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arxiv: 2312.05344 · v3 · pith:2LB5GXJVnew · submitted 2023-12-08 · 🪐 quant-ph · hep-lat· hep-ph· nucl-th

Quantum Algorithms for Simulating Nuclear Effective Field Theories

James D. Watson , Jacob Bringewatt , Alexander F. Shaw , Andrew M. Childs , Alexey V. Gorshkov , Zohreh Davoudi This is my paper

Pith reviewed 2026-05-24 05:13 UTC · model grok-4.3

classification 🪐 quant-ph hep-lathep-phnucl-th
keywords quantum simulationnuclear effective field theoryHamiltonian simulationresource estimationpionless EFTTrotter errorphase estimation
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The pith

Simulating low-energy nuclear effective field theories on quantum computers requires qubit and gate counts improved by several orders of magnitude over prior estimates, with the pionless EFT being the least costly.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper calculates the resources needed to run time evolution and energy estimation for nuclear lattice effective field theories on quantum computers. It compares the leading-order pionless EFT against one-pion-exchange and dynamical-pion versions, finding the pionless model cheapest, followed by static pions then dynamical pions. Costs incorporate truncation of long-range forces or pionic space as well as product-formula and phase-estimation errors. Symmetries of the Hamiltonians and locality of nucleonic interactions when mapped to qubits are used to tighten bounds and allow parallelization. New error bounds are derived for fermionic number-preserving Hamiltonians by explicit nested-commutator calculation. A sympathetic reader would care because the lower costs bring quantum simulation of nuclear processes closer to feasibility.

Core claim

Within the nuclear lattice EFT framework, the leading-order pionless EFT is the least costly to simulate, followed by the one-pion-exchange theory and then the dynamical-pion theory. Resource costs are estimated for time evolution and energy estimation at physically relevant scales, accounting for truncation errors in long-range interactions or the pionic Hilbert space and algorithmic errors from product-formula approximations and quantum phase estimation. Symmetries of the low-energy nuclear Hamiltonians are utilized to obtain tighter error bounds. By retaining the locality of nucleonic interactions when mapped to qubits, reduced circuit depth and substantial parallelization are achieved. T

What carries the argument

Hamiltonian simulation with product formulas and quantum phase estimation, using symmetries and locality-preserving mappings of fermionic interactions to obtain tighter Trotter and overall error bounds.

If this is right

  • The pionless EFT requires the fewest qubits and gates among the three models.
  • Retaining locality of interactions on qubits enables substantial parallelization and shallower circuits.
  • Explicit computation of nested commutators yields tighter Trotter error bounds than standard estimates.
  • Symmetries of the Hamiltonians produce improved error bounds for both time evolution and energy estimation.
  • Dynamical pions incur the highest costs because of the additional bosonic field degrees of freedom.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • These improved scalings could be used to set concrete targets for qubit counts and coherence times in hardware designed for nuclear many-body problems.
  • The locality-preserving mapping technique might be applied directly to other fermionic lattice models outside nuclear physics.
  • If the error bounds remain valid at larger system sizes, certain nuclear reaction rates previously inaccessible to classical computation could become simulable on intermediate-scale quantum devices.

Load-bearing premise

The chosen physical scales, truncation cutoffs for long-range interactions or pionic Hilbert space, and the validity of the leading-order EFTs themselves do not introduce errors that would invalidate the reported resource scalings.

What would settle it

An explicit gate-count calculation or small-scale simulation of a low-energy nuclear process whose measured resource requirement exceeds the paper's estimated scaling by more than one order of magnitude.

Figures

Figures reproduced from arXiv: 2312.05344 by Alexander F. Shaw, Alexey V. Gorshkov, Andrew M. Childs, Jacob Bringewatt, James D. Watson, Zohreh Davoudi.

