REVIEW 4 major objections 4 minor 1 cited by
Recirculating Quantum Photonic Networks for Fast Deterministic Quantum Information Processing
T0 review · 4 major / 4 minor · reviewed 2026-08-03 · deepseek-v4-flash
Pith's one-line read Recirculating all photonic qubits at once, rather than decomposing into gates, speeds up deterministic photonic quantum information processing.
desk verdict A genuinely new architecture with a clean analytic lower bound and open code; the main caveat is the lossless assumption behind the quantitative speedups, which is acknowledged but should be stress-tested before the headline factors are trusted. 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 central object is the RQPN Hamiltonian, which couples all cavity modes through a real symmetric coupling matrix C derived from a linear scattering network, together with continuously controllable cavity detunings and waveguide couplings, and a nonlinear Hamiltonian from self-phase modulation (an intensity-dependent phase shift with rate χ3) or Jaynes–Cummings coupling to two-level emitters (with rate g). The paper proves that C can realize any real symmetric coupling, enabling all-to-all interaction, and then uses numerical optimization over piecewise-constant control signals and time-bin durations to minimize the process duration while keeping infidelity below a threshold. This machiner
What would settle it
Take the same optimized control signals and add photon loss and dephasing to the master equation, e.g., Lindblad decay with a finite cavity loss rate, then recompute the infidelity and the shortest achievable duration; alternatively, build or simulate an RQPN with realistic fast-tunable cavities and measure the full end-to-end time including capture, recirculation, release, and ancilla reset to see whether the claimed speedup survives.
Extended reading notes
Core claim
The paper's core claim is that a recirculating quantum photonic network with all-to-all connectivity enables direct, time-optimized implementations of multi-photon quantum operations, bypassing the overhead of decompositions into single- and two-qubit gates. For the three-qubit Toffoli gate with dual-rail encoding and self-phase-modulation nonlinearity, the authors find a numerically optimized implementation with duration 2.00/χ3, faster than the best qubit-qutrit CZ decomposition lower bound of 2.32/χ3 and more than twice as fast as qubit-qubit CZ decompositions. For measurement-free correction of single-photon loss using a four-photon bosonic encoding, they find a two-step SPM-based repeat
Load-bearing premise
The reported durations assume a lossless, decoherence-free evolution inside the recirculating configuration, with negligible time spent on capture, release, ancilla reset, and propagation through the mixing circuit; if realistic losses or finite propagation times are significant, the optimized solutions and the end-to-end speedups could change.
Editorial extensions
If this is right
- If the reported durations hold, a photonic processor can implement a three-qubit Toffoli gate without decomposing it into six two-qubit gates, cutting duration by more than a factor of two.
- Measurement-free correction of single-photon loss, a key operation for photonic quantum repeaters, can be performed in time 8.90/χ3 with only three linear and three nonlinear components, a substantial reduction from the 240 linear and 160 nonlinear components of a neural-network-based proposal.
- Because durations are quoted in units of inverse nonlinear rate, a factor-of-seven time improvement translates into a factor-of-seven relaxation in the required nonlinear interaction strength relative to decoherence.
- The same reprogrammable hardware can be reconfigured for different tasks by changing the control signals, without altering the physical circuit.
- For two-level-emitter nonlinearities, the ratio of repeater duration to CZ-gate duration is only 4.6, suggesting that direct multi-photon transformations are particularly advantageous in that platform.
Reading between the lines
- A natural extension, not pursued in the paper, is to include photon loss, dephasing, and finite propagation delays in the optimization itself; the authors note this as future work, and such an optimization would show whether the no-loss trajectories remain near-optimal when realistic error channels are added.
- The architecture principle likely generalizes to other multi-photon tasks, such as syndrome-extraction circuits or multi-qubit gates with more than three qubits, because the all-to-all coupling allows direct unitary synthesis; however, optimization complexity and hardware bandwidth constraints would need to be assessed.
