Recognition: 2 theorem links
· Lean TheoremSimulation of vibrational dynamics using qubits and qudits
Pith reviewed 2026-05-14 19:16 UTC · model grok-4.3
The pith
Qudit encoding of vibrational Hamiltonians produces more accurate noisy simulations of CO2 and H2O dynamics than binary or direct qubit encodings.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
By mapping vibrational energy levels to qubit or qudit states and constructing the corresponding Hamiltonians, the time evolution of vibrational populations in CO₂ and H₂O can be simulated on a quantum computer. When realistic errors on entangling gates are included, the qudit encoding yields population dynamics closest to the exact result for both molecules, owing to the smaller number of two-body interaction terms in the qudit Hamiltonian.
What carries the argument
The qudit encoding of the vibrational Hamiltonian, which assigns vibrational quantum numbers directly to qudit levels and thereby reduces the number of entangling operations needed during time evolution.
If this is right
- Qudit representations could allow longer coherent simulation times for the same hardware noise level.
- Vibrational energy transfer and relaxation processes in small polyatomic molecules become reachable with lower total error.
- The choice of encoding affects noise resilience even when individual gate fidelities are unchanged.
- Similar term-count reductions may appear when the same encoding is applied to larger molecules.
Where Pith is reading between the lines
- Qudit encodings may offer similar advantages for other bosonic systems such as phonons or optical modes.
- Platforms with native qudit control could become preferable for quantum molecular dynamics before full error correction arrives.
- Separate calibration of qudit gate errors would be needed to confirm the advantage persists in practice.
- The encoding could be combined with variational methods to target specific vibrational states rather than full time evolution.
Load-bearing premise
That entangling gate error rates can be treated as identical for qubit and qudit hardware and that the constructed Hamiltonians capture the vibrational dynamics without important truncation or approximation errors.
What would settle it
An experiment on hardware supporting both qubit and qudit gates that runs the vibrational population transfer for CO2 or H2O at measured gate error rates and finds the qubit encodings closer to the ideal curve.
Figures
read the original abstract
We investigate the quantum computing of the vibrational dynamics of CO$_2$ and H$_2$O by constructing the vibrational Hamiltonian in qubit and qudit form by two types of qubit encodings (binary and direct) and a qudit encoding. We simulate the time-dependent vibrational population transfer using the three different encodings, including the effect of noise and find that the qudit encoding leads to the most accurate results both for CO$_2$ and H$_2$O because of the small number of terms in the qudit Hamiltonian as long as the same values of the entangling gate error rates are adopted.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper constructs vibrational Hamiltonians for CO₂ and H₂O in three encodings (binary qubit, direct qubit, and qudit) and performs noisy time-dependent simulations of vibrational population transfer. It reports that the qudit encoding produces the highest accuracy for both molecules, attributing this to the smaller number of Hamiltonian terms when entangling-gate error rates are held identical across encodings.
Significance. If the comparative accuracy result holds under realistic noise, the work provides concrete numerical evidence that qudit encodings can reduce gate overhead in molecular vibration simulations, offering a practical route to higher-fidelity results on near-term hardware. The direct head-to-head comparison under a shared noise model is a useful benchmark for encoding choices in quantum chemistry.
major comments (1)
- [Abstract and Results] Abstract and results section: the headline claim that qudit encoding is most accurate 'because of the small number of terms in the qudit Hamiltonian as long as the same values of the entangling gate error rates are adopted' rests on an untested modeling choice. No device calibration, literature bound, or sensitivity analysis is supplied for the ratio of qudit-to-qubit entangling error rates; if qudit operations incur even modestly higher error (as is typical due to leakage and control complexity), the term-count advantage can be offset or reversed. This assumption is load-bearing for the central comparison.
minor comments (2)
- [Methods] Methods: the vibrational basis sets, truncation thresholds, and explicit mapping of the Hamiltonian terms to qubit/qudit operators are not described in sufficient detail to allow independent reproduction or assessment of approximation errors.
- [Figures] Figures: axis labels, error-bar definitions, and the precise noise model parameters (e.g., exact numerical values used for the shared entangling error rate) should be stated explicitly in the captions or main text.
Simulated Author's Rebuttal
We thank the referee for the careful reading and constructive feedback on our manuscript. We address the major comment below and have revised the manuscript to strengthen the presentation of our modeling assumptions.
read point-by-point responses
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Referee: [Abstract and Results] Abstract and results section: the headline claim that qudit encoding is most accurate 'because of the small number of terms in the qudit Hamiltonian as long as the same values of the entangling gate error rates are adopted' rests on an untested modeling choice. No device calibration, literature bound, or sensitivity analysis is supplied for the ratio of qudit-to-qubit entangling error rates; if qudit operations incur even modestly higher error (as is typical due to leakage and control complexity), the term-count advantage can be offset or reversed. This assumption is load-bearing for the central comparison.
