真正的随机数生成

本文介绍了真正的随机数生成的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

当我们实际测量某物时，我们究竟是在谈论真正的随机数".我的意思是，它并不能衡量随机性的相反情况.

How is exactly that we talk about "true random" numbers when we are actually measuring something. I mean, isn't measuring almost the opposite of randomness.

Som文章说，例如，掷骰子是真正的随机".当然这不是伪随机的，但它甚至是随机的吗?如果您有一台可以从完全相同的位置向骰子投掷骰子的机器，并且总是以完全相同的力朝相同的方向投掷骰子，那么它不会总是产生相同的数字吗? (我知道是的.)

Som articles says that, for example, throwing a dice is "true random". Of course it isn't Pseudo-random, but is it even random?? If you could have a machine that throw dices from de exactly same position and always in the same direction with the exact same force always: woudn't it always turn out the same number? (I thing it does).

请，有人可以帮我理解真实随机"数字吗?

Please, can someone help me understand "true random" numbers??

推荐答案

量子效应是这种真实随机性"的来源.例如. 海森堡不诚实原则 说，掷骰子无法准确定义投掷臂的冲动和位置. (阅读流行科学量子物理学可能会让人感到恐惧-我们世界的可预测性和稳定性似乎不过是统计学的壮举.)

Quantum effects are the source of this "True Randomness". E.g. the Heisenberg Uncertanity Principle says that your dice thrower can't exactly define both impulse and location of its throwing arm. (Reading up on pop-sci quantum physics can be scary - the predictability and stability of our world seems to be no more than a great feat of statistics.)

[edit]由于它出现在注释中:还有其他一些较少模糊"的看起来随机"的过程，例如模辊的磨损和空气湍流.但是，所有这些事情都可能被认为超出了我们的知识范围，但是从根本上讲是确定性的(假设是客观的现实).至少在广泛接受的哥本哈根解释下，量子过程确实是随机的. [/edit]

[edit] Since it came up in the comments: There are other, less "obscure" processes "looking random", e.g. wear and air turbulence for a die roll. However, all these things could be argued to be beyond our knowledge but fundamentally deterministic (assuming an objective reality.) Quantum processes are truly random at least under the widely accepted Copenhagen interpretation. [/edit]

-如其他答复所述，有将量子效应转换为可观察到的随机数生成器的设备.有一些算法可以提取"任何数据流的随机性.有测试算法可以检查数据流是否像随机流一样表现".

There are - as mentioned in other replies - appliances that turn quantum effects into observable random number generators. There are algorithms to "extract" the randomness of any stream of data. There are test algorithms to check if a stream of data "behaves" like a random stream.

您可以 相当成功地论证随机"是人为概念，即不是客观世界的组成部分，而是我们的理解极限(尽管不确定性原则)被视为不只是观察者效果).

OTOH you can argue rather successfully that "random" is a man-made concept, i.e. something that isn't integral part of the objective world, but our limit of understanding (though the uncertainty principle is considered to be not just an observer effect).

当有人要求任何随机数生成器时，反问应该是:针对什么应用?在此讨论中:您需要愚弄谁?伪与真只是生成机制，而不是根本的对立面.

When someone asks for any random number generator, the counter question should be: for what application? In the context of this discussion: who do you need to fool? Pseudo vs. True are just generation mechanisms, not fundamental opposites.

从这个意义上讲，混乱的行为对于大多数目的来说通常是足够随机的"，并且已经可以以很少的自由度创建.

In that sense, chaotic beahvior is often "random enough" for most purposes, and can be created with few degrees of freedom already.