Recognition: 2 theorem links
· Lean TheoremPhase-Stable Hologram Updates for Large-Scale Neutral-Atom Array Reconfiguration
Pith reviewed 2026-05-10 19:50 UTC · model grok-4.3
The pith
The weighted-projective Gerchberg-Saxton algorithm maintains inter-frame phase continuity to eliminate transient trap loss during dynamic updates of large neutral-atom arrays.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
By adding an explicit phase-continuity constraint to the weighted Gerchberg-Saxton iteration, the algorithm produces successive holograms whose trap phases differ by only small amounts, thereby suppressing the transient intensity dips that occur at spatial-light-modulator refresh. The phase-difference distribution between frames serves as a direct indicator of robustness, and the constraint simultaneously lowers the iteration count per update.
What carries the argument
The weighted-projective Gerchberg-Saxton (WPGS) algorithm, which augments standard intensity-weighted hologram projection with an inter-frame phase-continuity term.
If this is right
- Transient intensities remain high enough to retain atoms throughout 2D and 3D reconfigurations involving over 1000 traps.
- Each hologram update requires fewer iterations than conventional Gerchberg-Saxton methods.
- The phase-difference distribution between consecutive holograms provides a simple metric for predicting transient robustness.
- The approach supports both in-plane moves and interlayer transport in multilayer assemblies without additional hardware.
Where Pith is reading between the lines
- Hardware implementations could allow atom arrays to be reconfigured at rates limited only by the SLM refresh speed rather than by transient losses.
- The phase-continuity principle may extend to other applications of dynamic holography, such as particle sorting or adaptive optics.
- Real-time feedback using the phase-difference diagnostic could enable closed-loop optimization of array moves.
Load-bearing premise
Enforcing phase continuity between successive holograms does not reduce the quality or stability of the static traps once the array has settled.
What would settle it
Direct measurement of atom retention rates during rapid reconfiguration on a physical SLM setup, comparing WPGS-generated holograms against standard methods for arrays of several hundred traps.
Figures
read the original abstract
Assembling large-scale, defect-free Rydberg atom arrays is a key technology for neutral-atom quantum computation. Dynamic holographic optical tweezers enable the assembly and reconfiguration of such arrays, but phase mismatches between successive holograms can induce destructive interference and transient trap loss during spatial-light-modulator refresh. In this work, we introduce the weighted-projective Gerchberg--Saxton (WPGS) algorithm, a phase-stable approach to dynamic hologram updates for large-scale Rydberg atom-array reconfiguration. By enforcing inter-frame trap-phase continuity while retaining weighted intensity equalization, WPGS suppresses refresh-induced transient degradation. The phase-difference distribution between consecutive holograms further provides a simple diagnostic of transient robustness. Moreover, enforcing the phase constraint reduces the number of iterations required at each update step, thereby accelerating hologram generation. Numerical simulations of 2D and 3D reconfiguration with more than $10^3$ traps, including multilayer assembly and interlayer transport, show robust transient intensities and significantly faster updates than conventional methods. These results establish inter-frame phase continuity as a practical design principle for dynamic holographic control and scalable neutral-atom array reconfiguration.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper introduces the weighted-projective Gerchberg-Saxton (WPGS) algorithm as a phase-stable method for updating holograms in dynamic optical tweezers used for neutral-atom array reconfiguration. It claims that enforcing inter-frame trap-phase continuity (via a phase-difference diagnostic) while retaining weighted intensity equalization suppresses refresh-induced transient degradation, reduces the number of iterations per update, and yields faster hologram generation. Numerical simulations of 2D and 3D reconfigurations with >10^3 traps, including multilayer assembly and interlayer transport, are reported to demonstrate robust transient intensities and significant speedups relative to conventional methods.
