Review of some existing QML frameworks and novel hybrid classical–quantum neural networks realising binary classification for the noisy datasets
One of the most promising areas of research to obtain practical advantage is Quantum
Machine Learning which was born as a result of cross-fertilisation of ideas between …
Machine Learning which was born as a result of cross-fertilisation of ideas between …
Capacity and quantum geometry of parametrized quantum circuits
To harness the potential of noisy intermediate-scale quantum devices, it is paramount to find
the best type of circuits to run hybrid quantum-classical algorithms. Key candidates are …
the best type of circuits to run hybrid quantum-classical algorithms. Key candidates are …
Optimal training of variational quantum algorithms without barren plateaus
T Haug, MS Kim - arxiv preprint arxiv:2104.14543, 2021 - arxiv.org
Variational quantum algorithms (VQAs) promise efficient use of near-term quantum
computers. However, training VQAs often requires an extensive amount of time and suffers …
computers. However, training VQAs often requires an extensive amount of time and suffers …
Generalized quantum assisted simulator
We provide a noisy intermediate-scale quantum framework for simulating the dynamics of
open quantum systems, generalized time evolution, non-linear differential equations and …
open quantum systems, generalized time evolution, non-linear differential equations and …
Avoiding local minima in variational quantum algorithms with neural networks
Variational Quantum Algorithms have emerged as a leading paradigm for near-term
quantum computation. In such algorithms, a parameterized quantum circuit is controlled via …
quantum computation. In such algorithms, a parameterized quantum circuit is controlled via …
NISQ Algorithm for Hamiltonian simulation via truncated Taylor series
Simulating the dynamics of many-body quantum systems is believed to be one of the first
fields that quantum computers can show a quantum advantage over classical computers …
fields that quantum computers can show a quantum advantage over classical computers …
Fast-forwarding with NISQ processors without feedback loop
Simulating quantum dynamics is expected to be performed more easily on a quantum
computer than on a classical computer. However, the currently available quantum devices …
computer than on a classical computer. However, the currently available quantum devices …
Binary classifiers for noisy datasets: a comparative study of existing quantum machine learning frameworks and some new approaches
One of the most promising areas of research to obtain practical advantage is Quantum
Machine Learning which was born as a result of cross-fertilisation of ideas between …
Machine Learning which was born as a result of cross-fertilisation of ideas between …
Qubit efficient quantum algorithms for the vehicle routing problem on quantum computers of the nisq era
ID Leonidas, A Dukakis, B Tan… - arxiv preprint arxiv …, 2023 - arxiv.org
The vehicle routing problem with time windows (VRPTW) is a classic optimization problem
that arises in many different areas, such as logistics and transportation. The goal of the …
that arises in many different areas, such as logistics and transportation. The goal of the …
Near-term quantum algorithm for solving the MaxCut problem with fewer quantum resources
X Zhao, Y Li, J Li, S Wang, S Wang, S Qin… - Physica A: Statistical …, 2024 - Elsevier
MaxCut is an NP-hard combinatorial optimization problem in graph theory. The quantum
approximate optimization algorithms (QAOAs) offer new methods for solving such problems …
approximate optimization algorithms (QAOAs) offer new methods for solving such problems …