REVIEW 4 major objections 3 minor 55 references
Coordinate space representation for quantum simulation of scalar field theory
T0 review · 4 major / 3 minor · reviewed 2026-08-04 · deepseek-v4-flash
Pith's one-line read A coordinate-space harmonic-oscillator representation makes the lattice phi^4 Hamiltonian effectively band-diagonal, so quantum simulation costs scale linearly instead of quartically with lattice size.
desk verdict Band-diagonal structure is plausible, but the basis normalization error undermines the numerical claims. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The key object is the coordinate-space harmonic-oscillator basis, defined by site-local bosonic operators b^†_j obtained by Fourier transforming the momentum-space ladder operators. Its usefulness comes from the effective locality of the resulting Hamiltonian: the hopping matrix h_jk and the four-index interaction tensor U_ijkl have matrix elements that decay exponentially with spatial separation, with the correlation length ~1/m_gap controlling the decay. This turns an a priori fully connected problem into a banded one, with bandwidth cutoffs C_h and C_U that can be chosen independent of N_s, and it makes the free-theory vacuum a simple Fock product state. On top of this, the paper uses una
What would settle it
Take the site operators (25) and diagonalize the HO x Hamiltonian with and without rescaling b_j → sqrt(N_s) b_j; if the ground-state energy and mass gap in the rescaled calculation no longer match the HO p results shown in the paper, then the reported HO x spectra were obtained with a non-unitary representation and the truncation comparison is invalid.
Extended reading notes
Core claim
The central claim is that the HO x representation of the phi^4 Hamiltonian has an effective band-diagonal structure in the presence of a mass gap. The one-body matrix h_jk and the interaction tensor U_ijkl, while not strictly local, decay exponentially with the distance between sites, with the decay length set by the correlation length ~1/m_gap. This allows controlled truncations with bandwidths C_h and C_U that stay bounded as the lattice grows. The paper validates the truncation by showing that low-energy observables—ground-state energy, mass gap, and the extracted critical coupling—match those obtained from the momentum-space harmonic-oscillator representation and from a sharp-energy Hami
Load-bearing premise
The numerical validation assumes the site-basis operators are canonical bosonic operators with an orthonormal occupation basis, but as written their commutator is [b_j,b^†_k]=δ_{jk}/N_s; if that normalization is not absorbed into the matrix elements, the coordinate-space Hamiltonian being diagonalized is not the same Hamiltonian as the momentum-space one.
Editorial extensions
If this is right
- For a gapped phi^4 theory on a lattice, the coordinate-space harmonic-oscillator Hamiltonian can be truncated to fixed bandwidths so that the number of Pauli strings grows linearly with N_s after either binary or unary encoding.
- Low-energy observables—ground-state energy, mass gap, and critical coupling—are preserved under these truncations; retaining nearest-neighbor hopping with C_h=1 and interaction bandwidth C_U=2 was sufficient in the tested cases.
- For moderate-to-strong coupling, the coordinate-space Hamiltonian has a smaller Pauli 1-norm than the momentum-space one, which would reduce the query complexity of block-encoding and qubitization-based simulation algorithms.
- The advantage is representation-based rather than encoding-based: both unary and binary encodings benefit equally, so basis choice and boson-to-qubit mapping are independent optimization levers.
- In the weak-coupling regime the momentum-space representation remains cheaper, since its free Hamiltonian is diagonal; the crossover is a resource trade-off, not a universal gain.
Reading between the lines
- A reader should verify that the operators used in the numerics are rescaled: as written, [b_j,b^†_k]=δ_{jk}/N_s, not δ_{jk}; if the missing normalization is not absorbed into H_x, the diagonalized spectra would not correspond to the same Hamiltonian as H_p, and the truncation comparison would need to be redone.
- The bandedness argument applies to any gapped bosonic lattice theory, so the same coordinate-space harmonic-oscillator construction may reduce simulation costs for other scalar models or lattice field theories with massive excitations.
- Near criticality the correlation length diverges, so the bandwidths C_h and C_U grow as the mass gap closes; the practical regime of the linear-scaling advantage is bounded by how close the coupling is to λ_c, and a quantitative crossover curve could be derived.