Figure 1
Figure 1. Figure 1: Feynman diagrams that schematically represent the various interactions encountered at leading order in the [PITH_FULL_IMAGE:figures/full_fig_p008_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: A sketch of how the Jordan-Wigner string appears in the [PITH_FULL_IMAGE:figures/full_fig_p012_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Schematic representation of various interactions in the different EFTs on a representative 2D plane of the 3D [PITH_FULL_IMAGE:figures/full_fig_p018_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The circuit used to implement the time evolution of the contact interaction for the pionless EFT, taken from [PITH_FULL_IMAGE:figures/full_fig_p029_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: A 2D cross section of the 3D lattice showing how the kinetic hopping terms along a) [PITH_FULL_IMAGE:figures/full_fig_p030_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: A sample of interaction terms present in the long-range Hamiltonian. In each figure, the interactions denoted [PITH_FULL_IMAGE:figures/full_fig_p033_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Examples of 8-qubit and 7-qubit systems, where colored lines between the filled circles represent entangling [PITH_FULL_IMAGE:figures/full_fig_p036_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: The circuit used to implement evolution under the term [PITH_FULL_IMAGE:figures/full_fig_p038_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The circuit used to implement 𝑒 −𝑖𝑡𝐻WT (x) according to the decomposition proposed in Eq. (104). where 𝐼1 is fixed for given 𝐼2 and 𝐼3 because of the Levi-Civita tensor. Then, at each site x, one may decompose the operator 𝑒 −𝑖𝑡𝐻WT (x) as 𝑒 −𝑖𝑡𝐻WT (x) ≈ 𝑒 −𝑖𝑡𝐻(1,2) WT (x) 𝑒 −𝑖𝑡𝐻(3,2) WT (x) 𝑒 −𝑖𝑡𝐻(1,3) WT (x) 𝑒 −𝑖𝑡𝐻(2,3) WT (x) 𝑒 −𝑖𝑡𝐻(2,1) WT (x) 𝑒 −𝑖𝑡𝐻(3,1) WT (x) , (103) up to a Trotter error that is cal… view at source ↗
Figure 10
Figure 10. Figure 10: Circuit implementing evolution under 1 4 𝑓 2 𝜋  𝑃1 + 𝑄 Í𝑛𝑏 −1 𝑚=0 2 𝑚𝑍 (𝑚) 2,x  𝑃 ′1 + 𝑄 ′ Í𝑛𝑏 −1 𝑙=0 2 𝑙𝑍 (𝑙) 3,x  𝑋 ↑𝑝 𝑖 𝑋 ↑𝑛 𝑖 𝑍 ↓𝑝 𝑖 [see Eq. (74)]. 𝐻 denotes a Hadamard gate, 𝑅 ( 𝑓 ) 𝑧 is a 𝑍 rotation with angle 𝑡 𝑃𝑃′ 4 𝑓 2 𝜋 , 𝑅 (𝑘) 𝑧 is a 𝑍 rotation with angle 𝑡𝑄𝑃′ 4 𝑓 2 𝜋 2 𝑘 , 𝑅¯ (𝑘) 𝑧 is a 𝑍 rotation with angle 𝑡𝑄′𝑃 4 𝑓 2 𝜋 2 𝑘 , and 𝑅 (𝑘,𝑙) 𝑧 is a 𝑍 rotation with angle 𝑡𝑄𝑄′ 4 𝑓 2 𝜋 2 𝑘+𝑙 . … view at source ↗
Figure 11
Figure 11. Figure 11: Plots showing the 2-qubit circuit depth (left) and [PITH_FULL_IMAGE:figures/full_fig_p049_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Comparison of the pionless EFT 2-qubit circuit depths for this work and Ref. [50] for simulating evolution for the crossing time to a total error of 0.1 using a 𝑝 = 2 product formula. Here, we assume a 10×10×10 lattice with 𝑎𝐿 = 1.4 fm (to be consistent with the lattice spacing choice in Ref. [50]), with a kinetic energy per nucleon of 𝐸kin = 10 MeV. 1 10 100 105 106 107 108 109 Number of Nucleons 2-Qubit… view at source ↗
Figure 14
Figure 14. Figure 14: Circuit depth (left) and 𝑇-gate cost (right) as a function of the number of nucleons for quantum phase estimation to 1 MeV of precision on a 10 × 10 × 10 lattice with 𝑎𝐿 = 2.2 fm with an energy cutoff of 140 MeV, and with correctness probability 1 − 𝛿 = 0.3. gates that can be implemented before useful information can be extracted. In particular, given the requirement of a few hundred layers of gates to be… view at source ↗
Figure 15
Figure 15. Figure 15: Quantum-phase-estimation circuit depth costs for the pionless EFT for [PITH_FULL_IMAGE:figures/full_fig_p051_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: a) A possible ordering of the physical sites (circles) on a 2D lattice for mapping to qubits via a Jordan-Wigner [PITH_FULL_IMAGE:figures/full_fig_p061_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: a) A possible ordering of the physical sites on a 3D lattice for mapping to qubits via a Jordan-Wigner [PITH_FULL_IMAGE:figures/full_fig_p061_17.png] view at source ↗
Figure 18
Figure 18. Figure 18: Examples of 𝑋 and 𝑌 and their decompositions into local, disjoint, translationally invariant NPFOs. The colored regions represent where the operators act non-trivially [PITH_FULL_IMAGE:figures/full_fig_p074_18.png] view at source ↗
Figure 19
Figure 19. Figure 19: All possible overlapping translations of [PITH_FULL_IMAGE:figures/full_fig_p074_19.png] view at source ↗
Figure 20
Figure 20. Figure 20: Consider a set of terms which are translations of the top-left operator in [PITH_FULL_IMAGE:figures/full_fig_p075_20.png] view at source ↗
Figure 21
Figure 21. Figure 21: The lines represent the possible places the operators can overlap. Generally, the maximum number of [PITH_FULL_IMAGE:figures/full_fig_p075_21.png] view at source ↗
Figure 22
Figure 22. Figure 22: Solid red, blue, and green, and dashed red, blue, and green lines each represent hopping terms in a distinct [PITH_FULL_IMAGE:figures/full_fig_p082_22.png] view at source ↗
Figure 23
Figure 23. Figure 23: A decomposition of the kinetic-kinetic commutator terms. [PITH_FULL_IMAGE:figures/full_fig_p082_23.png] view at source ↗
Figure 24
Figure 24. Figure 24: A decomposition of the kinetic-kinetic-kinetic commutator terms. [PITH_FULL_IMAGE:figures/full_fig_p086_24.png] view at source ↗
Figure 25
Figure 25. Figure 25: (a) All diagonal north-west facing terms in [PITH_FULL_IMAGE:figures/full_fig_p092_25.png] view at source ↗
Figure 26
Figure 26. Figure 26: The red triangle represents the triangle formed by two vectors [PITH_FULL_IMAGE:figures/full_fig_p102_26.png] view at source ↗
read the original abstract

