如何成为成功的物理学家 | 科研工作者的成长方法论

注：本文为 “科研方法论” 相关合辑。

英文引文，机翻未校。
略作重排，如有内容异常，请看原文。

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How to become a successful physicist

如何成为一名成功的物理学家

All scientists and engineers solve research problems by calling on relevant knowledge to make a series of common, critical decisions.

所有科学家和工程师通过调用相关知识来做出一系列共同的、关键的决策来解决研究问题。

Carl Wieman
卡尔・维曼

Author & Article Information
作者与文章信息

Physics Today 75 (9), 46–52 (2022);
《今日物理》75 卷 (9), 46–52 页 (2022 年);

https://doi.org/10.1063/PT.3.5082

Physics graduate students may find it confusing and intimidating to figure out how to become a successful physicist. The good ones they see apparently know an enormous amount of stuff and come up with solutions before the student even understands the problem. Advisers can find it similarly difficult to figure out how to best guide their graduate students to become good physicists and may wonder, “What do I need to teach them, and how should I do that?” Although students have demonstrated success in physics courses, they often struggle when given a research problem. What is the source of their difficulties, and how can one best help them improve?

物理学研究生可能会觉得弄清楚如何成为一名成功的物理学家既令人困惑又令人畏惧。他们看到的优秀物理学家似乎知道大量的知识，并且在学生还没理解问题之前就能想出解决方案。导师们也面临着类似的难题，即如何最好地指导他们的研究生成为优秀的物理学家，他们可能会问：“我需要教他们什么，又该如何教呢？” 尽管学生在物理课程中表现出色，但当他们面临研究问题时往往会陷入困境。他们困难的根源是什么，又该如何最好地帮助他们提高呢？

An apprentice (right) glues parts of a double bass under the watchful eye of a teacher (left) at the Swiss School of Violin Making in Brienz on 5 June 1969. (Image from Photopress Archiv/Keystone/Bridgeman Images.)

一名学徒（右）在瑞士布里恩茨的瑞士小提琴制作学校的老师（左）的监督下粘合大提琴的部件，时间为 1969 年 6 月 5 日。（图片来自 Photopress Archiv/Keystone/Bridgeman Images。）

This article is intended to help students, advisers, and teachers understand what is needed to become a skilled physicist and what is the most efficient and effective way to reach that goal. The solutions to those problems can benefit all students and advisers in science. They are based on cognitive-science results of studies on the general acquisition of expertise and my current research group’s extensive work on expertise in science and how it is learned. That interest grew out of my own struggles with advising PhD students in my atomic-physics group.

本文旨在帮助学生、导师和教师了解成为熟练物理学家所需的条件以及实现这一目标的最高效、最有效的方法。这些解决方案可以惠及所有科学领域的学生和导师。它们基于认知科学关于专业知识获取的一般性研究成果以及我目前的研究小组在科学专业知识及其学习方式方面的大量工作。这种兴趣源于我自己在指导原子物理小组的博士生时所遇到的困难。

The primary characteristic of a successful physicist is being a good problem solver. Real physics problems are those pursued in research. Solving such problems involves a far more complex set of mental processes than are needed for even the most difficult textbook problem. Unlike real problems, textbook problems provide all the information needed and have a single well-defined path to a solution.

成功的物理学家的主要特点是善于解决问题。真正的物理问题是在研究中追求的问题。解决这些问题涉及的思维过程比解决最困难的教科书问题所需的思维过程要复杂得多。与真实问题不同，教科书问题提供了所需的所有信息，并且有一个明确的解决方案路径。

“Solving” is defined as everything a physicist does in their research, from selecting a suitable problem, to carrying out the lengthy process of obtaining results, to finally presenting those results and their implications to the community. That definition, however, is too broad to be useful. Becoming a good physics problem solver is typically learned through trial and error, but that method of learning is quite inefficient for such a complex task. There are just too many errors that can be made during the problem-solving involved in physics research.

“解决问题” 被定义为物理学家在其研究中所做的一切，从选择合适的问题，到进行漫长的结果获取过程，再到最终向社区展示这些结果及其意义。然而，这种定义过于宽泛，没有实际用途。成为一名优秀的物理问题解决者通常是通过试错法来学习的，但这种方法对于如此复杂的任务来说效率相当低。因为在物理研究中涉及的问题解决过程中可能会犯太多错误。

Cognitive-science research shows that people improve learning efficiency by practicing the set of specific cognitive tasks required for their area of expertise. [1] Although that approach is based on learning research, it is uncoincidentally quite similar to the ideal master–apprentice method for traditionally teaching a craft (see figure [1] ). The master decomposes the craft into a set of specific subskills, gives the apprentice a set of increasingly challenging tasks to practice each one, and intersperses feedback on how to improve. The apprentice practices each subskill to a reasonable mastery and then uses them together to produce the desired product. In the case of physics problem-solving, my research team and I have identified the necessary subskills as a set of problem-solving decisions.

认知科学研究表明，人们通过练习其专业领域所需的特定认知任务来提高学习效率。[1] 虽然这种方法基于学习研究，但它与传统工艺教学中的理想师徒方法非常相似（见图 [1]）。师傅将工艺分解为一组特定的子技能，给徒弟一组逐渐增加难度的任务来练习每一种技能，并穿插反馈以改进。徒弟将每种子技能练习到合理的熟练程度，然后将它们结合起来生产出期望的产品。在解决物理问题的情况下，我的研究团队和我已将必要的子技能确定为一组解决问题的决策。

Figure 1.

Monika Schleier-Smith(center) works in her cold-atom lab with students Emily Davis (left) and Eric Cooper (right). Experts in various building and craft occupations have taught the necessary trade skills to apprentices by giving them an increasingly complicated set of tasks to complete followed by regular feedback. Such an approach is also one of the best ways for students to learn to be successful physicists, according to cognitive-psychology research. (Courtesy of Dawn Harmer.)

Monika Schleier-Smith（中）在她的冷原子实验室与学生 Emily Davis（左）和 Eric Cooper（右）一起工作。各种建筑和工艺行业的专家通过给徒弟一系列越来越复杂的任务来完成，然后进行定期反馈，从而教会他们必要的交易技能。根据认知心理学研究，这种方法也是学生学习成为成功物理学家的最佳方法之一。（Dawn Harmer 提供。）

Much of the past research on scientific problem-solving has looked at expert–novice differences, usually in how they organized their knowledge to solve puzzles and simple textbook problems. That work looks at only a small fraction of the true process. There are many anecdotal descriptions of problem-solving methods in math and science. [2] Nearly every introductory physics textbook has its own problem-solving method, but little evidence has shown whether those methods are correct, complete, or effective for learning to solve authentic problems.