- The paper's suggestion of wavelet bases points to a possible further improvement: a multiscale localized basis could make the Hamiltonian even sparser than the single-scale HO x basis at the same truncation accuracy.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper proposes a coordinate-space harmonic-oscillator basis (HO_x) for the lattice phi^4 model. It derives the one-body coupling h_jk and the interaction tensor U_ijkl in this basis, gives numerical evidence that both are effectively band-diagonal for gapped parameters, and argues that bandwidth truncations preserve the low-energy spectrum. It then estimates the qubit count, Pauli-string count, and Pauli 1-norm for binary and unary boson-to-qubit encodings, comparing the HO_x and HO_p representations. The main claimed result is that the coordinate-space representation reduces the Pauli-string scaling from quartic (as stated in the abstract and Table 1) to linear in the number of lattice sites, with a lower Pauli 1-norm at moderate-to-strong coupling. The numerical validation compares low-energy spectra with the momentum-space HO basis and with the Hamiltonian-truncation benchmark of Rychkov–Vitale [11].
Significance. The underlying idea is potentially useful: basis choice is a largely independent lever for reducing the cost of quantum simulation of field theories, and the paper contains a concrete derivation plus numerical evidence. The benchmark against an independent Hamiltonian-truncation result is a strength, and the bandedness plots for h_jk and U_ijkl are suggestive. However, the current numerical validation is not reliable because the basis defined in Sec. 3 is not orthonormal as claimed, and the exact diagonalization does not state how the nontrivial metric is handled. The resource estimates also contain internal inconsistencies in the scaling with N_s and in the unary/binary decompositions. The central bandedness idea is plausible and probably repairable, but the quantitative claims in Secs. 5–6 need to be redone before the paper can be accepted.
major comments (4)
- [Section 3, Eqs. (27)–(29); Section 6.1, Eq. (40)] The basis defined by Eqs. (25) and (29) is not orthonormal. Eq. (27) gives [b_j,b_k^†]=N_s^{-1}δ_jk, so even the one-particle states have overlap <0|b_j b_k^†|0>=N_s^{-1}δ_jk, contradicting Eq. (28). The canonical modes are c_j=√N_s b_j; in that basis the free Hamiltonian carries a factor N_s^{-1} in front of Σ h_jk c_j^† c_k and the quartic term a factor N_s^{-2}, whereas Secs. 5–6 treat b_j as a canonical ladder operator. In particular, Eq. (40) assumes the standard action a_n|r_n>=√r_n|r_n−1> for the site labels, which is false for b_j. The spectra in Figs. 7–8 and the Pauli 1-norm comparison in Fig. 9 are therefore those of an unstated Hamiltonian that is not unitarily equivalent to H_p. The authors must either solve the generalized eigenvalue problem with the correct overlap metric or reformulate everything in the canonical c_j basis and repeat the numerical analysis.
- [Section 4, Eqs. (36)–(37); Section 6.2, Eqs. (61)–(63)] The counting of retained interaction tensor entries is inconsistent with the cutoff definition. If the cutoff is d(i,j,k,l)≤C_U as in Eq. (37), the number of retained quartets in one dimension is O(N_s C_U^3), not O(C_U N_s) as written in Eq. (61). The Pauli-string estimates in Eqs. (62)–(63) and Tables 1–2 therefore understate the prefactor by C_U^2. The linear-in-N_s conclusion may survive after correction, but the quantitative resource claims and Fig. 9 need to be recomputed with the correct C_U dependence.
- [Section 6.2, Eqs. (66)–(67) and Fig. 9] The comparison of encodings appears internally inconsistent. Eq. (66), a_n=σ^+_{2n}σ^−_{2n+1}, is the unary representation for N_φ=2 (occupations 0 and 1), not for a local Hilbert space of dimension four; unary encoding with N_φ=4 requires four qubits per site. Furthermore, Eq. (67) does not match the binary decomposition of Eq. (45) for N_φ=4: expanding Eq. (45) gives ((1+√3)/2)I⊗σ^+ + ((1−√3)/2)Z⊗σ^+ + √2 σ^+⊗σ^−, not the expression shown, and no derivation is supplied. Since Fig. 9 is the main quantitative evidence for the Pauli-norm advantage of HO_x, this comparison must be redone from explicit, correct decompositions.