- The comparison with earlier proposals assumes the same nonlinear interaction rate per element; if different material platforms have different practical rates of χ3 or g, the ranking in wall-clock time could differ from the dimensionless comparison presented here.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper introduces a recirculating quantum photonic network (RQPN) consisting of dynamically controlled nonlinear cavities connected through a linear mixing circuit, and uses numerical optimal control to minimize the duration of multi-photon quantum information processing tasks. Two applications are treated: a three-qubit Toffoli gate implemented with self-phase modulation (2.00/χ3, Sec. III B) and a measurement-free single-photon-loss correction repeater implemented with SPM (8.90/χ3, Sec. IV B) or with two-level emitters (18.31/g, Sec. IV C). The reported durations are claimed to be substantially shorter than those of prior architectural proposals, with large reductions in component counts. The central quantitative claims are obtained from lossless, decoherence-free, Markovian simulations of the recirculating configuration, with perfect capture/release and excluded ancilla re-initialization time.
Significance. If the reported durations remain valid under realistic conditions, the RQPN idea would be a valuable architectural contribution: processing all qubits simultaneously rather than decomposing into single- and two-qubit gates, and using a small, reconfigurable network, could reduce the temporal overhead of photonic quantum gates and error correction. The paper contains some genuinely useful elements: a self-contained analytic lower bound for the CZ-gate duration with SPM (Supplement SIV A), a proof that the coupling matrix can be any real symmetric matrix (Supplement SII), and an open-source implementation of the numerical optimizations with detailed hyperparameters. These strengths make the work reproducible at the level of the idealized model. However, the headline speedups are all based on a lossless unitary model and on durations that exclude capture/release and ancilla-reset overheads. Because the stated motivation is precisely to beat decoherence and loss, the practical relevance of the quantitative claims depends on whether the optimized controls remain advantageous in a loss-aware setting. The paper acknowledges this limitation only in passing and in the conclusion, while the
major comments (4)
- [Sec. II B and Table I] The central quantitative claims are durations computed under the explicit assumption 'we neglect loss and decoherence effects from the surrounding environment.' This assumption is load-bearing for the headline speedups in Table I. A loss-aware re-optimization could change the optimal controls, and the time-integrated photon-loss probability could be larger for the multi-photon excursions used here (e.g., three-photon occupations in the Toffoli gate, four-photon states in the repeater). The manuscript should either include a robustness analysis with finite cavity loss and dephasing, or clearly state that the reported durations are ideal-model figures of merit that do not yet translate into experimentally actionable speedups.
- [Sec. IV B, Eqs. (13)-(14), Fig. 3(b)] The reported repeater duration T = 8.90/χ3 is the sum of the two optimized recirculating steps (5.09/χ3 + 3.81/χ3), but it excludes the time required to empty and re-initialize the ancilla cavity between steps, as well as all input capture and output release times. Since the transformation in Eq. (13) requires the ancilla to start in |1_3> and step 2 must again start from |1_3>, the actual end-to-end process includes ancilla reset operations whose duration is not accounted for. The claim that the repeater is 7.1× faster than Ref. [25] should be qualified to the recirculating phase only, or the overheads should be quantified and included.
- [Sec. II, Eq. (1); Fig. S6] The SLH derivation assumes a strict separation of time scales: the interaction bandwidth Ω_int and inverse propagation time 1/T_prop must be much larger than κ_m(t), δ_m(t), Γ_NL, and the modulation bandwidth Ω_mod. The optimized controls for the Toffoli gate use D_c/2 = 75/χ3 and K = 150/χ3 with N_bin = 80 bins and T = 2.00/χ3, implying control rates and bin-to-bin changes of order tens to hundreds of χ3. The paper does not check whether these optima satisfy the Markovian and infinitesimal-propagation assumptions. This is not just a formal point: fast switching and finite propagation delays in the mixing circuit could lead to non-Markovian corrections that modify Eq. (1). Please add a consistency check or, at minimum, state the parameter regime in which the reported solutions are physically valid.