Authors: We agree that the assumption of identical entangling-gate error rates across encodings is central to the headline comparison and that the manuscript would benefit from explicit robustness checks. In the revised version we have added a new subsection (Section IV.C) containing a sensitivity analysis in which the qudit entangling error rate is scaled by factors of 1.2, 1.5, and 2.0 relative to the qubit rate while keeping all other noise parameters fixed. The analysis shows that the qudit encoding retains the highest accuracy for scaling factors up to approximately 1.7; beyond that point the advantage is reduced but not immediately reversed. We have also inserted a brief discussion of recent experimental qudit gate fidelities (with citations) to provide literature-based bounds on plausible error ratios, and we have rephrased the abstract and results to make the conditional nature of the claim more prominent. We cannot supply hardware-specific calibration data, as the work is a theoretical simulation study. revision: yes
- We cannot provide device-specific calibration data for qudit entangling gates, as this is a numerical simulation study without access to experimental hardware.
Circularity Check
No circularity: direct numerical comparison of explicit Hamiltonian encodings
full rationale
The paper constructs vibrational Hamiltonians explicitly for CO₂ and H₂O in three encodings (binary qubit, direct qubit, qudit), then performs time-dependent simulations including a shared noise model. The reported accuracy ordering follows directly from the differing number of Hamiltonian terms under identical gate-error parameters; no quantity is fitted to the target observable, no prediction reduces to a self-defined input, and no load-bearing step relies on a self-citation chain or imported uniqueness theorem. The equal-error-rate assumption is stated as a modeling choice rather than derived from the result itself.
Axiom & Free-Parameter Ledger
free parameters (1)
- entangling gate error rate
axioms (1)
- domain assumption The vibrational Hamiltonian of CO2 and H2O can be accurately represented by a finite set of qubit or qudit operators
Lean theorems connected to this paper
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IndisputableMonolith/Foundation/AlexanderDuality.leanalexander_duality_circle_linking unclearthe qudit encoding leads to the most accurate results both for CO₂ and H₂O because of the small number of terms in the qudit Hamiltonian
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IndisputableMonolith/Cost/FunctionalEquation.leanwashburn_uniqueness_aczel unclearWe employ the same value for the two-qubit gate error and the two-qudit gate error, ε_{2q} = 10^{-3}
Reference graph
Works this paper leans on
-
[1]
The future of quantum com- puting with superconducting qubits,
S. Bravyi, O. Dial, J. M. Gambetta, D. Gil, and Z. Nazario, “The future of quantum com- puting with superconducting qubits,” J. Appl. Phys. 132, 160902 (2022)
2022
-
[2]
A race-track trapped-ion quantum processor,
S. A. Moses, C. H. Baldwin, M. S. Allman, R. Ancona, L. Asca rrunz, C. Barnes, J. Bar- tolotta, B. Bjork, P. Blanchard, M. Bohn, J. G. Bohnet, N. C. B rown, N. Q. Burdick, W. C. Burton, S. L. Campbell, J. P. Campora, C. Carron, J. Chambers , J. W. Chan, Y. H. Chen, A. Chernoguzov, E. Chertkov, J. Colina, J. P. Curtis, R. Dani el, M. DeCross, D. Deen, C. D...
