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Bipartite entanglement harvesting with multiple detectors
Pith reviewed 2026-05-10 13:41 UTC · model grok-4.3
The pith
A linear chain of detectors harvests entanglement from the quantum vacuum with the amount scaling directly with the number of detectors.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
Using perturbation theory, the leading-order negativity between two multi-detector subsystems is fully determined by a submatrix of the reduced density matrix whose dimension scales only linearly with the number of detectors. For all three-detector configurations and several symmetric four-detector configurations the authors derive closed-form expressions for this negativity and identify the arrangements that maximize it. When the detectors form a linear chain the harvested entanglement grows linearly with the chain length, and increasing the detector count expands the ranges of energy gaps and spatial separations over which entanglement can be extracted.
What carries the argument
The submatrix of the reduced density matrix that encodes the leading-order negativity in perturbation theory, whose linear scaling with detector number permits explicit computation for small numbers of detectors.
If this is right
- In linear chains the harvested negativity increases linearly with the number of detectors.
- Closed analytic expressions for negativity exist for every three-detector arrangement and for several symmetric four-detector arrangements.
- Larger detector numbers widen the intervals of energy gaps and separations that allow entanglement extraction.
- Specific spatial placements can be ranked by the negativity they produce.
Where Pith is reading between the lines
- The linear scaling suggests that entanglement yield can be increased simply by extending a one-dimensional detector array without exponential growth in computational cost.
- The same submatrix method could be applied to time-dependent or curved-space backgrounds to test whether linear scaling persists beyond flat Minkowski spacetime.
- Optimal configurations identified here provide concrete targets for analog simulations in trapped-ion or superconducting-circuit systems.
Load-bearing premise
The leading-order perturbative contribution to negativity remains accurate and higher-order terms do not change which spatial arrangements maximize the harvested entanglement.
What would settle it
A direct numerical or experimental evaluation of the full negativity for a linear chain of four detectors that shows clear deviation from linear growth with detector number would falsify the scaling claim.
Figures
read the original abstract
We study bipartite entanglement harvesting from the quantum vacuum of a massless scalar field between two subsystems, each composed of a finite number of Unruh-DeWitt detectors. Using perturbation theory, we show that the leading-order negativity is fully determined by a submatrix of the reduced density matrix, with the submatrix dimension scaling only linearly with the number of detectors. Within this framework, we analyze how the detectors' spatial arrangement influences harvesting. For all three-detector configurations and several symmetric four-detector configurations, we derive analytic expressions for the negativity and identify the configurations that maximize it. For a linear chain, we find that the harvested entanglement scales linearly with the number of detectors. These results clarify how to arrange multiple detectors to optimize harvesting and show that increasing their number broadens the ranges of energy gaps and separations over which entanglement can be extracted from the field.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript studies bipartite entanglement harvesting from the vacuum of a massless scalar field using two subsystems, each with a finite number of Unruh-DeWitt detectors. Employing perturbation theory, it shows that the leading-order negativity is fully determined by a submatrix of the reduced density matrix whose dimension scales linearly with the total detector number. Analytic expressions for negativity are derived for all three-detector configurations and several symmetric four-detector configurations, with optimal arrangements identified. For linear chains, the harvested entanglement scales linearly with detector number, and increasing the number of detectors is shown to broaden the ranges of energy gaps and separations permitting entanglement extraction.
