pith. sign in

arxiv: 2606.27508 · v1 · pith:52UY5PXGnew · submitted 2026-06-25 · 🪐 quant-ph

I-QMapper: Error-Aware Layout Optimization and Device Diagnostics for NISQ Hardware

Milana Bazayeva , Kenneth Merz This is my paper

Pith reviewed 2026-06-29 01:40 UTC · model grok-4.3

classification 🪐 quant-ph
keywords NISQqubit mappinglayout optimizationdevice calibrationquantum chemistryLUCJ ansatzinteractive visualizationerror aggregation
0
0 comments X

The pith

I-QMapper lets users interactively build and score qubit layouts on NISQ hardware by aggregating readout and two-qubit errors into a single Layout-Quality Score.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces I-QMapper as a Jupyter-based tool that combines interactive layout design with calibration analytics for superconducting quantum devices. It supports two modes, one general and one specialized for the LUCJ quantum-chemistry ansatz, and supplies temporal views of error data plus threshold and delta comparisons to spot drift. Each candidate layout is assigned a Layout-Quality Score that folds readout and two-qubit gate errors into one numeric value. The tool also enables multi-programming of multiple circuits on one QPU, side-by-side backend comparison, and session export. The central goal is to replace manual or black-box mapping with an explicit, error-aware workflow that can be used for both rapid prototyping and reproducible experiments.

Core claim

I-QMapper supplies an interactive Design panel for constructing layouts and an Error panel offering Live, Snapshot, Intraday, and Multi-day calibration views, threshold filtering, and delta-mode drift detection; every layout is scored by a Layout-Quality Score that aggregates its readout and two-qubit gate errors, and the same framework extends automatic LUCJ generation to multi-programming on a single QPU while allowing side-by-side backend visualization and session export.

What carries the argument

The Layout-Quality Score (LQS), which aggregates the readout and two-qubit gate errors of a chosen layout into one scalar quality value.

If this is right

  • Users can rapidly prototype and compare multiple layouts while viewing live error trends.
  • Multi-programming of several circuits on one QPU becomes straightforward for the LUCJ ansatz.
  • Temporal modes and delta comparison make device drift visible during layout decisions.
  • Side-by-side backend views and session export support reproducible noise-aware experiments.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • An LQS-style scalar could be fed directly into automated compilers to bias mapping algorithms toward lower-error regions.
  • The same interactive analytics might generalize beyond LUCJ to other variational ansatzes that require many two-qubit gates.
  • Public release of such a tool could standardize how experimental groups document and share layout choices.

Load-bearing premise

The calibration data supplied by hardware providers is accurate and timely enough that the aggregated Layout-Quality Score actually predicts which physical layout will produce higher-fidelity results.

What would settle it

Execute identical circuits on layouts that receive distinctly different LQS values and check whether higher LQS reliably yields measurably higher fidelity; a null result would falsify the claim that LQS guides useful layout selection.

Figures

Figures reproduced from arXiv: 2606.27508 by Kenneth Merz, Milana Bazayeva.

Figure 1
Figure 1. Figure 1: The connection panel guides the user through five steps: i selection of the quantum [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Design Mode interface of I-QMapper for the IBM Heron 156-qubit processor [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Side-by-side comparison of two IBM Heron r3 processors, [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The QPU panel mirrors the IBM Quantum device map, with qubits and edges [PITH_FULL_IMAGE:figures/full_fig_p014_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: The four diagnostic tools of the Analysis tab on ibm boston. Top-left: the Qubit Inspector summarizes all calibration properties of a selected qubit (here Q85) and of its connected gates. Top-right: Trend charts show the time evolution of a property across the fetched history, for qubits and gate edges respectively. Bottom-left: the Ranking table sorts qubits by any selected property, with auxiliary column… view at source ↗
read the original abstract

