rusty-capacitance-model-core 1.4.1

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Rusty Capacitance Model 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:

pip install rusty-capacitance-model-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:

from rusty_capacitance_model_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)
n_closed = ground_state_closed(vg, n_charge, cgd, cdd, cdd_inv, threshold)

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. 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.