VQE method: a short survey and recent developments

نویسندگان

چکیده

Abstract The variational quantum eigensolver (VQE) is a method that uses hybrid quantum-classical computational approach to find eigenvalues of Hamiltonian. VQE has been proposed as an alternative fully algorithms such phase estimation (QPE) because require hardware will not be accessible in the near future. successfully applied solve electronic Schrödinger equation for variety small molecules. However, scalability this limited by two factors: complexity circuits and classical optimization problem. Both these factors are affected choice ansatz used represent trial wave function. Hence, construction efficient active area research. Put another way, modern computers capable executing deep produced using currently available ansatzes problems map onto more than several qubits. In review, we present recent developments field designing fall into categories—chemistry–inspired hardware–efficient—that produce easier run on hardware. We discuss shortfalls originally formulated simulations, how they addressed sophisticated methods, potential ways further improvements.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Recent Developments in Vacation Queueing Models : A Short Survey

Queueing systems with server vacations (server’s performing non-queueing jobs) have been studied extensively since the late 70’s. A considerable number of works in this area were completed in the early 80’s and surveyed by Doshi in 1986. As an extension to the classical queueing system, allowing idle servers to work on non-queueing jobs makes the vacation models more applicable in a variety of ...

متن کامل

Survey of Recent Developments

Bulletin of Indonesian Economic Studies, Vol. 37, No. 1, 2001: 7–41 ISSN 0007-4918 print/ISSN 1472-7234 online/01/010007-35 © 2001 Indonesia Project ANU SURVEY OF RECENT DEVELOPMENTS

متن کامل

Recent developments in kernelization: A survey

Kernelization is a formalization of efficient preprocessing, aimed mainly at combinatorially hard problems. Empirically, preprocessing is highly successful in practice, e.g., in state-of-the-art SAT and ILP solvers. The notion of kernelization from parameterized complexity makes it possible to rigorously prove upper and lower bounds on, e.g., the maximum output size of a preprocessing in terms ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Materials Theory

سال: 2022

ISSN: ['2509-8012']

DOI: https://doi.org/10.1186/s41313-021-00032-6