过去关于科学问题解决的大部分研究都关注专家与新手之间的差异，通常是在他们如何组织知识以解决谜题和简单的教科书问题方面。这些研究只涉及真实过程的一小部分。在数学和科学中，关于问题解决方法有许多轶事描述。[2] 几乎每一本基础物理教科书都有自己的问题解决方法，但很少有证据表明这些方法是否正确、完整或有效，以学习解决真实问题。

Decisions decisions

决策决策

My research group interviewed some 50 skilled scientists and engineers (“experts”), including physicists, on how they solved authentic problems in their discipline. We analyzed the interviews in terms of the decisions made during the solving process. Decisions were defined as instances when an expert selected between competing alternatives before taking some action. To my surprise, we found that the same set of 29 decisions occurred over and over (see the box on page 50). Nearly all of them showed up in every interview, and they essentially defined the problem-solving process. [3]

我的研究小组采访了大约 50 名熟练的科学家和工程师（“专家”），包括物理学家，了解他们如何解决其学科中的真实问题。我们从解决问题过程中的决策来分析这些访谈。决策被定义为专家在采取行动之前在竞争性选择之间进行选择的情况。令我惊讶的是，我们发现相同的 29 个决策反复出现（见第 50 页的方框）。几乎所有的决策都出现在每次访谈中，它们基本上定义了问题解决过程。[3]

The decisions were always made with limited information. To reach their decisions, the experts answered such questions as the following: “What information is needed to solve this problem?” “What assumptions and simplifications are appropriate?” “What is the most difficult or uncertain aspect of my solution plan?” If complete information was available, then the steps to follow were just procedures that required little thought and so were seen as relatively unimportant. With limited information, the decisions can never be certain; rather, they are educated guesses or judgments, albeit highly informed ones. The problem-solving skill was in the quality of the judgments. The experts often noted that research breakthroughs came from recognizing the significance of some additional information that other researchers had overlooked.

这些决策总是在信息有限的情况下做出的。为了做出决策，专家们会回答诸如以下问题：“解决这个问题需要什么信息？”“什么样的假设和简化是合适的？”“我的解决方案计划中最困难或不确定的部分是什么？” 如果信息是完整的，那么接下来的步骤只是需要很少思考的程序，因此被视为相对不重要。在信息有限的情况下，决策永远无法确定；它们是有根据的猜测或判断，尽管是非常有根据的。问题解决的技能在于判断的质量。专家们经常指出，研究突破来自于认识到其他研究人员忽视的某些额外信息的重要性。

Whereas the decisions the experts needed to make were common to all disciplines, how they came to each decision was not. When making any of those decisions, the experts called on specific disciplinary knowledge and experience. Most of the relevant knowledge was common in a discipline and different across disciplines. Experts who solved interdisciplinary problems still called on an established body of knowledge in essentially the same way, although it spanned more than one academic discipline.

尽管专家们需要做出的决策在所有学科中都很常见，但他们做出每个决策的方式却并非如此。在做出这些决策时，专家们会调用特定学科的知识和经验。大多数相关知识在学科内是常见的，但在不同学科之间是不同的。解决跨学科问题的专家仍然以基本相同的方式调用已建立的知识体系，尽管它跨越了不止一个学术领域。

Knowing what information to apply and how to apply it was essential to making every decision well. Meaningful learning of the knowledge in a discipline, therefore, must include mastering how to make good decisions with that knowledge. That means that knowledge-free problem-solving is a meaningless concept.

知道要应用什么信息以及如何应用它是做出每个决策的关键。因此，对学科知识的有意义学习必须包括掌握如何用这些知识做出良好决策。这意味着没有知识的问题解决是一个毫无意义的概念。

We found that all the experts organized their disciplinary knowledge in a way that was optimized for making decisions. We describe that knowledge-organization structure as a “predictive framework.” Such frameworks are mental models that embody all the key features relevant to the problem and their relationships via an underlying mechanism. The frameworks are used to predict the behavior of the system being modeled when any of the variables are changed. As our experts explained to us, when they made decisions, they continually ran thought experiments using the frameworks.

我们发现，所有专家都以一种优化决策的方式组织他们的学科知识。我们将这种知识组织结构描述为 “预测框架”。这些框架是体现问题相关所有关键特征及其通过底层机制的关系的心理模型。这些框架用于预测当任何变量发生变化时被建模系统的的行为。正如我们的专家向我们解释的那样，当他们做出决策时，他们不断地使用这些框架进行思想实验。

An early and repeated decision in the problem-solving process was to determine which predictive framework was most suitable to the problem (decisions 5 and 23; see the box on page 50 for this and the other decisions mentioned throughout this article). The complexity of the model and mechanism was selected to match the needs of the problem.

在问题解决过程中，一个早期且反复出现的决策是确定哪种预测框架最适合该问题（决策 5 和 23；见第 50 页的方框. 以及本文中提到的其他决策）。模型和机制的复杂性被选为与问题的需求相匹配。

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Below are 29 sets of questions that students and physicists need to ask themselves during the research process. The answers at each step allow them to make the 29 decisions needed to solve a physics problem. (Adapted from reference [3] .)

下面是学生和物理学家在研究过程中需要问自己的 29 组问题。在每个步骤中的答案使他们能够做出解决物理问题所需的 29 个决策。（改编自参考文献 [3]。）

A. Selection and planning

A. 选择与计划

1. What is important in the field? Where is the field heading? Are there advances in the field that open new possibilities?

该领域中什么是重要的？该领域的发展方向是什么？该领域中是否有新的进展为新的可能性铺平了道路？

2. Are there opportunities that fit the physicist’s expertise? Are there gaps in the field that need solving or opportunities to challenge the status quo and question assumptions in the field? Given experts’ capabilities, are there opportunities particularly accessible to them?

是否有符合物理学家专业知识的机会？该领域中是否有需要解决的空白，或者有机会挑战现状并质疑该领域的假设？鉴于专家的能力，是否有他们特别容易获得的机会？

3. What are the goals, design criteria, or requirements of the problem solution? What is the scope of the problem? What will be the criteria on which the solution is evaluated?

问题解决方案的目标、设计标准或要求是什么？问题的范围是什么？将根据什么标准来评估解决方案？

4. What are the important underlying features or concepts that apply? Which available information is relevant to solving the problem and why? To better identify the important information, create a suitable representation of core ideas.

适用的重要底层特征或概念是什么？哪些可用信息与解决问题相关，为什么？为了更好地识别重要信息，创建核心思想的合适表示。

5. Which predictive frameworks should be used? Decide on the appropriate level of mechanism and structure that the framework needs to be most useful for the problem at hand.

应该使用哪些预测框架？决定框架需要的机制和结构的适当水平，使其对当前问题最有用。

6. How can the problem be narrowed? Formulate specific questions and hypotheses to make the problem more tractable.

如何缩小问题范围？制定具体的问题和假设，使问题更易于处理。

7. What are related problems or work that have been seen before? What aspects of their problem-solving process and solutions might be useful?

以前见过哪些相关问题或工作？他们的问题解决过程和解决方案的哪些方面可能有用？

8. What are some potential solutions? (This decision is based on experience and the results of decisions 3 and 4.)

一些潜在的解决方案是什么？（此决策基于经验和决策 3 和 4 的结果。）

9. Is the problem plausibly solvable? Is the solution worth pursuing given the difficulties, constraints, risks, and uncertainties?

