REVIEW 3 major objections 6 minor 3 cited by
Complexity of PXP scars revisited
T0 review · 3 major / 6 minor · reviewed 2026-08-06 · deepseek-v4-flash
Pith's one-line read The arch-shaped profile of Lanczos coefficients in the PXP model comes from a linear sl(3,C) part of the Hamiltonian, and the arch width above a threshold in (3L/4, 5L/6) marks an initial state as a quantum many-body scar.
desk verdict The sl(3,C) decomposition and analytic Lanczos coefficients are a solid advance, but the arch-width scar criterion is post hoc and the linear-to-full transfer is only checked for tiny systems. 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 load-bearing object is the decomposition $H_{\mathrm{PXP}} = H_{\mathrm{PXP,lin}} + H_{\mathrm{PXP,res}}$, obtained by mapping each pair of qubits to one qutrit ($L = 2\ell$) and rewriting the PXP terms with the Gell-Mann/Cartan–Weyl generators of $\mathfrak{sl}_3(\mathbb{C})$. $H_{\mathrm{PXP,lin}}$ is a sum of single-site operators $E_{\pm\alpha} + E_{\pm\beta}$ that close on an $\mathfrak{su}(2)$ subalgebra; for initial states $|Z_k\rangle$ this makes the Krylov ladder exactly solvable, yielding the closed-form Lanczos coefficients of formula (5.50) and the arch width $n_{\max} = (k+2)L/(2k)$ listed in Table 1. The arch width is the quantity that carries the scar diagnostic. The residual term $H_{\mathrm{PXP,res}}$, which does not commute with the $\mathfrak{sl}_3(\mathbb{C})$ Casimir operators and therefore mixes irreducible representations, accounts for the collapse of the arch and the growth of the buttress; the number of states reachable by the full Hamiltonian along the way is counted by Lucas numbers. The supporting numerics are full-orthogonalization Lanczos spectra, the comb-like FFT of the $|Z_2\rangle$ fidelity, and the near-equally-spaced spectra of arch-truncated Hamiltonians.
What would settle it
Run the full-orthogonalization Lanczos algorithm on the full PXP Hamiltonian at a larger lattice, say $L=20$, and count the coefficients before the erratic tail for $|Z_3\rangle$ and $|Z_4\rangle$: if the arch width of $|Z_3\rangle$ falls below $5L/6$, or that of $|Z_4\rangle$ rises above $3L/4$, the threshold criterion fails. A sharper probe is to scale the residual part of the Hamiltonian by a continuous factor $\lambda$: if the linear part truly governs the arch, $n_{\max}$ must be $\lambda$-independent, so any $\lambda$-dependence of the arch width would show the equality is accidental rather than structural.
Extended reading notes
Core claim
The central claim is that the PXP Hamiltonian, in a two-qubits-per-qutrit encoding, splits into a linear term $H_{\mathrm{PXP,lin}}$ built from the Cartan–Weyl generators of $\mathfrak{sl}_3(\mathbb{C})$ and a residual interaction term $H_{\mathrm{PXP,res}}$. The linear term preserves the irreducible representations of $\mathfrak{sl}_3(\mathbb{C})$, and on the initial states $|Z_k\rangle$ it generates a Krylov subspace whose Lanczos coefficients form an arch; for the scarred states these coefficients are computed exactly, for example $b_m = \sqrt{m(2n-m+1)/2}$ for the $|2\rangle$-tower, an arch of width $2n$. The linear term admits a spectrum-generating operator $Q^\dagger$ with $[H_{\mathrm{PXP,lin}}, Q^\dagger] = \sqrt{2}\,Q^\dagger$, so it carries an equally spaced scar tower, and the truncated Hamiltonian that keeps only the arch coefficients reproduces nearly equally spaced spectra for $|Z_2\rangle$ and $|Z_3\rangle$ but not for $|Z_4\rangle$. The residual term cancels states containing the pattern $|1\rangle \otimes |2\rangle$ (the '$|12\rangle$ issue'), collapses the arch, activates other irreducible representations, and engenders the buttress, whose extent the authors bound by Lucas numbers. The paper concludes that an arch width larger than some number in the interval $(3L/4, 5L/6)$ can be used as a signal that the corresponding initial state is a scar.
