Infinite-dimensional symmetry opens up possibility of a new physics—and new particles November 16, 2018, University of Warsaw Credit: CC0 Public Domain The symmetries that govern the world of elementary particles at the most elementary level could be radically different from what has so far been thought. This surprising conclusion emerges from new work published by theoreticians from Warsaw and Potsdam. The scheme they posit unifies all the forces of nature in a way that is consistent with existing observations and anticipates the existence of new particles with unusual properties that may even be present in our close environs. For a half-century, physicists have been trying to construct a theory that unites all four fundamental forces of nature, describes the known elementary particles and predicts the existence of new ones. So far, these attempts have not found experimental confirmation, and the Standard Model—an incomplete, but surprisingly effective theoretical construct—is still the best description of the quantum world. In a recent paper in Physical Review Letters , Prof. Krzysztof Meissner from the Institute of Theoretical Physics, Faculty of Physics, University of Warsaw, and Prof. Hermann Nicolai from the Max-Planck-Institut für Gravitationsphysik in Potsdam have presented a new scheme generalizing the Standard Model that incorporates gravitation into the description. The new model applies a kind of symmetry not previously used in the description of elementary particles. In physics, symmetries are understood somewhat differently than in the colloquial sense of the word. For instance, whether a ball is dropped now or one minute from now, it will still fall in the same way. That is a manifestation of a certain symmetry: the laws of physics remain unchanged with respect to shifts in time. Similarly, dropping the ball from the same height in one location has the same result as dropping it in another. This means that the laws of physics are also symmetrical with respect to spatial operations. Symmetries play a huge role in physics because they are related to principles of conservation. For instance, the principle of the conservation of energy involves symmetry with respect to shifts in time, the principle of the conservation of momentum relates to symmetry of spatial displacement, and the principle of the conservation of angular momentum relates to rotational symmetry, says Prof. Meissner. Developing a supersymmetric theory to describe the symmetries between fermions and bosons began back in the 1970s. Fermions are elementary particles whose spin, a quantum property related to rotation, is expressed in odd multiples of the fraction 1/2, and they include both quarks and leptons. Among the latter are electrons, muons, tauons, and their associated neutrinos (as well as their antiparticles). Protons and neutrons, common non-elementary particles, are also fermions. Bosons, in turn, are particles with integer spin values. They include the particles responsible for forces (photons, carriers of the electromagnetic force; gluons, carrying the strong nuclear force; W and Z bosons, carrying the weak nuclear force), as well as the Higgs boson. The first supersymmetric theories tried to combine the forces typical of elementary particles, in other words the electromagnetic force with a symmetry known as U(1), the weak force with symmetry SU(2) and the strong force with symmetry SU(3). Gravity was still missing, Prof. Meissner says. The symmetry between the bosons and fermions was still global, which means the same at every point in space. Soon thereafter, theories were posited