Bang-bang preparation of quantum many-body ground states in two dimensions: optimization of the algorithm with a two-dimensional tensor network
- URL: http://arxiv.org/abs/2401.09158v4
- Date: Tue, 11 Jun 2024 20:14:02 GMT
- Title: Bang-bang preparation of quantum many-body ground states in two dimensions: optimization of the algorithm with a two-dimensional tensor network
- Authors: Yintai Zhang, Jacek Dziarmaga,
- Abstract summary: A bang-bang (BB) algorithm prepares the ground state of a two-dimensional (2D) quantum many-body Hamiltonian $H=H1-+H$.
We use the neighborhood tensor update to simulate the BB evolution with an infinite pair-dentangle projected state (iPEPS)
The optimal BB energy converges with the number of bangs much faster than the optimal AP energy.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A bang-bang (BB) algorithm prepares the ground state of a two-dimensional (2D) quantum many-body Hamiltonian $H=H_1+H_2$ by evolving an initial product state alternating between $H_1$ and $H_2$. We use the neighborhood tensor update to simulate the BB evolution with an infinite pair-entangled projected state (iPEPS). The alternating sequence is optimized with the final energy as a cost function. The energy is calculated with the tangent space methods for the sake of their stability. The method is benchmarked in the 2D transverse field quantum Ising model near its quantum critical point against a ground state obtained by variational optimization of the iPEPS. The optimal BB sequence differs non-perturbatively from a sequence simulating quantum annealing or adiabatic preparation (AP) of the ground state. The optimal BB energy converges with the number of bangs much faster than the optimal AP energy.
Related papers
- Single-step Quantum Simulation of Two Nucleons [0.0]
This work presents a numerical simulation of the subspace search variational quantum eigensolver (SSVQE) combined with an adaptive derivative-assembles pseudo-trotter (ADAPT) ansatz.<n>We demonstrate the accuracy of the method by benchmarking against the exact diagonalization.
arXiv Detail & Related papers (2025-12-14T18:41:57Z) - Learning Feasible Quantum States for Quadratic Constrained Binary Optimization Problems [41.23247424467223]
We develop a variational approach that creates an equal superposition of quantum states that satisfy constraints in a QCBO.<n>The resulting equal superposition can be used as an initial state for quantum algorithms that solve QUBOs/QCBOs.
arXiv Detail & Related papers (2025-08-04T16:44:53Z) - Bang-bang preparation of a quantum many-body ground state in a finite lattice: optimization of the algorithm with a tensor network [0.0]
A bang-bang (BB) algorithm prepares the ground state of a lattice quantum many-body Hamiltonian $H=H_1+H$.<n>We optimize the algorithm with tensor networks in one and two dimensions.<n>We test the procedure in the 1D and 2D quantum Ising model near its quantum critical point employing, respectively, the matrix product state (MPS) and the pair-entangled projected state (PEPS)
arXiv Detail & Related papers (2025-05-13T05:01:49Z) - A Unified Variational Framework for Quantum Excited States [2.935517095941649]
We introduce a novel variational principle that overcomes limitations, enabling the textitsimultaneous determination of multiple low-energy excited states.
We demonstrate the power and generality of this method across diverse physical systems and variational ansatzes.
In all applications, the method accurately and simultaneously obtains multiple lowest-lying energy levels and their corresponding states.
arXiv Detail & Related papers (2025-04-30T09:28:04Z) - Grover's search meets Ising models: a quantum algorithm for finding low-energy states [0.0]
We propose a methodology for implementing Grover's algorithm in the digital quantum simulation of disordered Ising models.
We determine the optimal evolution time by ensuring a phase flip for the target states.
This method yields a quadratic speedup compared to classical methods.
arXiv Detail & Related papers (2024-12-24T07:35:24Z) - Optimizing random local Hamiltonians by dissipation [44.99833362998488]
We prove that a simplified quantum Gibbs sampling algorithm achieves a $Omega(frac1k)$-fraction approximation of the optimum.
Our results suggest that finding low-energy states for sparsified (quasi)local spin and fermionic models is quantumly easy but classically nontrivial.
arXiv Detail & Related papers (2024-11-04T20:21:16Z) - Orbital-free density functional theory with first-quantized quantum subroutines [0.0]
We propose a quantum-classical hybrid scheme for performing orbital-free density functional theory (OFDFT) using probabilistic imaginary-time evolution (PITE)
PITE is applied to the part of OFDFT that searches the ground state of the Hamiltonian in each self-consistent field (SCF) iteration.
It is shown that obtaining the ground state energy of Hamiltonian requires a circuit depth of $O(log N_mathrmg)$.
arXiv Detail & Related papers (2024-07-23T05:34:11Z) - Variational Optimization for Quantum Problems using Deep Generative Networks [9.011023101133953]
We propose a general approach to design variational optimization algorithms based on generative models.