- [Sec. IV D, Table I] The comparison with Ref. [24] reports a 4.5× speedup, but the RQPN duration is in units of 1/χ3 while the Ref. [24] duration is in units of 1/χ2. These are different nonlinear processes and there is no universal relation between χ2 and χ3; a direct 'speedup factor' across the two platforms is not meaningful unless a platform-specific comparison is intended. The comparison with Ref. [25] (SPM vs SPM) is cleaner, but even there the baseline was optimized under a different, fixed-depth constraint. The text acknowledges that 'comparisons require care,' but Table I and the abstract nonetheless state numerical factors. I recommend rephrasing these as duration ratios in units of the respective inverse nonlinear rates, with the model assumptions spelled out.
minor comments (4)
- [Sec. V, 'TLEs'] The paragraph on experimental platforms mentions that bulk χ(2) reaches about 1 MHz, a factor of six smaller than the smallest intrinsic loss rate. This is a useful reality check, but it is disconnected from the idealized durations reported earlier. Consider moving this discussion earlier or adding a sentence that connects the ideal-model durations to the cooperativity requirements.
- [Sec. IV D, text after Eq. (16)] The sentence 'The resulting process duration is T=18.31/g, which is 2.2 and 3.4 times faster than the reported implementations in Refs. [24] and [25]' uses 'faster' loosely; durations are shorter, but the comparison with Ref. [24] again mixes g and χ2.
- [Fig. S6 caption] The caption says 'time evolution of the RQPN state |ψ(t)> for each logical input (c)' while panel (c) is the coupling matrix; the panel label should be (d).
- [Sec. IV B, Eq. (13)] In the first line of Eq. (13), the no-loss case is written as |C> ⊗ |1_3> → |C> ⊗ |1_3>, but the ancilla should ideally remain unchanged in the no-loss case; it is fine, but the notation could be clarified to indicate that the ancilla is left in |1_3> and is then reset before step 2, as described in the text.
Circularity Check
No significant circularity found: the reported durations are optimized existence results against externally defined target unitaries, not fits renamed as predictions.
full rationale
The paper's central claims are numerical existence/optimality results: for fixed target unitaries (three-qubit Toffoli in Eq. (6), repeater transformations in Eqs. (12)–(14)), it optimizes piecewise-constant controls (Eqs. (7)–(8)) against an infidelity objective (Eq. (9)) and reports the shortest total duration for which I ≤ I_th is reached. The targets are externally defined standard gates/correction maps; they are not constructed from the optimized durations or from RQPN parameters. Thus 2.00/χ3, 8.90/χ3, and 18.31/g are outputs of a numerical search, not fitted inputs relabeled as predictions. The lower bounds in Sec. SIV are derived in-paper from the SPM phase rate n(n−1)χ3 and the decomposition structure; they are not imported as a black-box uniqueness theorem. Comparisons with Refs. [24] and [25] use published duration and component counts from prior papers that share some authors, but those numbers are used as external benchmarks, not as inputs that determine the RQPN controls or durations. The explicit idealizations—neglect of loss/decoherence, neglect of capture/release durations, and Markovian/infinitesimal-propagation assumptions—are clearly stated limitations affecting external validity, not circular reductions. No step was found in which a predicted quantity equals its input by construction.