where symmetry was local, meaning it could manifest differently at each point in space. Ensuring such symmetry in the theory required for gravitation to be included, and such theories became known as supergravities. Physicists noticed that in supergravity theories in four spatiotemporal dimensions, there cannot be more than eight different supersymmetric rotations. Each such theory has a strictly defined set of fields (degrees of freedom) with different spins (0, 1/2, 1, 3/2 and 2), known respectively as the fields of scalars, fermions, bosons, gravitinos and gravitons. For supergravity N=8, which has the maximal number of rotations, there are 48 fermions (with spin 1/2), which is precisely the number of degrees of freedom required to account for the six types of quarks and six types of leptons observed in nature. There was therefore every indication that supergravity N=8 is exceptional in many respects. However, it was not ideal. One of the problems in incorporating the Standard Model into N=8 supergravity was posed by the electrical charges of quarks and leptons. All the charges turned out to be shifted by 1/6 with respect to those observed in nature: the electron had a charge of -5/6 instead of -1, the neutrino had 1/6 instead of 0, etc. This problem, first observed by Murray Gell-Mann more than 30 years ago, was not resolved until 2015, when Professors Meissner and Nicolai presented the respective mechanism for modifying the U(1) symmetry. After making this adjustment we obtained a structure with the symmetries U(1) and SU(3) known from the Standard Model. The approach proved to be very different from all other attempts at generalizing the symmetries of the Standard Model. The motivation was strengthened by the fact that the LHC accelerator failed to produce anything beyond the Standard Model and N=8 supergravity fermion content is compatible with this observation. What was missing was to add the SU(2) group, responsible for the weak nuclear force. In our recent paper, we show how this can be done. That would explain why all previous attempts at detecting new particles, motivated by theories that treated the SU(2) symmetry as spontaneously violated for low energies, but as holding in the range of high energies, had to be unsuccessful. In our view, SU(2) is just an approximation for both low and high energies, Prof. Meissner explains. Both the mechanism reconciling the electric charges of the particles, and the improvement incorporating the weak force proved to belong to a symmetry group known as E10. Unlike the symmetry groups previously used in unification theories, E10 is an infinite group, very poorly studied even in the purely mathematical sense. Prof. Nicolai with Thibault Damour and Marc Henneaux had worked on this group before, because it appeared as a symmetry in N=8 supergravity under conditions similar to those during the first moments after the Big Bang, when only one dimension was significant: time. For the first time, we have a scheme that precisely anticipates the composition of the fermions in the Standard Model—quarks and leptons—and does so with the proper electric charges. At the same time it includes gravity into the description. It is a huge surprise that the proper symmetry is the staggeringly huge symmetry group E10, virtually unknown mathematically. If further work confirms the role of this group, that will mean a radical change in our knowledge of the symmetries of nature, Prof. Meissner says. Although the dynamics is not yet understood, the scheme proposed by Professors Meissner and Nicolai makes specific predictions. It keeps the