- [Section 6.2, Eq. (55); Section 4, final paragraph; Tables 1–2; Abstract] The momentum-space Pauli-string count is stated inconsistently. Eq. (55) gives (2N_max+1)N_φ^4 + (2N_max+1)^3 N_φ^8, i.e. O(N_s^3) for the interaction, consistent with the momentum-conservation constraint noted in Section 4. The abstract and Tables 1–2 instead quote (2N_max+1)^4, i.e. 'quartic to linear'. The claimed asymptotic improvement is therefore cubic-to-linear if Eq. (55) is correct, or Eq. (55) is wrong. The exponent must be fixed and all statements relying on 'quartic to linear' updated.
minor comments (3)
- [Section 5, after Eq. (38)] The definitions of H_x and H_p appear swapped: the text says H_x is the momentum-space Hamiltonian truncated via (N_max,N_φ) and H_p is the coordinate-space Hamiltonian, but the rest of the section and Fig. 6 use H_p for the momentum-space Hamiltonian. Please harmonize the notation.
- [Figures 1 and 3] The y-axis label 'Number of entries > max(h)' does not show the threshold τ that appears in the legend; it should read '> τ max(h)' or similar. In Fig. 3 the caption refers to C_{ijk} while the text defines U_{ijkl}.
- [Throughout] Typos and minor presentation issues: 'choise', 'obatained', 'communly'; Eq. (9) labels b=1,…,N_φ but likely should start at 0 or include an offset; the x-axis tick labels in Fig. 4 are garbled. These should be cleaned up.
Circularity Check
No significant circularity: H_x is an explicit Fourier transform of H_p, and the bandwidth/spectrum claims are validated against independent benchmarks and numerical truncation tests.
full rationale
The derivation chain is self-contained and benchmarked externally. H_x is constructed in Sec. 3 by the explicit lattice Fourier transform (25)-(34) of the momentum-space HO Hamiltonian, with no parameter fitted to low-energy observables; the one-body matrix h_jk and the interaction tensor U_ijkl are computed from the dispersion relation and momentum conservation, not tuned to reproduce E0 or m_ph. The band-diagonal structure is supported by direct numerical counting of matrix elements above thresholds (Figs. 1-4), and the truncation is validated by comparing truncated versus full spectra (Figs. 7b and 8) and by comparing both representations against the independent Hamiltonian-truncation results of Rychkov-Vitale [11]. No load-bearing self-citation occurs: [11], [28], [29], and [36] are all external works. The bandwidth cutoffs C_h and C_U are numerical truncation parameters, not data-fit predictions of the target observables. A separate normalization inconsistency in Eqs. (27)-(29) (the operators satisfy [b_j,b_k^†] = 1/Ns delta_jk rather than delta_jk, so the asserted orthonormal occupation basis is not literally orthonormal) is a correctness issue, not a circularity: it does not make any claimed prediction equivalent to an input by construction. Therefore the circularity score is 0.
