Taking into account the coupling of these two antagonistic processes by the FDT, an equilibrium between entropy flows from microscopic to macroscopic scales and vice versa will eventually arise. It prevents distributions from approaching sharp points delta functions or steps Theta functions that amount to an infinite information content.
The Axiom of Determinancy Forcing Axioms and its Nonstationary Ideal
Diffusion, a paradigm for irreversibility, blurs and eventually erases distinct patterns in a distribution, replacing the initial information gradually by random noise. It occurs in thermodynamics as well as in technical processes like repeated copying or communication via noisy channels. Combining all these considerations around information exchange between different scales, a pattern emerges that resembles convection cells and subduction zones above a hot surface figure 17 : while as dominating tendency, macroscopic information is absorbed by microscopic freedoms and turned into heat, isolated chaotic processes lift information from small to large dimensions where they become visible and are perceived as unpredictable events.
Combining the information flows top-down, macro—micro, in dissipation, and bottom-up, from small to large scales in deterministic chaos, a pattern of counter directed 'vertical' currents emerge which resemble convection cells in hydrodynamics. The preferred time arrow we observe thus appears to be rooted in the combination of two crucial effects: the existence of information flows both from large to small and from small to large scales, and the fact that the universe has been born in a state of imbalance where structures on the largest scales prevailed [ 4 , 33 ].
The preceding discussion leaves a crucial question open: how is information processed on the smallest scales, on the bottom level of natural computation where the laws of quantum mechanics supersede classical physics? To fill this gap, a section on the specific way quantum systems process information is indispensable. The question cannot be answered by merely extrapolating classical mechanics to atomic and molecular dimensions.
Scale matters in information dynamics, as the considerations concerning Gibbs' paradox have shown. Entropy diverges if an unlimited information density is assumed. A drastic modification of classical mechanics was required to fix this problem and related anomalies which by the end of the 19th century led to a profound crisis of classical physics.
The way out of the impasse followed closely Thomas Kuhn's scheme of scientific revolution [ 2 ]: quantum mechanics, the new paradigm, provides a radical answer, lifting physics to a new level of self-consistency. Imposing a fundamental bound to an information-related quantity, it is closely related to special relativity: the vacuum speed of light forms an absolute limit only if understood as an upper bound for the group velocity of waves, or more generally, the propagation of information.
Quantum mechanics reformulates the fundamental laws of physics under the strict verdict that the density of information is finite. It is close in spirit to signal-processing theories based on finite available data sets and coincides with many of their consequences. This theorem becomes a law of physics once, e. The uncertainty relations impose an objective limit for the information content of a system and are not a mere subjective restriction owing to imperfections, however insurmountable, of the measuring equipment.
Quantum mechanics is frequently reduced to quantization, often understood as discretization or pixelization, and the contrast quantum versus classical is simplified to discrete versus continuous. This is inappropriate and misleading. Quantum mechanics does not imply the discreteness of any specific quantity. Depending on the system at hand, they can be rectangular potential box , elliptic harmonic oscillator , or take any other, even arbitrarily irregular, shape.
As a consequence, only in particular cases does the compartmentalization of phase space result in the discretization of an observable quantity. While in this respect, quantum theory revolutionized classical physics, it agrees perfectly with Hamiltonian mechanics in another important aspect: the time evolution of closed systems, the way they process information, is invariant under time reversal and preserves the total entropy content. Following John von Neumann, a pioneer who anticipated an information-based approach to quantum theory, entropy can be defined in quantum mechanics in a way closely analogous to Shannon's definition [ 43 ].
Quantum mechanics replaces canonical transformations, which generate the time evolution of classical systems in phase space, by unitary transformations of Hilbert space, the state space in quantum physics. Von Neumann's entropy is invariant under the action of unitary transformations, just as Hamiltonian mechanics conserves classical entropy. This implies in particular that the apparent incompatibility of the second law with the fundamental microscopic physics is by no means restricted to classical mechanics.
Worse even, the possibility offered by quantum mechanics to quantify the information content of every state renders the contradiction even more inescapable. Both features taken together, finite information density and conservation of entropy, however, also indicate how to remove the classical inconsistencies. The picture developed above of counter-directed information flows—dissipation as sink, chaos as source of entropy—suggests there should be a ground level where the paternoster lift turns around.