问题是否有可能解决？考虑到困难、约束、风险和不确定性，解决方案是否值得追求？

Decisions 10–15 establish the specifics needed to solve the problem.

决策 10-15 确定解决该问题所需的细节。

1. What approximations or simplifications are appropriate?

适当的近似或简化是什么？

2. How can the research problem be decomposed into subproblems? Subproblems are independently solvable pieces with their own subgoals.

如何将研究问题分解为子问题？子问题是具有自己子目标的独立可解部分。

3. Which areas of a problem are particularly difficult or uncertain in the solving process? What are acceptable levels of uncertainty with which to proceed at various stages?

在解决问题的过程中，问题的哪些领域特别困难或不确定？在各个阶段可以接受的不确定性水平是什么？

4. What information is needed to solve the problem? What approach will be sufficient to test and distinguish between potential solutions?

解决问题需要什么信息？什么方法足以测试并区分潜在解决方案？

5. Which among the many competing considerations should be prioritized? Considerations could include the following: What are the most important or most difficult? What are the time, materials, and cost constraints?

在众多竞争性考虑因素中，应该优先考虑哪些？考虑因素可能包括：最重要或最困难的是什么？时间、材料和成本的约束是什么？

6. How can necessary information be obtained? Options include designing and conducting experiments, making observations, talking to experts, consulting the literature, performing calculations, building models, and using simulations. Plans also involve setting milestones and metrics for evaluating progress and considering possible alternative outcomes and paths that may arise during the problem-solving process.

如何获取必要的信息？选项包括设计和进行实验、进行观察、与专家交谈、查阅文献、进行计算、构建模型和使用模拟。计划还涉及设定评估进度的里程碑和指标，并考虑在问题解决过程中可能出现的可能的替代结果和路径。

B. Analysis and conclusions

B. 分析与结论

1. Which calculations and data analysis should be done? How should they be carried out?

应该进行哪些计算和数据分析？应该如何进行？

2. What is the best way to represent and organize available information to provide clarity and insights?

表示和组织可用信息以提供清晰度和见解的最佳方式是什么？

3. Is information valid, reliable, and believable? Is the interpretation unbiased?

信息是否有效、可靠且可信？解释是否无偏见？

4. How does information compare with predictions? As new information is collected, how does it compare with expected results based on the predictive framework?

信息与预测如何比较？随着新信息的收集，它如何与基于预测框架的预期结果进行比较？

5. If a result is different from expected, how should one follow up? Does a potential anomaly fit within the acceptable range of predictive frameworks, given their limitations and underlying assumptions and approximations?

如果结果与预期不同，应该如何跟进？考虑到预测框架的局限性和基本假设和近似，潜在的异常是否在可接受范围内？

6. What are appropriate, justifiable conclusions based on the data?

基于数据的适当且合理的结论是什么？

7. What is the best solution from the candidate solutions? To narrow down the list, decide which of those solutions are consistent with all available information, and which can be rejected. Determine what refinements need to be made to the candidate solutions. For this decision, which should be made repeatedly throughout the problem-solving process, the candidate list need not be narrowed down to a single solution.

候选解决方案中最好的解决方案是什么？为了缩小列表，决定哪些解决方案与所有可用信息一致，哪些可以被拒绝。确定需要对候选解决方案进行哪些改进。这个决策应该在问题解决过程中反复做出，候选列表不必缩小到一个解决方案。

8. Are previous decisions about simplifications and predictive frameworks still appropriate in light of new information? Does the chosen predictive framework need to be modified?

鉴于新信息，关于简化和预测框架的先前决策是否仍然合适？所选的预测框架是否需要修改？

9. Is the physicist’s relevant knowledge and the current information they have sufficient? Is more information needed, and if so, what is it? Does some information need to be verified?

物理学家的相关知识和他们目前拥有的信息是否足够？是否需要更多信息，如果是，是什么？是否需要验证某些信息？

10. How well is the problem-solving approach working? Does it need to be modified? A physicist should reflect on their strategy by evaluating progress toward the solution and possibly revising their goals.

问题解决方法的效果如何？是否需要修改？物理学家应该通过评估朝着解决方案的进展并可能修订他们的目标来反思他们的策略。

11. How good is the chosen solution? After selecting one from the candidate solutions and reflecting on it, does it make sense and pass discipline-specific tests for solutions to the problem? How might it fail?

所选解决方案有多好？在从候选解决方案中选择一个并反思之后，它是否有意义并通过针对该问题的特定学科解决方案测试？它可能会如何失败？

Decisions 27–29 are about the significance of the work and how to communicate the results.

决策 27-29 涉及工作的意义以及如何传达结果。

1. What are the broader implications of the results? Over what range of contexts does the solution apply? What outstanding problems in the field might it solve? What novel predictions can it enable? How and why might the solution be seen as interesting to a broader community?

结果的更广泛含义是什么？解决方案适用于哪些范围的上下文？它可能解决该领域的哪些突出问题？它可以启用哪些新的预测？解决方案如何以及为什么可能被更广泛的社区视为有趣？

2. Who is the audience for the work? What are the audience’s important characteristics?

作品的受众是谁？受众的重要特征是什么？

3. What is the best way to present the work to have it understood and to have its correctness and importance appreciated? How can a compelling story be made of the work?

以何种方式呈现作品，使其被理解并让其正确性和重要性得到欣赏？如何使作品成为一个引人入胜的故事？

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Consider, for example, a physicist working on a research problem involving laser cooling. A predictive framework they might initially adopt would include the momentum of the light, the mass and momentum of atoms, the conversion between the two forms of momentum because of light scattering, and the dependence of the scattering rate on the frequency of the light and the Doppler shift. As they carried out experiments and collected data, they might decide that the data were reliable (decision 18) but inconsistent with the predictions of the framework (decision 19). That may lead them to modify their predictive framework by, for example, adding the AC Stark effect and its spatial variation across the laser beam.

例如，考虑一位从事涉及激光冷却的研究问题的物理学家。他们最初可能采用的预测框架将包括光的动量、原子的质量和动量、由于光散射而产生的两种动量形式之间的转换，以及散射率对光频率和多普勒频移的依赖。当他们进行实验并收集数据时，他们可能会决定数据是可靠的（决策 18），但与框架的预测不一致（决策 19）。这可能会导致他们通过添加例如激光束横截面上的交流斯塔克效应及其空间变化来修改他们的预测框架。

The set of decisions

决策集合

The list of decisions is organized into somewhat arbitrary categories represented in figure [2] and in more detail in the box on page 50. It roughly corresponds to the order in which they appear during the solving process. No one, however, follows such a simple, time-ordered process. Based on new information and reflection, experts frequently jump to a different step in the process and revise earlier decisions, conclusions, and plans.

