Breakdown of Lorentz Invariance: The Order of Quantum Gravity Phenomenology. Thought of the Day 132.0

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The purpose of quantum gravity phenomenology is to analyze the physical consequences arising from various models of quantum gravity. One hope for obtaining an experimental grasp on quantum gravity is the generic prediction arising in many (but not all) quantum gravity models that ultraviolet physics at or near the Planck scale, MPlanck = 1.2 × 1019 GeV/c2, (or in some models the string scale), typically induces violations of Lorentz invariance at lower scales. Interestingly most investigations, even if they arise from quite different fundamental physics, seem to converge on the prediction that the breakdown of Lorentz invariance can generically become manifest in the form of modified dispersion relations

ω2 = ω02 + (1 + η2) c2k2 + η4(ħ/MLorentz violation)2 + k4 + ….

where the coefficients ηn are dimensionless (and possibly dependent on the particle species under consideration). The particular inertial frame for these dispersion relations is generally specified to be the frame set by cosmological microwave background, and MLorentz violation is the scale of Lorentz symmetry breaking which furthermore is generally assumed to be of the order of MPlanck.

Although several alternative scenarios have been considered to justify the modified kinematics,the most commonly explored avenue is an effective field theory (EFT) approach. Here, the focus is explicitly on the class of non-renormalizable EFTs with Lorentz violations associated to dispersion relations. Even if this framework as a “test theory” is successful, it is interesting to note that there are still significant open issues concerning its theoretical foundations. Perhaps the most pressing one is the so called naturalness problem which can be expressed in the following way: The lowest-order correction, proportional to η2, is not explicitly Planck suppressed. This implies that such a term would always be dominant with respect to the higher-order ones and grossly incompatible with observations (given that we have very good constraints on the universality of the speed of light for different elementary particles). If one were to take cues from observational leads, it is assumed either that some symmetry (other than Lorentz invariance) enforces the η2 coefficients to be exactly zero, or that the presence of some other characteristic EFT mass scale μ ≪ MPlanck (e.g., some particle physics mass scale) associated with the Lorentz symmetry breaking might enter in the lowest order dimensionless coefficient η2, which will be then generically suppressed by appropriate ratios of this characteristic mass to the Planck mass: η2 ∝ (μ/MPlanck)σ where σ ≥ 1 is some positive power (often taken as one or two). If this is the case then one has two distinct regimes: For low momenta p/(MPlanckc) ≪ (μ/MPlanck)σ the lower-order (quadratic in the momentum) deviations will dominate over the higher-order ones, while at high energies p/(MPlanckc) ≫ (μ/MPlanck)σ the higher order terms will be dominant.

The naturalness problem arises because such a scenario is not well justified within an EFT framework; in other words there is no natural suppression of the low-order modifications. EFT cannot justify why only the dimensionless coefficients of the n ≤ 2 terms should be suppressed by powers of the small ratio μ/MPlanck. Even worse, renormalization group arguments seem to imply that a similar mass ratio, μ/MPlanck would implicitly be present also in all the dimensionless n > 2 coefficients, hence suppressing them even further, to the point of complete undetectability. Furthermore, without some protecting symmetry, it is generic that radiative corrections due to particle interactions in an EFT with only Lorentz violations of order n > 2 for the free particles, will generate n = 2 Lorentz violating terms in the dispersion relation, which will then be dominant. Naturalness in EFT would then imply that the higher order terms are at least as suppressed as this, and hence beyond observational reach.

A second issue is that of universality, which is not so much a problem, as an issue of debate as to the best strategy to adopt. In dealing with situations with multiple particles one has to choose between the case of universal (particle-independent) Lorentz violating coefficients ηn, or instead go for a more general ansatz and allow for particle-dependent coefficients; hence allowing different magnitudes of Lorentz symmetry violation for different particles even when considering the same order terms (same n) in regards to momentum. Any violation of Lorentz invariance should be due to the microscopic structure of the effective space-time. This implies that one has to tune the system in order to cancel exactly all those violations of Lorentz invariance which are solely due to mode-mixing interactions in the hydrodynamic limit.

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Weakness of Gravity and Transverse Spreading of Gravitational Flux. Drunken Risibility.

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Dirichlet branes, or their dual heterotic fivebranes and Horava-Witten walls – can trap non-abelian gauge interactions in their worldvolumes. This has placed on a firmer basis an old idea, according to which we might be living on a brane embedded in a higher-dimensional world. The idea arises naturally in compactifications of type I theory, which typically involve collections of orientifold planes and D-branes. The ‘brane-world’ scenario admits a fully perturbative string description.

