Quantum computing for finance
Quantum computers are expected to surpass the computational capabilities of classical
computers and have a transformative impact on numerous industry sectors. We present a …
computers and have a transformative impact on numerous industry sectors. We present a …
Challenges and opportunities in quantum optimization
Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …
force classical simulation. Interest in quantum algorithms has developed in many areas …
Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem
The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm
for solving optimization problems on quantum computers. However, the potential of QAOA to …
for solving optimization problems on quantum computers. However, the potential of QAOA to …
Quantum optimization: Potential, challenges, and the path forward
Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …
scale beyond brute force classical simulation. As such, a widespread interest in quantum …
Solving non-native combinatorial optimization problems using hybrid quantum-classical algorithms
Combinatorial optimization is a challenging problem applicable in a wide range of fields
from logistics to finance. Recently, quantum computing has been used to attempt to solve …
from logistics to finance. Recently, quantum computing has been used to attempt to solve …
Expressive variational quantum circuits provide inherent privacy in federated learning
Federated learning has emerged as a viable distributed solution to train machine learning
models without the actual need to share data with the central aggregator. However, standard …
models without the actual need to share data with the central aggregator. However, standard …
Utilizing modern computer architectures to solve mathematical optimization problems: A survey
Numerical algorithms to solve mathematical optimization problems efficiently are essential to
applications in many areas of engineering and computational science. To solve optimization …
applications in many areas of engineering and computational science. To solve optimization …
$ Des $-$ q $: a quantum algorithm to construct and efficiently retrain decision trees for regression and binary classification
Decision trees are widely used in machine learning due to their simplicity in construction
and interpretability. However, as data sizes grow, traditional methods for construction and …
and interpretability. However, as data sizes grow, traditional methods for construction and …
Solving QUBOs with a quantum-amenable branch and bound method
Due to the expected disparity in quantum vs. classical clock speeds, quantum advantage for
branch and bound algorithms is more likely achievable in settings involving large search …
branch and bound algorithms is more likely achievable in settings involving large search …
Discrete optimization: A quantum revolution?
We develop several quantum procedures and investigate their potential to solve discrete
optimization problems. First, we introduce a binary search procedure and illustrate how it …
optimization problems. First, we introduce a binary search procedure and illustrate how it …