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Installation and License Questions / max_force_threshold

« Last post by caliskan on December 27, 2025, 07:44 »

Hello,
My script involves:

method = NVEVelocityVerlet(
initial_velocity=ConfigurationVelocities(remove_center_of_mass_momentum=True),
max_force_threshold=10.0 * eV / Angstrom,
)

Here, "max_force_threshold=10.0 * eV / Angstrom," somehow, causes an error:

"NL.ComputerScienceUtilities.Exceptions.NLTypeError: The parameter, max_force_threshold, must be a PhysicalQuantity with units of eV/Ang."

I believe, it should normally work but it ends up with this error.

Thanks for your help in advance,

General Questions and Answers / Questions about mace trainingset

« Last post by Lim changmin on December 23, 2025, 18:57 »

Hi QuantumATK Support Team,

I’m following the QuantumATK MACE machine-learning tutorial, and I have a few questions about how the TrainingSet(s) used in the tutorial were prepared.

How was the “tutorial TrainingSet” generated?

The tutorial provides a pre-made TrainingSet file. From what I can tell, it looks like crystal random displacements (CRD) may have been used to generate structures.

However, I’m not sure whether the dataset was created via the MTP tutorial-style workflow (e.g., Step 1: “MomentTensorPotential training” / “reference calculator” to label energies/forces/stresses), or if a different workflow was used.

Also, was the TrainingSet created with “Recalculate training data = True” (i.e., structures generated first and then re-labeled with a specified reference calculator), or were the labels produced directly at the time the structures were generated?

Could you clarify the exact workflow and tools used to produce the provided TrainingSet?

How was the amorphous-only TrainingSet produced (and with what DFT settings)?

I noticed another TrainingSet that seems to contain only amorphous structures. Could you share how those amorphous configurations were generated?

Were they obtained from AIMD trajectories (e.g., melt–quench), or were they produced by geometry optimization from some initial amorphous guess (or another sampling method)?

For the DFT labeling step: what k-point sampling was used (Γ-only vs. Monkhorst–Pack, and the specific mesh if applicable)?

If AIMD was used: were the AIMD steps also run at Γ-only and then re-labeled later with a denser k-mesh, or were they labeled with the final k-point settings from the beginning?

Any details you can provide (e.g., whether stresses were included, exact k-point mesh, basis set / pseudopotentials, XC functional, and whether re-labeling was performed) would be very helpful so I can reproduce the tutorial dataset preparation reliably.

Thank you

General Questions and Answers / Regarding the directionality of the gate voltage

« Last post by zwh on December 23, 2025, 08:34 »

Dear Expert,

I would like to ask for your guidance on gate voltage settings in device simulations:

1. In single-gate devices, symmetric materials show nearly identical current whether the gate is on top or bottom. However, Janus materials show large differences depending on gate position. What causes this asymmetry?

2. For dual-gate devices with symmetric top and bottom gates, how are gate voltages set in the IV Characteristics module? When sweeping from 0 V to 1 V over 11 points, does 1 V mean both gates are biased at 1 V? If so, won’t the opposing electric fields cancel each other, reducing net field strength and weakening channel control?

Your insights would be greatly appreciated.

General Questions and Answers / Why device density of states is not opening to visualize the curve ?

« Last post by techenthusiast on December 19, 2025, 06:35 »

Dear experts,

Why device density of states is not opening to visualize the curve ? It is opening as editor where the data is written after execution.

General Questions and Answers / Showing Memory allocation error for one job task execution_Reg.

« Last post by techenthusiast on December 17, 2025, 10:08 »

Dear sir,

Good afternoon, Hope you are doing well. it is showing --Showing Memory allocation error for one job task execution_Reg..

The device structure is like - 4 Cylindrical GAA FET (2X2) . 4 Devices are having 4 different common dielectric (30) & 4 different metal gate.

How to resolve the issues?

General Questions and Answers / Regarding questions of MTP error problem

« Last post by Lim changmin on December 15, 2025, 17:53 »

Hi, a few days ago, I posted some questions about MTP error(https://forum.quantumatk.com/index.php?topic=13336.0). From the reply, I tried to study MACE training potential, but didn't work out due to the fact that I didn't have GPU. So I returned to the MTP training, but an error occurred that I have never encountered.

This time the job terminates with many repeated warnings about the Study HDF5 file not existing, and then crashes with an HDF5 “truncated file” error leading to MPI_Abort.
UserWarning: The original file of the Study object 'GeTeCN_amor_train_gga.hdf5' no longer exists.
This means no task results will be saved to the new file.

