http://sciexplorer.blogspot.ca/2013/09/gauge-theory.html
量子computer can do "类比和联想" - 西西河
2014年4月1日 - I wrote in the past about 彭恒武commenting on "愛因斯坦两句話", but can't find the link. basically, 愛因斯坦分析逻辑/演繹法則model helped ...
量子 computer can do "类比和联想" [ 晓兵 ] 于:2014-04-01 12:41:03 复:3995559
量子 computer can do "类比和联想" [ 晓兵 ] 于:2014-04-01 12:41:03 复:3995559
first of all, this is a very important point, thanks you two for bringing it up in the discussion.
鸿乾：
"在现在的计算机中，你存一个图像就是一个图像，你取出来，还是那个图像，非常精确，如果有所误差，你就根本取不出来。而且这个图像的记忆和对这个图像的理解一点关系都没有，记忆是记忆，理解是理解，记忆是存储体中的，理解是存储外面的软件的运行的结果。因此，这个计算技术体系中，不可能产生类别和联系，即使有，也不是自然产生的，而是外部刻意追求而加进去的。扩大了讲，就是说，基本上没有可能产生智能。
但是在脑中，完全不同。记忆的东西，是神经系统分解进而理解（这个理解的含义，请注意，有所不同）的东西。因此，在这个基础上，如果有所误差（有意的，比如说放开了幻想，或无意的，比如说醉酒），那么就自然产生有些不同的记忆提取，但是其主体又是同样的。这样就产生了类比和联想的神经基础。现在大家都比较认同，这其实是智能的最基础的属性和特征。" this is wonderful.
1.
now, without going into specifics, human brain "类比和联想" can be approximated by future quantum computer's "量子態相互作用";
roughly speaking, in real world mesoscopic (vs newton macroscopic and qm microscopic, kind of) 纳米 material & technology, we already have 隧道效应与隧道电流 due to
some kind of "量子態相互作用 (kind of 心有灵犀一点通 between people across SR/GR time/space if you will, as an analogy)", where we don't have 载流子(some kind of quasi "real" 粒子, 準粒子 )加速和碰撞, so it is real 量子效应 (still local, non-sr, & if SR, we get into QFT) in room temperature, functioning kind of like our brain doing 量子 computing everyday;
similarly, in 超導 material and technology, we basically have figured out how to utilize "量子態相互作用" tricks, as opposed to the conventional/classic 粒子 such as 電子 doing heavy lifting of energy transfer stuff by themselves only, now we have an "quantum organization" at work, still largely @mesoscopic level.
"Mesoscopic physics就是「介觀」物理. 一. 「介觀」物理. 「介觀」物理的主要研究對象是介於「微觀」尺度與「巨觀」尺度之間的物質性質。微觀的尺度是指原子、", etc.
2.
生物大分子尺寸为纳米级 or close, and again roughly speaking "量子態相互作用" induced 隧道电流 in 纳米 stuff in many case are due to "能带简并" stuff, and I would guess that very likely in our brain, we have similar 神经元"能带简并" (very organized, vs "自由粒子玻尔兹曼分布 etc, not really organized) making "量子態相互作用" possible;
3.
so what is point or where is money? or "implications"? what & where is the "apps" for me and now?
量子 computer in macroscopic environment/heat bath (like room temperature and massive of whatever) in real life/large production is really hard, if ever possible;
"witten1 原创】量子生物学 I 摘要和前言 ( 复:91 ↑69 ↓0
这是前几天在Nature Physics看到是一篇有趣综述，现在寒假时间，尝试翻译一下以作为科普", kind of an example of bio system's real quantum working in macroscopic heat bath, and how to model it, etc.
so, fundamentally, AI challenge is not a math issue, it is a physics issue; without real breaking through in physics, software based computing like AI/大數據 stuff are not really going anywhere;
as I wroted before, we still don't even have a real model for quantum 生物大分子 computing, which is so far limited to a couple of thousands atoms working together, where in gene or protein we have millions if not zillions atoms working together;
one road block is how to model the strong if not full interaction between those atoms or 分子, so far physics can only handle quantized interaction or linearized/renormalized interaction, or "simplified" interaction, roughly speacking; but that kind of interaction is not real interaction anymore, humanity needs 爱因斯坦 or his type.
