Pith. sign in

REVIEW 5 minor 57 references

Passive linear optics and multiple noisy copies let bosonic processors estimate observables as if the state had been purified.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

T0 review · grok-4.5

2026-07-11 11:31 UTC pith:BKTM2PW5

load-bearing objection Solid, hardware-ready extension of virtual distillation to bosonic observables via linear optics; eigenvector drift is the real limit and they own it.

arxiv 2607.04914 v1 pith:BKTM2PW5 submitted 2026-07-06 quant-ph

Error Mitigation in Bosonic Systems via Virtual Distillation

classification quant-ph
keywords virtual distillationbosonic quantum computingcontinuous-variable error mitigationlinear opticsphoton lossdephasingphoton-number characteristic functioncyclic-shift operators
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

Virtual distillation turns several imperfect copies of a quantum state into an estimate of an observable as though the state itself had been cleaned of noise. The idea first appeared for bosonic many-body systems under the name virtual cooling, yet most later work stayed with qubits. This paper brings the technique fully into continuous-variable and bosonic quantum computing. By routing the copies through ordinary passive interferometers that diagonalize the cyclic-shift operator, the authors obtain experimentally realistic measurement protocols for photon number, phase-shift operators, arbitrary field quadratures, and higher-order number correlators. They show that the same circuits suppress the two dominant bosonic errors—photon loss and dephasing—whenever the ideal state remains the dominant eigenvector of the noisy density matrix. The result is a practical, linear-optics-only route to higher-fidelity readout on near-term bosonic hardware without needing full error correction.

Core claim

The paper shows that diagonalizing the cyclic-shift operator with a Fourier interferometer (and, when needed, a second passive unitary) converts multi-copy measurements into noise-mitigated expectation values of the number operator, any phase-shift operator e^{i ϕ n̂}, and arbitrary quadratures; the same data also yield the characteristic function of the photon-number distribution and therefore all number correlators. The protocols work for photon loss and dephasing and require only linear-optical resources already available in bosonic platforms.

What carries the argument

The spectral decomposition of the cyclic-shift operator S^(M) = F† D_S F, realized by a passive Fourier interferometer followed by photon-number (or homodyne) detection; when the target observable is not diagonal after this transform, a second passive unitary diagonalizes the product of the observable with S^(M).

Load-bearing premise

The ideal pure target must stay the unique largest eigenvector of the noisy state; if loss or dephasing moves that eigenvector, the protocol purifies the wrong state and gives no improvement.

What would settle it

Prepare a Fock or even-cat state, apply a controlled loss channel whose Kraus operators leave the target as the dominant eigenvector, run the multi-copy Fourier protocol, and check whether the recovered number or parity expectation value converges exponentially to the ideal pure-state value as the number of copies increases.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • Bosonic processors can extract higher-fidelity Wigner functions and stellar-rank witnesses by virtual distillation of displaced parity measurements.
  • Logical Pauli-Z readout of cat qubits improves without extra physical redundancy, aiding variational algorithms.
  • Arbitrary photon-number correlators become accessible for near-term many-body simulations of long-range order and phase transitions.
  • The same linear-optics circuits remain effective under modest additional coherent and incoherent noise inside the distillation interferometers themselves.

Where Pith is reading between the lines

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

  • Extending the same diagonalization to higher moments of quadratures would give a direct error-mitigated probe of non-Gaussianity and non-classicality.
  • When eigenvector drift is inevitable, hybrid schemes that first apply a cheap symmetry expansion or post-selection step before virtual distillation may restore the dominant-eigenvector condition.
  • The characteristic-function route to correlators could be ported to atomic boson-sampling platforms to mitigate partial distinguishability without changing the lattice Hamiltonian.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