Assumptions & free parameters
free parameters (3)
- C_h (effective hopping bandwidth)
- C_U (effective interaction bandwidth)
- Threshold τ for 'non-zero' entries =
10^-1 to 10^-7
assumptions (7)
- standard math Canonical quantization of the lattice scalar field (commutation relations eq. 7)
- standard math Harmonic-oscillator/Fock representation with bosonic ladder operators
- domain assumption Restriction to the zero-momentum sector (Sec. 2.2, following [11])
- domain assumption Finite-volume and normal-ordering counterterm corrections are exponentially suppressed for mL>>1 (Sec. 2.2)
- domain assumption Matrix elements h_jk and U_ijkl decay exponentially with distance, with correlation length ξ~1/m_gap (Sec. 3)
- domain assumption Local occupation truncation Nφ preserves the low-energy spectrum
- standard math Binary and unary boson-to-qubit encodings correctly represent the truncated ladder operators
Cite this review
Pith. "Pith review of Coordinate space representation for quantum simulation of scalar field theory." pith.science (2026). https://pith.science/paper/RFH2ONLL
@misc{pith2026260800670,
author = {Pith},
title = {Pith review of: Coordinate space representation for quantum simulation of scalar field theory},
year = {2026},
howpublished = {\url{https://pith.science/paper/RFH2ONLL}},
note = {Machine review of arXiv:2608.00670}
}
abstract
Quantum computing provides a promising framework for the simulation of quantum field theories, where the computational cost depends both on the quantum algorithm employed and on the representation of the Hamiltonian. We investigate a formulation of the $\phi^4$ model based on the harmonic-oscillator basis in coordinate space. We derive the lattice $\phi^4$ Hamiltonian in this representation and analyze the structure of the resulting one-body matrix and interaction tensor. We show that both exhibit an effective band-diagonal structure, allowing controlled truncations of the Hamiltonian while preserving the low-energy spectrum. We validate this formulation by comparing low-energy observables obtained from numerical diagonalization with those computed in the standard harmonic-oscillator momentum-space representation. Finally, we estimate the resources required to encode the Hamiltonian on a quantum computer using both binary and unary boson-to-qubit mappings. By exploiting effective locality, the coordinate-space representation reduces the resources required for quantum simulation over a broad range of parameters.
Reference graph
Works this paper leans on
-
[11]
Slava Rychkov and Lorenzo G. Vitale. Hamiltonian truncation study of theϕ 4 theory in two dimensions.Physical Review D, 91(8), April 2015
2015
-
[1]
World Scien- tific, Singapore, 2001
Hagen Kleinert and Verena Schulte-Frohlinde.Critical Properties ofϕ 4-Theories. World Scien- tific, Singapore, 2001
2001
-
[2]
S. Durr, Z. Fodor, J. Frison, C. Hoelbling, R. Hoffmann, S. D. Katz, S. Krieg, T. Kurth, L. Lellouch, T. Lippert, K. K. Szabo, and G. Vulvert. Ab initio determination of light hadron masses.Science, 322(5905):1224–1227, November 2008. 21
2008
-
[3]
McNeile, C
C. McNeile, C. T. H. Davies, E. Follana, K. Hornbostel, and G. P. Lepage. High-precisioncand bmasses, and QCD coupling from current-current correlators in lattice and continuum QCD. Phys. Rev. D, 82:034512, Aug 2010
2010
-
[4]
Borsanyi, Z
Sz. Borsanyi, Z. Fodor, J. N. Guenther, C. Hoelbling, S. D. Katz, L. Lellouch, T. Lippert, K. Miura, L. Parato, K. K. Szabo, F. Stokes, B. C. Toth, Cs. Torok, and L. Varnhorst. Leading hadronic contribution to the muon magnetic moment from lattice QCD.Nature, 593(7857):51–55, April 2021
2021
-
[5]
Hasenbusch