Quantum computers offer the potential to simulate nuclear processes that are classically intractable. With the goal of understanding the necessary quantum resources to realize this potential, we employ state-of-the-art Hamiltonian-simulation methods, and conduct a thorough algorithmic analysis, to estimate the qubit and gate costs to simulate low-energy effective field theories (EFTs) of nuclear physics. Within the framework of nuclear lattice EFT, we obtain simulation costs for the leading-order pionless and pionful EFTs. For the latter, we consider both static pions represented by a one-pion-exchange potential between the nucleons, and dynamical pions represented by relativistic bosonic fields coupled to non-relativistic nucleons. Within these models, we examine the resource costs for the tasks of time evolution and energy estimation for physically relevant scales. We account for model errors associated with truncating either long-range interactions in the one-pion-exchange EFT or the pionic Hilbert space in the dynamical-pion EFT, and for algorithmic errors associated with product-formula approximations and quantum phase estimation. We find that the pionless EFT is the least costly to simulate, followed by the one-pion-exchange theory, then the dynamical-pion theory. We demonstrate how symmetries of the low-energy nuclear Hamiltonians can be utilized to obtain tighter error bounds. By retaining the locality of nucleonic interactions when mapped to qubits, we achieve reduced circuit depth and substantial parallelization. In the process, we develop new methods to bound the algorithmic error for classes of fermionic number-preserving Hamiltonians, and obtain tighter Trotter error bounds by explicitly computing nested commutators of Hamiltonian terms. Compared to previous estimates for the pionless EFT, our results represent an improvement by several orders of magnitude.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript estimates qubit and gate costs for quantum simulation of leading-order nuclear lattice EFTs (pionless, static one-pion-exchange, and dynamical-pion) using product formulas and quantum phase estimation. It accounts for model truncation errors and algorithmic errors, derives new Trotter bounds via explicit nested commutators for number-preserving fermionic Hamiltonians, exploits symmetries and locality for tighter bounds and parallelization, and claims several orders-of-magnitude resource improvement over prior pionless-EFT estimates.

Significance. If the resource numbers and fair comparison hold, the work supplies concrete, improved feasibility estimates for nuclear EFT simulation and introduces reusable techniques for bounding Trotter error in local fermionic Hamiltonians; the explicit commutator calculations and retention of interaction locality are concrete strengths that could be adopted more broadly.

major comments (2)
  1. [Abstract] Abstract: the central claim of 'an improvement by several orders of magnitude' relative to previous pionless-EFT estimates is load-bearing for the paper's contribution; however, no side-by-side table or explicit matching argument is provided for lattice spacing, spatial volume, nucleon number, target accuracy, or truncation cutoffs, leaving open the possibility that part of the reported reduction arises from a redefinition of the physical problem instance rather than algorithmic advance alone.
  2. [Abstract / model-error discussion] Model-error paragraph (abstract and corresponding methods section): the statement that 'model errors associated with truncating either long-range interactions... or the pionic Hilbert space' are accounted for is central to validating the final resource scalings, yet the manuscript does not show how the chosen cutoffs propagate into the quoted gate counts or whether they are stricter, equal, or looser than those used in the referenced prior estimates.
minor comments (2)
  1. [Throughout] Notation for lattice parameters (a, L, N) should be introduced once with a dedicated table and used uniformly in all resource formulas and numerical examples.
  2. [Figures] Figure captions for resource plots should explicitly state the physical scales (volume, nucleon number, target precision) used in each curve.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the careful review and constructive feedback. The comments correctly identify areas where explicit comparisons to prior work can be strengthened for clarity. We address each point below and will revise the manuscript accordingly.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the central claim of 'an improvement by several orders of magnitude' relative to previous pionless-EFT estimates is load-bearing for the paper's contribution; however, no side-by-side table or explicit matching argument is provided for lattice spacing, spatial volume, nucleon number, target accuracy, or truncation cutoffs, leaving open the possibility that part of the reported reduction arises from a redefinition of the physical problem instance rather than algorithmic advance alone.

    Authors: We agree that an explicit side-by-side comparison would eliminate ambiguity. In the revised manuscript we will add a table (main text or appendix) that matches lattice spacing, spatial volume, nucleon number, target accuracy, and truncation cutoffs between our pionless-EFT estimates and the referenced prior work. The table will be accompanied by text clarifying that the reported orders-of-magnitude reduction originates from the new symmetry-based Trotter bounds, explicit nested-commutator calculations, and locality-preserving qubit mapping rather than from altered problem definitions. revision: yes

  2. Referee: [Abstract / model-error discussion] Model-error paragraph (abstract and corresponding methods section): the statement that 'model errors associated with truncating either long-range interactions... or the pionic Hilbert space' are accounted for is central to validating the final resource scalings, yet the manuscript does not show how the chosen cutoffs propagate into the quoted gate counts or whether they are stricter, equal, or looser than those used in the referenced prior estimates.

