Supplemental data for our article "A Quantum Definition of Molecular Structure". Version 1.1.0 contains data for additional k-medoids runs performed on different subsets of the complete sample.

Molecular structure, a key concept of chemistry, has remained elusive from the perspective of all-particle quantum mechanics, despite many efforts. Viewing molecular structure as a manifestation of strong statistical correlation between nuclear positions, we propose a practical method based on Markov chain Monte Carlo sampling and unsupervised machine learning. Application to the D3+ molecule unambiguously shows that it possesses an equilateral triangular structure. These results provide a major step forward in our understanding of the molecular structure from fundamental quantum principles.

The dataset consists of a graphical language for describing quantum phenomena and meaning-related linguistic phenomena.

Supplemental data for our article "A Quantum Definition of Molecular Structure".

The use of nuclear spins for quantum computation is limited by the difficulty in creating genuine quantum entanglement between distant nuclei. Current demonstrations of nuclear entanglement in semiconductors rely upon coupling the nuclei to a common electron, which is not a scalable strategy. Here we demonstrate a two-qubit Control-Z logic operation between the nuclei of two phosphorus atoms in a silicon device, separated by up to 20 nanometers. Each atom binds separate electrons, whose exchange interaction mediates the nuclear two-qubit gate. We prove that the nuclei are entangled by preparing and measuring Bell states with a fidelity of 76 +/- 5% and a concurrence of 0.67+/- 0.05. With this method, future progress in scaling up semiconductor spin qubits can be extended to the development of nuclear-spin based quantum computers., , , # Scalable entanglement of nuclear spins mediated by electron exchange

https://doi.org/10.5061/dryad.brv15dvm5

Description of the data

This is accompanying data for the journal article 'Scalable entanglement of nuclear spins mediated by electron exchange'.

Outline of the dataset

The dataset consists of the following folders:

1 - Main_text

This folder contains the experimental data used to generate the figures in the main text of the article. It also contains the Jupyter notebook file 'Main_text_figure_plotting.ipynb', which can be used to plot this data. The data is partitioned into subfolders for each paper figure. The naming convention of the data is the following: #A_B_C where A is the number of the measurement for that date (i.e. #1 means this was the first measurement run that day for a given date), B is the name of the measurement that was run and C is the time at which the measurement was run in the format ...,

The conversion of integral single analogue files into the digital domain remains toundermine the integrity and the fidelity of the real-world source of recorded capturethrough signal chopping, even as technology has advanced significantly within theseareas. This study shows significance in the investigations of various requirements ofsuch conversion in order to understand the effects (both advantageous and adverse) ithas had on the source signal and therefore why technological advancements towards thebetterment of fidelity (and reduction in losses thereof) have been undertaken, andpresently continue to do so. In order for a means for the sound heard naturally to beheard in the same fashion through recorded means, it was contemplated as necessary toconsider the eradication of the binary Pulse Code Modulation system and all it’sadvanced attempts to better it in favour of researching new theories. Currentadvancements in capture technology as well as environmental sound reconstructionprocesses have inspired future design considerations using developmental technologiesdiscovered and advancing in a non-binary computing domain. The rise of such a domainis reflected upon for future audio production aspects.

The dataset consists of a graphical language for describing quantum phenomena and meaning-related linguistic phenomena.

Simulation data for paper: "Variational approach to open quantum systems with long-range competing interactions". Full article accessible under https://arxiv.org/abs/2510.01543Overview: This datasets contains simulation data presented in figures 1-6 in the Main Text and figures 2-61 in the Supplementary Material. This data was obtained from t-VMC+MPO (the method introduced in the above article) and t-MPS simulations. t-VMC+MPO is a method for efficient and scalable simulation of the dynamics of open quantum lattices. It relies on solving the variational equations of motion efficiently by means of time-dependent variational Monte Carlo (t-VMC), while employing compact matrix product operator (MPO) trial states for the many-body density matrix. Among its other advantages, this method is suitable for simulating large driven-dissipative lattices with multiple long-ranged interactions.Implementation: A Julia implementation of t-VMC+MPO (termed t-VMPOMC), which was used to generate this dataset, is available at the public GitHub repository https://github.com/dhryniuk/t-VMPOMC. This repository contains example simulation scripts aimed to make the method accessible for first-time users. Directory and file organisation: For the Main text, the data is divided first by figure/subplot index, and second by simulation type (please refer to the relevant figure in the article). For the Supplementary Material, the data is divided first by the optimisation hyperparameter label, for which convergence was analysed, and second by model. The folder names specify the model via initialism: I - Ising, C - competing, XYZ - the XYZ model, e.g. the folder name "CI_N200_strong" will contain simulation data for an spin chain of N=200 sites with strong long-ranged competing Ising interactions. Relevant parameter and hyperparameter values distinguishing individual simulations are included in the folder titles. Remaining parameter values not specified can be found in tables 1 and 2 in Supplementary Note 3 on pages 57-59. Explanation on t-VMPOMC simulations data file names and structure: "obs.out" - m_x, m_y, m_z, S_2 expectation values per iteration; "corrD.out" - D_local C_xx, C_yy, C_zz correlation functions per iteration; "times.out" - recorded simulation time t per iteration, "iter_times.out" - wall time per iteration; "C.out" - cost function value per iteration; "lambda.out" - smallest eigenvalue of reduced density matrix per iteration; "Schmidt_values.out" - Schmidt singular values per iteration.