quantum chemistry 's monte carlo simulation etc (basically 大數據) has been going on for years, still limited by computing capacity as said, and fundamentally, limited by the lack of a theoretical model in handling a strong/non-linear interactions.
before breaking through in quantum chemistry and quantum computer, as I wrote before, we are basically eating GMO/基因 food stuff, with an experience based/very rough model only, taking unknown risk, unhedged, how can you hedge something unknown?
for quantum chemistry, even the "simplified" interaction" is difficult when simulating millions atom/分子 working together, future quantum computer may help that, still, we need a strong/or full interaction model to handle 阶级斗争 stuff at brain atom/分子 level, as good as TG does, at least, or TG senior folks will still have their best jobs in the world(:).
4.
没有新的热庫=溫度不變, 能量交換,sys 自我内耗 (晓兵;字2282 花6 2013-08-15 23:34:59
近代自然科学禀性探讨（一） 花56 总阅:13577 witten1 2013
http://www.ccthere.com/topic/3903480/2
strong or full interactions is one of 新的热庫, if we break into it, then we will have an gigantic progress in civilization, where "social science" 神职人员 like Chinese TG and US wall street will still have jobs, but getting paid much much less for their "BS" work.
kind of like today, because of global internet, 作家哲学家 still 忽悠 around, but getting paid much much less, a few of them still 忽悠 mass/ordinary people, but society as a whole is paying 作家哲学家 much less for their 忽悠;
5.
it has been for a while: Chinese TG and US wall street (excluding US political elite and google folks) somehow & for some known and unknown reasons, possibly because of "量子態相互作用" between them(:)(TG knows US WS always likes money, so buy them out), they have and will much more likely to work together to make big money and therefore to defend their jobs than otherwise, and they have been working together anyway in the past, planned or not planned, etc. of course, on other hand, google folks always try to break down the GFW of china, relentlessly.
Or one could argue that, as a strategy to survive and prosper, Chinese TG has been and will be carefully doing 统一战线 with US financial capital, to hedge against US political elite and google folks' long term strategic evil goal of breaking down Chinese TG into pieces, eventually.
with that model, Chinese TG's 2nd 淮海战役/城镇化 will and must work out with US capital's strong pariticipation, and both of them will make big money as usual, with money and china's GDP growth, TG can maintain its ruling elite status in china, and china somehow as a super global power, next 10 years, very likely.
and google will keep bring out new toys based on likely fake AI, until MIT folks figure out a real quantum computer for massive production, before that, china's GFW will be fairly solid. no worry for TG.
as I posted before, fundamentally, the best strategy for Chinese nation to fend off this eventual "white wolf offense" on Chinese nation (TG and Chinese nation some how are all mingled together, as a strategy of TG, TG=china) is to develop a 李光耀 连战 proposed 新加坡/TW/china mainland 邦聯, and with a global network of almost 100 million Chinese possessing white's science/technology etc, this great china encompassing pacific will be a nightmare to us/Europe political elite and google alike technology power. then, a real global game changer may come into play, OMG, white house in nightmare everyday, in and out of its war room.
But, TG already fxxked 李光耀/连战 day dream, TG's red Gen I&II doesn't want to share power with other Chinese elite, period. never. and that window of opportunity has likely been closed on TG already now.
and I would think, that uncle sam's political elite will work even harder to make sure that "window" is closed forever. It is the super #1 priority for every US president going forward.
6.
still, after all these stuff, I would think that a much more diversified ccthere.com as it used to be will benefit everybody, including those TG 党小组 folks (many overseas volunteers) here, new stuff/new brain food from ccthere.com will help them expand their knowledge and to get promoted, while doing 熱輻射 (治大国如烹小鲜, maximizing brain entropy of Chinese folks, kind of, 意识形态战役, if 赢不了, messing it up, my guess of X'意识形态战役 model ) work for TG, better to keep your own brain from maximizing entropy, this is good for you, I really mean it, not to offend anybody, which is meaning less in this anonymous public forum, aside from TG's ccthere project goal(:).
