Time is one of the undisputed foundations of our life in the real world. Here it is argued that inside small isolated quantum systems, time does not pass as we are used to, and it is primarily in this sense that quantum objects enjoy only limited reality. Quantum systems, which we know, are embedded in the everyday classical world. Their preparation as well as their measurement-phases leave durable records and traces in the entropy of the environment. The Landauer Principle then gives a quantitative threshold for irreversibility. With double slit experiments and tunneling as paradigmatic examples, it is proposed that a label of timelessness offers clues for rendering a Copenhagen-type interpretation of quantum physics more “realistic” and acceptable by providing a coarse but viable link from the fundamental quantum realm to the classical world which humans directly experience. There are at least two levels of uncertainty associated with Quantum Physics since its discovery, and they are not independent of each other. The basic quantum formalisms are well-established and they comprise intrinsic quantified uncertainty relations. The observed behavior of quantum systems seems weird and runs in many cases completely counter to expectations directly based on everyday experience. Interpretations of quantum mechanics try to bridge that gulf. Interpretations of the formalism are many and partly mutually exclusive or even contradictory . From thKeeping to the overwhelming naive observational evidence and leaving Einstein relativity aside for a start, one can coarsely outline a distinction between two major domains.Massive bodies occupy single well-defined positions; there are macroscopically distinguishable states, quantities like mass, energy and momentum can assume continuous values, thermodynamics provides the foundation with global irreversibility and an undeniable arrow of time according to the Second Law of Thermodynamics, entailing causal order; measurements do not perturb the measured, and Special and General Relativity deliver the best models of the spacetime-background with Newtonian space and time as almost perfect approximations for daily use.Many quantities, like energy and spin, come in discrete packets—they are quantized. In some sense, mostly microscopic systems are rather fragile and undisturbed (most often isolated) ones are described by the linear Schrödinger Equation, characterizing a unitary evolution of the wavefunction, superpositions of wavefunctions, entanglement, decoherence, reversibility, non-locality and uncertainty relations for joint measurements of non-commuting observables. Measuring entails back-action to a measured system, and the Born rule applies when obtaining definitive results in the form of individual random single outcomes of measurements.It goes without saying that this distinction is referring to theories and descriptions and their respective scopes of application and not to Kant’s “Ding an sich”. Even when starting with a rather broad notion of classical (and quantum) phenomena, some intrinsic quantum mechanical aspects, which cannot be understood in classical terms, remain . It is tThe Copenhagen interpretation postulates a disruptive collapse of the wavefunction, whereas decoherence accounts, as the seemingly major alternative, formally stay inside quantum mechanics and expound why a result is effectively  as good as a genuine classical state .Decoherence does not entirely resolve the measurement problem as the mechanism by itself does not explain the occurrence of definite outcomes according to the Born rule; the composite system remains a superposition, and at least some robust entangled states are still reversible in principle ,7,8,9. TDifferent thresholds from criteria for entanglement can be given, while limits to easily detect existing entanglement in the presence of noise have been pointed out recently ,16,17.Mixing these levels of QM and CM, and stepping back and forth between the relevant descriptions can easily lead to inconsistencies and contradictions. A recent thought experiment has highlighted that the three naively innocent assumptions of Universality, Consistency and Uniqueness apparently cannot be met simultaneously by plain unitary quantum physics applied indiscriminately to itself .In a short paper, it has been argued that emphasizing complementarity and keeping with a fundamental distinction between QM and CM, accepting the importance of a clear Heisenberg cut, one can avoid the purported contradictions . The conWhen a measurement has been performed and the outcome is determined (and remembered), an outside observer not knowing that outcome, can assign classical probabilities to it, but cannot put the total system - including an inside classical observer—in superposition, with humans living in CM. A version of the experiment, where these are replaced by fully reversible quantum computers and thus remaining completely inside QM, would be principally different ,12,19,25This line of argument redeems Schrödinger’s cat from its unpleasant status: the constellation would just describe an improper use of the quantum formalism when including a truly macroscopic entity, where a lot of entropy is generated and time-reversal of the full system simply is not possible. Isolated is only the decaying nucleus; the relevant observer and a record is established by the poor animal. The uncertainty for an external observer is purely epistemological, only secondary to the one of the quantum system hidden inside the sealed arrangement.