pith. sign in

arxiv: 2412.17209 · v2 · submitted 2024-12-23 · 🪐 quant-ph

Classical simulability of Clifford+T circuits with Clifford-augmented matrix product states

Pith reviewed 2026-05-23 07:20 UTC · model grok-4.3

classification 🪐 quant-ph
keywords classical simulation of quantum circuitsClifford+T circuitsmatrix product statesdisentangling algorithmslinear algebra over GF(2)bond dimensionquantum entanglement and magic
0
0 comments X

The pith

An algebraic criterion based on the null space of a GF(2) matrix determines when Clifford circuits doped with gates of the form alpha I + beta P admit efficient classical simulation via Clifford-augmented matrix product states.

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

The paper introduces an optimization-free disentangling algorithm for Clifford circuits that include multi-qubit gates of the specific form alpha I + beta P. It derives a simple algebraic criterion showing that the bond dimension of the resulting Clifford-augmented matrix product state is exponential in the null-space dimension of a GF(2) matrix built from the tableau of twisted Pauli strings. This criterion allows rigorous polynomial-time simulation for all circuits where that null space is small, expanding the known simulable set. The work also presents evidence that typical random instances with N such T-gates at sufficient depth satisfy the condition for polynomial scaling.

Core claim

For Clifford circuits with added gates of the form alpha I + beta P, the optimization-free disentangling algorithm produces a Clifford-augmented matrix product state whose bond dimension is set by the size of the null space of a GF(2) matrix from the tableau of the twisted Pauli strings P. Circuits for which this null space is small therefore permit classical computation of Pauli expectations in time polynomial in the system size.

What carries the argument

The GF(2) null-space dimension of the matrix induced by the tableau of twisted Pauli strings, which controls the bond dimension in the Clifford-augmented matrix product state representation after optimization-free disentangling.

If this is right

  • A larger class of Clifford+T circuits now has a rigorous guarantee of polynomial-time classical simulation.
  • Random Clifford circuits with N T gates of poly-log depth typically have polynomial bond dimension under this representation.
  • CAMPS enables more efficient algorithms than standard MPS for sampling, probability estimation, and Renyi entropy, even if still exponential overall.
  • The interplay between entanglement and magic can be analyzed through this algebraic lens for simulatability.

Where Pith is reading between the lines

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

  • One could design quantum circuits that deliberately violate the criterion to ensure they are hard to simulate classically.
  • The method might inspire similar algebraic criteria for other non-Clifford gate families beyond the alpha I + beta P form.
  • Small-scale numerical experiments could directly compute the matrix nullity and compare it to observed bond dimensions to test the prediction.

Load-bearing premise

The non-Clifford gates must all be exactly of the form alpha I + beta P where P is a Pauli string.

What would settle it

Observe a specific circuit containing only such gates for which the CAMPS bond dimension after applying the OFD algorithm is larger than predicted by the null space dimension of its GF(2) tableau matrix.

Figures

Figures reproduced from arXiv: 2412.17209 by Bryan K. Clark, Zejun Liu.