7.
http://www.ccthere.com/alist/3986059
科学 = 逻辑 + 实证 [ Solitude ]
前者主要指分析（演绎）逻辑，也就是假设，推理，结论，blabla...这个东西主要起源于古希腊的苏格拉底，柏拉图，亚里士多德，最早最有名的产品就是欧几里德的几何原本了。欧几里德本人就是柏拉图学园的学生。后者我想还是要感谢伽利略的启蒙吧，就不多说了。
科学当然也需要归纳逻辑（白米，黑米，红米都能吃，所以所有的米都能吃）的帮助。其实任何人都离不开归纳逻辑，否则会饿死的（罗素语）。但是依赖归纳逻辑的科学是不严谨的，最终还是要靠分析逻辑"
"歸納法是採用「由部分累積到整全」的研究途徑，而演繹法則是「由已知部分透過邏輯推知未知部分」的研究途徑"
I wrote in the past about 彭恒武 commenting on "愛因斯坦两句話", but can't find the link. basically, 愛因斯坦 分析逻辑/演繹法則 model helped humanity discovered atom/分子, with his 理論模型 (basically statistical physics/波爾茨曼 theory based modeling of 布朗運動 ) work on 布朗運動, and his 光电效应 pioneered quantum physics, and without those two breaking through, where humanity would have been today? likely we will be all toiling somewhere in a coal mine etc, supervised by a bounce of 政治委员/政治部主任, globally.
and 愛因斯坦 分析逻辑/演繹法則 model on atom/分子 is a non 简并 model("自由粒子玻尔兹曼分布"), later, he and 玻色 worked out 玻色－爱因斯坦统计, the 简并 version (it has a 自由粒子 version as well), which is still one of the fundamental model quantum physics use today in working on 玻色－愛因斯坦凝聚 type material & technology in those such as 量子效应 in 介觀物理/纳米, and we have not talked about 愛因斯坦's SR & GR yet. He is a great man.
by the way, 费米统计 is an another qm stat model, some us researchers already utilized that model in analyzing consumption pattern for mass consumers, such as movie renting, I posed it somewhere in that past.
now, social science, yes, it is "different" from physics, but without physics, social science will be still a science inside churches, with 政治委员/政治部主任 telling you about what 宇宙真理 looks like, we all know what that BS looks like;
can humanity afford losing "科学 = 逻辑 + 实证" as a 公知 model in physical science in particular and in humanity/society in general? what is risk? is TG china type 7% GDP growth worth the risk/cost of abandoning white's 公知 model for humanity? does humanity have any alternative model at all?
actually, even some white 公知 social scientists are bit of worried about brain science progress too, (charlierose.com). there is this very famous US 作家哲学家 recently talking about brain science breaking through vs white's traditional ideology myth/idols of thousand years. In the show, this super famous 作家 asks, if computer can do all the thinking as our brain do, what about our "faith" systems? he can't imagine a world of that, thinking that would be as serious as the earth is hit by an earth shaking object from universe. I don't remember his name.
if nothing else, nobody would care about his half political half history and beautifully written 文学作品 anymore, but he said, he really worries about humanity as a whole in the face of this mind boggling quantum brain science potential break through.
8.
as I keep saying, Chinese TG and its model will work out in china for the foreseeable future, and it will benefit Chinese and global economy, but for god's sake, for your children, if you can afford it, have them study English and quantum physics, in US or Europe, and I hope I don't get anybody offended.
meanwhile, TG's 2nd 淮海战役/城镇化 will go on relentlessly and likely successfully, anyway, regardless, get it? and on the way, get some money into your accout (:), the way many TG senor traders do, why not!?
