This paper investigates numerically a phenomenon which can be used to transport a single q-bit down a J1-J2 Heisenberg spin chain using a quantum adiabatic process. The motivation for investigating such pro-cesses comes from the idea that this method of transport could poten-tially be used as a means of sending data to various parts of a quantum computer made of artificial spins, and that this method could take advan-tage of the easily prepared ground state at the so called Majumdar-Ghosh point. We examine several annealing protocols for this process and find similar results for all of them. The annealing process works well up to a critical frustration threshold. There is also a brief section examining what other models this protocol could ...
In this thesis we summarize the principles of quantum computing. We specifically consider adiabatic ...
We give an overview of a quantum adiabatic algorithm for Hilbert's tenth problem, including some dis...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
The shift of interest from general purpose quantum computers to adiabatic quantum computing or quant...
Adiabatic theorem of quantum mechanics was used by E. Farhi, J. Goldstone, S. Gutmann and M. Sipser ...
Transporting quantum information is an important prerequisite for quantum computers. We study how th...
Quantum computing seeks to use the powers of quantum mechanics to accomplish tasks that classical co...
Recent experiments with increasingly larger numbers of qubits have sparked renewed interest in adiab...
Solid state quantum computer architectures are often touted as inherently scalable on the basis of p...
Training deep learning networks is a difficult task due to computational complexity, and this is tra...
Quantum annealing is a new-generation tool of information technology, which helps in solving combina...
We review here some recent work in the field of quantum annealing, alias adiabatic quantum computati...
Since the appearance of Shor's factoring algorithm in 1994, the search for novel quantum computer al...
2013-05-28This thesis deals with e ffects on antiferromagnetic Heisenberg spin chains and clusters w...
Quantum adiabatic algorithm is a method of solving computational problems by evolving the ground sta...
In this thesis we summarize the principles of quantum computing. We specifically consider adiabatic ...
We give an overview of a quantum adiabatic algorithm for Hilbert's tenth problem, including some dis...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...
The shift of interest from general purpose quantum computers to adiabatic quantum computing or quant...
Adiabatic theorem of quantum mechanics was used by E. Farhi, J. Goldstone, S. Gutmann and M. Sipser ...
Transporting quantum information is an important prerequisite for quantum computers. We study how th...
Quantum computing seeks to use the powers of quantum mechanics to accomplish tasks that classical co...
Recent experiments with increasingly larger numbers of qubits have sparked renewed interest in adiab...
Solid state quantum computer architectures are often touted as inherently scalable on the basis of p...
Training deep learning networks is a difficult task due to computational complexity, and this is tra...
Quantum annealing is a new-generation tool of information technology, which helps in solving combina...
We review here some recent work in the field of quantum annealing, alias adiabatic quantum computati...
Since the appearance of Shor's factoring algorithm in 1994, the search for novel quantum computer al...
2013-05-28This thesis deals with e ffects on antiferromagnetic Heisenberg spin chains and clusters w...
Quantum adiabatic algorithm is a method of solving computational problems by evolving the ground sta...
In this thesis we summarize the principles of quantum computing. We specifically consider adiabatic ...
We give an overview of a quantum adiabatic algorithm for Hilbert's tenth problem, including some dis...
Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. ...