Load-bearing premise
The argument assumes that the width of the arch — the number of hump-shaped Lanczos coefficients before the erratic tail — is the same whether it is computed from the simplified linear part or from the full PXP Hamiltonian, so that $n_{\max}$ can serve as a scar detector; this equality is demonstrated explicitly only for $L=6$ and $L=8$, and for larger lattices it is inferred from plots rather than proved or bounded.
Editorial extensions
If this is right
- Scarring of an initial state becomes checkable from Lanczos data alone: run full-orthogonalization Lanczos, count the coefficients before the erratic tail sets in, and compare the arch width with $(3L/4, 5L/6)$; no fidelity curve or eigenstate decomposition is needed.
- The analytic formula $n_{\max} = (k+2)L/(2k)$ arranges the $|Z_k\rangle$ states into a hierarchy — $|Z_2\rangle$ at width $L$ and $|Z_3\rangle$ at $5L/6$ above the threshold, $|Z_4\rangle$ at $3L/4$ and higher-$k$ states below it — which is exactly the pattern of which states exhibit quantum revivals.
- For scarred initial states, spread complexity and Krylov entropy oscillate periodically in time, whereas for thermalizing states the oscillations are suppressed; both quantities thereby join fidelity as probes of quantum scarring.
- For large lattices the full PXP Krylov subspace has dimension close to a Lucas number, giving an exponential-in-$L$ estimate of how far the constrained dynamics extend beyond the scar subspace.
Reading between the lines
- Since no integer $k$ puts $(k+2)/2k$ strictly inside $(3/4, 5/6)$, the $|Z_k\rangle$ family itself cannot locate the threshold within that interval; initial states interpolating between $|Z_3\rangle$ and $|Z_4\rangle$ (for instance, dilute defects in the periodic pattern) would be the sharp test, and the criterion predicts their revival-to-thermal transition to occur exactly where $n_{\max}$ cross
- The mechanism suggests arch-plus-buttress should be generic for kinetically constrained models whose qutrit encoding contains a forbidden pattern such as $|1\rangle\otimes|2\rangle$: the residual term that cancels the pattern will generically collapse the arch and activate neighbouring irreducible representations. This extrapolation goes beyond what the paper establishes for the PXP model.
- A quantitative link left implicit: the arch-truncated Hamiltonian for $|Z_2\rangle$ at $L=12$ has level spacing near 1.31, slightly below the spectrum-generating-algebra prediction $\sqrt{2}\approx 1.414$; the small gap between them measures how much the residual term distorts the perfect scar tower even within the arch.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper analyzes the Lanczos coefficients and spread complexity for quenches of product states |Z_k> under the PXP Hamiltonian. By mapping two qubits to one qutrit, the authors decompose H_PXP into a non-interacting 'linear' part H_PXP,lin and a residual interacting part H_PXP,res, both expressed in the Cartan-Weyl basis of sl3(C). For H_PXP,lin they derive closed-form Lanczos coefficients and an arch width n_max = L(k+2)/(2k), summarized in Table 1, and they propose that an arch width exceeding some value in (3L/4, 5L/6) signals scarring. The residual part is argued to explain the collapse of the arch and the subsequent 'buttress' via the |12> issue, with an upper bound on the Krylov dimension given by Lucas numbers. The paper also presents numerical evidence from fidelity, FFT, truncated-Hamiltonian spectra, and spread complexity oscillations for scarred versus thermalizing states, and it provides explicit Krylov bases for small system sizes in the appendices.
Significance. If the central claim holds, the paper offers an analytical, parameter-free explanation of the arch/buttress morphology of Lanczos coefficients in the PXP model, grounded in sl3(C) representation theory, and a Krylov-space criterion for detecting quantum many-body scars. The algebraic decomposition H_PXP = H_lin + H_res is exact, the analytic b_m for H_lin follows from su(2) representation theory, and the small-system Krylov bases in Appendix F are worked out in explicit detail. The Lucas-number counting of the constrained Krylov space is a useful structural result, and the numerical comparisons, including the FFT comb for |Z2> and the truncated-spectrum analysis, provide supporting evidence. The main weakness is that the connection between the analytic arch width of H_lin and the arch width of the full Hamiltonian is established only for L=6,8 for |Z2>, and the proposed threshold is calibrated on the same |Z_k> family it is used to classify.