-----------
隧道效应与隧道电流_百度文库
wenku.baidu.com/view/f488e723af45b307e87197e6.html
轉為繁體網頁
2011年5月24日 - 1-6 隧道效应与隧道电流? 当p-n结两边都是重掺杂，费米能级进入导带和价带时，Esaki隧穿产生，可以因此制得隧道二极管。这种器件可以用作高速
---------
今天在arXiv上读到了一篇非常有趣的论文，由MIT的物理学家Max Tegmark撰写，名为《 Consciousnessas a State of Matter》(作为物质状态的意识）。他认为，自我意识可以认为是某种物质形态，如文中的表一所示，意识必须同时包含有长期存在的状态，集成化的信息，容易写入性，以及复杂的动力学。气体，液体，固体，乃至计算机都只能满足一部分判据。
index为了解释意识可以被看成是物质的一种形态，他提出了六条原理，见表二
火狐截图_2014-01-08T02-53-08.299Z
利用这些原理，他主要研究了”量子因子分解问题“，或者说作为一个有意识的的观察者，比如说我们，为什么可以感受特定的希尔伯特空间分解所对应的经典空 间，而不是傅里叶空间。或者更一般的，为什么我们把周围的世界理解为动态的层级，其中包含许多强烈集成且相对独立的物体。他认为，这个原理与所谓的从头开 始物理问题（physics-from-scratch）有关：我们如何才能从不过两个厄米矩阵中提取出三维空间和我们周围的半经典世界。能否仅从哈密顿 量H中提取出这些信息，而H完全可以仅从它的本征能谱来描述。
接下来，Max Tegmark详细的讨论了什么叫做Integration(整体性)。在他看来，我们的世界是分层次的客体。比如说，你正在喝一杯冰水，你会感受到在玻 璃杯中有冰块。玻璃和冰块是分立的客体，因为它们都各自是一个整体且相对独立，它们内部的联系远远比与外部的联系紧密。我们可以定义物体的稳定性为集成温 度（把整体分离为部分所需的能量密度）和独立性温度（在层级内把母辈物体分离开所需的能量密度）之比。比如说，冰块的独立温度大概是3毫开，集成温度大概 是300开，稳定性是10^5。在下一级的结构中，氧原子和氢原子的稳定性都是10。氧原子核的稳定性是10^5。稳定性越高，这个物体越容易被我们感知和定义。
他发现，利用纠错码，经典物理允许信息基本上完全地被集成。任意一个包含至少半个比特的信息的子系统就可从剩下的比特中重建出来。存储在Hopeld neural networks (Hopeld神经网络）中的信息是天然的可纠错的。但是10^11个 神经元只能支持大概37个比特的集成了的信息。这就带来了一个集成化的悖论：为什么在我们意识体验所包含的信息内容似乎远大于37个比特。更糟的是，他发 现把这个结果推广到量子信息领域，反而加重了集成性悖论：量子信息系统只能支持不多于四分之一集成化的比特。实际上，对于任意大的量子系统，无论我们如何 编码，它所包含的可集成的信息都不会超过四分之一个比特。这强烈的暗示我们，集成性原理至少需要一个附加的原理作为补充。
他接下来探讨了独立性原理，讨论了如何通过希尔伯特空间分解实现其对应的哈密顿量分立为互相独立的部分。他发现了量子芝诺效应悖论：如果我们把宇宙分为最 为相互独立的几个客体，那么所有的运动都会陷入中止。既然有意识的的观察者显然没有感受到任何的停滞，那么集成性和独立性原理必须还需要至少一个原理来作 为补充。
进一步的，他研究了动力学原理，因为有意识的系统不仅能存储信息，还要能处理它。他认为能量相干性（energy coherence）\delta H \equiv \sqrt{2\text{tr}\dot{\rho}^2} 可以作为动力学的合适度量，它与时间无关，且在某些纯态情况下约化为能量的不确定性\Delta H。把动力学最大化只会导致无聊的周期解，无法支撑复杂的信息处理。但是减小\Delta H到合适的值时，将出现混沌和复杂的动力学，能遍历希尔伯特空间的所有维度。他 发现高度的自主性（独立性和动力学原理的结合）即使在一个高度开放的系统中也是可以实现的。
由上可知，Max Tegmark并未解决量子分解问题，但是这些结果可以帮助人们聚焦问题，并能强调具体的公开子问题和从观察得来的各种暗示和线索 。他还提出了一些公开的问题：
1.因子分解和鸡与蛋的问题：量子态和分解哪个先哪个后？
2.因子分解和集成化悖论
3.因子分解和时间的浮现
正定矩阵怎么理解较好？
鸿乾：
"在现在的计算机中，你存一个图像就是一个图像，你取出来，还是那个图像，非常精确，如果有所误差，你就根本取不出来。而且这个图像的记忆和对这个图像的理解一点关系都没有，记忆是记忆，理解是理解，记忆是存储体中的，理解是存储外面的软件的运行的结果。因此，这个计算技术体系中，不可能产生类别和联系，即使有，也不是自然产生的，而是外部刻意追求而加进去的。扩大了讲，就是说，基本上没有可能产生智能。
但是在脑中，完全不同。记忆的东西，是神经系统分解进而理解（这个理解的含义，请注意，有所不同）的东西。因此，在这个基础上，如果有所误差（有意的，比如说放开了幻想，或无意的，比如说醉酒），那么就自然产生有些不同的记忆提取，但是其主体又是同样的。这样就产生了类比和联想的神经基础。现在大家都比较认同，这其实是智能的最基础的属性和特征。" this is wonderful.
1.
now, without going into specifics, human brain "类比和联想" can be approximated by future quantum computer's "量子態相互作用";
roughly speaking, in real world mesoscopic (vs newton macroscopic and qm microscopic, kind of) 纳米 material & technology, we already have 隧道效应与隧道电流 due to
some kind of "量子態相互作用 (kind of 心有灵犀一点通 between people across SR/GR time/space if you will, as an analogy)", where we don't have 载流子(some kind of quasi "real" 粒子, 準粒子 )加速和碰撞, so it is real 量子效应 (still local, non-sr, & if SR, we get into QFT) in room temperature, functioning kind of like our brain doing 量子 computing everyday;
