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Questions, especially from students and aspiring physicists, are answered in the FAQ below. For contact & collaboration, jump to get in touch.
问题，尤其是来自学生和有志于物理的朋友，大多可以在下面的常见问题中找到答案。 如需联系与合作，请前往联系方式。
For aspiring physicists & the curious 致有志于物理者与好奇者
Career & Study 职业与学习
The most important thing is to enjoy learning. I don't mean this in the poetic 'live laugh love' sort of way (though that's also true) — I mean that to thrive in physics (or, really, anything for that matter) you have to love the process of doing it and not simply the idea of being it. For physics, that means solving problems and being curious about things that do not currently make sense! Don't always simply chase the answer; enjoy sitting with a problem and taking time to solve it. With the internet and AI it's so easy to get an immediate answer. Sometimes that can be great, but when it comes to getting better at problem solving, avoid it! At every level, physics involves trying to overcome problems. That's kind of the whole job. If you learn to love working through a problem that doesn't fully make sense, or that isn't immediately obvious, then you will set yourself up well for research.
In practical terms, take mathematics and physics at the highest level available to you, and if further mathematics is offered, take it. Mathematical fluency is something you will draw on for the rest of your career, and it is much harder to develop later than it is now.
I would also strongly encourage you to learn to code as early as possible. Python is the best language for most of astrophysics, and even a basic familiarity with it will give you an advantage. There are excellent free resources available online. I taught myself over a summer using a book I picked up from Waterstones (Python Programming by Michael Dawson). One important caution, though: resist the temptation to reach for AI coding assistants while you are still learning. They are useful tools once you understand what you are doing, but using them before that foundation is in place will leave you unable to debug or reason independently about your own code. It's plausible that AI will be writing a lot of code in the future — but while humans are still in the loop (i.e. involved in the research process), you will still need to be able to read, modify, validate, and interpret it. And this is only possible if you work through problems yourself! You have been warned!!
Beyond that, read widely. Popular science is a great place to start, but don't limit yourself. Follow your curiosity: attend talks, read papers, watch videos, ask questions. Don't feel you have to 'wait' until you are at a certain level to engage with something that interests you.
最重要的是享受学习的过程。我说这话不是在讲什么"活着就要快乐"之类的励志口号（尽管那当然也没错）——我的意思是：在物理（或者说任何事情上）要真正做好，你必须爱上做这件事的过程，而不只是爱上"成为那种人"的想象。对物理来说，这意味着解题和保持好奇！不要总是直奔答案，享受与一道题较劲的过程，花时间把它解出来。在有了互联网和 AI 之后，立刻得到答案变得太容易了。有时候这当然很方便，但在培养解题能力这件事上，请尽量避免它！在物理的每一个阶段，你都会面对需要克服的难题。如果你学会了享受攻克那些一开始看不懂、或者不那么一眼就明白的问题的过程，你就为做研究打下了很好的基础。
从实际角度来说，尽可能选择最高水平的数学和物理课程，如果有深度数学课程可选，务必选修。数学能力是你整个职业生涯的基础，现在培养比日后补救容易得多。物理知识可以在大学里反复学习；而真正的数学流利度会让你受益匪浅。
我也强烈建议你尽早学会编程。Python 是天体物理领域最适合的语言，哪怕只是基本掌握，也能给你带来明显的优势。网上有许多优质的免费资源；我自己当年是利用一个暑假、靠着买的一本书自学的。不过要注意一点：在学习阶段，请抵制依赖 AI 编程助手的诱惑。这些工具在你真正理解自己在做什么之后确实很有用，但在那之前就依赖它们，会让你无法独立调试代码或进行独立思考。AI 很可能在未来承担大量编程工作——但只要人类还参与其中，你就需要能够读懂并理解代码。而这只有在自己做题的过程中才能培养出来。你已经被警告过了！！
此外，广泛阅读。科普书籍是个很好的起点，但不要局限于此：跟着好奇心走，听讲座，读论文，提问题。不要觉得自己要等到某个"足够高的水平"才能去接触感兴趣的东西。
First: be curious, and resist specialising too early. Keep taking the courses that really interest you. My philosophy has been, and will always be, to do what interests you, not what is necessarily easy, or strategic for your grades. Wherever you can, do what you love.