major comments (3)
- [Sections 5.2.1–5.2.2, 7, Table 1, Appendix F] The central diagnostic claim is that the arch width n_max computed analytically for H_PXP,lin in (5.53) equals the arch width of the full PXP Lanczos coefficients, so that n_max can be used as a scarring signal. This equality is explicitly verified only for L=6 and L=8 for |Z2> in Appendix F; for |Z3>, |Z4> and larger sizes it is inferred from Figures 3b–3d. The paper itself states in Section 5.3 that H_PXP,res modifies the Lanczos coefficients from the very beginning, and in the explicit L=8 example the full chain has nonzero b_9 through b_12, so the full-Hamiltonian 'arch width' is not the first vanishing Lanczos coefficient. A precise operational definition of the arch width for the full model is needed, together with a general argument or error estimate that the residual term does not shift the arch boundary. Without this, the threshold criterion in Section 7 lacks its stated footing.
- [Section 5.2.1, Table 1, Section 7] The threshold interval (3L/4, 5L/6) appears to be selected after the fact. Table 1 labels |Z2> and |Z3> as scars and |Z4> as not a scar, and the interval is exactly the gap between n_max(k=4)=3L/4 and n_max(k=3)=5L/6. Thus the criterion reproduces the classification of the states from which it was inferred rather than providing an independent prediction. To make the claim load-bearing, the authors should either derive the threshold from the SGA/energy-gap analysis (for instance from the truncated-spectrum data in Figure 10) before comparing with scar status, or test the criterion on initial states outside the |Z_k> family, such as superpositions or states with the same arch width but different overlap with the scar subspace.
- [Section 5.2.2, final paragraph] The quantitative explanation of the buttress is explicitly incomplete: the paper admits that the ratio of coefficients of |2001> and |2020> in |K4> 'does not match our prediction' and leaves it as an open puzzle. Since the authors frame the residual-part analysis as qualitative, this does not undermine the arch-width formula, but it does mean that the statement that H_PXP,res 'accounts for the emergence of the buttress' is only partially supported. The limitation should be stated more prominently in the conclusions, and the mismatch should be acknowledged as a gap in the claimed decomposition of the Lanczos coefficients into arch and buttress contributions.
minor comments (6)
- [Abstract and Section 1] The abstract contains a duplicated phrase 'we observe that that there exists a threshold'; also 'quqit' should be 'qudit' throughout.
- [Section 5.2.2, L=8 example] In the sentence 'Using a similar arguments to the case of L=2ℓ=3', the reference to L=2ℓ=3 should read L=2ℓ=6.
- [Figure 9 caption] The caption reads '(9a) and (9a)' for the second panel; it should be '(9a) and (9b)'.
- [Table 1] The k=∞ row reports 'nmax = 1ℓ', which is notationally confusing; the authors should write n_max = ℓ.
- [Section 5.3] The standard deviations of energy gaps are reported as 0.05688, 0.09624, and 0.1582 without stating the number of gaps used or the error on the standard deviation; please clarify the sample size and the criterion for 'lowest five energy levels'.
- [Appendix A, Figure 16] The plots in Figure 16 compare FO, PRO, and standard Lanczos, but the panels lack axis labels for the PRO case (16b); adding labels would improve readability.
Circularity Check
The arch-width scar criterion is calibrated post hoc on the known revival states, so the Section 7 'signal' reduces to the input classification; the sl3/Lucas derivations themselves are independent.
-
fitted input called prediction
[Section 5.2.1 (Table 1) and Section 7]
"Based on this, we give our observation here – the pattern of the growth of the Lanczos coefficient with the arch width smaller than some number in the interval (3/2ℓ,5/3ℓ) is no longer able to support any quantum revivals."