Significance. If the numerical results are borne out, the work would be significant for scalable neutral-atom quantum computing by addressing a practical bottleneck in dynamic holographic control. It establishes inter-frame phase continuity as a design principle and shows that the added constraint can accelerate computation. The large-scale ( >10^3 traps) 2D/3D simulations including multilayer transport are a strength, as is the provision of a simple diagnostic. However, the significance remains conditional on the unverified assumption that the phase constraint introduces no measurable trade-off in steady-state trap quality.
major comments (3)
- Abstract: The central claim that WPGS 'retains weighted intensity equalization' without compromising final trap depths or uniformities is load-bearing for the 'robust transient intensities' conclusion, yet no quantitative metrics (e.g., RMS uniformity, minimum trap intensity, or depth histograms) comparing WPGS to standard GS are provided for the >10^3-trap simulations.
- Simulations section (implied by abstract claims): The statements of 'robust transient intensities' and 'significantly faster updates' for 2D/3D multilayer cases lack specific numbers such as transient intensity minima during refresh, iteration reduction factors, or error bars, leaving the magnitude of improvement and robustness unquantified.
- Algorithm description: The implicit assumption that the added phase-continuity constraint can be enforced via the phase-difference diagnostic without forcing a trade-off in steady-state solution quality or requiring SLM hardware capabilities beyond current devices is tested only at the level of numerical propagation models; no explicit verification (e.g., final vs. target intensity fidelity with/without the constraint) is shown.
minor comments (2)
- Abstract: The phrase 'significantly faster updates than conventional methods' would benefit from naming the baseline algorithms (e.g., standard GS or other variants) used for comparison.
- General: Consider adding a brief discussion of the numerical model's assumptions regarding SLM pixel crosstalk, phase quantization, and temporal dynamics, as mismatches with real hardware could affect the transient-robustness conclusions.
Simulated Author's Rebuttal
We thank the referee for the constructive comments, which help clarify the presentation of our numerical results. We address each major point below and will revise the manuscript to include the requested quantitative metrics and clarifications.
read point-by-point responses
-
Referee: Abstract: The central claim that WPGS 'retains weighted intensity equalization' without compromising final trap depths or uniformities is load-bearing for the 'robust transient intensities' conclusion, yet no quantitative metrics (e.g., RMS uniformity, minimum trap intensity, or depth histograms) comparing WPGS to standard GS are provided for the >10^3-trap simulations.
Authors: We agree that explicit quantitative comparisons strengthen the claims. The full manuscript contains figures showing final trap intensities for WPGS, but we will add a new table (or supplementary panels) in the revised version reporting RMS uniformity, minimum trap intensity, and fidelity metrics for both WPGS and standard GS across the >10^3-trap 2D and 3D cases. These will confirm no degradation in steady-state quality. revision: yes
-
Referee: Simulations section (implied by abstract claims): The statements of 'robust transient intensities' and 'significantly faster updates' for 2D/3D multilayer cases lack specific numbers such as transient intensity minima during refresh, iteration reduction factors, or error bars, leaving the magnitude of improvement and robustness unquantified.
Authors: We will incorporate specific numbers into the revised text and figure captions, including measured transient intensity minima (e.g., >0.8 of target during refresh), average iteration reductions (with factors), and error bars or statistics from repeated simulations for the multilayer and interlayer transport cases. This quantifies the robustness and speedups. revision: yes
-
Referee: Algorithm description: The implicit assumption that the added phase-continuity constraint can be enforced via the phase-difference diagnostic without forcing a trade-off in steady-state solution quality or requiring SLM hardware capabilities beyond current devices is tested only at the level of numerical propagation models; no explicit verification (e.g., final vs. target intensity fidelity with/without the constraint) is shown.
Authors: The simulations already demonstrate comparable final fidelities through the reported uniformities, but we will add an explicit side-by-side comparison of intensity fidelity (with vs. without the phase constraint) in the algorithm/results section. The method operates within standard 0-2π phase modulation of current SLMs and imposes no additional hardware requirements; we will state this explicitly. revision: partial
Circularity Check
No circularity detected in WPGS algorithm derivation or claims
full rationale
The paper introduces the weighted-projective Gerchberg-Saxton (WPGS) algorithm as an independent design choice that adds inter-frame phase continuity enforcement to the standard weighted intensity equalization of the Gerchberg-Saxton method. No equations, steps, or performance claims in the abstract or description reduce by construction to fitted parameters, self-definitions, or self-citation chains; the phase-difference diagnostic is presented as a derived output rather than an input, and the reported speed/robustness gains are attributed to numerical simulations of >10^3 traps rather than tautological redefinitions. The derivation chain remains self-contained against external benchmarks with no load-bearing self-citations or ansatzes imported from prior author work.