Achieving high-fidelity execution on noisy intermediate-scale quantum (NISQ) hardware requires careful selection of physical qubit layouts, as gate errors, readout errors, and coherence times vary across the device and drift over time. Currently, qubit mapping is performed either through manual inspection of device calibration data or through automated layout pipelines, neither of which provides integrated, interactive layout visualization combined with calibration analytics. In this work, we present the Interactive Quantum Mapper (I-QMapper), a Jupyter-based, open-source tool for noise-aware layout selection, visualization, and analysis on superconducting quantum hardware. I-QMapper offers two operating modes: a general-purpose mode for arbitrary circuits, and a dedicated mode for quantum-chemistry applications, specifically tailored to the Local Unitary Cluster Jastrow (LUCJ) ansatz. Within each mode, a Design panel supports interactive layout construction, while an Error panel provides calibration analytics through four temporal viewing modes (Live, Snapshot, Intraday, and Multi-day range) together with threshold filtering and delta-mode comparison for drift identification. Each layout receives a Layout-Quality Score (LQS) that aggregates the readout and two-qubit gate errors of the layout into a single quality value. Starting from the automatic LUCJ circuit-generation provided by IBM Quantum, we extend it to a multi-programming setting in which multiple circuits are mapped onto a single quantum processing unit (QPU). I-QMapper further supports side-by-side visualization of two quantum backends and layout comparison, and session export for experimental reproducibility. By combining interactive exploration with calibration analytics, I-QMapper aims to support both rapid layout prototyping and informed noise-aware experimental design on NISQ devices.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The manuscript introduces I-QMapper, an open-source Jupyter-based tool for interactive noise-aware qubit layout selection and device diagnostics on superconducting NISQ hardware. It provides a general-purpose mode for arbitrary circuits and a dedicated mode for the LUCJ ansatz in quantum chemistry, including a Design panel for layout construction, an Error panel with four temporal calibration views (Live, Snapshot, Intraday, Multi-day), threshold filtering, delta-mode drift detection, a Layout-Quality Score (LQS) that aggregates readout and two-qubit gate errors, multi-programming support, side-by-side backend comparison, and session export for reproducibility.

Significance. If the tool's LQS and interactive features demonstrably improve layout quality, it could fill a practical gap between manual calibration inspection and fully automated mappers by enabling rapid prototyping and drift-aware decisions. The open-source release and explicit LUCJ multi-programming extension are constructive contributions for the NISQ community.

major comments (1)
  1. [Abstract] Abstract: The central utility claim that I-QMapper supports 'informed noise-aware experimental design' rests on the LQS aggregation meaningfully predicting execution fidelity, yet the manuscript supplies no hardware benchmarks, fidelity measurements, correlation studies, or statistical comparisons showing that LQS-selected layouts outperform default or random mappings on actual NISQ devices.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the positive assessment of I-QMapper's features and potential contributions. We address the single major comment below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The central utility claim that I-QMapper supports 'informed noise-aware experimental design' rests on the LQS aggregation meaningfully predicting execution fidelity, yet the manuscript supplies no hardware benchmarks, fidelity measurements, correlation studies, or statistical comparisons showing that LQS-selected layouts outperform default or random mappings on actual NISQ devices.

    Authors: The referee is correct that the manuscript contains no hardware benchmarks, fidelity measurements, or statistical comparisons validating that LQS-selected layouts outperform alternatives. The paper is a tool-description manuscript whose primary contributions are the Jupyter-based interface, the four temporal calibration views, threshold and delta-mode analytics, multi-programming extension for LUCJ, and the definition of LQS as a simple aggregate of readout and two-qubit errors. The abstract deliberately uses 'aims to support' rather than asserting proven performance. Empirical validation of LQS would require a separate, resource-intensive experimental campaign across devices and circuit families, which lies outside the stated scope. We therefore do not intend to add such benchmarks; we can, however, revise the abstract and a new limitations paragraph to make the heuristic nature of LQS and the absence of validation explicit. revision: no

Circularity Check

0 steps flagged

No circularity: tool-description paper with no derivations or predictions

full rationale

The manuscript is a description of the I-QMapper software tool, its UI modes, visualization features, and the LQS heuristic that simply sums readout and two-qubit error rates supplied by the vendor. No equations, first-principles derivations, fitted parameters, or predictive claims appear in the provided text. Consequently there is no derivation chain that could reduce to its own inputs, no self-citation load-bearing on a uniqueness theorem, and no renaming of known results. The absence of any such structure makes circularity impossible; the work is self-contained as an engineering artifact.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

The paper is a software tool description and introduces no free parameters, mathematical axioms, or new physical entities.

pith-pipeline@v0.9.1-grok · 5836 in / 1104 out tokens · 38512 ms · 2026-06-29T01:40:07.423625+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

279 extracted references · 105 canonical work pages

  1. [1]

    , title =

    Plotly Technologies Inc. , title =

  2. [2]

