Paper Citation Record · LEDGER

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2502.01730.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.01730 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation 026f450a-eeea-48ab-b02e-15ff5c9aabb7 · outbound

This paper cites an unresolved cited work.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Unresolved cited work

Reference 1

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This paper cites Disentangling Hype from Practicality: On Realistically Achieving Quantum Advantage.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Disentangling Hype from Practicality: On Realistically Achieving Quantum Advantage

Reference 2

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This paper cites Prospects of Quantum Computing for Molecular Sciences.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Prospects of Quantum Computing for Molecular Sciences

Reference 3

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This paper cites Emerging quantum computing algorithms for quantum chemistry.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Emerging quantum computing algorithms for quantum chemistry

Reference 4

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This paper cites Measurements as a roadblock to near-term practical quantum advantage in chemistry: resource analysis.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Measurements as a roadblock to near-term practical quantum advantage in chemistry: resource analysis

Reference 5

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This paper cites Minimizing State Preparations in Variational Quantum Eigensolver by Partitioning into Commuting Families.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Minimizing State Preparations in Variational Quantum Eigensolver by Partitioning into Commuting Families

Reference 6

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This paper cites Pauli Partitioning with Respect to Gate Sets.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Pauli Partitioning with Respect to Gate Sets

Reference 7

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This paper cites Measurement Optimization in the Variational Quantum Eigensolver Using a Minimum Clique Cover.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Measurement Optimization in the Variational Quantum Eigensolver Using a Minimum Clique Cover

Reference 8

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This paper cites Efficient quantum measurement of Pauli operators in the presence of finite sampling error.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Efficient quantum measurement of Pauli operators in the presence of finite sampling error

Reference 9

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This paper cites Measurement reduction in variational quantum algorithms.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Measurement reduction in variational quantum algorithms

Reference 10

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Observation 66346ba3-1aa3-4391-86da-a54d3dd1b48e · outbound

This paper cites Operator Sampling for Shot-frugal Optimization in Variational Algorithms.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Operator Sampling for Shot-frugal Optimization in Variational Algorithms

Reference 11

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This paper cites Predicting Features of Quantum Systems from Very Few Measurements.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Predicting Features of Quantum Systems from Very Few Measurements

Reference 12

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Predicting Many Properties of a Quantum System from Very Few Measurements

Reference 13

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This paper cites The randomized measurement toolbox.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information The randomized measurement toolbox

Reference 14

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This paper cites Measurements of Quantum Hamiltonians with Locally-Biased Classical Shadows.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Measurements of Quantum Hamiltonians with Locally-Biased Classical Shadows

Reference 15

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This paper cites Adaptive estimation of quantum observables.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Adaptive estimation of quantum observables

Reference 16

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This paper cites Overlapped grouping measurement: A unified framework for measuring quantum states.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Overlapped grouping measurement: A unified framework for measuring quantum states

Reference 17

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Observation bc38d4e0-acd4-4f05-b6b7-b6d7f0e12eac · outbound

This paper cites Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping

Reference 18

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This paper cites Optimizing Shot Assignment in Variational Quantum Eigensolver Measurement.

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Optimizing Shot Assignment in Variational Quantum Eigensolver Measurement

Reference 19

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Unresolved cited work

Reference 20

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Audibert, R

Reference 21

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This paper cites Mnih,Efficient stopping rules, Master’s thesis, Univer- sity of Alberta (2008).

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Mnih,Efficient stopping rules, Master’s thesis, Univer- sity of Alberta (2008)

Reference 22

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Elucidating Reaction Mechanisms on Quantum Computers

Reference 23

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Quantum computing enhanced computational catalysis

Reference 24

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets

Reference 25

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Quantum chemistry calculations on a trapped-ion quantum simulator

Reference 26

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Hartree-Fock on a superconducting qubit quantum computer

Reference 27

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Optimizing Electronic Structure Simulations on a Trapped-ion Quantum Computer using Problem Decomposition

Reference 28

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Unresolved cited work

Reference 29

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Qibo: a framework for quantum simulation with hardware acceleration

Reference 30

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Unresolved cited work

Reference 31

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information A variational eigenvalue solver on a quantum processor

Reference 32

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Towards Practical Quantum Variational Algorithms

Reference 33

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information The theory of variational hybrid quantum-classical algorithms

Reference 34

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Shot-noise reduction for lattice Hamiltonians

Reference 35

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Scalable Quantum Simulation of Molecular Energies

Reference 36

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This paper cites Hadfield, adaptiveshadows, GitHub repos- itory https://github.com/charleshadfield/ adaptiveshadows/tree/main/Hamiltonians (2021).

Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Hadfield, adaptiveshadows, GitHub repos- itory https://github.com/charleshadfield/ adaptiveshadows/tree/main/Hamiltonians (2021)

Reference 37

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Gresch and M

Reference 38

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Jordan and W

Reference 39

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Observation 1c5f310c-1bc6-4ab5-84be-6e6c77420a86 · outbound

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information Unresolved cited work

Reference 40

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Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information The Bravyi-Kitaev transformation for quantum computation of electronic structure

Reference 41

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