number of spin 1/2 fermions as in the Standard Model but on the other hand suggests the existence of new particles with very unusual properties. Importantly, at least some of them could be present in our immediate surroundings, and their detection should be within the possibilities of modern detection equipment. But that is a topic for a separate story. Explore further: Breaking supersymmetry More information: Krzysztof A. Meissner, Hermann Nicolai. Standard Model Fermions and Infinite-Dimensional R Symmetries, Physical Review Letters, 2018, 121 , 091601 – Published 31 August 2018 . DOI: 10.1103/PhysRevLett.121.091601 ABSTRACT Following up on our earlier work where we showed how to amend a scheme originally proposed by M. Gell-Mann to identify the 48 spin- 1 2 fermions of N = 8 supergravity that remain after complete breaking of N = 8 supersymmetry with the 3 × 16 quarks and leptons of the standard model, we further generalize the construction to account for the full SU ( 3 ) c × SU ( 2 ) w × U ( 1 ) Y assignments, with an additional family symmetry SU ( 3 ) f . Our proposal relies in an essential way on embedding the SU(8) R symmetry of N = 8 supergravity into the (infinite-dimensional) “maximal compact” subgroup K ( E 10 ) of the conjectured maximal duality symmetry E 10 . As a by-product, it predicts fractionally charged and possibly strongly interacting massive gravitinos. It also indicates how E 10 and K ( E 10 ) can supersede supersymmetry as a guiding principle for unification.
0.33333!=1/3 but 0.333333=1/3 symmetry operation 转载 ▼ 标签: graphene phonon vc-relax fft 分类: pwscf The day befor yestday, Icomplete my first phonon calculation using PWscf: phonon ofmonolayer graphene. Although I only calculated 2 kpoints in reciprocal space, I find one important trick inPWscf. That is 0.33333!=1/3 but0.333333=1/3 Firstly, I choose Hexagonalprimitive cell. Then I give the atomic position in crystalcoordinate. C 0.000000000 0.000000000 0.000000000 C 0.333330000 -0.333330000 0.000000000 In MS, the software willenforce manually input coordinates to conform the symmetry. But, PWscf does not do it.Therefore, both in cell relax and phonon calculation, PWscf willgive error message: from checkallsym : error# 1 some of the original symmetryoperations not satisfied When I change the input atomicposition to the below data, every thing goes smoothly. C 0.000000000 0.000000000 0.000000000 C 0.333333000 -0.333333000 0.000000000 The whole process can bedivided into four steps: 1.try to relax the crystalstructure and get equilibrium configuration. (using PWgui to open inputfilegraphene.rx.in) 2.try a scf calculation forfurther band calculation. (using PWgui to open input filegraphene.scf.in) 3.try to calculate phonondispersion for arbitary wavevectors. (using PWgui to open input filegraphene.ph.in) 4.use q2r.x in PH dictionary toget interatomic force constant in real space. (./q2r.x graphene.q2r.in graphene.q2r.out) 1.file name: graphene.rx.in CONTROL calculation = 'vc-relax' , restart_mode = 'from_scratch' , outdir = '/root/tmp' , pseudo_dir = '/home/raman/espresso-4.0.4/pseudo' , prefix = 'graphene' , tstress = .true. , tprnfor = .true. , / SYSTEM ibrav = 4, celldm(1) = 4.008737, celldm(3) = 4.536666, nat = 2, ntyp = 1, ecutwfc = 60 , nosym = .false. , nbnd = 8, nelec = 8, tot_charge = 0.000000, occupations = 'smearing' , degauss = 0.05D0 , smearing = 'methfessel-paxton' , / ELECTRONS conv_thr = 1.D-8 , mixing_mode = 'plain' , mixing_beta = 0.3D0 , diagonalization = 'david' , / IONS ion_dynamics = 'bfgs' , pot_extrapolation = 'second_order' , wfc_extrapolation = 'second_order' , / CELL