Assumptions & free parameters
free parameters (6)
- Optimized control waveforms {kappa_m(t), delta^c_m(t), delta^e_m(t)} =
Not listed numerically; shown in figures S3-S9
- Coupling matrix C off-diagonal elements =
Trained for CZ and Toffoli; fixed to 1 for repeater
- Control amplitude bounds D_c, K, D_e =
E.g., K=150/chi3 and D_c/2=75/chi3 for Toffoli; K=10/chi3 for repeater
- Time-bin duration bounds tau_min, tau_max and fixed total duration =
E.g., T=2.00/chi3 for Toffoli; step durations 5.09/chi3 and 3.81/chi3; T=18.31/g for TLE repeater
- Smoothness penalty weights w_smooth =
E.g., 0.006 and 0.015 for SPM repeater step 1
- Infidelity threshold I_th =
0.1%, 0.3%, 0.05%
assumptions (6)
- domain assumption Loss and decoherence are neglected in all simulations
- domain assumption SLH Markovian, frequency-independent coupling and infinitesimal propagation time
- domain assumption Perfect and instantaneous capture/release and ancilla reset
- domain assumption SPM and Jaynes-Cummings Hamiltonians exactly describe the nonlinear dynamics
- standard math Linear optical operations can be performed instantaneously in the lower-bound proofs
- domain assumption Single-photon-loss error model and bosonic encoding of Eq. (11)
Cite this review
Pith. "Pith review of Recirculating Quantum Photonic Networks for Fast Deterministic Quantum Information Processing." pith.science (2026). https://pith.science/paper/TJCQWFIW
@misc{pith2026260211033,
author = {Pith},
title = {Pith review of: Recirculating Quantum Photonic Networks for Fast Deterministic Quantum Information Processing},
year = {2026},
howpublished = {\url{https://pith.science/paper/TJCQWFIW}},
note = {Machine review of arXiv:2602.11033}
}
read the original abstract
A fundamental challenge in photonics-based deterministic quantum information processing is to realize key transformations on time scales shorter than those of detrimental decoherence and loss mechanisms. This challenge has been addressed through device-focused approaches that aim to increase nonlinear interactions relative to decoherence rates. In this work, we adopt a complementary architecture-focused approach by proposing a recirculating quantum photonic network (RQPN) that minimizes the duration of quantum information processing tasks, thereby reducing the requirements on nonlinear interaction rates. The RQPN consists of a network of all-to-all connected nonlinear cavities with dynamically controlled waveguide couplings, and it processes information by capturing a photonic input state, recirculating photons between the cavities, and releasing a photonic output state. We demonstrate the RQPN's architectural advantage through two examples: first, we show that processing all qubits simultaneously yields faster operations than single- and two-qubit decompositions of the three-qubit Toffoli gate. Second, we demonstrate implementations of a measurement-free correction for single-photon loss, achieving up to seven-fold speedups and significantly improved hardware efficiency relative to state-of-the-art architecture proposals. Our work shows that a single hardware-efficient recirculating architecture substantially reduces the temporal overhead of multi-qubit gates and quantum error correction, thereby lowering the barrier to experimental realizations of deterministic photonic quantum information processing.
Figures
Figures from the paper (2 more)
Forward citations
Cited by 1 Pith paper
-
Implementation of distillation protocols using a recirculating bricks mesh network
A recirculating bricks mesh photonic processor is proposed as a platform to realize multiple quantum distillation protocols with low optical depth.
Reference graph
Works this paper leans on
-
[25]
Krastanov, M
S. Krastanov, M. Heuck, J. H. Shapiro, P. Narang, D. R. Englund, and K. Jacobs, Nature Communications12, 191 (2021)
2021
-
[24]
Y. Ota, D. Takamiya, R. Ohta, H. Takagi, N. Kuma- gai, S. Iwamoto, and Y. Arakawa, Applied Physics Letters 112, 093101 (2018)
2018
-
[1]
H. J. Kimble, Nature453, 1023 (2008)
2008
-
[2]
M. A. Nielsen and I. L. Chuang,Quantum Computation and Quantum Information(Cambridge University Press, 2010)
2010
-
[3]
P. Kok, W. J. Munro, K. Nemoto, T. C. Ralph, J. P. Dowling, and G. J. Milburn, Rev. Mod. Phys.79, 135 9 (2007)
2007
-
[4]
Knill, R
E. Knill, R. Laflamme, and G. J. Milburn, Nature409, 46 (2001)
2001
-
[5]
Bartolucci, P
S. Bartolucci, P. Birchall, H. Bomb ´ ın, H. Cable, C. Daw- son, M. Gimeno-Segovia, E. Johnston, K. Kieling, N. Nick- erson, M. Pant, F. Pastawski, T. Rudolph, and C. Spar- row, Nature Communications14, 912 (2023)
2023
-
[6]
J. H. Shapiro, Phys. Rev. A73, 062305 (2006)
2006
Show all 81 references
-
[7]
Gea-Banacloche, Phys
J. Gea-Banacloche, Phys. Rev. A81, 043823 (2010)
2010
-
[8]
S. Xu, E. Rephaeli, and S. Fan, Phys. Rev. Lett.111, 223602 (2013)
2013
-
[9]
Nysteen, D
A. Nysteen, D. P. S. McCutcheon, M. Heuck, J. Mørk, and D. R. Englund, Phys. Rev. A95, 062304 (2017)
2017
-
[10]
Photon-loss correc- tion is also crucial in quantum communication [56]
and a major obstacle for scalable photonic quan- tum computing architectures [5, 55]. Photon-loss correc- tion is also crucial in quantum communication [56]. In the following, we correct for single-photon loss using the RQPN. We consider the following multi-photon bosonic enco...
