### 物理代写|量子计算代写Quantum computer代考|Quantum Computing and Qubits with Python

statistics-lab™ 为您的留学生涯保驾护航 在代写量子计算Quantum computer方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写量子计算Quantum computer代写方面经验极为丰富，各种代写量子计算Quantum computer相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 物理代写|量子计算代写Quantum computer代考|Keeping your Qiskit® environment up to date

Qiskit” is an open source programming environment that is in continuous flux. Over the course of writing this book, I have passed through many minor and major version updates of the software.

It is generally a good idea to stay updated with the latest version, but with some updates, components of the code might change behavior. It is always a good idea to have a good look at the release notes for each new version. Sometimes changes are introduced that will change the way your code behaves. In those cases, you might want to hold off on upgrading until you have verified that your code still works as expected.

If you are using Anaconda environments, then you can maintain more than one environment at different Qiskit” levels, to have a fallback environment in case an upgraded Qiskit” version breaks your code.
Qiskit” moves fast
The IBM Quantum Experience” Notebook environment always runs the latest version of Qiskit”, and it might be a good idea to test drive your code in that environment before you upgrade your local environment.
You can also subscribe to notification updates, to find out when a new release has been offered:

2. On the IBM Quantum Experience ${ }^{*}$ dashboard, find your user icon in the upperright corner, click it, and select My account.
3. On the account page, under Notification settings, set Updates and new feature announcements to $\mathrm{On}$.

## 物理代写|量子计算代写Quantum computer代考|Comparing a bit and a qubit

So, let’s start with the obvious-or perhaps, not so obvious-notion that most people who read this book know what a bit is.

An intuitive feeling that we have says that a bit is something that is either zero (0) or one (1). By putting many bits together, you can create bytes as well as arbitrary large binary numbers, and with those, build the most amazing computer programs, encode digital images, encrypt your love letters and bank transactions, and more.

In a classical computer, a bit is realized by using low or high voltages over the transistors that make up the logic board, typically something such as $0 \mathrm{~V}$ and $5 \mathrm{~V}$. In a hard drive, the bit might be a region magnetized in a certain way to represent 0 and the other way for 1 , and so on.

In books about quantum computing, the important point to drive home is that a classical bit can only be a 0 or a 1 ; it can never be anything else. In the computer example, you can imagine a box with an input and an output, where the box represents the program that you are running. With a classical computer (and I use the term classical here to indicate a binary computer that is not a quantum computer), the input is a string of bits, the output is another string of bits, and the box is a bunch of bits being manipulated, massaged, and organized to generate that output with some kind of algorithm. An important thing, again, to emphasize is that while in the box, the bits are still bits, always 0 s or $1 \mathrm{~s}$, and nothing else.
A qubit, as we will discover in this chapter, is something quite different. Let’s go explore.

## 物理代写|量子计算代写Quantum computer代考|Visualizing a qubit in Python

In this recipe, we will use generic Python with NumPy to create a vector and visual representation of a bit and show how it can be in only two states, 0 and 1 . We will also introduce our first, smallish foray into the Qiskit” world by showing how a qubit can not only be in the unique 0 and 1 states but also in a superposition of these states. The way to do this is to take the vector form of the qubit and project it on the so-called Bloch sphere, for which there is a Qiskit” method. Let’s get to work!

In the preceding recipe, we defined our qubits with the help of two complex parameters- $a$ and $b$. This meant that our qubits could take values other than the 0 and 1 of a classical bit. But it is hard to visualize a qubit halfway between 0 and 1 , even if you know $a$ and $b$.

However, with a little mathematical trickery, it turns out that you can also describe a qubit using two angles-theta $(\theta)$ and phi $(\varphi)$-and visualize the qubit on a Bloch sphere. You can think of the $\theta$ and $\varphi$ angles much as the latitude and longitude of the earth. On the Bloch sphere, we can project any possible value that the qubit can take.
The equation for the transformation is as follows:
$$|\Psi\rangle=\cos \left(\frac{\theta}{2}\right)|0\rangle+\mathrm{e}^{\mathrm{ip}} \sin \left(\frac{\theta}{2}\right)|1\rangle$$
Here, we use the formula we saw before:
$$|\psi\rangle=a|0\rangle+b|1\rangle$$
$a$ and $b$ are, respectively, as follows:
\begin{aligned} a &=\cos \left(\frac{\theta}{2}\right) \ b &=e^{\mathrm{ip}} \sin \left(\frac{\theta}{2}\right) \end{aligned}

## 物理代写|量子计算代写Quantum computer代考|Keeping your Qiskit® environment up to date

Qiskit”是一个不断变化的开源编程环境。在编写本书的过程中，我经历了软件的许多次要和主要版本更新。

Qiskit” 快速移动
IBM Quantum Experience“笔记本环境始终运行最新版本的 Qiskit”，在升级本地环境之前在该环境中测试驱动代码可能是个好主意。

1. 登录 IBM Quantum Experience”，网址为 https://quantum-computing。ibm。com/登录。
2. 关于 IBM Quantum Experience∗仪表板，在右上角找到您的用户图标，单击它，然后选择我的帐户。
3. 在帐户页面的通知设置下，将更新和新功能公告设置为○n.

## 物理代写|量子计算代写Quantum computer代考|Visualizing a qubit in Python

|Ψ⟩=因⁡(θ2)|0⟩+和一世p罪⁡(θ2)|1⟩

|ψ⟩=一个|0⟩+b|1⟩

## 有限元方法代写

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。