cell_dynamics = 'bfgs' , press_conv_thr = 0.1 , / ATOMIC_SPECIES C 12.01000 C.pz-rrkjus.UPF ATOMIC_POSITIONS crystal C 0.000000000 0.000000000 0.000000000 C 0.333333333 -0.333333330 0.000000000 K_POINTS automatic 11 11 1 0 00 2.file name: graphene.scf.in CONTROL calculation = 'scf' , restart_mode = 'from_scratch' , outdir = '/root/tmp/' , pseudo_dir = '/home/raman/espresso-4.0.4/pseudo/' , prefix = 'graphene' , tstress = .true. , tprnfor = .true. , / SYSTEM ibrav = 4, celldm(1) = 4.608737, celldm(3) = 4.536666, nat = 2, ntyp = 1, ecutwfc = 60.0 , / ELECTRONS conv_thr = 1.0d-8 , mixing_beta = 0.3 , / ATOMIC_SPECIES C 12.01000 C.pz-rrkjus.UPF ATOMIC_POSITIONS crystal C 0.000000000 0.000000000 0.000000000 C 0.333333333 -0.333333333 0.000000000 K_POINTS automatic 11 11 1 0 00 3.file name: graphene.ph.in phonons ofgraphene INPUTPH outdir = '/root/tmp/' , prefix = 'graphene' , fildyn = 'graphene.dyn' , ldisp = .true., nq1 = 2 , nq2 = 2 , nq3 = 1 , epsil = .false., elph = .false., fpol = .false. , recover = .false. , amass(1) = 12.01, tr2_ph = 1.0d-12 , / 4.file name: graphene.q2r.in input fildyn='graphene.dyn',zasr='simple', flfrc='graphene111.fc' / afterthought ``warning: symmetry operation # Nnot allowed''. This is not an error. pw.x determines first the symmetryoperations (rotations) of the Bravais lattice; then checks which ofthese are symmetry operations of the system (including if neededfractional translations). This is done by rotating (and translatingif needed) the atoms in the unit cell and verifying if the rotatedunit cell coincides with the original one. If a symmetry operation contains a fractional translation that isincompatible with the FFT grid, it is discarded in order to preventproblems with symmetrization. Typicalfractional translations are 1/2 or 1/3 of a lattice vector. If theFFT grid dimension along that direction is not divisiblerespectively by 2 or by 3 , the symmetry operation will nottransform the FFT grid intoitself.(在有1/2和1/3分数坐标时,fft的grid要选择是2或者三的倍数,否则会出现对称性判断错误) Ref: http://www.pwscf.org/guide/2.1.2/html-node/node56.html pw.x doesn't find all thesymmetries you expected. See above to learnhow PWscf finds symmetry operations. Some of them might be missingbecause: the number ofsignificant figures in the atomic positions is not large enough. Infile PW/eqvect.f90, the variable accep is used todecide whether a rotation is a symmetry operation. Its current value (10 -5 ) is quite strict: arotated atom must coincide with another atom to 5 significantdigits. You may change the value of accep andrecompile. they are notacceptable symmetry operations of the Bravais lattice. This is thecase for C 60 , for instance: the I h icosahedral group ofC 60 contains 5-fold rotations that areincompatible with translation symmetry. the system isrotated with respect to symmetry axis. For instance: aC 60 molecule in the fcc lattice will have24 symmetry operations ( T h group)only if the double bond is aligned along oneof the crystal axis; if C 60 is rotated insome arbitrary way, pw.x may not find any symmetry, apartfrom inversion. they contain afractional translation that is incompatible with the FFT grid (seeprevious paragraph). Note that if you changecutoff or unit cell volume, the automatically computed FFT gridchanges, and this may explain changes in symmetry (and in thenumber of k-points as a consequence) for no apparent goodreason (only if you have fractional translations in the system,though). a fractional translation, without rotation, is a symmetryoperation of the system. This means that the cell is actually asupercell. In this case, all symmetry operations