During MTP training update / dataset construction, the run fails while reading an HDF5 file:

OSError: Unable to open file (truncated file: eof = 338986776, sblock->base_addr = 0, stored_eoa = 338986929)
File "zipdir/sergio/HDF5/HDF5.py", line 111, in __init__
File "/home/synopsys/quantumatk/X-2025.06/atkpython/lib/python3.11/site-packages/h5py/_hl/files.py", line 567, in __init__
OSError: Unable to open file (truncated file: eof = 338986776, sblock->base_addr = 0, stored_eoa = 338986929)
OSError: Unable to open file (truncated file: eof = 338986776, sblock->base_addr = 0, stored_eoa = 338986929)
fid = make_fid(name, mode, userblock_size, fapl, fcpl, swmr=swmr)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/synopsys/quantumatk/X-2025.06/atkpython/lib/python3.11/site-packages/h5py/_hl/files.py", line 231, in make_fid
fid = h5f.open(name, flags, fapl=fapl)
I attached the rest of the error script below file.

So here's the question
1. What exactly triggers the repeated warning:
“The original file of the Study object … no longer exists”?
Is this typically caused by launching the run from a temporary working directory (e.g., scratch/zipdir) where the original Study HDF5 is not available?
Is there a recommended way to set an absolute/persistent output path for the Study/Workflow files in Active Learning?

2. Regarding the fatal error:
HDF5 truncated file
Is this usually due to interrupted I/O (walltime kill, quota/full filesystem, network filesystem instability), or can concurrent MPI access to the same HDF5 also corrupt/truncate it?
In Active Learning MTP, which specific HDF5 file is being read at this stage (the Study file, a workflow state file, training dataset file, or something else)? Any tips to identify it deterministically?

3. What is the recommended restart/recovery procedure after an HDF5 truncation?
Should I delete/rename the corrupted HDF5 and restart from the last valid iteration?
Is there an official method to validate/repair the HDF5 (or is rollback the only safe option)?

I also attached slurm file and py file that I used

Thank you

General Questions and Answers / The GPU is not supported

« Last post by Roc2019 on December 14, 2025, 03:01 »

Dear Sir,

Recently, I did test the GPU performance of ATK2025.6 version on my GPU node with Tesla P100-PCIE-16GB cards.

However it prints the following errors,
###
The GPU is not supported. Verify that the GPU has CUDA compute capability 7 or
higher and is in compute mode.

Address this issue or run without CUDA acceleration.
####

So, does it mean the code can not work with the Tesla P100-PCIE-16GB cards?

In addition, it can work with my another node with NVIDIA GeForce RTX 4090

Thanks so much.

Roc

General Questions and Answers / Re: Difference Between electrode_extension_lengths and equivalent_electrode_lengths

« Last post by kaihuang on December 7, 2025, 21:17 »

Would an expert be able to answer this question?

Scripts, Tutorials and Applications / electron phonon coupling as function of fermi shift

« Last post by huang96 on December 2, 2025, 16:52 »

I have a question about electron-phonon coupling simulation in Quantum ATK.
I was following this guide https://docs.quantumatk.com/tutorials/mobility/mobility.html to set up a model to calculate the e-ph coupling rate of graphene.
Also referred to this https://spdocs.synopsys.com/dow_retrieve/qsc-x/seg/quantumatk/X-2025.06/manual/Types/ElectronPhononCoupling/ElectronPhononCoupling.html to know how the function works.

Here comes the problem, I think e-ph coupling rate is a function of graphene's fermi level.
However, I cannot tune it either in the interface window nor the python codes.
For example, in the codes, it is like below where no input parameters as 'fermi shift'

electron_phonon_coupling = ElectronPhononCoupling(
configuration=optimized_configuration,
hamiltonian_derivatives=hamiltonian_derivatives,
dynamical_matrix=dynamical_matrix,
kpoints_fractional=kpoints_fractional,
qpoints_fractional=qpoints_fractional,
electron_bands=All,
energy_tolerance=0.01 * eV,
initial_state_energy_range=[-0.4, 0.4] * eV,
)

I do find one 'fermi shift' in the definition of inverseLfieTime:

inverse_life_time = electron_phonon_coupling.inverseLifeTime(phonon_modes=All, electron_bands=All, temperature=300*Kelvin, fermi_shift=0.0*eV, integration_method=GaussianBroadening(), refinement=1)

But it cannot be plot properly.
So by any chance anyone can take a look to see how to get a simulation result of e-ph coupling rate as function of fermi shift ?
Thanks in advance.

General Questions and Answers / Re: Questions Regarding GPU Acceleration

« Last post by filipr on November 28, 2025, 11:18 »

We have recently been made aware that Nvidia has implemented algorithms that can do linear algebra operations using emulated floating point operations on tensor cores on GPUs that do not necessarily have many native FP64 units such as RTX 6000: https://developer.nvidia.com/blog/unlocking-tensor-core-performance-with-floating-point-emulation-in-cublas/

This requires using the newest CUDA version (and probably also newest drivers). We have not had time to do any experiments with this, but feel free to try yourself. Note that QuantumATK ships with CUDA 12.2, so you will have to modify the launcher script (bin/atkpython is just a Bash script that sets LD_LIBRARY_PATH and other relevant environment variables) so that the program picks up the right CUDA libraries.