“We just cannot have classical and quantum behavior at the same TIME” was proposed as catchphrase for epitomizing “timelessness” inside QM. The argument is that, with time starting anew with each collapse at the strongly asymmetric transition from QM → CM, the very concept of time inside QM appears questionable . At the In the following, this proposal shall be somewhat detailed and some explications of how this might offer interesting perspectives are sketched, including some relationships to selected experiments, extant approaches and interpretations.The concept of time has a long and rich history in itself. In CM, time is Newtonian, absolute and existing from its own nature, linearly passing without relation to anything external, without reference to any change of matter. Later, with special and general relativity, the universality and absoluteness of time has been overthrown. Interestingly, also inside QM, Newtonian time is (mostly tacitly) presupposed as a fixed background causal structure, i.e., the standard Schrödinger Equation as well as the Heisenberg picture work with linear time. An approach to rectify this and to devise a true quantum clock (Page-Wootters mechanism) and similar constructions claim their success by yielding essential Newtonian behavior for subsystems while the global system is stationary ,28,29. TThis and the following leave out the very beginning of time, i.e., the first split moments where it all began with The Big Bang. An embedding in overall boundary conditions including the start of the universe shall come as a later topic following the more modest and restricted aim of first outlining a link between ordinary human everyday reality and QM in the sense advocated by Anton Zeilinger ,31.Time has been thought of as similar to space and, later, it has also been declared as devoid of any independent existence without space ,33,34. TQuite the same argument can actually be raised with respect to time. Leibniz, and later, amongst others, Einstein, saw it as the order of successive phenomena (which need to be distinguishable from each other).Time in fact is relational at a very basic level, even without special or general relativity, as time is always measured relating to some type of “enduring” reference.No clock is a clock without some memory. There are minimum requirements on traces, i.e., distinguishable and telling memory records .Taking a simple pendulum as an example, one needs to recall that (where) the mass has started to move in order to take this as a basis for monitoring any change or process. For durations spanning more than one full swing, additional information storage is required, e.g., a little friction (energy transferred to a heat reservoir and increasing entropy there) to distinguish one period from another . When buFor a classic pendulum, its dynamics are always well defined whether specifically looked at or not. Moreover, for isolated CM set-ups without observing the system, we can tell the position of the mass for any selected point in time, and, upon observation, we find just this one predicted value. Uncertainties are not at all a matter of principle at the same level as with the case of an isolated quantum system.Not only classical mechanisms but also useful quantum clocks need to generate observable time marks; CM “tick registers” are required for keeping an irreversible record of the clock time ,39,40.With full identity or full reversibility of repetitive states, no elapsing of time nor any direction of it can be told. Thus, even before many specific and rather involved problems with time can be identified, the notion appears a little more intricate at its conceptual foundation than is commonly thought ,41,42,43Overall irreversibility is described by the statistical Second Law of Thermodynamics, which states that the total entropy of an isolated (sufficiently large) system can never decrease over time; only in cases where all processes are reversible does it stay constant. As an example, large increases in coherence times for the dephasing of a qubit are observed as a cavity is decoupled from its environment . In smalThere is a well-defined condition for connecting activity (changes in time) with changes in information. That “Information is Physical” has been put on a solid theoretical basis by Rolf Landauer already 50 years ago . LandaueThis energy must be dumped to the environment, i.e., transferred to a heat reservoir. Landauer’s principle has been found generally valid in a large number of experiments, actually comprising CM and specific QM settings ,53. For For QM, this might offer a way to pin down the shifting split, which is not even new: it is the merging in the flow of control, a two(or more)-to-one mapping of states, which is decisive ,54,59. LLandauer’s principle also dovetails with the Holevo bound stating that for n qubits only n bits of classic information are retrievable ,62.John Cramer reports Erwin Schrödinger saying that a state vector would collapse as soon as some macroscopic record of the result of a measurement is made, and Werner Heisenberg suggested a collapse occurs when a quantum measurement would pass from the domain of reversible processes to the domain of thermodynamic irreversibility .With the uncontrolled transfer of a minimum amount of energy (or of another conserved quantity), unitary evolution of a quantum system, as described by the linear Schrödinger Equation, is interrupted . IncreasBefore an interruption like this occurs, decoherence can be effective .Von Neumann entropy grows with increasing decoherence in quantum systems, evolving with scattering processes . LesovikA full projective measurement in a quantum system irreversibly reduces the entire set of possible outcomes to a single specific one. This precludes complete reversal and thus means some loss of information and an increasing total