Significance. If the leading-order perturbative results remain valid in the reported regimes, the work provides concrete guidance on detector arrangements that optimize entanglement harvesting and demonstrates a practical advantage to using larger numbers of detectors. The linear scaling for chains and the broadening of harvestable parameter space are notable findings. The submatrix construction that keeps computational cost linear in N is a technical strength, as are the closed-form expressions for small detector counts, which support reproducibility.
major comments (1)
- [multi-detector analysis and linear-chain results] The linear scaling of negativity with detector number for the linear chain (abstract and the multi-detector analysis section) is obtained entirely at leading order in the Dyson expansion. The paper states that the leading-order negativity is fixed by a submatrix whose dimension grows only linearly with N, but supplies no explicit bound on O(λ³) or higher contributions to the reduced density matrix, nor any numerical check of next-order terms, for the coupling strengths, gaps, and separations at which the scaling and broadening are claimed. This assumption is load-bearing for the central result that larger N broadens the harvestable ranges.
minor comments (2)
- [Abstract] The abstract refers to 'several symmetric four-detector configurations' without enumerating them; listing the specific geometries considered would improve clarity.
- [Methods/perturbation-theory setup] Notation for the detector response functions and field correlators could be cross-referenced more explicitly to the submatrix construction to aid readers following the linear-scaling argument.
Simulated Author's Rebuttal
We thank the referee for their positive evaluation of the manuscript and for identifying this important point concerning the perturbative validity of our results. We address the major comment below.
read point-by-point responses
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Referee: The linear scaling of negativity with detector number for the linear chain (abstract and the multi-detector analysis section) is obtained entirely at leading order in the Dyson expansion. The paper states that the leading-order negativity is fixed by a submatrix whose dimension grows only linearly with N, but supplies no explicit bound on O(λ³) or higher contributions to the reduced density matrix, nor any numerical check of next-order terms, for the coupling strengths, gaps, and separations at which the scaling and broadening are claimed. This assumption is load-bearing for the central result that larger N broadens the harvestable ranges.
Authors: We agree that the linear scaling of negativity with detector number and the broadening of harvestable ranges are demonstrated strictly at leading order in the Dyson expansion, as stated throughout the manuscript. The submatrix construction correctly isolates the O(λ²) contributions that determine the leading-order negativity, enabling the linear-in-N scaling to be obtained analytically for chains. We do not supply explicit bounds on O(λ³) or higher terms, nor numerical comparisons with next-order corrections, for the specific parameter regimes considered. In the revised manuscript we will add a dedicated paragraph in the conclusions section that explicitly states the weak-coupling assumption underlying all results, notes that higher-order contributions are neglected, and clarifies that the reported scaling and broadening hold within the leading-order perturbative regime. This addition will make the scope of the claims more precise without altering the technical content of the leading-order analysis. revision: partial
Circularity Check
No circularity: direct perturbative derivation from field correlators
full rationale
The paper computes leading-order negativity via the Dyson expansion of the time-evolution operator for multiple Unruh-DeWitt detectors coupled to a massless scalar field. The claim that negativity is fixed by a submatrix whose size grows linearly with detector number follows directly from the first-order structure of the reduced density matrix elements (which involve only pairwise field correlators between detectors). Analytic expressions for three- and four-detector configurations and the reported linear scaling for linear chains are obtained by explicit evaluation of these correlators for chosen geometries; no parameters are fitted, no results are renamed as predictions, and no self-citations supply load-bearing uniqueness theorems or ansatzes. The derivation chain is therefore self-contained and does not reduce to its inputs by construction.
Axiom & Free-Parameter Ledger
axioms (2)
- domain assumption Perturbation theory to leading order suffices to compute the negativity between detector subsystems
- domain assumption Detectors are weakly coupled to the field and remain in the perturbative regime
Reference graph
Works this paper leans on
-
[1]
Symmetric2 + 2partition For the 2 + 2 partition, we get the ˜ρ1 block according to Eq. (31) ˜ρ1 = C∗ BB X † BA XBA CAA = P4 C43 X ∗ 42 X ∗ 41 C ∗ 43 P3 X ∗ 32 X ∗ 31 X42 X32 P2 C ∗ 21 X41 X31 C21 P1 ,(45) where, for identical detectors, we setP 4 =P 3 =P 2 = P1 ≡P. As in the three-detector case, the eigenvalue problem can be simplified by shifti...
