In this paper, we study the cyclicity of binary group codes, identifying them as ideals in a group algebra. We focus on the construction of ω|ω¯ codes, proving that they are self-dual group codes over the abelian group C2×Ck. We demonstrate that for even integers k>2, if the polynomial xk-1 splits into self-reciprocal irreducible factors, these codes are not permutationally equivalent to any cyclic code. Additionally, we present computational results for binary group codes of length n<24 using the MAGMA software (V2.29-4). These results confirm that while all cyclic codes in this range are equivalent to abelian group codes, there exist non-cyclic group codes that cannot be realized as ideals in a cyclic group algebra, highlighting the strictly larger scope of the class of group codes.

While abelian group codes are classically known to be asymptotically bad—constrained by strict structural limitations such as the Square-Root and Logarithmic barriers—this traditional, infinite-length perspective obscures their rich mathematical behavior at finite block lengths. In this contribution, we move beyond the standard paradigm of asymptotic metrics to investigate the non-asymptotic goodness of abelian codes. We introduce the framework of (F, G)-goodness and a machinery that enables us to rigorously classify abelian codes into distinct performance “tiers”.

The quantum gate teleportation mechanism allows for the fault-tolerant implementation of "Clifford hierarchies" of gates assuming, among other things, a fault-tolerant implementation of the Pauli gates. We discuss how this method can be extended to assume the fault-tolerant implementation of any orthogonal unitary basis of operators, in such a way that each of these bases can be used to implement its own hierarchy of gates. Noticing that all of these hierarchies are defined through the same algebraic construction, we study this construction from a group-theoretic perspective. This allows us to deduce general results concerning all the hierarchies. We also discuss alternative hierarchies, study their properties, and compute some of their first few levels.

The so-called Hamming distance measures the difference between two binary strings A and B. In simplified form, it measures the number of changes in A to get B. This type of distance is very useful in classical computing in applications such as error correction. It is also advantageous in quantum computing, being for example widely used in quantum machine learning. Since current quantum computers have limited resources, this type of distance is particularly attractive because it can be computed using fewer qubits and operations than other distances such as Euclidean or Manhattan distances. In this paper, two circuits for calculating Hamming distances using exclusively Clifford+T gates are presented. The aim of both circuits is to reduce the quantum cost and number of T gates needed to compute the Hamming distance. The T gate is more expensive than the other gates, so this reduction will have a significant impact on the total cost of the circuits. Furthermore, the proposed circuits are implemented using only Clifford+T gates. The circuits implemented exclusively with this group of gates are compatible with proven error detection and correction codes.

Quantum abstract detecting systems (QADS) were introduced as a common framework for the study and design of detecting algorithms in a quantum computing setting. In this paper, we introduce new families of such QADS, known as combinatorial and rotational, which, respectively, generalize detecting systems based on single qubit controlled gates and on Grover’s algorithm. We study the algorithmic closure of each family and prove that some of these QADS are equivalent (in the sense of having the same detection rate) to others constructed from tensor product of controlled operators and their square roots. We also apply the combinatorial QADS construction to a problem of eigenvalue decision, and to a problem of phase estimation.

One of the strategies to reduce the complexity of N -body simulations is the computation of the neighbour list. However, this list needs to be updated from time to time, with a high computational cost. This paper focuses on the use of quantum computing to accelerate such a computation. Our proposal is based on a well-known oracular quantum algorithm (Grover). We introduce an efficient quantum circuit to build the oracle that marks pairs of closed bodies, and we provide three novel algorithms to calculate the neighbour list under several hypotheses which take into account a-priori information of the system. We also describe a decision methodology for the actual use of the proposed quantum algorithms. The performance of the algorithms is tested with a statistical simulation of the oracle, where a fixed number of pairs of bodies are set as neighbours. A statistical analysis of the number of oracle queries is carried out. The results obtained with our simulations indicate that when the density of bodies is low, our algorithms clearly outperform the best classical algorithm in terms of oracle queries.

Finite semifields Rúa, I.are finite nonassociative rings with an identity element, such that the set of nonzero elements is a loop under the product. Their number of elements is a prime power, known as order. They were considered first by Dickson [2], and studied by Albert [1] and Knuth [3]. Finite semifields of order 16 have been classified by Kleinfeld in [7], of order 32 by Knuth in [3], and by Walker in [8]. The classification of finite semifields can be rephrased as a problem of finding certain sets of matrices, which can be solved by computer search. So, classification of semifields with high order such as 64, was achieved by Rúa, Combarro, Ranilla in [4], or of order 243 by Rúa, Combarro, Ranilla in [5], and of order 81 by Dempwolff [9]. Based on this approach, classification of finite semifields of any order via a quantum procedure is possible. We present quantum techniques for the classification of semifields with 8 and 16 elements with their respective simulations, based on Grover’s quantum search algorithm.