entropy. Tradeoffs between information gain and the disturbance of a quantum state are close to the heart of QM . True coAssigning a maximum amount of information of one bit to a basic quantum system  fits the picture ,61. ReveConversely, in the absence of disturbance, entanglement can be swapped and new partners to a quantum object are recruited.Avoiding uncontrolled entropy production, a prepared central quantum state can be recovered from an ancilla or the environment in a second step if they were sufficiently entangled, even if that original state is destroyed specifically between the start and end measurements ,70.With tightly engineered and controlled dissipation, an approximate Bell state in qubits can be produced deterministically and stabilized ,72. PrevThe collapse of the wave function according to the Copenhagen interpretation can be understood as asymmetric and as defining a clear arrow of time, each time a projective measurement is made. It points from QM → CM, and it has the direction of the general thermodynamic arrow of time in full accordance with Landauer’s principle ,74,75,76The above-identified irreversibility applies to reconstructing the undisturbed quantum state, leading to a specific outcome, but in particular also to the earlier preparation stage, when and where that quantum system started out . At thisJust the same as measurement, preparing a quantum state, reduces many options to one, both can be understood as erasing information concerning an earlier state, which is not fully accessible and cannot be reconstructed thereafter.State preparation is a measurement, and it generally involves energy transfer to, and associated entropy increase in, the environment containing and constraining the quantum system, in which the special delicate state is realized ,78,79,80Contrasting the CM state immediately before the preparation of a quantum system with the CM situation after the measurement, many options have been reduced to one; certainly, some information has also been obtained. A many-to-one mapping actually can be claimed to have happened at both borders of the embedded quantum system in a CM frame. These local increases in order have a price in the form of increasing entropy outside that limited subsystem and outside the time interval between preparation and measurement. The arrow of time thus nicely points from the preparation to the measurement of a quantum state, both in the outside enshrining CM; it effectively bypasses or bridges the quantum domain.This does not entail any circularity as a potential problem, which Tejinder Singh has warned of . On the Classical states enclose the thus embedded QM realm at both ends, fixed and marked by enduring records, at least since time started quickly after The Big Bang with the universe in a very special, highly ordered, low-entropy initial condition. Such records need not be clear-cut snapshots of a situation possibly containing a detailed logging of earlier events; increases in overall entropy as in the case of a damped pendulum also qualify. It is reassuring also that Murray Gell-Mann and James Hartle, in their attempt to derive classical behavior from the sophisticated application or quantum mechanics and coarse graining, employ records but conclude that “generalized records of histories” need “not represent records in the usual sense of being constructed from quasi-classical variables accessible to us” .Even non-measurements, i.e., (quantum) measurements completely without disturbing the measured object, as first envisioned by Mauritius Renninger, can be understood as relying on, in this case well-defined, CM framing .Interaction-free measurements in a well-controlled set-up, with an object including knowledge about its prior location, can yield information about that object without changing its momentum, but then the momentum of the detection device will necessarily be altered upon absorption of the involved photon, as in the example by Lev Vaidman .Quite generally, no result is a result without knowing what the measurement set-up was. Niels Bohr formulated a contextuality requirement: “the unambiguous account of proper quantum phenomena must, in principle, include a description of all relevant features of experimental arrangement” . ArchibaThis complementary embedding and framing of QM in a context of CM is claimed as necessary and marking limits and constraints for all meaningful interpretations of QM. At the same time, it preserves some overall  “distributed” locality as well as real causality and guarantees that no information or energy is transmitted between the endpoints with a velocity faster than the speed of light . It has The proposal here then is that in-between state preparation and measurement, in undisturbed QM, a concept of time, different from our standard one, applies. In the absence of irreversibility and without permanent records, time just is not “real” inside an isolated quantum system. Restricting the notion of time to its classical manifestation in CM (records), “timelessness” could be a label for the quantum world, QM. Lacking time as a fundamental pillar, QM objects, no matter whether waves, particles or their paths might be considered “unreal” ,79.