Where classical physics appears fathomless, quantum mechanics inserts the missing bottom. In the case of chaotic dynamics, consequences are particularly drastic: if information is permanently conveyed up from a limited source, the supply will eventually run out. That is exactly what happens: after a finite time, closed quantum systems cease to be chaotic. They become periodic—no more surprise, no further entropy is produced. The time for this breakdown to occur depends on the output rate the Lyapunov exponent and the supply system size.
In this rigorous sense, chaos in quantum mechanics cannot exist. So far about bottom-up information currents. This is true, however, only for strictly closed systems. It is a commonplace, though, that closed systems are an idealization and practically do not exist. Even a minimum interaction suffices to enable an exchange of information between systems, however slow. For this reason, dissipation is so ubiquitous: there is always a loophole for entropy to escape—and to enter where it is in short supply. Chaos combined with dissipation exemplifies the interplay of these two processes, seen from a quantum viewpoint.
On the one hand, uncertainty destroys the hallmark of dissipative chaos, strange attractors with a self-similar fractal geometry figure Viewed from sufficiently close, approaching the scale of Planck's constant, the infinitely fine structure disappears and gives way to smooth distributions [ 44 , 45 ]. However, this does not occur on a fixed raster, as if rendering the attractor on a computer screen with low resolution. Rather, the coarsening adapts to the shape of the attractor at hand. At the same time, including dissipation restores chaotic structures in the time evolution, injecting the missing information whose scarcity dries out chaos in closed quantum systems.
On a timescale independent of the breakdown discussed above, dissipative quantum chaos restores irregular, aperiodic motion [ 44 , 45 ]. The Zaslavsky map is a standard model for dissipative chaos, exhibiting a strange self-similar attractor a. Treating the same model as a quantum system, the strange attractor loses its self-similarity. The infinitely fine classical details are replaced by a structure that is smooth on the scale of Planck's constant b. After [ 44 ]. Reprinted from [ 44 ], figure 11, Copyright , with permission from Elsevier.
Whence the information that revives chaotic irregularity? Microscopic models of quantum dissipation coincide in their basic setup: the system of interest, for example a chaotic model with a few dimensions, is coupled to an environment comprising an infinite number of degrees of freedom, often modelled following specific prototypes, for example the modes of the quantized electromagnetic field or quantum vacuum for short. In this system, permeating virtually the entire universe, quantum uncertainty is manifest in a zero-point energy of its normal modes.
The finite energy contained even in their ground states, in turn, is observable as vacuum fluctuations, a remainder of thermal fluctuations which persists down to zero absolute temperature. In this way, the image of rising and descending information currents is complemented by a picture of what is going on at the bottom where these flows connect: the quantum vacuum acts as a huge universal garbage dump where all lost information finally ends, the bits of an archive deleted on some computer as much as the emphatic words of Julius Caesar, the echo of a supernova somewhere in the Universe just as the roar of Triassic monsters, and is recycled to surface eventually as fresh quantum randomness.
Quantum mechanics not only resolves information-related inconsistencies of classical physics, it also implies unexpected consequences not related to the failures of its precursor. Akin to the twin paradox of special relativity, emblematic quantum features such as entanglement, nonlocality, and action at a distance, combined in the Einstein—Podolsky—Rosen EPR paradox figure 19 , have sparked decades of debate among physicists and philosophers. However, interpreting quantum mechanics as a theory of finite information, they appear as natural, inevitable results.
An account of quantum physics along these lines, complementing Bohr's Copenhagen interpretation by a contemporary approach, has been proposed by Anton Zeilinger [ 46 ], the Austrian pioneer in experimental evidence of entanglement. The two spins are undetermined till they are measured and take specific directions. The individual results for each spin are a typical quantum random process, both orientations are equally probable and cannot be predicted. The sum rule, however, requires invariably that the two spins take opposite signs.
This anticorrelation occurs instantaneously between the two measurements. It does not violate causality, though: no information is transmitted. Rather, the two particles, despite their growing spatial separation, form a single indivisible qubit that is set with the measurement. While largely analogous to classical information according to Boltzmann or Shannon, von Neumann's entropy is different in a decisive point: there is an absolute zero for quantum entropy, a lower bound that is missing in the classical case.