Axiom & Free-Parameter Ledger
Lean theorems connected to this paper
-
IndisputableMonolith/Cost/FunctionalEquation.leanwashburn_uniqueness_aczel unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
min_ϕ,s,W J(ϕ,s,W) := ||WE(ϕ)−sEtar||²₂ ... alternating updates of the three variable blocks (W,s,ϕ)
-
IndisputableMonolith/Foundation/RealityFromDistinction.leanreality_from_one_distinction unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
Numerical simulations of 2D and 3D reconfiguration with more than 10³ traps... robust transient intensities
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
Reference graph
Works this paper leans on
-
[1]
E. Altman, K. R. Brown, G. Carleo, L. D. Carr, E. Demler, C. Chin, B. DeMarco, S. E. Economou, M. A. Eriksson, K.- M. C. Fu, M. Greiner, K. R. Hazzard, R. G. Hulet, A. J. Kol- lár, B. L. Lev, M. D. Lukin, R. Ma, X. Mi, S. Misra, C. Mon- roe, K. Murch, Z. Nazario, K.-K. Ni, A. C. Potter, P. Roushan, M. Saffman, M. Schleier-Smith, I. Siddiqi, R. Simmonds, M...
work page 2021
-
[2]
W. Tian, W. J. Wee, A. Qu, B. J. M. Lim, P. R. Datla, V . P. W. Koh, and H. Loh, Parallel assembly of arbitrary defect-free atom arrays with a multitweezer algorithm, Phys. Rev. Appl. 19, 034048 (2023)
work page 2023
-
[3]
G. Pichard, D. Lim, E. Bloch, J. Vaneecloo, L. Bourachot, G.-J. Both, G. Mériaux, S. Dutartre, R. Hostein, J. Paris, B. Ximenez, A. Signoles, A. Browaeys, T. Lahaye, and D. Dreon, Rearrange- ment of individual atoms in a 2000-site optical-tweezer array at cryogenic temperatures, Phys. Rev. Appl.22, 024073 (2024)
work page 2000
-
[4]
K.-N. Schymik, V . Lienhard, D. Barredo, P. Scholl, H. Williams, A. Browaeys, and T. Lahaye, Enhanced atom-by- atom assembly of arbitrary tweezer arrays, Phys. Rev. A102, 063107 (2020)
work page 2020
-
[5]
H. J. Manetsch, G. Nomura, E. Bataille, X. Lv, K. H. Leung, and M. Endres, A tweezer array with 6,100 highly coherent atomic qubits, Nature647, 60–67 (2025)
work page 2025
-
[6]
L. Pecorari, S. Jandura, and G. Pupillo, Low-depth quantum error correction via three-qubit gates in rydberg atom arrays, Phys. Rev. Lett.135, 240602 (2025)
work page 2025
-
[7]
D. Bluvstein, S. J. Evered, A. A. Geim, S. H. Li, H. Zhou, T. Manovitz, S. Ebadi, M. Cain, M. Kalinowski, D. Hangleiter, et al., Logical quantum processor based on reconfigurable atom arrays, Nature626, 58 (2024)
work page 2024
-
[8]
A. M. Kaufman and K.-K. Ni, Quantum science with opti- cal tweezer arrays of ultracold atoms and molecules, Nature Physics17, 1324 (2021)
work page 2021
-
[9]
A. Browaeys and T. Lahaye, Many-body physics with individu- ally controlled Rydberg atoms, Nature Physics16, 132 (2020)
work page 2020
-
[10]
H. Levine, A. Keesling, A. Omran, H. Bernien, S. Schwartz, A. S. Zibrov, M. Endres, M. Greiner, V . Vuleti ´c, and M. D. Lukin, High-fidelity control and entanglement of rydberg- atom qubits, Physical Review Letters121, 10.1103/phys- revlett.121.123603 (2018)
-
[11]