    Authors: We acknowledge that the propagation of the chosen cutoffs into the final gate counts should be shown explicitly. In the revision we will expand the methods section and add a short appendix subsection that derives or bounds how the long-range-interaction cutoff (one-pion-exchange EFT) and pionic-Hilbert-space truncation (dynamical-pion EFT) enter the resource estimates. Where data from prior estimates are available we will note whether our cutoffs are comparable, stricter, or adjusted for the specific models, thereby making the accounting for model error transparent. revision: yes

Circularity Check

0 steps flagged

Resource estimates derived via explicit commutator calculations and algorithmic constructions with no reduction to fitted inputs or self-definitional steps

full rationale

The paper performs explicit algorithmic analysis of Hamiltonian simulation costs for nuclear EFTs, including computation of nested commutators to tighten Trotter bounds, utilization of symmetries for error bounds, and retention of locality in qubit mappings. These steps are constructive and independent of the target resource numbers being estimated. The orders-of-magnitude improvement claim is a post-hoc comparison to external prior work rather than a derivation that reduces to the same data or parameters by construction. No self-citation chains, ansatzes smuggled via citation, or fitted inputs renamed as predictions appear in the load-bearing steps. The derivations remain self-contained against external benchmarks such as explicit error accounting and model truncations.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

Resource estimates depend on domain-standard choices of EFT cutoffs, physical scales, and the assumption that leading-order nuclear lattice EFTs capture the relevant low-energy physics; no new entities are postulated.

free parameters (1)
  • truncation cutoffs for long-range interactions or pionic Hilbert space
    Explicitly invoked when accounting for model errors; values chosen to keep errors below algorithmic targets but not derived from first principles within the paper.
axioms (2)
  • domain assumption Leading-order pionless and pionful nuclear lattice EFTs provide faithful low-energy descriptions of nuclear interactions at the scales considered
    Foundation for all cost estimates; stated in the abstract's description of the models examined.
  • standard math Standard Hamiltonian-simulation error bounds (product formulas, phase estimation) apply directly once the nuclear Hamiltonian is mapped to qubits
    Used to convert Trotter and phase-estimation errors into gate counts.

pith-pipeline@v0.9.0 · 5870 in / 1532 out tokens · 37191 ms · 2026-05-24T05:13:54.871826+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

207 extracted references · 207 canonical work pages · cited by 6 Pith papers · 7 internal anchors

  1. [1]

    Theorem 48(One-Pion-Exchange Trotter Error Bound)

    One-Pion-Exchange Bounds In this Appendix, we derive the𝑝 = 1Trotter error bounds for the OPE EFT Hamiltonian. Theorem 48(One-Pion-Exchange Trotter Error Bound). For the time evolution of the OPE EFT with a first-order product formula, P (OPE) 1 (𝑡) − 𝑒−𝑖𝑡 𝐻OPE 𝜂 ≤ 𝑡2 2 𝜁, where𝜁 is the sum of the bounds which are reported in the Lemmas noted in Table XVI...

    work page

  2. [2]

    Wethenpartition the terms as per the Trotter decomposition used

    Dynamical-Pion Bounds Thedynamical-pioncaserequiresustodealwiththeexplicitrepresentationofthepions. Wethenpartition the terms as per the Trotter decomposition used. To this end,𝐻 𝜋 defined in Eq. (67) is split into two separate contributions: 𝐻 (1) 𝜋 B 𝐻Π2 = 𝑎𝐷 𝐿 2 ∑︁ x ∑︁ 𝐼 Π2 𝐼 (x), (G124) 𝐻 (2) 𝜋 B 𝐻(∇ 𝜋 )2 + 𝐻 𝜋2 = 𝑎𝐷−2 𝐿 2 ∑︁ x, 𝑗 ∑︁ 𝐼 𝜋𝐼 (x + 𝑎 𝐿 ˆn...

    work page

  3. [3]

    Carlson and W

    J. Carlson and W. Nazarewicz,Exascale Requirements Review for Nuclear Physics, Tech. Rep. (Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2016)

    work page 2016

  4. [4]

    Bedaqueet al., A.I

    P. Bedaqueet al., A.I. for nuclear physics, Eur. Phys. J. A57, 100 (2021)

    work page 2021

  5. [5]

    Boehnlein, M

    A. Boehnlein, M. Diefenthaler, N. Sato, M. Schram, V. Ziegler, C. Fanelli, M. Hjorth-Jensen, T. Horn, M. P. Kuchera, D. Lee, W. Nazarewicz, P. Ostroumov, K. Orginos, A. Poon, X.-N. Wang, A. Scheinker, M. S. Smith, and L.-G. Pang, Colloquium: Machine learning in nuclear physics, Rev. Mod. Phys.94, 031003 (2022)

    work page 2022

  6. [6]

    Y. Aoki, T. Blum, G. Colangelo, S. Collins, M. D. Morte, P. Dimopoulos, S. Dürr, X. Feng, H. Fukaya, M. Golterman,et al., Flag review 2021, Eur. Phys. J. C82, 869 (2022)

    work page 2021

  7. [7]