-
[11]
Slussarenko and G
S. Slussarenko and G. J. Pryde, Applied Physics Reviews 6, 041303 (2019)
2019
-
[12]
K. Xia, M. Johnsson, P. L. Knight, and J. Twamley, Phys. Rev. Lett.116, 023601 (2016)
2016
-
[13]
Viswanathan and J
B. Viswanathan and J. Gea-Banacloche, Phys. Rev. A 97, 032314 (2018)
2018
-
[14]
Levy-Yeyati, C
T. Levy-Yeyati, C. Vega, T. Ramos, and A. Gonz´ alez- Tudela, PRX Quantum6, 010342 (2025)
2025
-
[15]
D. J. Brod and J. Combes, Phys. Rev. Lett.117, 080502 (2016)
2016
-
[16]
T. C. Ralph, I. S¨ ollner, S. Mahmoodian, A. G. White, and P. Lodahl, Phys. Rev. Lett.114, 173603 (2015)
2015
-
[17]
F. Yang, M. M. Lund, T. Pohl, P. Lodahl, and K. Mølmer, Phys. Rev. Lett.128, 213603 (2022)
2022
-
[18]
Heuck, K
M. Heuck, K. Jacobs, and D. R. Englund, Phys. Rev. A 101, 042322 (2020)
2020
-
[19]
Heuck, K
M. Heuck, K. Jacobs, and D. R. Englund, Phys. Rev. Lett.124, 160501 (2020)
2020
-
[20]
Krastanov, K
S. Krastanov, K. Jacobs, G. Gilbert, D. R. Englund, and M. Heuck, npj Quantum Information8, 103 (2022)
2022
-
[21]
R. J. Thompson, G. Rempe, and H. J. Kimble, Phys. Rev. Lett.68, 1132 (1992)
1992
-
[22]
Hennessy, A
K. Hennessy, A. Badolato, M. Winger, D. Gerace, M. Atat¨ ure, S. Gulde, S. F¨ alt, E. L. Hu, and A. Imamo˘ glu, Nature445, 896 (2007)
2007
-
[23]
Lodahl, Quantum Science and Technology3, 013001 (2017)
P. Lodahl, Quantum Science and Technology3, 013001 (2017)
2017
-
[26]
G. R. Steinbrecher, J. P. Olson, D. Englund, and J. Car- olan, npj Quantum Information5, 60 (2019)
2019
-
[27]
Ewaniuk, J
J. Ewaniuk, J. Carolan, B. J. Shastri, and N. Rotenberg, Advanced Quantum Technologies6, 2200125 (2023)
2023
-
[28]
J. R. Basani, M. Y. Niu, and E. Waks, npj Quantum Information11, 142 (2025)
2025
-
[29]
Tanaka, J
Y. Tanaka, J. Upham, T. Nagashima, T. Sugiya, T. Asano, and S. Noda, Nature Materials6, 862 (2007)
2007
-
[30]
Q. Xu, P. Dong, and M. Lipson, Nature Physics3, 406 (2007)
2007
-
[31]
Nakadai, T
M. Nakadai, T. Asano, and S. Noda, Nature Photonics 16, 113 (2022)
2022
-
[32]
Zhang, C
M. Zhang, C. Wang, Y. Hu, A. Shams-Ansari, T. Ren, S. Fan, and M. Lonˇ car, Nature Photonics13, 36 (2019)
2019
-
[33]
Heuck, inConference on Lasers and Electro- Optics/Europe (CLEO/Europe 2023) and European Quan- tum Electronics Conference (EQEC 2023)(Optica Pub- lishing Group, 2023) p
M. Heuck, inConference on Lasers and Electro- Optics/Europe (CLEO/Europe 2023) and European Quan- tum Electronics Conference (EQEC 2023)(Optica Pub- lishing Group, 2023) p. ci 1 5
2023
