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The Cabello Nonlocality Argument is Stronger Control than the Hardy Nonlocality Argument for Detecting Post-Quantum Correlations in the Bipartite Systems

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In this paper, we study the Hardy nonlocality argument (HNA) and the Cabello nonlocality argument (CNA) under the Information Causality (IC), Macroscopic Locality (ML) and Local Orthogonality (LO) principles with respected to Local Randomness. We show that, in the context of all possibilities of local randomness, the gap between the quantum mechanics and the above principles, in the CNA is larger than the HNA. Therefore, the CNA is stronger control than the HNA for detecting post-quantum nosignalling correlations in the bipartite systems.

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Appendices

Appendix 1

The 16 Local matrices for bipartite system with binary input-output:

$$ {\displaystyle \begin{array}{l}{P}^{0000}=\left(\begin{array}{llll}1& 0& 0& 0\\ {}1& 0& 0& 0\\ {}1& 0& 0& 0\\ {}1& 0& 0& 0\end{array}\right),{P}^{0001}=\left(\begin{array}{llll}0& 1& 0& 0\\ {}0& 1& 0& 0\\ {}0& 1& 0& 0\\ {}0& 1& 0& 0\end{array}\right)\\ {}{P}^{0010}=\left(\begin{array}{llll}1& 0& 0& 0\\ {}0& 1& 0& 0\\ {}1& 0& 0& 0\\ {}0& 1& 0& 0\end{array}\right),{P}^{0011}=\left(\begin{array}{llll}0& 1& 0& 0\\ {}1& 0& 0& 0\\ {}0& 1& 0& 0\\ {}1& 0& 0& 0\end{array}\right)\\ {}{P}^{0100}=\left(\begin{array}{llll}0& 0& 1& 0\\ {}0& 0& 1& 0\\ {}0& 0& 1& 0\\ {}0& 0& 1& 0\end{array}\right),{P}^{0101}=\left(\begin{array}{llll}0& 0& 0& 1\\ {}0& 0& 0& 1\\ {}0& 0& 0& 1\\ {}0& 0& 0& 1\end{array}\right)\\ {}{P}^{0110}=\left(\begin{array}{llll}0& 0& 1& 0\\ {}0& 0& 0& 1\\ {}0& 0& 1& 0\\ {}0& 0& 0& 1\end{array}\right),{P}^{0111}=\left(\begin{array}{llll}0& 0& 0& 1\\ {}0& 0& 1& 0\\ {}0& 0& 0& 1\\ {}0& 0& 1& 0\end{array}\right)\\ {}{P}^{1000}=\left(\begin{array}{llll}1& 0& 0& 0\\ {}1& 0& 0& 0\\ {}0& 0& 1& 0\\ {}0& 0& 1& 0\end{array}\right),{P}^{1001}=\left(\begin{array}{llll}0& 1& 0& 0\\ {}0& 1& 0& 0\\ {}0& 0& 0& 1\\ {}0& 0& 0& 1\end{array}\right)\\ {}{P}^{1010}=\left(\begin{array}{llll}1& 0& 0& 0\\ {}0& 1& 0& 0\\ {}0& 0& 1& 0\\ {}0& 0& 0& 1\end{array}\right),{P}^{1011}=\left(\begin{array}{llll}0& 1& 0& 0\\ {}1& 0& 0& 0\\ {}0& 0& 0& 1\\ {}0& 0& 1& 0\end{array}\right)\\ {}{P}^{1100}=\left(\begin{array}{llll}0& 0& 1& 0\\ {}0& 0& 1& 0\\ {}1& 0& 0& 0\\ {}1& 0& 0& 0\end{array}\right),{P}^{1101}=\left(\begin{array}{llll}0& 0& 0& 1\\ {}0& 0& 0& 1\\ {}0& 1& 0& 0\\ {}0& 1& 0& 0\end{array}\right)\\ {}{P}^{1110}=\left(\begin{array}{llll}0& 0& 1& 0\\ {}0& 0& 0& 1\\ {}1& 0& 0& 0\\ {}0& 1& 0& 0\end{array}\right),{P}^{1111}=\left(\begin{array}{llll}0& 0& 0& 1\\ {}0& 0& 1& 0\\ {}0& 1& 0& 0\\ {}1& 0& 0& 0\end{array}\right)\end{array}} $$