    Davoudi, E

    Z. Davoudi, E. T. Neil, C. W. Bauer, T. Bhattacharya, T. Blum, P. Boyle, R. C. Brower, S. Catterall, N. H. Christ, V. Cirigliano,et al., Report of the snowmass 2021 topical group on lattice gauge theory, arXiv preprint arXiv:2209.10758 (2022)

    work page arXiv 2021

  8. [8]

    Davoudi, W

    Z. Davoudi, W. Detmold, P. Shanahan, K. Orginos, A. Parreno, M. J. Savage, and M. L. Wagman, Nuclear matrix elements from lattice QCD for electroweak and beyond-standard-model processes, Phys. Rep.900, 1 (2021)

    work page 2021

  9. [9]

    Drischler, W

    C. Drischler, W. Haxton, K. McElvain, E. Mereghetti, A. Nicholson, P. Vranas, and A. Walker-Loud, Towards grounding nuclear physics in QCD, Prog. Part. Nucl. Phys.121, 103888 (2021)

    work page 2021

  10. [10]

    Carlson, S

    J. Carlson, S. Gandolfi, F. Pederiva, S. C. Pieper, R. Schiavilla, K. Schmidt, and R. B. Wiringa, Quantum monte carlo methods for nuclear physics, Rev. Mod. Phys.87, 1067 (2015)

    work page 2015

  11. [11]

    B. R. Barrett, P. Navrátil, and J. P. Vary, Ab initio no core shell model, Prog. Part. Nucl. Phys.69, 131 (2013)

    work page 2013

  12. [12]

    Hagen, T

    G. Hagen, T. Papenbrock, M. Hjorth-Jensen, and D. J. Dean, Coupled-cluster computations of atomic nuclei, Rep. Prog. Phys.77, 096302 (2014)

    work page 2014

  13. [13]

    Carbone, A

    A. Carbone, A. Cipollone, C. Barbieri, A. Rios, and A. Polls, Self-consistent Green’s functions formalism with three-body interactions, Phys. Rev. C88, 054326 (2013)

    work page 2013

  14. [14]

    Rep.621, 165 (2016)

    H.Hergert,S.K.Bogner,T.D.Morris,A.Schwenk,andK.Tsukiyama,Thein-mediumsimilarityrenormalization group: A novel ab initio method for nuclei, Phys. Rep.621, 165 (2016)

    work page 2016

  15. [15]

    T. A. Lähde and U.-G. Meißner,Nuclear lattice effective field theory: An introduction, Vol. 957 (Springer, 2019)

    work page 2019

  16. [16]

    I. Tews, Z. Davoudi, A. Ekström, J. D. Holt, and J. E. Lynn, New ideas in constraining nuclear forces, J. Phys. G 47, 103001 (2020). 112

    work page 2020

  17. [17]

    Navratil and S

    P. Navratil and S. Quaglioni, Ab initio nuclear reaction theory with applications to astrophysics, arXiv preprint arXiv:2204.01187 (2022)

    work page arXiv 2022

  18. [18]

    L. A. Ruso, A. Ankowski, S. Bacca, A. Balantekin, J. Carlson, S. Gardiner, R. Gonzalez-Jimenez, R. Gupta, T. Hobbs, M. Hoferichter,et al., Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators, arXiv preprint arXiv:2203.09030 (2022)

    work page arXiv 2022

  19. [19]

    K. D. Launey, A. Mercenne, and T. Dytrych, Nuclear dynamics and reactions in the ab initio symmetry-adapted framework, Annu. Rev. Nucl. Part. Sci.71, 253 (2021)

    work page 2021

  20. [20]

    Faessler, G

    A. Faessler, G. L. Fogli, E. Lisi, V. Rodin, A. M. Rotunno, and F. Šimkovic, Quasiparticle random phase approximation uncertainties and their correlations in the analysis of0𝜈𝛽𝛽 decay, Phys. Rev. D79, 053001 (2009)

    work page 2009

  21. [21]

    Arima and F

    A. Arima and F. Iachello, The interacting boson model, Annu. Rev. Nucl. Part. Sci.31, 75 (1981)

    work page 1981

  22. [22]

    Nikšić, D

    T. Nikšić, D. Vretenar, and P. Ring, Relativistic nuclear energy density functionals: Mean-field and beyond, Prog. Part. Nucl. Phys.66, 519 (2011)

    work page 2011

  23. [23]

    90,222501(2003)

    Y.YuandA.Bulgac,Energydensityfunctionalapproachtosuperfluidnuclei,Phys.Rev.Lett. 90,222501(2003)

    work page 2003

  24. [24]

    A.Bulgac,S.Jin,andI.Stetcu,Nuclearfissiondynamics: past,present,needs,andfuture,Front.Phys.(Lausanne) , 63 (2020)

    work page 2020

  25. [25]

    J. W. Negele, The mean-field theory of nuclear structure and dynamics, Rev. Mod. Phys.54, 913 (1982)

    work page 1982

  26. [26]

