First, we review the Bernstein-Vazirani algorithm for determining a bit string. Next, we discuss the generalized Bernstein-Vazirani algorithm for determining a natural number string. Finally, we discuss the generalized Bernstein-Vazirani algorithm for determining an integer string. All of the generalized algorithms presented here have the following structure. Given the set of real values $\{a_1,a_2,a_3,\ldots,a_N\}$ and a special function $g$ , we determine $N$ values of the function $g(a_1),g(a_2),g(a_3),\ldots, g(a_N)$ simultaneously. The speed of determining the strings is shown to outperform the best classical case by a factor of $N$ in every case.First, we review the Bernstein-Vazirani algorithm for determining a bit string. Next, we discuss the generalized Bernstein-Vazirani algorithm for determining a natural number string. Finally, we discuss the generalized Bernstein-Vazirani algorithm for determining an integer string. All of the generalized algorithms presented here have the following structure. Given the set of real values $\{a_1,a_2,a_3,\ldots,a_N\}$ and a special function $g$, we determine $N$ values of the function $g(a_1),g(a_2),g(a_3),\ldots, g(a_N)$ simultaneously. The speed of determining the strings is shown to outperform the best classical case by a factor of $N$ in every case.

Sep 1, 20180 citations

Relevant Quantum Algorithms

Davide Pastorello

Machine learningDec 16, 20220 citations

Effects of noise on performance of Bernstein-Vazirani algorithm

Gupta, Archi, Priya Ghosh, Kornikar Sen +1 more

The Bernstein-Vazirani (BV) algorithm offers exceptional accuracy in finding the hidden bit string of a function. We explore how the algorithm performs in real-world situations where noise can potentially interfere with its performance. In order to assess the impact of imperfect equipments, we introduce various forms of glassy disorders into the effect of the Hadamard gates used in the Bernstein-Vazirani circuit. We incorporated disorders of five different forms, viz., Haar-uniform with finite cutoff, spherical Gaussian, discrete circular, spherical Cauchy-Lorentz, and squeezed. We find that the effectiveness of the algorithm decreases with increasing disorder strength in all cases. Additionally, we demonstrate that as the number of bits in the secret string increases, the success probability of correctly guessing the string becomes increasingly insensitive to the type of disorder and instead depends only on the mean and spread of the disorder. We compare our results with the performance of the analogous classical algorithm in the presence of similar noise. When the length of the secret string is small or moderate, the quantum BV algorithm is found to be more efficient compared to the classical algorithm for almost all types of disorders under consideration, unless the strength of the disorder is very high and the disorder follows a discrete circular distribution. However, if we move to extremely large secret strings, the success probability of the disordered BV algorithm merges with the success probability of the disordered classical algorithm for all considered disorders having arbitrary strengths. The limit on the length of the string after which the efficiency of the quantum algorithm becomes equivalent to the classical algorithm depends on the amount of disorder and not on the type of disorder.The Bernstein-Vazirani (BV) algorithm offers exceptional accuracy in finding the hidden bit string of a function. We explore how the algorithm performs in real-world situations where noise can potentially interfere with its performance. In order to assess the impact of imperfect equipments, we introduce various forms of glassy disorders into the effect of the Hadamard gates used in the Bernstein-Vazirani circuit. We incorporated disorders of five different forms, viz., Haar-uniform with finite cutoff, spherical Gaussian, discrete circular, spherical Cauchy-Lorentz, and squeezed. We find that the effectiveness of the algorithm decreases with increasing disorder strength in all cases. Additionally, we demonstrate that as the number of bits in the secret string increases, the success probability of correctly guessing the string becomes increasingly insensitive to the type of disorder and instead depends only on the mean and spread of the disorder. We compare our results with the performance of the analogous classical algorithm in the presence of similar noise. When the length of the secret string is small or moderate, the quantum BV algorithm is found to be more efficient compared to the classical algorithm for almost all types of disorders under consideration, unless the strength of the disorder is very high and the disorder follows a discrete circular distribution. However, if we move to extremely large secret strings, the success probability of the disordered BV algorithm merges with the success probability of the disordered classical algorithm for all considered disorders having arbitrary strengths. The limit on the length of the string after which the efficiency of the quantum algorithm becomes equivalent to the classical algorithm depends on the amount of disorder and not on the type of disorder.

arXiv:2305.19745May 31, 20233 citations

Quantum Algorithms with Potential for New Applications

Takashi Yamakawa

NTT technical reviewJul 1, 20231 citation

A Generalization of Bernstein-Vazirani Algorithm to Qudit Systems

R Narayanan Krishna, Vishesh Makwana, Ananda Padhmanabhan Suresh

A quantum algorithm to solve the parity problem is better than its most efficient classical counter- part with a separation that is polynomial in the number of queries. This was shown by E. Bernstein and U. Vazirani and was one of the earliest indications that the quantum information processing can outperform the classical one by a significant margin. The problem and its solution both is usually stated for a 2-level system since we generally work with bits/qubits. However, many works have been done generalizing known quantum computing techniques to higher level systems. Following this, we look at a generalization of the Bernstein-Vazirani algorithm implemented on a general qudit system.A quantum algorithm to solve the parity problem is better than its most efficient classical counter- part with a separation that is polynomial in the number of queries. This was shown by E. Bernstein and U. Vazirani and was one of the earliest indications that the quantum information processing can outperform the classical one by a significant margin. The problem and its solution both is usually stated for a 2-level system since we generally work with bits/qubits. However, many works have been done generalizing known quantum computing techniques to higher level systems. Following this, we look at a generalization of the Bernstein-Vazirani algorithm implemented on a general qudit system.

arXiv:1609.03185Sep 11, 20165 citations

\{a_1,a_2,a_3,\ldots,a_N\}

and a special function

g

, we determine

N

values of the function

g(a_1),g(a_2),g(a_3),\ldots, g(a_N)

simultaneously. The speed of determining the strings is shown to outperform the best classical case by a factor of

N

in every case.