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 …
Quantum simulation of partial differential equations: Applications and detailed analysis
We study a recently introduced simple method [S. **, N. Liu, and Y. Yu, Quantum simulation
of partial differential equations via Schrödingerisation, arxiv: 2212.13969] for solving …
of partial differential equations via Schrödingerisation, arxiv: 2212.13969] for solving …
Quantum simulation of partial differential equations via schrodingerisation: technical details
We study a new method-called Schrodingerisation introduced in [**, Liu, Yu, arxiv:
2212.13969]-for solving general linear partial differential equations with quantum simulation …
2212.13969]-for solving general linear partial differential equations with quantum simulation …
Quantum algorithms for approximate function loading
Loading classical data into quantum computers represents an essential stage in many
relevant quantum algorithms, especially in the field of quantum machine learning. Therefore …
relevant quantum algorithms, especially in the field of quantum machine learning. Therefore …
Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions
The ability to efficiently load functions on quantum computers with high fidelity is essential
for many quantum algorithms, including those for solving partial differential equations and …
for many quantum algorithms, including those for solving partial differential equations and …
Analog quantum simulation of partial differential equations
Quantum simulators were originally proposed for simulating one partial differential equation
in particular--Schrodinger's equation. Can quantum simulators also efficiently simulate other …
in particular--Schrodinger's equation. Can quantum simulators also efficiently simulate other …
Quantum variational solving of nonlinear and multidimensional partial differential equations
A variational quantum algorithm for numerically solving partial differential equations (PDEs)
on a quantum computer was proposed by Lubasch et al.[Phys. Rev. A 101, 010301 …
on a quantum computer was proposed by Lubasch et al.[Phys. Rev. A 101, 010301 …
Robuststate: Boosting fidelity of quantum state preparation via noise-aware variational training
Quantum state preparation, a crucial subroutine in quantum computing, involves generating
a target quantum state from initialized qubits. Arbitrary state preparation algorithms can be …
a target quantum state from initialized qubits. Arbitrary state preparation algorithms can be …
Protocols for trainable and differentiable quantum generative modeling
We propose an approach for learning probability distributions as differentiable quantum
circuits (DQC) that enable efficient quantum generative modeling (QGM) and synthetic data …
circuits (DQC) that enable efficient quantum generative modeling (QGM) and synthetic data …
Quantum approximated cloning-assisted density matrix exponentiation
Classical information loading is an essential task for many processing quantum algorithms,
constituting a cornerstone in the field of quantum machine learning. In particular, the …
constituting a cornerstone in the field of quantum machine learning. In particular, the …