决策列表被组织成在图 [2] 中表示并在第 50 页的方框中更详细描述的相对任意的类别。它大致对应于它们在解决问题过程中出现的顺序。然而，没有人遵循这样一个简单的、按时间顺序的过程。基于新信息和反思，专家们经常跳到过程中的不同步骤，并修订早期的决策、结论和计划。

Figure 2.

Solving physics problems. The black arrows represent a hypothetical but unrealistic order of decision making that begins with selecting a research direction and identifying goals for the project. The white arrows represent more realistic iteration paths. Decisions are grouped into categories for presentation purposes; the parentheticals indicate the number of decisions that need to be made in each category. Although both knowledge and skills development are not decisions per se, based on interviews with physics experts about how they solve problems, the two are commonly mentioned themes. (Adapted from ref. [3] .)

解决物理问题。黑色箭头表示一种假设但不现实的决策顺序，从选择研究方向和确定项目目标开始。白色箭头表示更现实的迭代路径。决策出于展示目的被分组；括号内表示每个类别中需要做出的决策数量。尽管知识和技能发展本身并非决策，但根据与物理专家关于他们如何解决问题的访谈，这两个是常被提及的主题。（改编自参考文献 [3]。）

Few physicists will be surprised to see the decisions on the list. What is more notable is that a finite list of 29 seems sufficient to characterize the entire problem-solving process across all sciences and engineering. They provide a much more specific guide as to what is important to master to become a successful physicist or, for that matter, any flavor of scientist or engineer.

很少有物理学家会对列表中的决策感到惊讶。更值得注意的是，一个有限的 29 项列表似乎足以描述整个科学和工程领域的解决问题过程。它们为成为成功的物理学家，或者更广泛地说，任何类型的科学家或工程师，提供了更具体的掌握要点指南。

In addition to the decisions, which were our focus, the experts volunteered common areas of general skills they saw as important elements of expertise in their fields.

除了我们关注的决策之外，专家们还主动提供了一些他们认为在其领域内专业知识的重要组成部分的通用技能领域。

Stay up to date in the fieldby learning relevant new knowledge, ideas, and technology from literature, conferences, and colleagues.

保持在该领域的最新状态，通过从文献、会议和同事那里学习相关的最新知识、想法和技术。

Develop intuition and experienceto improve problem-solving.

培养直觉和经验，以提高解决问题的能力。

Enhance interpersonal and teamwork skills—for example, how to navigate collaborations, manage a team, and strengthen communication—particularly as they apply in the context of the different problem-solving processes.

增强人际交往和团队合作技能—— 例如，如何进行合作、管理团队以及加强沟通，特别是它们在不同问题解决过程中的应用。

Improve one’s efficiencyby practicing time management, including learning to complete certain common tasks efficiently and accurately.

提高个人效率，通过练习时间管理，包括学习高效且准确地完成某些常见任务。

Cultivate an attitude, or motivation, which includes persevering in the task despite obstacles, dealing with stress, and having confidence in decisions.

培养一种态度，或动机，包括尽管存在障碍也要坚持完成任务、应对压力以及对决策有信心。

Becoming a highly skilled physicist requires developing those common skills and learning to make decisions well.

成为一名技艺高超的物理学家需要培养这些通用技能并学会做出良好的决策。

The cognitive psychologist K.Anders Ericsson and collaborators have demonstrated the process by which people become experts in many disciplines, [1] and my group has applied those ideas to teaching physics. [4] ,[5] The level of mastery is primarily determined by the amount of what Ericsson has labeled “deliberate practice.” It entails identifying the specific subskills involved for expertise in the discipline, usually by a good teacher or coach. The learner intensively practices those specific subskills individually and then in combination. That practice is interleaved with frequent targeted feedback, typically by a teacher or coach, and reflection on how to improve. The focus, intensity, and extent of the mental effort is critically important. Those factors likely determine the extent to which the desired changes in the neuronal connections in the brain are achieved, which results in improved capabilities.

认知心理学家 K.Anders Ericsson 及其合作者已经展示了人们如何在许多学科中成为专家的过程，[1] 我们团队将这些想法应用于物理教学。[4]、[5] 掌握程度主要由 Ericsson 所称的 “刻意练习” 的数量决定。它包括确定该学科专业知识所涉及的具体子技能，通常由一位优秀的教师或教练来完成。学习者单独并组合地密集练习这些具体子技能。这种练习穿插着频繁的针对性反馈，通常由教师或教练提供，并反思如何改进。专注、强度和心理努力的程度至关重要。这些因素可能决定了大脑中神经连接所期望的变化程度，从而提高了能力。

In the case of physics, the subskills to be mastered are the problem-solving decisions. We have found that for typical realistic problems in any given science or engineering discipline, skilled practitioners tend to make similar decisions with similar justifications, whereas students do not. [6] The mismatch between students and skilled practitioners is understandable if one notes how few of the decisions are required, and hence practiced, in solving the typical textbook or exam problems encountered in courses (see figure [3] ). That also explains the puzzle that originally got me interested in physics-education research some decades ago. Namely, why is there so little correlation between students’ performance in their physics courses and their ability to do physics research?

在物理学的情况下，要掌握的子技能是解决问题的决策。我们发现，在任何给定的科学或工程学科中，对于典型的现实问题，熟练的从业者倾向于做出类似的决策并给出类似的理由，而学生则不是这样。[6] 如果注意到在课程中遇到的典型教科书或考试问题中只需要并因此练习很少的决策，那么学生和熟练从业者之间的不匹配是可以理解的（见图 [3]）。这也解释了几十年前最初让我对物理教育研究感兴趣的谜题。也就是说，为什么学生在物理课程中的表现与他们进行物理研究的能力之间几乎没有相关性？

Figure 3.

Textbook physics problems—including this one ( a ) to calculate the acceleration of $m_2$ assuming a massless pulley and rope—don’t require much decision making and often lack any context that motivates a student to solve them. ( b ) Real-world physics problems, such as determining the requirements necessary for a rocket to launch the James Webb Space Telescope, are societally relevant. Yet they can be too difficult because of the many complex decisions that must be made. ( c )An example of an authentic but skill-appropriate physics problem calls for a student to calculate the weight that can be pulled up to a treehouse using a rope over a branch and to decide whether it’s worth the time and money to buy a pulley for the job. Authentic problems are designed to include many decisions and be more relevant but still need to be approachable for those with limited knowledge and decision-making skills.

教科书物理问题—— 包括这个（a）假设滑轮和绳索质量为零，计算 $m_2$ 的加速度 —— 不需要太多决策，而且通常缺乏激励学生解决问题的背景。（b）现实世界的物理问题，例如确定发射 James Webb Space Telescope 所需的火箭要求，与社会相关。然而，由于需要做出许多复杂的决策，它们可能太难了。（c）一个真实但适合技能水平的物理问题的例子要求学生计算使用绳索越过树枝将重量拉到树屋，并决定是否值得花费时间和金钱购买滑轮来完成这项工作。真实问题旨在包含许多决策并更具相关性，但仍需要对那些知识有限和决策技能有限的人具有可接近性。

Deliberate practice in the research setting

在研究环境中进行刻意练习

Research always involves problem-solving, and decisions arise naturally. When conducting research, the learner should explicitly focus on the decisions from the list, think about which ones are encountered during the research process, and practice making those decisions. Then they should reflect on how and why they made each decision they did and how subsequent results indicate how each one could have been improved. They should also seek out the adviser or more experienced members of the research group to discuss their process for making those decisions and get feedback on it.