M. Hasenbusch. A Monte Carlo study of leading order scaling corrections ofϕ 4 theory on a three-dimensional lattice.J. Phys. A, 32:4851–4865, 1999
1999
-
[6]
Ashley Milsted, Jutho Haegeman, and Tobias J. Osborne. Matrix product states and variational methods applied to critical quantum field theory.Physical Review D, 88(8), October 2013
2013
-
[7]
Real-time scattering inϕ 4 theory using matrix product states.Physical Review Research, 8(2), May 2026
Bahaa Al Sayegh and Wissam Chemissany. Real-time scattering inϕ 4 theory using matrix product states.Physical Review Research, 8(2), May 2026
2026
Show all 55 references
-
[8]
Steven R. White. Density matrix formulation for quantum renormalization groups.Phys. Rev. Lett., 69:2863–2866, Nov 1992
1992
-
[9]
Density matrix renormalization group in a two-dimensional hamiltonian lattice model.Journal of High Energy Physics, 2004(05):007–007, May 2004
Takanori Sugihara. Density matrix renormalization group in a two-dimensional hamiltonian lattice model.Journal of High Energy Physics, 2004(05):007–007, May 2004
2004
-
[10]
The diagonalization of quantum field hamiltonians
Dean Lee, Nathan Salwen, and Daniel Lee. The diagonalization of quantum field hamiltonians. Physics Letters B, 503(1–2):223–235, March 2001
2001
-
[12]
Truncated hilbert space approach to the 2dϕ 4 theory.Journal of High Energy Physics, 2016(10), October 2016
Zoltan Bajnok and Marton Lajer. Truncated hilbert space approach to the 2dϕ 4 theory.Journal of High Energy Physics, 2016(10), October 2016
2016
-
[13]
Joan Elias-Mir´ o, Slava Rychkov, and Lorenzo G. Vitale. NLO renormalization in the hamiltonian truncation.Physical Review D, 96(6), 2017
2017
-
[14]
Exploring hamiltonian truncation in 1+1d.Physical Review D, 102(6), September 2020
Joan Elias-Mir´ o and Edward Hardy. Exploring hamiltonian truncation in 1+1d.Physical Review D, 102(6), September 2020
2020
-
[15]
Liam Fitzpatrick and Emanuel Katz
A. Liam Fitzpatrick and Emanuel Katz. Snowmass white paper: Hamiltonian truncation, 2022
2022
-
[16]
The density-matrix renormalization group in the age of matrix product states.Annals of Physics, 326(1):96–192, January 2011
Ulrich Schollw¨ ock. The density-matrix renormalization group in the age of matrix product states.Annals of Physics, 326(1):96–192, January 2011
2011
-
[17]
Richard P. Feynman. Simulating physics with computers.Int. J. Theor. Phys., 21:467–488, 1982
1982
-
[18]
Efficient simulation of quantum systems by quantum computers.Proc
Christof Zalka. Efficient simulation of quantum systems by quantum computers.Proc. Roy. Soc. Lond. A, 454:313–322, 1998
1998
-
[19]
Quantum computing in the NISQ era and beyond.Quantum, 2:79, August 2018
John Preskill. Quantum computing in the NISQ era and beyond.Quantum, 2:79, August 2018
2018
-
[20]
Quantum information processing with atoms and photons.Nature, 416:238–46, 04 2002
Christie Monroe. Quantum information processing with atoms and photons.Nature, 416:238–46, 04 2002
2002
-
[21]
Monroe, and D.J
David Kielpinski, C.R. Monroe, and D.J. Wineland. Architecture for a large-scale ion-trap quantum computer.Nature, 417:709–11, 07 2002. 22
2002
-
[22]
Alexandre Blais, Ren-Shou Huang, Andreas Wallraff, S. M. Girvin, and R. J. Schoelkopf. Cavity quantum electrodynamics for superconducting electrical circuits: An architecture for quantum computation.Phys. Rev. A, 69:062320, Jun 2004
2004
-
[23]
Bauer, Zohreh Davoudi, A
Christian W. Bauer, Zohreh Davoudi, A. Baha Balantekin, Tanmoy Bhattacharya, Marcela Carena, Wibe A. de Jong, Patrick Draper, Aida El-Khadra, Nate Gemelke, Masanori Hanada, Dmitri Kharzeev, Henry Lamm, Ying-Ying Li, Junyu Liu, Mikhail Lukin, Yannick Meurice, Christopher Monroe...