When classifying a collection of finite algebras (for instance, in the computational classification of finite semifields), an important task is the determination of substructures such as the right, middle, and left nuclei, the nucleus, and the center. Finding these structures may become computationally expensive when there is no additional information about the algebra properties. In this paper, we introduce quantum algorithms than solve this task efficiently, by formulating it as an instance of the Hidden Subgroup Problem (HSP) {over Abelian groups}. We give detailed constructions of the quantum circuits involved in the process and prove that the overall (quantum) complexity of our algorithm is polynomial in the dimension of the algebra, while a similar approach with classical computers would require an exponential number of queries to the HSP function

In this work we present a standard model for Galois rings based on the standard model of their residual fields, that is, a a sequence of Galois rings starting with ℤ_p^r that coves all the Galois rings with that characteristic ring and such that there is an algorithm producing each member of the sequence whose input is the size of the required ring.

Current quantum computers have a limited number of resources and are heavily affected by internal and external noise. Therefore, small, noise-tolerant circuits are of great interest. With regard to circuit size, it is especially important to reduce the number of required qubits. Concerning to fault-tolerance, circuits entirely built with Clifford+T gates allow the use of error correction codes. However, the T-gate has an excessive cost, so circuits with a high number of T-gates should be avoided. This work focuses on optimising in such terms an operation that is widely used in larger circuits and algorithms: the calculation of the absolute-value of two’s complement encoded integers. The proposed circuit halves the number of required T gates with respect to the best circuit currently available in the literature. Moreover, our circuit requires at least 2 qubits less than the other circuits for such an operation.

The Quantum Approximate Optimization Algorithm (QAOA) was proposed as a way of finding good, approximate solutions to hard combinatorial optimization problems. QAOA uses a hybrid approach. A parametrized quantum state is repeatedly prepared and measured on a quantum computer to estimate its average energy. Then, a classical optimizer, running in a classical computer, uses such information to decide on the new parameters that are then provided to the quantum computer. This process is iterated until some convergence criteria are met. Theoretically, almost all classical minimizers can be used in the hybrid scheme. However, their behaviour can vary greatly in both the quality of the final solution and the time they take to find it. In this work, we study the performance of twelve different classical optimizers when used with QAOA to solve the maximum cut problem in graphs. We conduct a thorough set of tests on a quantum simulator both, with and without noise, and present results that show that some optimizers can be hundreds of times more efficient than others in some cases.

The algorithms that best demonstrate the potential of quantum computing are Shor’s algorithm and Grover’s algorithm. To this day, new evidence continues to emerge in the form of algorithms or ingenious applications that increase the field of application of this type of computing. However, given the limited number of qubits in current quantum computers, and also the noise problems they currently suffer from, implementing optimized circuits that allow us to take full advantage of the available resources, as well as detecting and correcting the errors caused by this noise, is a priority. In this work we present several leading zero detector circuits for quantum computers and simulators, optimized in terms of noise tolerance and number of qubits. These circuits are a fundamental part in major circuits that perform operations as important and basic in computation as addition and division.

In 1985, Gabidulin introduced the rank metric in coding theory over finite fields, and used this kind of codes in a McEliece cryptosystem, six years later. In this paper, we consider rank metric codes over Galois rings. We propose a suitable metric for codes over such rings, and show its main properties. With this metric, we define Gabidulin codes over Galois rings, propose an efficient decoding algorithm for them, and hint their cryptographic application.

In this paper, we introduce and study the quantum measurement detection algorithms (QMDA), whose objective is to detect whether unwanted measurements are being taken in a quantum circuit or not by applying the Zeno effect. A QMDA is a quantum circuit that includes three unitary matrices, one of them being applied numerous times consecutively, and whose initial state is fixed when no foreign measurements occur. One example is the Elitzur–Vaidman bomb tester, which is generalized by the QMDA definition, allowing the detection of measurements that are taken in an unknown basis and in circuits with an arbitrary number of qubits. We prove some key properties and limitations of these algorithms, as well as studying the performance of the Elitzur–Vaidman bomb tester and its possible improvements. Some extensions of the definition would lead to algorithms such as the counterfactual communication one.

