| Name | qarray-rust-core JSON |
| Version |
1.3.1
JSON |
| download |
| home_page | None |
| Summary | None |
| upload_time | 2024-09-18 18:36:48 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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No Travis.
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# qarray-rust-core
**Quantum Dot Constant Capacitance Simulator** is a high-performance Python package that leverages the power of Rust and Rayon to provide a fully parallelised and optimised simulation environment for quantum dots with constant capacitance.
**This package provides core functionality; it is not intended that the user will interact with it directly.**
## Features
- **Ultra-fast Simulation:** Harnesses the speed of Rust and the parallelism of Rayon to deliver lightning-fast simulations.
- **Constant Capacitance:** Specialized for simulating quantum dots with constant capacitance, allowing precise modelling of charge dynamics.
- **User-Friendly:** Designed with ease of use in mind, making it accessible to both experts and newcomers in quantum dot simulations.
- **Extensive Documentation:** Comprehensive documentation and examples to help you get started quickly.
## Installation
Install Quantum Dot Constant Capacitance Simulator using pip:
```bash
pip install qarray-rust-core
```
### Usage
This package exposes two functions to be called from python:
- `ground_state_open` - computes the lowest energy state of a quantum dot array with constant capacitance and which is open, such that the total number of changes is not fixed.
- `ground_state_closed` - computes the lowest energy state of a quantum dot array with constant capacitance and which is closed, such that the total number of changes is fixed.
The python code to call these functions is as follows:
```python
from qarray-rust-core import (ground_state_open, ground_state_closed)
import numpy as np
# the dot-dot capacitance matrix
cdd = np.array([
[1, -0.1],
[-0.1, 1]
])
cdd_inv = np.linalg.inv(cdd)
# the dot-gate capacitance matrix
cgd = np.array([
[1, 0.3],
[0.3, 1]
])
# define a matrix of gate voltages to sweep over the first gate
vg = np.stack([np.linspace(-1, 1, 100), np.zeros(100)], axis = -1)
n_charge = 3 # the number of changes to confine in the quantum dot array for the closed case
threshold = 1 # threshold to avoid having to consider all possible charge states, setting it 1 is always correct, however has a computatinal cost.
n_open = ground_state_open(vg, cgd, cdd_inv, threshold, T = 0)
n_closed = ground_state_closed(vg, n_charge, cgd, cdd, cdd_inv, threshold, T = 0)
```
**It is not intended the user ever call these functions directly.**
There is a pure Python wrapper that provides a more user-friendly interface to this core functionality.
See [Quantum Dot Constant Capacitance Simulator](https://github.com/b-vanstraaten/rusty_capacitance_model). This package provides:
- **A user-friendly interface** to the core functionality.
- **Plotting, charge sensing, virtual gate** and gate voltage sweeping (1d and 2d) functionality.
- **Advanced type checking** using pydantic.
- **Automated testing** including for the functionality in this package.
- **More examples**.
Raw data
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"description": "# qarray-rust-core\n\n\n\n\n\n\n\n**Quantum Dot Constant Capacitance Simulator** is a high-performance Python package that leverages the power of Rust and Rayon to provide a fully parallelised and optimised simulation environment for quantum dots with constant capacitance.\n\n**This package provides core functionality; it is not intended that the user will interact with it directly.**\n\n## Features\n\n- **Ultra-fast Simulation:** Harnesses the speed of Rust and the parallelism of Rayon to deliver lightning-fast simulations.\n- **Constant Capacitance:** Specialized for simulating quantum dots with constant capacitance, allowing precise modelling of charge dynamics.\n- **User-Friendly:** Designed with ease of use in mind, making it accessible to both experts and newcomers in quantum dot simulations.\n- **Extensive Documentation:** Comprehensive documentation and examples to help you get started quickly.\n\n## Installation\n\nInstall Quantum Dot Constant Capacitance Simulator using pip:\n\n```bash\npip install qarray-rust-core\n```\n\n\n### Usage\n\nThis package exposes two functions to be called from python: \n\n- `ground_state_open` - computes the lowest energy state of a quantum dot array with constant capacitance and which is open, such that the total number of changes is not fixed. \n- `ground_state_closed` - computes the lowest energy state of a quantum dot array with constant capacitance and which is closed, such that the total number of changes is fixed.\n\nThe python code to call these functions is as follows:\n\n ```python\n from qarray-rust-core import (ground_state_open, ground_state_closed)\n import numpy as np \n \n # the dot-dot capacitance matrix\n cdd = np.array([\n [1, -0.1],\n [-0.1, 1]\n ])\n cdd_inv = np.linalg.inv(cdd)\n \n # the dot-gate capacitance matrix\n cgd = np.array([\n [1, 0.3],\n [0.3, 1]\n ])\n \n # define a matrix of gate voltages to sweep over the first gate\n vg = np.stack([np.linspace(-1, 1, 100), np.zeros(100)], axis = -1)\n \n n_charge = 3 # the number of changes to confine in the quantum dot array for the closed case \n threshold = 1 # threshold to avoid having to consider all possible charge states, setting it 1 is always correct, however has a computatinal cost. \n \n n_open = ground_state_open(vg, cgd, cdd_inv, threshold, T = 0)\n n_closed = ground_state_closed(vg, n_charge, cgd, cdd, cdd_inv, threshold, T = 0)\n ```\n**It is not intended the user ever call these functions directly.**\n\nThere is a pure Python wrapper that provides a more user-friendly interface to this core functionality. \nSee [Quantum Dot Constant Capacitance Simulator](https://github.com/b-vanstraaten/rusty_capacitance_model). This package provides: \n\n- **A user-friendly interface** to the core functionality.\n- **Plotting, charge sensing, virtual gate** and gate voltage sweeping (1d and 2d) functionality.\n- **Advanced type checking** using pydantic.\n- **Automated testing** including for the functionality in this package.\n- **More examples**.\n",
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