Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > quant-ph > arXiv:2510.14744

Help | Advanced Search

Quantum Physics

arXiv:2510.14744 (quant-ph)
[Submitted on 16 Oct 2025 ]

Title: Spectral subspace extraction via incoherent quantum phase estimation

Title: 通过非相干量子相位估算的谱子空间提取

Authors:Stefano Scali, Josh Kirsopp, Antonio Márquez Romero, Michał Krompiec
Abstract: Quantum phase estimation (QPE) is a cornerstone algorithm for extracting Hamiltonian eigenvalues, but its standard form targets individual eigenstates and requires carefully prepared coherent inputs. To overcome these limitations, we adopt an ensemble-based formulation of QPE that estimates the density of states (DOS) of the Hamiltonian generator of the evolution. This approach, which we refer to as DOS-QPE, builds on a prior formulation introduced by one of the authors. In this work, we present DOS-QPE as a circuit primitive, extending it with symmetry-adapted input ensembles and advanced spectrum reconstruction techniques. This variant of QPE enables natural access to thermodynamic properties, symmetry-resolved spectral functions, and features relevant to quantum many-body systems. We demonstrate its performance on fermionic models and nuclear Hamiltonians by casting the spectrum reconstruction problem as a quadratic program solved via compressed sensing. These use cases highlight the potential of DOS-QPE for early fault-tolerant quantum simulations in spectroscopy, electronic structure, and nuclear theory.
Abstract: 量子相位估计(QPE)是提取哈密顿量本征值的核心算法,但其标准形式针对单个本征态,并需要精心准备的相干输入。为了克服这些限制,我们采用了一种基于集合的QPE公式,该公式估计演化哈密顿量生成器的状态密度(DOS)。这种方法,我们称之为DOS-QPE,建立在作者之一之前提出的公式基础上。在本工作中,我们将DOS-QPE作为电路原语进行展示,并通过对称适应的输入集合和先进的光谱重构技术对其进行扩展。这种QPE变体能够自然地访问热力学性质、对称性分辨的光谱函数以及与量子多体系统相关的特性。我们通过将光谱重构问题转化为通过压缩感知求解的二次规划问题,在费米子模型和核哈密顿量上展示了其性能。这些用例突显了DOS-QPE在光谱学、电子结构和核理论中早期容错量子模拟中的潜力。
Comments: 15 pages, 5 figures
Subjects: Quantum Physics (quant-ph)
Cite as: arXiv:2510.14744 [quant-ph]
  (or arXiv:2510.14744v1 [quant-ph] for this version)
  https://doi.org/10.48550/arXiv.2510.14744
arXiv-issued DOI via DataCite

Submission history

From: Stefano Scali [view email]
[v1] Thu, 16 Oct 2025 14:49:27 UTC (641 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • HTML (experimental)
  • TeX Source
view license
Current browse context:
quant-ph
< prev   |   next >
new | recent | 2025-10

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号