This model is in part motivated by the fact that decoherence times of qubits are typically small, so it makes sense to parallelize quantum algorithms as much as possible. We show tight bounds for a number of problems, specifically
Θ
(
(
n
/
p
)
2
/
3
)
p
-parallel queries for element distinctness and
Θ
(
(
n
/
p
)
k
/
(
k
+
1
)
)
for
k
-sum. Our upper bounds are obtained by parallelized quantum walk algorithms, and our lower bounds are based on a relatively small modification of the adversary lower bound method, combined with recent results of Belovs et al. on learning graphs. We also prove some general bounds, in particular that quantum and classical
p
-parallel query complexity are polynomially related for all total functions
f
when
p
is small compared to
f
’s block sensitivity. |
|---|---|
| AbstractList | We study the complexity of quantum query algorithms that make
p
queries in parallel in each timestep. This model is in part motivated by the fact that decoherence times of qubits are typically small, so it makes sense to parallelize quantum algorithms as much as possible. We show tight bounds for a number of problems, specifically
Θ
(
(
n
/
p
)
2
/
3
)
p
-parallel queries for element distinctness and
Θ
(
(
n
/
p
)
k
/
(
k
+
1
)
)
for
k
-sum. Our upper bounds are obtained by parallelized quantum walk algorithms, and our lower bounds are based on a relatively small modification of the adversary lower bound method, combined with recent results of Belovs et al. on learning graphs. We also prove some general bounds, in particular that quantum and classical
p
-parallel query complexity are polynomially related for all total functions
f
when
p
is small compared to
f
’s block sensitivity. We define the Streaming Communication model that combines the main aspects of communication complexity and streaming. Input arrives as a stream, spread between several agents across a network. Each agent has a bounded memory, which can be updated upon receiving a new bit, or a message from another agent. We provide tight tradeoffs between the necessary resources, i.e., communication between agents and memory, for some of the canonical problems from communication complexity by proving a strong general lower bound technique. Second, we analyze the Approximate Matching problem and show that the complexity of this problem (i.e., the achievable approximation ratio) in the one-way variant of our model is strictly different both from the streaming complexity and the one-way communication complexity thereof. We study the complexity of quantum query algorithms that make p queries in parallel in each timestep. This model is in part motivated by the fact that decoherence times of qubits are typically small, so it makes sense to parallelize quantum algorithms as much as possible. We show tight bounds for a number of problems, specifically Θ ( ( n / p ) 2 / 3 ) p-parallel queries for element distinctness and Θ ( ( n / p ) k / ( k + 1 ) ) for k -sum. Our upper bounds are obtained by parallelized quantum walk algorithms, and our lower bounds are based on a relatively small modification of the adversary lower bound method, combined with recent results of Belovs et al. on learning graphs. We also prove some general bounds, in particular that quantum and classical p-parallel query complexity are polynomially related for all total functions f when p is small compared to f’s block sensitivity. |
| Author | Jeffery, Stacey de Wolf, Ronald Magniez, Frederic |
| Author_xml | – sequence: 1 givenname: Stacey surname: Jeffery fullname: Jeffery, Stacey email: sjeffery@caltech.edu organization: Institute for Quantum Information and Matter, California Institute of Technology – sequence: 2 givenname: Frederic surname: Magniez fullname: Magniez, Frederic organization: CNRS, IRIF, Univ Paris Diderot, Sorbonne Paris-Cité – sequence: 3 givenname: Ronald surname: de Wolf fullname: de Wolf, Ronald organization: QuSoft, CWI and University of Amsterdam |
