Quantum Phase Estimation Algorithm with Gaussian Spin States
- URL: http://arxiv.org/abs/2010.04001v2
- Date: Thu, 15 Oct 2020 07:59:42 GMT
- Title: Quantum Phase Estimation Algorithm with Gaussian Spin States
- Authors: Luca Pezz\`e and Augusto Smerzi
- Abstract summary: We propose a new QPE algorithm that scales linearly with time and is implemented with a cascade of Gaussian spin states (GSS)
Our work paves the way toward realistic quantum advantage demonstrations of the QPE, as well as applications of atomic squeezed states for quantum subroutines.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Quantum phase estimation (QPE) is one of the most important subroutines in
quantum computing. In general applications, current QPE algorithms either
suffer an exponential time overload or require a set of - notoriously quite
fragile - GHZ states. These limitations have prevented so far the demonstration
of QPE beyond proof-of-principles. Here we propose a new QPE algorithm that
scales linearly with time and is implemented with a cascade of Gaussian spin
states (GSS). GSS are renownedly resilient and have been created experimentally
in a variety of platforms, from hundreds of ions up to millions of
cold/ultracold neutral atoms. We show that our protocol achieves a QPE
sensitivity overcoming previous bounds, including those obtained with GHZ
states, and is robustly resistant to several sources of noise and decoherence.
Our work paves the way toward realistic quantum advantage demonstrations of the
QPE, as well as applications of atomic squeezed states for quantum computation.
Related papers
- Efficient Quantum Pseudorandomness from Hamiltonian Phase States [41.94295877935867]
We introduce a quantum hardness assumption called the Hamiltonian Phase State (HPS) problem.
We show that our assumption is plausibly fully quantum; meaning, it cannot be used to construct one-way functions.
We show that our assumption and its variants allow us to efficiently construct many pseudorandom quantum primitives.
arXiv Detail & Related papers (2024-10-10T16:10:10Z) - On Reducing the Execution Latency of Superconducting Quantum Processors via Quantum Program Scheduling [48.142860424323395]
We introduce the Quantum Program Scheduling Problem (QPSP) to improve the utility efficiency of quantum resources.
Specifically, a quantum program scheduling method concerning the circuit width, number of measurement shots, and submission time of quantum programs is proposed to reduce the execution latency.
arXiv Detail & Related papers (2024-04-11T16:12:01Z) - Reductive Quantum Phase Estimation [0.0]
We show a circuit that distinguishes an arbitrary set of phases with a fewer number of qubits and unitary applications.
We show a trade-off between measurement precision and phase distinguishability, which allows one to tune the circuit to be optimal for a specific application.
arXiv Detail & Related papers (2024-02-06T23:38:36Z) - QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum
Circuits [82.50620782471485]
QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits.
It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness.
Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
arXiv Detail & Related papers (2024-01-10T22:33:00Z) - Sparse Quantum State Preparation for Strongly Correlated Systems [0.0]
In principle, the encoding of the exponentially scaling many-electron wave function onto a linearly scaling qubit register offers a promising solution to overcome the limitations of traditional quantum chemistry methods.
An essential requirement for ground state quantum algorithms to be practical is the initialisation of the qubits to a high-quality approximation of the sought-after ground state.
Quantum State Preparation (QSP) allows the preparation of approximate eigenstates obtained from classical calculations, but it is frequently treated as an oracle in quantum information.
arXiv Detail & Related papers (2023-11-06T18:53:50Z) - Demonstrating Bayesian Quantum Phase Estimation with Quantum Error
Detection [0.5018156030818881]
We take a step towards fault-tolerant quantum computing by demonstrating a QPE algorithm on a Quantinuum trapped-ion computer.
As a simple quantum chemistry example, we take a hydrogen molecule represented by a two-qubit Hamiltonian and estimate its ground state energy using our QPE protocol.
arXiv Detail & Related papers (2023-06-29T00:22:07Z) - 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) - 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) - Preparing random states and benchmarking with many-body quantum chaos [48.044162981804526]
We show how to predict and experimentally observe the emergence of random state ensembles naturally under time-independent Hamiltonian dynamics.
The observed random ensembles emerge from projective measurements and are intimately linked to universal correlations built up between subsystems of a larger quantum system.
Our work has implications for understanding randomness in quantum dynamics, and enables applications of this concept in a wider context.
arXiv Detail & Related papers (2021-03-05T08:32:43Z) - Quantum simulation of open quantum systems in heavy-ion collisions [0.0]
We present a framework to simulate the dynamics of hard probes such as heavy quarks or jets in a hot, strongly-coupled quark-gluon plasma (QGP) on a quantum computer.
Our work demonstrates the feasibility of simulating open quantum systems on current and near-term quantum devices.
arXiv Detail & Related papers (2020-10-07T18:00:02Z) - Minimizing estimation runtime on noisy quantum computers [0.0]
"engineered likelihood function" (ELF) is used for carrying out Bayesian inference.
We show how the ELF formalism enhances the rate of information gain in sampling as the physical hardware transitions from the regime of noisy quantum computers.
This technique speeds up a central component of many quantum algorithms, with applications including chemistry, materials, finance, and beyond.
arXiv Detail & Related papers (2020-06-16T17:46:18Z)
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.