Figure 1
Figure 1. Figure 1: FIG. 1: (a) [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2: Schematic diagram for OFD algorithm (on [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3: Average number of entangling gates versus [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4: Results of applying different types of disentangling algorithms (square, upward and downward triangular [PITH_FULL_IMAGE:figures/full_fig_p010_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5: Illustration of OBD procedure removing [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6: The CMPS [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8: The CMPS [PITH_FULL_IMAGE:figures/full_fig_p011_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: FIG. 9: Stabilizer nullity [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 11
Figure 11. Figure 11: FIG. 11: (a) The CMPS [PITH_FULL_IMAGE:figures/full_fig_p012_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: FIG. 12: The CMPS [PITH_FULL_IMAGE:figures/full_fig_p013_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: FIG. 13: In the same setting to Fig [PITH_FULL_IMAGE:figures/full_fig_p014_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: FIG. 14: Probability measurement from CAMPS: (a) [PITH_FULL_IMAGE:figures/full_fig_p015_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: FIG. 15: Evolution of the MPS bond dimension during the probability measurement using CAMPS: (a) [PITH_FULL_IMAGE:figures/full_fig_p016_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: FIG. 16: (a) The magnitude and (b) the phase of the [PITH_FULL_IMAGE:figures/full_fig_p017_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: FIG. 17: (a) Second R´enyi entropy of CAMPS on a Clifford circuit ( [PITH_FULL_IMAGE:figures/full_fig_p019_17.png] view at source ↗
Figure 18
Figure 18. Figure 18: FIG. 18: Probability for an [PITH_FULL_IMAGE:figures/full_fig_p024_18.png] view at source ↗
Figure 19
Figure 19. Figure 19: FIG. 19: Average number of entangling gates versus [PITH_FULL_IMAGE:figures/full_fig_p025_19.png] view at source ↗
Figure 21
Figure 21. Figure 21: FIG. 21: The CMPS second R´enyi entropy from the [PITH_FULL_IMAGE:figures/full_fig_p026_21.png] view at source ↗
Figure 22
Figure 22. Figure 22: FIG. 22: Prototypical example of a distribution of [PITH_FULL_IMAGE:figures/full_fig_p026_22.png] view at source ↗
Figure 23
Figure 23. Figure 23: FIG. 23: Success probabilities of the stabilizer group [PITH_FULL_IMAGE:figures/full_fig_p027_23.png] view at source ↗
Figure 24
Figure 24. Figure 24: FIG. 24: Visualization of the simulation of [PITH_FULL_IMAGE:figures/full_fig_p029_24.png] view at source ↗
Figure 25
Figure 25. Figure 25: FIG. 25: Maximum error [PITH_FULL_IMAGE:figures/full_fig_p031_25.png] view at source ↗
read the original abstract

Determining the quantum-classical boundary between quantum circuits which can be efficiently simulated classically and those which cannot remains a fundamental question. One approach to classical simulation is to represent the output of a quantum circuit as a Clifford-augmented Matrix Product State (CAMPS) which, via a disentangling algorithm, decomposes the wave function into Clifford and MPS components and from which Pauli expectation values can be computed in time polynomial in the MPS bond-dimension. In this work, we develop an optimization-free disentangling (OFD) algorithm for Clifford circuits either doped with multi-qubit gates of the form $\alpha I+\beta P$. We give a simple algebraic criterion which characterizes the individual quantum circuits for which OFD generates an efficient CAMPS - the bond-dimension is exponential in the null space of a GF(2) matrix induced by a tableau of the twisted Pauli strings $P$. This significantly increases the number of circuits with rigorous polynomial time classical simulations. We also give evidence that the typical $N$ qubit random Clifford circuit doped with $N$ uniformly distributed $T$ gates of poly-logarithmic depth or greater has a CAMPS with polynomial bond-dimension. In addition, we compare OFD against disentangling by optimization. We further explore the representability of CAMPS for random Clifford circuits doped with more than $N$ $T$-gates. We also propose algorithms for sampling, probability and amplitude estimation of bitstrings, and evaluation of entanglement R\'enyi entropy from CAMPS, which, though still having exponential complexity, are more efficient than standard MPS simulations. This work establishes a versatile framework for understanding classical simulatability of Clifford+$T$ circuits and explores the interplay between quantum entanglement and quantum magic in quantum systems.

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

1 major / 0 minor

Summary. The manuscript introduces an optimization-free disentangling (OFD) algorithm applicable to Clifford circuits doped with multi-qubit non-Clifford gates of the form αI + βP. It claims to supply a simple algebraic criterion that characterizes precisely those circuits for which OFD produces an efficient Clifford-augmented matrix product state (CAMPS): the bond dimension is exponential in the dimension of the null space of a GF(2) matrix constructed from the tableau of the twisted Pauli strings P. The work additionally reports typical-case evidence that random Clifford circuits of poly-logarithmic depth doped with N uniformly placed T gates possess polynomial-bond-dimension CAMPS, compares OFD with optimization-based disentangling, examines representability for circuits containing more than N T gates, and proposes CAMPS-based algorithms for bitstring sampling, probability/amplitude estimation, and Rényi entropy evaluation.