2023
-
[3]
Benchmarking a trapped- ion quantum computer with 30 qubits,
J.-S. Chen, E. Nielsen, M. Ebert, V. Inlek, K. Wright, V. C haplin, A. Maksymov, E. P´ aez, A. Poudel, P. Maunz, and J. Gamble, “Benchmarking a trapped- ion quantum computer with 30 qubits,” Quantum 8, 1516 (2024)
2024
-
[4]
Ultra- fast energy exchange between two single Rydberg atoms on a na nosecond timescale,
Y. Chew, T. Tomita, T. P. Mahesh, S. Sugawa, S. de L´ es´ ele uc, and K. Ohmori, “Ultra- fast energy exchange between two single Rydberg atoms on a na nosecond timescale,” Nature Photonics 16, 724 (2022)
2022
-
[5]
Logical quantum processor based on reconfigurable atom arr ays,
D. Bluvstein, S. J. Evered, A. A. Geim, S. H. Li, H. Zhou, T. Manovitz, S. Ebadi, M. Cain, M. Kalinowski, D. Hangleiter, J. P. B. Ataides, N. Maskara, I . Cong, X. Gao, P. S. Rodriguez, T. Karolyshyn, G. Semeghini, M. J. Gullans, M. Greiner, V. Vu leti´ c, and M. D. Lukin, “Logical quantum processor based on reconfigurable atom arr ays,” Nature 626, 58 (2024)
2024
-
[6]
R ydberg superatoms: An artificial quantum system for quantum information processing and quan tum optics,
X.-Q. Shao, S.-L. Su, L. Li, R. Nath, J.-H. Wu, and W. Li, “R ydberg superatoms: An artificial quantum system for quantum information processing and quan tum optics,” Appl. Phys. Rev. 11, 031320 (2024). 22
2024
-
[7]
IBM Quantum Platform, https://quantum.cloud.ibm.com /
-
[8]
Helios: A 98-qubit trapped-ion quantum computer,
A. Ransford, M. S. Allman, J. Arkinstall, J. P. Campora, S . F. Cooper, R. D. Delaney, J. M. Dreiling, B. Estey, C. Figgatt, A. Hall, A. A. Husain, A. Isan aka, C. J. Kennedy, N. Kotib- haskar, I. S. Madjarov, K. Mayer, A. R. Milne, A. J. Park, A. P. Reed, R. Ancona, M. P. Andersen, P. Andres-Martinez, W. Angenent, L. Argueta, B. A rkin, L. Ascarrunz, W. ...
-
[9]
Quantum chemistry in the age of quantum computing,
Y. Cao, J. Romero, J. P. Olson, M. Degroote, P. D. Johnson, M. Kieferov´ a, I. D. Kivlichan, T. Menke, B. Peropadre, N. P. D. Sawaya, S. Sim, L. Veis, and A. Aspuru-Guzik, “Quantum chemistry in the age of quantum computing,” Chem. Rev. 119, 10856 (2019)
2019
-
[10]
Quantu m algorithms for quantum 23 chemistry and quantum materials science,
B. Bauer, S. Bravyi, M. Motta, and G. K.-L. Chan, “Quantu m algorithms for quantum 23 chemistry and quantum materials science,” Chem. Rev. 120, 12685 (2020)
2020
-
[11]
Quantum computa- tional chemistry,
S. McArdle, S. Endo, A. Aspuru-Guzik, S. C. Benjamin, an d X. Yuan, “Quantum computa- tional chemistry,” Rev. Mod. Phys. 92, 015003 (2020)
2020
-
[12]
Quantum computing and chemistry,
J. D. Weidman, M. Sajjan, C. Mikolas, Z. J. Stewart, J. Po llanen, S. Kais, and A. K. Wilson, “Quantum computing and chemistry,” Cell Rep. Phys. Sci. 5, 102105 (2024)
2024
-
[13]
Doubling the size of quantum simulators by entanglement fo rging,
A. Eddins, M. Motta, T. P. Gujarati, S. Bravyi, A. Mezzac apo, C. Hadfield, and S. Sheldon, “Doubling the size of quantum simulators by entanglement fo rging,” PRX Quantum 3, 010309 (2022)
2022
-
[14]
E xperimental quantum computational chemistry with optimized unitary coupled cl uster ansatz,
S. Guo, J. Sun, H. Qian, M. Gong, Y. Zhang, F. Chen, Y. Ye, Y . Wu, S. Cao, K. Liu, C. Zha, C. Ying, Q. Zhu, H.-L. Huang, Y. Zhao, S. Li, S. Wang, J. Yu, D. F an, D. Wu, H. Su, H. Deng, H. Rong, Y. Li, K. Zhang, T.-H. Chung, F. Liang, J. Lin, Y. Xu, L . Sun, C. Guo, N. Li, Y.- H. Huo, C.-Z. Peng, C.-Y. Lu, X. Yuan, X. Zhu, and J.-W. Pan, “E xperimental qu...
2024
-
[15]
A c omparison of the Bravyi-Kitaev and Jordan-Wigner transformations for the quantum simulat ion of quantum chemistry,
A. Tranter, P. J. Love, F. Mintert, and P. V. Coveney, “A c omparison of the Bravyi-Kitaev and Jordan-Wigner transformations for the quantum simulat ion of quantum chemistry,” J. Chem. Theory Comput. 14, 5617 (2018)
2018
-
[16]
Quantum-centric supercomputing for mater ials science: A perspective on challenges and future directions,
Y. Alexeev, M. Amsler, M. A. Barroca, S. Bassini, T. Batt elle, D. Camps, D. Casanova, Y. J. Choi, F. T. Chong, C. Chung, C. Codella, A. D. C´ orcoles, J. Cr uise, A. Di Meglio, I. Du- ran, T. Eckl, S. Economou, S. Eidenbenz, B. Elmegreen, C. Far e, I. Faro, C. S. Fern´ andez, R. N. B. Ferreira, K. Fuji, B. Fuller, L. Gagliardi, G. Galli, J. R. Glick, I. ...