Learn to code seriously. Become familiar with Python, version control (Git), and numerical methods. Learn to use LaTeX.
Make the most of the research opportunities available to you during your degree. Most physics departments offer summer bursaries, and some universities run formal placement programmes. This will give you an honest picture of what a research career involves, and will let you build relationships with academics who can support your PhD application.
Finally, the same caveat about AI applies here as it does at school: these tools can have great value once you know what you're doing, but they provide the easy way out. There is no substitute for struggling through a problem. Think of every coding bug or physics problem you have to solve as an extra rep that will strengthen the physics part of your brain.
首先：保持好奇心，不要过早专攻某个方向。继续选修真正让你感兴趣的课程。我的哲学一直是，去做你真正热爱的事——而不是那些简单的、或者对成绩最"策略性"的事。只要有可能，就做你喜欢的事。
认真学习编程。熟悉 Python、版本控制（Git）和数值方法，学会使用 LaTeX。
充分利用学位期间的科研机会。大多数物理系都提供暑期科研奖学金，有些大学还有正式实习项目。这会让你对科研职业的实际情况有清醒认识，也能帮你建立与学术界的联系，为申请博士提供有力支持。
在这一点上：多和让你感兴趣的人交流。你建立的人脉可能会大有裨益。
最后，关于 AI 工具的注意事项和学校阶段一样：这些工具一旦你知道自己在做什么就会很有价值，但它们提供的是捷径。没有什么能替代与问题较劲的过程！把每一个编程 bug 或物理难题都看作一次让你"物理肌肉"变强的训练。
Almost certainly not, but it may require some deliberate effort.
Ultimately, coming from a physics background will give you a significant advantage. Some PhD candidates come in through adjacent degrees like mathematics, engineering, or computer science and find themselves well-placed to do astrophysics.
Whatever your background, the skills that matter most are mathematics, physics, and programming. There are lots of free resources available online to help you learn these, though it will take time and may be harder than doing a university course.
Get research experience wherever you can. A summer project, even in a related field, demonstrates commitment and gives you the academic contacts you'll need for references.
几乎肯定还来得及，但可能需要一些刻意的努力。
有些博士生是通过数学、工程或计算机科学等相关学科进入天体物理领域的，而且往往准备得相当充分。
无论背景如何，最重要的技能都是数学和编程。网上有很多资源可以帮助你学习这些。
尽可能争取科研经历。即使是相关领域的暑期项目，也能证明你的投入，并帮助你建立申请推荐信所需的学术人脉。
Learning & Resources 学习与资源
Video
Lecture notes
Books
视频
讲义
教材
Here is a highly non-exhaustive list of books and films I like.
Non-fiction
In terms of physics books, before I started studying physics I'd tend to just pick up whatever sounded cool to me at the time. I ended up reading a lot of non-fiction (not limited to just physics — I really loved biology, chemistry, philosophy, maths, psychology, etc.) but I can't say that the books I read were the best resources available, and I'd be reluctant to recommend them as such. So my advice instead would be to just go for whatever looks interesting to you. Searching around in a bookshop for something that looks exciting is a really fun thing to do.
I think popular science is a great way to get a flavour of the scientific landscape and to get excited about it. However, learning physics is always a more hands-on process than popular science books will allow, so if you are committed to learning physics, you will ultimately need to pick up a textbook and start solving problems!
That being said, here are a few books I have really enjoyed:
Fiction
Films
以下是一份很不完整的书单和片单，列举了我喜欢的一些作品。
非虚构类
在开始学习物理之前，我读书的方式一向是看什么觉得有意思就拿什么。我读了很多非虚构类书籍（不局限于物理——我真的很爱生物、化学、哲学、数学、心理学等各个领域），但我不能说那些书都是该领域最好的资源，所以我也不太好直接推荐。我的建议反而是：去找你自己觉得有意思的！在书店里四处翻翻，找到一本让你眼睛一亮的书，这本身就是一件很有趣的事。
我认为科普书籍是了解科学全貌、对它产生热情的绝佳方式。但是，学习物理终究是一个比科普书籍所能提供的更加动手的过程，所以如果你真的想学物理，终究需要拿起一本教材，开始做题！
话虽如此，下面是一些我非常喜欢的书：
虚构类
电影
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