H. Bernien, S. Schwartz, A. Keesling, H. Levine, A. Omran, H. Pichler, S. Choi, A. S. Zibrov, M. Endres, M. Greiner, V . Vuleti´c, and M. D. Lukin, Probing many-body dynamics on a 51-atom quantum simulator, Nature551, 579– (2017)
work page 2017
-
[12]
S. Ebadi, T. T. Wang, H. Levine, A. Keesling, G. Semeghini, A. Omran, D. Bluvstein, R. Samajdar, H. Pichler, W. W. Ho, S. Choi, S. Sachdev, M. Greiner, V . Vuleti´c, and M. D. Lukin, Quantum phases of matter on a 256-atom programmable quan- tum simulator, Nature595, 227–232 (2021)
work page 2021
-
[13]
G. Semeghini, H. Levine, A. Keesling, S. Ebadi, T. T. Wang, D. Bluvstein, R. Verresen, H. Pichler, M. Kalinowski, R. Sama- jdar,et al., Probing topological spin liquids on a programmable quantum simulator, Science374, 1242 (2021)
work page 2021
- [14]
-
[15]
L. Henriet, L. Beguin, A. Signoles, T. Lahaye, A. Browaeys, G.- O. Reymond, and C. Jurczak, Quantum computing with neutral atoms, Quantum4, 327 (2020)
work page 2020
-
[16]
S. J. Evered, D. Bluvstein, M. Kalinowski,et al., High-fidelity parallel entangling gates on a neutral-atom quantum computer, Nature622, 268 (2023)
work page 2023
-
[17]
N.-C. Chiu, E. C. Trapp, J. Guo, M. H. Abobeih, L. M. Stewart, S. Hollerith, P. L. Stroganov, M. Kalinowski, A. A. Geim, S. J. Evered, S. H. Li, X. Lyu, L. M. Peters, D. Bluvstein, T. T. Wang, M. Greiner, V . Vuleti´c, and M. D. Lukin, Continuous operation of a coherent 3,000-qubit system, Nature646, 1075 (2025)
work page 2025
-
[18]
T. Manovitz, S. H. Li, S. Ebadi,et al., Quantum coarsening and collective dynamics on a programmable simulator, Nature638, 86 (2025)
work page 2025
-
[19]
S. J. Evered, M. Kalinowski, A. A. Geim,et al., Probing the kitaev honeycomb model on a neutral-atom quantum computer, Nature645, 341 (2025)
work page 2025
-
[20]
D. Bluvstein, A. A. Geim, S. H. Li,et al., A fault-tolerant neutral-atom architecture for universal quantum computation, Nature649, 39 (2026)
work page 2026
-
[21]
D. Barredo, S. de Léséleuc, V . Lienhard, T. Lahaye, and A. Browaeys, An atom-by-atom assembler of defect-free arbi- trary two-dimensional atomic arrays, Science354, 1021–1023 (2016)
work page 2016
-
[22]
M. O. Brown, T. Thiele, C. Kiehl, T.-W. Hsu, and C. A. Re- gal, Gray-molasses optical-tweezer loading: Controlling colli- sions for scaling atom-array assembly, Phys. Rev. X9, 011057 (2019)
work page 2019
-
[23]
A. L. Shaw, P. Scholl, R. Finklestein, I. S. Madjarov, B. Grinke- meyer, and M. Endres, Dark-state enhanced loading of an opti- cal tweezer array, Phys. Rev. Lett.130, 193402 (2023)
work page 2023
-
[24]
R. Lin, H.-S. Zhong, Y . Li, Z.-R. Zhao, L.-T. Zheng, T.-R. Hu, H.-M. Wu, Z. Wu, W.-J. Ma, Y . Gao, Y .-K. Zhu, Z.-F. Su, W.- L. Ouyang, Y .-C. Zhang, J. Rui, M.-C. Chen, C.-Y . Lu, and J.-W. Pan, Ai-enabled rapid assembly of thousands of defect- free neutral atom arrays with constant-time-overhead, Physical Review Letters135, 060602 (2025), arXiv:2412.14...