Significance. If the algebraic criterion is placed on a fully rigorous footing, the result would enlarge the rigorously simulable fragment of Clifford+T circuits by supplying an explicit, parameter-free test based on linear algebra over GF(2). The typical-case evidence for random ensembles and the auxiliary algorithms for sampling and entropy from CAMPS constitute further contributions. The direct connection drawn between tableau null-space dimension and post-disentangling bond dimension is a conceptually clean approach that, once verified, would be a clear strength.

major comments (1)
  1. [paragraph presenting the algebraic criterion (following the description of the OFD algorithm)] The central claim that OFD produces a CAMPS whose bond dimension is exactly exponential in the null-space dimension of the GF(2) matrix induced by the tableau of twisted Pauli strings P is stated without an explicit derivation of the mapping or verification against counter-examples. The implicit assumption that the linear dependence relations captured by the null space fully determine the residual entanglement rank after disentangling, with no additional growth arising from the Clifford component or gate ordering, is not demonstrated in the text.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for the constructive suggestion to strengthen the presentation of the algebraic criterion. We address the major comment below.

read point-by-point responses
  1. Referee: The central claim that OFD produces a CAMPS whose bond dimension is exactly exponential in the null-space dimension of the GF(2) matrix induced by the tableau of twisted Pauli strings P is stated without an explicit derivation of the mapping or verification against counter-examples. The implicit assumption that the linear dependence relations captured by the null space fully determine the residual entanglement rank after disentangling, with no additional growth arising from the Clifford component or gate ordering, is not demonstrated in the text.

    Authors: We agree that an explicit derivation would improve the rigor of the central claim. The manuscript presents the algebraic criterion and its connection to the null-space dimension of the GF(2) matrix constructed from the twisted Pauli strings, but the step-by-step mapping from the null-space dimension to the post-OFD bond dimension (including why Clifford operations and gate ordering introduce no additional entanglement growth) is only sketched implicitly through the structure of the OFD algorithm. In the revised manuscript we will add a dedicated subsection that derives this relation in detail from the tableau update rules and the action of the OFD procedure, together with explicit verification on small-scale examples that confirm the absence of extra rank growth. This will place the criterion on a fully rigorous footing as the referee recommends. revision: yes

Circularity Check

0 steps flagged

Algebraic criterion derived directly from tableau structure with no reduction to inputs

full rationale

The paper's central result is an algebraic criterion stating that CAMPS bond dimension after OFD is exponential in the null-space dimension of a GF(2) matrix constructed from the tableau of twisted Pauli strings P. This mapping is presented as following from the linear algebra of the circuit tableau and the definition of the OFD disentangling procedure for gates of the form αI + βP. No parameter is fitted to simulation outcomes and then relabeled as a prediction, no self-citation chain is invoked to justify the uniqueness or correctness of the mapping, and the derivation does not redefine any quantity in terms of the claimed result. The abstract and described claims remain self-contained against external benchmarks such as explicit tableau construction and null-space computation.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claims rest on the assumption that the non-Clifford gates are exactly of the form αI+βP and that the tableau of twisted Paulis correctly encodes the entanglement structure after Clifford operations; no free parameters or invented entities are introduced in the abstract.

axioms (1)
  • domain assumption Non-Clifford gates are restricted to the two-qubit or multi-qubit form αI + βP for Pauli string P.
    Stated in the description of the OFD algorithm; the algebraic criterion applies only under this restriction.

pith-pipeline@v0.9.0 · 5844 in / 1387 out tokens · 19111 ms · 2026-05-23T07:20:10.742212+00:00 · methodology

discussion (0)

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

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Classical Simulations of Low Magic Quantum Dynamics

    quant-ph 2025-08 unverdicted novelty 6.0

    Classical simulation algorithms for low-magic adaptive quantum circuits with high Pauli measurement rates, demonstrated on all-to-all monitored circuits with sub-extensive T-gates to study measurement-induced phase tr...