No more can be known, no less can remain open about a system than if it is in a pure state. This amounts to zero entropy; it takes positive values if the system is not in a pure state. Quantum mechanics not only limits the maximum information content of a closed system, it also implies a lower bound. The minimum is a single bit, a system that can take only one of two possible states. Quantum systems as small as that, such as spins, are often called 'qubits'. The crucial point is that an isolated two-state system cannot carry more information, either.
It is tempting to imagine this elementary quantum of information to be also associated to a single indivisible point-like particle, e. In fact, this expectation is unfounded. The fundamental property, an information content of 1 bit, can well refer to a system that consists of two or more spatially distributed parts: the subsystems become entangled. The prototypical case are EPR pairs, for example an electron and a positron generated simultaneously in a decay process.
Their total internal angular momentum is zero, so that their spins must take opposite orientations. Together they form a single qubit, shared by two particles that move arbitrarily far apart in space. It can be manipulated, in particular oriented in a specific direction, operating on only one of the two particles. Once fixed, the spin orientation involves both particles simultaneously, it occurs nonlocally. This process does not contradict causality, there is no 'spooky action at a distance', as Einstein put it: no information is transmitted from one system to another; a single qubit just takes a definite value that can be observed at different places.
This situation sheds light, too, on quantum-mechanical measurement and the fundamental randomness ascribed to it, a matter of fierce debate since the advent of quantum mechanics. As long as the two particles remain isolated as a pair, the sign of their common spin does not take any definite value. Performing a measurement on the system forces the spin to assume a specific direction. This creates 1 bit of information that did not exist before; the conservation of entropy in closed systems requires that it cannot come from the EPR pair itself.
As in the case of quantum chaos with dissipation, the only possible source is the environment the pair couples to when it interacts with the measurement apparatus.
This indicates that in the random outcome of the measurement, information is not created from nothing, either. It merely amplifies a fluctuation of the quantum vacuum or the degrees of freedom of the apparatus to macroscopic visibility. Robert Laughlin, in his monograph 'A different universe. Reinventing physics from the bottom down' [ 50 ], compares this situation with a radio station where in the dead season, in lack of true news, editors start interviewing each other. The common feature that renders these quantum paradoxes comprehensible is the fact that a limited amount of information, a single bit in the extreme, is shared by parts of a system that are distributed in space.
It is the paucity, not abundance, of this resource that leads to entanglement and to counterintuitive effects. Analogies are symmetric relations [ 8 ]. The metaphor underlying this essay, comparing natural systems to computers, actually has two sides: while the preceding sections elucidate computation-like features in nature, the remaining part highlights the natural conditions dominating computers. After all, entropy is a physical quantity, its storage and transport in computers underlies the same fundamental constraints, such as energy conservation, as in 'natural' systems.
In the words of Rolf Landauer [ 51 ]: information is physical. As an initial insight, the distinction between computers on the one hand and natural systems on the other is no more than a convention. In particular, where computation means simulation, these roles become interchangeable: water waves serve to simulate light, but light waves can also be used to simulate wavelets on a water surface.
Electrons in a metal resemble cold atoms in optical lattices.
Inversely, they allow to anticipate the behaviour of particles in standing laser fields. Microwaves in superconducting cavities are analogous to wave functions in quantum billiards. Measuring their eigenmodes and their frequencies can outperform double-accuracy numerical calculations, adding a third tier of simulation. If indeed this distinction is pointless, what in fact are the criteria that qualify a technical system to be called a computer in the more limited colloquial meaning?
The following general conditions are expected to apply:. More restrictive criteria, like a binary code or a hardware built from silicon-based electronic circuits, are not necessary; a mechanical calculator and even an abacus are acceptable as computers. These last two examples show that the notion of a nominal state space is decisive. Abaci and mechanical calculators are evidently macroscopic physical systems where all relevant variables are continuous, not discrete.
Time advances continuously, anyway. As man-made objects, computers are natural systems embedded in human culture.
