Multi-level quantum signal processing with applications to ground state preparation using fast-forwarded Hamiltonian evolution
- URL: http://arxiv.org/abs/2406.02086v1
- Date: Tue, 4 Jun 2024 08:09:51 GMT
- Title: Multi-level quantum signal processing with applications to ground state preparation using fast-forwarded Hamiltonian evolution
- Authors: Yulong Dong, Lin Lin,
- Abstract summary: Preparation of the ground state of a Hamiltonian $H$ with a large spectral radius has applications in many areas.
We develop a multi-level Quantum Signal Processing (QSP)-based algorithm that exploits the fast-forwarding feature.
- Score: 0.8359711817610189
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The preparation of the ground state of a Hamiltonian $H$ with a large spectral radius has applications in many areas such as electronic structure theory and quantum field theory. Given an initial state with a constant overlap with the ground state, and assuming that the Hamiltonian $H$ can be efficiently simulated with an ideal fast-forwarding protocol, we first demonstrate that employing a linear combination of unitaries (LCU) approach can prepare the ground state at a cost of $\mathcal{O}(\log^2(\|H\| \Delta^{-1}))$ queries to controlled Hamiltonian evolution. Here $\|H\|$ is the spectral radius of $H$ and $\Delta$ the spectral gap. However, traditional Quantum Signal Processing (QSP)-based methods fail to capitalize on this efficient protocol, and its cost scales as $\mathcal{O}(\|H\| \Delta^{-1})$. To bridge this gap, we develop a multi-level QSP-based algorithm that exploits the fast-forwarding feature. This novel algorithm not only matches the efficiency of the LCU approach when an ideal fast-forwarding protocol is available, but also exceeds it with a reduced cost that scales as $\mathcal{O}(\log(\|H\| \Delta^{-1}))$. Additionally, our multi-level QSP method requires only $\mathcal{O}(\log(\|H\| \Delta^{-1}))$ coefficients for implementing single qubit rotations. This eliminates the need for constructing the PREPARE oracle in LCU, which prepares a state encoding $\mathcal{O}(\|H\| \Delta^{-1})$ coefficients regardless of whether the Hamiltonian can be fast-forwarded.
Related papers
- High-precision and low-depth eigenstate property estimation: theory and resource estimation [2.6811507121199325]
Estimating the eigenstate properties of quantum many-body systems is a long-standing, challenging problem for both classical and quantum computing.
Here, we present a full-stack design of a random sampling algorithm for estimating the eigenenergy and the observable expectations on the eigenstates.
arXiv Detail & Related papers (2024-06-06T17:54:26Z) - Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms [48.869199703062606]
A fundamental problem in quantum many-body physics is that of finding ground states of local Hamiltonians.
We introduce two approaches that achieve a constant sample complexity, independent of system size $n$, for learning ground state properties.
arXiv Detail & Related papers (2024-05-28T18:00:32Z) - Hamiltonian simulation for low-energy states with optimal time dependence [45.02537589779136]
We consider the task of simulating time evolution under a Hamiltonian $H$ within its low-energy subspace.
We present a quantum algorithm that uses $O(tsqrtlambdaGamma + sqrtlambda/Gammalog (1/epsilon))$ queries to the block-encoding for any $Gamma$.
arXiv Detail & Related papers (2024-04-04T17:58:01Z) - A polynomial-time dissipation-based quantum algorithm for solving the ground states of a class of classically hard Hamiltonians [4.500918096201963]
We give a quantum algorithm for solving the ground states of a class of Hamiltonians.
The mechanism of the exponential speedup that appeared in our algorithm comes from dissipation in open quantum systems.
arXiv Detail & Related papers (2024-01-25T05:01:02Z) - Quantum Simulation of the First-Quantized Pauli-Fierz Hamiltonian [0.5097809301149342]
We show that a na"ive partitioning and low-order splitting formula can yield, through our divide and conquer formalism, superior scaling to qubitization for large $Lambda$.
We also give new algorithmic and circuit level techniques for gate optimization including a new way of implementing a group of multi-controlled-X gates.
arXiv Detail & Related papers (2023-06-19T23:20:30Z) - Spacetime-Efficient Low-Depth Quantum State Preparation with
Applications [93.56766264306764]
We show that a novel deterministic method for preparing arbitrary quantum states requires fewer quantum resources than previous methods.
We highlight several applications where this ability would be useful, including quantum machine learning, Hamiltonian simulation, and solving linear systems of equations.
arXiv Detail & Related papers (2023-03-03T18:23:20Z) - On the complexity of implementing Trotter steps [2.1369834525800138]
We develop methods to perform faster Trotter steps with complexity sublinear in number of terms.
We also realize faster Trotter steps when certain blocks of Hamiltonian coefficients have low rank.
Our result suggests the use of Hamiltonian structural properties as both necessary and sufficient to implement Trotter synthesis steps with lower gate complexity.
arXiv Detail & Related papers (2022-11-16T19:00:01Z) - Quantum Resources Required to Block-Encode a Matrix of Classical Data [56.508135743727934]
We provide circuit-level implementations and resource estimates for several methods of block-encoding a dense $Ntimes N$ matrix of classical data to precision $epsilon$.
We examine resource tradeoffs between the different approaches and explore implementations of two separate models of quantum random access memory (QRAM)
Our results go beyond simple query complexity and provide a clear picture into the resource costs when large amounts of classical data are assumed to be accessible to quantum algorithms.
arXiv Detail & Related papers (2022-06-07T18:00:01Z) - Quantum Gram-Schmidt Processes and Their Application to Efficient State
Read-out for Quantum Algorithms [87.04438831673063]
We present an efficient read-out protocol that yields the classical vector form of the generated state.
Our protocol suits the case that the output state lies in the row space of the input matrix.
One of our technical tools is an efficient quantum algorithm for performing the Gram-Schmidt orthonormal procedure.
arXiv Detail & Related papers (2020-04-14T11:05:26Z) - Quantum Algorithms for Simulating the Lattice Schwinger Model [63.18141027763459]
We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and fault-tolerant settings.
In lattice units, we find a Schwinger model on $N/2$ physical sites with coupling constant $x-1/2$ and electric field cutoff $x-1/2Lambda$.
We estimate observables which we cost in both the NISQ and fault-tolerant settings by assuming a simple target observable---the mean pair density.
arXiv Detail & Related papers (2020-02-25T19:18:36Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.