Reference graph

Works this paper leans on

50 extracted references · 50 canonical work pages · cited by 1 Pith paper · 4 internal anchors

  1. [1]

    12(b), when LT = 1, S2 has the same rate of growth per layer for NT > 1, while NT = 1 displays obvious deviation

    In Fig. 12(b), when LT = 1, S2 has the same rate of growth per layer for NT > 1, while NT = 1 displays obvious deviation

  2. [2]

    12(a), when NT = 1, S2 has the same rate of growth per T -gate, regardless of the number of Clifford layers LT

    In Fig. 12(a), when NT = 1, S2 has the same rate of growth per T -gate, regardless of the number of Clifford layers LT

  3. [3]

    In Fig. 12(a), when NT > 1, LT affects S2 incre- ment per T -gate in a non-trivial way, for example, the rate of S2 growth per T -gate for ( LT , NT ) = (2, 2) is close to that of ( LT , NT ) = (1 , 1), and (LT , NT ) = (4, 4) is close to ( LT , NT ) = (1, 2). We also show in Fig. 13 the distribution of ∆ S2 – the amount S2 changes from each T -gate – bef...

  4. [4]

    (29) We can evaluate the probability of any bitstring using the method described in Sec

    For simplicity, we define z[0] = ⟨s[j] N \kj 0|C|ψ⟩, z [1] = ⟨s[j] N \kj 1|C|ψ⟩. (29) We can evaluate the probability of any bitstring using the method described in Sec. VI A. Thus, we can ob- tain p0 = |z[0]|2, p1 = |z[1]|2, p2 = |z[0] + z[1]|2/2, 16 0.0 0.2 0.4 0.6 0.8 1.0 projection steps/N 100 101 102 103 bond dimension (a) t = N/2 N 12 14 16 18 20 24...

  5. [5]

    R. P. Feynman, Simulating physics with computers, in Feynman and computation (cRc Press, 2018) pp. 133– 153

  6. [6]

    Bouland, B

    A. Bouland, B. Fefferman, C. Nirkhe, and U. Vazirani, On the complexity and verification of quantum random circuit sampling, Nature Physics 15, 159 (2019)

  7. [7]

    Hangleiter and J

    D. Hangleiter and J. Eisert, Computational advantage of quantum random sampling, Reviews of Modern Physics 95, 035001 (2023)

  8. [8]

    Jozsa and A

    R. Jozsa and A. Miyake, Matchgates and classical simu- lation of quantum circuits, Proceedings of the Royal Soci- ety A: Mathematical, Physical and Engineering Sciences 464, 3089 (2008)

  9. [9]

    Aaronson and D

    S. Aaronson and D. Gottesman, Improved simulation of stabilizer circuits, Phys. Rev. A 70, 052328 (2004)

  10. [10]

    The Heisenberg Representation of Quantum Computers

    D. Gottesman, The heisenberg representation of quan- tum computers (1998), arXiv:quant-ph/9807006 [quant- ph]

  11. [11]

    J. C. Napp, R. L. La Placa, A. M. Dalzell, F. G. S. L. Brand˜ ao, and A. W. Harrow, Efficient classical simula- tion of random shallow 2d quantum circuits, Phys. Rev. X 12, 021021 (2022)

  12. [12]

    Vidal, Efficient classical simulation of slightly entan- gled quantum computations, Phys

    G. Vidal, Efficient classical simulation of slightly entan- gled quantum computations, Phys. Rev. Lett.91, 147902 (2003)

  13. [13]

    Vidal, Efficient simulation of one-dimensional quan- tum many-body systems, Phys

    G. Vidal, Efficient simulation of one-dimensional quan- tum many-body systems, Phys. Rev. Lett. 93, 040502 (2004)

  14. [14]

    F. Pan, K. Chen, and P. Zhang, Solving the sampling problem of the sycamore quantum circuits, Phys. Rev. Lett. 129, 090502 (2022)

  15. [15]

    Pan and P

    F. Pan and P. Zhang, Simulation of quantum circuits using the big-batch tensor network method, Phys. Rev. Lett. 128, 030501 (2022)