    E.Caurier,G.Martínez-Pinedo,F.Nowacki,A.Poves,andA.Zuker,Theshellmodelasaunifiedviewofnuclear structure, Rev. Mod. Phys.77, 427 (2005)

    work page 2005

  27. [27]

    Otsuka, M

    T. Otsuka, M. Honma, T. Mizusaki, N. Shimizu, and Y. Utsuno, Monte carlo shell model for atomic nuclei, Prog. Part. Nucl. Phys.47, 319 (2001)

    work page 2001

  28. [28]

    McArdle, S

    S. McArdle, S. Endo, A. Aspuru-Guzik, S. C. Benjamin, and X. Yuan, Quantum computational chemistry, Rev. Mod. Phys.92, 015003 (2020)

    work page 2020

  29. [29]

    Y.Cao,J.Romero,J.P.Olson,M.Degroote,P.D.Johnson,M.Kieferová,I.D.Kivlichan,T.Menke,B.Peropadre, N. P. Sawaya,et al., Quantum chemistry in the age of quantum computing, Chem. Rev.119, 10856 (2019)

    work page 2019

  30. [31]

    Bauer, S

    B. Bauer, S. Bravyi, M. Motta, and G. K.-L. Chan, Quantum algorithms for quantum chemistry and quantum materials science, Chem. Rev.120, 12685 (2020)

    work page 2020

  31. [32]

    von Burg, G

    V. von Burg, G. H. Low, T. Häner, D. S. Steiger, M. Reiher, M. Roetteler, and M. Troyer, Quantum computing enhanced computational catalysis, Phys. Rev. Research3, 033055 (2021)

    work page 2021

  32. [33]

    Clinton, T

    L. Clinton, T. Cubitt, B. Flynn, F. M. Gambetta, J. Klassen, A. Montanaro, S. Piddock, R. A. Santos, and E. Sheridan, Towards near-term quantum simulation of materials, Nat. Commun.15, 211 (2024)

    work page 2024

  33. [34]

    C. W. Bauer, Z. Davoudi, A. B. Balantekin, T. Bhattacharya, M. Carena, W. A. de Jong, P. Draper, A. El-Khadra, N.Gemelke,M.Hanada,D.Kharzeev,H.Lamm,Y.-Y.Li,J.Liu,M.Lukin,Y.Meurice,C.Monroe,B.Nachman, G. Pagano, J. Preskill, E. Rinaldi, A. Roggero, D. I. Santiago, M. J. Savage, I. Siddiqi, G. Siopsis, D. Van Zanten, N. Wiebe, Y. Yamauchi, K. Yeter-Aydeniz,...

    work page 2023

  34. [35]

    Catterall, R

    S. Catterall, R. Harnik, V. E. Hubeny, C. W. Bauer, A. Berlin, Z. Davoudi, T. Faulkner, T. Hartman, M. Headrick, Y. F. Kahn,et al., Report of the snowmass 2021 theory frontier topical group on quantum information science, arXiv preprint arXiv:2209.14839 (2022)

    work page arXiv 2021

  35. [36]

    T. S. Humble, G. N. Perdue, and M. J. Savage, Snowmass computational frontier: Topical group report on quantum computing, arXiv preprint arXiv:2209.06786 (2022)

    work page arXiv 2022

  36. [37]

    Becket al., Nuclear Physics and Quantum Information Science: Report by the NSAC QIS Subcommittee, Tech

    D. Becket al., Nuclear Physics and Quantum Information Science: Report by the NSAC QIS Subcommittee, Tech. Rep. (NSF & DOE Office of Science, 2019)

    work page 2019

  37. [38]

    D. Beck, J. Carlson, Z. Davoudi, J. Formaggio, S. Quaglioni, M. Savage, J. Barata, T. Bhattacharya, M. Bishof, I. Cloet,et al., Quantum information science and technology for nuclear physics. input into us long-range planning, 2023, arXiv preprint arXiv:2303.00113 (2023)

    work page arXiv 2023

  38. [39]

    C. W. Bauer, Z. Davoudi, N. Klco, and M. J. Savage, Quantum simulation of fundamental particles and forces, Nature Rev. Phys.5, 420 (2023)

    work page 2023

  39. [40]

    N. C. Rubin, D. W. Berry, A. Kononov, F. D. Malone, T. Khattar, A. White, J. Lee, H. Neven, R. Babbush, and A. D. Baczewski, Quantum computation of stopping power for inertial fusion target design, Proceedings of the 113 National Academy of Sciences121, e2317772121 (2024)

    work page 2024

  40. [41]

    Wecker, B

    D. Wecker, B. Bauer, B. K. Clark, M. B. Hastings, and M. Troyer, Gate-count estimates for performing quantum chemistry on small quantum computers, Phys. Rev. A90, 022305 (2014)

    work page 2014

  41. [42]

    M. B. Hastings, D. Wecker, B. Bauer, and M. Troyer, Improving quantum algorithms for quantum chemistry, arXiv preprint arXiv:1403.1539 (2014)

    work page internal anchor Pith review Pith/arXiv arXiv 2014

  42. [43]

    Wecker, M

    D. Wecker, M. B. Hastings, N. Wiebe, B. K. Clark, C. Nayak, and M. Troyer, Solving strongly correlated electron models on a quantum computer, Phys. Rev. A92, 062318 (2015)

    work page 2015

  43. [44]