In type I string theory the graviton (a closed-string state) lives in the ten-dimensional bulk, while open-string vector bosons are in general localized on lower-dimensional D-branes. Furthermore while closed strings interact to leading order via the sphere diagram, open strings interact via the disk diagram which is of higher order in the genus expansion. The four-dimensional Planck mass and Yang-Mills couplings therefore take the form

αU ∼ gI/(r˜MI)6-n

M2Planck ∼ rn6-nM8I/g2

where r is the typical radius of the n compact dimensions transverse to the brane, f the typical radius of the remaining (6-n) compact longitudinal dimensions, MI the type-I string scale and gI the string coupling constant. By appropriate T-dualities we can again ensure that both r and r˜ are greater than or equal to the fundamental string scale. T- dualities change n and may take us either to Ia or to Ib theory (also called I or I’, respectively).

It follows from these formulae that (a) there is no universal relation between MPlanck, αand MI anymore, and (b) tree-level gauge couplings corresponding to different sets of D-branes have radius-dependent ratios and need not unify at all. Thus type-I string theory is much more flexible (and less predictive) than its heterotic counterpart. The fundamental string scale, MI, in particular is a free parameter, even if one insists that αU be kept fixed and of order one, and that the string theory be weakly coupled. This added flexibility can be used to ‘remove’ the order-of magnitude discrepancy between the apparent unification and string scales of the heterotic theory, to lower MI to an intemediate scale or even all the way down to its experimentally-allowed limit of order the TeV. Keeping for instance gI, α and r˜MI fixed and of order one, leads to the condition

rn ∼ M2Planck/M2+nI

A TeV string scale would then require from n = 2 millimetric to n = 6 fermi-size dimensions transverse to our brane world. The relative weakness of gravity is in this picture attributed to the large transverse spreading of the gravitational flux.

Superstrings as Grand Unifier. Thought of the Day 86.0

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The first step of deriving General Relativity and particle physics from a common fundamental source may lie within the quantization of the classical string action. At a given momentum, quantized strings exist only at discrete energy levels, each level containing a finite number of string states, or particle types. There are huge energy gaps between each level, which means that the directly observable particles belong to a small subset of string vibrations. In principle, a string has harmonic frequency modes ad infinitum. However, the masses of the corresponding particles get larger, and decay to lighter particles all the quicker.

Most importantly, the ground energy state of the string contains a massless, spin-two particle. There are no higher spin particles, which is fortunate since their presence would ruin the consistency of the theory. The presence of a massless spin-two particle is undesirable if string theory has the limited goal of explaining hadronic interactions. This had been the initial intention. However, attempts at a quantum field theoretic description of gravity had shown that the force-carrier of gravity, known as the graviton, had to be a massless spin-two particle. Thus, in string theory’s comeback as a potential “theory of everything,” a curse turns into a blessing.

Once again, as with the case of supersymmetry and supergravity, we have the astonishing result that quantum considerations require the existence of gravity! From this vantage point, right from the start the quantum divergences of gravity are swept away by the extended string. Rather than being mutually exclusive, as it seems at first sight, quantum physics and gravitation have a symbiotic relationship. This reinforces the idea that quantum gravity may be a mandatory step towards the unification of all forces.

Unfortunately, the ground state energy level also includes negative-mass particles, known as tachyons. Such particles have light speed as their limiting minimum speed, thus violating causality. Tachyonic particles generally suggest an instability, or possibly even an inconsistency, in a theory. Since tachyons have negative mass, an interaction involving finite input energy could result in particles of arbitrarily high energies together with arbitrarily many tachyons. There is no limit to the number of such processes, thus preventing a perturbative understanding of the theory.

An additional problem is that the string states only include bosonic particles. However, it is known that nature certainly contains fermions, such as electrons and quarks. Since supersymmetry is the invariance of a theory under the interchange of bosons and fermions, it may come as no surprise, post priori, that this is the key to resolving the second issue. As it turns out, the bosonic sector of the theory corresponds to the spacetime coordinates of a string, from the point of view of the conformal field theory living on the string worldvolume. This means that the additional fields are fermionic, so that the particle spectrum can potentially include all observable particles. In addition, the lowest energy level of a supersymmetric string is naturally massless, which eliminates the unwanted tachyons from the theory.

The inclusion of supersymmetry has some additional bonuses. Firstly, supersymmetry enforces the cancellation of zero-point energies between the bosonic and fermionic sectors. Since gravity couples to all energy, if these zero-point energies were not canceled, as in the case of non-supersymmetric particle physics, then they would have an enormous contribution to the cosmological constant. This would disagree with the observed cosmological constant being very close to zero, on the positive side, relative to the energy scales of particle physics.