onlineAppendix1R functions used to calculate the geometric mean of favourabilities (equation 3) and its increment (equation 4)

Research Data for: "On the meaning of de-excitations in time-dependent density functional theory computations" by F. Plasser.Contents (folders and files are given in bold)STRUC_*deg: Parent folder for a given torsion angleFor each torsion angle subfolders for the various computations are provided, e.g., PBE0.rpa, PBE0.tda, PBE0.uks, PBE.rpa. Note that "rpa" refers to full TDDFT as this is the keyword used within Q-Chem. "rpa-sing" refers to a computation with only singlets in cases where the triplets had convergence issues.These containQ-Chem input/output files: qchem.[in/out]Coordinates: coord.qcinSummary of libwfa results: libwfa_summ.txt

We investigate the nature of quantum jumps occurring between macroscopic metastable states of light in the open driven Jaynes-Cummings model. We find that, in the limit of zero spontaneous emission considered in Carmichael (2015), the jumps from a high-photon state to the vacuum state entail two stages. The first part is coherent and modelled by the localization of a state superposition, in the example of a null-measurement record predicted by quantum trajectory theory. The underlying evolution is mediated by an unstable state (which often splits to a complex of states), identified by the conditioned density matrix and the corresponding quasiprobability distribution of the cavity field. The unstable state subsequently decays to the vacuum to complete the jump. Coherence in the localization allows for inverting the null-measurement photon average about its initial value, to account for the full switch which typically lasts a small fraction of the average cavity lifetime; an asymptotic law for the jump time is established in high-amplitude bistability. This mechanism is contrasted to the jumps leading from the vacuum to the high-photon state in the bistable signal. Spontaneous emission degrades coherence in the localization, and prolongs the jumps.

The datasets in the .mat files (MATLAB) correspond to the paper figure indicated in each filename. They are primarily generated from the code JCRK4_Amp_Bist.m (solving the matrix elements equations of motion by employing a 4th order Runge-Kutta method) as well as JCBist.cc (refer to the C++ library used for quantum trajectories in the main text). The code JCRK4_Amp_Bist_Kerr.mat is used only for generating data for Fig. 8, while for Fig. 6 a subset of data used for Fig. 5 has been deployed. The conditioned Q functions and density matrix barplots are generated using Qfunction.m, while steady-state results have been generated using Qfunc_bist.m (from Quantum Optics Toolbox). The code neoclassical.m generates the mean-field bistability curve pictured in Fig. 9.

1. Repository Information

This repository contains the data produced during the work discussed in in the paper "Towards quantum gravity with neural networks: Solving quantum Hamilton constraints of 3d Euclidean gravity in the weak coupling limit". Please refer to this paper for more details on how the data was produced.

2. Citing

In addition to citing this repository, please also cite the paper mentioned above if you use the data. The citation is:

Hanno Sahlmann and Waleed Sherif 2024 Class. Quantum Grav. 41 215006

3. File Description

In this repository, you will find 4 general directories (here called parent directories):

1. Ground Energy + Fluctuations
2. Misc
3. Quantum Constraint
4. Volume

Each of these directories correposnd to different data produced and discussed in the corresponding parts in the paper mentioned above (e.g. the directory "Ground Energy + Fluctuations" contains the data used in Table 1 and Table 2 in the paper while the "Volume" directory contains the data used in Section 4.3 of the paper).

Some of these parent directories, which involve simulations solving constraints, contain within them several sub-directories (child directories) corresponding to different produced data. The raw data of the simulation can be found in a .json file inside the child directories.