0 major / 5 minor

Summary. The manuscript develops a practical framework for virtual distillation (VD) in bosonic and continuous-variable systems. Starting from the standard multi-copy identities Tr[O ho^M] = Tr[O^(M) S^(M) ho^oxtimes M] and Tr[O ho^M] = Tr[O_k S^(M) ho^oxtimes M], the authors diagonalize the cyclic-shift operator S^(M) with a passive Fourier interferometer (Eqs. 15–17) and obtain two experimentally accessible protocols. Method 1 recovers noise-mitigated expectation values of the number operator and of arbitrary quadratures from a single Fourier interferometer plus local number/homodyne measurements (Eqs. 19, 21). Method 2 diagonalizes the composite operator e^{i heta n̂_1} S^(M) and thereby estimates phase-shift operators (including parity) and the full photon-number characteristic function, from which arbitrary-order number correlators follow (Eqs. 24–29, 34). Multimode extensions are given. Numerical simulations under photon loss and dephasing (Figs. 2–6) demonstrate exponential error suppression when the target pure state remains the dominant eigenvector of the noisy state and is an eigenstate of the measured observable; the same figures quantify the failure mode (eigenvector drift) when that spectral condition is violated. Appendices supply sample-complexity bounds, an explicit three-mode example, analytic forms of the diagonalizing unitaries, finite-difference error analysis for correlators, and a robustness check against coherent and incoherent circuit noise.

Significance. The work reclaims the original bosonic “virtual cooling” idea for modern continuous-variable quantum information processing and supplies concrete linear-optical circuits that use only passive interferometers already available in photonic and microwave platforms. The ability to extract purified number correlators and Wigner functions via the characteristic function is a genuine extension beyond the qubit literature and beyond the restricted observables of the 2019 virtual-cooling paper. The numerical evidence is carefully conditioned on the spectral assumption that the authors themselves state, and the appendices contain reproducible analytic and sampling analyses. If the protocols can be realized with a few copies on existing multi-mode platforms, they offer a near-term route to error-mitigated measurements of photon-number statistics and parity without full error correction.

minor comments (5)
  1. In Sec. II A the phrase “1/2 || ho - |ψ_{0} angle⟨ψ_{0}||_{1} = O(ϵ)” is used without an explicit definition of the O-notation for the trace distance; a one-line clarification would help readers who skip the later bound (Eq. 20).
  2. Fig. 1 caption mentions that a Fourier interferometer can be realized with O(M ln M) elements under arbitrary connectivity, citing Ref. [33]; a brief remark on whether current integrated-photonics platforms support that connectivity would strengthen the experimental claim.
  3. Appendix A, Eq. (A14): the optimal α is given, but the resulting n_tot is left in a somewhat cumbersome form; a short asymptotic statement “n_tot ∼ (1-ϵ)^{-2M}” would make the exponential cost immediately visible.
  4. In the multimode characteristic-function discussion (Sec. III C and Appendix E) the truncation N for the discrete Fourier inversion is left implicit; a pointer to the exponential-error bounds of Refs. [35,36] already cited elsewhere would be useful.
  5. Typographical: “VIR TUAL DISTILLA TION” appears with spaces in the section heading of Sec. III; likewise “SIMULA TIONS” and “APPLICA TIONS” in Sec. IV.

Circularity Check

0 steps flagged

No significant circularity; protocols follow by direct application of standard virtual-distillation identities and known Fourier diagonalization of cyclic shifts, with no fitted parameters or load-bearing self-citation loops.

full rationale

The derivation chain begins from the textbook virtual-distillation identities Tr[O ρ^M] = Tr[O^(M) S^(M) ρ^⊗M] and Tr[O ρ^M] = Tr[O_k S^(M) ρ^⊗M] (Eqs. 5–6), which are taken from the external literature [17,18] and are not redefined here. The cyclic-shift operator is diagonalized by the known M-mode Fourier interferometer (Eqs. 15–17, citing [21]), again an external construction. Method 1 then follows immediately by conjugating the symmetrized quadrature or number operator through that Fourier transform (Eq. 21); Method 2 follows by the elementary spectral decomposition of any passive linear unitary (Eq. 12) applied to e^{iϕ n̂_1} S^(M) (Eq. 24 and Appendix D). Multimode correlators are recovered from the characteristic function by the ordinary Fourier inversion or finite-difference formulae (Appendix E). All numerical examples are forward simulations of known loss/dephasing channels; no parameters are fitted to data and then re-presented as predictions. Self-citations (e.g., [41] for the multimode Fourier layer) supply only technical background and do not close any logical loop that forces the central claims. The sole acknowledged limitation—eigenvector drift when the target is not an eigenstate of the measured observable—is stated explicitly by the authors themselves and is not hidden by circular reasoning. Hence the paper is self-contained against external benchmarks and exhibits at most a negligible self-citation that is not load-bearing.