Also, the weak, strong and electromagnetic couplings of the Standard Model differ by several orders of magnitude at low energies. However, at high energies, the couplings take on almost the same value, almost but not quite. It turns out that a supersymmetric extension of the Standard Model appears to render the values of the couplings identical at approximately 1016 GeV. This may be the manifestation of the fundamental unity of forces. It would appear that the “bottom-up” approach to unification is winning. That is, gravitation arises from the quantization of strings. To put it another way, supergravity is the low-energy limit of string theory, and has General Relativity as its own low-energy limit.

Universal Turing Machine: Algorithmic Halting

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A natural number x will be identified with the x’th binary string in lexicographic order (Λ,0,1,00,01,10,11,000…), and a set X of natural numbers will be identified with its characteristic sequence, and with the real number between 0 and 1 having that sequence as its dyadic expansion. The length of a string x will be denoted |x|, the n’th bit of an infinite sequence X will be noted X(n), and the initial n bits of X will be denoted Xn. Concatenation of strings p and q will be denoted pq.

We now define the information content (and later the depth) of finite strings using a universal Turing machine U. A universal Turing machine may be viewed as a partial recursive function of two arguments. It is universal in the sense that by varying one argument (“program”) any partial recursive function of the other argument (“data”) can be obtained. In the usual machine formats, program, data and output are all finite strings, or, equivalently, natural numbers. However, it is not possible to take a uniformly weighted average over a countably infinite set. Chaitin’s universal machine has two tapes: a read-only one-way tape containing the infinite program; and an ordinary two-way read/write tape, which is used for data input, intermediate work, and output, all of which are finite strings. Our machine differs from Chaitin’s in having some additional auxiliary storage (e.g. another read/write tape) which is needed only to improve the time efficiency of simulations.

We consider only terminating computations, during which, of course, only a finite portion of the program tape can be read. Therefore, the machine’s behavior can still be described by a partial recursive function of two string arguments U(p, w), if we use the first argument to represent that portion of the program that is actually read in the course of a particular computation. The expression U (p, w) = x will be used to indicate that the U machine, started with any infinite sequence beginning with p on its program tape and the finite string w on its data tape, performs a halting computation which reads exactly the initial portion p of the program, and leaves output data x on the data tape at the end of the computation. In all other cases (reading less than p, more than p, or failing to halt), the function U(p, w) is undefined. Wherever U(p, w) is defined, we say that p is a self-delimiting program to compute x from w, and we use T(p, w) to represent the time (machine cycles) of the computation. Often we will consider computations without input data; in that case we abbreviate U(p, Λ) and T(p, Λ) as U(p) and T(p) respectively.

The self-delimiting convention for the program tape forces the domain of U and T, for each data input w, to be a prefix set, that is, a set of strings no member of which is the extension of any other member. Any prefix set S obeys the Kraft inequality

p∈S 2−|p| ≤ 1

Besides being self-delimiting with regard to its program tape, the U machine must be efficiently universal in the sense of being able to simulate any other machine of its kind (Turing machines with self-delimiting program tape) with at most an additive constant constant increase in program size and a linear increase in execution time.

Without loss of generality we assume that there exists for the U machine a constant prefix r which has the effect of stacking an instruction to restart the computation when it would otherwise end. This gives the machine the ability to concatenate programs to run consecutively: if U(p, w) = x and U(q, x) = y, then U(rpq, w) = y. Moreover, this concatenation should be efficient in the sense that T (rpq, w) should exceed T (p, w) + T (q, x) by at most O(1). This efficiency of running concatenated programs can be realized with the help of the auxiliary storage to stack the restart instructions.

Sometimes we will generalize U to have access to an “oracle” A, i.e. an infinite look-up table which the machine can consult in the course of its computation. The oracle may be thought of as an arbitrary 0/1-valued function A(x) which the machine can cause to be evaluated by writing the argument x on a special tape and entering a special state of the finite control unit. In the next machine cycle the oracle responds by sending back the value A(x). The time required to evaluate the function is thus linear in the length of its argument. In particular we consider the case in which the information in the oracle is random, each location of the look-up table having been filled by an independent coin toss. Such a random oracle is a function whose values are reproducible, but otherwise unpredictable and uncorrelated.