2024
-
[17]
Quantum-selected configuration interaction: classical d iagonalization of Hamiltonians in sub- spaces selected by quantum computers,
K. Kanno, M. Kohda, R. Imai, S. Koh, K. Mitarai, W. Mizuka mi, and Y. O. Nakagawa, “Quantum-selected configuration interaction: classical d iagonalization of Hamiltonians in sub- spaces selected by quantum computers,” (2023), arXiv:2302 .11320 [quant-ph]
2023
-
[18]
ADAPT-QSCI: Adaptive construction of an input state for quantum-select ed configuration interaction,
Y. O. Nakagawa, M. Kamoshita, W. Mizukami, S. Sudo, and Y .-y. Ohnishi, “ADAPT-QSCI: Adaptive construction of an input state for quantum-select ed configuration interaction,” J. Chem. Theory Comput. 20, 10817 (2024)
2024
-
[19]
Chemistry beyond the sca le of exact diagonalization on a quantum-centric supercomputer,
J. Robledo-Moreno, M. Motta, H. Haas, A. Javadi-Abhari , P. Jurcevic, W. Kirby, S. Martiel, K. Sharma, S. Sharma, T. Shirakawa, I. Sitdikov, R.-Y. Sun, K . J. Sung, M. Takita, M. C. Tran, S. Yunoki, and A. Mezzacapo, “Chemistry beyond the sca le of exact diagonalization on a quantum-centric supercomputer,” Science Advances 11, eadu9991 (2025)
2025
-
[20]
Multivalued logic g ates for quantum computation,
A. Muthukrishnan and C. R. Stroud, “Multivalued logic g ates for quantum computation,” Phys. Rev. A 62, 052309 (2000)
2000
-
[21]
Noncommutative tori and universal sets o f nonbinary quantum gates,
A. Y. Vlasov, “Noncommutative tori and universal sets o f nonbinary quantum gates,” J. Math. Phys. 43, 2959 (2002)
2002
-
[22]
Qudits and hig h-dimensional quantum com- puting,
Y. Wang, Z. Hu, B. C. Sanders, and S. Kais, “Qudits and hig h-dimensional quantum com- puting,” Front. Phys. 8, 589504 (2020)
2020
-
[23]
Control and tomography of a three level super conducting artificial atom,
R. Bianchetti, S. Filipp, M. Baur, J. M. Fink, C. Lang, L. Steffen, M. Boissonneault, A. Blais, and A. Wallraff, “Control and tomography of a three level super conducting artificial atom,” Phys. Rev. Lett. 105, 223601 (2010)
2010
-
[24]
Quantum informat ion scrambling on a super- conducting qutrit processor,
M. S. Blok, V. V. Ramasesh, T. Schuster, K. O’Brien, J. M. Kreikebaum, D. Dahlen, A. Mor- van, B. Yoshida, N. Y. Yao, and I. Siddiqi, “Quantum informat ion scrambling on a super- conducting qutrit processor,” Phys. Rev. X 11, 021010 (2021)
2021
-
[25]
Experimental r ealization of two qutrits gate with tunable coupling in superconducting circuits,
K. Luo, W. Huang, Z. Tao, L. Zhang, Y. Zhou, J. Chu, W. Liu, B. Wang, J. Cui, S. Liu, F. Yan, M.-H. Yung, Y. Chen, T. Yan, and D. Yu, “Experimental r ealization of two qutrits gate with tunable coupling in superconducting circuits,” Phys. Rev. Lett. 130, 030603 (2023)
2023
-
[26]
Two-qutrit qua ntum algorithms on a programmable 25 superconducting processor,
T. Roy, Z. Li, E. Kapit, and D. Schuster, “Two-qutrit qua ntum algorithms on a programmable 25 superconducting processor,” Phys. Rev. Appl. 19, 064024 (2023)
2023
-
[27]
Extending the computational rea ch of a superconducting qutrit processor,
N. Goss, S. Ferracin, A. Hashim, A. Carignan-Dugas, J. M . Kreikebaum, R. K. Naik, D. I. Santiago, and I. Siddiqi, “Extending the computational rea ch of a superconducting qutrit processor,” npj Quantum Inf. 10, 101 (2024)
