Казанский (Приволжский) федеральный университет, КФУ
КАЗАНСКИЙ
ФЕДЕРАЛЬНЫЙ УНИВЕРСИТЕТ
 
QUANTUM ALGORITHMS FOR THE SHORTEST COMMON SUPERSTRING AND TEXT ASSEMBLING PROBLEMS
Форма представленияСтатьи в зарубежных журналах и сборниках
Год публикации2024
Языканглийский
  • Хадиев Камиль Равилевич, автор
  • Библиографическое описание на языке оригинала Khadiev K, Bosch Machado C.M, Chen Z, Wu J, QUANTUM ALGORITHMS FOR THE SHORTEST COMMON SUPERSTRING AND TEXT ASSEMBLING PROBLEMS//Quantum Information and Computation. - 2024. - Vol.24, Is.3-4. - P.267-294.
    Аннотация In this paper, we consider two versions of the Text Assembling problem. We are given a sequence of strings s1, …, sn of total length L that is a dictionary, and a string t of length m that is a text. The first version of the problem is assembling t from the dictionary. The second version is the “Shortest Superstring Problem”(SSP) or the “Shortest Common Superstring Problem”(SCS). In this case, t is not given, and we should construct the shortest string (we call it superstring) that contains each string from the given sequence as a substring. These problems are connected with the sequence assembly method for reconstructing a long DNA sequence from small fragments. For both problems, we suggest new quantum algorithms that work better than their classical counterparts. In the first case, we present a quantum algorithm with O(m+log m√nL) query complexity. In the case of SSP, we present a quantum algorithm with Õ(n^3*1.728^n + L + n^1.5√L) query complexity. Here Õ hides not only constants but logarithms of L and n also.
    Ключевые слова quantum algorithms, shortest common superstring, NP-complete problems
    Название журнала Quantum Information and Computation
    URL https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188899281&doi=10.26421%2fQIC24.3-4-4&partnerID=40&md5=3d6712dd95d5d0ec6d918a0c95fd9bd4
    Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку https://repository.kpfu.ru/?p_id=297969

    Полная запись метаданных