4. Usage

4.1 Raw Simulation Data

The .json files include the raw data produced during the study. These files can be easily accessed using a python script, as an example, by using:

import json

filePath = ...

data = json.load(open(filePath))

where filePath should hold the correct path to the local data once downloaded. Once loaded, the data is handled as a python dict.

The dictionary will have at least one parent key called "Energy". The data in the "Energy" key corresponds to the data being minimised. The data in any other parent key correspond to operators which were being observed during the simulation. For example, in the data in the "Quantum Constraint" directory, some .json files will have multiple parent keys such as FG, H, HG, .... Each of these keys correspond to different operators which were observed during that simulation. Each parent key is yet another dictionary in itself. The structure of the dictionaries corresponding to any parent key are always the same and always include the keys:

• iters
• Mean
• Variance
• Sigma
• R_hat
• TauCorr

Hence, to access the "Mean" values, you use data["Energy"]["Mean"] (or alternatively data["FG"]["Mean"] if you wish to observe the value of the F + G operator during the simulation). The data represents the values during a simulation of typically 500 iterations, hence, each of the keys mentioned above will correspond to an array of 500 items. The iters array includes merely the iteration number. The Mean array includes the value of the expectation value of the constraint at the corresponding iteration. The Variance, Sigma, R_hat and TauCorr includes the values of the variance and error in the expectation value at the given iteration as well as the split R-hat diagnostic and the time correlation also in the given iteration.

4.2 Variational State Data

The files for the variational arrays are too large to be uploaded to a general repository hosting service. Therefore, they will be provided directly upon request in a direct download link. Please contact the author of the paper (Waleed Sherif, email: waleed.sherif@fau.de) for accessing the data.

4.3 Fluctuation results

In some child directories, there will be a .txt file which includes the output of the calculation of the expectation value of some operators and their quantum fluctuations. These are only results, and not data, as the data can only be computed during the simulation.

4.4 Probabilities

The "Misc/Probabilities" directory contains .npy files which should be handled in the same manner as the variational states. These files correspond to the probability simulations conducted in section 4.4.4 in the paper.

5. Contact

Shall you have any unanswered questions regarding the usage of the data, please contact the author:

Waleed Sherif

email: waleed.sherif@fau.de

6. References

The data provided in this repository was produced using the NetKet[1] package

[1] doi: 10.21468/SciPostPhysCodeb.7

The theory of quantum mechanics provides the means to calculate the structure of molecules, and how molecules will behave. The calculations are complicated, partly because a molecule has many interacting components, and partly because of the intrinsic complications of quantum mechanics itself. Exact quantum mechanical results can be obtained for the simplest of systems, but for real problems, approximations are needed. The field that produces these approximations, then converts them into usable software tools is molecular electronic structure theory. It turns out that the most highly cited papers in chemistry describe breakthroughs in molecular electronic structure theory. The reason is that these methods can be applied universally: they can inform us about the structure and reactivity of any molecule, so they are used by an enormous range of chemists. Currently two approximations dominate the field, density functional theory (DFT) and coupled cluster theory (CC). The first is very efficient (ie runs quickly on computers) and the second is amazingly accurate for many problems. There has been a great deal of progress in making DFT more accurate, and CC theory more efficient; our group has been involved in some of these efforts. In this proposal we set out a new branch of molecular electronic structure theory, based on the concept of treating the electrons one pair at a time, but with each pair embedded in a model provided by the rest of the molecule. These methods could be revolutionary, because their cost appears not much greater than that of DFT, but their accuracy could be competitive with CC theory. Now is the right time for this research partly because of the demand for better theoretical methods; and partly because recent breakthroughs in quantum embedding theory give a remarkable opportunity to build new and potentially amazing electronic structure methods. Complete download (zip, 885 MiB)