研究总是涉及问题解决，决策自然产生。在进行研究时，学习者应明确关注列表中的决策，思考在研究过程中遇到了哪些决策，并练习做出这些决策。然后，他们应该反思他们做出每个决策的方式和原因，以及后续结果表明每个决策本可以如何改进。他们还应该寻求导师或研究小组中更有经验的成员，讨论他们做出这些决策的过程并获得反馈。

The adviser should also encourage the student to carry out that type of practice by identifying when a specific decision needs to be made and challenging them to make it. The adviser may then discuss the student’s choices and justifications and point out what aspects were good and what could be improved. That process is a much more effective educational experience than simply telling the student what the decision should be. [7] But speaking from extensive personal experience, I know that human nature strongly inclines a person in an advisory position to instead make the decision and tell the student. It may be more efficient in the short term for advancing the research, but that approach is far less effective educationally and for producing skilled researchers in the long run.

导师也应该通过识别何时需要做出特定决策并挑战学生做出决策来鼓励学生进行这种练习。然后，导师可以讨论学生的选项和理由，并指出哪些方面是好的，哪些可以改进。这个过程比简单地告诉学生决策应该是什么要有效得多。[7] 但从我丰富的个人经验来看，我知道，人的本性强烈地倾向于让处于顾问位置的人做出决策并告诉学生。从短期来看，这种方法可能更有利于推进研究，但从长远来看，它在教育上以及培养熟练的研究人员方面要低效得多。

An adviser typically trains new research students by giving them small projects to work on, usually a piece of the group’s larger research agenda. The decisions list provides guidance on what sorts of projects are likely to be the most educationally beneficial. Ericsson’s work has shown the importance of having practice tasks that are just above the student’s ability so they can finish those tasks only with intense effort. To be effective, therefore, practice projects should have neither too few nor too simple decisions for the student to make, nor should the projects have decisions that are of such complexity that the student finds them impossible.

导师通常通过给新研究学生分配小项目来培训他们，通常是该团队更大研究计划的一部分。决策列表为可能最具教育效益的项目类型提供了指导。埃里克森的工作表明，拥有略高于学生能力的练习任务的重要性，这样他们只能通过努力才能完成这些任务。因此，为了有效，练习项目应该既不能让学生做出太少或太简单的决策，也不能让学生做出如此复杂的决策以至于他们觉得不可能完成。

The downside of the research environment is that the nature and pace of the work can make it difficult for the student to practice the full set of decisions, particularly the repeated practice and improvement at making a particular decision. Although decisions 16–26 will come up frequently and repeatedly during research, many of the earlier ones appear less often, and some need to be made without consulting the student. For example, many of the problem-definition and planning decisions occur when the adviser develops proposals to fund the work and hire students and postdocs.

研究环境的缺点是，工作性质和节奏可能会使学生难以练习整套决策，尤其是重复练习和改进特定决策。尽管决策 16-26 在研究中会频繁且反复出现，但许多早期的决策出现得较少，有些甚至在不咨询学生的情况下做出。例如，许多问题定义和规划决策发生在导师制定资助工作和招聘学生及博士后的提案时。

To address that weakness, the student (or postdoc) and adviser should seek out opportunities to review those previous decisions and how they were made. Whenever possible, the adviser should challenge the student to think of alternatives and then discuss why those alternatives would usually not be as good. Of course, if the student comes up with an improvement, so much the better. Additionally, the student could apply for graduate fellowships, such as from NSF’s Graduate Research Fellowship Program, that require them to write a research proposal, which should include making and justifying those first decisions.

为了克服这一弱点，学生（或博士后）和导师应该寻找机会来回顾这些早期的决策及其制定过程。只要可能，导师应该挑战学生思考替代方案，然后讨论为什么这些替代方案通常不会更好。当然，如果学生想出了改进办法，那就更好了。此外，学生还可以申请研究生奖学金，例如 NSF 的研究生研究奖学金项目，这要求他们撰写研究提案，其中应包括做出并论证这些最初的决策。

Deliberate learning in the classroom

在课堂上进行刻意学习

In the typical physics course, students practice and learn to make very few problem-solving decisions. Seldom are any encountered in a lecture, and only two or three of the 29 decisions are called for in doing typical homework or non-project-based laboratory courses. In a lecture, the outcomes of the decisions are presented, usually without the student ever recognizing that the decision needed to be made.

在典型的物理课程中，学生练习并学习做出很少的问题解决决策。很少在讲座中遇到任何决策，而且在典型的作业或非项目基础的实验课程中，只有两三个决策被要求。在讲座中，决策的结果被呈现，通常学生甚至没有意识到需要做出决策。

With good teaching, however, most of the decisions can be made an explicit part of course activities. For example, students in introductory physics, [4] advanced undergraduate, [5] and advanced graduate [8] courses can work through authentic problems in class. Those problems are simpler than most research problems, but they involve many more decisions than standard textbook problems. In solving authentic problems in class, students make and justify many of the decisions explicitly in consultation with their peers and get regular feedback and guidance from the instructor (see figure [3] ). Similarly, solving homework or exam problems can involve explicitly justifying various decision choices. Of course, including all 29 decisions is impractical, but the instructor can select those they find particularly important in the context.

然而，通过良好的教学，大多数决策可以成为课程活动的明确部分。例如，在基础物理 [4]、高级本科 [5] 和高级研究生 [8] 课程中，学生可以在课堂上解决真实问题。这些问题比大多数研究问题更简单，但它们涉及的决策比标准教科书问题要多得多。在课堂上解决真实问题时，学生在与同伴协商的情况下明确地做出并论证许多决策，并从教师那里获得定期的反馈和指导（见图 [3]）。同样，解决作业或考试问题可以涉及明确论证各种决策选择。当然，包括所有 29 个决策是不切实际的，但教师可以选择那些在他们看来特别重要的决策。

At their best, courses do have an advantage over the research setting: Thoughtful instructors have the freedom to assign problems that give students practice in making various decisions, including the repeated practice of making particularly important decisions. My personal preference in undergraduate courses is to make every problem solution include identifying important features (decision 4), determining what information is needed (decision 13), planning the solution process (decision 15), and evaluating potential solutions (decision 26). Problems can be varied to probe other decisions and call on a variety of physics knowledge. Courses have the disadvantage of the decisions always being more artificial than in the research setting, but that issue can be minimized with careful thought, usually by ignoring the textbook!