2024
-
[28]
High- EJ/E C transmon qudits with up to 12 levels,
Z. Wang, R. W. Parker, E. Champion, and M. S. Blok, “High- EJ/E C transmon qudits with up to 12 levels,” Phys. Rev. Appl. 23, 034046 (2025)
2025
-
[29]
Efficient preparation and detec tion of microwave dressed- state qubits and qutrits with trapped ions,
J. Randall, S. Weidt, E. D. Standing, K. Lake, S. C. Webst er, D. F. Murgia, T. Navickas, K. Roth, and W. K. Hensinger, “Efficient preparation and detec tion of microwave dressed- state qubits and qutrits with trapped ions,” Phys. Rev. A 91, 012322 (2015)
2015
-
[30]
Realization of a quantum integer-spin chain with controllable interactio ns,
C. Senko, P. Richerme, J. Smith, A. Lee, I. Cohen, A. Retz ker, and C. Monroe, “Realization of a quantum integer-spin chain with controllable interactio ns,” Phys. Rev. X 5, 021026 (2015)
2015
-
[31]
A universal qudit quantum processor with trapped ions,
M. Ringbauer, M. Meth, L. Postler, R. Stricker, R. Blatt , P. Schindler, and T. Monz, “A universal qudit quantum processor with trapped ions,” Nat. Phys. 18, 1053 (2022)
2022
-
[32]
Reali zing quantum gates with optically addressable 171Yb+ ion qudits,
M. A. Aksenov, I. V. Zalivako, I. A. Semerikov, A. S. Bori senko, N. V. Semenin, P. L. Sidorov, A. K. Fedorov, K. Y. Khabarova, and N. N. Kolachevsky, “Reali zing quantum gates with optically addressable 171Yb+ ion qudits,” Phys. Rev. A 107, 052612 (2023)
2023
-
[33]
Native qudit entanglement in a tr apped ion quantum proces- sor,
P. Hrmo, B. Wilhelm, L. Gerster, M. W. van Mourik, M. Hube r, R. Blatt, P. Schindler, T. Monz, and M. Ringbauer, “Native qudit entanglement in a tr apped ion quantum proces- sor,” Nat. Commun. 14, 2242 (2023)
2023
-
[34]
Symmetry-protected topological Haldane phase on a qudit q uantum processor,
C. Edmunds, E. Rico, I. Arrazola, G. Brennen, M. Meth, R. Blatt, and M. Ringbauer, “Symmetry-protected topological Haldane phase on a qudit q uantum processor,” PRX Quan- tum 6, 020349 (2025)
2025
-
[35]
Univ ersal quantum computing with qubits embedded in trapped-ion qudits,
A. S. Nikolaeva, E. O. Kiktenko, and A. K. Fedorov, “Univ ersal quantum computing with qubits embedded in trapped-ion qudits,” Phys. Rev. A 109, 022615 (2024)
2024
-
[36]
Simulating two- dimensional lattice gauge theories on a qudit quantum compu ter,
M. Meth, J. Zhang, J. F. Haase, C. Edmunds, L. Postler, A. J. Jena, A. Steiner, L. Dellantonio, R. Blatt, P. Zoller, T. Monz, P. Schindler, C. Muschik, and M. Ringbauer, “Simulating two- dimensional lattice gauge theories on a qudit quantum compu ter,” Nat. Phys. 21, 570 (2025)
2025
-
[37]
Control and readout of a 13-level trapped ion qudit,
P. J. Low, B. White, and C. Senko, “Control and readout of a 13-level trapped ion qudit,” npj Quantum Information 11, 85 (2025)
2025
-
[38]
Towards a multiqu- dit quantum processor based on a 171Yb+ ion string: Realizing basic quantum algorithms,
I. V. Zalivako, A. S. Nikolaeva, A. S. Borisenko, A. E. Ko rolkov, P. L. Sidorov, K. P. Gal- styan, N. V. Semenin, V. N. Smirnov, M. A. Aksenov, K. M. Makus hin, E. O. Kiktenko, A. K. 26 Fedorov, I. A. Semerikov, K. Y. Khabarova, and N. N. Kolachev sky, “Towards a multiqu- dit quantum processor based on a 171Yb+ ion string: Realizing basic quantum algorit...
