250 citations · 895 across the 20 of their papers we have counts for
21 papers
Constrained minimax approximation for quantum signal processing
Yulong Dong, James B. Larsen, Lin Lin +1
Quantum signal processing (QSP) provides a simple and efficient framework for implementing polynomial transformations using quantum circuits. Its classical design stage leads to a…
Accelerating quantum Gibbs sampling without quantum walks
Jiaqi Leng, Jiaqing Jiang, Lin Lin
Szegedy's quantum walk quadratically accelerates reversible classical Markov chains, but extending this mechanism to efficiently implementable quantum Gibbs samplers has remained c…
Single-ancilla ground state preparation via Lindbladians
Zhiyan Ding, Chi-Fang Chen, Lin Lin
We design a quantum algorithm for ground state preparation in the early fault tolerant regime. As a Monte Carlo-style quantum algorithm, our method features a Lindbladian where the…
Robust iterative method for symmetric quantum signal processing in all parameter regimes
Yulong Dong, Lin Lin, Hongkang Ni +1
This paper addresses the problem of solving nonlinear systems in the context of symmetric quantum signal processing (QSP), a powerful technique for implementing matrix functions on…
Dense outputs from quantum simulations
Jin-Peng Liu, Lin Lin
The quantum dense output problem is the process of evaluating time-accumulated observables from time-dependent quantum dynamics using quantum computers. This problem arises frequen…
Robust ground-state energy estimation under depolarizing noise
Zhiyan Ding, Yulong Dong, Yu Tong +1
We present a novel ground-state energy estimation algorithm that is robust under global depolarizing error channels. Building upon the recently developed Quantum Exponential Least…
Anti-symmetric Barron functions and their approximation with sums of determinants
Nilin Abrahamsen, Lin Lin
A fundamental problem in quantum physics is to encode functions that are completely anti-symmetric under permutations of identical particles. The Barron space consists of high-dime…
Convergence of variational Monte Carlo simulation and scale-invariant pre-training
Nilin Abrahamsen, Zhiyan Ding, Gil Goldshlager +1
We provide theoretical convergence bounds for the variational Monte Carlo (VMC) method as applied to optimize neural network wave functions for the electronic structure problem. We…
Simultaneous estimation of multiple eigenvalues with short-depth quantum circuit on early fault-tolerant quantum computers
Zhiyan Ding, Lin Lin
We introduce a multi-modal, multi-level quantum complex exponential least squares (MM-QCELS) method to simultaneously estimate multiple eigenvalues of a quantum Hamiltonian on earl…
Linear combination of Hamiltonian simulation for nonunitary dynamics with optimal state preparation cost
Dong An, Jin-Peng Liu, Lin Lin
We propose a simple method for simulating a general class of non-unitary dynamics as a linear combination of Hamiltonian simulation (LCHS) problems. LCHS does not rely on convertin…
Even shorter quantum circuit for phase estimation on early fault-tolerant quantum computers with applications to ground-state energy estimation
Zhiyan Ding, Lin Lin
We develop a phase estimation method with a distinct feature: its maximal runtime (which determines the circuit depth) is , where is the target precision, and the preconst…
Infinite quantum signal processing
Yulong Dong, Lin Lin, Hongkang Ni +1
Quantum signal processing (QSP) represents a real scalar polynomial of degree using a product of unitary matrices of size , parameterized by real numbers cal…
Time-marching based quantum solvers for time-dependent linear differential equations
Di Fang, Lin Lin, Yu Tong
The time-marching strategy, which propagates the solution from one time step to the next, is a natural strategy for solving time-dependent differential equations on classical compu…
Is there evidence for exponential quantum advantage in quantum chemistry?
Seunghoon Lee, Joonho Lee, Huanchen Zhai +15
The idea to use quantum mechanical devices to simulate other quantum systems is commonly ascribed to Feynman. Since the original suggestion, concrete proposals have appeared for si…
Efficient anti-symmetrization of a neural network layer by taming the sign problem
Nilin Abrahamsen, Lin Lin
Explicit antisymmetrization of a neural network is a potential candidate for a universal function approximator for generic antisymmetric functions, which are ubiquitous in quantum…
Ground state preparation and energy estimation on early fault-tolerant quantum computers via quantum eigenvalue transformation of unitary matrices
Yulong Dong, Lin Lin, Yu Tong
Under suitable assumptions, the algorithms in [Lin, Tong, Quantum 2020] can estimate the ground state energy and prepare the ground state of a quantum Hamiltonian with near-optimal…
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…
Lecture Notes on Quantum Algorithms for Scientific Computation
Lin Lin
This is a set of lecture notes used in a graduate topic class in applied mathematics called ``Quantum Algorithms for Scientific Computation'' at the Department of Mathematics, UC B…
Time-dependent Hamiltonian Simulation of Highly Oscillatory Dynamics and Superconvergence for Schrödinger Equation
Dong An, Di Fang, Lin Lin
We propose a simple quantum algorithm for simulating highly oscillatory quantum dynamics, which does not require complicated quantum control logic for handling time-ordering operat…
On the energy landscape of symmetric quantum signal processing
Jiasu Wang, Yulong Dong, Lin Lin
Symmetric quantum signal processing provides a parameterized representation of a real polynomial, which can be translated into an efficient quantum circuit for performing a wide ra…
A quantum hamiltonian simulation benchmark
Yulong Dong, K. Birgitta Whaley, Lin Lin
Hamiltonian simulation is one of the most important problems in quantum computation, and quantum singular value transformation (QSVT) is an efficient way to simulate a general clas…