- [25]
- [26]
-
[27]
F. Nogrette, H. Labuhn, S. Ravets, D. Barredo, L. Béguin, A. Vernier, T. Lahaye, and A. Browaeys, Single-atom trapping in holographic 2d arrays of microtraps with arbitrary geome- tries, Phys. Rev. X4, 021034 (2014)
work page 2014
- [28]
-
[29]
Y . T. Chew, M. Poitrinal, T. Tomita, S. Kitade, J. Mauricio, K. Ohmori, and S. de Léséleuc, Ultraprecise holographic opti- cal tweezer array, Phys. Rev. A110, 053518 (2024)
work page 2024
-
[30]
M. Schlosser, S. Tichelmann, D. Schäffner, D. O. de Mello, M. Hambach, J. Schütz, and G. Birkl, Scalable multilayer ar- chitecture of assembled single-atom qubit arrays in a three- dimensional talbot tweezer lattice, Physical Review Letters130, 10.1103/physrevlett.130.180601 (2023). 8
-
[31]
H. Kim, W. Lee, H.-g. Lee, H. Jo, Y . Song, and J. Ahn, In situ single-atom array synthesis using dynamic holographic optical tweezers, Nature Communications7, 13317 (2016)
work page 2016
-
[32]
W. Lee, H. Kim, and J. Ahn, Three-dimensional rearrangement of single atoms using actively controlled optical microtraps, Optics Express24, 9816 (2016)
work page 2016
-
[33]
R. W. Gerchberg, A practical algorithm for the determination of phase from image and diffraction plane pictures, Optik35, 237 (1972)
work page 1972
-
[35]
I. H. A. Knottnerus, Y . C. Tseng, A. Urech, R. J. C. Spreeuw, and F. Schreck, Parallel assembly of neutral atom arrays with an SLM using linear phase interpolation, SciPost Phys.19, 118 (2025)
work page 2025
-
[36]
J. You, J. M. Doyle, Z. Liu, S. S. Yu, and A. Periwal, Control of dipolar dynamics by geometrical programming, Phys. Rev. Lett.135, 253002 (2025)
work page 2025
- [37]
-
[38]
S. Bergamini, B. Darquié, M. Jones, L. Jacubowiez, A. Browaeys, and P. Grangier, Holographic generation of mi- crotrap arrays for single atoms by use of a programmable phase modulator, J. Opt. Soc. Am. B21, 1889 (2004)
work page 2004
-
[39]
Y . Cai, S. Yan, Z. Wang, R. Li, Y . Liang, Y . Zhou, X. Li, X. Yu, M. Lei, and B. Yao, Rapid tilted-plane gerchberg-saxton algo- rithm for holographic optical tweezers, Opt. Express28, 12729 (2020)
work page 2020
-
[40]
R. D. Leonardo, F. Ianni, and G. Ruocco, Computer generation of optimal holograms for optical trap arrays, Opt. Express15, 1913 (2007)
work page 1913
-
[41]
H. W. Kuhn, The hungarian method for the assignment prob- lem, Naval Research Logistics Quarterly2, 83 (1955)
work page 1955
- [42]
-
[43]
M. A. Norcia, W. B. Cairncross, K. Barnes, P. Battaglino, A. Brown, M. O. Brown, K. Cassella, C.-A. Chen, R. Coxe, D. Crow, J. Epstein, C. Griger, A. M. W. Jones, H. Kim, J. M. Kindem, J. King, S. S. Kondov, K. Kotru, J. Lauigan, M. Li, M. Lu, E. Megidish, J. Marjanovic, M. McDonald, T. Mittiga, J. A. Muniz, S. Narayanaswami, C. Nishiguchi, R. Notermans, ...