“Timelessness”, as such, is not a new idea. It was proposed in a specific form by Albert Einstein. In a block universe, all of space and time is claimed to exist eternally ,75,90.Long known general findings fit nicely: the entropy in an isolated quantum system is constant, and that time is not a simple quantum observable has been pointed out already by Wolfgang Pauli . Time caIn order to obtain real eigenvalues of a Hamiltonian, it is not really mandatory to have only Hermitian operators; the weaker condition of PT symmetry is sufficient ,95. WithSystems, which are characterized by time-dependent Hamiltonians and where energy is not conserved, clearly cannot be considered “isolated”. They are tied to boundary conditions and to laboratory time (CM) and are by definition, easy to accommodate in the Heisenberg picture of QM. With discrete time, “individual instants” might be considered timeless, and Born’s rule applies for measurements at those points. In turn, from the discreteness of time with a finite step size in the presence of a location-dependent force, microscopic entropy and time irreversibility can be derived via ensemble averaging .A recent proposal for an evolving block universe acknowledges the omnipresent daily use of classical boundary conditions; the past is fixed and the future is (described as) open; the future simply does not exist at any experienced point in time yet  . SpacetiAccording to the famous statement by Richard Feynman, Thomas Young’s double slit experiment contains the essence of QM. Therefore, it seems only natural trying to look at how a fresh proposal of CM-constrained QM-timelessness might shed a little light on the paradigmatic double slit experiment in some of its different versions.60 and C82 [Packets of energy, photons or particles arrive in single locations as particles while exhibiting wave-like interference on a screen, which is placed at the opposite side of the source, far behind the slits (Fraunhofer regime). The interference pattern builds up when probes are sent one by one, and what is observed is self-interference for each single particle . The sam and C82 ,102.Richard Feynman’s path integral approach does take into account all possible routes of a probe between source and detector, not only classical trajectories where action is stationary (at a minimum), but also non-classical paths .Only recently has it been confirmed by extensive simulations that in a triple-slit set-up, simply assuming an interference between signals from slits, open one at a time, is not fully correct ,104. AllIn the case of three slits, experiments have actually shown that all conceivable paths contribute, and Sorkin parameters quantifying this have actually been measured ,106. DevDeliberately constraining and excluding looped trajectories by adding carefully placed absorbers allows for quantitatively controlling the magnitude of the Sorkin parameters, which depend also on the Gouy phase ,108.Timelessness in this context would simply mean that a particle or photon can in a sense effectively explore all of the possibilities permitted by the boundary conditions. With no time passing, there is also no shortage of time, and all possible transits do contribute according to their weight (based on the integrated action). Looking at the outside CM world, the occurrence of non-classic paths can be detected as a phase shift in the recorded interference pattern .Complementarity as proclaimed by Niels Bohr implies that in a single experiment a quantum object either shows wave or particle characteristics. In particular, in the double slit experiment, there is no way of determining with certainty which path a particle took while still observing a wave-like interference pattern at a screen some distance behind the slits. The important point to observe now appears to be that this information  certainly belongs to the CM world outside of the investigated quantum system. Whenever complete which-path information is available in principle, classical behavior is observed and interference is destroyed. This has been found in uncountable experiments for waves and particles including heavy-weights like Fullerenes ,102. ForOne line of argumentation does not necessarily in all cases obviate or invalidate a second one; on the contrary, several somewhat independent lines of argument and derivation—the more diverse , the better—substantiate any result; e.g., wave-particle duality relations have been shown to be equivalent to entropic uncertainty relations .Looking at the primary examples, the full determination of which way a particle travelled seems to imply the blocking or full detection of a particle, and thus some non-negligible energy transfer before, or rather instead of, the probe hitting the final screen. In light of the above, this would just mean that a collapse has occurred and QM has been left at that first occasion.Particles and wave packets, which are strongly marked in order to disclose a path, e.g., by spin, show no (self-) interference pattern.For cases with reduced information on the path, a deterioration of the interference fringes has been calculated and observed for ensemble averages; non-demolition experiments allow to explore the trade-off between particle and wave signatures, necessarily employing ensembles of probes, not specific single ones . In expeIf disturbance is kept to a minimum using weak measurements, it is possible to observe post-selected average trajectories of single photons in a two-slit interferometer . Which-wSimilar to tests of Bell’s inequality, in delayed choice experiments as conceived of by Archibald Wheeler, any change is effected after the probe has left the source, but definitively before it is recorded ,117. ExpWith timelessness for the free particle/wave in between, it does not know when something happened and there is no well-defined moment in (nor record of) the pure QM phase, while boundary conditions are effective throughout. “Erasing” afterwards means filtering applicable sub-ensembles , which reestablishes an interference, strictly limited to the selected/filtered ensembles. Any actual choice brings suitable coincidences to the foreground and out of the hiding