Axiom & Free-Parameter Ledger

0 free parameters · 3 axioms · 0 invented entities

The work rests on standard quantum-optics identities (bosonic commutation relations, Fourier diagonalization of cyclic shifts, Kraus representations of loss and dephasing) plus the spectral assumption that the target pure state remains the dominant eigenvector of the noisy density operator. No free parameters are fitted; no new physical entities are postulated.

axioms (3)
  • domain assumption The noisy state admits the spectral form ρ = (1-ε)|ψ₀⟩⟨ψ₀| + Σ ε_i |ψ_i⟩⟨ψ_i| with 1-ε > ε_i (Eq. 1).
    Load-bearing for the exponential error suppression claim; the paper itself shows that loss and dephasing frequently violate it (eigenvector drift).
  • standard math Cyclic-shift operators on M bosonic modes are unitarily diagonalized by the discrete Fourier interferometer (Eqs. 15–17).
    Standard linear-optics fact used throughout Secs. II–III; proved by direct matrix diagonalization.
  • domain assumption Photon loss and pure dephasing are accurately described by the given Kraus operators with rates κ, γ.
    Standard continuous-variable noise models (Sec. IV); used for all numerical validation.

pith-pipeline@v1.1.0-grok45 · 30009 in / 2391 out tokens · 21711 ms · 2026-07-11T11:31:29.960567+00:00 · methodology

0 comments
read the original abstract

Virtual distillation is a promising error-mitigation technique that exploits multiple copies of a noisy quantum state to estimate observables as if measured on a purified state. Although originally introduced in the context of bosonic many-body systems under the name of virtual cooling, its development and applications have largely focused on qubit-based quantum computation. Here, we establish a framework for virtual distillation in bosonic quantum information processing and continuous-variable quantum computing. Building on a diagonalization of cyclic shift operators implemented with passive linear-optical interferometers, we derive experimentally accessible protocols for estimating virtually distilled expectation values of observables relevant to bosonic architectures. In particular, we show how to recover noise-mitigated expectation values of number operators, phase-shift operators, and arbitrary quadratures from multi-copy measurements. For number operators, we further demonstrate the estimation of virtually distilled correlators of arbitrary order through the characteristic function of the photon-number distribution. We apply the framework to states affected by photon loss and dephasing, two of the dominant noise mechanisms in bosonic quantum computation, and quantify the resulting suppression of noise contributions. Our results extend virtual distillation beyond its original setting and provide a practical route toward error-mitigated measurements in bosonic quantum processors using experimentally available linear-optical resources.

Figures

Figures reproduced from arXiv: 2607.04914 by Adithi Udupa, Axel M. Eriksson, David Gunn, Diogo Gomes, Giulia Ferrini, Leonardo Finocchiaro, Leonardo Novo, Marco Robbio.

Figure 1
Figure 1. Figure 1: FIG. 1: Schematic of the two possible approaches to virtual distillation using the diagonalizing technique: (a) The [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2: Expectation value of the number operator as a function of the dimensionless loss rate, [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3: Reconstruction of the Wigner function [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4: Expectation value of the parity operator ( [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5: Modulus square of the characteristic function of the photon-number distribution of a two-mode [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6: The expected value of quadrature operators ˆq [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7: Circuit decomposition [26, 27] of the 3-mode Fourier transform F3 into three beam splitters and local phase shifts. Here P(ϕ) denotes a single-mode phase shifter applying a phase ϕ, i.e. e iϕnˆj , and BS(θ) denotes a beam splitter with transmissivity T = cos2 θ under the standard convention. Since we have a mixture of single photons and vacuum, we can explicitly write down the probabilities in term… view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8: Estimation of the particle number correlator [PITH_FULL_IMAGE:figures/full_fig_p017_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9: Expectation values of VD on input Fock states, with a noisy implementation of the protocol. We add both [PITH_FULL_IMAGE:figures/full_fig_p018_9.png] view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

57 extracted references · 14 linked inside Pith

  1. [1]