similarly, in 超導 material and technology, we basically have figured out how to utilize "量子態相互作用" tricks, as opposed to the conventional/classic 粒子 such as 電子 doing heavy lifting of energy transfer stuff by themselves only, now we have an "quantum organization" at work, still largely @mesoscopic level.
"Mesoscopic physics就是「介觀」物理. 一. 「介觀」物理. 「介觀」物理的主要研究對象是介於「微觀」尺度與「巨觀」尺度之間的物質性質。微觀的尺度是指原子、", etc.
2.
生物大分子尺寸为纳米级 or close, and again roughly speaking "量子態相互作用" induced 隧道电流 in 纳米 stuff in many case are due to "能带简并" stuff, and I would guess that very likely in our brain, we have similar 神经元"能带简并" (very organized, vs "自由粒子玻尔兹曼分布 etc, not really organized) making "量子態相互作用" possible;
3.
so what is point or where is money? or "implications"? what & where is the "apps" for me and now?
量子 computer in macroscopic environment/heat bath (like room temperature and massive of whatever) in real life/large production is really hard, if ever possible;
"witten1 原创】量子生物学 I 摘要和前言 ( 复:91 ↑69 ↓0
这是前几天在Nature Physics看到是一篇有趣综述，现在寒假时间，尝试翻译一下以作为科普", kind of an example of bio system's real quantum working in macroscopic heat bath, and how to model it, etc.
so, fundamentally, AI challenge is not a math issue, it is a physics issue; without real breaking through in physics, software based computing like AI/大數據 stuff are not really going anywhere;
as I wroted before, we still don't even have a real model for quantum 生物大分子 computing, which is so far limited to a couple of thousands atoms working together, where in gene or protein we have millions if not zillions atoms working together;
one road block is how to model the strong if not full interaction between those atoms or 分子, so far physics can only handle quantized interaction or linearized/renormalized interaction, or "simplified" interaction, roughly speacking; but that kind of interaction is not real interaction anymore, humanity needs 爱因斯坦 or his type.
quantum chemistry 's monte carlo simulation etc (basically 大數據) has been going on for years, still limited by computing capacity as said, and fundamentally, limited by the lack of a theoretical model in handling a strong/non-linear interactions.
before breaking through in quantum chemistry and quantum computer, as I wrote before, we are basically eating GMO/基因 food stuff, with an experience based/very rough model only, taking unknown risk, unhedged, how can you hedge something unknown?
for quantum chemistry, even the "simplified" interaction" is difficult when simulating millions atom/分子 working together, future quantum computer may help that, still, we need a strong/or full interaction model to handle 阶级斗争 stuff at brain atom/分子 level, as good as TG does, at least, or TG senior folks will still have their best jobs in the world(:).
