We implement the Bernstein-Vazirani algorithm on a 15-bit register encoding 215-1 elements using optics. The apparatus is efficient in that the physical size of the apparatus scales linearly with the size (i.e. number of digits) of the register. We demonstrate also that the algorithm may be performed not only without entanglement, as Meyer has indicated, but also with a computational basis that does not consist of orthogonal states, and that this coding is the source of the efficiency of the algorithm. This raises several questions: is this the only algorithm that makes use of these simplifying features, or do all quantum Oracles in fact require exponential resources for their construction?
We implement the Bernstein-Vazirani algorithm on a 15-bit register encoding 215-1 elements using optics. The apparatus is efficient in that the physical size of the apparatus scales linearly with the size (i.e. number of digits) of the register. We demonstrate also that the algorithm may be performed not only without entanglement, as Meyer has indicated, but also with a computational basis that does not consist of orthogonal states, and that this coding is the source of the efficiency of the algorithm. This raises several questions: is this the only algorithm that makes use of these simplifying features, or do all quantum Oracles in fact require exponential resources for their construction?
We implement the Bernstein-Vazirani algorithm on a 15-bit register encoding 215 elements using optics. The algorithm provides a polynomial speed up for oracle queries. The apparatus is physically efficient in that its size (i.e., space-time volume) scales linearly with the size (i.e., number of digits) of the register. We demonstrate also that the algorithm may be performed not only without entanglement, but also with a computational basis that does not consist of orthogonal states, and that this coding is the source of the efficiency of the algorithm.
We describe a new implementation of the Bernstein-Vazirani algorithm that relies on the fact that the polarization states of classical light beams can be cloned. We explore the possibility of computing with waves and discuss a classical optical model capable of implementing any algorithm (on n qubits) that does not involve entanglement. The Bernstein-Vazirani algorithm (with a suitably modified oracle), wherein a hidden n-bit vector is discovered by one oracle query as against n oracle queries required classically, belongs to this category. In our scheme, the modified oracle is also capable of computing f(x) for a given x, which is not possible with earlier versions used in recent NMR and optics implementations of the algorithm.
Naseri et al. [Phys. Rev. A 106, 062429 (2022); arXiv:2205.13610] studied which quantum resources in initial states are essential for the probabilistic Bernstein-Vazirani (BV) algorithm, defining its performance as the optimal average success probability over all measurements. In this work, we consider a variant of BV algorithm, which is called the initialization-free (IF) BV algorithm, in which an arbitrary ancilla state as the oracle register is allowed, to improve the performance. We derive an explicit formula for the performance of the probabilistic IF-BV algorithm and obtain a necessary and sufficient condition for an initial state to achieve maximal performance. We further prove that, under a suitable ordering assumption on the coefficients of the initial state, the probabilistic IF-BV algorithm outperforms the standard probabilistic BV algorithm.
Quantum algorithms can outperform their classical counterparts in various tasks, the most prominent example being Shor's algorithm for efficient prime factorization on a quantum computer. It is clear that one of the reasons for the speedup is the superposition principle of quantum mechanics, which allows a quantum processor to be in a superposition of different states at the same time. While such a superposition can lead to entanglement across different qubits of the processors, there also exist quantum algorithms that outperform classical ones using superpositions of individual qubits without entangling them. As an example, the Bernstein-Vazirani algorithm allows one to determine a bit string encoded into an oracle. While the classical version of the algorithm requires multiple calls of the oracle to learn the bit string, a single query of the oracle is enough in the quantum case. In this article, we analyze in detail the quantum resources in the Bernstein-Vazirani algorithm. For this, we introduce and study its probabilistic version, where the goal is to guess the bit string after a single call of the oracle. We show that in the absence of entanglement, the performance of the algorithm is directly related to the amount of quantum coherence in the initial state. We further demonstrate that a large amount of entanglement in the initial state prevents the algorithm from achieving optimal performance. We also apply our methods to quantum computation with mixed states, proving that pseudopure states achieve optimal performance for a given purity in the Bernstein-Vazirani algorithm. We further investigate quantum resources in the one clean qubit model, showing that the model can exhibit speedup over any known classical algorithm even with an arbitrarily little amount of multipartite entanglement, general quantum correlations, and coherence.
The essential operations of a quantum computer can all be accomplished using only standard linear optical elements (e.g., beamsplitters, waveplates, polarizers, etc.), with the individual bits represented by different spatial orpolarization degrees of freedom. The difference from a genuine quantum computer with distinct entangleable registers is that the optical implementation requires a number of elements which grows exponentially with the number of bits. However, by “compiling” the code, and making multiple use of redundant components, the required number of elements can be substantially reduced, allowing the realization of quantum algorithms involving several bits. Here we present a simple optical implementation of Grover’s algorithm for efficiently searching a database. In our example a database of four elements is searched with a single query, in contrast to the classical expected value of 2.25 queries. It is seen that the “quantum” computer in this case is no more than an interferometer, albeit a complicated one. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
The complexity of certain classical computer algorithms can be reduced by a quantum algorithm completing the same task. We examine the implementation of the Bernstein–Vazirani algorithm. It finds the hidden n-bit string s from the function fs(x)=sx that takes an n-bit input string x and outputs one bit, the dot product. This algorithm reduces the complexity from n queries for the best classical algorithm to just one. Though the quantum algorithm theoretically always gives the correct string, in practice, factors such as decoherence of the physical qubits due to external noise reduce the algorithm’s accuracy. By implementing the algorithm on the IBM 5-qubit and 14-qubit quantum computers, we are able to analyze correlations between the accuracy of the results and the properties of the physical qubits used. Not all qubits are pairwise connected, nor do they have the same coherence times. Using Python to build the quantum circuits, we create several implementations of the circuit with different qubits. We establish that 1/T1, 1/T2, and gate errors are positively correlated with calculation errors. Consequently, we observe that the 14-qubit quantum computer, on average, is more prone to errors than the 5-qubit quantum computer.