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REVIEW 3 major objections 3 minor 70 references

Resource-efficient quantum-selected configuration interaction for molecular properties

T0 review · 3 major / 3 minor · reviewed 2026-08-01 · deepseek-v4-flash

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Pith's one-line read Truncating a molecular Hamiltonian to its most reference-exciting Pauli terms preserves chemical accuracy while cutting quantum circuit resources by over 98 percent.

desk verdict Useful heuristic for QSCI resource reduction, honestly presented; hardware results are encouraging but the central ranking justification is acknowledged as incomplete and one text claim overstates the energy agreement. read the letter →

arxiv 2607.27777 v1 pith:HSJFIRIU submitted 2026-07-30 quant-ph physics.atom-phphysics.chem-ph

Suprava Sahoo , Abdul Kalam , Kenji Sugisaki , V. S. Prasannaa , B.P. Das This is my paper
classification quant-phphysics.atom-phphysics.chem-ph PACS 03.67.-a31.15.A33.15.-e
keywords quantum-selectedconfigurationinteractionHamiltoniantruncationreference-statefidelitylossrelativisticquantumchemistryelectricdipolemomentsPaulioperatorsortingTrotter-basedtimeevolutionNISQdevices
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper claims that the full electronic Hamiltonian of a molecule can be replaced, for quantum time evolution, by a compact Hamiltonian containing only the few Pauli terms that most strongly excite the Dirac–Hartree–Fock reference state. Ranking terms by a cheap, classical second-order fidelity-loss estimate and keeping 99 percent of the cumulative weight reproduces complete-active-space configuration interaction energies and permanent electric dipole moments, while cutting the number of Hamiltonian terms, circuit depth, and two-qubit gates by around 95–98 percent for 20-qubit relativistic systems. Demonstrated on real quantum hardware for AlF and TlF, the truncated Hamiltonian yields dipole moments matching CASCI within about 0.1 percent. If correct, this removes a major bottleneck—circuit depth and gate count—in quantum-selected configuration interaction on noisy intermediate-scale quantum devices.

What carries the argument

The central object is the reference-state fidelity loss omega_alpha(t) = h_alpha^2 t^2 [1 − |<Phi_0|P_alpha|Phi_0>|^2], the second-order short-time probability that a single Pauli operator P_alpha with coefficient h_alpha drives the Dirac–Hartree–Fock reference out of the state. Each Pauli string is ranked by this scalar, a cumulative normalized weight is formed, and the smallest K terms reaching 99 percent weight define the truncated Hamiltonian H' = sum_{alpha=1}^K h_alpha P_alpha. This screening happens entirely classically, before any circuit is built, and it is what converts a 10,000-term Hamiltonian into a few hundred terms.

What would settle it

Take a molecule in a strongly correlated regime (e.g., a stretched bond or a diradical) where single-reference perturbation theory is known to fail; run the truncated QSCI with c.w.(K)=0.99 and compare the time-evolved determinant distribution to full-Hamiltonian HSB-QSCI. If the truncated Hamiltonian omits determinants that carry significant CASCI weight, the energy will miss chemical accuracy and the central claim collapses.

Watch

Extended reading notes

Core claim

On its own terms, the paper establishes that reference-state fidelity loss, computed as omega_alpha ≈ h_alpha^2 [1 − |<Phi_0|P_alpha|Phi_0>|^2], is a reliable ranking criterion for Pauli terms in the molecular Hamiltonian. Discarding all terms whose cumulative weight falls below 1 percent leaves a Hamiltonian whose real-time evolution samples the same dominant determinants as the full Hamiltonian, so the classically diagonalized projected Hamiltonian recovers ground-state energies within about 1 mHa and PDMs within about 0.015 a.u. of CASCI across the Group IIIA monofluoride series. The scaling advantage grows with system size: the retained-term count grows roughly as N^2.3 versus N^4 for th

Load-bearing premise

The ordering of Pauli terms by their single-operator, second-order effect on the Hartree–Fock reference state is assumed to stay valid when many terms act together during the full time evolution, an assumption the paper explicitly leaves unverified for longer evolution or higher Krylov order.