among the total observed events by means of considering only relevant corresponding events (records thereof).Timelessness entails non-locality, a particle and its entangled partner in a sense are everywhere, continuously, always together (if sufficiently undisturbed). Provoking an event, i.e., interrupting anywhere/anytime, leads to one integral result following from the overall probability distribution and the intimate link between fully entangled partners.In a variant of the double slit experiment, Shahriar Afshar has devised a layout, which seems to demonstrate a violation of the complementarity principle, as it is (incorrectly) understood as posited by the Copenhagen interpretation . A grid These findings have been taken as an argument for the transactional interpretation of QM, which proposes some hand-shake between retarded and advanced waves and thus describes atemporal pseudo-time conditions between emitter and absorber . John CrThe realization of a modified Afshar experiment using a Fresnel biprism and single photons yielded results fully compatible with the standard interpretation of QM including the complementarity relation .Answering an objection that the measurements would not be simultaneous, Afshar claims that complementarity is violated as both findings would refer back to what “takes place” at the pinholes when a photon passes that plane.An interpretation emphasizing the uncontrolled transfer of energy (collapse) could elucidate Afshar’s findings by the fact that the grid (the obstacle) is placed in areas which are not crossed by the main contributing “paths”, and at these locations, no interference pattern is effectively recorded. An interference pattern is just inferred; hardly any collapse takes place there and no time-stamp clearly visible in the statistics is generated.Timelessness with the full probing of all possible options for an undisturbed wave function might offer a heuristic connection to the randomness intrinsic to QM. Chance results are what happens when from a wide range of different options, one is selected like in a lottery. In the classical world, statistics on the results for ergodic processes can be compiled by either repeating the drawing exercise over and over again at different points in time or at one time in parallel from many instantiations of that distribution, i.e., identical ensembles. Aside from the principal problems of having a quantum state over time resembling a composite quantum state at a single time, both appear hard, with only one particle on its way between source and detector .Dropping the requirement of Hermiticity  while keeping four other reasonable assumptions for a quantum state over time, allows treating quantum systems over time in the same manner as composite systems at a single time .With all (timeless) potential outcomes available together, a single particle (or the universe during the The Big Bang) might constitute something like its own ensemble , suggesting a link to a frequentist interpretation of probability.With weak measurements, it is possible to characterize quantum trajectories, which bear some similarity to classical stochastic trajectories of particles interacting with a thermal reservoir ,114,116.The Born rule can be seen as a particular way of counting configurations, emerging from the factorization property of records as defined by Henrique Gomes and a reduction to the purely classical density . The difBorn’s rule has also been shown to result from picking outcomes with threshold detectors in a natural way from classical random signals for ergodic processes ,126. SomTaking collapse seriously with durable records laid down only then and defining these specific moments, entails monotonic incremental time in distinguishable steps as well as causality, and it obviates back-acting handshakes with the future ,63.The proposal here to “understand” the behavior of probes in the double slit experiment then is that classical records are essential and only they constitute “real” time or time compatible with special and general relativity . Classical marking points mandatorily enclose every isolated (or very tightly controlled) quantum system, for which  no “real” time passes in between state preparation and projective measurement .Records of different types have been postulated before ,131,132.A next grade of “timelessness” could be seen in the measurements of tunneling times. QM allows particles to transcend barriers, which are too high to overcome according to the laws in CM; i.e., particles/waves tunnel through them. Inherently in QM, when there is a finite probability density attached to one side of the barrier, there is some at the other side, too. Since the discovery of QM, the question has been raised as to what time the tunneling process would take, or whether it would take any time at all, and whether any delay might be understood as a transit time ,93,133. Just the same in each instantiation, state preparation and measurement of a tunneled particle would still need some time. Assuming an uncertainty relationship between energy and time, which is far from clear itself, it can be taken that with both of these steps, some short duration would be associated ,142.Even with zero time spent on tunneling itself, there is no problem with superluminal information transmission, as the probability of any useful signaling is negligible low .Time–energy uncertainty relations have been discussed already by the founding fathers of quantum physics and ever since. The only thing clear so far is that time–energy uncertainty is not at the same level as others, e.g., position–momentum, and there are many facets to the topic ,142,144.The situation becomes especially