在最好的情况下，课程比研究环境有一个优势：深思熟虑的教师有自由分配问题，让学生练习做出各种决策，包括重复练习做出特别重要的决策。我个人在本科课程中的偏好是让每个问题解决方案都包括确定重要特征（决策 4）、确定需要什么信息（决策 13）、规划解决方案过程（决策 15）和评估潜在解决方案（决策 26）。问题可以变化，以探究其他决策并调用各种物理知识。课程的缺点是决策总是比研究环境更人为，但这个问题可以通过仔细思考来最小化，通常方法是忽略教科书！

For students to make decisions, they must learn a substantial amount of physics knowledge. The best way to learn that knowledge is to witness its importance when it’s used to make the problem-solving decisions. The traditional practice is for the instructor to teach physics knowledge to the students and then later give them problems so that they can practice using that knowledge. A much more effective approach is to give them a meaningful problem to struggle with first and then provide them with the knowledge they need to figure it out. [9] When information is presented as useful for solving certain kinds of problems, the brain stores that information so that it is readily accessed and applied when needed to solve novel related problems.

要让学生做出决策，他们必须学习大量的物理知识。学习这些知识的最好方法是见证其在做出问题解决决策时的重要性。传统做法是教师先向学生传授物理知识，然后给他们问题，让他们练习使用这些知识。一个更有效的方法是先给他们一个有意义的问题去努力解决，然后提供他们需要的知识来解决它。[9] 当信息被呈现为对解决某些类型问题有用时，大脑会存储这些信息，以便在需要解决新的相关问题时能够轻松访问和应用。

Whereas most of the 29 decisions are applicable for problem-solving at every level of a physics education, a few are only appropriate for advanced graduate students and postdocs. Deciding on the state of the field (decision 1), the broader implications of the research results (decision 27), the audience (decision 28), and the most effective way to present research results (decision 29) all require extensive exposure to current research and attitudes in the field. Most of the other decisions are suitable for every level of student to practice, but the physics topics and knowledge necessary to make them needs to be appropriate to the course and level of the student. That specific physics knowledge is usually set by the problem context.

虽然 29 个决策中的大多数适用于物理教育各个层次的问题解决，但少数只适合高级研究生和博士后。确定该领域的现状（决策 1）、研究结果的更广泛含义（决策 27）、受众（决策 28）以及呈现研究结果的最有效方式（决策 29）都需要广泛接触该领域的当前研究和态度。大多数其他决策都适合每个层次的学生练习，但做出这些决策所需的物理主题和知识需要与课程和学生的水平相适应。这种特定的物理知识通常由问题背景设定。

A student in a graduate class can practice making such decisions even when the decisions are not part of the curriculum. Every new physics concept and calculational technique the graduate student sees was originally the solution to an authentic physics problem. They can ask themselves what decisions called for that solution? How was the problem framed (decisions 4 and 5)? What approximations were used (decision 10)? Where would the solution method apply and not apply (decisions 25 and 26)? Discussing such questions with peers and usually the instructor will benefit their learning.

即使这些决策不是课程内容的一部分，研究生课程中的学生也可以练习做出这样的决策。研究生看到的每一个新的物理概念和计算技术最初都是真实物理问题的解决方案。他们可以问自己，是什么决策需要这样的解决方案？问题是如何提出的（决策 4 和 5）？使用了哪些近似（决策 10）？解决方案方法在哪里适用，在哪里不适用（决策 25 和 26）？与同伴和通常的教师讨论这些问题将有助于他们的学习。

In deciding how to use the instructional time, teachers should remember that the body of physics knowledge learned in school will always be a small fraction of the knowledge needed in a physics career. The skill of making good problem-solving decisions, however, will always remain essential.

在决定如何使用教学时间时，教师应该记住，在学校学到的物理知识体系将始终只是物理职业生涯中所需知识的一小部分。然而，做出良好问题解决决策的技能将始终是必不可少的。

Most important and difficult

最重要且最困难

To be a successful physicist requires mastering how to make all 29 decisions, but the reflection decisions (decisions 23–26) are arguably the most difficult to learn. They require students to examine their own thinking, which is challenging for three reasons. First, having that kind of perspective on one’s own thinking is just difficult. Talking through the ideas with others can help. Second, a good physicist tends to be consumed with the immediate challenge of the work—for example, how to improve the vacuum, how to reduce the jitter in the detector trigger, or how to create faster code for evaluating that complex integral. Shifting mental gears to put those thoughts aside and think more broadly is hard. I find it helpful to schedule blocks of time in my week to think about those reflective decisions.

要成为一名成功的物理学家，需要掌握如何做出所有 29 个决策，但反思决策（决策 23-26）可能是最难学的。它们要求学生审视自己的思维，这因三个原因而具有挑战性。首先，对自己的思维有这种视角本身就是困难的。与他人讨论这些想法会有帮助。其次，优秀的物理学家往往会专注于工作的即时挑战 —— 例如，如何提高真空度、如何减少探测器触发器的抖动，或者如何为评估那个复杂积分创建更快的代码。将这些想法放在一边，更广泛地思考是很难的。我发现，在我的一周中安排整块时间来思考这些反思决策是有帮助的。

The third and probably most serious difficulty in making good reflective decisions is confirmation bias. It’s a well-established psychological tendency for humans, once they have decided on an answer that they think is correct, to be strongly prepossessed toward maintaining that belief. Confirmation bias causes them to suppress thinking about alternatives and interpret all new evidence in a way that confirms their belief. I suspect most of the serious errors in physics have been the result of such bias. Students (and scientists in general) should practice fighting against it when making reflective decisions.

做出良好反思决策的第三个也是可能最严重的困难是确认偏误。一旦人类决定了一个他们认为正确的答案，就强烈倾向于维持这种信念，这是一种众所周知的心理倾向。确认偏误使他们压抑对其他选择的思考，并以一种确认他们信念的方式解释所有新证据。我怀疑物理学中大多数严重的错误都是这种偏误的结果。学生（以及科学家）在做出反思决策时应该练习与之对抗。

Despite the difficulty in learning them, the reflection decisions are also the most important. They are the error-correction decisions of the problem-solving process and allow students to catch when they have made a poor decision and fix it. Frequently, corrections happen when new information becomes available or the relevance of overlooked information is recognized, such as why an assumption that was made does not apply. An adviser should have their students explicitly practice decisions 25 and 26, test their solutions, and try to come up with the ways their decisions could fail, including alternative conclusions that are not the findings that they were hoping for. Thinking of such failure modes is something that even many experienced physicists are not very good at, but our research has shown that it can be readily learned with practice.