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| Cites_doi | 10.1098/rspa.2012.0686 10.1016/j.ipl.2010.09.009 10.1137/S0097539705447311 10.1145/2897518.2897644 10.1098/rspa.1992.0167 10.1007/978-3-642-39206-1_10 10.1109/CCC.2013.14 10.1109/FOCS.2012.18 10.1145/2213977.2213985 10.1109/SFCS.2000.892140 10.1145/1008731.1008735 10.1109/FOCS.2009.55 10.4086/toc.2005.v001a005 10.1145/2897518.2897524 10.1145/502090.502097 10.1145/1250790.1250867 10.1137/090745854 10.1109/SFCS.1998.743486 10.1145/237814.237866 10.1145/2422436.2422474 10.1137/0220062 10.1016/S0304-3975(01)00144-X 10.1137/S0097539799355053 10.1137/S0097539795293172 10.1103/PhysRevA.60.2746 10.1006/jcss.2002.1826 10.1007/BF01263419 10.1137/S0097539796298637 10.1109/CCC.2013.25 10.1007/s00453-002-0978-1 |
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| Keywords | Quantum algorithms Lower bounds Query complexity Parallel algorithms |
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| References | Belovs, A., Childs, A., Jeffery, S., Kothari, R., Magniez, F.: Time-efficient quantum walks for 3-distinctness. In: Proceedings of 40th ICALP(1), pp. 105–122 (2013) AmbainisAQuantum lower bounds by quantum argumentsJ. Comput. Syst. Sci.2002644750767191230110.1006/jcss.2002.18261015.68075 Cleve, R., Watrous, J.: Fast parallel circuits for the quantum Fourier transform. In: Proceedings of 41st IEEE FOCS, pp. 526–536 (2000) AmbainisAQuantum walk algorithm for element distinctnessSIAM J. Comput.2007371210239230629010.1137/S00975397054473111134.81010 ZalkaChGrover’s quantum searching algorithm is optimalPhys. Rev. A1999602746275110.1103/PhysRevA.60.2746 MagniezFNayakARolandJSanthaMSearch via quantum walkSIAM J. Comput.2011401142164278320610.1137/0907458541223.05289 Lee, T., Mittal, R., Reichardt, B., Špalek, R., Szegedy, M.: Quantum query complexity of state conversion. In: Proceedings of 52nd IEEE FOCS, pp. 344–353, (2011). arXiv:1011.3020v2 Belovs, A.: Learning-graph-based quantum algorithm for k-distinctness. In: Proceedings of 53rd IEEE FOCS, pp. 207–216 (2012) MontanaroANonadaptive quantum query complexityInf. Process. Lett.20101102411101113277824410.1016/j.ipl.2010.09.009 SimonDOn the power of quantum computationSIAM J. Comput.199726514741483147198910.1137/S00975397962986370883.03024 de BeaudrapNCleveRWatrousJSharp quantum vs. classical query complexity separationsAlgorithmica2002344449461194351710.1007/s00453-002-0978-11012.68220 Aaronson, S., Ben-David, S., Kothari, R.: Separations in query complexity using cheat sheets. In: Proceedings of 48th STOC, pp. 863–876 (2016) MooreCNilssonMParallel quantum computation and quantum codesSIAM J. Comput.2002313799815189645910.1137/S00975397993550531161.81326 Belovs, A.: Adversary lower bound for element distinctness (2012). arXiv:1204.5074 Aaronson, S., Ambainis, A.: Forrelation: a problem that optimally separates quantum from classical computing. In: Proceedings of 47th ACM STOC, pp. 307–316 (2015). arXiv:1411.5729 Ambainis, A., Balodis, K., Belovs, A., Lee, T., Santha, M., Smotrovs, J.: Separations in query complexity based on pointer functions. In: Proceedings of 48th STOC, pp 800–813 (2016) DeutschDJozsaRRapid solution of problems by quantum computationProc. R. Soc. Lond.1992A439553558119643310.1098/rspa.1992.01670792.68058 van Dam, W.: Quantum oracle interrogation: getting all information for almost half the price. In: Proceedings of 39th IEEE FOCS, pp. 362–367 (1998) Ambainis, A., Bačkurs, A., Smotrovs, J., de Wolf, R.: Optimal quantum query bounds for almost all Boolean functions. In: Proceedings of 30th STACS, pp. 446–453 (2013) NisanNCREW PRAMs and decision treesSIAM J. Comput.19912069991007113574410.1137/02200620737.68028 BealsRBuhrmanHCleveRMoscaMde WolfRQuantum lower bounds by polynomialsJ. ACM2001484778797214493010.1145/502090.5020971127.68404 Høyer, P., Lee, T., Špalek, R.: Negative weights make adversaries stronger. In: Proceedings of 39th ACM STOC, pp. 526–535 (2007) JozsaRAngelakisDGChristandlMEkertAAn introduction to measurement based quantum computationQuantum Information Processing2006AmsterdamIOS Press137158 Takahashi, Y., Tani, S.: Collapse of the hierarchy of constant-depth exact quantum circuits. In: Proceedings of 28th IEEE CCC (2013) Grover, L., Radhakrishnan, J.: Quantum search for multiple items using parallel queries (2004). arXiv:quant-ph/0407217 Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Proceedings of 28th ACM STOC, pp. 212–219 (1996) NisanNSzegedyMOn the degree of Boolean functions as real polynomialsComput. Complex.199444301313131353110.1007/BF012634190829.68047 AaronsonSShiYQuantum lower