We apply VGON to three quantum tasks: finding the best state in an entanglement-detection protocol, finding the ground state of a 1D quantum spin model with variational quantum circuits, and generating degenerate ground states of many-body quantum Hamiltonians.
arXiv Detail & Related papers (2024-04-28T00:58:28Z) - Neutron-nucleus dynamics simulations for quantum computers [49.369935809497214]
We develop a novel quantum algorithm for neutron-nucleus simulations with general potentials.
It provides acceptable bound-state energies even in the presence of noise, through the noise-resilient training method.
We introduce a new commutativity scheme called distance-grouped commutativity (DGC) and compare its performance with the well-known qubit-commutativity scheme.
arXiv Detail & Related papers (2024-02-22T16:33:48Z) - Simulating 2D topological quantum phase transitions on a digital quantum computer [3.727382912998531]
Efficient preparation of many-body ground states is key to harnessing the power of quantum computers in studying quantum many-body systems.
We propose a simple method to design exact linear-depth parameterized quantum circuits which prepare a family of ground states across topological quantum phase transitions in 2D.
We show that the 2D isoTNS can also be efficiently simulated by a holographic quantum algorithm requiring only an 1D array of qubits.
arXiv Detail & Related papers (2023-12-08T15:01:44Z) - A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games [102.46640028830441]
We introduce the Optimistic Matrix Multiplicative Weights Update (OMMWU) algorithm and establish its average-iterate convergence complexity as $mathcalO(d/epsilon)$ to $epsilon$-Nash equilibria.
This quadratic speed-up sets a new benchmark for computing $epsilon$-Nash equilibria in quantum zero-sum games.
arXiv Detail & Related papers (2023-11-17T20:38:38Z) - Quantum Gate Generation in Two-Level Open Quantum Systems by Coherent
and Incoherent Photons Found with Gradient Search [77.34726150561087]
We consider an environment formed by incoherent photons as a resource for controlling open quantum systems via an incoherent control.
We exploit a coherent control in the Hamiltonian and an incoherent control in the dissipator which induces the time-dependent decoherence rates.
arXiv Detail & Related papers (2023-02-28T07:36:02Z) - Simulating scalar field theories on quantum computers with limited
resources [62.997667081978825]
We present a quantum algorithm for implementing $phi4$ lattice scalar field theory on qubit computers.
The algorithm allows efficient $phi4$ state preparation for a large range of input parameters in both the normal and broken symmetry phases.
arXiv Detail & Related papers (2022-10-14T17:28:15Z) - Quantum Davidson Algorithm for Excited States [42.666709382892265]
We introduce the quantum Krylov subspace (QKS) method to address both ground and excited states.
By using the residues of eigenstates to expand the Krylov subspace, we formulate a compact subspace that aligns closely with the exact solutions.
Using quantum simulators, we employ the novel QDavidson algorithm to delve into the excited state properties of various systems.
arXiv Detail & Related papers (2022-04-22T15:03:03Z) - Twisted hybrid algorithms for combinatorial optimization [68.8204255655161]
Proposed hybrid algorithms encode a cost function into a problem Hamiltonian and optimize its energy by varying over a set of states with low circuit complexity.
We show that for levels $p=2,ldots, 6$, the level $p$ can be reduced by one while roughly maintaining the expected approximation ratio.
arXiv Detail & Related papers (2022-03-01T19:47:16Z) - Robust preparation of Wigner-negative states with optimized
SNAP-displacement sequences [41.42601188771239]
We create non-classical states of light in three-dimensional microwave cavities.
These states are useful for quantum computation.
We show that this way of creating non-classical states is robust to fluctuations of the system parameters.
arXiv Detail & Related papers (2021-11-15T18:20:38Z) - Nearly optimal quantum algorithm for generating the ground state of a
free quantum field theory [0.0]
We devise a quasilinear quantum algorithm for generating an approximation for the ground state of a quantum field theory.
Our algorithm delivers a super-quadratic speedup over the state-of-the-art quantum algorithm for ground-state generation.
arXiv Detail & Related papers (2021-10-12T02:48:46Z) - Computing molecular excited states on a D-Wave quantum annealer [52.5289706853773]
We demonstrate the use of a D-Wave quantum annealer for the calculation of excited electronic states of molecular systems.
These simulations play an important role in a number of areas, such as photovoltaics, semiconductor technology and nanoscience.
arXiv Detail & Related papers (2021-07-01T01:02:17Z) - Adiabatic Spectroscopy and a Variational Quantum Adiabatic Algorithm [0.7734726150561088]
We propose a method to obtain information about the spectral profile of the adiabatic evolution.
We present the concept of a variational quantum adiabatic algorithm (VQAA) for optimized adiabatic paths.
arXiv Detail & Related papers (2021-03-01T19:00:00Z)
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.