containingfractional translations are disabled. The reason is that inthis rather exotic case there is no simple way to select thosesymmetry operations forming a true group, in the mathematical senseof the term. (如果含有只有部分平移而不含旋转的对称操作,则可判定,这是个超原胞) Ref: http://www.pwscf.org/guide/2.1.2/html-node/node57.html 补记: CONTROL calculation = 'scf' , restart_mode = 'from_scratch' , outdir = './' , pseudo_dir = '/home/raman/espresso-4.0.4/pseudo/' , tstress = .true. , tprnfor = .true. , / SYSTEM ibrav = 4, celldm(1) = 4.590642253, celldm(3) = 4.554490003, nat = 2, ntyp = 1, ecutwfc = 70.D0 , nbnd = 8, nelec = 8, nr1 = 30 , nr2 = 30 , nr3 = 120 , / ELECTRONS conv_thr = 1.D-8 , mixing_beta = 0.7D0 , diago_full_acc = .false. , / ATOMIC_SPECIES C 12.00000 C.pz-vbc.UPF ATOMIC_POSITIONS crystal C 0.000000000 0.000000000 0.000000000 C 0.333333333 -0.333333333 0.000000000 K_POINTS automatic 23 23 1 0 00 如果让系统自动计算fft的数目:nr1,nr2,scf.out文件中会出现警告: warning: symmetry operation # 2 notallowed. fractionaltranslation: -0.3333333 0.3333333 0.0000000 in crystalcoordinates。 所以需要将nr1,nr2设置为3的倍数。但并不是所有的3的倍数都可以运行,很快会出现: fromset_fft_dim : error # 1;input nr1 value notallowed。 所以必须进行试验。(2010-05-04) 转载: http://blog.sina.com.cn/s/blog_5f15ead20100cbbt.html 我的测试:单层石墨烯 1. 坐标 C 0.000000 0.000000 0.5 C 0.333333 0.333333 0.5 2. system中设置FFT grid: nr1=30,nr2=30, nr3=120 input如下: CONTROL calculation = 'vc-relax' restart_mode = 'from_scratch', outdir = './tmp', pseudo_dir = '/home/plgong/pseudo', prefix = 'graphene' , tstress = .true., tprnfor = .true., / SYSTEM ibrav = 4, a = 2.46, c = 10 nat = 2, ntyp = 1, ecutwfc = 60, ecutrho = 480 occupations = 'smearing', degauss = 0.01, smearing = 'methfessel-paxton' nr1=60, nr2=60, nr3=120 / ELECTRONS conv_thr = 1.D-8, mixing_mode = 'plain' mixing_beta = 0.3D0 , diagonalization = 'david', / IONS ion_dynamics = 'bfgs', pot_extrapolation = 'second_order', wfc_extrapolation = 'second_order', / CELL cell_dynamics = 'bfgs', press_conv_thr = 0.1, / ATOMIC_SPECIES C 12.01000 C.pz-rrkjus.UPF ATOMIC_POSITIONS crystal C 0.000000000 0.000000000 0.5000000000 C 0.333333333 -0.333333330 0.500000000 K_POINTS automatic 12 12 1 1 1 1 结果: 24 Sym.Ops. (with inversion) 对比MS:Oprators 24 (note that:nr1,nr2,nr3大小是3的倍数,需要尝试几个数值,有时系统报错不运行!)
原载 http://blog.sina.com.cn/s/blog_729a92140101oxbx.html 在Matlab-R2011a中,用 =wavefun('bior2.2',10); subplot(2,1,1); plot(x,w); axis tight; subplot(2,1,2); plot(x,w1); axis tight; 看到国际标准 JPEG2000的小波的“连续时间函数”,像感觉到分形曲线的味道。至于得到的bior3.1、bior3.3、bior3.5的函数波形,如果是居士自己搞的,那么很可能自认为它们是错误的。不过,尖叫“Matlab牛”后,居士还是偏爱“基向量”,并以为,本短文对简化、理清文献中的连续时间小波包基函数、其自然排序、其频率排序等问题的长期缠绕,有重要意义。 无先验知识以明确被分析数据与尺度函数的关系,用Tpwp的“小波包基向量”,无需工具箱生成函数(Building Wavelet Packets, Wavelet Packet Atoms),即可方便地确定小波包变换树上任意位置的频率中心(功率或能量谱中心,区别正频率、负频率和直流)。 常用三个索引指标,尺度、频率、位置,标示一个小波包。但是,频率指标值越大,不同于1兆赫兹大于1千赫兹这样的事情,也不必意味着相应的小包中的高频能量(功率)就更大、或在低频时更小。实际上,尺度指标,常与水平(level)、深度(depth)混用,也并不直接就是小波函数概念中的“尺度值”。频率指标是,把“基本 小波和尺度函数 (或序列) ”以适当方式“运算、组合”而 形成某个“波的包裹” 的过程的一种编码。在离散变换中,可以简明地看到“高通、低通”滤波器的组合过程,但是注意,“下抽样”使频谱搬移了、使高低频率的位置转换了! 普通离散小波分解中,第一级分解后,得到的“细节系数序列”中的“直流部分”,对应原信号中的“高频成分”。 在某个尺度上,如果它的节点数(频率指标的个数)不超过被处理序列的长度N的一半,那么简单用功率谱的中心、波形过零率等物理直观真实的正频率概念,区别小波包,是自然的。 然而,在最大的尺度上,节点数(频率指标的个数)等于N,那么这些普通的“频率分辨观念”就可能显得不方便。例如,实数序列的离散傅里叶变换DFT中正频率部分(0,fs/2)中,只有N/2-1点,难道,小波包分解能分辨出约N个“正”频率点吗? 这时,小波包基向量,存在配对关系:幅度谱相同,则其定义的频率中心就相同,然而,相谱不同、有不相等的频率索引指标。这类似于DFT中的正负频率、共轭对称、幅相谱等的状况和问题。单个节点内,不再存在,可以用于分辨相位的“位置指标”。 如果遵从那些小波工具箱的处理,用滤波器和信号序列的长度,来限制分解深度,那么就遇不到这种状况。 在《随机设置小波包变换及其优选基的随机降秩矩阵》(2014-03-19)的基础上,居士做试验程序PwpRandNegf.sce,附于本文末。运行 clear ; LessLevel = 0 ; rand ( 'seed' , 1e9 ) ; exec ( 'PwpRandNegf.sce' ) ; 可得图片 1。 假设信号序列长度,随机地取为16、32、64、128,相应的最大分解深度分别为4、5、6、7。