Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userStrange attractor simulated on a quantum computer
117
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We show that dissipative classical dynamics converging to a strange attractor can be simulated on a quantum computer. Such quantum computations allow to investigate efficiently the small scale structure of strange attractors, yielding new information inaccessible to classical computers. This opens new possibilities for quantum simulations of various dissipative processes in nature.
rate research
Read More
Quantum computers are invaluable tools to explore the properties of complex quantum systems. We show that dynamical localization of the quantum sawtooth map, a highly sensitive quantum coherent phenomenon, can be simulated on actual, small-scale quantum processors. Our results demonstrate that quantum computing of dynamical localization may become a convenient tool for evaluating advances in quantum hardware performances.
We present efficient quantum algorithms for simulating time-dependent Hamiltonian evolution of general input states using an oracular model of a quantum computer. Our algorithms use either constant or adaptively chosen time steps and are significant because they are the first to have time-complexities that are comparable to the best known methods for simulating time-independent Hamiltonian evolution, given appropriate smoothness criteria on the Hamiltonian are satisfied. We provide a thorough cost analysis of these algorithms that considers discretizion errors in both the time and the representation of the Hamiltonian. In addition, we provide the first upper bounds for the error in Lie-Trotter-Suzuki approximations to unitary evolution operators, that use adaptively chosen time steps.
For variational algorithms on the near term quantum computing hardware, it is highly desirable to use very accurate ansatze with low implementation cost. Recent studies have shown that the antisymmetrized geminal power (AGP) wavefunction can be an excellent starting point for ansatze describing systems with strong pairing correlations, as those occurring in superconductors. In this work, we show how AGP can be efficiently implemented on a quantum computer with circuit depth, number of CNOTs, and number of measurements being linear in system size. Using AGP as the initial reference, we propose and implement a unitary correlator on AGP and benchmark it on the ground state of the pairing Hamiltonian. The results show highly accurate ground state energies in all correlation regimes of this model Hamiltonian.
We consider the feasibility of studying the anisotropic Heisenberg quantum spin chain with the Variational Quantum Eigensolver (VQE) algorithm, by treating Bethe states as variational states, and Bethe roots as variational parameters. For short chains, we construct exact one-magnon trial states that are functions of the variational parameter, and implement the VQE calculations in Qiskit. However, exact multi-magnon trial states appear to be out out of reach.
Predicting antibody structure plays a central role in drug development. The structural region responsible for most of the binding and function of an antibody, namely the H3 loop, is also the most variable and hard to predict to atomic accuracy. The desire to facilitate and accelerate the engineering of therapeutic antibodies has led to the development of computational methodologies aimed at antibody and H3 loop structure prediction. However, such approaches can be computationally demanding and time consuming, and still limited in their prediction accuracy. While quantum computing has been recently proposed for protein folding problems, antibody H3 loop modelling is still unexplored. In this paper we discuss the potential of quantum computing for fast and high-accuracy loop modelling with possible direct applications to pharmaceutical research. We propose a framework based on quantum Markov chain Monte Carlo for modelling H3 loops on a fault-tolerant quantum computer, and estimate the resources required for this algorithm to run. Our results indicate that further improvements in both hardware and algorithm design will be necessary for a practical advantage to be realized on a quantum computer. However, beyond loop modelling, our approach is also applicable to more general protein folding problems, and we believe that the end-to-end framework and analysis presented here can serve as a useful starting point for further improvements.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