Editorial extensions

If this is right

  • Relativistic molecular-property calculations (e.g., permanent electric dipole moments) become feasible on present-day noisy quantum processors up to at least 20 qubits, because circuit depth and CX-count scale with the retained terms, not the full Hamiltonian.
  • The classical cost of QSCI's final diagonalization drops as well: only about 0.9 percent of the CASCI determinant space was needed for 20-qubit TlF, turning a 4845-determinant problem into a 43-determinant one.
  • The resource gap between the truncated and full-Hamiltonian approaches widens with system size (fitted exponents ~1.7 for Hamiltonian terms, ~1.3–1.4 for depth and CX gates), so the method becomes more attractive as molecules grow.
  • Because the fidelity-loss computation is per-term and independent, the screening step can be parallelized across classical resources, keeping the classical overhead modest.
  • The same truncation strategy should transfer to other observables that are linear in the density, because the wavefunction itself is preserved in the selected subspace.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The fidelity-loss ordering is a single-reference heuristic; the paper itself flags that for K>1 multi-configurational evolution, terms with small omega can become relevant via higher-order excitations. A natural extension would be to iterate: run the truncated QSCI, use the sampled multi-configurational state to re-rank operators, and add terms based on a state-averaged fidelity loss.
  • Because the truncation is Hamiltonian-level rather than circuit-level, it is compatible with other cost-reduction strategies (Trotter ordering, randomized simulation, commutation-based grouping) and could be composed with them for further gains.
  • The method's success on 4-electron monofluorides, which are weakly correlated, leaves open whether the 99 percent cumulative-weight threshold remains sufficient for strongly correlated systems; a calibration study on bond-breaking or diradical systems would map where the single-reference ranking breaks down.
  • The PDM accuracy on hardware (within about 0.1 percent of CASCI) suggests that Hamiltonian truncation plus standard error mitigation may suffice for reliable expectation values of one-body operators; testing on transition dipoles or gradients would stress the method further.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 3 minor

Summary. The paper introduces eos-QSCI, a variant of Hamiltonian-simulation-based quantum-selected configuration interaction (HSB-QSCI) in which the Pauli Hamiltonian is truncated before time evolution. Pauli terms are ranked by a reference-state fidelity-loss score ωα(t) ≈ h_α^2 t^2 [1 − |⟨Φ0|Pα|Φ0⟩|^2] (Eq. 9), and the smallest set of terms whose cumulative weight reaches c.w.(K)=0.99 is retained. The method is applied to relativistic Group IIIA monofluorides (BF, AlF, GaF, InF, TlF) using Dirac–Coulomb Hamiltonians and active spaces of 12–20 qubits. The authors report classical simulations and hardware executions of AlF and TlF on IBM Marrakesh, claiming up to 98% reductions in circuit depth and two-qubit gate counts, with energies and permanent electric dipole moments close to CASCI reference values. The central claim is that this truncation preserves the determinant subspace needed for chemical accuracy while substantially reducing quantum resources.

Significance. If the heuristic is valid, eos-QSCI would be a practical way to extend QSCI to larger relativistic systems on NISQ devices, and the paper demonstrates a clear application to molecular properties beyond ground-state energies. The manuscript has several strengths: it benchmarks a consistent series of five molecules and four active-space sizes, reports real hardware runs with error mitigation, and explicitly acknowledges that the ranking criterion may fail for multi-configurational evolution. The resource reductions are quantified and the baseline is the full-Hamiltonian HSB-QSCI, not a fitted model. However, the central ranking principle is not validated for the actual multi-term Trotter product, and one hardware-results sentence overstates the accuracy. The method is therefore plausible and worth publishing after major revision, but the current version does not establish the generality of the claimed resource-accuracy trade-off.