  16. [16]

    Villalonga, M

    B. Villalonga, M. Y. Niu, L. Li, H. Neven, J. C. Platt, V. N. Smelyanskiy, and S. Boixo, Efficient approximation of experimental gaussian boson sampling, arXiv preprint arXiv:2109.11525 (2021)

  17. [17]

    Beguˇ si´ c, J

    T. Beguˇ si´ c, J. Gray, and G. K.-L. Chan, Fast and con- verged classical simulations of evidence for the utility of quantum computing before fault tolerance, Science Ad- vances 10, eadk4321 (2024)

  18. [18]

    Tindall, M

    J. Tindall, M. Fishman, E. M. Stoudenmire, and D. Sels, Efficient tensor network simulation of ibm’s eagle kicked ising experiment, PRX Quantum 5, 010308 (2024)

  19. [19]

    Or´ us, A practical introduction to tensor networks: Matrix product states and projected entangled pair states, Annals of Physics 349, 117 (2014)

    R. Or´ us, A practical introduction to tensor networks: Matrix product states and projected entangled pair states, Annals of Physics 349, 117 (2014)

  20. [20]

    Classical simulation of quantum computation, the Gottesman-Knill theorem, and slightly beyond

    M. Nest, Classical simulation of quantum computation, the gottesman-knill theorem, and slightly beyond, arXiv preprint arXiv:0811.0898 (2008)

  21. [21]

    G. Nebe, E. M. Rains, and N. J. Sloane, The invariants of the clifford groups, Designs, Codes and Cryptography 24, 99 (2001)

  22. [22]

    E. T. Campbell, H. Anwar, and D. E. Browne, Magic- state distillation in all prime dimensions using quantum reed-muller codes, Physical Review X 2, 041021 (2012)

  23. [23]

    Bravyi and A

    S. Bravyi and A. Kitaev, Universal quantum computa- tion with ideal clifford gates and noisy ancillas, Physical Review A—Atomic, Molecular, and Optical Physics 71, 022316 (2005)

  24. [24]

    Bravyi, D

    S. Bravyi, D. Browne, P. Calpin, E. Campbell, D. Gosset, and M. Howard, Simulation of quantum circuits by low- rank stabilizer decompositions, Quantum 3, 181 (2019)

  25. [25]

    Kissinger and J

    A. Kissinger and J. van de Wetering, Simulating quan- tum circuits with zx-calculus reduced stabiliser decom- positions, Quantum Science and Technology 7, 044001 (2022). 21

  26. [26]

    Beguˇ si´ c, K

    T. Beguˇ si´ c, K. Hejazi, and G. K.-L. Chan, Simulating quantum circuit expectation values by clifford perturba- tion theory (2023), arXiv:2306.04797 [quant-ph]

  27. [27]

    Pashayan, O

    H. Pashayan, O. Reardon-Smith, K. Korzekwa, and S. D. Bartlett, Fast estimation of outcome probabilities for quantum circuits, PRX Quantum 3, 020361 (2022)

  28. [28]

    G. Lami, T. Haug, and J. D. Nardis, Quantum state designs with clifford enhanced matrix product states (2024), arXiv:2404.18751 [quant-ph]

  29. [29]

    X. Qian, J. Huang, and M. Qin, Augmenting density ma- trix renormalization group with clifford circuits, Phys. Rev. Lett. 133, 190402 (2024)

  30. [30]

    A. F. Mello, A. Santini, G. Lami, J. D. Nardis, and M. Collura, Clifford dressed time-dependent variational principle (2024), arXiv:2407.01692 [quant-ph]

  31. [31]

    X. Qian, J. Huang, and M. Qin, Clifford circuits augmented time-dependent variational principle (2024), arXiv:2407.03202 [cond-mat.str-el]

  32. [32]

    Huang, X

    J. Huang, X. Qian, and M. Qin, Non-stabilizerness en- tanglement entropy: a measure of hardness in the clas- sical simulation of quantum many-body systems (2024), arXiv:2409.16895 [quant-ph]