4.
没有新的热庫=溫度不變, 能量交換,sys 自我内耗 (晓兵;字2282 花6 2013-08-15 23:34:59
近代自然科学禀性探讨（一） 花56 总阅:13577 witten1 2013
http://www.ccthere.com/topic/3903480/2
strong or full interactions is one of 新的热庫, if we break into it, then we will have an gigantic progress in civilization, where "social science" 神职人员 like Chinese TG and US wall street will still have jobs, but getting paid much much less for their "BS" work.
kind of like today, because of global internet, 作家哲学家 still 忽悠 around, but getting paid much much less, a few of them still 忽悠 mass/ordinary people, but society as a whole is paying 作家哲学家 much less for their 忽悠;
5.
it has been for a while: Chinese TG and US wall street (excluding US political elite and google folks) somehow & for some known and unknown reasons, possibly because of "量子態相互作用" between them(:)(TG knows US WS always likes money, so buy them out), they have and will much more likely to work together to make big money and therefore to defend their jobs than otherwise, and they have been working together anyway in the past, planned or not planned, etc. of course, on other hand, google folks always try to break down the GFW of china, relentlessly.
Or one could argue that, as a strategy to survive and prosper, Chinese TG has been and will be carefully doing 统一战线 with US financial capital, to hedge against US political elite and google folks' long term strategic evil goal of breaking down Chinese TG into pieces, eventually.
with that model, Chinese TG's 2nd 淮海战役/城镇化 will and must work out with US capital's strong pariticipation, and both of them will make big money as usual, with money and china's GDP growth, TG can maintain its ruling elite status in china, and china somehow as a super global power, next 10 years, very likely.
and google will keep bring out new toys based on likely fake AI, until MIT folks figure out a real quantum computer for massive production, before that, china's GFW will be fairly solid. no worry for TG.
as I posted before, fundamentally, the best strategy for Chinese nation to fend off this eventual "white wolf offense" on Chinese nation (TG and Chinese nation some how are all mingled together, as a strategy of TG, TG=china) is to develop a 李光耀 连战 proposed 新加坡/TW/china mainland 邦聯, and with a global network of almost 100 million Chinese possessing white's science/technology etc, this great china encompassing pacific will be a nightmare to us/Europe political elite and google alike technology power. then, a real global game changer may come into play, OMG, white house in nightmare everyday, in and out of its war room.
But, TG already fxxked 李光耀/连战 day dream, TG's red Gen I&II doesn't want to share power with other Chinese elite, period. never. and that window of opportunity has likely been closed on TG already now.
and I would think, that uncle sam's political elite will work even harder to make sure that "window" is closed forever. It is the super #1 priority for every US president going forward.
6.
still, after all these stuff, I would think that a much more diversified ccthere.com as it used to be will benefit everybody, including those TG 党小组 folks (many overseas volunteers) here, new stuff/new brain food from ccthere.com will help them expand their knowledge and to get promoted, while doing 熱輻射 (治大国如烹小鲜, maximizing brain entropy of Chinese folks, kind of, 意识形态战役, if 赢不了, messing it up, my guess of X'意识形态战役 model ) work for TG, better to keep your own brain from maximizing entropy, this is good for you, I really mean it, not to offend anybody, which is meaning less in this anonymous public forum, aside from TG's ccthere project goal(:).