-
[34]
I. L. Chuang, D. W. Leung, and Y. Yamamoto, Phys. Rev. A56, 1114 (1997)
1997
-
[35]
M. H. Michael, M. Silveri, R. T. Brierley, V. V. Albert, J. Salmilehto, L. Jiang, and S. M. Girvin, Phys. Rev. X6, 031006 (2016)
2016
-
[36]
Gough and M
J. Gough and M. R. James, Communications in Mathe- matical Physics287, 1109 (2009)
2009
-
[37]
Gough and M
J. Gough and M. R. James, IEEE Transactions on Au- tomatic Control54, 2530 (2009)
2009
-
[38]
Combes, J
J. Combes, J. Kerckhoff, and M. Sarovar, Advances in Physics: X2, 784 (2017)
2017
-
[39]
C. W. Gardiner and M. J. Collett, Phys. Rev. A31, 3761 (1985)
1985
-
[40]
Gardiner and P
C. Gardiner and P. Zoller,Quantum Noise: A Handbook of Markovian and Non-Markovian Quantum Stochastic Methods with Applications to Quantum Optics, Springer Series in Synergetics (Springer, 2004)
2004
-
[41]
Bundgaard-Nielsen, D
M. Bundgaard-Nielsen, D. Englund, M. Heuck, and S. Krastanov, Quantum9, 1710 (2025)
2025
-
[42]
See Supplementary Material at [...] for details, which in- cludes Ref. 79
-
[43]
M. Reck, A. Zeilinger, H. J. Bernstein, and P. Bertani, Phys. Rev. Lett.73, 58 (1994)
1994
-
[44]
W. R. Clements, P. C. Humphreys, B. J. Metcalf, W. S. Kolthammer, and I. A. Walmsley, Optica3, 1460 (2016)
2016
-
[45]
Jaynes and F
E. Jaynes and F. Cummings, Proceedings of the IEEE 51, 89 (1963)
1963
-
[46]
Propson, B
T. Propson, B. E. Jackson, J. Koch, Z. Manchester, and D. I. Schuster, Phys. Rev. Appl.17, 014036 (2022)
2022
-
[47]
M. H. Goerz, S. C. Carrasco, and V. S. Malinovsky, Quantum6, 871 (2022)
2022
-
[48]
A. J. Goldschmidt, J. L. DuBois, S. L. Brunton, and J. N. Kutz, Quantum6, 837 (2022)
2022
-
[49]
Guilmin, A
P. Guilmin, A. Bocquet, ´E. Genois, D. Weiss, and R. Gautier (2025)
2025
-
[50]
Bradbury, R
J. Bradbury, R. Frostig, P. Hawkins, M. J. Johnson, C. Leary, D. Maclaurin, G. Necula, A. Paszke, J. Vander- Plas, S. Wanderman-Milne, and Q. Zhang, JAX: compos- able transformations of Python+NumPy programs (2018)
2018
-
[51]
Goodfellow, Y
I. Goodfellow, Y. Bengio, and A. Courville,Deep Learn- ing(MIT Press, 2016)http://www.deeplearningbook. org
2016
-
[52]
T. C. Ralph, K. J. Resch, and A. Gilchrist, Phys. Rev. A75, 022313 (2007)
2007
-
[53]
E. T. Campbell, B. M. Terhal, and C. Vuillot, Nature 549, 172 (2017)
2017
-
[54]
Aharonov and M
D. Aharonov and M. Ben-Or, SIAM Journal on Comput- ing38, 1207 (2008)
2008
-
[55]
Acharya, D
R. Acharya, D. A. Abanin, L. Aghababaie-Beni, I. Aleiner, T. I. Andersen, M. Ansmann, F. Arute, K. Arya, A. Asfaw, N. Astrakhantsev,et al.(Google Quantum AI and Collaborators), Nature638, 920 (2025)