intricate in cases where energy below some (Landauer) threshold is exchanged with a quantum system and/or, in particular, when this is tightly controlled to carefully minimize disturbing back-action from the environment . “CollapAvoiding “instantaneousness” renders a “collapse” more “physical” and “real”. Real effective “moments” are “thick” and have a minimum duration. At the same time, there is less need to push “collapse” and the generation of records to the epistemic and mathematical realm like in interpretations of QM as purely individual Bayesian updating.Records cannot be arbitrarily sharp, not in CM and even less so in QM, where uncertainty relations prevail.An important class of time intervals is commonly derived for the durations it takes for any reversible quantum process to unwind completely, for a (QM) system to return to its initial state. This would mark the other end of the scale for time, as there are good arguments that this, in interesting cases, could take forever ,49. IdeaSimilar considerations actually are not confined to QM as full and exact measurable reversibility does not exist in any realistic CM system either. A common feature is that Poincare recurrence assumes infinitely accurately determined (and known) initial conditions, which have been debunked as un-physical ,152. As Long before close to an end of time, another limit is encountered. Even with arbitrarily accurate starting conditions, a “predictability horizon” in many cases limits time intervals for which interesting and meaningful forecasts are possible, i.e., the range for which developments and approximate expectation values for acceptable errors can be given (Lyapunov time).Principal limits to the achievable accuracy of boundary conditions and measurements , both in QM and CM, could be seen as somewhat blurring the distinction between these respective realms. On a conceptual level, it is obvious that with two areas closely bordering each other and actually interleaved with each other, with one of them comprising intrinsic uncertainty, the second one cannot also exhibit infinitely sharp conditions .An intimate link relating distinctions in time to causality and to entropy is obvious; it can convincingly be argued that time has to come in discrete increments for any meaningful concept of causality ,154.Stretching the frame here to its maximum, situations with effectively “infinitely long” as well as with “zero” time passing might be labeled as “timeless”. What remains in a limited middle ground would then be just “permanent” traces, entropy increased in the environment, i.e., records in their relative  ordering. It matches nicely that in the quasi-static limit, any logically irreversible computation can be performed in a thermodynamically reversible manner. Only if erasure is performed with a finite velocity the erasure becomes thermodynamically irreversible ,56.Real causality is inseparably linked to processes unfolding over time and total entropy accumulation. Causality does not go backwards, “events do not unhappen” is the formula coined by Lee Smolin . With anTaking into account that it is only classic records, which at the end can be unambiguously ordered in one or more light cones, findings where the future seems to influence or determine the past thus do not disturb everyday reality. This situation can only be (weakly) observed in sophisticated (QM) experiments and can possibly be harnessed in quantum computers ,157,158.Starting from small isolated quantum systems, a hierarchy of scales can be built including the meshing of relevant time scales ,161. “MoTaken together, contained “timelessness” might be a suitable label, which allows some “comprehension” by applying a sensible name for the peculiar conditions of isolated (very tightly controlled) systems in the underlying quantum world, which appear very strange and are distinctly different from what we know in the one world of classical physics, in which humans bodily live. Staying consistent with observations, with the well-established QM formalism, and also with some basic common-sense plausibility seems possible on a coarse and still meaningful level.Amending the Copenhagen interpretation rudimentarily with (at last) a quantitative physical correlate for “collapse” given by the Landauer Principle and thus anchoring QM systems in the reality of CM, the importance of durable records is emphasized. At the same time, the role of conscious observers is downgraded to being mostly inconsequential. Thus embedded in CM and the general flow of time as witnessed by increasing overall entropy, quantum states are real to a certain extent. Isolated quantum systems can be seen as “timeless”, while still constituting “objective elements of reality”. Inside QM, neither records nor the order of stages are determined; there is neither causality, nor retro-causality, nor both (at the same no-time). It might be seen as paradox that “timelessness”, when strictly contained in QM by classic framing in the real world, animates a “timeless” static block universe, which knows only unitary quantum physics, to be real, evolving, and open. Concerning questions relating to circularity, the speed limit for light fully applies in the accessible CM world, and a second mechanism also makes sure that effective “leaps” and “jumps” cannot be truly instantaneous: some time–energy uncertainty relations certainly prevent unphysical infinitely fast changes.A little light is shed even on subjective interpretations where consciousness interaction is claimed to be responsible for something like a collapse in a wave function; there might be cases when this is the first contact to CM, which triggers irreversible records, in