Abstract The NP-hardness of the Minimum Distance Decoding Problem (MDDP) is the core of the McEliece cryptosystem. The difficulty of decoding a received word to the closest codeword in a given arbitrary code is key to its security. Related to the MDDP is the Coset Leader Problem (CLP), which consists in finding a word of a given syndrome and minimum Hamming weight. Both can be modelled as optimization problems, and solved using the Quantum Approximate Optimization Algorithm (QAOA), a well-known hybrid quantum- classical algorithm. In this paper, we model both the MDDP and CLP for linear codes over arbitrary m−ary alphabets, we make the theoretical analysis of the first level for the binary CLP problem, and introduce some experiments to test its performance. The experiments were carried out on both quantum computer simulators and real quantum devices, and use codes of different lengths and different depths of the QAOA.

Two of the most well-known quantum algorithms, those introduced by Deutsch–Jozsa and Bernstein–Vazirani, can solve promise problems with just one function query, showing an oracular separation with deterministic classical algorithms. In this work, we generalise those methods to study a family of quantum algorithms that can, with just one query, exactly solve promise problems stated over Boolean functions. We also show that these problems can be naturally ordered, inducing a partially ordered set of promise problems. We study the properties of such a poset, showing that the Deutsch–Jozsa and Bernstein–Vazirani problems are, in a certain sense, extremal problems in it, determining some of its automorphisms and proving that it is connected. We also prove that, for the problems in the poset, the corresponding classical query complexities can take any value between 1 and 2^n-1+1 .

The standard description of a quantum algorithm consists in three steps. First, encoding the data in a suitable initial quantum state. Second, driving such a state by a convenient sequence of unitary transformations until a final quantum state is reached. Third, measuring the final state and use such a measurement to solve the problem the quantum algorithm was designed for. An alternative description is provided by the stabilizer formalism, which was originally introduced in connection with quantum error correcting codes. In this paradigm, the focus is on the subgroup of elements of the Pauli group stabilizing the initial quantum state, and the transformations that such a subgroup experiments along the algorithm. In this work, we provide an explanation of two foundational quantum algorithms (Bernstein-Vazinari and Deustch-Josza) based on such a quantum stabilizer formalism. Doing so, we provide a better understanding and insight into both procedures which yield to see Bernstein-Vazirani as a particular case of Deustch-Josza, and to introduce a generalized version of Deustch-Josza algorithm.

The security of a broad family of coding-based cryptographic techniques relies on the hardness of the Syndrome Decoding Problem (SDP). In this problem, the aim is to find a word with a given syndrome and of Hamming weight smaller than a prefixed bound. If this last condition is replaced by “of minimum weight,” then we have the Coset Leader Problem (CLP), being Finding Low Weight Codewords (FLWC) a particular case (when the zero syndrome is considered). An algorithm that has been proposed in order to obtain approximate solutions of problems of these kind (NP-complete) is the Quantum Approximate Optimization Algorithm (QAOA), a variational hybrid quantum-classical algorithm. In this paper, we apply the QAOA to the CLP for binary linear codes. We model the problem, make the theoretical analysis the case of the first level, and introduce some experiments to test its performance. The experiments have been carried out on quantum computer simulators with codes of different lengths and QAOA of different depth.

Generating random numbers is important for many real-world applications, including cryptography, statistical sampling and Monte Carlo simulations. Quantum systems subject to a measurement produce random results via Born's rule, and thus it is natural to study the possibility of using such systems in order to generate high-quality random numbers. However, current quantum devices are subject to errors and noise, which can make the output bits deviate from the uniform distribution. In this work, we propose and analyse two protocols that can be used to increase the uniformity of the bits obtained when running a circuit with a Hadamard gate and a measurement in a noisy quantum computer. These protocols may be used prior to other standard processes, such as randomness amplification. We conduct experiments on both a quantum simulator and a real quantum computer, obtaining results that suggest that these protocols are useful to improve the probability of the generated bits passing statistical tests for uniformity.

In this paper, we study Quantum Abstract Detecting Systems (QADS), that generalize some key characteristics of the operators used in Grover’s algorithm, a wide variety of quantum walks and the quantum abstract search algorithm. A QADS is an algorithm that constructs a quantum state and a quantum operator that help testing whether a circuit-implemented boolean function f is identically zero. We also identify some relatively weak properties of QADS that lead to the construction of algorithms for the detection problem (i.e. determining whether there is a marked element in a given set). Our results provide not only a common framework to all the aforementioned search methods, and their transformation into algorithms for the detection problem, but also allow the development of new similar methods. As an example, we construct a modification of Grover’s algorithm (from the tensor product of controlled QADS) that shows improved detection probability.