2023
-
[24]
Quantum Computing for High-Energy Physics: State of the Art and Challenges.PRX Quantum, 5(3):037001, 2024
Alberto Di Meglio et al. Quantum Computing for High-Energy Physics: State of the Art and Challenges.PRX Quantum, 5(3):037001, 2024
2024
-
[25]
Natalie Klco, Alessandro Roggero, and Martin J. Savage. Standard model physics and the digital quantum revolution: thoughts about the interface.Rept. Prog. Phys., 85(6):064301, 2022
2022
-
[26]
Bauer, Zohreh Davoudi, Natalie Klco, and Martin J
Christian W. Bauer, Zohreh Davoudi, Natalie Klco, and Martin J. Savage. Quantum simulation of fundamental particles and forces.Nature Rev. Phys., 5(7):420–432, 2023
2023
-
[27]
Bauer et al
Christian W. Bauer et al. Quantum Simulation for High-Energy Physics.PRX Quantum, 4(2):027001, 2023
2023
-
[28]
Jordan, Keith S
Stephen P. Jordan, Keith S. M. Lee, and John Preskill. Quantum algorithms for quantum field theories.Science, 336(6085):1130–1133, 2012
2012
-
[29]
Jordan, Keith S
Stephen P. Jordan, Keith S. M. Lee, and John Preskill. Quantum computation of scattering in scalar quantum field theories, 2019
2019
-
[30]
Natalie Klco and Martin J. Savage. Digitization of scalar fields for quantum computing.Phys. Rev. A, 99:052335, May 2019
2019
-
[31]
Single-particle digitiza- tion strategy for quantum computation of aϕ 4 scalar field theory.Phys
Jo˜ ao Barata, Niklas Mueller, Andrey Tarasov, and Raju Venugopalan. Single-particle digitiza- tion strategy for quantum computation of aϕ 4 scalar field theory.Phys. Rev. A, 103:042410, Apr 2021
2021
-
[32]
Alexandru Macridin, Andy C. Y. Li, Stephen Mrenna, and Panagiotis Spentzouris. Bosonic field digitization for quantum computers.Physical Review A, 105(5), May 2022
2022
-
[33]
Discretizing quantum field theories for quantum simulation, 2020
Terry Farrelly and Julien Streich. Discretizing quantum field theories for quantum simulation, 2020
2020
-
[34]
Towards a variational Jor- dan–Lee–Preskill quantum algorithm.Machine Learning: Science and Technology, 3(4):045030, December 2022
Junyu Liu, Zimu Li, Han Zheng, Xiao Yuan, and Jinzhao Sun. Towards a variational Jor- dan–Lee–Preskill quantum algorithm.Machine Learning: Science and Technology, 3(4):045030, December 2022
2022
-
[35]
Andy C. Y. Li, Alexandru Macridin, Stephen Mrenna, and Panagiotis Spentzouris. Simulating scalar field theories on quantum computers with limited resources.Physical Review A, 107(3), March 2023
2023
-
[36]
Sohaib Alam, Robert Konik, Layla Hormozi, Eleanor Rieffel, Stuart Hadfield, Jo˜ ao Barata, Raju Venugopalan, Dmitri E
Andrew Hardy, Priyanka Mukhopadhyay, M. Sohaib Alam, Robert Konik, Layla Hormozi, Eleanor Rieffel, Stuart Hadfield, Jo˜ ao Barata, Raju Venugopalan, Dmitri E. Kharzeev, and Nathan Wiebe. Scattering processes from quantum simulation algorithms for scalar field theo- ries.PRX Qu...
2026
-
[37]
Quantum simulation of quantum field theories as quantum chemistry
Junyu Liu and Yuan Xin. Quantum simulation of quantum field theories as quantum chemistry. Journal of High Energy Physics, 2020(12), December 2020
2020
-
[38]
Enhancing quan- tum field theory simulations on NISQ devices with hamiltonian truncation, 2024
James Ingoldby, Michael Spannowsky, Timur Sypchenko, and Simon Williams. Enhancing quan- tum field theory simulations on NISQ devices with hamiltonian truncation, 2024
2024
-
[39]
Real-time scattering on quantum computers via hamiltonian truncation, 2025
James Ingoldby, Michael Spannowsky, Timur Sypchenko, Simon Williams, and Matthew Wingate. Real-time scattering on quantum computers via hamiltonian truncation, 2025
2025
-
[40]
Farrell, Nikita A