    Preskill, Quantum2, 79 (2018)

    J. Preskill, Quantum2, 79 (2018)

  2. [2]

    Katabarwa, K

    A. Katabarwa, K. Gratsea, A. Caesura, and P. D. John- son, PRX Quantum5, 020101 (2024)

  3. [3]

    Z. Cai, R. Babbush, S. C. Benjamin, S. Endo, W. J. Huggins, Y. Li, J. R. McClean, and T. E. O’Brien, Rev. Mod. Phys.95, 045005 (2023)

  4. [4]

    Zimbor´ as, B

    Z. Zimbor´ as, B. Koczor, Z. Holmes, E.-M. Borrelli, A. Gily´ en, H.-Y. Huang, Z. Cai, A. Ac´ ın, L. Aolita, L. Banchi, F. G. S. L. Brand˜ ao, D. Cavalcanti, T. Cubitt, S. N. Filippov, G. Garc´ ıa-P´ erez, J. Goold, O. K´ alm´ an, E. Kyoseva, M. A. C. Rossi, B. Sokolov, I. Tavernelli, and S. Maniscalco, Myths around quantum computation be- fore full fault...

  5. [5]

    Barenco, A

    A. Barenco, A. Berthiaume, D. Deutsch, A. Ekert, R. Jozsa, and C. Macchiavello, SIAM Journal on Com- puting26, 1541 (1997)

  6. [6]

    J. I. Cirac, A. Ekert, and C. Macchiavello, Physical re- view letters82, 4344 (1999)

  7. [7]

    A. M. Childs, H. Fu, D. Leung, Z. Li, M. Ozols, and V. Vyas, Quantum9, 1603 (2025)

  8. [8]

    B. Yang, E. Kashefi, D. Leichtle, and H. Ollivier, arXiv preprint arXiv:2404.09973 (2024)

  9. [9]

    Keyl and R

    M. Keyl and R. F. Werner, inAnnales Henri Poincare, Vol. 2 (Springer, 2001) pp. 1–26

  10. [10]

    Zhang, H

    K. Zhang, H. Li, J. Jing, N. Treps, and M. Walschaers, Purification of gaussian states by photon subtraction 12 (2024), arXiv:2409.03473 [quant-ph]

  11. [11]

    Niset, J

    J. Niset, J. Fiur´ aˇ sek, and N. J. Cerf, Physical review letters102, 120501 (2009)

  12. [12]

    Giedke and J

    G. Giedke and J. I. Cirac, Physical Review A66, 032316 (2002)

  13. [13]

    C. F. D. Faurby, L. Carosini, H. Cao, P. I. Sund, L. M. Hansen, F. Giorgino, A. B. Villadsen, S. N. van den Hoven, P. Lodahl, S. Paesani, J. C. Loredo, and P. Walther, Purifying photon indistinguishability through quantum interference (2024), arXiv:2403.12866 [quant-ph]

  14. [14]

    F. Hoch, A. Camillini, G. Rodari, E. Caruccio, G. Carva- cho, T. Giordani, R. Albiero, N. D. Giano, G. Corrielli, F. Ceccarelli, R. Osellame, M. Robbio, L. Novo, N. Spag- nolo, E. F. Galv˜ ao, and F. Sciarrino, Optimal distillation of photonic indistinguishability (2025), arXiv:2509.02296 [quant-ph]

  15. [15]

    Marshall, Physical Review Letters129, 213601 (2022), arXiv:2203.15197 [quant-ph]

    J. Marshall, Physical Review Letters129, 213601 (2022), arXiv:2203.15197 [quant-ph]

  16. [16]

    S. Endo, Y. Suzuki, K. Tsubouchi, R. Asaoka, K. Ya- mamoto, Y. Matsuzaki, and Y. Tokunaga, Phys. Rev. A 111, 062402 (2025)

  17. [17]

    Cotler, S

    J. Cotler, S. Choi, A. Lukin, H. Gharibyan, T. Grover, M. E. Tai, M. Rispoli, R. Schittko, P. M. Preiss, A. M. Kaufman, M. Greiner, H. Pichler, and P. Hayden, Phys- ical Review X9, 10.1103/physrevx.9.031013 (2019)

