45 citations · 138 across the 13 of their papers we have counts for
13 papers
Quantum Multiple Eigenvalue Gaussian filtered Search: an efficient and versatile quantum phase estimation method
Zhiyan Ding, Haoya Li, Lin Lin +3
Quantum phase estimation is one of the most powerful quantum primitives. This work proposes a new approach for the problem of multiple eigenvalue estimation: Quantum Multiple Eigen…
Quantum Hamiltonian Learning for the Fermi-Hubbard Model
Hongkang Ni, Haoya Li, Lexing Ying
This work proposes a protocol for Fermionic Hamiltonian learning. For the Hubbard model defined on a bounded-degree graph, the Heisenberg-limited scaling is achieved while allowing…
Heisenberg-limited Hamiltonian learning for interacting bosons
Haoya Li, Yu Tong, Hongkang Ni +2
We develop a protocol for learning a class of interacting bosonic Hamiltonians from dynamics with Heisenberg-limited scaling. For Hamiltonians with an underlying bounded-degree gra…
A note on spike localization for line spectrum estimation
Haoya Li, Hongkang Ni, Lexing Ying
This note considers the problem of approximating the locations of dominant spikes for a probability measure from noisy spectrum measurements under the condition of residue signal,…
On adaptive low-depth quantum algorithms for robust multiple-phase estimation
Haoya Li, Hongkang Ni, Lexing Ying
This paper is an algorithmic study of quantum phase estimation with multiple eigenvalues. We present robust multiple-phase estimation (RMPE) algorithms with Heisenberg-limited scal…
On low-depth algorithms for quantum phase estimation
Hongkang Ni, Haoya Li, Lexing Ying
Quantum phase estimation is one of the critical building blocks of quantum computing. For early fault-tolerant quantum devices, it is desirable for a quantum phase estimation algor…
On efficient quantum block encoding of pseudo-differential operators
Haoya Li, Hongkang Ni, Lexing Ying
Block encoding lies at the core of many existing quantum algorithms. Meanwhile, efficient and explicit block encodings of dense operators are commonly acknowledged as a challenging…
Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits
Jiahao Yao, Haoya Li, Marin Bukov +2
Variational quantum algorithms stand at the forefront of simulations on near-term and future fault-tolerant quantum devices. While most variational quantum algorithms involve only…
Accelerating Primal-dual Methods for Regularized Markov Decision Processes
Haoya Li, Hsiang-fu Yu, Lexing Ying +1
Entropy regularized Markov decision processes have been widely used in reinforcement learning. This paper is concerned with the primal-dual formulation of the entropy regularized p…
Approximate Newton policy gradient algorithms
Haoya Li, Samarth Gupta, Hsiangfu Yu +2
Policy gradient algorithms have been widely applied to Markov decision processes and reinforcement learning problems in recent years. Regularization with various entropy functions…
A semigroup method for high dimensional elliptic PDEs and eigenvalue problems based on neural networks
Haoya Li, Lexing Ying
In this paper, we propose a semigroup method for solving high-dimensional elliptic partial differential equations (PDEs) and the associated eigenvalue problems based on neural netw…
A semigroup method for high dimensional committor functions based on neural network
Haoya Li, Yuehaw Khoo, Yinuo Ren +1
This paper proposes a new method based on neural networks for computing the high-dimensional committor functions that satisfy Fokker-Planck equations. Instead of working with parti…
A Simple Multiscale Method for Mean Field Games
Haoya Li, Yuwei Fan, Lexing Ying
This paper proposes a multiscale method for solving the numerical solution of mean field games which accelerates the convergence and addresses the problem of determining the initia…