Challenges and opportunities in quantum machine learning
At the intersection of machine learning and quantum computing, quantum machine learning
has the potential of accelerating data analysis, especially for quantum data, with …
has the potential of accelerating data analysis, especially for quantum data, with …
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 …
A survey of quantum computing for finance
Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade and have transformative impact on numerous industry sectors …
computers during this decade and have transformative impact on numerous industry sectors …
[HTML][HTML] A threshold for quantum advantage in derivative pricing
We give an upper bound on the resources required for valuable quantum advantage in
pricing derivatives. To do so, we give the first complete resource estimates for useful …
pricing derivatives. To do so, we give the first complete resource estimates for useful …
Nearest centroid classification on a trapped ion quantum computer
Quantum machine learning has seen considerable theoretical and practical developments
in recent years and has become a promising area for finding real world applications of …
in recent years and has become a promising area for finding real world applications of …
Basic elements for simulations of standard-model physics with quantum annealers: Multigrid and clock states
We explore the potential of D-Wave's quantum annealers for computing some of the basic
components required for quantum simulations of standard model physics. By implementing …
components required for quantum simulations of standard model physics. By implementing …
Low depth algorithms for quantum amplitude estimation
We design and analyze two new low depth algorithms for amplitude estimation (AE)
achieving an optimal tradeoff between the quantum speedup and circuit depth. For $\beta\in …
achieving an optimal tradeoff between the quantum speedup and circuit depth. For $\beta\in …
Portfolio optimization with digitized counterdiabatic quantum algorithms
We consider digitized-counterdiabatic quantum computing as an advanced paradigm to
approach quantum advantage for industrial applications in the NISQ era. We apply this …
approach quantum advantage for industrial applications in the NISQ era. We apply this …
Quantum computational finance: quantum algorithm for portfolio optimization
P Rebentrost, S Lloyd - KI-Künstliche Intelligenz, 2024 - Springer
We present a quantum algorithm for portfolio optimization. We discuss the market data input
of asset prices, the processing of such data via quantum operations, and the output of …
of asset prices, the processing of such data via quantum operations, and the output of …
Quantum algorithm for the Navier–Stokes equations by using the streamfunction-vorticity formulation and the lattice Boltzmann method
B Ljubomir - International Journal of Quantum Information, 2022 - World Scientific
In this paper, a new algorithm for solving the Navier–Stokes equations (NSE) on a quantum
device is presented. For the fluid flow equations, the stream function-vorticity formulation is …
device is presented. For the fluid flow equations, the stream function-vorticity formulation is …