In this theoretical thesis we apply the time-delayed Pyragas feedback scheme to several many-body quantum systems in order to control the quantum phases in a rather new way. The systems are the dissipative Dicke model, the dissipative Lipkin-Meshkov-Glick (LMG) model and a two-mode Tavis-Cummings laser. In the dissipative Dicke model our chosen way of feedback control, namely the modulation of the atom-field coupling by a difference of emitted photon numbers at different times, creates additional new quantum phases. These show up as an infinite sequence of super- and subcritical Hopf bifurcations of the stationary state by generation of stable and unstable limit cycles. We analyze and discuss the appearing bifurcations as a function of time delay and feedback strength and calculate an analytical expression for the phase boundaries. On top of this, we argue that our scheme is easy to implement within existing experimental setups, as in experiments the coupling is tuned by laser intensity. In the dissipative LMG model we investigate how the dissipation affects the excited state quantum phase transition (ESQPT). We show that with dissipative effects the ESQPT is directly visible in the spectrum of the effective Hamiltonian and not only in the density of states. Moreover, the ESQPT signal in the system observables gets smoothed. Then we use time delayed feedback control to restore the ESQPT signal by creation of new phases. We analyze and discuss the behavior of the system for different time delays. We argue that using our feedback scheme it is easier to measure ESQPT in the open LMG system than without it in the closed one. Then we use a 2-mode laser based on the Tavis-Cummings model with additional incoherent pumping and decay channels. Instead of the usually used rate-equation model, we describe the two-mode laser starting from a quantum mechanical description and present an analytical solution of the corresponding stationary mean-field equations in thermodynamic limit. We analyze the stationary solutions and their stability and obtain a complex phase diagram with up to 4 fixed points. In addition to this, we apply different time delayed Pyragas feedback control schemes, which allow us to influence the laser dynamic. The frequency of the emitted laser light can be controlled then or an unstable fixed point stabilized. In this way, our thesis links the topics of control, phase transitions and dissipation together which induce an interesting and unexpected dynamics in quantum many-body systems. Although all final calculations are at the mean-field level, we hold them to be valid in thermodynamic limit.

The dataset consists of two files: Paper_Figures_Data.pkl Paper_Figures_Data_Resubmission.pkl These files contain the numerical data used to generate the figures in both the main text and supplementary materials of the associated research article. All data were obtained using Density Matrix Renormalization Group (DMRG) calculations for a bosonic ladder model with varying parameters. Contents: Paper_Figures_Data.pkl contains the replication data for the figures presented in the main text: Figure 2: (a) Entanglement entropy SvN, (b) P, and (c) the maximum of the structure factor S(k) for k ≠ 0, computed for a ladder with L = 96 rungs. Figure 3: Structure factor S(k) for t/V = 0.05 as a function of Δ/V, calculated for L = 12, 24, 48, and 96. Peaks at incommensurate k values that become continuous with increasing L illustrate the floating phase. Figure 4: (a) P and (b) the central charge c, both obtained via finite-size scaling ∼1/L for t/V = 0.05 using DMRG. Calculations were performed with χ = 600 for L ∈ {60, 72, 84, 96}. Error bars are shown for each data point. Paper_Figures_Data_Resubmission.pkl contains the replication data for the supplementary material: Figure S3: Structure factor S(k) for t/V = 0.05, as a function of Δ/V, for L = 12, 24, 48, and 96. Figure S4: Structure factor S(k) for t/V = 0.3 and t⊥/t = 0.1, as a function of Δ/V, for L = 12, 24, 48, and 96. File format: The data are stored as Python pickle (.pkl) files and can be read using Python’s pickle module. A sample script (tree.py) is included to browse the file contents. Data fields (file Paper_Figures_Data.pkl): Common: 'DeltaV_list' (Δ/V values), 'tV_list' (t/V values) Figure 2: 'EntEntrs', 'PLams', 'Skmax'. These arrays have dimensions corresponding to the number of items in 'DeltaV_list' and 'tV_list', and they represent panels (a), (b), and (c) of Figure 2 in the main text, respectively. Figure 3: 'Skcuts'. Array of shape (5, 200, 51). The first dimension corresponds to four system sizes L and an extrapolation to L → ∞. The other two axes represent Δ/V (51 values) and k between -π and π (200 values), Figure 4: 'PLamcut', 'ccut', 'OScut'. These contain lists of (value, error) pairs and correspond to quantities shown in Figure 4: P and the central charge c, obtained via finite-size scaling for t/V = 0.05, using DMRG data for L ∈ {60, 72, 84, 96}. 'Oscut' shows a similar string order (not shown in Fig 4) fit Data fields (file Paper_Figures_Data_Resubmission.pkl): 'SkcutsNNN': Structure factor data corresponding to Figure S3. Array of shape (5, 200, 81), where the first dimension spans four system sizes L and an extrapolation to L → ∞. The second and third dimensions correspond to momentum k (sampled between –π and π) and Δ/V (sampled uniformly between 3 and 5), respectively. 'Skcutsty': Structure factor data corresponding to Figure S4. Same array shape and axis meaning as above: (5, 200, 81) = (L, k, Δ/V). All arrays are stored in NumPy format within the pickle files and are structured for direct plotting and analysis.