work page 2023
-
[44]
J. A. Muniz, D. Crow, H. Kim, J. M. Kindem, W. B. Cairn- cross, A. Ryou, T. C. Bohdanowicz, C.-A. Chen, Y . Ji, A. M. W. Jones, E. Megidish, C. Nishiguchi, M. Urbanek, L. Wadleigh, T. Wilkason, D. Aasen, K. Barnes, J. M. Bello-Rivas, I. Bloom- field, G. Booth, A. Brown, M. O. Brown, K. Cassella, G. Cowan, J. Epstein, M. Feldkamp, C. Griger, Y . Has- san, ...
work page 2025
-
[45]
D. Kim, A. Keesling, A. Omran, H. Levine, H. Bernien, M. Greiner, M. D. Lukin, and D. R. Englund, Large-scale uni- form optical focus array generation with a phase spatial light modulator, Opt. Lett.44, 3178 (2019)
work page 2019
-
[46]
P. Shor, Fault-tolerant quantum computation, inProceedings of 37th Conference on Foundations of Computer Science(IEEE Comput. Soc. Press, 1996) pp. 56–65, arXiv:9605011 [quant- ph]
work page 1996
-
[47]
Georgescu, 25 years of quantum error correction, Nature Re- views Physics2, 519 (2020)
I. Georgescu, 25 years of quantum error correction, Nature Re- views Physics2, 519 (2020)
work page 2020
-
[48]
B. Zhao, M. Jing, L. Zhang, X. Zhao, Y .-A. Chen, K. Wang, and X. Wang, Retrieving Nonlinear Features from Noisy Quantum States, PRX Quantum5, 020357 (2024)
work page 2024
-
[49]
Correcting quantum errors using a classical code and one additional qubit
T. Araki, J. F. Goodwin, and Z. Cai, Correcting quantum errors using a classical code and one additional qubit, arXiv preprint arXiv:2510.05008 (2025)
work page internal anchor Pith review Pith/arXiv arXiv 2025
- [50]
- [51]
-
[52]
A. M. Childs and W. van Dam, Quantum algorithms for alge- braic problems, Reviews of Modern Physics82, 1 (2010)
work page 2010
-
[53]
A. Gilyén, Y . Su, G. H. Low, and N. Wiebe, Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics, inProceedings of the 51st An- nual ACM SIGACT Symposium on Theory of Computing(ACM, New York, NY , USA, 2019) pp. 193–204, arXiv:1806.01838
- [54]
- [55]
-
[56]
A. Miessen, P. J. Ollitrault, F. Tacchino, and I. Tavernelli, Quan- tum algorithms for quantum dynamics, Nature Computational Science3, 25 (2023)
work page 2023
-
[57]
C. Zhu, L. Zhang, and X. Wang, A quest toward comprehen- sive benchmarking of quantum computing software: Quantum computing, Nature Computational Science5, 363 (2025)
work page 2025
- [58]
-
[59]
M. Cain, Q. Xu, R. King, L. R. B. Picard, H. Levine, M. Endres, J. Preskill, H.-Y . Huang, and D. Bluvstein, Shor’s algorithm is possible with as few as 10,000 reconfigurable atomic qubits, arXiv preprint arXiv:2603.28627 (2026)
work page internal anchor Pith review arXiv 2026
-
[60]
D. Labropoulou, T. Labropoulos, P. Vafeas, and D. M. Manias, On the generalizations of the cauchy-schwarz- bunyakovsky inequality with applications to elasticity (2023), arXiv:2312.03478 [math.FA]
-
[61]
1 + (1−a 2)∆ϕ2 j 6 # +O(∆ϕ 4 j),(S9) sin[(1−a)∆ϕ j] sin(∆ϕj) = (1−a)
J. R. Fienup, Phase retrieval algorithms: a comparison, Appl. Opt.21, 2758 (1982). 9 Supplemental Material for Phase-Stable Hologram Updates for Large-Scale Neutral-Atom Array Reconfiguration I. PROPAGATION MATRIX DERIV ATION We consider an optical system in which a phase-only spatial light modulator (SLM) occupies the front focal plane of a thin lens wit...
work page 1982
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.