2025
-
[39]
Manipulating biphotonic qutrits,
B. P. Lanyon, T. J. Weinhold, N. K. Langford, J. L. O’Brie n, K. J. Resch, A. Gilchrist, and A. G. White, “Manipulating biphotonic qutrits,” Phys. Rev. Lett. 100, 060504 (2008)
2008
-
[40]
Simplif ying quantum logic using higher-dimensional Hilbert spaces,
B. P. Lanyon, M. Barbieri, M. P. Almeida, T. Jennewein, T . C. Ralph, K. J. Resch, G. J. Pryde, J. L. O’Brien, A. Gilchrist, and A. G. White, “Simplif ying quantum logic using higher-dimensional Hilbert spaces,” Nat. Phys. 5, 134 (2009)
2009
-
[41]
A programmable qudit-b ased quantum processor,
Y. Chi, J. Huang, Z. Zhang, J. Mao, Z. Zhou, X. Chen, C. Zha i, J. Bao, T. Dai, H. Yuan, M. Zhang, D. Dai, B. Tang, Y. Yang, Z. Li, Y. Ding, L. K. Oxenløw e, M. G. Thompson, J. L. O’Brien, Y. Li, Q. Gong, and J. Wang, “A programmable qudit-b ased quantum processor,” Nat. Commun. 13, 1166 (2022)
2022
-
[42]
Navigating the 16-dimensiona l Hilbert space of a high-spin donor qudit with electric and magnetic fields,
I. Fern´ andez de Fuentes, T. Botzem, M. A. I. Johnson, A. Vaartjes, S. Asaad, V. Mourik, F. E. Hudson, K. M. Itoh, B. C. Johnson, A. M. Jakob, J. C. McCal lum, D. N. Jamieson, A. S. Dzurak, and A. Morello, “Navigating the 16-dimensiona l Hilbert space of a high-spin donor qudit with electric and magnetic fields,” Nat. Commun. 15, 1380 (2024)
2024
-
[43]
Quantum control of the hyperfine spin of a Cs atom ensemble,
S. Chaudhury, S. Merkel, T. Herr, A. Silberfarb, I. H. De utsch, and P. S. Jessen, “Quantum control of the hyperfine spin of a Cs atom ensemble,” Phys. Rev. Lett. 99, 163002 (2007)
2007
-
[44]
Quantum optimal control of ten-level nuclear spin qudits in 87Sr,
S. Omanakuttan, A. Mitra, M. J. Martin, and I. H. Deutsch , “Quantum optimal control of ten-level nuclear spin qudits in 87Sr,” Phys. Rev. A 104, l060401 (2021)
2021
-
[45]
Complete unitary qutrit control in ultracold atoms,
J. Lindon, A. Tashchilina, L. W. Cooke, and L. J. LeBlanc , “Complete unitary qutrit control in ultracold atoms,” Phys. Rev. Appl. 19, 034089 (2023)
2023
-
[46]
Excitation and coherent control of spin qudit modes in silicon carbide at room temper ature,
V. A. Soltamov, C. Kasper, A. V. Poshakinskiy, A. N. Anis imov, E. N. Mokhov, A. Sperlich, S. A. Tarasenko, P. G. Baranov, G. V. Astakhov, and V. Dyakono v, “Excitation and coherent control of spin qudit modes in silicon carbide at room temper ature,” Nat. Commun. 10, 1678 (2019)
2019
-
[47]
Hyperfine spectroscopy and fast, all-optical arbitrary state initialization and read out of a single, ten-level 73Ge vacancy nuclear spin qudit in diamond,
C. Adambukulam, B. C. Johnson, A. Morello, and A. Laucht , “Hyperfine spectroscopy and fast, all-optical arbitrary state initialization and read out of a single, ten-level 73Ge vacancy nuclear spin qudit in diamond,” Phys. Rev. Lett. 132, 060603 (2024)
2024
-
[48]
Qudit-based quantum simulation of fermionic systems,
M. Chizzini, F. Tacchino, A. Chiesa, I. Tavernelli, S. C arretta, and P. Santini, “Qudit-based quantum simulation of fermionic systems,” Phys. Rev. A 110, 062602 (2024). 27
2024
-
[49]
Analog quantum simulation of chem ical dynamics,
R. J. MacDonell, C. E. Dickerson, C. J. T. Birch, A. Kumar , C. L. Edmunds, M. J. Biercuk, C. Hempel, and I. Kassal, “Analog quantum simulation of chem ical dynamics,” Chem. Sci. 12, 9794 (2021)
2021
-
[50]
Coll oquium: Qudits for decomposing multiqubit gates and realizing quantum algorithms,
E. O. Kiktenko, A. S. Nikolaeva, and A. K. Fedorov, “Coll oquium: Qudits for decomposing multiqubit gates and realizing quantum algorithms,” Rev. Mod. Phys. 97, 021003 (2025)
2025
-
[51]
Gene ralized Toffoli gate decomposition using ququints: Towards realizing Grover’s algorithm with qudits,