    2015 , note =

    Jupyter widgets community , title =. 2015 , note =

    2015

  3. [3]

    2025 , eprint=

    From Promise to Practice: Benchmarking Quantum Chemistry on Quantum Hardware , author=. 2025 , eprint=

    2025

  4. [4]

    Nature , volume =

    Biamonte, Jacob and Wittek, Peter and Pancotti, Nicola and Rebentrost, Patrick and Wiebe, Nathan and Lloyd, Seth , title =. Nature , volume =. 2017 , doi =

    2017

  5. [5]

    2024 , note =

    Sample-based Quantum Diagonalization , author =. 2024 , note =

    2024

  6. [6]

    2020 , isbn =

    Ash-Saki, Abdullah and Alam, Mahabubul and Ghosh, Swaroop , title =. 2020 , isbn =. doi:10.1145/3370748.3406570 , pages =

    work page doi:10.1145/3370748.3406570 2020

  7. [7]

    2025 , eprint=

    Sample-based quantum diagonalization as parallel fragment solver for the localized active space self-consistent field method , author=. 2025 , eprint=

    2025

  8. [8]

    and Nair, Prashant J

    Das, Poulami and Tannu, Swamit S. and Nair, Prashant J. and Qureshi, Moinuddin , title =. 2019 , isbn =. doi:10.1145/3352460.3358287 , booktitle =

    work page doi:10.1145/3352460.3358287 2019

  9. [9]

    and Gambetta, Jay M

    Bravyi, Sergey and Sheldon, Sarah and Kandala, Abhinav and Mckay, David C. and Gambetta, Jay M. , year=. Mitigating measurement errors in multiqubit experiments , volume=. Physical Review A , publisher=. doi:10.1103/physreva.103.042605 , number=

    work page doi:10.1103/physreva.103.042605

  10. [10]

    PRX Quantum , volume =

    Doubling the Size of Quantum Simulators by Entanglement Forging , author =. PRX Quantum , volume =. 2022 , month =. doi:10.1103/PRXQuantum.3.010309 , url =

    work page doi:10.1103/prxquantum.3.010309 2022

  11. [11]

    QuCloud: A New Qubit Mapping Mechanism for Multi-programming Quantum Computing in Cloud Environment , year=

    Liu, Lei and Dou, Xinglei , booktitle=. QuCloud: A New Qubit Mapping Mechanism for Multi-programming Quantum Computing in Cloud Environment , year=

  12. [12]

    2021 , isbn =

    Das, Poulami and Tannu, Swamit and Dangwal, Siddharth and Qureshi, Moinuddin , title =. 2021 , isbn =. doi:10.1145/3466752.3480059 , booktitle =

    work page doi:10.1145/3466752.3480059 2021

  13. [13]

    PRX Quantum , volume =

    Quantum Crosstalk Analysis for Simultaneous Gate Operations on Superconducting Qubits , author =. PRX Quantum , volume =. 2022 , month =. doi:10.1103/PRXQuantum.3.020301 , url =

    work page doi:10.1103/prxquantum.3.020301 2022

  14. [14]

    PRX Quantum , volume =

    Experimental Characterization of Crosstalk Errors with Simultaneous Gate Set Tomography , author =. PRX Quantum , volume =. 2021 , month =. doi:10.1103/PRXQuantum.2.040338 , url =

    work page doi:10.1103/prxquantum.2.040338 2021

  15. [15]

    2024 , eprint=

    Crosstalk-induced Side Channel Threats in Multi-Tenant NISQ Computers , author=. 2024 , eprint=

    2024

  16. [16]

    Detecting crosstalk errors in quantum information processors

    Detecting crosstalk errors in quantum information processors , author =. doi:10.22331/q-2020-09-11-321 , url =

    work page doi:10.22331/q-2020-09-11-321 2020

  17. [17]

    Quantum , volume =

    Preskill, John , title =. Quantum , volume =. 2018 , doi =

    2018

  18. [18]

    Noisy intermediate-scale quantum algorithms , author =. Rev. Mod. Phys. , volume =. 2022 , month =. doi:10.1103/RevModPhys.94.015004 , url =

    work page doi:10.1103/revmodphys.94.015004 2022

  19. [19]

