scholarly journals Exact quantum algorithms have advantage for almost all Boolean functions

2015 ◽  
pp. 435-452
Author(s):  
Andris Ambainis ◽  
Jozef Gruska ◽  
Shenggen Zheng
Keyword(s):  
Boolean Function ◽  
Boolean Functions ◽  
Quantum Algorithms ◽  
Quantum Algorithm ◽  
Query Complexity ◽  
Exact Quantum ◽  
Quantum Query Complexity ◽  
Almost All ◽  
Quantum Query

It has been proved that almost all n-bit Boolean functions have exact classical query complexity n. However, the situation seemed to be very different when we deal with exact quantum query complexity. In this paper, we prove that almost all n-bit Boolean functions can be computed by an exact quantum algorithm with less than n queries. More exactly, we prove that ANDn is the only n-bit Boolean function, up to isomorphism, that requires n queries.

scholarly journals Partial Boolean Functions With Exact Quantum Query Complexity One

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 189
Author(s):  
Guoliang Xu ◽  
Daowen Qiu
Keyword(s):  
Boolean Function ◽  
Upper Bound ◽  
Boolean Functions ◽  
Necessary Conditions ◽  
Quantum Algorithm ◽  
Query Complexity ◽  
Exact Quantum ◽  
Quantum Query Complexity ◽  
Sufficient And Necessary Conditions ◽  
Quantum Query

We provide two sufficient and necessary conditions to characterize any n-bit partial Boolean function with exact quantum query complexity 1. Using the first characterization, we present all n-bit partial Boolean functions that depend on n bits and can be computed exactly by a 1-query quantum algorithm. Due to the second characterization, we construct a function F that maps any n-bit partial Boolean function to some integer, and if an n-bit partial Boolean function f depends on k bits and can be computed exactly by a 1-query quantum algorithm, then F(f) is non-positive. In addition, we show that the number of all n-bit partial Boolean functions that depend on k bits and can be computed exactly by a 1-query quantum algorithm is not bigger than an upper bound depending on n and k. Most importantly, the upper bound is far less than the number of all n-bit partial Boolean functions for all efficiently big n.

scholarly journals Following Forrelation – quantum algorithms in exploring Boolean functions' spectra

2022 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Suman Dutta ◽  
Subhamoy Maitra ◽  
Chandra Sekhar Mukherjee
Keyword(s):  
Boolean Functions ◽  
Cross Correlation ◽  
Quantum Algorithms ◽  
Quantum Algorithm ◽  
Sampling Technique ◽  
Linear Functions ◽  
Query Complexity ◽  
Walsh Spectrum ◽  
Correlation Spectrum ◽  
The Cross

<p style='text-indent:20px;'>Here we revisit the quantum algorithms for obtaining Forrelation [Aaronson et al., 2015] values to evaluate some of the well-known cryptographically significant spectra of Boolean functions, namely the Walsh spectrum, the cross-correlation spectrum, and the autocorrelation spectrum. We introduce the existing 2-fold Forrelation formulation with bent duality-based promise problems as desirable instantiations. Next, we concentrate on the 3-fold version through two approaches. First, we judiciously set up some of the functions in 3-fold Forrelation so that given oracle access, one can sample from the Walsh Spectrum of <inline-formula><tex-math id="M1">\begin{document}$ f $\end{document}</tex-math></inline-formula>. Using this, we obtain improved results than what one can achieve by exploiting the Deutsch-Jozsa algorithm. In turn, it has implications in resiliency checking. Furthermore, we use a similar idea to obtain a technique in estimating the cross-correlation (and thus autocorrelation) value at any point, improving upon the existing algorithms. Finally, we tweak the quantum algorithm with the superposition of linear functions to obtain a cross-correlation sampling technique. This is the first cross-correlation sampling algorithm with constant query complexity to the best of our knowledge. This also provides a strategy to check if two functions are uncorrelated of degree <inline-formula><tex-math id="M2">\begin{document}$ m $\end{document}</tex-math></inline-formula>. We further modify this using Dicke states so that the time complexity reduces, particularly for constant values of <inline-formula><tex-math id="M3">\begin{document}$ m $\end{document}</tex-math></inline-formula>.</p>

scholarly journals The quantum query complexity of AC0

2012 ◽  
Vol 12 (7&8) ◽  
pp. 670-676
Author(s):  
Paul Beame ◽  
Widad Machmouchi
Keyword(s):  
Lower Bound ◽  
Quantum Algorithm ◽  
Input Function ◽  
Query Complexity ◽  
Quantum Query Complexity ◽  
Quantum Query