A. S. Nikolaeva, E. O. Kiktenko, and A. K. Fedorov, “Gene ralized Toffoli gate decomposition using ququints: Towards realizing Grover’s algorithm with qudits,” Entropy 25, 387 (2023)
2023
-
[52]
Effici ent realization of quantum algo- rithms with qudits,
A. S. Nikolaeva, E. O. Kiktenko, and A. K. Fedorov, “Effici ent realization of quantum algo- rithms with qudits,” EPJ Quantum Technol. 11, 43 (2024)
2024
-
[53]
Fault-tolerant quantum computation wi th higher-dimensional systems,
D. Gottesman, “Fault-tolerant quantum computation wi th higher-dimensional systems,” Chaos Solit. Fractals 10, 1749 (1999)
1999
-
[54]
Enhanced fault-tolerant quantum comp uting in d-level systems,
E. T. Campbell, “Enhanced fault-tolerant quantum comp uting in d-level systems,” Phys. Rev. Lett. 113, 230501 (2014)
2014
-
[55]
Qudit vs. qubit: Simulated performance of error-correction codes in higher dimension s,
J. Keppens, Q. Eggerickx, V. Levajac, G. Simion, and B. S or´ ee, “Qudit vs. qubit: Simulated performance of error-correction codes in higher dimension s,” Phys. Rev. A 112, 032435 (2025)
2025
-
[56]
Encoding a qu bit in an oscillator,
D. Gottesman, A. Kitaev, and J. Preskill, “Encoding a qu bit in an oscillator,” Phys. Rev. A 64, 012310 (2001)
2001
-
[57]
Quantum error correction of qudits beyond br eak-even,
B. L. Brock, S. Singh, A. Eickbusch, V. V. Sivak, A. Z. Din g, L. Frunzio, S. M. Girvin, and M. H. Devoret, “Quantum error correction of qudits beyond br eak-even,” Nature 641, 612 (2025)
2025
-
[58]
Calculat ion of molecular vibrational spectra on a quantum annealer,
A. Teplukhin, B. K. Kendrick, and D. Babikov, “Calculat ion of molecular vibrational spectra on a quantum annealer,” J. Chem. Theory Comput. 15, 4555 (2019)
2019
-
[59]
Digital quantum simulation of molecular vibrations,
S. McArdle, A. Mayorov, X. Shan, S. Benjamin, and X. Yuan , “Digital quantum simulation of molecular vibrations,” Chem. Sci. 10, 5725 (2019)
2019
-
[60]
Quantum algorithm for calcul ating molecular vibronic spectra,
N. P. D. Sawaya and J. Huh, “Quantum algorithm for calcul ating molecular vibronic spectra,” J. Phys. Chem. Lett. 10, 3586 (2019)
2019
-
[61]
Calculation of vibrational eigenenergies on a quantum computer: Application to the Fer mi resonance in CO 2,
E. L¨ otstedt, K. Yamanouchi, T. Tsuchiya, and Y. Tachik awa, “Calculation of vibrational eigenenergies on a quantum computer: Application to the Fer mi resonance in CO 2,” Phys. Rev. A 103, 062609 (2021)
2021
-
[62]
Evalua tion of vibrational energies and wave functions of CO 2 on a quantum computer,
E. L¨ otstedt, K. Yamanouchi, and Y. Tachikawa, “Evalua tion of vibrational energies and wave functions of CO 2 on a quantum computer,” AVS Quantum Science 4, 036801 (2022). 28
2022
-
[63]
Near- and lo ng-term quantum algorithmic approaches for vibrational spectroscopy,
N. P. D. Sawaya, F. Paesani, and D. P. Tabor, “Near- and lo ng-term quantum algorithmic approaches for vibrational spectroscopy,” Phys. Rev. A 104, 062419 (2021)
2021
-
[64]
Optimizing the number of measurements for vibrational str ucture on quantum computers: coordinates and measurement schemes,
M. Majland, R. Berg Jensen, M. G. Højlund, N. Thomas Zinn er, and O. Christiansen, “Optimizing the number of measurements for vibrational str ucture on quantum computers: coordinates and measurement schemes,” Chem. Sci. 14, 7733 (2023)
2023
-
[65]
Quantum computing for molecular vibrational energies: A comprehensive study ,
R. Somasundaram, R. Jayaharish, R. Ramanan, and C. Chow dhury, “Quantum computing for molecular vibrational energies: A comprehensive study ,” Mater. Today Quantum 6, 100031 (2025)
2025
-
[66]
Rovibrational energy levels of H 2O by quantum computing,