particular, in sophisticated thought experiments.In summary, it is claimed that the proposal here obviates all types of “queer” interpretations and allows for a “comprehensible” link between our everyday classical environment and bizarre quantum systems; at the same time, the well-proven mathematical formalism stays practically the same and untouched.All real clocks are fundamentally thermodynamic. A most recent result shows that timekeeping has associated costs; a fundamental universal relationship between entropy production and clock accuracy applies in both quantum and classical regimes .Timelessness strictly inside the quantum realm with quantum systems embedded in the complementary classical world leaves an open end at the very beginning of the universe. Widely accepted notions of inflation might be rendered obsolete there. It goes far beyond what is possible in this short paper, but it could be well worth while attempting to correct the applicable time scale instead of finetuning an inflationary potential and process. In light of the above, the concept of  time simply would not fully apply before first structures, i.e., durable records, can form, conserved in a way (through their impact) and effective later (observable) in our epoch.The working hypothesis for the peculiar boundary conditions at The Big Bang: no space, no records, no time, no entropy.Claus Kiefer coarsely describes the emergence of space and time from the fundamental timelessness of quantum gravity, which appears to fit with the account advocated here . EntropyModular spacetime, with relative locality, offers another promising alternative, while apparently not necessarily contradicting, approach .Notably, a “slow beginning” of time can be interpreted as an effectively changing  speed of light. Swapping decoherence for collapses and entropy-production with records, classical irreversibility is obtained, while leaving the arguments relating to the beginnings (The Big Bang without inflation) pretty much the same, and averting a Big Crunch.In the end, the widest conceivable consistency is all that can meaningfully be asked for.


While different operators have different approaches to this functionality, overall it requires a demand-supply analysis of the various stations. While trip data can be used for this task, the existing methods in the literature only capture the observed demand and supply rates. However, the excess demand rates  are not recorded in these data, but they are important for the in-depth understanding of the systems’ demand patterns that ultimately can inform operations like rebalancing. In this work we propose a method to estimate the excess demand and supply rates from trip and station availability data. Key to our approach is identifying what we term as excess demand pulse (EDP) in availability data as a signal for the existence of excess demand. We then proceed to build a Skellam regression model that is able to predict the difference between the total demand and supply at a given station during a specific time period. Our experiments with real data further validate the accuracy of our proposed method.One of the most crucial elements for the long-term success of shared transportation systems  is their ubiquitous availability. To achieve this, and avoid having stations with no available vehicle, service operators rely on  During the past few years, urban and transportation planners have come to realize that if we want our cities to thrive and lead the way to a sustainable future, a turn to multimodal and shared transportation is needed. This has led to the fast growth of shared transportation options, with shared bike systems enjoying particularly wide adoption across the world . The firrebalancing  is very important for estimating the bike excess demand, which is part of the total bike demand . A similar approach can be used for the supply side, i.e., for the cases where a user wants to return a bike but the station is full and hence, she cannot store it at the dock.In this study we provide an empirical approach for estimating the ing spot . As we wConsequently, we show that even though the total demand  can be predicted at an acceptable level through a Poisson regression, the correlations between the supply and demand side—each of which modeled through an independent Poisson distribution—are high enough that leads to biased results when using them for predicting the net total demand . The net total demand is our target of prediction since it provides direct insights for the bike operator to decide the number of bikes to be rebalanced. To overcome this challenge we further develop a Skellam regression model that directly models the net total demand in a station, and, thus, accounting for this correlation.In summary, the contributions of our study are twofold:We introduce an approach for estimating the excess demand of bike sharing systems using high-level ideas from queuing theory. Key to our approach is identifying temporal segments—which we term excess demand pulse (EDP)—in the bike availability data, that include changes in the availability from zero  to non-zero . After introducing the theoretical underpinnings of our method, we verify through simulations its ability to estimate the excess demand present in the system. We consequently apply our approach on data obtained from a real bike sharing system, Chicago’s Divvy, to estimate the excess demand present in the system.Using the estimated excess demand, we learn a Skellam regression model through maximum likelihood estimation for predicting the net total demand, which shows advantages over other alternative models, both in terms of predictive performance, as well