-
[2]
Finally, we emphasize that the number of detectors has a significant impact on the magnitude of the leading- order negativity
Maximal entanglement is obtained when detectors belonging to different subsystems are placed in close proximity, while detectors within the same subsys- tem are maximally separated. Finally, we emphasize that the number of detectors has a significant impact on the magnitude of the leading- order negativity. This is evident when comparing the optimal confi...
-
[3]
Asymmetric3 + 1partition For the 3 + 1 partition, we get the ˜ρ1 block according to Eq. (31): ˜ρ1 = C∗ BB X † BA XBA CAA = P4 X ∗ 43 X ∗ 42 X ∗ 41 X43 P3 C ∗ 32 C ∗ 31 X42 C32 P2 C ∗ 21 X41 C31 C21 P1 .(53) For an asymmetric partition, we consider a setup with two degrees of freedom in the spatial configuration. The setup is shown in Fig. 9, whe...
-
[4]
In particular, we compute the leading-order neg- ativity for different spatial arrangements as a function of the distancelbetween subsystemsAandB
Varying the spatial scale of the optimal arrangements In this brief subsection we explore how entanglement changes when we rescale the distances between the de- tectors. In particular, we compute the leading-order neg- ativity for different spatial arrangements as a function of the distancelbetween subsystemsAandB. In Fig. 10 we compare the two-detector c...
-
[5]
(36) by impos- ing a hard cutoff, χ(t) = 1√ 2πσ2 e− t2 2σ2 Θ(T− |t|), where the tails are removed atT= 5σby multiplication with the Heaviside step function Θ
Truncated Gaussian switching The simplest way to enforce strict compact support is to truncate the Gaussian switching in Eq. (36) by impos- ing a hard cutoff, χ(t) = 1√ 2πσ2 e− t2 2σ2 Θ(T− |t|), where the tails are removed atT= 5σby multiplication with the Heaviside step function Θ. For a clearer com- parison, we do not renormalize the truncated Gaussian ...
-
[6]
Compactified polynomial switching In this subsection we introduce a different family of compactly supported polynomial functions with differen- tiability classC δ−1 (see [56]), χ(δ)(t) =N norm 1− t2 T 2 δ Θ(T− |t|).(55) The parameterδcontrols the differentiability at the boundaryt=±T: largerδmeans the cutoff is smoother. In our study, we mainly consider t...
2024
-
[7]
Witten, Rev
E. Witten, Rev. Mod. Phys.90, 045003 (2018)
2018
-
[8]
Reeh and S
H. Reeh and S. Schlieder, Il Nuovo Cimento (1955-1965) 22, 1051 (1961)
1955
-
[9]
S. J. Summers and R. Werner, J. Math. Phys.28, 2440 (1987)
1987
-
[10]
Preskill, inProceedings of the International Sympo- sium on Black Holes, Membranes, Wormholes and Su- perstrings, S
J. Preskill, inProceedings of the International Sympo- sium on Black Holes, Membranes, Wormholes and Su- perstrings, S. Kalara and DV Nanopoulos, eds.(World Scientific, Singapore, 1993) pp(World Scientific, 1992) pp. 22–39