    Hassan and Peng, Lu , journal=

    LeCompte, Travis and Qi, Fang and Yuan, Xu and Tzeng, Nian-Feng and Najafi, M. Hassan and Peng, Lu , journal=. Machine-Learning-Based Qubit Allocation for Error Reduction in Quantum Circuits , year=

  20. [20]

    Quantum circuit mapping based on discrete particle swarm optimization and deep reinforcement learning , journal =

    Yang-Zhi Li and Wen Liu and Guo-Sheng Xu and Mao-Duo Li and Kai Chen and Shou-Li He , keywords =. Quantum circuit mapping based on discrete particle swarm optimization and deep reinforcement learning , journal =. 2025 , issn =. doi:https://doi.org/10.1016/j.swevo.2025.101923 , url =

    work page doi:10.1016/j.swevo.2025.101923 2025

  21. [21]

    Journal of Open Source Software , volume =

    Qiskit Experiments: A Python package to characterize and calibrate quantum computers , author =. Journal of Open Source Software , volume =. 2023 , doi =

    2023

  22. [22]

    Characterization of Addressability by Simultaneous Randomized Benchmarking , author =. Phys. Rev. Lett. , volume =. 2012 , month =. doi:10.1103/PhysRevLett.109.240504 , url =

    work page doi:10.1103/physrevlett.109.240504 2012

  23. [23]

    Suppression of Qubit Crosstalk in a Tunable Coupling Superconducting Circuit , author =. Phys. Rev. Appl. , volume =. 2019 , month =. doi:10.1103/PhysRevApplied.12.054023 , url =

    work page doi:10.1103/physrevapplied.12.054023 2019

  24. [24]

    High-Contrast ZZ Interaction Using Superconducting Qubits with Opposite-Sign Anharmonicity , author =. Phys. Rev. Lett. , volume =. 2020 , month =. doi:10.1103/PhysRevLett.125.200503 , url =

    work page doi:10.1103/physrevlett.125.200503 2020

  25. [25]

    Quantum , year=

    Enabling Multi-programming Mechanism for Quantum Computing in the NISQ Era , author=. Quantum , year=

  26. [26]

    arXiv preprint arXiv:2001.02826 , year=

    Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers , author=. arXiv preprint arXiv:2001.02826 , year=. doi:10.48550/arXiv.2001.02826 , url=

    work page doi:10.48550/arxiv.2001.02826 2001

  27. [27]

    Advanced Quantum Technologies , volume =

    Mao, Yikai and Shresthamali, Shaswot and Kondo, Masaaki , title =. Advanced Quantum Technologies , volume =. doi:https://doi.org/10.1002/qute.202500022 , url =. https://advanced.onlinelibrary.wiley.com/doi/pdf/10.1002/qute.202500022 , year =

    work page doi:10.1002/qute.202500022

  28. [28]

    2024 , eprint=

    LightSABRE: A Lightweight and Enhanced SABRE Algorithm , author=. 2024 , eprint=

    2024

  29. [29]

    2019 , isbn =

    Li, Gushu and Ding, Yufei and Xie, Yuan , title =. 2019 , isbn =. doi:10.1145/3297858.3304023 , pages =

    work page doi:10.1145/3297858.3304023 2019

  30. [30]

    2026 , eprint=

    A Quantum Multi-Programming Framework to Maximize Quantum Resources for the LUCJ Ansatz , author=. 2026 , eprint=

    2026

  31. [31]

    2022 , publisher =

    Matthew Treinish and Ivan Carvalho and Georgios Tsilimigkounakis and Nahum Sá , title =. 2022 , publisher =. doi:10.21105/joss.03968 , url =

    work page doi:10.21105/joss.03968 2022

  32. [32]

    2023 , isbn =

    Wille, Robert and Burgholzer, Lukas , title =. 2023 , isbn =. doi:10.1145/3569052.3578928 , booktitle =

    work page doi:10.1145/3569052.3578928 2023

  33. [33]

    Chemical Science , volume =

    Bridging physical intuition and hardware efficiency for correlated electronic states: the local unitary cluster Jastrow ansatz for electronic structure , author =. Chemical Science , volume =. 2023 , doi =