This is a collection of saddle-point solutions for SU(N) Heisenberg modes on triangular and honeycomb lattices. They are obtained by simplifying the SU(N) Heisenberg Hamiltonian in the large-N limit and apply a self-consistent minimization algorithm to the derived mean-field Hamiltonian. The binary programs and Mathematica notebooks are included together for data generation, analysis and visualization.

The acid dissociation constant (pKa) has an important influence on molecular properties crucial to compound development in synthesis, formulation, and optimization of absorption, distribution, metabolism, and excretion properties. We will present a method that combines quantum mechanical calculations, at a semi-empirical level of theory, with machine learning to accurately predict pKa for a diverse range of mono- and polyprotic compounds. The resulting model has been tested on two external data sets, one specifically used to test pKa prediction methods (SAMPL6) and the second covering known drugs containing basic functionalities. Both sets were predicted with excellent accuracy (root-mean-square errors of 0.7–1.0 log units), comparable to other methodologies using a much higher level of theory and computational cost.

Gerhard Ris former lawyer and magistrate with thirty years of experience in courts of law

Inverse final statements

· Science Starts with Descartes & Discarding Descartes

· The proper scientific procedure for starting with inverse final statements is as long as needed and as short as possible.

· Flying an aircraft in an emergency is also scientific in science proper.

· Producing proper science requires a multi-majority consensus in eight departments of the collective instrument brain, which can be achieved by following its now-available Train Your Intuitive Brain instruction manual the One Law of Human Nature.

· Teaching Empowerment White Magic Illusionism alas also teaches Black Magic illusionism

· Being Empowered by White or Black Magic Illusionism has immediate rewards

· Deciding to do the proposed Oracle Senate Test by any oligarch such as the Dutch Research Council NWO will instantly shift the paradigm, producing peace and prosperity for all and especially benefiting NATO.

· Homo Sapiens hasn’t even lived for one galactic year and is nearing extinction playing with nukes.

· The One Law of Human Nature proves that most mathematicians and physicists are, as a genotype, deep idiots at more than average complex geometry. Yet they have oligarch power in science via improper peer review. They use computers to fraudulently claim to be the best at complex geometry because they are indeed best at computing.

· The current paradigm procedure requires naming, shaming, and ridiculing NWO for failing the improved Elementary Scientist Exam as science proper.

· This can best be done by other than Dutch scientists who aren’t dependent on funding from NWO because the effect is global.

· NWO thus isn’t certified as a reliable source for funding Elementary Science and Education like Dada Easter Bunny.

· Current science incorrectly doesn’t accept humour and relativism as a per definition essential part of the marketing, advertisement, and sales of science. Current science demands autistic deadly serious tediously dull conscientiousness a deadly sin in artistic R&D.

· Current science and NWO don’t have a definition of science or pseudo-science other than oligarchs of science peer review deem to be scientific. This falsifies current science on elementary issues.

· NWO is most guilty of the mainstream woke madness in most universities which is antifeminism, racist slaveholding egotrip of gender-neutral female logic better seen as sales management/ HRM hypnotic relation manipulation. A Bayesian inversion of the synapse in the instrument brain. Needing to keep antifeminism, racism, and slavery going because otherwise losing their meaning in life.

· NWO is also most guilty of the anti-scientific polarisation against science and scientists in society as a reaction to the actions of wokeism.

· NWO primarily caused the serious intended cuts in science and education in the Netherlands.

· NWO is a representative of the greatest bosses of god delusion of the god that doesn’t listen.

· NWO represents a criminally insane personality cult that for 5000 years has successfully built ever better “unsinkable” Titanics and sunk them in the same peat-burn-like genocidal iceberg scenario.

· When you do the same the same happens.

· The Oracle Senate Test is akin to the first flight of a prototype exclusively built out of successfully tested parts.

· The New Secretary General of NATO nearly decided to do the then still too taboo even for PM Mr. Teflon's radical plan for new governance Oracle Senate Test by an emergency law in the Omtzigt affaire.

· More than 99.9% of Old School tried and tested Sun Tzu's Art of War to never corner one's opponent and always build them a Golden Bridge way out.

· Save Our Mighty Billionaires and all other oligarchs like NWO!