尽管学习起来有困难，但反思决策也是最重要的。它们是问题解决过程中纠错的决策，允许学生发现自己做出了糟糕的决策并加以纠正。通常，当新信息出现或被忽视的信息的相关性被认识到时，就会进行更正，例如为什么做出的假设不适用。导师应该让学生明确练习决策 25 和 26，测试他们的解决方案，并尝试想出他们的决策可能失败的方式，包括不是他们期望的结果的替代结论。考虑这样的失败模式是许多经验丰富的物理学家也不擅长的，但我们的研究表明，通过练习可以很容易地学会。

The set of decisions for how to become a good physics problem solver also provides a good framework for measuring a person’s strengths and weaknesses in solving authentic physics problems. I am sure many advisers are like I was: Although I knew a student was failing to solve the research problems I gave them to work on, I didn’t know why or how I could help them improve.

如何成为一名优秀的物理问题解决者的决策集合也为衡量一个人在解决真实物理问题方面的优势和劣势提供了一个很好的框架。我相信许多导师和我一样：虽然我知道一个学生没能解决我给他们做的研究问题，但我不知道为什么，也不知道如何帮助他们改进。

My group has now developed tests in several areas of science and engineering based on those problem-solving decisions. We give the student a realistic scenario and then ask them to make and justify a representative subset of the decisions. We then compare their responses with those of experts in the field. Typically, students are quite poor at making those decisions despite having successfully completed courses that covered the relevant knowledge. But the more experience they have had in doing authentic problem-solving, the more expert-like they tend to be in their decisions. If properly taught, the skills are quite learnable.

我的团队现在已经根据这些解决问题的决策在科学和工程的几个领域开发了测试。我们给学生一个现实的情景，然后让他们做出并论证一组具有代表性的决策。然后我们将他们的回答与该领域的专家的回答进行比较。通常，尽管学生成功完成了涵盖相关知识的课程，但他们做出这些决策的能力很差。但他们进行真实问题解决的经验越多，他们的决策就越倾向于专家型。如果教学得当，这些技能是相当可学的。

This work was supported by the Howard Hughes Medical Institute. The research was led by Argenta Price and carried out by many members of my group.

这项工作得到了霍华德・休斯医学研究所的支持。该研究由 Argenta Price 领导，我的团队的许多成员参与实施。

References

1. K. A. Ericsson, R. T.Krampe, C. Tesch-Römer, Psych. Rev. 100, 363 (1993). https://doi.org/10.1037/0033-295X.100.3.363
   A. Ericsson, R. Pool, Peak: Secrets from the New Science of Expertise, HarperOne (2017).

2. G. Polya, How to Solve It: A New Aspect of Mathematical Method, 2nd ed., Doubleday (1957).

3. A. M. Price et al., CBE–Life Sci. Edu. 20, ar43 (2021). https://doi.org/10.1187/cbe.20-12-0276

4. L. Deslauriers, E. Schelew, C. Wieman, Science 332, 862 (2011). https://doi.org/10.1126/science.1201783 PubMed

5. D. J. Jones, K. W. Madison, C. E. Wieman, Phys. Rev. ST Phys. Educ. Res. 11, 020108 (2015). https://doi.org/10.1103/PhysRevSTPER.11.020108

6. E. Burkholder, L. Hwang, C. E. Wieman, Educ. Chem. Eng. 34, 68 (2021). https://doi.org/10.1016/j.ece.2020.11.006

7. N. G. Holmes, B. Keep, C. E. Wieman, Phys. Rev. Phys. Educ. Res. 16, 010109 (2020). https://doi.org/10.1103/PhysRevPhysEducRes.16.010109

8. G. P. Lepage, Am. J. Phys. 89, 317 (2021). https://doi.org/10.1119/10.0002349

9. D. L. Schwartz, T. Martin, Cogn. Instr. 22, 129 (2004). https://doi.org/10.1207/s1532690xci2202_1

Carl Wieman is a professor of physics and of education at Stanford University in California.

原文：

• How to become a successful physicist
  https://pubs.aip.org/physicstoday/article/75/9/46/2845437/How-to-become-a-successful-physicistAll-scientists

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如何成为一个顶级科学家？

撰文 | 文双春（湖南大学物理与微电子科学学院院长）

（2025 年 6 月 16 日在学院 2025 年毕业典礼暨学位授予仪式上讲的主要内容）

今天，我们齐聚一堂，共同庆祝 2025 届毕业生同学圆满完成学业，即将奔赴新天地。

作为老师，作为院长，此时此刻，我应该对同学们说些什么呢？学工办李老师为我精心准备了一个讲稿，写得非常好，非常文艺，我感觉我可能念不好，达不到讲稿应当达到的效果。今天上午，我临时决定，把这次毕业典礼作为同学们在学院的最后一堂课、最后一次院长午餐会，与同学们共同探讨一个问题：如何成为一个顶级物理学家？

十天前，也就是 2025 年 6 月 6 日，学工组织了第 66 期院长午餐会，主题是 “心启新程：2024 级转专业同学交流会”。一位由英语专业转入物理专业学习的学弟提出了这个问题。

这个问题令我眼前一亮，也令我无比喜悦。“顶级” 是一流中的一流。学生有如此顶级抱负，作为老师，作为院长，我怎不为之喜悦？

但喜悦之后，我又马上陷入困境：我怎么回答这个问题？

我的第一感觉是 —— 我回答不了这个问题，因为我不是顶级物理学家。同学们也许与我有同样感觉。但慢慢地，受两点启发，我又感觉这个感觉只是感觉，并不一定靠谱。

其一，动画电影《哪吒之魔童闹海》中，东海龙王敖光对儿子敖丙说：“父王只是想用自己的经验，为你谋个幸福，但现在看来，父辈的经验毕竟是过往，未必全对，你的路还需你自己去闯。” 它启发我们：纵然是顶级物理学家，纵然他们愿意毫无保留地告诉我们如何成为一个顶级物理学家，对我们也未必管用。

其二，谁能领导和指导爱因斯坦？《爱因斯坦的老板》一书有个核心观点：你能领导天才恰恰因为你不是天才。它启发我们：恰恰因为我们不是顶级物理学家，所以我们能告诉那位学弟如何成为一个顶级物理学家。

举个例子。晶体管发明人、诺贝尔物理学奖得主肖克利（William Shockley）曾在美国贝尔实验室领导一个团队，他聘用了 60 名世界上最聪明的人。事实证明，尽管肖克利是一位顶级科学家，但他也是一名糟糕的领导。很快，八名最优秀的员工，包括后来创立英特尔的诺伊斯（Bob Noyce）和提出摩尔定律的摩尔（Gordon Moore）离开了他。离开肖克利的人，后来都发展得非常好。

由此，同学们，你我都能解答那个学弟的问题。当然，很多同学将来不会做物理学家。那么，我们都可以解答一个更普遍性的问题：如何成为自己领域的顶级人才？

我认为，解答好这个问题，对在读的学弟学妹们很重要，对即将开启新征程的你们也很重要。

物理学的一个重要思维是从现象、事实、数据、信息等等中，也就是透过纷繁复杂的世界，找到或发现本质和规律。我最近用这个思维做了一些功课，感觉成为任何领域的顶级人才，有三点至关重要。请容我在这里与同学们分享。