bounds for the collision and the element distinctness problemsJ. ACM2004514595605214784910.1145/1008731.10087351169.68406 ShorPWPolynomial-time algorithms for prime factorization and discrete logarithms on a quantum computerSIAM J. Comput.199726514841509147199010.1137/S00975397952931721005.11065 BealsRBrierleySGrayOHarrowAKutinSLindenNShepherdDStatherMEfficient distributed quantum computingProc. R. Soc A20134692153302978910.1098/rspa.2012.0686 HøyerPŠpalekRQuantum fan-out is powerfulTheory Comput.20051181103232251510.4086/toc.2005.v001a0051213.68298 GreenFHomerSMooreCPollettCCounting, fanout and the complexity of quantum ACCQuantum Inf. Comput.200221356519075201187.81065 Belovs, A., Lee, T.: Quantum algorithm for k-distinctness with prior knowledge on the input. Technical Report (2011). arXiv:1108.3022 Belovs, A., Rosmanis, A.: On the power of non-adaptive learning graphs. In: Proceedings of 28th IEEE CCC, pp. 44–55 (2013). arXiv:1210.3279v2 Belovs, A., Špalek, R.: Adversary lower bound for the k-sum problem. In: Proceedings of 4th ITCS, pp. 323–328 (2013) BuhrmanHde WolfRComplexity measures and decision tree complexity: a surveyTheor. Comput. Sci.200228812143193488810.1016/S0304-3975(01)00144-X1061.68058 Reichardt, B.: Span programs and quantum query complexity: The general adversary bound is nearly tight for every Boolean function. In: Proceedings of 50th IEEE FOCS, pp. 544–551 (2009) Belovs, A.: Span programs for functions with constant-sized 1-certificates. In: Proceedings of 43rd ACM STOC, pp. 77–84 (2012) GroverLRudolphTHow significant are the known collision and element distinctness quantum algorithms?Quantum Inf. Comput.20044320120620904551175.81056 D Deutsch (206_CR21) 1992; A439 A Ambainis (206_CR4) 2002; 64 R Beals (206_CR9) 2001; 48 F Green (206_CR22) 2002; 2 N Nisan (206_CR34) 1994; 4 206_CR12 206_CR11 R Jozsa (206_CR28) 2006 C Moore (206_CR32) 2002; 31 N Nisan (206_CR33) 1991; 20 R Beals (206_CR8) 2013; 469 206_CR2 206_CR17 N Beaudrap de (206_CR10) 2002; 34 206_CR19 206_CR14 206_CR13 206_CR35 206_CR1 206_CR16 206_CR38 206_CR15 H Buhrman (206_CR18) 2002; 288 206_CR7 206_CR6 F Magniez (206_CR30) 2011; 40 P Høyer (206_CR27) 2005; 1 Ch Zalka (206_CR39) 1999; 60 A Montanaro (206_CR31) 2010; 110 PW Shor (206_CR36) 1997; 26 S Aaronson (206_CR3) 2004; 51 206_CR20 206_CR23 L Grover (206_CR24) 2004; 4 D Simon (206_CR37) 1997; 26 A Ambainis (206_CR5) 2007; 37 206_CR29 206_CR25 206_CR26 |
| References_xml | – reference: AmbainisAQuantum lower bounds by quantum argumentsJ. Comput. Syst. Sci.2002644750767191230110.1006/jcss.2002.18261015.68075 – reference: van Dam, W.: Quantum oracle interrogation: getting all information for almost half the price. In: Proceedings of 39th IEEE FOCS, pp. 362–367 (1998) – reference: GreenFHomerSMooreCPollettCCounting, fanout and the complexity of quantum ACCQuantum Inf. Comput.200221356519075201187.81065 – reference: GroverLRudolphTHow significant are the known collision and element distinctness quantum algorithms?Quantum Inf. Comput.20044320120620904551175.81056 – reference: Belovs, A., Lee, T.: Quantum algorithm for k-distinctness with prior knowledge on the input. Technical Report (2011). arXiv:1108.3022 – reference: BuhrmanHde WolfRComplexity measures and decision tree complexity: a surveyTheor. Comput. Sci.200228812143193488810.1016/S0304-3975(01)00144-X1061.68058 – reference: DeutschDJozsaRRapid solution of problems by quantum computationProc. R. Soc. Lond.1992A439553558119643310.1098/rspa.1992.01670792.68058 – reference: Aaronson, S., Ambainis, A.: Forrelation: a problem that optimally separates quantum from classical computing. In: Proceedings of 47th ACM STOC, pp. 307–316 (2015). arXiv:1411.5729 – reference: Aaronson, S., Ben-David, S., Kothari, R.: Separations in query complexity using cheat sheets. In: Proceedings of 48th STOC, pp. 863–876 (2016) – reference: HøyerPŠpalekRQuantum fan-out is powerfulTheory Comput.20051181103232251510.4086/toc.2005.v001a0051213.68298 – reference: NisanNCREW PRAMs and decision treesSIAM J. Comput.19912069991007113574410.1137/02200620737.68028 – reference: Høyer, P., Lee, T., Špalek, R.: Negative weights make adversaries stronger. In: Proceedings of 39th ACM STOC, pp. 526–535 (2007) – reference: Cleve, R., Watrous, J.: Fast parallel circuits for the