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Their states, besides comprising physical variables, bear symbolic meanings, subject in turn to norms and conventions. An elementary example is a two-state, on—off switch figure 20 : taken as a mechanical system, it can assume a continuum of states associated to the spatial position of the switch. It is constructed, though, such that its mechanical potential is bistable.
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The switch will fall into one of its two minima, corresponding to the nominal states 'off' versus 'on', and, sufficiently strong friction provided, stay there. The barrier separating them must be sufficiently high to prevent switching by thermal fluctuations but low enough to be surmounted by a fingertip. An ordinary switch exemplifies a basic principle of digital computing: the two states of the device, e. This construction already represents basic physical traits of a computer.
Within a continuous state space, the nominal states are marked by steep potential minima, separated by barriers chosen such that with high probability, a control impulse, but no thermal fluctuation, will trigger a transition. Evidently, such losses occur as soon as stored information is deleted. The erasure of one bit generates at least k B ln 2 of entropy, converting an energy k B T ln 2 into heat [ 51 ].
In fact, most logical operations have the same consequence. They constitute irreversible processes, hence generate as much entropy and heat as a mere deletion. A computer in the colloquial sense therefore inevitably represents a dissipative system, not only for possible friction between its parts. Classifying its asymptotic states in the terminology of dynamical systems theory [ 52 ], it can only comprise point attractors single states eventually reached by the system or limit cycles a periodic sequence of states the system terminates in, figure By contrast, strange attractors with fractal geometry are not compatible with a finite discrete state space.
Digital computers thus provide qualitative classical models for the quantum suppression of chaos, except for the fact that their state space forms a rigid raster while quantum distributions in phase space can take any shape. Digital computers have a discrete state space comprising only a finite number of distinct states. This requires their dynamics to start repeating itself after a finite number of steps in the absence of external input from keyboards etc.
In the case of dissipative computing, final states can be point attractors a or limit cycles b. In reversible computing c and d , the state space initially occupied cannot contract, a limit cycle comprises as many states as led into it. In both cases, chaotic behaviour is excluded. However, the standard modus operandi of a digital computer, as outlined here, is not the only possibility.
The idea of reversible, frictionless computation enjoyed considerable attention at the time when the basic design of quantum computers emerged [ 53 ]. In quantum computation see the subsequent section 3. The loss of information in binary logical operations can in fact be avoided by saving one of the input bits which, combined with the output, allows to restore the other input. Quite some creativity has been devoted, at the same time, to conceiving ballistic mechanical computers that operate with only negligible friction between their moving parts [ 53 ], the only purpose of such fictitious devices being to demonstrate the feasibility of computation without generating entropy.
Having a finite discrete state space in common with conventional dissipative computers, they cannot simulate chaotic dynamics. Classical reversible computers share a fundamental problem with their quantum counterparts: due to the verdict not to contract different inputs to a single output, they cannot exploit redundancy as a strategy to prevent and correct errors. Therefore, the error frequency increases linearly with the computation time or the number of operations realized. It can be reduced by slowing down the processing speed, resulting in a trade-off with performance.
Likewise, replication and transcription constitute copying operations, as a rudimentary instance of computation. They even work with astonishing accuracy, given that they go on in molecular systems exposed to thermal noise at physiological temperature. Inspired by such natural systems, the idea of Brownian computers emerged, where thermal fluctuations drive a system through a sequence of logical-like operations.
In order to achieve a well-defined direction of the process, a finite gradient has to be imposed. To avoid a concomitant energy loss, this gradient can be made arbitrarily small, again on the expense of computational speed. Inherent thermodynamic limitations are by no means the only aspects where physics constrains digital computing. Also quantum mechanics and special relativity have tangible effects. Their general discussion, linking computer science back to physics, has been pioneered by Landauer [ 51 ].
Summarizing these issues, the following problems remain largely open:. After visionary initial steps by theoreticians like Richard Feynman in the early s [ 54 ], quantum computation enjoyed a hype in the first years of the 21st century, driven by fast progress in experimental quantum optics and a concomitant theoretical development bringing together physicists, mathematicians, and computer scientists.