1993
-
[11]
S. W. Hawking, Phys. Rev. D72, 084013 (2005)
2005
-
[12]
S. L. Braunstein, S. Pirandola, and K. ˙Zyczkowski, Phys. Rev. Lett.110, 101301 (2013)
2013
- [13]
- [14]
- [15]
-
[16]
Mart´ ın-Mart´ ınez, E
E. Mart´ ın-Mart´ ınez, E. G. Brown, W. Donnelly, and A. Kempf, Phys. Rev. A88, 052310 (2013)
2013
-
[17]
Yamaguchi, A
K. Yamaguchi, A. Ahmadzadegan, P. Simidzija, A. Kempf, and E. Mart´ ın-Mart´ ınez, Phys. Rev. D101, 105009 (2020)
2020
-
[18]
Hotta, Journal of the Physical Society of Japan78, 034001 (2009)
M. Hotta, Journal of the Physical Society of Japan78, 034001 (2009)
2009
-
[19]
S. Hollands and K. Sanders,34(2017), 10.1007/978-3- 319-94902-4, arXiv:1702.04924 [quant-ph]
- [20]
-
[21]
L. van Luijk, A. Stottmeister, R. F. Werner, and H. Wilming, Commun. Math. Phys.406, 296 (2025), arXiv:2409.17739 [quant-ph]
-
[22]
Valentini, Phys
A. Valentini, Phys. Lett. A153, 321 (1991)
1991
-
[23]
Reznik, A
B. Reznik, A. Retzker, and J. Silman, Phys. Rev. A71, 042104 (2005)
2005
-
[24]
Silman and B
J. Silman and B. Reznik, Phys. Rev. A75, 052307 (2007)
2007
-
[25]
Pozas-Kerstjens and E
A. Pozas-Kerstjens and E. Mart´ ın-Mart´ ınez, Phys. Rev. D92, 064042 (2015)
2015
-
[26]
Pozas-Kerstjens and E
A. Pozas-Kerstjens and E. Mart´ ın-Mart´ ınez, Phys. Rev. D94, 064074 (2016)
2016
-
[27]
Salton, R
G. Salton, R. B. Mann, and N. C. Menicucci, New J. Phys.17, 035001 (2015)
2015
-
[28]
K. K. Ng, L. Hodgkinson, J. Louko, R. B. Mann, and E. Mart´ ın-Mart´ ınez, Phys. Rev. D90, 064003 (2014)
2014
-
[29]
Bueley, L
K. Bueley, L. Huang, K. Gallock-Yoshimura, and R. B. Mann, Phys. Rev. D106, 025010 (2022)
2022
-
[30]
Gallock-Yoshimura, E
K. Gallock-Yoshimura, E. Tjoa, and R. B. Mann, Phys. Rev. D104, 025001 (2021)
2021
-
[31]
J. Foo, R. B. Mann, and M. Zych, Phys. Rev. D103, 065013 (2021)
2021
-
[32]
L. J. Henderson, R. A. Hennigar, R. B. Mann, A. R. H. Smith, and J. Zhang, J. High Energy Phys.2019, 178 (2019)
2019
-
[33]
L. J. Henderson and N. C. Menicucci, Phys. Rev. D102, 125026 (2020)
2020
-
[34]
M. P. G. Robbins, L. J. Henderson, and R. B. Mann, Class. Quantum Gravity39, 02LT01 (2021)
2021
-
[35]
T. R. Perche, C. Lima, and E. Mart´ ın-Mart´ ınez, Phys. Rev. D105, 065016 (2022)
2022
-
[36]
T. R. Perche, B. Ragula, and E. Mart´ ın-Mart´ ınez, Phys. Rev. D108, 085025 (2023)
2023
-
[37]
Tjoa and E
E. Tjoa and E. Mart´ ın-Mart´ ınez, Phys. Rev. D104, 125005 (2021)
2021
-
[38]
L. J. Henderson, S. Y. Ding, and R. B. Mann, AVS Quantum Sci.4, 014402 (2022)
2022
-
[39]
J. G. A. Carib´ e, R. H. Jonsson, M. Casals, A. Kempf, and E. Mart´ ın-Mart´ ınez, Phys. Rev. D108, 025016 (2023)
2023
-
[40]
A. Teixid´ o-Bonfill, X. Dai, A. Lupascu, and E. Mart´ ın- Mart´ ınez, (2025), arXiv:2505.01516 [quant-ph]