Let {φAi (p, w): i = 0,1,2…} be an acceptable Gödel numbering of A-partial recursive functions of two arguments and {φAi (p, w)} an associated Blum complexity measure, henceforth referred to as time. An index j is called self-delimiting iff, for all oracles A and all values w of the second argument, the set { x : φAj (x, w) is defined} is a prefix set. A self-delimiting index has efficient concatenation if there exists a string r such that for all oracles A and all strings w, x, y, p, and q,if φAj (p, w) = x and φAj (q, x) = y, then φAj(rpq, w) = y and φAj (rpq, w) = φAj (p, w) + φAj (q, x) + O(1). A self-delimiting index u with efficient concatenation is called efficiently universal iff, for every self-delimiting index j with efficient concatenation, there exists a simulation program s and a linear polynomial L such that for all oracles A and all strings p and w, and

φAu(sp, w) = φAj (p, w)

and

ΦAu(sp, w) ≤ L(ΦAj (p, w))

The functions UA(p,w) and TA(p,w) are defined respectively as φAu(p, w) and ΦAu(p, w), where u is an efficiently universal index.

For any string x, the minimal program, denoted x∗, is min{p : U(p) = x}, the least self-delimiting program to compute x. For any two strings x and w, the minimal program of x relative to w, denoted (x/w)∗, is defined similarly as min{p : U(p,w) = x}.

By contrast to its minimal program, any string x also has a print program, of length |x| + O(log|x|), which simply transcribes the string x from a verbatim description of x contained within the program. The print program is logarithmically longer than x because, being self-delimiting, it must indicate the length as well as the contents of x. Because it makes no effort to exploit redundancies to achieve efficient coding, the print program can be made to run quickly (e.g. linear time in |x|, in the present formalism). Extra information w may help, but cannot significantly hinder, the computation of x, since a finite subprogram would suffice to tell U to simply erase w before proceeding. Therefore, a relative minimal program (x/w)∗ may be much shorter than the corresponding absolute minimal program x∗, but can only be longer by O(1), independent of x and w.

A string is compressible by s bits if its minimal program is shorter by at least s bits than the string itself, i.e. if |x∗| ≤ |x| − s. Similarly, a string x is said to be compressible by s bits relative to a string w if |(x/w)∗| ≤ |x| − s. Regardless of how compressible a string x may be, its minimal program x∗ is compressible by at most an additive constant depending on the universal computer but independent of x. [If (x∗)∗ were much smaller than x∗, then the role of x∗ as minimal program for x would be undercut by a program of the form “execute the result of executing (x∗)∗.”] Similarly, a relative minimal program (x/w)∗ is compressible relative to w by at most a constant number of bits independent of x or w.

The algorithmic probability of a string x, denoted P(x), is defined as {∑2−|p| : U(p) = x}. This is the probability that the U machine, with a random program chosen by coin tossing and an initially blank data tape, will halt with output x. The time-bounded algorithmic probability, Pt(x), is defined similarly, except that the sum is taken only over programs which halt within time t. We use P(x/w) and Pt(x/w) to denote the analogous algorithmic probabilities of one string x relative to another w, i.e. for computations that begin with w on the data tape and halt with x on the data tape.

The algorithmic entropy H(x) is defined as the least integer greater than −log2P(x), and the conditional entropy H(x/w) is defined similarly as the least integer greater than − log2P(x/w). Among the most important properties of the algorithmic entropy is its equality, to within O(1), with the size of the minimal program:

∃c∀x∀wH(x/w) ≤ |(x/w)∗| ≤ H(x/w) + c

The first part of the relation, viz. that algorithmic entropy should be no greater than minimal program size, is obvious, because of the minimal program’s own contribution to the algorithmic probability. The second half of the relation is less obvious. The approximate equality of algorithmic entropy and minimal program size means that there are few near-minimal programs for any given input/output pair (x/w), and that every string gets an O(1) fraction of its algorithmic probability from its minimal program.

Finite strings, such as minimal programs, which are incompressible or nearly so are called algorithmically random. The definition of randomness for finite strings is necessarily a little vague because of the ±O(1) machine-dependence of H(x) and, in the case of strings other than self-delimiting programs, because of the question of how to count the information encoded in the string’s length, as opposed to its bit sequence. Roughly speaking, an n-bit self-delimiting program is considered random (and therefore not ad-hoc as a hypothesis) iff its information content is about n bits, i.e. iff it is incompressible; while an externally delimited n-bit string is considered random iff its information content is about n + H(n) bits, enough to specify both its length and its contents.

