Fast Quantum Many Body State Synthesis

• URL: http://arxiv.org/abs/2511.12923v1
• Date: Mon, 17 Nov 2025 03:21:12 GMT
• Title: Fast Quantum Many Body State Synthesis
• Authors: Prashasti Tiwari, Dylan Lewis, Sougato Bose,
• Abstract summary: We investigate the possibility of preparing a many-body entangled ground state of a certain Hamiltonian.<n>The parameters of the solver Hamiltonian are optimised classically using energy minimisation as the cost function.<n>We present a study of up to n=10 qubit many-body states prepared using this methodology.
• Score: 0.038233569758620044
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum Mechanical ground states of many-body systems can be important resources for various investigations: for quantum sensing, as the initial state for nonequilibrium quantum dynamics following quenches, and the simulation of quantum processes that start by coupling systems in ground states, eg, could be a process in quantum chemistry. However, to prepare ground states can be challenging; for example, requires adiabatic switching of Hamiltonian terms slower than an inverse gap, which can be time consuming and bring in decoherence. Here we investigate the possibility of preparing a many-body entangled ground state of a certain Hamiltonian, which can be called a quantum ``problem'' Hamiltonian, using the time evolution of an initial fiducial state by another ``solver'' Hamiltonian/s for a very short fixed (unit) time. The parameters of the solver Hamiltonian are optimised classically using energy minimisation as the cost function. We present a study of up to n=10 qubit many-body states prepared using this methodology.

Related papers

• Digital quantum simulation of many-body systems: Making the most of intermediate-scale, noisy quantum computers [51.56484100374058]
  This thesis is centered around simulating quantum dynamics on quantum devices.<n>We present an overview of the most relevant quantum algorithms for quantum dynamics.<n>We identify relevant problems within quantum dynamics that could benefit from quantum simulation in the near future.
  arXiv  Detail & Related papers  (2025-08-29T10:37:19Z)
• State-Based Quantum Simulation: Releasing the Powers of Quantum States and Copies [0.0]
  We introduce a method for quantum simulation in which the Hamiltonian is decomposed in terms of states.<n>We show how classical nonlinear and time-delayed ordinary differential equations can be simulated with the state-based method.
  arXiv  Detail & Related papers  (2025-05-20T04:05:26Z)
• 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)
• Quantum superpositions of current states in Rydberg-atom networks [0.0]
  We propose a quantum optimal control protocol to engineer current states. quantum states characterized by Rydberg excitations propagating in a given spatially closed tweezer networks.
  arXiv  Detail & Related papers  (2024-03-05T18:39:01Z)
• Quantum data learning for quantum simulations in high-energy physics [55.41644538483948]
  We explore the applicability of quantum-data learning to practical problems in high-energy physics. We make use of ansatz based on quantum convolutional neural networks and numerically show that it is capable of recognizing quantum phases of ground states. The observation of non-trivial learning properties demonstrated in these benchmarks will motivate further exploration of the quantum-data learning architecture in high-energy physics.
  arXiv  Detail & Related papers  (2023-06-29T18:00:01Z)
• Sparse random Hamiltonians are quantumly easy [105.6788971265845]
  A candidate application for quantum computers is to simulate the low-temperature properties of quantum systems. This paper shows that, for most random Hamiltonians, the maximally mixed state is a sufficiently good trial state. Phase estimation efficiently prepares states with energy arbitrarily close to the ground energy.
  arXiv  Detail & Related papers  (2023-02-07T10:57:36Z)
• Exact quantum dynamics for two-level systems with time-dependent driving [2.69899958854431]
  Time-dependent Schr"odinger equation can only be exactly solvable in very rare cases. We present a method which could generate a near infinite number of analytical-assisted solutions of the Schr"odinger equation for a qubit.
  arXiv  Detail & Related papers  (2022-11-07T07:29:13Z)
• An Empirical Study of Quantum Dynamics as a Ground State Problem with Neural Quantum States [0.0]
  Neural quantum states are variational wave functions parameterised by artificial neural networks. In the context of many-body physics, methods such as variational Monte Carlo with neural quantum states as variational wave functions are successful in approximating. However, all the difficulties of proposing neural network architectures, along with exploring their expressivity and trainability, permeate their application as neural quantum states.
  arXiv  Detail & Related papers  (2022-06-18T16:42:39Z)
• Algebraic Compression of Quantum Circuits for Hamiltonian Evolution [52.77024349608834]
  Unitary evolution under a time dependent Hamiltonian is a key component of simulation on quantum hardware. We present an algorithm that compresses the Trotter steps into a single block of quantum gates. This results in a fixed depth time evolution for certain classes of Hamiltonians.
  arXiv  Detail & Related papers  (2021-08-06T19:38:01Z)
• Imaginary Time Propagation on a Quantum Chip [50.591267188664666]
  Evolution in imaginary time is a prominent technique for finding the ground state of quantum many-body systems. We propose an algorithm to implement imaginary time propagation on a quantum computer.
  arXiv  Detail & Related papers  (2021-02-24T12:48:00Z)
• Iterative Quantum Assisted Eigensolver [0.0]
  We provide a hybrid quantum-classical algorithm for approximating the ground state of a Hamiltonian. Our algorithm builds on the powerful Krylov subspace method in a way that is suitable for current quantum computers.
  arXiv  Detail & Related papers  (2020-10-12T12:25:16Z)

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.