major comments (3)
  1. [§II.D, Eq. (9); §III time-evolution parameters (n=1, t=1, K=1)] The fidelity-loss score ωα is derived for evolution under a single Pauli operator, but the state used in the results is a first-order Trotter product of hundreds of Pauli exponentials (e.g., 271 terms for TlF at 20 qubits). For non-commuting operators, the fidelity loss of the product is not the sum of single-operator losses; nested commutators can generate determinants that no individual Pα creates from |Φ0⟩. The limitation paragraph in §II.D only addresses 'K>1' (Krylov order) and does not cover the multi-term single-step product. The empirical CASCI agreement is encouraging, but it does not validate the ranking principle. A concrete test would be to compare the determinant subspace produced by the truncated Hamiltonian with that produced by the full Hamiltonian in the same Trotter product, especially for a more strongly correlated system.
  2. [Table IV and §III (hardware results)] The sentence 'The resulting ground-state energies agree with the CASCI reference within ~0.01 mHa' is contradicted by Table IV: ΔE = 0.289 mHa for AlF (20 qubits), 0.114 mHa for AlF (18), and 0.465 mHa for TlF (14). This is an order-of-magnitude overclaim. The conclusion's 'below 0.01%' is ambiguous if it refers to relative energy error. The authors should either correct the summary statement or report per-system deviations explicitly.
  3. [§II.D / Appendix B: cumulative-weight threshold] The truncation threshold c.w.(K)=0.99 is chosen post hoc: no a priori selection rule is given, and Appendix B only demonstrates that increasing the threshold retains more terms. Since the claimed 98% Hamiltonian-term reduction is reported at this specific threshold, the resource advantage is conditional on a user-tuned parameter. A systematic study of energy/PDM error and resource counts as a function of η, including statistical uncertainties, is needed to show that the truncation is robust rather than a fit to the CASCI benchmark.
minor comments (3)
  1. [§II.C and §II.D, Eqs. (5) and (10)] The symbol K is used both for the Krylov expansion order in Eq. (5) and for the number of retained Hamiltonian terms in Eq. (10). This is confusing; please use distinct symbols (e.g., M for the number of retained terms).
  2. [Fig. 3 and Appendix C] The power-law exponents b_HT=1.70±0.37, b_CD=1.31±0.36, and b_CX=1.41±0.35 are based on only four system sizes per molecule. The uncertainty intervals overlap with linear scaling (b=1) and quadratic scaling (b=2); the abstract's 'near-quadratic' claim should be tempered or accompanied by confidence intervals and goodness-of-fit measures.
  3. [Data Availability Statement] The statement 'The data are available from the authors on reasonable request' is vague. For a computational methods paper, depositing the code, integral-generation scripts, and raw measurement data in a public repository would substantially improve reproducibility.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: Pauli-term ranking and Hamiltonian truncation are independent of the target energies/PDMs; the acknowledged multi-configurational limitation is an accuracy risk, not a circular reduction.

full rationale

The eos-QSCI derivation chain is self-contained: PHASE-I applies an occupation-based screening rule (annihilation operators must act on occupied orbitals), which is a structural selection independent of the target observables. PHASE-II ranks Pauli terms by the reference-state fidelity loss of Eq. (9), computed from the DHF reference and Hamiltonian coefficients only. The cumulative-weight threshold c.w.(K)=0.99 is applied uniformly across systems, and the final energies and PDMs are obtained by diagonalizing the truncated Hamiltonian and are reported against external CASCI references; they are not fitted individually to CASCI. The resource reductions are compared with the full-Hamiltonian HSB-QSCI baseline, so the claimed >98% savings are not reductions to the method's own inputs. The paper itself flags the main limitation: 'The present framework ranks Hamiltonian terms based on their action on the reference state, UK|Φ0⟩ for K=1. For K>1, the evolved state becomes multi-configurational, allowing operators that initially have negligible contributions to become important through higher-order excitations. The systematic assessment of this limitation is left for future investigation.' That is a genuine transferability/accuracy caveat about the single-operator ranking applied to a multi-term Trotter evolution, but it is not a circular step: no equation equates the predicted energy/PDM to the ranking input. Self-citations involving coauthors (e.g., refs. 17, 24, 27, 29, 30) appear as background or baseline references, not as load-bearing uniqueness or ansatz-smuggling arguments. Score 2 reflects only the minor presence of self-citations and the post hoc-sounding threshold justification, not any construction-level circularity.

Assumptions & free parameters 4 free parameters · 4 assumptions · 0 invented entities

The central claims rest on four protocol choices and two heuristic assumptions: the 99% cumulative-weight threshold, the t=1/n=1/K=1 evolution settings, and the reference-state-based screening/fidelity-loss ordering. No new physical entities are introduced.

free parameters (4)
  • cumulative-weight truncation threshold (c.w.) = 0.99
    Chosen as the smallest K with c.w.(K) ≥ 0.99 (Section II.D); all accuracy and resource claims use this threshold. It is selected post hoc to stay within chemical accuracy for the studied systems, not fixed by an a priori error bound.
  • real-time evolution length t = 1 (atomic units)
    Set to t=1 for all simulations; no convergence study of t is reported, and the fidelity-loss second-order expansion assumes small h_α t for each retained term.
  • Trotter-Suzuki order and step count = first-order, n=1
    Single Trotter step with first-order formula is used; Trotter error is not separately quantified in the determinant-selection step.
  • Krylov expansion order K = 1
    Only K=1 time-evolved state is used; the paper states the K>1 case is left for future investigation.
assumptions (4)
  • domain assumption The Dirac-Coulomb Hamiltonian in the Born-Oppenheimer approximation describes the relevant molecular electronic structure.
    Eq. (1) is the starting point; standard in relativistic quantum chemistry but not verified in this paper.
  • ad hoc to paper Pauli term importance for the full time evolution is rankable by the second-order single-operator fidelity loss ωα(t).
    Eq. (9) truncates the expansion at O(t²) and ignores multi-term interference; the authors acknowledge breakdown for K>1.
  • ad hoc to paper Hamiltonian terms that annihilate the DHF reference can be discarded without changing the sampled determinant subspace.
    PHASE-I/Appendix A screening eliminates terms with zero action on |Φ0⟩; for multi-configurational evolved states such terms can contribute.
  • domain assumption Active-space PDMs plus frozen-core and nuclear contributions give the total PDM.
    Standard active-space property evaluation; not compared with experiment in this work.

