SRBB-Based Quantum State Preparation
- URL: http://arxiv.org/abs/2503.13647v1
- Date: Mon, 17 Mar 2025 18:51:07 GMT
- Title: SRBB-Based Quantum State Preparation
- Authors: Giacomo Belli, Marco Mordacci, Michele Amoretti,
- Abstract summary: A scalable algorithm for the approximate quantum state preparation problem is proposed.<n>The algorithm uses a variational quantum circuit based on the Standard Recursive Block Basis (SRBB)<n>The desired quantum state is then approximated by a scalable quantum neural network.
- Score: 1.3108652488669736
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In this work, a scalable algorithm for the approximate quantum state preparation problem is proposed, facing a challenge of fundamental importance in many topic areas of quantum computing. The algorithm uses a variational quantum circuit based on the Standard Recursive Block Basis (SRBB), a hierarchical construction for the matrix algebra of the $SU(2^n)$ group, which is capable of linking the variational parameters with the topology of the Lie group. Compared to the full algebra, using only diagonal components reduces the number of CNOTs by an exponential factor, as well as the circuit depth, in full agreement with the relaxation principle, inherent to the approximation methodology, of minimizing resources while achieving high accuracy. The desired quantum state is then approximated by a scalable quantum neural network, which is designed upon the diagonal SRBB sub-algebra. This approach provides a new scheme for approximate quantum state preparation in a variational framework and a specific use case for the SRBB hierarchy. The performance of the algorithm is assessed with different loss functions, like fidelity, trace distance, and Frobenius norm, in relation to two optimizers: Adam and Nelder-Mead. The results highlight the potential of SRBB in close connection with the geometry of unitary groups, achieving high accuracy up to 4 qubits in simulation, but also its current limitations with an increasing number of qubits. Additionally, the approximate SRBB-based QSP algorithm has been tested on real quantum devices to assess its performance with a small number of qubits.
Related papers
- Branch-and-bound digitized counterdiabatic quantum optimization [39.58317527488534]
Branch-and-bound algorithms effectively solve convex optimization problems, relying on the relaxation the objective function to obtain tight lower bounds.
We propose a branch-and-bound digitized counterdiabatic quantum optimization (BB-DCQO) algorithm that addresses the relaxation difficulties.
arXiv Detail & Related papers (2025-04-21T18:19:19Z) - A Scalable Quantum Neural Network for Approximate SRBB-Based Unitary Synthesis [1.3108652488669736]
This work introduces scalable quantum neural networks to approximate unitary evolutions through the Standard Recursive Block Basis (SRBB)<n>An algorithm to reduce the number of CNOTs is proposed, thus deriving a new implementable scaling scheme that requires one single layer of approximation.<n>The effectiveness of the approximation is measured with different metrics in relation to two gradient-based methods.
arXiv Detail & Related papers (2024-12-04T07:21:23Z) - Characterizing randomness in parameterized quantum circuits through expressibility and average entanglement [39.58317527488534]
Quantum Circuits (PQCs) are still not fully understood outside the scope of their principal application.
We analyse the generation of random states in PQCs under restrictions on the qubits connectivities.
We place a connection between how steep is the increase on the uniformity of the distribution of the generated states and the generation of entanglement.
arXiv Detail & Related papers (2024-05-03T17:32:55Z) - 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) - A multiple-circuit approach to quantum resource reduction with application to the quantum lattice Boltzmann method [39.671915199737846]
We introduce a multiple-circuit algorithm for a quantum lattice Boltzmann method (QLBM) solve of the incompressible Navier--Stokes equations.
The presented method is validated and demonstrated for 2D lid-driven cavity flow.
arXiv Detail & Related papers (2024-01-20T15:32:01Z) - Efficient Quantum Circuits based on the Quantum Natural Gradient [0.0]
Efficient preparation of arbitrary entangled quantum states is crucial for quantum computation.
We propose symmetry-conserving modified quantum approximate optimization algorithm(SCom-QAOA) circuits.
The proposed scheme enlarges the set of the initial states accessible for variational quantum algorithms and widens the scope of investigation of non-equilibrium phenomena in quantum simulators.
arXiv Detail & Related papers (2023-10-16T16:08:57Z) - Quantum Semidefinite Programming with Thermal Pure Quantum States [0.5639904484784125]
We show that a quantization'' of the matrix multiplicative-weight algorithm can provide approximate solutions to SDPs quadratically faster than the best classical algorithms.
We propose a modification of this quantum algorithm and show that a similar speedup can be obtained by replacing the Gibbs-state sampler with the preparation of thermal pure quantum (TPQ) states.
arXiv Detail & Related papers (2023-10-11T18:00:53Z) - 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) - Iterative Qubit Coupled Cluster using only Clifford circuits [36.136619420474766]
An ideal state preparation protocol can be characterized by being easily generated classically.
We propose a method that meets these requirements by introducing a variant of the iterative qubit coupled cluster (iQCC)
We demonstrate the algorithm's correctness in ground-state simulations and extend our study to complex systems like the titanium-based compound Ti(C5H5)(CH3)3 with a (20, 20) active space.
arXiv Detail & Related papers (2022-11-18T20:31:10Z) - Analyzing Prospects for Quantum Advantage in Topological Data Analysis [35.423446067065576]
We analyze and optimize an improved quantum algorithm for topological data analysis.
We show that super-quadratic quantum speedups are only possible when targeting a multiplicative error approximation.
We argue that quantum circuits with tens of billions of Toffoli can solve seemingly classically intractable instances.
arXiv Detail & Related papers (2022-09-27T17:56:15Z) - 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) - Quantum Speedup for Higher-Order Unconstrained Binary Optimization and
MIMO Maximum Likelihood Detection [2.5272389610447856]
We propose a quantum algorithm that supports a real-valued higher-order unconstrained binary optimization problem.
The proposed algorithm is capable of reducing the query complexity in the classical domain and providing a quadratic speedup in the quantum domain.
arXiv Detail & Related papers (2022-05-31T00:14:49Z) - Quantum Robustness Verification: A Hybrid Quantum-Classical Neural
Network Certification Algorithm [1.439946676159516]
In this work, we investigate the verification of ReLU networks, which involves solving a robustness many-variable mixed-integer programs (MIPs)
To alleviate this issue, we propose to use QC for neural network verification and introduce a hybrid quantum procedure to compute provable certificates.
We show that, in a simulated environment, our certificate is sound, and provide bounds on the minimum number of qubits necessary to approximate the problem.
arXiv Detail & Related papers (2022-05-02T13:23:56Z)
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.