The 8 Non-Local matrices for bipartite system with binary input-output:

$$ {\displaystyle \begin{array}{l}{P}^{000}=\frac{1}{2}\left(\begin{array}{llll}1& 0& 0& 1\\ {}1& 0& 0& 1\\ {}1& 0& 0& 1\\ {}0& 1& 1& 0\end{array}\right),{P}^{001}=\frac{1}{2}\left(\begin{array}{llll}0& 1& 1& 0\\ {}0& 1& 1& 0\\ {}0& 1& 1& 0\\ {}1& 0& 0& 1\end{array}\right)\\ {}{P}^{010}=\frac{1}{2}\left(\begin{array}{llll}1& 0& 0& 1\\ {}0& 1& 1& 0\\ {}1& 0& 0& 1\\ {}1& 0& 0& 1\end{array}\right),{P}^{011}=\frac{1}{2}\left(\begin{array}{llll}0& 1& 1& 0\\ {}1& 0& 0& 1\\ {}0& 1& 1& 0\\ {}0& 1& 1& 0\end{array}\right)\\ {}{P}^{100}=\frac{1}{2}\left(\begin{array}{llll}1& 0& 0& 1\\ {}1& 0& 0& 1\\ {}0& 1& 1& 0\\ {}1& 0& 0& 1\end{array}\right),{P}^{101}=\frac{1}{2}\left(\begin{array}{llll}0& 1& 1& 0\\ {}0& 1& 1& 0\\ {}1& 0& 0& 1\\ {}0& 1& 1& 0\end{array}\right)\\ {}{P}^{110}=\frac{1}{2}\left(\begin{array}{llll}1& 0& 0& 1\\ {}0& 1& 1& 0\\ {}0& 1& 1& 0\\ {}0& 1& 1& 0\end{array}\right),{P}^{111}=\frac{1}{2}\left(\begin{array}{llll}0& 1& 1& 0\\ {}1& 0& 0& 1\\ {}1& 0& 0& 1\\ {}1& 0& 0& 1\end{array}\right)\end{array}} $$

Appendix 2

The following inequalities are sufficient for obtaining the upper bound of the HNA under LO principle [27]. The inequalities can be shown, in terms of variables ek, mi and ni (k ∈ {1, 2, 3, 4} and i ∈ {1, 2}).

$$ {e}_3^2+2{e}_2{g}_2-{g}_2^2-{e}_2^2\le 0 $$
(32)
$$ {e}_3^2+2{e}_1{g}_2-{e}_1^2-{g}_2^2\le 0 $$
(33)
$$ {e}_3^2+\left({e}_3-{e}_1\right)\left(1-{e}_2-{f}_2\right)\le 0 $$
(34)
$$ {e}_3^2+\left({e}_3-{e}_2\right)\left(1-{f}_2-{g}_2\right)\le 0 $$
(35)
$$ {e}_2\left({e}_3+{f}_2-{e}_2\right)+\left({e}_3-{f}_2\right){g}_2\le 0 $$
(36)
$$ {e}_1\left({f}_2-{e}_3\right)+{e}_3\left({e}_3+{g}_2\right)-{f}_2{g}_2\le 0 $$
(37)
$$ \left({g}_2-{e}_2\right)\left({f}_2+{g}_2-1\right)+2{e}_1{e}_3-{e}_1^2\le 0 $$
(38)
$$ {e}_3\left(1+{f}_2-{g}_2\right)+{e}_2\left({f}_2+{g}_2-1\right)-{f}_2^2\le 0 $$
(39)
$$ {e}_3^2+\left({f}_2-{e}_3\right)\left({f}_2+{g}_2-1\right)-{\left({e}_1-{e}_2\right)}^2\le 0 $$
(40)
$$ {e}_1\left({e}_3-{f}_2-{g}_2\right)+{e}_2\left(-1+{e}_1-{e}_3+{f}_2+{g}_2\right)+{e}_3\le 0 $$
(41)

The relation between the 8 independent parameter and the coefficients ci is obtained by comparing the matrix (5) and the Hardy correlation matrix (15). So, we have:

$$ {\displaystyle \begin{array}{l}{e}_1={c}_3+\frac{c_6}{2}\\ {}{e}_2={c}_{3,4}+\frac{c_6}{2}\\ {}{e}_3=\frac{c_6}{2}\\ {}{e}_4=0\\ {}{f}_1={e}_2\\ {}{f}_2={c}_5+\frac{c_6}{2}\\ {}{g}_1={e}_1\\ {}{g}_2={c}_2+{e}_2\end{array}} $$