在最大分解尺度上,频率分辨率达到极限。抽出最大尺度上的所有小波包基向量,做两两比较,检验它们的FFT幅度谱的关系。 两基向量,其规范化幅度谱之间的误差,RMSE,er0,小于千之一,则视为是配对的。对于正交变换,附带地确认:两基向量为等腰三角形的直角边,即不可能是因为两向量本身相同所以幅度谱才相同,如若不然,程序报告错误。 从数据序列长度的二分之一中,减去(倒记数)相配的对数,得图片1.中的第一幅曲线图。结果始终为1,与滤波器、小波包变换的随机设置、序列长度都无关。 余下一对(故结果恒为1):涉及直流成分,和高频向量。980次实验的直流基向量偏离理想值的误差(RMSE)的累加总和,TestDC = 0.000038,很小。高频向量,被归入某对的计数结果,TestHF = 0。 配对向量的幅度谱之间的实际误差er0的总和,示于图片1.中的第二幅曲线图。“总和”用的数值的数目,与序列长度有关,但结果仍都很小。 在一个稳定的变换中,尺度参数、频率参数都相同而只是位置参数不同的小波包基向量,它们也具有相同的幅度谱,但与图片1.反应的情形不同。例如,没有直流基向量;配对向量,经历的数字运算过程更相近,所以它们的幅度谱之间的数字误差更小。 运行 clear ; LessLevel = 1 ; rand ( 'seed' , 1e9 ) ; exec ( 'PwpRandNegf.sce' ) ; 可得图片 2,反应“次最大”尺度上的基向量的情况。无单纯的直流基向量,所以TestDC = 125.14948,很大;TestHF = 980,即,等于随机实验次数,所以高频向量也总是成对的。 由于,必须覆盖相同的物理正频率带,所以, LessLevel =0 时的向量对,与 LessLevel =1 时的向量对,不可能有实质上不同的正频率带宽度,然而频率中心须错位。这种错位,改变了正、负频率中心的距离,提供了一种频率信息“分辨能力”。在 LessLevel =0 时,配对向量,可来自前面的尺度上的不同频率指标块。为此转换问题,居士杜撰“负频率幽灵”一词,供有兴趣者参考。 程序的Matlab版的处理,约更快1倍。 附程序: PwpRandNegf-2014-03-27.zip // PwpRandNegf.sce // for the concept: wavelet packet basis vector // test the random settings of wavelet packet vectors // and the ghost/compare of negative frequency of DFT basis // in order to run with fixed seed, use one of following lines: // clear; LessLevel=0; rand('seed',1e9); exec('PwpRandNegf.sce'); // clear; LessLevel=1; rand('seed',1e9); exec('PwpRandNegf.sce'); // in order to run with variable seed, use one of following lines: // clear; LessLevel=0; exec('PwpRandNegf.sce'); // clear; LessLevel=1; exec('PwpRandNegf.sce'); // note: TpwpSubs.bin, TpwpSubs_E01.bin, MatOrtWlts.bin are // in Scilab current directory // reference: PwpRandPsbm.sce, uploaded, 2014-03-19 // in Scilab-5.3.3,Baiyu Tang( tang.baiyu@gmail.com ) // last revised,2014-Mar xdel(winsid()); // kill all figures mode(0); ieee(1); // clear; // LessLevel=0; // rand('seed',1e9); // ---start timing date1=getdate(); date1=date1( ); disp( ); tic(); load('TpwpSubs.bin'); // load function subroutines load('TpwpSubs_E01.bin'); // extended set of subroutines for PreSet Basis load('MatOrtWlts.bin'); // load the filter cases TestDC=0; // DC vector error, all, total TestHF=0; // count high frequency vectors in pairs TestCount=zeros(98,10); // count matrix TestError=zeros(98,10); // error matrix // ---compute for ii=1:98; // filter case index. 98 filter cases for jj=1:10; // random test index. 10 tests per filter-case // ---random length and decomposition depth of test signal Wp.DecL=4+round(3*rand(1,1,'uniform'));// maximal level, 4,5,6 or 7 Wp.DatL=2^Wp.DecL; // data length, 16,32,64 or 128 Wp.DecL=Wp.DecL-LessLevel; // less-level decomposition CIndx0= *(Wp.DecL+1); // coefficient index, Last-Level // ---random settings Set0=rand(1,9,'normal')*1e6; Wp.RightShift=Set0(1); Wp.ExchangeR_D=Set0(2); Wp.FlipFirst=Set0(3); Wp.MatchFilter=Set0(4); Wp.LowT_zero=fix(Set0(5)); // integer Wp.HighT_shift=fix(Set0(6)); // integer Wp.FlipTime=Set0(7); Wp.PeriodFirst=Set0(8); Wp.AlterL4fSign=Set0(9); // ---get filters if Wp.ExchangeR_D0 then =WltFilters(ii); else =WltFilters(ii); end if length(hcoef(:))2 then if length(rhcoef(:))1 then hcoef=rhcoef; rhcoef= =TpwpAllGH(hcoef,rhcoef,Wp.DatL,Wp.DecL,... Wp.MatchFilter,Wp.PeriodFirst,Wp.LowT_zero,Wp.HighT_shift,Wp.FlipTime); if Wp.AlterL4fSign0 then // forced sign. usually not used hlen=max(round(length(hcoef)/2),round(length(rhcoef)/2))/2; if fix(hlen)==hlen then pgcoef=-pgcoef; // rpgcoef=-rpgcoef; end end =PsbMatrix(CIndx0,Wp.DecL,Wp.DatL,phcoef,pgcoef,Wp.RightShift); // ---match, compare x1=tM0(1,:)-1/sqrt(Wp.DatL); // DC error, realization and idea TestDC=TestDC+sqrt(mean(x1.