    Babbush, N

    R. Babbush, N. Wiebe, J. McClean, J. McClain, H. Neven, and G. K.-L. Chan, Low-depth quantum simulation of materials, Phys. Rev. X8, 011044 (2018)

    work page 2018

  44. [45]

    Peruzzo, J

    A. Peruzzo, J. McClean, P. Shadbolt, M.-H. Yung, X.-Q. Zhou, P. J. Love, A. Aspuru-Guzik, and J. L. O’Brien, A variational eigenvalue solver on a photonic quantum processor, Nat. Commun.5, 4213 (2014)

    work page 2014

  45. [46]

    Phys.18, 023023 (2016)

    J.R.McClean,J.Romero,R.Babbush,andA.Aspuru-Guzik,Thetheoryofvariationalhybridquantum-classical algorithms, New J. Phys.18, 023023 (2016)

    work page 2016

  46. [47]

    P. J. O’Malley, R. Babbush, I. D. Kivlichan, J. Romero, J. R. McClean, R. Barends, J. Kelly, P. Roushan, A. Tranter, N. Ding,et al., Scalable quantum simulation of molecular energies, Phys. Rev. X6, 031007 (2016)

    work page 2016

  47. [48]

    Cerezo, A

    M. Cerezo, A. Arrasmith, R. Babbush, S. C. Benjamin, S. Endo, K. Fujii, J. R. McClean, K. Mitarai, X. Yuan, L. Cincio,et al., Variational quantum algorithms, Nat. Rev. Phys.3, 625 (2021)

    work page 2021

  48. [49]

    Quantum computation algorithm for many-body studies

    E. Ovrum and M. Hjorth-Jensen, Quantum computation algorithm for many-body studies, arXiv preprint arXiv:0705.1928 (2007)

    work page internal anchor Pith review Pith/arXiv arXiv 1928

  49. [50]

    E. F. Dumitrescu, A. J. McCaskey, G. Hagen, G. R. Jansen, T. D. Morris, T. Papenbrock, R. C. Pooser, D. J. Dean, and P. Lougovski, Cloud quantum computing of an atomic nucleus, Phys. Rev. Lett.120, 210501 (2018)

    work page 2018

  50. [51]

    Roggero and J

    A. Roggero and J. Carlson, Dynamic linear response quantum algorithm, Phys. Rev. C100, 034610 (2019), arXiv:1804.01505 [quant-ph]

    work page arXiv 2019

  51. [52]

    A.Roggero,A.C.Li,J.Carlson,R.Gupta,andG.N.Perdue,Quantumcomputingforneutrino-nucleusscattering, Phys. Rev. D101, 074038 (2020)

    work page 2020

  52. [53]

    Roggero, C

    A. Roggero, C. Gu, A. Baroni, and T. Papenbrock, Preparation of excited states for nuclear dynamics on a quantum computer, Phys. Rev. C102, 064624 (2020)

    work page 2020

  53. [54]

    Baroni, J

    A. Baroni, J. Carlson, R. Gupta, A. C. Li, G. N. Perdue, and A. Roggero, Nuclear two point correlation functions on a quantum computer, Phys. Rev. D105, 074503 (2022)

    work page 2022

  54. [55]

    K. Choi, D. Lee, J. Bonitati, Z. Qian, and J. Watkins, Rodeo algorithm for quantum computing, Phys. Rev. Lett. 127, 040505 (2021)

    work page 2021

  55. [56]

    Z. Qian, J. Watkins, G. Given, J. Bonitati, K. Choi, and D. Lee, Demonstration of the rodeo algorithm on a quantum computer, arXiv preprint arXiv:2110.07747 (2021)

    work page arXiv 2021

  56. [57]

    E. T. Holland, K. A. Wendt, K. Kravvaris, X. Wu, W. E. Ormand, J. L. DuBois, S. Quaglioni, and F. Pederiva, Optimal control for the quantum simulation of nuclear dynamics, Phys. Rev. A101, 062307 (2020)

    work page 2020

  57. [58]

    Turro, T

    F. Turro, T. Chistolini, A. Hashim, Y. Kim, W. Livingston, J. M. Kreikebaum, K. A. Wendt, J. L. Dubois, F. Pederiva, S. Quaglioni, D. I. Santiago, and I. Siddiqi, Demonstration of a quantum-classical coprocessing protocol for simulating nuclear reactions, Phys. Rev. A108, 032417 (2023)

    work page 2023

  58. [59]

    Turro, A

    F. Turro, A. Roggero, V. Amitrano, P. Luchi, K. A. Wendt, J. L. DuBois, S. Quaglioni, and F. Pederiva, Imaginary-time propagation on a quantum chip, Phys. Rev. A105, 022440 (2022)

    work page 2022

  59. [60]

    Stetcu, A

    I. Stetcu, A. Baroni, and J. Carlson, Projection algorithm for state preparation on quantum computers, Phys. Rev. C108, L031306 (2023)

    work page 2023

  60. [61]