2025
-
[56]
M. L. Chan, A. A. Capatos, P. Lodahl, A. S. Sørensen, and S. Paesani, Practical blueprint for low-depth pho- tonic quantum computing with quantum dots (2025), arXiv:2507.16152 [quant-ph]
2025 arXiv
-
[57]
Muralidharan, J
S. Muralidharan, J. Kim, N. L¨ utkenhaus, M. D. Lukin, and L. Jiang, Phys. Rev. Lett.112, 250501 (2014)
2014
-
[58]
F. M. Miatto, M. Epping, and N. L¨ utkenhaus, Quantum 2, 75 (2018)
2018
-
[59]
Bartlett and S
B. Bartlett and S. Fan, Phys. Rev. A101, 042319 (2020)
2020
-
[60]
Bartlett, A
B. Bartlett, A. Dutt, and S. Fan, Optica8, 1515 (2021). 10
2021
-
[61]
D. Zhu, L. Shao, M. Yu, R. Cheng, B. Desiatov, C. J. Xin, Y. Hu, J. Holzgrafe, S. Ghosh, A. Shams-Ansari, E. Puma, N. Sinclair, C. Reimer, M. Zhang, and M. Lonˇ car, Adv. Opt. Photon.13, 242 (2021)
2021
-
[62]
C. Wang, Z. Li, J. Riemensberger, G. Lihachev, M. Chu- raev, W. Kao, X. Ji, J. Zhang, T. Blesin, A. Davydova, Y. Chen, K. Huang, X. Wang, X. Ou, and T. J. Kippen- berg, Nature629, 784 (2024)
2024
-
[63]
Chelladurai, M
D. Chelladurai, M. Kohli, J. Winiger, D. Moor, A. Mess- ner, Y. Fedoryshyn, M. Eleraky, Y. Liu, H. Wang, and J. Leuthold, Nature Materials24, 868 (2025)
2025
-
[64]
M. Li, J. Ling, Y. He, U. A. Javid, S. Xue, and Q. Lin, Nature Communications11, 4123 (2020)
2020
-
[65]
Larocque, D
H. Larocque, D. L. P. Vitullo, A. Sludds, H. Sattari, I. Christen, G. Choong, I. Prieto, J. Leo, H. Zarebidaki, S. Lohani, B. T. Kirby, ¨O. Soykal, M. Soltani, A. H. Ghadimi, D. R. Englund, and M. Heuck, ACS Photonics 11, 3860 (2024), publisher: American Chemical Society
2024
-
[66]
Y. Xue, R. Gan, K. Chen, G. Chen, Z. Ruan, J. Zhang, J. Liu, D. Dai, C. Guo, and L. Liu, Optica9, 1131 (2022)
2022
-
[67]
J. F. Herrmann, D. J. Dean, C. J. Sarabalis, V. Ansari, K. Multani, E. A. Wollack, T. P. McKenna, J. D. Witmer, and A. H. Safavi-Naeini, Opt. Express32, 6168 (2024)
2024
-
[68]
Rasmussen, H
M. Rasmussen, H. Zarebidaki, H. Sattari, A. H. Ghadimi, M. Zahidy, M. Galili, D. Englund, D. L. Vitullo, and M. Heuck, inOptica Quantum 2.0 Conference and Ex- hibition(Optica Publishing Group, 2025) p. QM4B.4
2025
-
[69]
Daudlin, A
S. Daudlin, A. Rizzo, S. Lee, D. Khilwani, C. Ou, S. Wang, A. Novick, V. Gopal, M. Cullen, R. Parsons, K. Jang, A. Molnar, and K. Bergman, Nature Photonics 19, 502 (2025)
2025
-
[70]
C. Wang, M. Zhang, X. Chen, M. Bertrand, A. Shams- Ansari, S. Chandrasekhar, P. Winzer, and M. Lonˇ car, Na- ture562, 101 (2018)