  33. [33]

    G. E. Fux, B. B´ eri, R. Fazio, and E. Tirrito, Disentan- gling unitary dynamics with classically simulable quan- tum circuits (2024), arXiv:2410.09001 [quant-ph]

  34. [34]

    Paviglianiti, G

    A. Paviglianiti, G. Lami, M. Collura, and A. Silva, Es- timating non-stabilizerness dynamics without simulating it (2024), arXiv:2405.06054 [quant-ph]

  35. [35]

    V. F. Kolchin, Random graphs, 53 (Cambridge University Press, 1999)

  36. [36]

    Gidney, Stim: a fast stabilizer circuit simulator, Quan- tum 5, 497 (2021)

    C. Gidney, Stim: a fast stabilizer circuit simulator, Quan- tum 5, 497 (2021)

  37. [37]

    Y. Zhou, E. M. Stoudenmire, and X. Waintal, What lim- its the simulation of quantum computers?, Phys. Rev. X 10, 041038 (2020)

  38. [38]

    Ayral, T

    T. Ayral, T. Louvet, Y. Zhou, C. Lambert, E. M. Stoudenmire, and X. Waintal, Density-matrix renormal- ization group algorithm for simulating quantum circuits with a finite fidelity, PRX Quantum 4, 020304 (2023)

  39. [39]

    A. F. Mello, A. Santini, and M. Collura, Clifford-dressed variational principles for precise loschmidt echoes, Phys- ical Review A 111, 052401 (2025)

  40. [40]

    D. M. Ceperley and B. J. Alder, Ground state of the electron gas by a stochastic method, Phys. Rev. Lett. 45, 566 (1980)

  41. [41]

    R. M. Martin, L. Reining, and D. M. Ceperley, Interact- ing electrons (Cambridge University Press, 2016)

  42. [42]

    Huang, J

    H.-Y. Huang, J. Preskill, and M. Soleimanifar, Certifying almost all quantum states with few single-qubit measure- ments (2024), arXiv:2404.07281 [quant-ph]

  43. [43]

    Entanglement in the stabilizer formalism

    D. Fattal, T. S. Cubitt, Y. Yamamoto, S. Bravyi, and I. L. Chuang, Entanglement in the stabilizer formalism (2004), arXiv:quant-ph/0406168 [quant-ph]

  44. [44]

    Viscardi, M

    M. Viscardi, M. Dalmonte, A. Hamma, and E. Tirrito, In- terplay of entanglement structures and stabilizer entropy in spin models (2025), arXiv:2503.08620 [quant-ph]

  45. [45]

    A. Gu, S. F. E. Oliviero, and L. Leone, Magic-induced computational separation in entanglement theory (2024), arXiv:2403.19610 [quant-ph]

  46. [46]

    Bejan, C

    M. Bejan, C. McLauchlan, and B. B´ eri, Dynamical magic transitions in monitored clifford+ t circuits, PRX Quan- tum 5, 030332 (2024)

  47. [47]

    Zhang and Y

    Y. Zhang and Y. Zhang, Classical simulability of quantum circuits with shallow magic depth (2024), arXiv:2409.13809 [quant-ph]

  48. [48]

    Wei and Z.-W

    F. Wei and Z.-W. Liu, Long-range nonstabilizerness from quantum codes, orders, and correlations, arXiv preprint arXiv:2503.04566 (2025)

  49. [49]

    A. C. Nakhl, B. Harper, M. West, N. Dowling, M. Sev- ior, T. Quella, and M. Usman, Stabilizer tensor networks with magic state injection, Phys. Rev. Lett. 134, 190602 (2025)

  50. [50]

    Lami and M

    G. Lami and M. Collura, Unveiling the stabilizer group of a matrix product state, Phys. Rev. Lett. 133, 010602 (2024). Appendix A: Notations In this section we introduce the notations used throughout this work. We denote the identity and Pauli operators as I = 1 0 1 0 , X = 0 1 1 0 , Y = 0 −i i 0 , Z = 1 0 0 −1 . (A1) For a quantum system composed of N qu...