    W. Du, J. P. Vary, X. Zhao, and W. Zuo, Ab initio nuclear structure via quantum adiabatic algorithm, arXiv preprint arXiv:2105.08910 (2021)

    work page arXiv 2021

  61. [62]

    W. Du, J. P. Vary, X. Zhao, and W. Zuo, Quantum simulation of nuclear inelastic scattering, Phys. Rev. A104, 012611 (2021)

    work page 2021

  62. [63]

    W. Qian, R. Basili, S. Pal, G. Luecke, and J. P. Vary, Solving hadron structures with variational quantum eigensolvers, arXiv preprint arXiv:2112.01927 (2021)

    work page arXiv 2021

  63. [64]

    Shehab, K

    O. Shehab, K. Landsman, Y. Nam, D. Zhu, N. M. Linke, M. Keesan, R. C. Pooser, and C. Monroe, Toward convergence of effective-field-theory simulations on digital quantum computers, Phys. Rev. A100, 062319 (2019). 114

    work page 2019

  64. [65]

    Pérez-Obiol, A

    A. Pérez-Obiol, A. Romero, J. Menéndez, A. Rios, A. García-Sáez, and B. Juliá-Díaz, Nuclear shell-model simulation in digital quantum computers, Sci. Rep.13, 12291 (2023)

    work page 2023

  65. [66]

    C.E.P.RobinandM.J.Savage,Quantumsimulationsineffectivemodelspaces: Hamiltonian-learningvariational quantum eigensolver using digital quantum computers and application to the lipkin-meshkov-glick model, Phys. Rev. C108, 024313 (2023)

    work page 2023

  66. [67]

    I. D. Kivlichan, N. Wiebe, R. Babbush, and A. Aspuru-Guzik, Bounding the costs of quantum simulation of many-body physics in real space, J. Phys. A: Math. Theor.50, 305301 (2017)

    work page 2017

  67. [68]

    Y. Su, D. W. Berry, N. Wiebe, N. Rubin, and R. Babbush, Fault-tolerant quantum simulations of chemistry in first quantization, PRX Quantum2, 040332 (2021), arXiv:2105.12767

    work page arXiv 2021

  68. [69]

    Babbush, D

    R. Babbush, D. W. Berry, I. D. Kivlichan, A. Y. Wei, P. J. Love, and A. Aspuru-Guzik, Exponentially more precise quantum simulation of fermions in second quantization, New J. Phys.18, 033032 (2016)

    work page 2016

  69. [70]

    Jorgensen,Second quantization-based methods in quantum chemistry(Elsevier, 2012)

    P. Jorgensen,Second quantization-based methods in quantum chemistry(Elsevier, 2012)

    work page 2012

  70. [71]

    N. Moll, A. Fuhrer, P. Staar, and I. Tavernelli, Optimizing qubit resources for quantum chemistry simulations in second quantization on a quantum computer, J. Phys. A: Math. Theor.49, 295301 (2016)

    work page 2016

  71. [72]

    Babbush, D

    R. Babbush, D. W. Berry, Y. R. Sanders, I. D. Kivlichan, A. Scherer, A. Y. Wei, P. J. Love, and A. Aspuru-Guzik, Exponentially more precise quantum simulation of fermions in the configuration interaction representation, Quantum Science and Technology3, 015006 (2017)

    work page 2017

  72. [73]

    T. F. Stetina, A. Ciavarella, X. Li, and N. Wiebe, Simulating effective qed on quantum computers, Quantum6, 622 (2022)

    work page 2022

  73. [74]

    Lee, Lattice simulations for few-and many-body systems, Prog

    D. Lee, Lattice simulations for few-and many-body systems, Prog. Part. Nucl. Phys.63, 117 (2009)

    work page 2009

  74. [75]

    M.Suzuki,Generaltheoryoffractalpathintegralswithapplicationstomany-bodytheoriesandstatisticalphysics, J. Math. Phys.32, 400 (1991)

    work page 1991

  75. [76]

    Wiebe, D

    N. Wiebe, D. Berry, P. Hoyer, and B. C. Sanders, Higher order decompositions of ordered operator exponentials, J. Phys. A: Math. Theor.43, 065203 (2010)

    work page 2010

  76. [77]

    A. M. Childs, Y. Su, M. C. Tran, N. Wiebe, and S. Zhu, Theory of trotter error with commutator scaling, Phys. Rev. X11, 011020 (2021)

    work page 2021

  77. [78]

    Su, H.-Y

    Y. Su, H.-Y. Huang, and E. T. Campbell, Nearly tight trotterization of interacting electrons, Quantum5, 495 (2021)

    work page 2021

  78. [79]

    Yi and E

    C. Yi and E. Crosson, Spectral analysis of product formulas for quantum simulation, npj Quantum Inf.8, 37 (2022)

    work page 2022

  79. [80]

    Şahinoğlu and R

    B. Şahinoğlu and R. D. Somma, Hamiltonian simulation in the low-energy subspace, npj Quantum Inf.7, 119 (2021)

    work page 2021

  80. [81]

    Q. Zhao, Y. Zhou, A. F. Shaw, T. Li, and A. M. Childs, Hamiltonian simulation with random inputs, Phys. Rev. Lett.129, 270502 (2022)

    work page 2022

Showing first 80 references.