State preparation in quantum algorithms for fragment-based quantum
chemistry
- URL: http://arxiv.org/abs/2305.18110v2
- Date: Wed, 7 Jun 2023 15:38:03 GMT
- Title: State preparation in quantum algorithms for fragment-based quantum
chemistry
- Authors: Ruhee D'Cunha, Matthew Otten, Matthew R. Hermes, Laura Gagliardi and
Stephen K. Gray
- Abstract summary: State preparation for quantum algorithms is crucial for achieving high accuracy in quantum chemistry.
We compare two state preparation methods, quantum phase estimation (QPE) and direct initialization (DI)
We find a trade-off between the methods, where DI requires fewer resources for smaller fragments, while QPE is more efficient for larger fragments.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: State preparation for quantum algorithms is crucial for achieving high
accuracy in quantum chemistry and competing with classical algorithms. The
localized active space unitary coupled cluster (LAS-UCC) algorithm iteratively
loads a fragment-based multireference wave function onto a quantum computer. In
this study, we compare two state preparation methods, quantum phase estimation
(QPE) and direct initialization (DI), for each fragment. We analyze the impact
of QPE parameters, such as the number of ancilla qubits and Trotter steps, on
the prepared state. We find a trade-off between the methods, where DI requires
fewer resources for smaller fragments, while QPE is more efficient for larger
fragments. Our resource estimates highlight the benefits of system
fragmentation in state preparation for subsequent quantum chemical
calculations. These findings have broad applications for preparing
multireference quantum chemical wave functions on quantum circuits,
particularly via QPE circuits.
Related papers
- Non-unitary Coupled Cluster Enabled by Mid-circuit Measurements on Quantum Computers [37.69303106863453]
We propose a state preparation method based on coupled cluster (CC) theory, which is a pillar of quantum chemistry on classical computers.
Our approach leads to a reduction of the classical computation overhead, and the number of CNOT and T gates by 28% and 57% on average.
arXiv Detail & Related papers (2024-06-17T14:10:10Z) - Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
Quantum computing sets the foundation for new ways of designing algorithms.
New challenges arise concerning which field quantum speedup can be achieved.
Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
arXiv Detail & Related papers (2024-02-26T09:32:07Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Applicability of Measurement-based Quantum Computation towards Physically-driven Variational Quantum Eigensolver [17.975555487972166]
Variational quantum algorithms are considered one of the most promising methods for obtaining near-term quantum advantages.
The roadblock to developing quantum algorithms with the measurement-based quantum computation scheme is resource cost.
We propose an efficient measurement-based quantum algorithm for quantum many-body system simulation tasks, called measurement-based Hamiltonian variational ansatz (MBHVA)
arXiv Detail & Related papers (2023-07-19T08:07:53Z) - End-to-end resource analysis for quantum interior point methods and portfolio optimization [63.4863637315163]
We provide a complete quantum circuit-level description of the algorithm from problem input to problem output.
We report the number of logical qubits and the quantity/depth of non-Clifford T-gates needed to run the algorithm.
arXiv Detail & Related papers (2022-11-22T18:54:48Z) - Anticipative measurements in hybrid quantum-classical computation [68.8204255655161]
We present an approach where the quantum computation is supplemented by a classical result.
Taking advantage of its anticipation also leads to a new type of quantum measurements, which we call anticipative.
In an anticipative quantum measurement the combination of the results from classical and quantum computations happens only in the end.
arXiv Detail & Related papers (2022-09-12T15:47:44Z) - Decomposition of Matrix Product States into Shallow Quantum Circuits [62.5210028594015]
tensor network (TN) algorithms can be mapped to parametrized quantum circuits (PQCs)
We propose a new protocol for approximating TN states using realistic quantum circuits.
Our results reveal one particular protocol, involving sequential growth and optimization of the quantum circuit, to outperform all other methods.
arXiv Detail & Related papers (2022-09-01T17:08:41Z) - Optimal quantum kernels for small data classification [0.0]
We show an algorithm for constructing quantum kernels for support vector machines that adapts quantum gate sequences to data.
The performance of the resulting quantum models for classification problems with a small number of training points significantly exceeds that of optimized classical models.
arXiv Detail & Related papers (2022-03-25T18:26:44Z) - Distributed Quantum Computing with QMPI [11.71212583708166]
We introduce an extension of the Message Passing Interface (MPI) to enable high-performance implementations of distributed quantum algorithms.
In addition to a prototype implementation of quantum MPI, we present a performance model for distributed quantum computing, SENDQ.
arXiv Detail & Related papers (2021-05-03T18:30:43Z) - Resource-efficient encoding algorithm for variational bosonic quantum
simulations [0.0]
In the Noisy Intermediate Scale Quantum (NISQ) era of quantum computing, quantum resources are limited.
We present a resource-efficient quantum algorithm for bosonic ground and excited state computations.
arXiv Detail & Related papers (2021-02-23T19:00:05Z) - Quantum circuit architecture search for variational quantum algorithms [88.71725630554758]
We propose a resource and runtime efficient scheme termed quantum architecture search (QAS)
QAS automatically seeks a near-optimal ansatz to balance benefits and side-effects brought by adding more noisy quantum gates.
We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks.
arXiv Detail & Related papers (2020-10-20T12:06:27Z)
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.