    2023

  34. [34]

    arXiv preprint arXiv:2506.20825 , year =

    Quantum-Centric Alchemical Free Energy Calculations , author =. arXiv preprint arXiv:2506.20825 , year =

    arXiv

  35. [35]

    arXiv preprint arXiv:2512.17130 , year =

    Molecular Quantum Computations on a Protein , author =. arXiv preprint arXiv:2512.17130 , year =. doi:10.48550/arXiv.2512.17130 , url =

    work page doi:10.48550/arxiv.2512.17130

  36. [36]

    arXiv preprint arXiv:2601.07872 , year =

    Quantum Computing and Visualization Research Challenges and Opportunities , author =. arXiv preprint arXiv:2601.07872 , year =. doi:10.48550/arXiv.2601.07872 , url =

    work page doi:10.48550/arxiv.2601.07872

  37. [37]

    arXiv preprint arXiv:2306.12346 , year =

    A Practical Overview of Quantum Computing: Is Exascale Possible? , author =. arXiv preprint arXiv:2306.12346 , year =

    arXiv

  38. [38]

    arXiv preprint arXiv:2112.07091 , year =

    Simultaneous Quantum Circuits Execution on Current and Near-Future NISQ Systems , author =. arXiv preprint arXiv:2112.07091 , year =

    arXiv

  39. [39]

    arXiv preprint arXiv:2512.01055 , year =

    Accelerating CCSD(T) on Graphical Processing Units (GPUs) , author =. arXiv preprint arXiv:2512.01055 , year =. doi:10.48550/arXiv.2512.01055 , url =

    work page doi:10.48550/arxiv.2512.01055

  40. [40]

    arXiv preprint arXiv:2411.15631 , year =

    Understanding and Estimating the Execution Time of Quantum Programs , author =. arXiv preprint arXiv:2411.15631 , year =. doi:10.48550/arXiv.2411.15631 , url =

    work page doi:10.48550/arxiv.2411.15631

  41. [41]

    Doubling down on open-access quantum computing , howpublished =

  42. [42]

    Physical Review X , volume =

    What Limits the Simulation of Quantum Computers? , author =. Physical Review X , volume =. 2020 , doi =

    2020

  43. [43]

    Lin, Wen-Hao and Liang, Fang and Motta, Mario and Zhang, Hao and McClean, K. M. Jr. and Sung, K. J. , title =. 2511.22476 , journal =

    arXiv

  44. [44]

    and Lu, Peihuang and Nocedal, Jorge and Zhu, Ciyou , title =

    Byrd, Richard H. and Lu, Peihuang and Nocedal, Jorge and Zhu, Ciyou , title =. SIAM Journal on Scientific Computing , volume =

  45. [45]

    and Wigner, E

    Jordan, P. and Wigner, E. , title =. Zeitschrift f. 1928 , doi =

    1928

  46. [46]

    and Haberland, Matt and Reddy, Tyler and Cournapeau, David and Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and Bright, Jonathan and van der Walt, St

    Virtanen, Pauli and Gommers, Ralf and Oliphant, Travis E. and Haberland, Matt and Reddy, Tyler and Cournapeau, David and Burovski, Evgeni and Peterson, Pearu and Weckesser, Warren and Bright, Jonathan and van der Walt, St. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python , journal =

  47. [47]

    Saki, A. A. and Barison, S. and Fuller, B. and Garrison, J. R. and Glick, J. R. and Johnson, C. and Mezzacapo, A. and Robledo-Moreno, J. and Rossmannek, M. and Schweigert, P. and others , title =. 2024 , howpublished =

    2024

  48. [48]

    doi:10.1021/acsomega.0c01148 , author =

    A Simple Method for Including Polarization Effects in Solvation Free Energy Calculations When Using Fixed-Charge Force Fields: Alchemically Polarized Charges , journal =. doi:10.1021/acsomega.0c01148 , author =

    work page doi:10.1021/acsomega.0c01148

  49. [49]

    doi:10.1021/acs.jcim.9b00962 , author =

    Benchmarking Electronic Structure Methods for Accurate Fixed-Charge Electrostatic Models , journal =. doi:10.1021/acs.jcim.9b00962 , author =

    work page doi:10.1021/acs.jcim.9b00962

  50. [50]

    and Evans, Alicia K

    Pitman, Samuel J. and Evans, Alicia K. and Ireland, Robbie T. and Lempriere, Felix and McKemmish, Laura K. , title =. The Journal of Physical Chemistry A , volume =. 2023 , doi =

    2023

  51. [51]

    2025 , doi =

    Quantum-Centric Computational Study of Methylene Singlet and Triplet States , journal =. 2025 , doi =