· The cosmos/ everything is proven on the beginning of absolute proof in the reductio ad absurdum that our instrument brain thinks in an everything not only nothing and observes One Law of Nature that is absolute without contradictions including loopholes by far proven best practice circumstantial evidence proof with only data pro and absolutely no data con in all of several fields DOI published in proper peer review with access to all the raw data. Completely theorem based on what all the science was in, ages ago only requiring a few new easy twists to solve. The validation rises every time no valid opposition is met on the inherently circular argument claim that workability (werkelijkheid in Dutch) is an infinite topology of truths and infinite realities that only seemingly ever contradict in one of infinite parallel and in-line Nirvana movie scenario compositions achieving very practical workability (werkbaarheid in Dutch)

· Everything of the deterministic meaningless cosmos has infinite separate elements of classical mechanical Eucledian 3D geometry mass atomos movable connections that interact akin to snowballs in one 3D Euclidian empty space ether. The observed absence of evidence only leaves room for illegal unreasonable doubt on the correct definition of science which is further improved in this article. The 3rd law of everything as an undividable part of the ten dualistic laws of one law of nature dictates the scientific goal by one law of human nature the decent survival of homo sapiens that life has meaning and free will. The cosmos is both quantified and continuous at the same time in infinite time. Time is a thought and a thought is interactive moving timeless mass. Mass is internally absolutely motionless and thus can not be described by the notion of time. Mass is lifeless. Mass produces matter in a proto-DNA waving life non-waving proto-death cycle. Internal waves are proto-DNA consciousness memory bank of intelligent action is intelligent reaction infinite past moving toward an infinite future.

· Homo sapiens are proven to be robots that must inherently religiously believe not to be robots to hedge the bets on the goal of decent survival. The easiest to detect is the 1/64 specific sort of genotype of anyone which is also the greatest predictor of human behavior. In decreasing predictive order on behavior, the model proves phenotype (deeply religious), religious type, hypnotic (slightly religious)type, and unique type that all must be taken into account. This can only be done by the well-trained brain in an intuitive brain as part of a team with Bildung.

· The model proves that bashing opens a new market in litigation. This should be done via advertisement and sales techniques. This can only be achieved by any oligarch like NWO. NWO is in the know and is thus the easiest prey. Observe the thumbnails as the posters that science proper demands at the end of this article. These are a startup of the classes that as remedial teaching should be given in universities because they weren’t given in high school.

RECAP EXCERPT DOI PUBLICATIONS

Add this trial and erratum to my last publication

During the last few decades, considerable advances in quantum information theory have shown deep existing connections between quantum correlation effects (like entanglement and quantum discord) and thermodynamics. Here the concept of conditional entropy plays a considerable role. In contrast to the classical case, quantum conditional entropy can take negative values. This counter-intuitive feature, already well understood in the context of information theory, was recently shown theoretically to also have a physical meaning in quantum thermodynamics [del Rio et al. Nature 2011, 474, 61]. Extending this existing work, here we provide evidence of the significance of negative conditional entropy in a concrete experimental context: Incoherent Neutron Scattering (INS) from protons of H2 in nano-scale environments; e.g., in INS from H2 in C-nanotubes, the data of the H2 translational motion along the nanotube axis seems to show that the neutron apparently scatters from a fictitious particle with mass of 0.64 atomic mass units (a.m.u.)—instead of the value of 2 a.m.u. as conventionally expected. An independent second experiment confirms this finding. However, taking into account the possible negativity of conditional entropy, we explain that this effect has a natural interpretation in terms of quantum thermodynamics. Moreover, it is intrinsically related to the number of qubits capturing the interaction of the two quantum systems H2 and C-nanotube. The considered effect may have technological applications (e.g., in H-storage materials and fuel cells).

Abstract We present the 10th revision of the pi7 code, a program to calculate the electronic structure of ionic materials by means of theab initio Perturbed Ion (aiPI) method. The program has been extensively optimized and partially vectorized since the last published version, significantly improving its performance. Two completely new modules have been incorporated into the main code. The first of them computes interionic potentials directly from theaiPI solution, and the second one introduces a ...

Program title: pi7r10 Catalogue ID: ACNZ_v2_0 [ADFT]

Nature of Problem Ab initio determination of the electronic structure and properties of ionic materials, including pure and defective crystals and isolated finite clusters.

Versions of this program held in the CPC repository in Mendeley Data ACNZ_v2_0; pi7r10; 10.1016/S0010-4655(97)00030-1

This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)