7.
http://www.ccthere.com/alist/3986059
科学 = 逻辑 + 实证 [ Solitude ]
前者主要指分析（演绎）逻辑，也就是假设，推理，结论，blabla...这个东西主要起源于古希腊的苏格拉底，柏拉图，亚里士多德，最早最有名的产品就是欧几里德的几何原本了。欧几里德本人就是柏拉图学园的学生。后者我想还是要感谢伽利略的启蒙吧，就不多说了。
科学当然也需要归纳逻辑（白米，黑米，红米都能吃，所以所有的米都能吃）的帮助。其实任何人都离不开归纳逻辑，否则会饿死的（罗素语）。但是依赖归纳逻辑的科学是不严谨的，最终还是要靠分析逻辑"
"歸納法是採用「由部分累積到整全」的研究途徑，而演繹法則是「由已知部分透過邏輯推知未知部分」的研究途徑"
I wrote in the past about 彭恒武 commenting on "愛因斯坦两句話", but can't find the link. basically, 愛因斯坦 分析逻辑/演繹法則 model helped humanity discovered atom/分子, with his 理論模型 (basically statistical physics/波爾茨曼 theory based modeling of 布朗運動 ) work on 布朗運動, and his 光电效应 pioneered quantum physics, and without those two breaking through, where humanity would have been today? likely we will be all toiling somewhere in a coal mine etc, supervised by a bounce of 政治委员/政治部主任, globally.
and 愛因斯坦 分析逻辑/演繹法則 model on atom/分子 is a non 简并 model("自由粒子玻尔兹曼分布"), later, he and 玻色 worked out 玻色－爱因斯坦统计, the 简并 version (it has a 自由粒子 version as well), which is still one of the fundamental model quantum physics use today in working on 玻色－愛因斯坦凝聚 type material & technology in those such as 量子效应 in 介觀物理/纳米, and we have not talked about 愛因斯坦's SR & GR yet. He is a great man.
by the way, 费米统计 is an another qm stat model, some us researchers already utilized that model in analyzing consumption pattern for mass consumers, such as movie renting, I posed it somewhere in that past.
now, social science, yes, it is "different" from physics, but without physics, social science will be still a science inside churches, with 政治委员/政治部主任 telling you about what 宇宙真理 looks like, we all know what that BS looks like;
can humanity afford losing "科学 = 逻辑 + 实证" as a 公知 model in physical science in particular and in humanity/society in general? what is risk? is TG china type 7% GDP growth worth the risk/cost of abandoning white's 公知 model for humanity? does humanity have any alternative model at all?
actually, even some white 公知 social scientists are bit of worried about brain science progress too, (charlierose.com). there is this very famous US 作家哲学家 recently talking about brain science breaking through vs white's traditional ideology myth/idols of thousand years. In the show, this super famous 作家 asks, if computer can do all the thinking as our brain do, what about our "faith" systems? he can't imagine a world of that, thinking that would be as serious as the earth is hit by an earth shaking object from universe. I don't remember his name.
if nothing else, nobody would care about his half political half history and beautifully written 文学作品 anymore, but he said, he really worries about humanity as a whole in the face of this mind boggling quantum brain science potential break through.
8.
as I keep saying, Chinese TG and its model will work out in china for the foreseeable future, and it will benefit Chinese and global economy, but for god's sake, for your children, if you can afford it, have them study English and quantum physics, in US or Europe, and I hope I don't get anybody offended.
meanwhile, TG's 2nd 淮海战役/城镇化 will go on relentlessly and likely successfully, anyway, regardless, get it? and on the way, get some money into your accout (:), the way many TG senor traders do, why not!?