    2025

  52. [52]

    Journal of Computational Chemistry , volume =

    Sun, Qiming , title =. Journal of Computational Chemistry , volume =. doi:https://doi.org/10.1002/jcc.23981 , url =. https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcc.23981 , year =

    work page doi:10.1002/jcc.23981

  53. [53]

    Quantum-centric computation of molecular excited states with extended sample-based quantum diagonalization,

    Barison, Stefano and Robledo Moreno, Javier and Motta, Mario , title =. 2025 , month =. doi:10.1088/2058-9565/adb781 , url =

    work page doi:10.1088/2058-9565/adb781 2025

  54. [54]

    arXiv preprint arXiv:2503.10923 , year =

    Surface Reaction Simulations for Battery Materials through Sample-Based Quantum Diagonalization and Local Embedding , author =. arXiv preprint arXiv:2503.10923 , year =. 2503.10923 , archivePrefix =

    arXiv

  55. [55]

    arXiv preprint arXiv:2501.09702 , year =

    Quantum-Centric Algorithm for Sample-Based Krylov Diagonalization , author =. arXiv preprint arXiv:2501.09702 , year =. 2501.09702 , archivePrefix =

    arXiv

  56. [56]

    2023 , doi =

    Analytic Gradients for Selected Configuration Interaction , journal =. 2023 , doi =. doi:10.1021/acs.jctc.2c01062 , author =

    work page doi:10.1021/acs.jctc.2c01062 2023

  57. [57]

    and Zhang, X

    Li, G. and Zhang, X. and Cui, Q. , title =. J. Phys. Chem. B , year =

  58. [58]

    Monkey Patching

    Hunt, John. Monkey Patching. A Beginners Guide to Python 3 Programming. 2023. doi:10.1007/978-3-031-35122-8_43

    work page doi:10.1007/978-3-031-35122-8_43 2023

  59. [59]

    and Aktulga, H

    Manathunga, M. and Aktulga, H. M. and Götz, A. W. and Merz, K. M. , title =. J. Chem. Inf. Model. , year =

  60. [60]

    Cruzeiro, V. W. D. and Manathunga, M. and Merz, K. M. and Götz, A. W. , title =. J. Chem. Inf. Model. , year =

  61. [61]

    1996 , doi =

    Electron Correlation Effects in Molecules , journal =. 1996 , doi =. doi:10.1021/jp953749i , author =

    work page doi:10.1021/jp953749i 1996

  62. [62]

    Martin, Jan M. L. , title =. Israel Journal of Chemistry , volume =. doi:https://doi.org/10.1002/ijch.202100111 , eprint =

    work page doi:10.1002/ijch.202100111

  63. [63]

    Molecular Simulation , volume =

    Xiya Lu and Dong Fang and Shingo Ito and Yuko Okamoto and Victor Ovchinnikov and Qiang Cui and , title =. Molecular Simulation , volume =. 2016 , publisher =. doi:10.1080/08927022.2015.1132317 , note =

    work page doi:10.1080/08927022.2015.1132317 2016

  64. [64]

    and Kelly, Casey P

    Marenich, Aleksandr V. and Kelly, Casey P. and Thompson, Jason D. and Hawkins, Gregory D. and Chambers, Candee C. and Giesen, David J. and Winget, Paul and Cramer, Christopher J. and Truhlar, Donald G. , title =. 2020 , howpublished =

    2020

  65. [65]

    2023 , doi =

    Best Practices on QM/MM Simulations of Biological Systems , journal =. 2023 , doi =. doi:10.1021/acs.jcim.2c01522 , author =

    work page doi:10.1021/acs.jcim.2c01522 2023

  66. [66]

    Challenges for density functional theory,

    Challenges for Density Functional Theory , journal =. 2012 , doi =. doi:10.1021/cr200107z , author =

    work page doi:10.1021/cr200107z 2012

  67. [67]

    2020 , doi =

    Selected Configuration Interaction in a Basis of Cluster State Tensor Products , journal =. 2020 , doi =. doi:10.1021/acs.jctc.0c00141 , author =

    work page doi:10.1021/acs.jctc.0c00141 2020

  68. [68]

    2023 , doi =

    Modern Alchemical Free Energy Methods for Drug Discovery Explained , journal =. 2023 , doi =. doi:10.1021/acsphyschemau.3c00033 , author =

    work page doi:10.1021/acsphyschemau.3c00033 2023

  69. [69]