*x1)); // DC RMSE accumulation TestCount(ii,jj)=Wp.DatL/2; // half the length of vectors and signals tM0f=zeros(Wp.DatL,Wp.DatL); for k1=1:Wp.DatL; x0=fft(tM0(k1,:)); // fast Fourier Transform, DFT x1=abs(x0); // magnitude spectrum tM0f(k1,:)=x1/sqrt(sum(x1.*x1)); // normalized with power end for k1=1:(Wp.DatL-1); // check the pairs of base vectors k12=0; // count vectors in one group for k2=(k1+1):Wp.DatL; x1=tM0f(k1,:)-tM0f(k2,:); er0=sqrt(mean(x1.*x1)); // magnitude RMSE if er00.001 then // equal if ii81 then // orthogonal cases x1=tM0(k1,:)-tM0(k2,:); er1=sqrt(sum(x1.*x1)); // vector error, l_2 norm if er11.4 then // confirm difference, two disp( ); error('Strange Vector Pair.'); end end if (k1==(Wp.DatL/2+1))|(k2==(Wp.DatL/2+1)) then TestHF=TestHF+1; // count, high frequency end k12=k12+1; TestCount(ii,jj)=TestCount(ii,jj)-1; // count, pairs TestError(ii,jj)=TestError(ii,jj)+er0; // RMSE accumulation,total end end if k121 then disp( ); error('The group has too many vectors for PwpRandNegf.sce .'); end end end end // ---display TestDC, TestHF, subplot(2,1,1); plot2d('nn',TestCount, rect= ); set(gca(),'tight_limits','on'); set(gca(),'box','on'); set(gca(),'grid', ); xlabel('Filters: sym1-sym35,coif1-coif5,dmey,db4-db42,18 biorthogonal cases'); ylabel('Length by 2 minus Magnitude-Match Count'); AuLabel1= ; xstring(1,-4+%eps,AuLabel1); Note1= ; if LessLevel0 then title('PwpRandNegf.sce: One Level Less than Maximal Decomposition'); xstring(1,2,Note1( )); else title('PwpRandNegf.sce: Tpwp Transform Trees Hold Negative Frequency of DFT ?'); xstring(1,1.5,Note1( )); end subplot(2,1,2); plot2d('nl', TestError+%eps, rect= ); set(gca(),'tight_limits','on'); set(gca(),'box','on'); set(gca(),'grid', ); xlabel('Filters: sym1-sym35,coif1-coif5,dmey,db4-db42,18 biorthogonal cases'); ylabel('Error of Magnitude of Matched Pairs'); xstring(1,2e-16,AuLabel1); if LessLevel0 then title('PwpRandNegf.sce: One Level Less than Maximal Decomposition'); xstring(1,1e-5,Note1( )); else title('PwpRandNegf.sce: Tpwp Transform Trees Hold Negative Frequency of DFT ?'); xstring(1,1e-5,Note1( )); end // ---timing Time_In_second=toc(), // --clear; LessLevel=0; rand('seed',1e9); exec('PwpRandNegf.sce'); // !Date and Time: 2014 3 25 8 41 23 ...... ! // TestDC = // 0.0000380 // TestHF = // 0. // Time_In_second = // 209.516 // --clear; LessLevel=1; rand('seed',1e9); exec('PwpRandNegf.sce'); // !Date and Time: 2014 3 25 8 46 55 ...... ! // TestDC = // 125.14948 // TestHF = // 980. // Time_In_second = // 194.25 // ***** The Version in Matlab ***** // clear; LessLevel=0; rng(1e9); PwpRandNegf; // Date and Time: 2014 3 25 8 57 ...... // TestDC = // 4.6382e-005 // TestHF = // 0 // Time_In_second = // 84.647 // clear; LessLevel=1; rng(1e9); PwpRandNegf; // Date and Time: 2014 3 25 8 59 ...... // TestDC = // 124.64 // TestHF = // 980 // Time_In_second = // 81.178 新浪赛特居士SciteJushi-2014-03-27。 图片 1。用小波包基向量从变换树上捕捉DFT中负频率的影子 图片 2。用同样的处理检验在次最大尺度上小波包基向量
对称性在自然界中的存在是一个普遍的现象。99%的现代动物是左右对称祖先的后代;连海葵这种非左右对称动物的后代,也存在对称性;对称性甚至在左右对称和非左右对称动物分化之前就已存在。在植物界,我们有多少次惊异于那些具有完美对称性蕨类、铁树的叶子和娇艳的花朵?生命里如果没有对称性会是什么样子呢?如果动物长三条腿,其古怪的形象会多么令人畏惧?如果人不是左右对称,只有一只眼睛、一只耳朵和半个脸世界就不再美好了。 人具有独一无二的对称美,所以人们又往往以是否符合对称性去审视大自然,并且创造了许许多多的具有对称性美的艺术品:服饰、雕塑和建筑物。 生命从最原始的单细胞动物向多细胞后生动物演化,最早拥有了以对称性为特征的复杂性。对称性对于人,不仅仅是外在的美,也是健康和生存的需要。如果只有一只眼睛,人的视野不仅变小、对与目标的距离判断不精确,而且对物体立体形状的认知会发生扭曲。如果一只耳朵失聪,对于声源的定位就会不准确:因为当人对声源定位时,大脑需要声音对于听者的方位仰角信息,也需要到达左右耳间的时间和强度差线索。对于野外生存的动物,失去声源定位的能力,意味着生命随时会受到威胁。另外,左右手脚需要默契的配合。对于花朵,如果花冠的发育失去对称性,雄蕊就会失去受粉能力,不能传种接代,物种将绝灭。 在科学研究中,对称性给科学家们提供了无限想象的空间,也是揭示新发现和否定错误观念的手段。生命科学家不止探讨认识生命活动的本质,而且也探讨存在于生命中的美、为什么这么美? 人大脑的两个半球,从它们的沟回和细胞排列层次看,非常相似,具有完美的对称性;这种对称性之于两手、两脚的对称性无异,似乎功能应是一样的。