-----------
隧道效应与隧道电流_百度文库
wenku.baidu.com/view/f488e723af45b307e87197e6.html
轉為繁體網頁
2011年5月24日 - 1-6 隧道效应与隧道电流? 当p-n结两边都是重掺杂，费米能级进入导带和价带时，Esaki隧穿产生，可以因此制得隧道二极管。这种器件可以用作高速
---------
今天在arXiv上读到了一篇非常有趣的论文，由MIT的物理学家Max Tegmark撰写，名为《 Consciousnessas a State of Matter》(作为物质状态的意识）。他认为，自我意识可以认为是某种物质形态，如文中的表一所示，意识必须同时包含有长期存在的状态，集成化的信息，容易写入性，以及复杂的动力学。气体，液体，固体，乃至计算机都只能满足一部分判据。
index为了解释意识可以被看成是物质的一种形态，他提出了六条原理，见表二
火狐截图_2014-01-08T02-53-08.299Z
利用这些原理，他主要研究了”量子因子分解问题“，或者说作为一个有意识的的观察者，比如说我们，为什么可以感受特定的希尔伯特空间分解所对应的经典空 间，而不是傅里叶空间。或者更一般的，为什么我们把周围的世界理解为动态的层级，其中包含许多强烈集成且相对独立的物体。他认为，这个原理与所谓的从头开 始物理问题（physics-from-scratch）有关：我们如何才能从不过两个厄米矩阵中提取出三维空间和我们周围的半经典世界。能否仅从哈密顿 量H中提取出这些信息，而H完全可以仅从它的本征能谱来描述。
接下来，Max Tegmark详细的讨论了什么叫做Integration(整体性)。在他看来，我们的世界是分层次的客体。比如说，你正在喝一杯冰水，你会感受到在玻 璃杯中有冰块。玻璃和冰块是分立的客体，因为它们都各自是一个整体且相对独立，它们内部的联系远远比与外部的联系紧密。我们可以定义物体的稳定性为集成温 度（把整体分离为部分所需的能量密度）和独立性温度（在层级内把母辈物体分离开所需的能量密度）之比。比如说，冰块的独立温度大概是3毫开，集成温度大概 是300开，稳定性是10^5。在下一级的结构中，氧原子和氢原子的稳定性都是10。氧原子核的稳定性是10^5。稳定性越高，这个物体越容易被我们感知和定义。
他发现，利用纠错码，经典物理允许信息基本上完全地被集成。任意一个包含至少半个比特的信息的子系统就可从剩下的比特中重建出来。存储在Hopeld neural networks (Hopeld神经网络）中的信息是天然的可纠错的。但是10^11个 神经元只能支持大概37个比特的集成了的信息。这就带来了一个集成化的悖论：为什么在我们意识体验所包含的信息内容似乎远大于37个比特。更糟的是，他发 现把这个结果推广到量子信息领域，反而加重了集成性悖论：量子信息系统只能支持不多于四分之一集成化的比特。实际上，对于任意大的量子系统，无论我们如何 编码，它所包含的可集成的信息都不会超过四分之一个比特。这强烈的暗示我们，集成性原理至少需要一个附加的原理作为补充。
他接下来探讨了独立性原理，讨论了如何通过希尔伯特空间分解实现其对应的哈密顿量分立为互相独立的部分。他发现了量子芝诺效应悖论：如果我们把宇宙分为最 为相互独立的几个客体，那么所有的运动都会陷入中止。既然有意识的的观察者显然没有感受到任何的停滞，那么集成性和独立性原理必须还需要至少一个原理来作 为补充。
进一步的，他研究了动力学原理，因为有意识的系统不仅能存储信息，还要能处理它。他认为能量相干性（energy coherence）\delta H \equiv \sqrt{2\text{tr}\dot{\rho}^2} 可以作为动力学的合适度量，它与时间无关，且在某些纯态情况下约化为能量的不确定性\Delta H。把动力学最大化只会导致无聊的周期解，无法支撑复杂的信息处理。但是减小\Delta H到合适的值时，将出现混沌和复杂的动力学，能遍历希尔伯特空间的所有维度。他 发现高度的自主性（独立性和动力学原理的结合）即使在一个高度开放的系统中也是可以实现的。
由上可知，Max Tegmark并未解决量子分解问题，但是这些结果可以帮助人们聚焦问题，并能强调具体的公开子问题和从观察得来的各种暗示和线索 。他还提出了一些公开的问题：
1.因子分解和鸡与蛋的问题：量子态和分解哪个先哪个后？
2.因子分解和集成化悖论
3.因子分解和时间的浮现
正定矩阵怎么理解较好？
No comments:
Post a Comment