quantum Fourier transform. In: Proceedings of 41st IEEE FOCS, pp. 526–536 (2000) – reference: MontanaroANonadaptive quantum query complexityInf. Process. Lett.20101102411101113277824410.1016/j.ipl.2010.09.009 – reference: Belovs, A.: Adversary lower bound for element distinctness (2012). arXiv:1204.5074 – reference: MooreCNilssonMParallel quantum computation and quantum codesSIAM J. Comput.2002313799815189645910.1137/S00975397993550531161.81326 – reference: Belovs, A.: Learning-graph-based quantum algorithm for k-distinctness. In: Proceedings of 53rd IEEE FOCS, pp. 207–216 (2012) – reference: JozsaRAngelakisDGChristandlMEkertAAn introduction to measurement based quantum computationQuantum Information Processing2006AmsterdamIOS Press137158 – reference: NisanNSzegedyMOn the degree of Boolean functions as real polynomialsComput. Complex.199444301313131353110.1007/BF012634190829.68047 – reference: ShorPWPolynomial-time algorithms for prime factorization and discrete logarithms on a quantum computerSIAM J. Comput.199726514841509147199010.1137/S00975397952931721005.11065 – reference: MagniezFNayakARolandJSanthaMSearch via quantum walkSIAM J. Comput.2011401142164278320610.1137/0907458541223.05289 – reference: BealsRBrierleySGrayOHarrowAKutinSLindenNShepherdDStatherMEfficient distributed quantum computingProc. R. Soc A20134692153302978910.1098/rspa.2012.0686 – reference: Ambainis, A., Bačkurs, A., Smotrovs, J., de Wolf, R.: Optimal quantum query bounds for almost all Boolean functions. In: Proceedings of 30th STACS, pp. 446–453 (2013) – reference: Belovs, A., Rosmanis, A.: On the power of non-adaptive learning graphs. In: Proceedings of 28th IEEE CCC, pp. 44–55 (2013). arXiv:1210.3279v2 – reference: Belovs, A.: Span programs for functions with constant-sized 1-certificates. In: Proceedings of 43rd ACM STOC, pp. 77–84 (2012) – reference: Reichardt, B.: Span programs and quantum query complexity: The general adversary bound is nearly tight for every Boolean function. In: Proceedings of 50th IEEE FOCS, pp. 544–551 (2009) – reference: AaronsonSShiYQuantum lower bounds for the collision and the element distinctness problemsJ. ACM2004514595605214784910.1145/1008731.10087351169.68406 – reference: Ambainis, A., Balodis, K., Belovs, A., Lee, T., Santha, M., Smotrovs, J.: Separations in query complexity based on pointer functions. In: Proceedings of 48th STOC, pp 800–813 (2016) – reference: Grover, L., Radhakrishnan, J.: Quantum search for multiple items using parallel queries (2004). arXiv:quant-ph/0407217 – reference: de BeaudrapNCleveRWatrousJSharp quantum vs. classical query complexity separationsAlgorithmica2002344449461194351710.1007/s00453-002-0978-11012.68220 – reference: Belovs, A., Childs, A., Jeffery, S., Kothari, R., Magniez, F.: Time-efficient quantum walks for 3-distinctness. In: Proceedings of 40th ICALP(1), pp. 105–122 (2013) – reference: Lee, T., Mittal, R., Reichardt, B., Špalek, R., Szegedy, M.: Quantum query complexity of state conversion. In: Proceedings of 52nd IEEE FOCS, pp. 344–353, (2011). arXiv:1011.3020v2 – reference: BealsRBuhrmanHCleveRMoscaMde WolfRQuantum lower bounds by polynomialsJ. ACM2001484778797214493010.1145/502090.5020971127.68404 – reference: Belovs, A., Špalek, R.: Adversary lower bound for the k-sum problem. 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| Snippet | We study the complexity of quantum query algorithms that make
p
queries in parallel in each timestep. This model is in part motivated by the fact that... We study the complexity of quantum query algorithms that make p queries in parallel in each timestep. This model is in part motivated by the fact that... We define the Streaming Communication model that combines the main aspects of communication complexity and streaming. Input arrives as a stream, spread between... |
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| SubjectTerms | Algorithm Analysis and Problem Complexity Algorithms Complexity Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Functions (mathematics) Lower bounds Mathematical analysis Mathematics of Computing Parallel processing Qubits (quantum computing) Queries Theory of Computation Upper bounds |
| Title | Optimal Parallel Quantum Query Algorithms |
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