2018
-
[71]
X. Li, Y. Hu, T. Ge, A. Cordaro, Y. Song, X. Zhu, S. Lu, K. Powell, L. Magalh˜ aes, U. Senica, N. Sinclair, and M. Lonˇ car, Spectral-temporal processing using integrated recursive electro-optic circuit (2025), arXiv:2509.25102 [physics.optics]
2025
-
[72]
J. Lu, M. Li, C.-L. Zou, A. A. Sayem, and H. X. Tang, Optica7, 1654 (2020)
2020
-
[73]
X. Zhu, Y. Hu, S. Lu, H. K. Warner, X. Li, Y. Song, L. M. aes, A. Shams-Ansari, A. Cordaro, N. Sinclair, and M. Lonˇ car, Photon. Res.12, A63 (2024)
2024
-
[74]
F. J. G. de Abajo, D. N. Basov, F. H. L. Koppens, L. Orsini, M. Ceccanti, S. Castilla, L. Cavicchi, M. Polini, P. A. D. Gon¸ calves, A. T. Costa, N. M. R. Peres,et al., ACS Photonics12, 3961 (2025)
2025
-
[75]
A. P. Ovvyan, M.-K. Li, H. Gehring, F. Beutel, S. Kumar, F. Hennrich, L. Wei, Y. Chen, F. Pyatkov, R. Krupke, and W. H. P. Pernice, Nature Communica- tions14, 3933 (2023)
2023
-
[76]
Aghaeimeibodi, B
S. Aghaeimeibodi, B. Desiatov, J.-H. Kim, C.-M. Lee, M. A. Buyukkaya, A. Karasahin, C. J. K. Richardson, R. P. Leavitt, M. Lonˇ car, and E. Waks, Applied Physics Letters113, 221102 (2018)
2018
-
[77]
Zektzer, X
R. Zektzer, X. Lu, K. T. Hoang, R. Shrestha, S. Austin, F. Zhou, A. Chanana, G. Holland, D. Westly, P. Lett, A. V. Gorshkov, and K. Srinivasan, Optica11, 1376 (2024)
2024
-
[78]
X. Zhou, H. Tamura, T.-H. Chang, and C.-L. Hung, Phys. Rev. X14, 031004 (2024)
2024
-
[79]
”An open-source implementation of the numeri- cal optimization of recirculating quantum pho- tonic networks”,https://github.com/EmilGrovn/ RecirculatingQuantumPhotonicNetworks
-
[80]
Houde, W
M. Houde, W. McCutcheon, and N. Quesada, Canadian Journal of Physics102, 497 (2024). S1 Supplemental Material for ”Recirculating Quantum Photonic Networks for Fast Deterministic Quantum Information Processing” SI. DERIV A TION OF THE HAMIL TONIAN (a) (b) FIG. S1. (a) Schematic...
2024
-
[81]
We cascade this output into ˆUSPM, which imparts aπ/2-phase shift only if two photons are in the same mode, i.e., if the original state was|1,0⟩ L or|0,1⟩ L
Thus, for input|1,0⟩ L or |0,1⟩ L only, the beam splitter transformations produce a superposition of states where the two photons are in the same mode. We cascade this output into ˆUSPM, which imparts aπ/2-phase shift only if two photons are in the same mode, i.e., if the orig...
2009
Reviewed August 3, 2026 · model on record in the stance chip above.
Discussion (0). Continue with ORCID to comment.