  18. [18]

    W. J. Huggins, S. McArdle, T. E. O’Brien, J. Lee, N. C. Rubin, S. Boixo, K. B. Whaley, R. Babbush, and J. R. McClean, Physical Review X11, 10.1103/phys- revx.11.041036 (2021)

  19. [19]

    Koczor, Physical Review X11, 031057 (2021)

    B. Koczor, Physical Review X11, 031057 (2021)

  20. [20]

    O’Brien, G

    T. O’Brien, G. Anselmetti, Gkritsis, F. V. E. Elfving, S. Polla, W. J. Huggins, O. Oumarou, K. Kechedzhi, D. Abanin, R. Acharya, and N. C. Rubin, Nat. Phys. 19, 1782 (2023)

  21. [21]

    A. J. Daley, H. Pichler, J. Schachenmayer, and P. Zoller, Phys. Rev. Lett.109, 020505 (2012)

  22. [22]

    Hertz, O

    A. Hertz, O. Oreshkov, and N. J. Cerf, Phys. Rev. A100, 052112 (2019)

  23. [23]

    Arnhem, C

    M. Arnhem, C. Griffet, and N. J. Cerf, Phys. Rev. A106, 043705 (2022)

  24. [24]

    Griffet, M

    C. Griffet, M. Arnhem, S. De Bi` evre, and N. J. Cerf, Phys. Rev. A108, 023730 (2023)

  25. [25]

    Griffet, T

    C. Griffet, T. Haas, and N. J. Cerf, Phys. Rev. A108, 022421 (2023)

  26. [26]

    ˙Zukowski, A

    M. ˙Zukowski, A. Zeilinger, and M. A. Horne, Phys. Rev. A55, 2564 (1997)

  27. [27]

    I. Jex, S. Stenholm, and A. Zeilinger, Optics Communi- cations117, 95 (1995)

  28. [28]

    Joshi, K

    A. Joshi, K. Noh, and Y. Y. Gao, Quantum Science and Technology6, 033001 (2021)

  29. [29]

    Rudin,Real and Complex Analysis, 3rd ed., McGraw- Hill International Editions Mathematics Series (McGraw- Hill, New York, NY, 2013)

    W. Rudin,Real and Complex Analysis, 3rd ed., McGraw- Hill International Editions Mathematics Series (McGraw- Hill, New York, NY, 2013)

  30. [30]

    Koczor, New Journal of Physics23, 123047 (2021)

    B. Koczor, New Journal of Physics23, 123047 (2021)

  31. [31]

    M. Reck, A. Zeilinger, H. J. Bernstein, and P. Bertani, Physical Review Letters73, 58 (1994)

  32. [32]

    W. R. Clements, P. C. Humphreys, B. J. Metcalf, W. S. Kolthammer, and I. A. Walmsley, An Optimal Design for Universal Multiport Interferometers (2017), arXiv:1603.08788 [physics]

  33. [33]

    Marcandelli, S

    P. Marcandelli, S. Mariani, M. Siena, and S. Markidis, Algorithms19, 370 (2026)

  34. [34]

    (17), we see that the operator ˆD ˆS(M) only involves theM−1 first modes, since the last one is associated with the observablee 2iπ M MˆnM = 1ˆnM which does not affect the result

    By Eq. (17), we see that the operator ˆD ˆS(M) only involves theM−1 first modes, since the last one is associated with the observablee 2iπ M MˆnM = 1ˆnM which does not affect the result

  35. [35]

    Upreti, N

    V. Upreti, N. Quesada, and U. Chabaud, Exponentially- improved effective descriptions of physical bosonic sys- tems (2026), arXiv:2604.18720 [quant-ph]

  36. [36]

    Bressanini, B

    G. Bressanini, B. Seron, L. Novo, N. J. Cerf, and M. S. Kim, Gaussian boson sampling validation via detector binning (2024), arXiv:2310.18113 [quant-ph]

  37. [37]

    Robbio, M

    M. Robbio, M. G. Jabbour, and N. J. Cerf, Complemen- tarity between bosonic and fermionic many-body inter- ferences with partially distinguishable particles (2026), arXiv:2604.23316 [quant-ph]