Table 1 already labels |Z2> and |Z3> as scars and |Z4> and higher as non-scars, a classification established independently in Section 4.1 from fidelity revivals. The analytic widths are n_max=2ℓ for |Z2>, 5/3ℓ for |Z3>, and 3/2ℓ for |Z4>. The proposed threshold interval (3/2ℓ,5/3ℓ) is exactly the open gap between the known scar |Z3> and the known non-scar |Z4>. Thus 'arch width greater than some number in that interval' is logically equivalent to selecting the previously known scar classes k=2,3 over the previously known non-scar classes k≥4. The threshold is a post-hoc separator fitted to the known revival data, not a parameter-free consequence of the sl3 analysis, and Section 7 then exports it as a scar signal.
full rationale
The central independent content — the sl3(C) decomposition into H_lin and H_res, the algebraic Lanczos coefficients (5.50)–(5.53), the n_max formula k+2/k ℓ, the Lucas-number bound, and the numerical FFT/spectral comparisons — is self-contained and does not reduce to its inputs. However, the paper's headline diagnostic claim, that an arch wider than some number in (3/4L,5/6L) signals scarring, is not derived from the algebra. It is an observed threshold placed between the n_max values of states whose scar/non-scar status was already known from fidelity revivals, so the 'signal' reproduces the calibration data in new coordinates. The admitted coefficient mismatch at the end of Section 5.2.2 and the qualitative nature of the residual analysis are correctness limitations rather than circularity, and the self-citations to [6] and [42] are standard published methods rather than unverified load-bearing references.
Assumptions & free parameters
free parameters (1)
- Scarring threshold arch width =
between 3L/4 and 5L/6
assumptions (4)
- standard math sl(3,C) representation theory and Young-tableaux decomposition of D(1,0)^{⊗ℓ}
- domain assumption The working hypothesis that H_PXP,lin generates the scar subspace while H_PXP,res generates the thermalizing subspace
- ad hoc to paper The arch width of the full PXP Hamiltonian matches the n_max computed from H_PXP,lin
- ad hoc to paper The residual Hamiltonian's effect is fully captured by removing |1>|2> product states (the '|12> issue')
Cite this review
Pith. "Pith review of Complexity of PXP scars revisited." pith.science (2026). https://pith.science/paper/2GIIVK4D
@misc{pith2026250621156,
author = {Pith},
title = {Pith review of: Complexity of PXP scars revisited},
year = {2026},
howpublished = {\url{https://pith.science/paper/2GIIVK4D}},
note = {Machine review of arXiv:2506.21156}
}
abstract
We revisit a quantum quench scenario in which either a scarring or thermalizing initial state evolves under the PXP Hamiltonian. Within this framework, we study the time evolution of spread complexity and related quantities in the Krylov basis. We find that the Lanczos coefficients $b_n$, as functions of the iteration number $n$, exhibit a characteristic arched growth and decay, followed by erratic oscillations which we refer to as buttress. The arched profile predominantly arises from contributions within the quantum many-body scar subspace, while the buttress is linked to thermalization dynamics. To explain this behavior, we utilize the representation theory of $\mathfrak{s}l_3(\mathbb{C})$, allowing us to decompose the PXP Hamiltonian into a linear component and a residual part. The linear term governs the formation and width of the arch, and we observe that that there exists a threshold of arch width which determines whether a given initial state exhibits scarring. Meanwhile, the residual term accounts qualitatively for the emergence of the buttress. We estimate an upper bound for the extent of the buttress using Lucas numbers. Finally, we demonstrate that spread complexity oscillates periodically over time for scarred initial states, whereas such oscillations are suppressed in thermalizing cases.
Forward citations
Cited by 3 Pith papers
-
Krylov-Space Memory Cores
Anomalous initial states in otherwise thermalizing models leave compact, stationary low-depth Krylov-space cores—regions with persistent fluctuations, Gibbs mismatch, and current activity—while generic states do not.
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Krylov complexity, mode-resolved complexity and entanglement entropy across phase transitions in the non-Hermitian extended Su-Schrieffer-Heeger model
Mode-resolved Krylov complexity and entanglement entropy signal exceptional-point and topological transitions and dynamical phases in the non-Hermitian extended SSH model.
-
Emergence of Krylov complexity through quantum walks: An exploration of the quantum origins of complexity
Reducing a graph walk to distance-layers reproduces Krylov/spread complexity, yielding analytic finite-q SYK Lanczos coefficients and hypercube complexity D sin²(t/D), with faster saturation than classical-walk circuits.
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