Meanwhile, enthusiasm has somewhat waned in view of the formidable technical problems that remain to be solved, but a certain fascination survives. It is nourished by the perspective of exploring a completely new construction principle for computers that appears to offer possibilities inaccessible to classical computation. Buzzwords like 'quantum teleportation' and 'quantum cryptography' produced their effect. Given the flood of recent literature on the subject, it cannot be the purpose of the course to add yet another introduction to quantum computation or to contribute to propaganda in its favour.
The topic is nevertheless included because it illuminates certain facets of the way quantum systems store and process information from a relatively applied point of view, contrasting it with the way similar tasks are solved on the classical level. Another crucial difference not yet mentioned between Hilbert space, the state space of quantum systems, and the phase space of classical mechanics is that quantum states are endowed with a phase, besides their position in Hilbert space, equivalent to a real vector.
By contrast to the direction of the state vector, this additional variable with the characteristics of an angle is not related to any directly observable physical quantity. Notwithstanding, it does play a role in an emblematic quantum phenomenon, interference. Like other waves, quantum matter waves can superpose and thus interfere constructively or destructively.
This alternative is decided by the relative phase of the superposed waves, ranging from plain addition to mutual annihilation. The phase determines the sign more generally, a direction in the complex plane associated to each component of a Hilbert-space vector, while information measures only take their magnitude into account. The decisive question in the context of information processing is: can this variable be utilized like any other state-space coordinate, adding a dimension that is not accounted for in classical measures of entropy and information such as Boltzmann's or Shannon's, respectively?
A brief comparison already reveals that the quantum phase cannot be treated as an information-carrying state variable, i. To be sure, there exist operators with the properties of an angle, as a cyclic spatial coordinate which fulfils a corresponding commutation relation with a quantized angular momentum.
The phase is of a different nature. In fact, there are alternative representations of quantum mechanics, like Wigner's [ 55 ], where quantum coherence is encoded in features other than phases. Claiming that information can be stored in the phase is misleading, at best. Physical reality can be attributed to the phase only as far as it is involved in superposition processes.
This does not exclude taking advantage of it as a resource in computation, though not in the same way as a common Hilbert-space dimension. As soon as a quantum system is forced to assume a specific state among several alternatives, such as in output processes, the phase is lost and with it its potential to participate in the computation. Till then, the system can be kept pending between alternatives and process them simultaneously; they remain latently present in the quantum state without becoming individually manifest.
The gist of quantum programming is to exploit this resource as far as possible, optimizing protocols and input and output procedures accordingly. Obviously, a system's capacity to store and process information increases with its size. In order to obtain an extensive variable, proportional to the number of involved degrees of freedom, Boltzmann made his entropy depend logarithmically on the spatial size accessible to each freedom and the resolution available to measure its position, etc. Classically, the information thus increases linearly with the number of subsystems and logarithmically with their size.
The same is true in quantum mechanics. Quantum computers consist of qubits, each one contributing two dimensions to Hilbert space, but can be perfectly compared to systems described by continuous observables like position and momentum, if only the Hilbert-space dimension is finite. The relevant unit in phase space, a Planck cell, amounts to one dimension of Hilbert space.
Recursion Theory and Complexity
Quantum coincides with classical entropy in that it grows logarithmically with the state-space dimension, hence linearly with the number of qubits. The advantage of quantum computing appears only in a subtler detail: quantum dense coding [ 43 ] does in fact not refer to the storage capacity as such but to the way qubits are addressed.
With a basis comprising entangled states, the entire content can be accessed operating only on a single subsystem. This feature reflects again that in quantum mechanics, subsystems are not necessarily associated to qubits one to one. The variety of alternatives encoded in a single entangled initial state can be processed in parallel in a quantum computer till a result is read out, reducing the initial superposition to a single option. A lead over classical computing can only be gained as far as it is advantageous to have the results of the same algorithm, applied simultaneously to several inputs, latently ready, till one of them needs to be finally saved or processed further.
There exist a number of tasks that fulfil this condition and serve as prototypes to demonstrate the virtues of quantum computation. They range from finding the parity of the outputs of a binary operation Deutsch's algorithm through factorization of natural numbers Shor's algorithm through sophisticated problems like fast Fourier transform. Quantum parallelism is already being applied to other tasks, such as network search engines, using parallel architecture on conventional platforms [ 56 ].