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Cite this review

Pith. "Pith review of Resource-efficient quantum-selected configuration interaction for molecular properties." pith.science (2026). https://pith.science/paper/HSJFIRIU

@misc{pith2026260727777,
  author       = {Pith},
  title        = {Pith review of: Resource-efficient quantum-selected configuration interaction for molecular properties},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HSJFIRIU}},
  note         = {Machine review of arXiv:2607.27777}
}
abstract

The quantum-selected configuration interaction identifies important determinantal basis functions through real-time evolution of a reference wavefunction and diagonalizing the Hamiltonian matrix in the resulting selected subspace. However, implementing the full electronic Hamiltonian on noisy quantum devices leads to rapidly increasing circuit complexity, limiting its scalability. To address this issue, we identify the dominant fermionic excitation operators and perform reference-state fidelity loss analysis to construct a compact Hamiltonian, reducing computational overhead while retaining high precision. Applied to Group IIIA monofluorides (BF, AlF, GaF, InF, and TlF), the proposed framework achieves a near-quadratic improvement in Hamiltonian-term scaling, enabling resource-efficient simulations. We employ this framework to compute the relativistic ground-state energies and permanent electric dipole moments (PDMs) of the systems under consideration. After validating the framework via simulations, we demonstrate hardware execution for AlF and TlF on the IBM Marrakesh processor using active spaces of up to 20 qubits. For a 20-qubit TlF system, the reduced Hamiltonian yields a reduction of higher than $ 98\%$ in both circuit depth and two-qubit gate counts, with the resulting PDMs from quantum hardware matching complete active space configuration interaction values within $99.99\%$. These results demonstrate the scalability of this approach on noisy intermediate-scale quantum devices.

Figures

Figures reproduced from arXiv: 2607.27777 by the authors.

Figure 1
Figure 1. Schematic workflow of the proposed eos-QSCI method. [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Absolute energy deviations, ∆E = |Eeos-QSCI − ECASCI|, for Group IIIA monofluorides obtained with eos￾QSCI for active spaces corresponding to (a) 12, (b) 14, (c) 18, and (d) 20 qubits. The vertical axis is shown on a logarithmic scale. The dashed horizontal line indicates the chemical ac￾curacy threshold (1.6 mHa), and the numerical values of ∆E (mHa) are labeled at each data point. step (n = 1), time t = 1, and K =… view at source ↗
Figure 3
Figure 3. Scaling of the normalized resource reduction ratio, [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗

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Works this paper leans on

70 extracted references · 3 linked inside Pith

  1. [1]

    The systematic assessment of this limitation is left for future investigation

    ForK>1, the evolved state becomes multi- configurational, allowing operators that initially have negligible contributions to become important through higher-order excitations. The systematic assessment of this limitation is left for future investigation. The selected operators define the truncated Hamilto- nian, H ′ q = KX α=1 hαPα,(11) which is partition...

    arXiv 1969

  2. [2]

    Y. Cao, J. Romero, J. P. Olson, M. Degroote, P. D. John- son, M. Kieferová, I. D. Kivlichan, T. Menke, B. Per- opadre, N. P. Sawaya,et al., Quantum chemistry in the age of quantum computing, Chemical Reviews119, 10856 (2019)

    2019

  3. [3]

    McArdle, S

    S. McArdle, S. Endo, A. Aspuru-Guzik, S. C. Benjamin, and X. Yuan, Quantum computational chemistry, Re- views of Modern Physics92, 015003 (2020)

    2020

  4. [4]

    Shavitt, The method of configuration interaction, in Methods of Electronic Structure Theory(Springer, 1977) pp

    I. Shavitt, The method of configuration interaction, in Methods of Electronic Structure Theory(Springer, 1977) pp. 189–275

    1977

  5. [5]

