Disorder-Free Localization for Benchmarking Quantum Computers
- URL: http://arxiv.org/abs/2410.08268v1
- Date: Thu, 10 Oct 2024 18:00:00 GMT
- Title: Disorder-Free Localization for Benchmarking Quantum Computers
- Authors: Jad C. Halimeh, Uliana E. Khodaeva, Dmitry L. Kovrizhin, Roderich Moessner, Johannes Knolle,
- Abstract summary: We show how a canonical model of Disorder-free localization can be efficiently implemented on gate-based quantum computers.
We show that the simultaneous observation of the absence of correlation spreading and tunable entanglement growth to a volume law provides an ideal testbed for benchmarking the capabilities of quantum computers.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Disorder-free localization (DFL) is a phenomenon as striking as it appears to be simple: a translationally invariant state evolving under a disorder-free Hamiltonian failing to thermalize. It is predicted to occur in a number of quantum systems exhibiting emergent or native \emph{local} symmetries. These include models of lattice gauge theories and, perhaps most simply, some two-component spin chains. Though well-established analytically for special soluble examples, numerical studies of generic systems have proven difficult. Moreover, the required local symmetries are a challenge for any experimental realization. Here, we show how a canonical model of DFL can be efficiently implemented on gate-based quantum computers, which relies on our efficient encoding of three-qubit gates. We show that the simultaneous observation of the absence of correlation spreading and tunable entanglement growth to a volume law provides an ideal testbed for benchmarking the capabilities of quantum computers. In particular, the availability of a soluble limit allows for a rigorous prediction of emergent localization length scales and tunable time scales for the volume law entanglement growth, which are ideal for testing capabilities of scalable quantum computers.
Related papers
- Observation of disorder-free localization and efficient disorder averaging on a quantum processor [117.33878347943316]
We implement an efficient procedure on a quantum processor, leveraging quantum parallelism, to efficiently sample over all disorder realizations.
We observe localization without disorder in quantum many-body dynamics in one and two dimensions.
arXiv Detail & Related papers (2024-10-09T05:28:14Z) - Large-scale quantum annealing simulation with tensor networks and belief propagation [0.0]
We show that quantum annealing for 3-regular graphs can be classically simulated even at scales of 1000 qubits and 5000000qubit gates.
For non-degenerate instances, the unique solution can be read out from the final reduced single-qubit states.
For degenerate problems, such as MaxCut, we introduce an approximate measurement simulation algorithm for graph tensor-network states.
arXiv Detail & Related papers (2024-09-18T18:00:08Z) - Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Quantum computational advantage with constant-temperature Gibbs sampling [1.1930434318557157]
A quantum system coupled to a bath at some fixed, finite temperature converges to its Gibbs state.
This thermalization process defines a natural, physically-motivated model of quantum computation.
We consider sampling from the measurement outcome distribution of quantum Gibbs states at constant temperatures.
arXiv Detail & Related papers (2024-04-23T00:29:21Z) - Learning the tensor network model of a quantum state using a few
single-qubit measurements [0.0]
The constantly increasing dimensionality of artificial quantum systems demands highly efficient methods for their characterization and benchmarking.
Here we present a constructive and numerically efficient protocol which learns a tensor network model of an unknown quantum system.
arXiv Detail & Related papers (2023-09-01T11:11:52Z) - Universality of critical dynamics with finite entanglement [68.8204255655161]
We study how low-energy dynamics of quantum systems near criticality are modified by finite entanglement.
Our result establishes the precise role played by entanglement in time-dependent critical phenomena.
arXiv Detail & Related papers (2023-01-23T19:23:54Z) - Towards Neural Variational Monte Carlo That Scales Linearly with System
Size [67.09349921751341]
Quantum many-body problems are central to demystifying some exotic quantum phenomena, e.g., high-temperature superconductors.
The combination of neural networks (NN) for representing quantum states, and the Variational Monte Carlo (VMC) algorithm, has been shown to be a promising method for solving such problems.
We propose a NN architecture called Vector-Quantized Neural Quantum States (VQ-NQS) that utilizes vector-quantization techniques to leverage redundancies in the local-energy calculations of the VMC algorithm.
arXiv Detail & Related papers (2022-12-21T19:00:04Z) - Probing finite-temperature observables in quantum simulators of spin
systems with short-time dynamics [62.997667081978825]
We show how finite-temperature observables can be obtained with an algorithm motivated from the Jarzynski equality.
We show that a finite temperature phase transition in the long-range transverse field Ising model can be characterized in trapped ion quantum simulators.
arXiv Detail & Related papers (2022-06-03T18:00:02Z) - Preparing Renormalization Group Fixed Points on NISQ Hardware [0.0]
We numerically and experimentally study the robust preparation of the ground state of the critical Ising model using circuits adapted from the work of Evenbly and White.
The experimental implementation exhibits self-correction through renormalization seen in the convergence and stability of local observables.
We also numerically test error mitigation by zero-noise extrapolation schemes specially adapted for renormalization circuits.
arXiv Detail & Related papers (2021-09-20T18:35:11Z) - Error mitigation and quantum-assisted simulation in the error corrected
regime [77.34726150561087]
A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations.
We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
arXiv Detail & Related papers (2021-03-12T20:58:41Z) - Towards simulating 2D effects in lattice gauge theories on a quantum
computer [1.327151508840301]
We propose an experimental quantum simulation scheme to study ground state properties in two-dimensional quantum electrodynamics (2D QED) using existing quantum technology.
The proposal builds on a formulation of lattice gauge theories as effective spin models in arXiv:2006.14160.
We present two Variational Quantum Eigensolver (VQE) based protocols for the study of magnetic field effects, and for taking an important first step towards computing the running coupling of QED.
arXiv Detail & Related papers (2020-08-21T01:20:55Z)
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.