一是立志。

决定一个人成长成才的因素很多，但最主要的因素无疑在自己。而自己的因素中，最重要的是志向。

研究表明，远大志向对一个人取得更高成就的决定作用与认知能力几乎一样大。经济学家通过大量调查研究发现，一个学生离开学校时的志向，比他的家庭出身、毕业的学校等能更准确预测其未来将取得怎样的成就。

《西游记》中，菩提祖师的弟子无数，为何唯独孙悟空学成了长生不老，并成长为千古流芳的 “齐天大圣”？孙悟空自己总结出的答案是：“举世无人肯立志，立志修玄玄自明。”

有同学可能要问，我也有志向呀，为何不见成效呢？有志向是容易的，关键是把志向立起来。立起来的志向才是真正的志向，没有立起来的志向是白日做梦，是空想，是幻想。

立起来的标志是什么？标志是：志向成为一种坚定不移的信念或信仰。

唐僧踏上取经之路时，向唐皇表示：“我这一去，定要捐躯努力，直至西天。如不到西天，不得真经，即死也不敢回国，永堕沉沦地狱。” 取经路上，无论是面对财富、美女、王位的诱惑，还是深陷被妖怪捉去或蒸或煮或煎着吃的险境，唐僧始终富贵不淫、贫贱不移、威武不屈。这就是立志，真正的把志向立起来了。

纵观科学史，顶级科学家无不立志献身科学，把科学当信仰、当使命。爱因斯坦说：“在思想深邃的科学家之列，你很难找到一个没有宗教情怀的人。” 他所谓的宗教情怀，是把科学当信仰。量子力学创始人普朗克说：“任何一位认真从事过科学工作的人都知道，在科学殿堂的入口处铭刻着这样一句话：你们必须有信仰。这是真正的科学家必备的品质。”

二是问题。

当我感觉我回答不了那位学弟的问题但又不能不回答时，我突然想起诺贝尔物理学奖得主威曼（Carl Wieman）回答过那个问题。他在《今日物理》杂志发表过一篇文章，题目是 “如何成为一个成功的物理学家”(How to become a successful physicist)。我当时请学工办袁老师把那篇文章转发给了参加院长午餐会的每一位同学。同学们如果有兴趣，可向袁老师索取。

威曼的文章通篇在讲问题。我理解，科学研究是提出问题和解决问题，意味着，成功的科学家必须是成功的问题提出者和问题解决者。

威曼认为，科学研究的问题，与同学们求学期间课本上的问题和考试题目中的问题大不相同 —— 最大的不同是，后者都有标准答案，有特定路径通向标准答案，而前者连你在做什么你都不知道，更别说标准答案和特定路径。因此，很会刷课本上的习题，在各种考试中都能得高分，并不预示着将来能成为一个成功的科学家。

研究生同学应该都有体会，本科生同学如果读研，也将很快体会到，做研究，没有问题是令人苦恼的最大问题。

唐僧师徒西天取经，最大的挑战是什么？很多人说是妖魔鬼怪。错了！最大的挑战是没有挑战，也就是没有来自妖魔鬼怪的挑战。没有妖魔鬼怪，就没有九九八十一难。没有九九八十一难，唐僧师徒就取不到真经、成不了佛，少一难都不行。

还有一点须注意，挑战不够不算挑战，问题不难不算问题，唐僧师徒即使战胜了它们、解决了它们，也入不了九九八十一难的 “难薄”。

或许正因为如此，量子力学创始人狄拉克曾无情地打击了一个想解决一个普通问题的学生：“你应该去解决基本问题，而不是那些琐碎的问题。” 据说卢瑟福等顶尖科学家都赞同狄拉克的 “打击”。

同学们都知道爱因斯坦追光的故事。爱因斯坦多次透露，他的相对论之路始于他 16 岁时思考的一个问题：如果你能追上光速，光波会是什么样子？这个问题困扰了他十年，也使他在十年后的 26 岁那年，创立了狭义相对论。

三是纯粹。

那位提出问题的学弟同时向学院提出了一个要求：“希望可以换到一个人少且安静的宿舍。”

从成就顶级人才考虑，我认为这个要求很合理。

爱因斯坦说过：“即便在现代社会，也确有某些职业，要求与世隔绝地生活，而不用怎么劳力劳心。我不禁想到看守灯塔或灯船。有没有可能，把愿意思考科学问题、尤其是数学问题或哲学问题的年轻人派去做这些工作呢？极少有有志青年在最出成果的人生阶段，得到这种机会，在任意长短时间内专注于科学问题而不受干扰。”

他在晚年有感慨：“我年轻时所向往的生活，只是静静地坐在某个角落，做我的工作，不要大众注意。”

说个更接近我们的例子。“首款国产 3A 游戏”《黑神话：悟空》制作人冯骥说，“单机游戏不像手游，一两年就能出来，需要一个不那么受物质困扰的地方。做的人也需要不太在意周围的繁华。” 游戏制作团队没有把 “工场” 选择在繁华闹市，而是选择了杭州的一个叫转塘的地方 —— 我相信转塘因《黑神话：悟空》才为天下更多人所知。他们为什么选择这么个不知名的地方？因为 “这个地方本身也可以筛掉一些对物质需求更高的人”。

这些都说明，要想取得大成就，专注于自己的工作，不受外界干扰，至关重要。科学研究也证明，在智力相差无几的同龄人中，谁能更集中精力，使个人的认知能力达到极限，谁就有机会脱颖而出，成为所在领域的顶级人才。

外部环境固然能为我们集中精力或专注于自己的工作创造客观条件，但地球不是，至少不总是围绕我们转的。因此，我们也要面对外部环境十之八九不随人愿的现实。

爱因斯坦一生都没有得到他渴望的类似看守灯塔或灯船那样的机会，也没有过上他年轻时所向往的那种生活。众所周知，他的主要科学成就是在他根本不想去工作的专利局做出的。

顶尖科学家是如何做到专注于自己的科研工作，不受外界干扰的呢？

最好的法子就是陶渊明说的 “心远地自偏”。

如何做到 “心远地自偏”？网上和各种书籍介绍了很多方法，例如自我控制。我认为，最轻松、最愉悦又最高效的方法是纯粹，也就是沉浸于自己的工作，没有任何功利目的，如果说有目的，那么唯一目的是乐在其中。

人只要纯粹，自然而然就进入 “心远地自偏” 的境地，根本无需刻意，无需自控。

放眼各行各业，静观芸芸众生，不难发现，虽然纯粹不一定使人成为顶级人才，但顶级人才都是纯粹的；纵使纯粹不一定使人成为顶级人才，但纯粹的人都是幸福快乐的。

同学们，自己的路得自己走。同样，自己的问题得自己解决。那位学弟的问题也是你们的问题。相信你们已经找到或将很快找到你们的答案。祝你们早日成为自己领域的顶级人才！

原文：

• 科学网 — 如何成为一个顶级科学家？ - 文双春的博文 2025-6-20 11:18
  https://blog.sciencenet.cn/blog-412323-1490547.html