• Corpus ID: 239885369

A Novel AQC Factoring Algorithm

@inproceedings{Crawford2021ANA,
  title={A Novel AQC Factoring Algorithm},
  author={Matthew Brendan Crawford},
  year={2021}
}
Due to recent technological advances, actual quantum devices are being constructed and used to perform computations. As a result, many classical problems are being restated so as to be solved on quantum computers. Some examples include satisfiability problems [3]; clustering and classification, [6], [7], [11]; protein folding [9]; and simulating many-body systems [1]. Converting these classical problems to a quantum framework is not always straightforward. As such, instances where researchers… 

References

SHOWING 1-10 OF 13 REFERENCES
Quantum-Assisted Clustering Algorithms for NISQ-Era Devices
TLDR
Several hybrid quantum-classical clustering algorithms that can be employed as subroutines on small, NISQ-era devices, and do not require a black-box oracle are developed.
Quantum search by local adiabatic evolution
The adiabatic theorem has been recently used to design quantum algorithms of a new kind, where the quantum computer evolves slowly enough so that it remains near its instantaneous ground state, which
Quantum Computation by Adiabatic Evolution
We give a quantum algorithm for solving instances of the satisfiability problem, based on adiabatic evolution. The evolution of the quantum state is governed by a time-dependent Hamiltonian that
A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
TLDR
For the small examples that the authors could simulate, the quantum adiabatic algorithm worked well, providing evidence that quantum computers (if large ones can be built) may be able to outperform ordinary computers on hard sets of instances of NP-complete problems.
Finding low-energy conformations of lattice protein models by quantum annealing
TLDR
This report presents a benchmark implementation of quantum annealing for lattice protein folding problems (six different experiments up to 81 superconducting quantum bits) and paves the way towards studying optimization problems in biophysics and statistical mechanics using quantum devices.
Adiabatic optimization versus diffusion Monte Carlo methods
Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as
Quantum algorithms for supervised and unsupervised machine learning
Machine-learning tasks frequently involve problems of manipulating and classifying large numbers of vectors in high-dimensional spaces. Classical algorithms for solving such problems typically take
Quantum Principal Component Analysis
Principal component analysis is a multivariate statistical method frequently used in science and engineering to reduce the dimension of a problem or extract the most significant features from a
Quantum simulations with ultracold quantum gases
Experiments with ultracold quantum gases provide a platform for creating many-body systems that can be well controlled and whose parameters can be tuned over a wide range. These properties put these
Beweis des Adiabatensatzes
ZusammenfassungDer Adiabatensatz in der neuen Quantenmechanik wird für den Fall des Punktspektrums in mathematisch strenger Weise bewiesen, wobei er sich auch bei einer vorübergehenden Entartung des
...
1
2
...