We show that any quantum algorithm deciding whether an input function $f$ from $[n]$ to $[n]$ is 2-to-1 or almost 2-to-1 requires $\Theta(n)$ queries to $f$. The same lower bound holds for determining whether or not a function $f$ from $[2n-2]$ to $[n]$ is surjective. These results yield a nearly linear $\Omega(n/\log n)$ lower bound on the quantum query complexity of $\cl{AC}^0$. The best previous lower bound known for any $\cl{AC^0}$ function was the $\Omega ((n/\log n)^{2/3})$ bound given by Aaronson and Shi's $\Omega(n^{2/3})$ lower bound for the element distinctness problem.

scholarly journals Explicit relation between all lower bound techniques for quantum query complexity

2015 ◽  
Vol 13 (04) ◽  
pp. 1350059
Author(s):  
Loïck Magnin ◽  
Jérémie Roland
Keyword(s):  
Lower Bound ◽  
Boolean Functions ◽  
Query Complexity ◽  
Polynomial Method ◽  
Quantum Query Complexity ◽  
State Generation ◽  
Adversary Method ◽  
Explicit Relation ◽  
Special Case ◽  
Quantum Query

The polynomial method and the adversary method are the two main techniques to prove lower bounds on quantum query complexity, and they have so far been considered as unrelated approaches. Here, we show an explicit reduction from the polynomial method to the multiplicative adversary method. The proof goes by extending the polynomial method from Boolean functions to quantum state generation problems. In the process, the bound is even strengthened. We then show that this extended polynomial method is a special case of the multiplicative adversary method with an adversary matrix that is independent of the function. This new result therefore provides insight on the reason why in some cases the adversary method is stronger than the polynomial method. It also reveals a clear picture of the relation between the different lower bound techniques, as it implies that all known techniques reduce to the multiplicative adversary method.

scholarly journals Quantum Query Complexity of Almost All Functions with Fixed On-set Size

2016 ◽  
Vol 25 (4) ◽  
pp. 723-735
Author(s):  
Andris Ambainis ◽  
Kazuo Iwama ◽  
Masaki Nakanishi ◽  
Harumichi Nishimura ◽  
Rudy Raymond ◽  
...  
Keyword(s):  
Query Complexity ◽  
Set Size ◽  
Quantum Query Complexity ◽  
Almost All ◽  
Quantum Query

scholarly journals On Exact Quantum Query Complexity

Algorithmica ◽  
2013 ◽  
Vol 71 (4) ◽  
pp. 775-796 ◽  
Author(s):  
Ashley Montanaro ◽  
Richard Jozsa ◽  
Graeme Mitchison
Keyword(s):  
Query Complexity ◽  
Exact Quantum ◽  
Quantum Query Complexity ◽  
Quantum Query

Quantum Query Complexity of Boolean Functions with Small On-Sets

2008 ◽  
pp. 907-918 ◽  
Author(s):  
Andris Ambainis ◽  
Kazuo Iwama ◽  
Masaki Nakanishi ◽  
Harumichi Nishimura ◽  
Rudy Raymond ◽  
...  
Keyword(s):  
Boolean Functions ◽  
Query Complexity ◽  
Quantum Query Complexity ◽  
Quantum Query

scholarly journals Quantum algorithms for graph connectivity and formula evaluation

Quantum ◽  
2017 ◽  
Vol 1 ◽  
pp. 26
Author(s):  
Stacey Jeffery ◽  
Shelby Kimmel
Keyword(s):  
Quantum Algorithms ◽  
Graph Connectivity ◽  
Query Complexity ◽  
Boolean Formula ◽  
Quantum Query Complexity ◽  
Boolean Formulas ◽  
Speed Up ◽  
The Right ◽  
Quantum Query ◽  
Better Than

We give a new upper bound on the quantum query complexity of decidingst-connectivity on certain classes of planar graphs, and show the bound is sometimes exponentially better than previous results. We then show Boolean formula evaluation reduces to deciding connectivity on just such a class of graphs. Applying the algorithm forst-connectivity to Boolean formula evaluation problems, we match theO(N)bound on the quantum query complexity of evaluating formulas onNvariables, give a quadratic speed-up over the classical query complexity of a certain class of promise Boolean formulas, and show this approach can yield superpolynomial quantum/classical separations. These results indicate that thisst-connectivity-based approach may be the "right" way of looking at quantum algorithms for formula evaluation.

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