Roland C. Farrell, Nikita A. Zemlevskiy, Marc Illa, and John Preskill. Digital quantum simula- tions of scattering in quantum field theories using W states, 2025
2025
-
[41]
Zemlevskiy
Nikita A. Zemlevskiy. Scalable quantum simulations of scattering in scalar field theory on 120 qubits.Physical Review D, 112(3), August 2025
2025
-
[42]
Dumitrescu, Alex J
K¨ ubra Yeter-Aydeniz, Eugene F. Dumitrescu, Alex J. McCaskey, Ryan S. Bennink, Raphael C. Pooser, and George Siopsis. Scalar quantum field theories as a benchmark for near-term quantum computers.Physical Review A, 99(3), March 2019
2019
-
[43]
Jordan, Hari Krovi, Keith S
Stephen P. Jordan, Hari Krovi, Keith S. M. Lee, and John Preskill. BQP-completeness of scattering in scalar quantum field theory.Quantum, 2:44, 2018
2018
-
[44]
Low-depth quantum simulation of materials.Phys
Ryan Babbush, Nathan Wiebe, Jarrod McClean, James McClain, Hartmut Neven, and Garnet Kin-Lic Chan. Low-depth quantum simulation of materials.Phys. Rev. X, 8:011044, Mar 2018
2018
-
[45]
Ollitrault, Jerome F
Pauline J. Ollitrault, Jerome F. Gonthier, Dario Rocca, Gian-Luca Anselmetti, Matthias Deg- roote, Nikolaj Moll, Raffaele Santagati, and Michael Streif. Improving the runtime of quantum phase estimation for chemistry through basis set optimization, 2025
2025
-
[46]
O’Brien, and Lucas Visscher
Emiel Koridon, Saad Yalouz, Bruno Senjean, Francesco Buda, Thomas E. O’Brien, and Lucas Visscher. Orbital transformations to reduce the 1-norm of the electronic structure hamiltonian for quantum computing applications.Phys. Rev. Res., 3:033127, Aug 2021
2021
-
[47]
Alexei Kitaev and William A. Webb. Wavefunction preparation and resampling using a quantum computer. 1 2008
2008
-
[48]
Somma.Quantum Computation, Complexity, and Many-Body Physics
Rolando D. Somma.Quantum Computation, Complexity, and Many-Body Physics. PhD thesis, Balseiro Inst., San Carlos de Bariloche, 2005
2005
-
[49]
Quantum chem- istry beyond Born–Oppenheimer approximation on a quantum computer: A simulated phase estimation study.Int
Libor Veis, Jakub Viˇ sˇ n´ ak, Hiroaki Nishizawa, Hiromi Nakai, and Jiˇ r ´ ı Pittner. Quantum chem- istry beyond Born–Oppenheimer approximation on a quantum computer: A simulated phase estimation study.Int. J. Quant. Chem., 116(18):1328–1336, 2016
2016
-
[50]
Digital quan- tum simulation of molecular vibrations.Chem
Sam McArdle, Alexander Mayorov, Xiao Shan, Simon Benjamin, and Xiao Yuan. Digital quan- tum simulation of molecular vibrations.Chem. Sci., 10(22):5725–5735, 2019
2019
-
[51]
Evangelista
Francesco A. Evangelista. A Multireference Quantum Krylov Algorithm for Strongly Correlated Electrons.J. Chem. Theor. Comput., 16(4):2236–2245, 2020
2020
-
[52]
Generalized quantum subspace expansion.Phys
Nobuyuki Yoshioka, Hideaki Hakoshima, Yuichiro Matsuzaki, Yuuki Tokunaga, Yasunari Suzuki, and Suguru Endo. Generalized quantum subspace expansion.Phys. Rev. Lett., 129:020502, Jul 2022
2022
-
[53]
Cortes and Stephen K
Cristian L. Cortes and Stephen K. Gray. Quantum krylov subspace algorithms for ground- and excited-state energy estimation.Phys. Rev. A, 105:022417, Feb 2022. 24
2022
-
[54]
Exact and efficient Lanczos method on a quantum computer.Quantum, 7:1018, 2023
William Kirby, Mario Motta, and Antonio Mezzacapo. Exact and efficient Lanczos method on a quantum computer.Quantum, 7:1018, 2023
2023
-
[55]
Anderson, Martin Kiffner, Tom O’Leary, Jason Crain, and Dieter Jaksch
Lewis W. Anderson, Martin Kiffner, Tom O’Leary, Jason Crain, and Dieter Jaksch. Solving lattice gauge theories using the quantum Krylov algorithm and qubitization.Quantum, 9:1669, 2025. 25
2025
Reviewed August 4, 2026 · model on record in the stance chip above.
Discussion (0). Continue with ORCID to comment.