Quantum dense coding and quantum parallelism make essential use of the quantum phase, thus depend on its faithful conservation during all operations. Quantum computers must preserve the coherence of the quantum states they are processing, that is, phase correlations must not be perturbed.
This requires above all that the system remain isolated from its environment while operating. As pointed out in the context of classical computing, even binary operations systematically discard one of their two input bits. For this reason, the exclusive use of reversible logic is vital for quantum computation. In analogy to reversible classical gates, quantum gates perform unitary transformations on qubits which in principle could be restored by applying the same operation backwards to the output—not to enable an 'undo' at any time, but to avoid the entropy generated by converting the unused bit into heat.
Usually, the complementary output bits are not processed further but kept idle till the algorithm terminates. In this way, the information loss inherent in logical operations can be circumvented. It proves much more difficult, however, to suppress natural decoherence through the coupling of the central processing unit CPU , typically implemented employing microscopic particles like single electrons or nuclei [ 43 , 57 ], to the ambient world.
Apparently a mere technical problem, it turns out to be almost prohibitive. Initially, the CPU must be prepared from outside in a predetermined quantum state. Upon completing the computation, it must be observed by measurement to extract the output. Both tasks require strong interaction with the macroscopic device containing the quantum CPU. Phase coherence is inextricably related to the limited information content of a small isolated quantum system. Any leak, any minute contact with the environment will allow this vacuum to be filled with entropy entering from outside.
Equivalently, decoherence can be analysed in terms of entanglement. As soon as a quantum system prepared in a superposition of many states, as in quantum computation, interacts with the ambient world, they exchange information.
The central system will leave a trace in the environment, in particular in its phases, while loosing internal coherence. This process occurs likewise in measurements and in unintentional decoherence, irrespective of whether the imprint of the central system is observed or not: entanglement is transferred from the central system to the environment. It is intriguing to return from this specific close look onto quantum computation to the broader viewpoint of information processing in natural quantum systems. Seth Lloyd's 'Programming the Universe' interprets the world as a huge quantum computer in [ 4 ], quite in the spirit of the analogy promoted in this report.
A host of related questions arise: does nature perform quantum parallel processing? If so, given that no system is perfectly isolated, how do they preserve coherence? Why is entanglement is largely eliminated on molecular scales and beyond, i. How is this phenomenon related to the exchange of information between subsystems? In particular, why did humans, as macroscopic IGUS see section 3.
Why has nature, in developing brains as its high-end computing devices, opted for classical information processing, dispensing with the benefits of quantum computation or has it? Going to larger scales even, is the Universe as a whole a closed system, hence in a pure quantum state, maybe globally entangled? Recent research activities shed light onto this complex from different sides. Stimulated by technological challenges arising around quantum computation, standard models of quantum dissipation, in quantum optics and solid-state physics, are being revised: how are the parts of a system disentangled once it gets coupled to a reservoir, how does this process induce, in turn, entanglement with and within the reservoir?
In quantum chemistry, the idea, prevailing for decades, is questioned that the functional dynamics of enzymes can be analysed on basis of Newtonian mechanics alone. Evidence accumulates that quantum coherence not only survives within their active core but is even vital for their biological function [ 58 ].
Questions concerning large-scale structures of the universe are increasingly studied in terms of quantum information. Parts of the material presented here have been conceived for the first time in various seminars, talks, and informal discussions. Time in Quantum Mechanics. Topics in Applied Physics. Related places Sun. Milky Way Galaxy. How do series work? Series: Lecture Notes in Physics Series by cover 1—8 of next show all. Experimental methods in heavy ion physics Lecture notes in physics. Hamiltonian cosmology Lecture notes in physics by Michael P. Lie Algebras and Applications by Francesco Iachello.
Space plasma simulation by J. Viscous vortical flows by L. Stochastic Quantization by Mikio Namiki. Nuclear Structure Physics by U. Constructive Quantum Field Theory by G. Twistors and Particles by L. Physics of the Expanding Universe by M. Critical Phenomena by F. Computing in Accelerator Design and Operation by W. Nuclear Astrophysics by Wolfgang Hillebrandt.
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