    Aspuru-Guzik, A

    A. Aspuru-Guzik, A. D. Dutoi, P. J. Love, and M. Head- Gordon, Simulated quantum computation of molecular energies, Science309, 1704 (2005)

    2005

  6. [6]

    Santagati, J

    R. Santagati, J. Wang, A. A. Gentile, S. Paesani, N. Wiebe, J. R. McClean, S. Morley-Short, P. J. Shad- bolt, D. Bonneau, J. W. Silverstone,et al., Witnessing eigenstates for quantum simulation of Hamiltonian spec- tra, Science Advances4, eaap9646 (2018)

    2018

  7. [7]

    N. S. Blunt, L. Caune, R. Izsák, E. T. Campbell, and N. Holzmann, Statistical phase estimation and error mit- igation on a superconducting quantum processor, PRX Quantum4, 040341 (2023)

    2023

  8. [8]

    Yamamoto, S

    K. Yamamoto, S. Duffield, Y. Kikuchi, and D. Muñoz Ramo, Demonstrating Bayesian quan- tum phase estimation with quantum error detection, Physical Review Research6, 013221 (2024)

    2024

Show all 70 references
  1. [9]

    Mohammadbagherpoor, Y.-H

    H. Mohammadbagherpoor, Y.-H. Oh, P. Dreher, A. Singh, X. Yu, and A. J. Rindos, An improved im- plementation approach for quantum phase estimation on quantum computers, in2019 IEEE International Confer- ence on Rebooting Computing (ICRC)(IEEE, 2019) pp. 1–9

    2019

  2. [10]

    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, Nature Communications5, 4213 (2014)

    2014

  3. [11]

    Tilly, H

    J. Tilly, H. Chen, S. Cao, D. Picozzi, K. Setia, Y. Li, E. Grant, L. Wossnig, I. Rungger, G. H. Booth,et al., The variational quantum eigensolver: a review of meth- ods and best practices, Physics Reports986, 1 (2022)

    2022

  4. [12]

    J. F. Gonthier, M. D. Radin, C. Buda, E. J. Doskocil, C. M. Abuan, and J. Romero, Measurements as a road- block tonear-term practical quantum advantage in chem- istry: Resource analysis, Physical Review Research4, 033154 (2022)

    2022

  5. [13]

    J. R. McClean, S. Boixo, V. N. Smelyanskiy, R. Bab- bush, and H. Neven, Barren plateaus in quantum neural network training landscapes, Nature Communications9, 4812 (2018)

    2018

  6. [14]

    Kanno, M

    K. Kanno, M. Kohda, R. Imai, S. Koh, K. Mitarai, W. Mizukami, and Y. O. Nakagawa, Quantum-selected configuration interaction: classical diagonalization of Hamiltonians in subspaces selected by quantum comput- ers, Physical Review Research8, 023268 (2026)

    2026

  7. [15]

    Y. O. Nakagawa, M. Kamoshita, W. Mizukami, S. Sudo, and Y.-y. Ohnishi, Adapt-qsci: Adaptive construction of an input state for quantum-selected configuration inter- action, Journal of Chemical Theory and Computation 20, 10817 (2024)

    2024

  8. [16]

    Farhi, J

    E. Farhi, J. Goldstone, S. Gutmann, and M. Sipser, Quantum computation by adiabatic evolution, arXiv preprint quant-ph/0001106 (2000)

    2000 arXiv

  9. [17]

    Robledo-Moreno, M

    J. Robledo-Moreno, M. Motta, H. Haas, A. Javadi- Abhari, P. Jurcevic, W. Kirby, S. Martiel, K. Sharma, S. Sharma, T. Shirakawa,et al., Chemistry beyond the scale of exact diagonalization on a quantum-centric su- percomputer, Science Advances11, eadu9991 (2025)

    2025

  10. [18]

    Sugisaki, S

    K. Sugisaki, S. Kanno, T. Itoko, R. Sakuma, and N. Yamamoto, Hamiltonian simulation-based quantum- selected configuration interaction for large-scale elec- tronic structure calculations with a quantum computer, Physical Chemistry Chemical Physics27, 20869 (2025)

    2025

  11. [19]

    Mikkelsen and Y

    M. Mikkelsen and Y. O. Nakagawa, Quantum-selected configuration interaction with time-evolved state, Physi- cal Review Research7, 043043 (2025)

    2025

  12. [20]

    J. Yu, J. R. Moreno, J. T. Iosue, L. Bertels, D. Claudino, B. Fuller, P. Groszkowski, T. S. Humble, P. Ju- rcevic, W. Kirby,et al., Quantum-centric algorithm for sample-based krylov diagonalization, arXiv preprint arXiv:2501.09702 (2025)

