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What is the benefits of quantum computing vs parallel processing using classical computer ?

Can classical parallel processors outperform quantum computing ?

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    Remainder: one 1970 Intel 4004 outperforms by orders of magnitude any available quantum computing device of a structure hoped/feared to become, in the future, usable for cryptanalysis (this excludes quantum-named computers specialized in quantum annealing, which do not aim at running Grover's or Shor's algorithms). – fgrieu Oct 23 '18 at 17:23

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1. What is the benefits of quantum computing vs parallel processing using classical computer?

The answer is in terms of Cryptography;

Quantum Computing (QC)

  • Key search on Block ciphers; Grover's algorithm is a brute-force quantum algorithm with complexity $\mathcal{O}(\sqrt{N})$ with asymptotically optimal on unstructured data.

  • Public key algorithms;

    • RSA factorization problem; Shor's algorithm can efficiently factor integer $n$ in $\mathcal{O}((\log n)^2(\log \log n)(\log \log \log n)$
    • Discrete logarithm problem; Shor's algorithm can efficiently solve.

Therefore, RSA, Diffie–Hellman, and Elliptic Curve Diffie–Hellman could be broken easily.

Parallelization

  • Parallel computing in keys searches only help linear time whereas using single QC already gives quadratic speed up. Examples are Distributed.net, DES Cracker, COPACOBANA hashcat
  • Parallel computing is used in factorization algorithms where the help again is linear with complexity;

    General Number Field Sieve with superpolynomial scaling: $$\mathcal{O}(exp [ c (\ln n)^{1/3} (\ln \ln n)^{2/3}])$$

2. Can classical parallel processors outperform quantum computing?

Firstly, quantum give new complexity classes;

The class of problems that can be efficiently solved by quantum computers is called BQP, for "bounded error, quantum, polynomial time".7

BQP is suspected to be disjoint from NP-complete and a strict superset of P, but that is not known. Both integer factorization and discrete log are in BQP.

Some $NP$ problems can be solved efficiently.

A Turing machine can simulate a QC and QC can simulate A Trung machine too,. So, once A QC is built, you can outperform a QC only by money.

Cost2

An important subject is also the cost of running the algoriths.

Daniel J. Bernstein asked the question in "Cost analysis of hash collisions: Will quantum computers make SHARCS1 obsolete". Some results if a QC is built;

  • Factorization; QC much more scalable and much more cost effective

    • The number-field sieve factors b-bit RSA moduli in time $2^{b^{1/3+\mathcal{o}(1)}}$
    • If a QC can be built for $b^{\mathcal{\Theta}(1)}$ Euros can factor b-bit integer in $b^{\mathcal{\Theta}(1)}$ seconds.
  • Pre-Image Search;

    • Traditional hardware can find in $2^bh$ operations
    • Quantum; much more cost effective

      • Grover $2^{b/2}h$ operations on $\mathcal{\Theta}(h)$ qubits.
      • Shor’s speedup from $2^{b^{1/3+\mathcal{o}(1)}}$ to $b^{\mathcal{\Theta}(1)}$
    • Collision search; He claims that all quantum algorithms upto his paper are less cost-effective than the traditional.

    • Parallelization

    • A size-$M$ machine finds collisions in time roughly $2^b/M^{3/2}$. if size $2^{b/3}$ than collision time is $2^{b/2}$ with $\epsilon$ time with $\epsilon$ probability.
    • a size-M QC after $2^{b/2}h\epsilon$ quantum operations each unit has $\epsilon^2$ success probability. After $2^{b/2}h/M^{1/2}$ total quantum operations the size-M machine has $M\epsilon^2$ success probability. If the size a quantum computer is $2^{b/3}$ then the time for finding collisions is approximately $2^{b/3}$. Compare to classical.

and he added;

Anyone afraid of quantum hash-collision algorithms already has much more to fear from non-quantum hash-collision algorithms.


1 Special-Purpose Hardware for Attacking Cryptographic Systems

2 Special Thanks to Ella-Rose for the article.

kelalaka
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