Adaptive time Compressed QITE (ACQ) and its geometrical interpretation
- URL: http://arxiv.org/abs/2510.15781v1
- Date: Fri, 17 Oct 2025 16:04:06 GMT
- Title: Adaptive time Compressed QITE (ACQ) and its geometrical interpretation
- Authors: Alberto Acevedo Meléndez, Carmen G. Almudéver, Miguel Angel Garcia-March, Rafael Gómez-Lurbe, Luca Ion, Mohit Lal Bera, Rodrigo M. Sanz, Somayeh Mehrabankar, Tanmoy Pandit, Armando Pérez, Andreu Anglés-Castillo,
- Abstract summary: We introduce a novel QITE algorithm, which leverages underlying geometric properties for algorithm-runtime and circuit depth reduction.<n>The depth-reduction will be carried out via approximating the resulting unitary operator estimated from the QITE algorithm.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Preparing the ground state of a given Hamiltonian is a computational task of interest in many fields, such as material science, chemistry and even some optimization problems, to name a few. Efficiently preparing ground states for large, strongly correlated systems is a challenging task for both classical and quantum hardware. Drawing from classical optimization methods, e.g. dynamical optimization techniques, one may deduce the spectral decomposition in manner that avoids direct spectral decomposition and is amenable to Trotterization methods. An instance of the latter is ground state preparation by Imaginary Time Evolution (ITE), understood in physical terms as a natural cooling process. Its quantum version QITE (Quantum Imaginary Time Evolution) aims at implementing ITE in a quantum computer. In this paper we introduce a novel QITE algorithm, which leverages underlying geometric properties for algorithm-runtime and circuit depth reduction. This will materialize in the form of an iterative Line Search approach for minimization of energy as well as a Newton's method approach for the deduction of the optimal time-steps for each iteration of QITE. The depth-reduction will be carried out via approximating the resulting unitary operator estimated from the QITE algorithm with unitary operator which is an element of a one-parameter group; making expressible as a single unitary in a quantum circuit. Furthermore, we perform a numerical study to stablish the scaling of fidelities with the different truncation parameters and give gate counts estimates for each.
Related papers
- Basis Adaptive Algorithm for Quantum Many-Body Systems on Quantum Computers [2.4713653282916126]
A new basis adaptive algorithm is introduced to efficiently find the ground-state properties of quantum many-body systems.<n>We benchmark this approach on the spin-1/2 XXZ chain up to 24 qubits using the IBM Heron processor.
arXiv Detail & Related papers (2025-12-14T16:34:19Z) - RhoDARTS: Differentiable Quantum Architecture Search with Density Matrix Simulations [44.13836547616739]
Variational Quantum Algorithms (VQAs) are a promising approach to leverage Noisy Intermediate-Scale Quantum (NISQ) computers.<n> choosing optimal quantum circuits that efficiently solve a given VQA problem is a non-trivial task.<n>Quantum Architecture Search (QAS) algorithms enable automatic generation of quantum circuits tailored to the provided problem.
arXiv Detail & Related papers (2025-06-04T08:30:35Z) - QAMA: Scalable Quantum Annealing Multi-Head Attention Operator for Deep Learning [48.12231190677108]
Quantum Annealing Multi-Head Attention (QAMA) is proposed, a novel drop-in operator that reformulates attention as an energy-based Hamiltonian optimization problem.<n>In this framework, token interactions are encoded into binary quadratic terms, and quantum annealing is employed to search for low-energy configurations.<n> Empirically, evaluation on both natural language and vision benchmarks shows that, across tasks, accuracy deviates by at most 2.7 points from standard multi-head attention.
arXiv Detail & Related papers (2025-04-15T11:29:09Z) - Variational Quantum Subspace Construction via Symmetry-Preserving Cost Functions [36.94429692322632]
We propose a variational strategy based on symmetry-preserving cost functions to iteratively construct a reduced subspace for extraction of low-lying energy states.<n>As a proof of concept, we test the proposed algorithms on H4 chain and ring, targeting both the ground-state energy and the charge gap.
arXiv Detail & Related papers (2024-11-25T20:33:47Z) - Efficient charge-preserving excited state preparation with variational quantum algorithms [33.03471460050495]
We introduce a charge-preserving VQD (CPVQD) algorithm, designed to incorporate symmetry and the corresponding conserved charge into the VQD framework.
Results show applications in high-energy physics, nuclear physics, and quantum chemistry.
arXiv Detail & Related papers (2024-10-18T10:30:14Z) - Depth scaling of unstructured search via quantum approximate optimization [0.0]
Variational quantum algorithms have become the de facto model for current quantum computations.
One such problem is unstructured search which consists on finding a particular bit of string.
We trotterize a CTQW to recover a QAOA sequence, and employ recent advances on the theory of Trotter formulas to bound the query complexity.
arXiv Detail & Related papers (2024-03-22T18:00:03Z) - 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) - 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) - Improved iterative quantum algorithm for ground-state preparation [4.921552273745794]
We propose an improved iterative quantum algorithm to prepare the ground state of a Hamiltonian system.
Our approach has advantages including the higher success probability at each iteration, the measurement precision-independent sampling complexity, the lower gate complexity, and only quantum resources are required when the ancillary state is well prepared.
arXiv Detail & Related papers (2022-10-16T05:57:43Z) - Exploring the role of parameters in variational quantum algorithms [59.20947681019466]
We introduce a quantum-control-inspired method for the characterization of variational quantum circuits using the rank of the dynamical Lie algebra.
A promising connection is found between the Lie rank, the accuracy of calculated energies, and the requisite depth to attain target states via a given circuit architecture.
arXiv Detail & Related papers (2022-09-28T20:24:53Z) - Adiabatic Quantum Computing for Multi Object Tracking [170.8716555363907]
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time.
As these optimization problems are often NP-hard, they can only be solved exactly for small instances on current hardware.
We show that our approach is competitive compared with state-of-the-art optimization-based approaches, even when using of-the-shelf integer programming solvers.
arXiv Detail & Related papers (2022-02-17T18:59:20Z) - Fixed Depth Hamiltonian Simulation via Cartan Decomposition [59.20417091220753]
We present a constructive algorithm for generating quantum circuits with time-independent depth.
We highlight our algorithm for special classes of models, including Anderson localization in one dimensional transverse field XY model.
In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.
arXiv Detail & Related papers (2021-04-01T19:06:00Z) - Optimization of the Variational Quantum Eigensolver for Quantum
Chemistry Applications [0.0]
The variational quantum eigensolver algorithm is designed to determine the ground state of a quantum mechanical system.
We study methods of reducing the number of required qubit manipulations, prone to induce errors, for the variational quantum eigensolver.
arXiv Detail & Related papers (2021-02-02T22:20:12Z)
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.