    2025

  13. [21]

    Y.-C. Chen, R. Wu, M. Cheng, and M.-H. Hsieh, Neural network assisted fermionic compression encod- ing: A lossy quantum-selected configuration interac- tion framework for resource-efficient ground-state simu- lations, Physical Review Research8, 013128 (2026)

    2026

  14. [22]

    Ohgoe, H

    T. Ohgoe, H. Iwakiri, K. Ichikawa, S. Koh, and M. Ko- hda,Quantumcomputationofaquasiparticlebandstruc- turewiththequantum-selectedconfigurationinteraction, Journal of the Physical Society of Japan94, 114002 (2025)

    2025

  15. [23]

    Schow, L

    K.Yamamoto, R.Masui, T.Nakajima, M.Tsuji, M.Sato, P. Schow, L. Heidemann, M. Burke, P. Seitz, O. J. Backhouse,et al., Quantum-HPC hybrid computation of biomolecular excited-state energies, arXiv preprint arXiv:2601.15677 (2026)

    2026

  16. [24]

    Kaliakin, A

    D. Kaliakin, A. Shajan, F. Liang, J. Robledo Moreno, Z. Li, A. Mitra, M. Motta, C. Johnson, A. A. Saki, S. Das,et al., Accurate quantum-centric simulations of intermolecular interactions, Communications Physics8, 9 396 (2025)

    2025

  17. [25]

    K. Sugisaki, Size-consistent implementation of hamilto- niansimulation-basedquantum-selectedconfigurationin- teraction method for the supramolecular approach, arXiv preprint arXiv:2510.23154 (2025)

    2025

  18. [26]

    L. Veis, J. Višňák, T. Fleig, S. Knecht, T. Saue, L. Viss- cher, and J. Pittner, Relativistic quantum chemistry on quantum computers, Physical Review A85, 030304 (2012)

    2012

  19. [27]

    T. F. Stetina, A. Ciavarella, X. Li, and N. Wiebe, Sim- ulating effective QED on quantum computers, Quantum 6, 622 (2022)

    2022

  20. [28]

    Chawla, Shweta, K

    P. Chawla, Shweta, K. Swain, T. Patel, R. Bala, D. Shetty, K. Sugisaki, S. B. Mandal, J. Riu, J. Nogue, et al., Relativistic variational-quantum-eigensolver calcu- lations of molecular electric dipole moments on quantum hardware, Physical Review A111, 022817 (2025)

    2025

  21. [29]

    Kumar, N

    V. Kumar, N. Baskaran, V. S. Prasannaa, K. Sugisaki, D. Mukherjee, K. Dyall, and B. P. Das, Computation of relativistic and many-body effects in atomic systems us- ing quantum annealing, Physical Review A109, 042808 (2024)

    2024

  22. [30]

    A. P. Singh, K. Sugisaki, V. S. Prasannaa, B. K. Sahoo, B.P.Das,andY.Nakamura,Experimentalcomputations of atomic properties on a superconducting quantum pro- cessor, Physical Review A110, 062620 (2024)

    2024

  23. [31]

    Sugisaki, V

    K. Sugisaki, V. S. Prasannaa, S. Ohshima, T. Katagiri, Y. Mochizuki, B. Sahoo, and B. Das, Bayesian phase dif- ference estimation algorithm for direct calculation of fine structure splitting: accelerated simulation of relativistic and quantum many-body effects, Electronic Stru...

    2023

  24. [32]

    Mishra, R

    T. Mishra, R. V. Pai, S. Ramanan, M. S. Luthra, and B. P. Das, Supersolid and solitonic phases in the one- dimensional extended Bose-Hubbard model, Physical Re- view A80, 043614 (2009)

    2009

  25. [33]

    Trefzger, C

    C. Trefzger, C. Menotti, B. Capogrosso-Sansone, and M. Lewenstein, Ultracold dipolar gases in optical lat- tices, Journal of Physics B: Atomic, Molecular and Op- tical Physics44, 193001 (2011)

    2011

  26. [34]

    DeMille, Quantum computation with trapped polar molecules, Physical Review Letters88, 067901 (2002)

    D. DeMille, Quantum computation with trapped polar molecules, Physical Review Letters88, 067901 (2002)

    2002

  27. [35]

    A. C. Vutha, W. C. Campbell, Y. V. Gurevich, N. R. Hutzler, M. Parsons, D. Patterson, E. Petrik, B. Spaun, J. M. Doyle, G. Gabrielse,et al., Search for the elec- tric dipole moment of the electron with thorium monox- ide, Journal of Physics B: Atomic, Molecular and Optical Phy...