美国科学家斯佩里(Roger W. Sperry)从1960年代初开始,对癫间病人实施胼胝体切断手术,把大脑一分为二,发现它们能独立工作,功能并不一样。这一成果开创了心理学和脑功能定位研究的新纪元,他因此于1981年荣膺诺贝尔医学奖。随着PET和功能核磁共振技术的发展,人类对大脑功能的分化定位的认识有了长足的进步;从功能上看,左右大脑是完全不对称的。但是在低级中枢,间脑、脑干、小脑和脊髓,在功能和形态上都表现完美的对称性。 虽然对称性左右对称或圆形对称的起源至今仍是一个迷,一种合理的猜测是:对称性与重力是密不可分的,可能源于生命在重力场中的进化历程;而地球是一个相对规则的球体,重力场是均匀的。中圆柱形辐射对称的树枝可以抵抗重力,同时向空中发展接受阳光和用于光合作用的二氧化碳;四足动物的完美对称性可以使动物对抗重力,又善奔跑。 循着对称性的思路去探究不对称性的问题,我们可以找到许多非常有意义的生命科学课题。为什么雌果蝇能通过翅膀的摩擦产生声音吸引雄果蝇交配,而雄果蝇刚好在第二个触角有分化的听器官接受声刺激;反之,雌果蝇没有听器官,而雄果蝇不会发声音?再如,既然神经元的兴奋特性取决于突触后膜受体通道的特性和神经突触前膜所释放的递质特性,为什么在形态上,神经系统中兴奋性的突触是非对称的,而抑制性突触是对称性的?事实上,对称性也存在于分子结构上;有手性对称分子,旋转对称分子。按照这样的思路,或许有一天我们会从中得到启示改造蛋白质,进而设计、发明新的药物。 同样,循着对称性的思路,可以去探讨不对称性的艺术。毕加索也许是探讨不对称性中最幸运的艺术家。 科学,有时是运气,有灵感的闪现,有幸遇上中意的合作伙伴、得心应手的课题,撞上了那个发现的时机;有时是艺术,你在精雕细刻之中得到了应有的回报;有时是理性使然,你对于文献和自己已有的知识、技能有纯熟的驾驭;有时是枯燥乏味的重复,在重复中静静等待那激动一刻的到来。我们在科学生活中可以体念到大自然造化所赐予的、无所不在的对称美,为平常而有时枯燥的日常工作增添了无穷的乐趣! 延伸阅读: Finnerty JR, et al: Science. 2004 May 28; 304(5675):1335-7. Hileman LC,et al. Proc Natl Acad Sci U S A. 2003 Oct 28;100(22):12814-9 In praise of plants By Francis Hall Timber Press, 2002 原载于博客中国: http://www.blogchina.com/2004081640726.html
哥德巴赫猜想证明的新思维之一:《Pn 阶准素数模型》 1 .基本概念和定义 传统筛法中,将大于 1 的自然数分为素数和合数两类,在 上,设小于 x 平方根的素数有 n 个,它们从小到大依次是: P 1 、 P 2 P i P n ,那么,在 上,等于 m P i (i=1 、 2 、 3n ; m=2 、 3 、 4) 的整数都是合数,筛掉这些合数数 , 剩余的整数中,除了 1 之外的都是素数。 这种筛除方法仅仅因为 m 从 2 开始才 取 连续整数 , 就破坏了 P i 筛点的等间距属性,从而就破坏了筛除点和剩余点在数轴上分布的周期性,堵塞了根据筛点和剩余点周期性分布等特性,研究整数域属性的渠道。 若将上述 m 的取值从 0 开始取连续整数,定义整数轴上等于 m P i (i=1 、 2 、 3n ; m=0 、 1 、 2 、 3 、 4) 的整数为 P n 阶准 合数 ,而包括 1 在内的剩余整数为 P n 阶准素数 。我们就得到了一个在整个数轴上周期性、对称性分布的 P n 阶准素数模型 。 如此以来,每个 P i 的整倍数点(亦称为 P i 的筛点)都是从 0 起始的等间距分布点, n 个 P i 筛点的公共重叠筛点,就是 P n 阶准素数分布周期的周期端点。因此 P n 阶准素数的周期长度是: ( 1 ) 由于筛除前的整数点和 n 个 P i 筛点都是关于周期端点和中点对称分布的,所以筛除后剩余下来的 P n 阶准素数 点、 关于 周期端点、中点 也是 对称性分布的。 在整个数轴上, P n 阶准素数是一个其中既有素数、又有合数、又包含 1 的混合集合,但在有些区间段上, P n 阶准素数的属性却比较单纯:在 上的 P n 阶准素数,就只有整数 1 ;在( 1 , ) 内的 P n 阶准素数,全部是素数;在 上的 P n 阶准素数,既包含了其上的全部素数,又包含了其上的部分合数。 2. Pn 阶 准素数模型的数学意义 《 1 》在仅仅研究 P n 阶 准素数属性时,研究区间 之长度 x 与准素数阶次表征量 P n 是相互无关的两个独立自变量。可以任取 x 值和 P n 值, 研究任意区间上、任意阶次的准素数之有关问题。 由于同一阶准素数在数轴上的分布是周期性的,所以,由 P n 阶 准素数在其第一个周期上的分布规律,就可以推知它在整个数轴上的分布规律。 比如奇数序列,就是 P 1 阶准素数,由 1 和 3 相差 2 我们就知道任何大小的相邻两个奇数都是相差 2 的。 又比如 P 2 阶准素数,其周期长度为 6 ,第一个周期只有 1 和 5 这两个准素数,第二个周期只有 7 和 11 这两个准素数,由此可知,无论多大的 P 2 阶准素数,都是围绕其周期端点孪生的等等。 P 2 阶准素数也因此成为证明孪生素数无穷性的坚实基础。 再比如 P 3 阶准素数,其周期长度为 ,第一个周期的左端点是 0 点;右端点是 30 点;其上的筛网见(例图 1 ); P 3 阶准素数共有 8 个,它们是 1 、 7 、 11 、 13 、 17 、 19 、 23 、 29 ,它们相对于周期中点 15 点对称分布。根据筛网、准素数、准合数都是以 30 为周期而周期性分布,且是关于周期端点、中点对称性分布,则由 0-30 间的分布,可以推知 30-60 、 60-90 、 90-120 、 120-150 、 间的分布;由我们熟悉的 0 点右侧的 P 3 阶准素数,可以推知 30 、 60 、 90 、 120 、 150 、 点两侧的 P 3 阶准素数。即由 0 点右侧半周期的 P 3 阶准素数有 1 、 7 、 11 、 13 ,可推知 30 点左侧半周期一定有 29 、 23 、 19 、 17 ;可推知 30 点右侧半周期一定有 31 、 37 、 41 、 43 ;可推知 60 点左侧半周期一定有 59 、 53 、 49 、 47 ;可推知 60 点右侧半周期一定有 61 、 67 、 71 、 73 ; 等等。 由此可知,这时的 P n 阶准素数模型,就是我们由有限通向无穷的平直绿色通道。 例图 1 : P 3 阶第一个周期上的筛网和准素数分布图 (见 http://sea3000.net/fengjungang/2_23.php 图 ① ) 《 2 》在利用 P n 阶准素数属性研究有关素数的问题时,( a )将整数 1 暂且视同为素数;( b )将研究区间 之长度 x 限定在 之间即可。这是因为,对于筛选素数而言, P n+1 在数轴上的第一个非重复有效筛点是 点。在此点之前的 P n+1 筛点,除了 x= P n+1 点是无效筛点外,其余的都是 P n+1 与小于它的 P i 筛点相重叠的筛点、也是无效筛点。因此,在此点之前的 P n 阶准素数,除 1 之外,已全部是素数了,不需要再用 P n+1 筛除了。例如, x=7 7=49 点之前的 P 3 阶准素数,除 1 之外全部是素数。而 x=11 11 之前的 P 3 阶准素数除了 1 和 7 的少数个整倍数 7 7=49 、 7 11=77 、 7 13=91 、 7 17=119 以外,都是素数。所以,前面举例中列出的 P 3 阶准素数,除 1 和 49 外都是素数。 因此, 点之前的 P n 阶准素数,减 1 、再加上 P 1 、 P 2 P i P n 这 n 个素 数,就是该点之前的全部素数。若用 表示小于 x 的素数数目;用 表 示小于 x 的 P n 阶准素数数目,在满足 的前提下,则有: ( ) ( 2 ) 为了今后叙述方便,定义 P 1 、 P 2 P i P n 这 n 个素数,为 P n 阶准素数的 基素数 ,也称它们为满足 的 x 之 基素数。 由利用 P n 阶准素数研究素数时的附加条件 可知,这时, P n 与 x 不再是两个相互独立的变量,在 x 增大到每个素数平方的点上时, P n 就要增大一次、准素数的阶次就要向上提升一阶。所以, 对于素数研究而言, P n 阶准素数模型又变成一个由有限通向无穷,由低阶通向高阶的阶梯型绿色通道。