    2015 , note =

    Recent advances in QM/MM free energy calculations using reference potentials , journal =. 2015 , note =. doi:https://doi.org/10.1016/j.bbagen.2014.07.008 , url =

    work page doi:10.1016/j.bbagen.2014.07.008 2015

  70. [70]

    2023 , issn =

    Benefits of hybrid QM/MM over traditional classical mechanics in pharmaceutical systems , journal =. 2023 , issn =. doi:https://doi.org/10.1016/j.drudis.2022.103374 , url =

    work page doi:10.1016/j.drudis.2022.103374 2023

  71. [71]

    and Warrensford, Luke and Boresch, Stefan and Woodcock, H

    Kearns, Fiona L. and Warrensford, Luke and Boresch, Stefan and Woodcock, H. Lee , title =. Molecules , volume =. 2019 , number =

    2019

  72. [72]

    2022 , issn =

    Computer-aided drug design, quantum-mechanical methods for biological problems , journal =. 2022 , issn =. doi:https://doi.org/10.1016/j.sbi.2022.102417 , url =

    work page doi:10.1016/j.sbi.2022.102417 2022

  73. [73]

    Understanding Molecular Simulation (Second Edition) , publisher =

    Daan Frenkel and Berend Smit , title =. Understanding Molecular Simulation (Second Edition) , publisher =. 2002 , isbn =. doi:https://doi.org/10.1016/B978-012267351-1/50021-3 , url =

    work page doi:10.1016/b978-012267351-1/50021-3 2002

  74. [74]

    Understanding Molecular Simulation (Second Edition) , publisher =

    Daan Frenkel and Berend Smit , title =. Understanding Molecular Simulation (Second Edition) , publisher =. 2002 , isbn =. doi:https://doi.org/10.1016/B978-012267351-1/50025-0 , url =

    work page doi:10.1016/b978-012267351-1/50025-0 2002

  75. [75]

    Journal of Medicinal Chemistry , volume =

    De Vivo, Marco and Masetti, Matteo and Bottegoni, Giovanni and Cavalli, Andrea , title =. Journal of Medicinal Chemistry , volume =. 2016 , doi =

    2016

  76. [76]

    and Chodera, John D

    Shirts, Michael R. and Chodera, John D. , title =. The Journal of Chemical Physics , volume =. 2008 , issn =. doi:10.1063/1.2978177 , url =

    work page doi:10.1063/1.2978177 2008

  77. [77]

    Jorgensen and Erin M

    William L. Jorgensen and Erin M. Duffy , abstract =. Prediction of drug solubility from Monte Carlo simulations , journal =. 2000 , issn =. doi:https://doi.org/10.1016/S0960-894X(00)00172-4 , url =

    work page doi:10.1016/s0960-894x(00)00172-4 2000

  78. [78]

    A hybrid quantum computing pipeline for real world drug discovery , volume=

    Li, Weitang and Yin, Zhi and Li, Xiaoran and Ma, Dongqiang and Yi, Shuang and Zhang, Zhenxing and Zou, Chenji and Bu, Kunliang and Dai, Maochun and Yue, Jie and Chen, Yuzong and Zhang, Xiaojin and Zhang, Shengyu , year=. A hybrid quantum computing pipeline for real world drug discovery , volume=. Scientific Reports , publisher=. doi:10.1038/s41598-024-678...

    work page doi:10.1038/s41598-024-67897-8

  79. [79]

    Salo-Ahen, Outi M. H. and Alanko, Ida and Bhadane, Rajendra and Bonvin, Alexandre M. J. J. and Honorato, Rodrigo Vargas and Hossain, Shakhawath and Juffer, André H. and Kabedev, Aleksei and Lahtela-Kakkonen, Maija and Larsen, Anders Støttrup and Lescrinier, Eveline and Marimuthu, Parthiban and Mirza, Muhammad Usman and Mustafa, Ghulam and Nunes-Alves, Ari...

    2021

  80. [80]

    Warshel and M

    A. Warshel and M. Levitt , abstract =. Theoretical studies of enzymic reactions: Dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozyme , journal =. 1976 , issn =. doi:https://doi.org/10.1016/0022-2836(76)90311-9 , url =

    work page doi:10.1016/0022-2836(76)90311-9 1976

Showing first 80 references.