    2010

  28. [36]

    Hoeft, F

    J. Hoeft, F. Lovas, E. Tiemann, and T. Törring, On the production and stability of some Group III A monofluo- rides, Zeitschrift für Naturforschung B25, 901 (1970)

    1970

  29. [37]

    Padilla-Castillo, J

    J. Padilla-Castillo, J. Cai, P. Agarwal, P. Kukreja, R. Thomas, B. G. Sartakov, S. Truppe, G. Meijer, and S. Wright, Magneto-optical trapping of aluminum monofluoride, Physical Review Letters135, 243401 (2025)

    2025

  30. [38]

    Hoeft, F

    J. Hoeft, F. Lovas, E. Tiemann, and T. Törring, Mi- crowave absorption spectra of AlF, GaF, InF, and TIF, Zeitschrift für Naturforschung A25, 1029 (1970)

    1970

  31. [39]

    Al Shawa, N

    S. Al Shawa, N. El-Kork, G. Younes, and M. Korek, The- oretical study with dipole moment calculation of new electronic states of the molecule BF, Nanotechnology Re- views5, 363 (2016)

    2016

  32. [40]

    Truppe, S

    S. Truppe, S. Marx, S. Kray, M. Doppelbauer, S. Hof- säss, H. C. Schewe, N. Walter, J. Pérez-Ríos, B. G. Sar- takov, and G. Meijer, Spectroscopic characterization of aluminum monofluoride with relevance to laser cooling and trapping, Physical Review A100, 052513 (2019)

    2019

  33. [41]

    Hunter, S

    L. Hunter, S. Peck, A. Greenspon, S. S. Alam, and D. De- Mille, Prospects for laser cooling TlF, Physical Review A85, 012511 (2012)

    2012

  34. [42]

    M. Abe, T. Tsutsui, J. Ekman, M. Hada, and B. Das, Accurate determination of the enhancement factor X for the nuclear schiff moment in205TlF molecule based on the four-component relativistic coupled-cluster theory, Molecular Physics118, e1767814 (2020)

    2020

  35. [43]

    Grasdijk, O

    O. Grasdijk, O. Timgren, J. Kastelic, T. Wright, S. Lam- oreaux, D. DeMille, K. Wenz, M. Aitken, T. Zelevinsky, T. Winick,et al., CeNTREX: a new search for time- reversal symmetry violation in the205Tl nucleus, Quan- tum Science & Technology6, 044007 (2021)

    2021

  36. [44]

    Gao and T

    Y.-f. Gao and T. Gao, Laser cooling of BH and GaF: in- sights from an ab initio study, Physical Chemistry Chem- ical Physics17, 10830 (2015)

    2015

  37. [45]

    Yang and T

    Q.-S. Yang and T. Gao, Feasibility study of laser cooling of InF molecule, Molecular Physics115, 702 (2017)

    2017

  38. [46]

    Pan and P

    F. Pan and P. Zhang, Simulation of quantum circuits using the big-batch tensor network method, Physical Re- view Letters128, 030501 (2022)

    2022

  39. [47]

    Rogerson and A

    D. Rogerson and A. Roy, Quantum circuit optimiza- tion using differentiable programming of tensor network states, arXiv preprint arXiv:2408.12583 (2024)

    2024 arXiv

  40. [48]

    I. P. Grant,Relativistic quantum theory of atoms and molecules: theory and computation(Springer, 2007)

    2007

  41. [49]

    Szabo and N

    A. Szabo and N. S. Ostlund,Modern quantum chem- istry: introduction to advanced electronic structure theory (Courier Corporation, 2012)

    2012

  42. [50]

    A. A. Holmes, N. M. Tubman, and C. J. Umrigar, Heat- bath configuration interaction: An efficient selected con- figuration interaction algorithm inspired by heat-bath sampling, Journal of Chemical Theory and Computation 12, 3674 (2016)

    2016

  43. [51]

    Jordan and E

    P. Jordan and E. Wigner, Über das paulische äquivalen- zverbot, Zeitschrift für Physik47, 631 (1928)

    1928

  44. [52]

    H. F. Trotter, On the product of semi-groups of opera- tors, Proceedings of the American Mathematical Society 10, 545 (1959)

    1959

  45. [53]

    M. Suzuki, Relationship between d-dimensional quan- tal spin systems and (d + 1)-dimensional Ising systems: Equivalence, critical exponents and systematic approx- imants of the partition function and spin correlations, Progress of Theoretical Physics56, 1454 (1976)