- [41]
-
[42]
C. Gooding, A. Sachs, R. B. Mann, and S. Weinfurt- ner, New J. Phys.26, 105001 (2024), arXiv:2308.07892 [quant-ph]
- [43]
-
[44]
Mendez-Avalos, L
D. Mendez-Avalos, L. J. Henderson, K. Gallock- Yoshimura, and R. B. Mann, Gen. Relativ. Gravit.54, 87 (2022)
2022
-
[45]
I. J. Membrere, K. Gallock-Yoshimura, L. J. Henderson, and R. B. Mann, Adv. Quantum Technol.6(2023)
2023
-
[46]
S. Kukita and Y. Nambu, Entropy19, 449 (2017), arXiv:1708.01359 [gr-qc]
-
[47]
Gurvits, in35th annual ACM symposium on Theory of computing(2003)
L. Gurvits, in35th annual ACM symposium on Theory of computing(2003)
2003
-
[48]
S. Gharibian, Quant. Inf. Comput.10, 0343 (2010), arXiv:0810.4507 [quant-ph]
-
[49]
Vidal and R
G. Vidal and R. F. Werner, Phys. Rev. A65, 032314 (2002)
2002
- [50]
-
[51]
M. Horodecki, P. Horodecki, and R. Horodecki, Phys. Lett. A223, 1 (1996), arXiv:quant-ph/9605038
-
[52]
Audenaert, M
K. Audenaert, M. B. Plenio, and J. Eisert, Phys. Rev. Lett.90, 027901 (2003)
2003
-
[53]
M. B. Plenio and S. Virmani, Quant. Inf. Comput.7, 001 (2007)
2007
-
[54]
M. Horodecki, P. Horodecki, and R. Horodecki, Phys. Rev. Lett.80, 5239 (1998), arXiv:quant-ph/9801069
- [55]
-
[56]
Mart´ ın-Mart´ ınez, Phys
E. Mart´ ın-Mart´ ınez, Phys. Rev. D92, 104019 (2015)
2015
-
[57]
de Ram´ on, M
J. de Ram´ on, M. Papageorgiou, and E. Mart´ ın-Mart´ ınez, Phys. Rev. D108, 045015 (2023). 24
2023
-
[58]
E. Tjoa and E. Mart´ ın-Mart´ ınez, Phys. Rev. D104, 125005 (2021), arXiv:2109.11561 [quant-ph]
- [59]
-
[60]
Maeso-Garc´ ıa, T
H. Maeso-Garc´ ıa, T. R. Perche, and E. Mart´ ın-Mart´ ınez, Phys. Rev. D106, 045014 (2022)
2022
-
[61]
Mendez-Avalos, L
D. Mendez-Avalos, L. J. Henderson, K. Gallock- Yoshimura, and R. B. Mann, General Relativity and Gravitation54, 87 (2022)
2022
-
[62]
Agullo, B
I. Agullo, B. Bonga, P. Ribes-Metidieri, D. Kranas, and S. Nadal-Gisbert, Phys. Rev. D108, 085005 (2023)
2023
-
[63]
M. Morote-Balboa and T. R. Perche, (2026), arXiv:2604.06303 [quant-ph]
work page internal anchor Pith review Pith/arXiv arXiv 2026
-
[64]
Simidzija and E
P. Simidzija and E. Mart´ ın-Mart´ ınez, Phys. Rev. D96, 065008 (2017)
2017
-
[65]
Polo-G´ omez and E
J. Polo-G´ omez and E. Mart´ ın-Mart´ ınez, Phys. Rev. D 109, 045014 (2024)
2024
-
[66]
Bipartite entanglement harvesting with multiple detectors (mathematica notebooks),
S. Salomaa, “Bipartite entanglement harvesting with multiple detectors (mathematica notebooks),” (2026)
2026
-
[67]
R. A. Horn and C. R. Johnson,Matrix Analysis, 2nd ed. (Cambridge University Press, 2013)
2013
-
[68]
J. J. Sakurai and J. Napolitano,Modern Quantum Me- chanics, 2nd ed. (Cambridge University Press, 2017)
2017
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