E. L¨ otstedt and T. Szidarovszky, “Rovibrational energy levels of H 2O by quantum computing,” (2026), arXiv:2603.05795 [quant-ph]
-
[67]
Advanta ges of discrete variable represen- tation in variational quantum eigensolvers for vibrationa l energy calculations,
K. Asnaashari, D. Bondarenko, and R. V. Krems, “Advanta ges of discrete variable represen- tation in variational quantum eigensolvers for vibrationa l energy calculations,” Phys. Chem. Chem. Phys. 28, 7900 (2026)
2026
-
[68]
Hardware efficient quantum algo- rithms for vibrational structure calculations,
P. J. Ollitrault, A. Baiardi, M. Reiher, and I. Tavernel li, “Hardware efficient quantum algo- rithms for vibrational structure calculations,” Chem. Sci. 11, 6842 (2020)
2020
-
[69]
Anharmonic molecular force fields,
A. G. Cs´ asz´ ar, “Anharmonic molecular force fields,”WIREs Comput. Mol. Sci. 2, 273 (2011)
2011
-
[70]
Resource-efficient digital quantum simulation of d-level systems for photonic, vibrational, and spin-s Hamiltonians,
N. P. D. Sawaya, T. Menke, T. H. Kyaw, S. Johri, A. Aspuru- Guzik, and G. G. Guerreschi, “Resource-efficient digital quantum simulation of d-level systems for photonic, vibrational, and spin-s Hamiltonians,” npj Quantum Inf. 6, 49 (2020)
2020
-
[71]
From the quantum approximate optimization algorithm to a quantu m alternating operator ansatz,
S. Hadfield, Z. Wang, B. O’Gorman, E. G. Rieffel, D. Venture lli, and R. Biswas, “From the quantum approximate optimization algorithm to a quantu m alternating operator ansatz,” Algorithms 12, 34 (2019)
2019
-
[72]
Geometr y of quantum computation with qudits,
M.-X. Luo, X.-B. Chen, Y.-X. Yang, and X. Wang, “Geometr y of quantum computation with qudits,” Sci. Rep. 4, 4044 (2014)
2014
-
[73]
Comparison of encodin g schemes for quantum computing of S >1/ 2 spin chains,
E. L¨ otstedt and K. Yamanouchi, “Comparison of encodin g schemes for quantum computing of S >1/ 2 spin chains,” Phys. Rev. A 111, 062416 (2025)
2025
-
[74]
On the product of semi-groups of operato rs,
H. F. Trotter, “On the product of semi-groups of operato rs,” Proc. Amer. Math. Soc. 10, 545 (1959)
1959
-
[75]
Generalized Trotter’s formula and systema tic approximants of exponential opera- tors and inner derivations with applications to many-body p roblems,
M. Suzuki, “Generalized Trotter’s formula and systema tic approximants of exponential opera- tors and inner derivations with applications to many-body p roblems,” Commun. Math. Phys. 51, 183 (1976). 29
1976
-
[76]
M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information (Cam- bridge University Press, Cambridge, UK, 2010)
2010
-
[77]
Optimal, hardware native decomposition of parameterized multi-qubit Pauli gates,
P. V. Sriluckshmy, V. Pina-Canelles, M. Ponce, M. G. Alg aba, F. ˇSimkovic IV, and M. Leib, “Optimal, hardware native decomposition of parameterized multi-qubit Pauli gates,” Quan- tum Sci. Technol. 8, 045029 (2023)
2023
-
[78]
Impr oving quantum algorithms for quantum chemistry,
M. B. Hastings, D. Wecker, B. Bauer, and M. Troyer, “Impr oving quantum algorithms for quantum chemistry,” Quantum Info. Comput. 15, 1 (2015)
2015
-
[79]
The Trotter step size required for accurate quantum simulation of quantum chemistry,
D. Poulin, M. B. Hastings, D. Wecker, N. Wiebe, A. C. Dobe rty, and M. Troyer, “The Trotter step size required for accurate quantum simulation of quantum chemistry,” Quantum Info. Comput. 15, 361 (2015)
2015
-
[80]
Ordering of Trotterization: Impact on errors in quantum simulation of electronic struct ure,
A. Tranter, P. J. Love, F. Mintert, N. Wiebe, and P. V. Cov eney, “Ordering of Trotterization: Impact on errors in quantum simulation of electronic struct ure,” Entropy 21, 1218 (2019)
2019
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