Appendix 3

The following inequalities are sufficient for obtaining the upper bound of CNA under LO principle [27]. The inequalities can be represented, in terms of variables ek, mi and ni (k ∈ {1, 2, 3, 4} and i ∈ {1, 2}):

$$ {e}_3\left(1+{e}_1-{f}_1-{g}_2\right)+\left(1+{e}_2+{e}_3-{f}_1-{f}_2-{g}_2\right){e}_2-{e}_1+\left({e}_1+{f}_2+{g}_2-1\right){g}_2\le 0 $$
$$ {\displaystyle \begin{array}{c}{e}_3\left(1+{e}_1-{f}_1-{g}_2\right)+\left(1+{e}_2+{e}_3-{f}_1-{f}_2-{g}_2\right){e}_2\\ {}-{e}_1+\left({e}_1+{f}_2+{g}_2-1\right){g}_2\le 0\end{array}} $$
(42)
$$ {\displaystyle \begin{array}{c}{\left({e}_2\right)}^2+\left(1-{f}_1-{g}_2\right){e}_3+\left(1+{e}_1+{e}_3-2{f}_1-{f}_2-{g}_2\right){e}_2\\ {}-{e}_1^2+\left({e}_3+{f}_1-{f}_2\right){e}_1+\left({f}_1+{f}_2\right)\left({f}_2+{g}_2\right)-\left({f}_1+{f}_2\right)\le 0\end{array}} $$
(43)
$$ {\displaystyle \begin{array}{c}\left({e}_2+{e}_3\right)\left({e}_3-{f}_1\right)+2{e}_2{g}_2-{g}_2^2\le 0\\ {}{e}_2^2+\left({e}_2+2{f}_2-{f}_1\right){e}_3-{e}_1{e}_2+\left(1-{f}_2\right){e}_1-\\ {}{f}_2^2+\left({f}_2-1\right){f}_1\le 0\end{array}} $$
(44)
$$ {\displaystyle \begin{array}{c}{e}_2^2+{e}_3\left(1+{f}_2-{f}_1-{g}_2\right)+{e}_3{e}_2+{e}_2\left(1-{f}_1-{f}_2-{g}_2\right)\\ {}+{e}_1\left({g}_2-{f}_1\right)+{f}_1^2+{f}_2\left({f}_1+{g}_2-1\right)-{f}_1\le 0\end{array}} $$
(45)
$$ {\displaystyle \begin{array}{c}{e}_3^2+{e}_3\left(-{f}_1\right)+{e}_2{e}_3+{e}_2\left(2-2{f}_1-{f}_2\right)+\\ {}{e}_1\left(1-{f}_2-{g}_2\right)+{f}_1^2+{f}_1\left(2{g}_2+{f}_2-2\right)\\ {}+\left({f}_2-1\right){g}_2\le 0\end{array}} $$
(46)
$$ {\displaystyle \begin{array}{c}{e}_3^2+\left({e}_2-{f}_1\right){e}_3+{e}_2\left(1-2{f}_1+{g}_2\right)+\\ {}{f}_1\left({f}_1+{g}_2\right)-{f}_1-{g}_2^2\le 0\end{array}} $$
(47)
$$ \left({e}_2+{e}_1\right)\left({e}_3+{e}_2+1-{e}_1-{g}_2\right)+{f}_1\left({f}_1+2{g}_2-2{e}_2-2\right)\le 0 $$
(48)

The relation between 8 independent parameters and coefficients ci is obtained by comparing the matrix (5) and the Cabelo correlation matrix(18). So, we have:

$$ {\displaystyle \begin{array}{l}{e}_1={c}_{3,8,10}+\frac{c_6+{c}_{11}}{2}\\ {}{e}_2={c}_{3,4}+\frac{c_6}{2}\\ {}{e}_3={c}_8+\frac{c_6}{2}\\ {}{e}_4=0\\ {}{f}_1={e}_1+{c}_{4,7,9}\\ {}{f}_2={e}_3+{c}_{5,7}+\frac{c_11}{2}\\ {}{g}_1={e}_1\\ {}{g}_2={e}_2+{c}_2+\frac{c_{11}}{2}\end{array}} $$

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Ahanj, A. The Cabello Nonlocality Argument is Stronger Control than the Hardy Nonlocality Argument for Detecting Post-Quantum Correlations in the Bipartite Systems. Int J Theor Phys 58, 1441–1455 (2019). https://doi.org/10.1007/s10773-019-04032-8

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