  38. [38]

    Van Herstraeten, M

    Z. Van Herstraeten, M. G. Jabbour, and N. J. Cerf, AVS Quantum Science5(2023)

  39. [39]

    M. C. Anguita, A. Camillini, S. Marzban, M. Robbio, B. Seron, L. Novo, and J. J. Renema, Experimental vali- dation of boson sampling using detector binning (2025), arXiv:2502.05093 [quant-ph]

  40. [40]

    M. E. O. Bezerra and V. Shchesnovich, arXiv preprint arXiv:2602.00071 (2026)

  41. [41]

    L. Novo, M. Robbio, E. F. Galv˜ ao, and N. J. Cerf, Na- tive linear-optical protocol for efficient multivariate trace estimation (2026), arXiv:2601.14204 [quant-ph]

  42. [42]

    Seron, L

    B. Seron, L. Novo, A. Arkhipov, and N. J. Cerf, Quantum 8, 1479 (2024)

  43. [43]

    A. W. Young, S. Geller, W. J. Eckner, N. Schine, S. Glancy, E. Knill, and A. M. Kaufman, Nature629, 311–316 (2024)

  44. [44]

    Vikst˚ al, G

    P. Vikst˚ al, G. Ferrini, and S. Puri, Quantum8, 1441 (2024)

  45. [45]

    Becker, N

    S. Becker, N. Datta, L. Lami, and C. Rouz´ e, Communi- cations in Mathematical Physics383, 223 (2021)

  46. [46]

    O. Hahn, V. Preti, A. Maltesson, M. Ellerbroek, S.-R. Keshari, G. Ferrini, A. Ferraro, and U. Chabaud, Wit- nessing and quantifying stellar rank with the wigner func- tion (2026), in preparation

  47. [47]

    A. L. Grimsmo, J. Combes, and B. Q. Baragiola, Phys. Rev. X10, 011058 (2020)

  48. [48]

    S. Puri, S. Boutin, and A. Blais, npj Quantum Informa- tion3, 18 (2017)

  49. [49]

    Vikst˚ al, L

    P. Vikst˚ al, L. Garc´ ıa-´Alvarez, S. Puri, and G. Ferrini, Quantum approximate optimization algorithm with cat qubits (2024), arXiv:2305.05556 [quant-ph]

  50. [50]

    Barbieri, PRX Quantum3, 010202 (2022)

    M. Barbieri, PRX Quantum3, 010202 (2022)

  51. [51]

    V. Kala, C. A. Breum, M. V. Larsen, U. L. Andersen, J. S. Neergaard-Nielsen, R. Filip, and P. Marek, Nul- lifiers of non-gaussian cluster states through homodyne measurement (2025), arXiv:2505.21066 [quant-ph]

  52. [52]

    A. I. Lvovsky and J. H. Shapiro, Phys. Rev. A65, 033830 (2002)

  53. [53]

    V. S. Alfaro, arXiv preprint arXiv:2606.15464 (2026)

  54. [54]

    M. C. Tichy, Journal of Physics B: Atomic, Molecular and Optical Physics47, 103001 (2014)

  55. [55]

    Aaronson and A

    S. Aaronson and A. Arkhipov, The computational com- plexity of linear optics (2010), arXiv:1011.3245 [quant- ph]

  56. [56]

    Geller and E

    S. Geller and E. Knill, Measuring multiparticle indis- tinguishability with the generalized bunching probability (2025), arXiv:2509.04550 [quant-ph]. 13 Appendix A: Sample complexity In the above discussion, we did not consider the sam- ple complexity of estimating Tr h ˆO˜ρ i , which of course will depend on the number of copies involved. Let us separate...

  57. [57]

    1 0   .(D1) First we compute the characteristic polynomial, which reduces to p(λ) =λ M −e iϕ =⇒λ k =e i (2πk+ϕ) M (D2) meaningD ϕ = diag(λ 1, . . . , λM). The corresponding eigenvector ofλ k can be found in the form vk = 1√ M   1 λ−1 k λ−2 k ... λ−M k   (D3) and as a consequence the matrixV ϕ can be written as (Vϕ)jk = 1√ M e− i(j−1) M (2...