For infinite binary sequences (which may be viewed also as real numbers in the unit interval, or as characteristic sequences of sets of natural numbers) randomness can be defined sharply: a sequence X is incompressible, or algorithmically random, if there is an O(1) bound to the compressibility of its initial segments Xn. Intuitively, an infinite sequence is random if it is typical in every way of sequences that might be produced by tossing a fair coin; in other words, if it belongs to no informally definable set of measure zero. Algorithmically random sequences constitute a larger class, including sequences such as Ω which can be specified by ineffective definitions.

The busy beaver function B(n) is the greatest number computable by a self-delimiting program of n bits or fewer. The halting set K is {x : φx(x) converges}. This is the standard representation of the halting problem.

The self-delimiting halting set K0 is the (prefix) set of all self-delimiting programs for the U machine that halt: {p : U(p) converges}.

K and K0 are readily computed from one another (e.g. by regarding the self-delimiting programs as a subset of ordinary programs, the first 2n bits of K0 can be recovered from the first 2n+O(1) bits of K; by encoding each n-bit ordinary program as a self-delimiting program of length n + O(log n), the first 2n bits of K can be recovered from the first 2n+O(log n) bits of K0.)

The halting probability Ω is defined as {2−|p| : U(p) converges}, the probability that the U machine would halt on an infinite input supplied by coin tossing. Ω is thus a real number between 0 and 1.

The first 2n bits of K0 can be computed from the first n bits of Ω, by enumerating halting programs until enough have halted to account for all but 2−n of the total halting probability. The time required for this decoding (between B(n − O(1)) and B(n + H(n) + O(1)) grows faster than any computable function of n. Although K0 is only slowly computable from Ω, the first n bits of Ω can be rapidly computed from the first 2n+H(n)+O(1) bits of K0, by asking about the halting of programs of the form “enumerate halting programs until (if ever) their cumulative weight exceeds q, then halt”, where q is an n-bit rational number…

von Neumann & Dis/belief in Hilbert Spaces

I would like to make a confession which may seem immoral: I do not believe absolutely in Hilbert space any more.

— John von Neumann, letter to Garrett Birkhoff, 1935.

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The mathematics: Let us consider the raison d’ˆetre for the Hilbert space formalism. So why would one need all this ‘Hilbert space stuff, i.e. the continuum structure, the field structure of complex numbers, a vector space over it, inner-product structure, etc. Why? According to von Neumann, he simply used it because it happened to be ‘available’. The use of linear algebra and complex numbers in so many different scientific areas, as well as results in model theory, clearly show that quite a bit of modeling can be done using Hilbert spaces. On the other hand, we can also model any movie by means of the data stream that runs through your cables when watching it. But does this mean that these data streams make up the stuff that makes a movie? Clearly not, we should rather turn our attention to the stuff that is being taught at drama schools and directing schools. Similarly, von Neumann turned his attention to the actual physical concepts behind quantum theory, more specifically, the notion of a physical property and the structure imposed on these by the peculiar nature of quantum observation. His quantum logic gave the resulting ‘algebra of physical properties’ a privileged role. All of this leads us to … the physics of it. Birkhoff and von Neumann crafted quantum logic in order to emphasize the notion of quantum superposition. In terms of states of a physical system and properties of that system, superposition means that the strongest property which is true for two distinct states is also true for states other than the two given ones. In order-theoretic terms this means, representing states by the atoms of a lattice of properties, that the join p ∨ q of two atoms p and q is also above other atoms. From this it easily follows that the distributive law breaks down: given atom r ≠ p, q with r < p ∨ q we have r ∧ (p ∨ q) = r while (r ∧ p) ∨ (r ∧ q) = 0 ∨ 0 = 0. Birkhoff and von Neumann as well as many others believed that understanding the deep structure of superposition is the key to obtaining a better understanding of quantum theory as a whole.

For Schrödinger, this is the behavior of compound quantum systems, described by the tensor product. While the quantum information endeavor is to a great extend the result of exploiting this important insight, the language of the field is still very much that of strings of complex numbers, which is akin to the strings of 0’s and 1’s in the early days of computer programming. If the manner in which we describe compound quantum systems captures so much of the essence of quantum theory, then it should be at the forefront of the presentation of the theory, and not preceded by continuum structure, field of complex numbers, vector space over the latter, etc, to only then pop up as some secondary construct. How much quantum phenomena can be derived from ‘compoundness + epsilon’. It turned out that epsilon can be taken to be ‘very little’, surely not involving anything like continuum, fields, vector spaces, but merely a ‘2D space’ of temporal composition and compoundness, together with some very natural purely operational assertion, including one which in a constructive manner asserts entanglement; among many other things, trace structure then follows.