    1976

  46. [54]

    C. L. Cortes and S. K. Gray, Quantum Krylov subspace algorithms for ground-and excited-state energy estima- tion, Physical Review A105, 022417 (2022)

    2022

  47. [55]

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

    2021

  48. [56]

    Campbell, A random compiler for fast hamiltonian simulation, Physical Review Letters123, 070503 (2019)

    E. Campbell, A random compiler for fast hamiltonian simulation, Physical Review Letters123, 070503 (2019)

    2019

  49. [57]

    L. T. Brady and S. Hadfield, Iterative quantum algo- rithms for maximum independent set, Physical Review A110, 052435 (2024)

    2024

  50. [58]

    Verteletskyi, T.-C

    V. Verteletskyi, T.-C. Yen, and A. F. Izmaylov, Measure- ment optimization in the variational quantum eigensolver using a minimum clique cover, The Journal of Chemical Physics152, 12 (2020)

    2020

  51. [59]

    Javadi-Abhari, M

    A. Javadi-Abhari, M. Treinish, K. Krsulich, C. J. Wood, 10 J. Lishman, J. Gacon, S. Martiel, P. D. Nation, L. S. Bishop, A. W. Cross,et al., Quantum computing with qiskit, arXiv preprint arXiv:2405.08810 (2024)

    2024 arXiv

  52. [60]

    Sivarajah, S

    S. Sivarajah, S. Dilkes, A. Cowtan, W. Simmons, A. Edg- ington, and R. Duncan, t| ket>: a retargetable com- piler for NISQ devices, Quantum Science & Technology 6, 014003 (2021)

    2021

  53. [61]

    K. G. Dyall, Relativistic quadruple-zeta and revised triple-zeta and double-zeta basis sets for the 4p, 5p, and 6p elements, Theoretical Chemistry Accounts115, 441 (2006)

    2006

  54. [62]

    Murad, D

    E. Murad, D. L. Hildenbrand, and R. P. Main, Dissoci- ation energies of Group IIIA monofluorides—the possi- bility of potential maxima in their excitedπstates, The Journal of Chemical Physics45, 263 (1966)

    1966

  55. [63]

    Jaszunski, T

    M. Jaszunski, T. B. Demissie, and K. Ruud, Spin- rotation and NMR shielding constants in XF molecules (X= B, Al, Ga, In, and Tl), The Journal of Physical Chemistry A118, 9588 (2014)

    2014

  56. [64]

    T. Saue, R. Bast, A. S. P. Gomes, H. J. A. Jensen, L. Visscher, I. A. Aucar, R. Di Remigio, K. G. Dyall, E. Eliav, E. Fasshauer,et al., The DIRAC code for rela- tivistic molecular calculations, The Journal of Chemical Physics152(2020)

    2020

  57. [65]

    E. R. Davidson, The iterative calculation of a few of the lowest eigenvalues and corresponding eigenvectors of large real symmetric matrices, Journal of Computational Physics17, 87 (1975)

    1975

  58. [66]

    Crouzeix, B

    M. Crouzeix, B. Philippe, and M. Sadkane, The Davidson method, SIAM Journal on Scientific Computing15, 62 (1994)

    1994

  59. [67]

    Viola, E

    L. Viola, E. Knill, and S. Lloyd, Dynamical decoupling of open quantum systems, Physical Review Letters82, 2417 (1999)

    1999

  60. [68]

    C. H. Bennett, G. Brassard, S. Popescu, B. Schumacher, J. A. Smolin, and W. K. Wootters, Purification of noisy entanglement and faithful teleportation via noisy chan- nels, Physical Review Letters76, 722 (1996). 11 SUPPLEMENTAL MATERIAL Appendix A: Reference-State-Based Screen...

    1996

  61. [69]

    A non-zero contribution requires that the annihilation operatoraq acts on an occupied orbital

    One-body terms We first consider one-body operators of the formˆOpq =a † paq and analyze their action on the reference determinant |Φ0⟩. A non-zero contribution requires that the annihilation operatoraq acts on an occupied orbital. This condition is satisfied whenq=i. If, in a...

  62. [70]

    For such terms to yield non-zero contributions, both annihilation operatorsa r anda s must act on occupied orbitals

    Two-body terms We now consider two-body operators of the formˆOpqrs =a † pa† qasar. For such terms to yield non-zero contributions, both annihilation operatorsa r anda s must act on occupied orbitals. This condition is satisfied when(r, s) = (i, j) belongs to the occupied spac...

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