as, interpretability. Moreover, our Skellam regression model, as a generalized linear model, allows us to get a better estimation of the uncertainty of our prediction, since we essentially obtain the whole probability distribution of our dependent variable.There have been several studies on demand prediction in bike sharing systems, i.e., the expected number of bikes to be rented and returned at each station. Most of them only consider the observed demand, i.e., the demand reflected in the trip data logged by the system –10. HoweIn a slightly different, but relevant, problem formulation some studies focus on bike availability prediction, i.e, the expected number of bikes available for rental at a station , 16–19. et al. [Some of these studies, such as the one from Schlote et al.  point ouet al.  identifyHowever, there are studies that attempt to estimate the volume of excess demand using a simple method based on the duration for a station being empty –23. Theset al. [While several distributions have been used to model the bike arrivals (and departures) within a bike sharing, including negative binomial , Weibullet al.  show thret al.  that theAs aforementioned, excess demand is not captured in the recorded consumption of a product, since it appears when there is zero supply. Hence, it is very challenging to estimate it. In this section, borrowing ideas from queuing theory, we will introduce a way to estimate the excess demand. We further simulate the bike rental and return process to show the ability of the proposed approach to estimate the excess demand in a bike sharing system. Then, we apply our approach on data obtained from a real bike sharing system, Chicago’s Divvy, to estimate the excess demand present in the system. Notations used in describing our approaches and models through the paper are shown in μ [μ), while the inter-event time intervals follow an exponential distribution with average At a bike station, we generally have two types of event flows occurring as illustrated in μ . This alf events . In thisa. a changes from 0 to 1 after a bike arrival at t1, and goes back to 0 after a rental at t2. This pattern is central to our estimation of bike excess demand rate (denoted with μe), and we refer to this curve pattern as excess demand pulse (EDP). We also define τf = t2 − t1 as EDP length. During the interval , the bike availability is constantly 0, which can be interpreted by someone that there are no events  happening during that time. However, this is not necessarily true. This constant 0 availability can indeed be due to no events happening during this interval, or due to failed bike rentals, that is, a customer tried to rent a bike but none was available. The pattern captured by the EDP serves as an important signal for the possible presence of excess demand and its degree. Intuitively, the presence of significant excess demand leads to situations where any supply that becomes available is consumed shortly thereafter. At the situation visualized in t1, it is quickly consumed (rented) at time t2. In contrast, if we consider the scenario presented in ta but it is not consumed quickly. Instead, another bike arrives at tb before a rental. Therefore, any bike demand in this case can be captured well from rental logs, and it is not excess. In other words, the pattern in Let us assume that the number of available bikes at a station is μe through the bike availability curves. μ). That is, the inter-event intervals of this mixture follow exponential distribution with intensity τf = t2 − t1 is a sample from an exponential distribution with average τF from multiple EDPs, denoting their average value as τm. By expectation, we should get Using these observations let us see how we can estimate excess supply in a bike station—e.g., a user tries to return a bike to a full dock—this is not an issue in the presence of bike excess demand. In general, there cannot be bike excess demand and excess supply at the same station during the same time. Therefore, each bike supply  event is successfully reflected in the bike availability curve when there is bike excess demand present. To reiterate, the inter-supply  intervals themselves follow exponential distribution with intensity τs. For example, in the segment in ta, tb, t1, resulting in We can also calculate the estimated arrival rate μe can now be estimated as Combining the two results above, the excess demand rate Evaluation on synthetic data. Since we do not have the ground truth for the excess demand in real data , we rely on simulations to evaluate whether μe. Our simulator begins with 0 available bikes at time t = 0 and ends at tend. The simulator operates as follows:Time to next event: We sample an exponential distribution with average τr that represents the time duration until the next event .Event type: We next have to decide the type of event happening. For this we sample a number re from a uniform distribution between 0 and 1. If a.Excess demand: If a = 0, i.e., there are no available bikes, the next event cannot be a departure. Every time (when a = 0) the next event is simulated as a departure, we mark it as a failed bike departure. This will allow us to simulate the ground truth for the excess demand.tend = 1000 hours), while we use μ = 3 bikes/hour, λ = 1 bikes/hour. By setting μ > λ, we can create several situations where the bike rental demand cannot be fulfilled hence generating excess demand. Finally, we repeat the simulation 400 times.We simulate 1,000 time points , we first focus on the number of departure trips nj,t. By daily collecting observations for nj,t during a given quarter , we obtain a sequence {nj,t}. We calculate the average B = 500 sequences of the same length as the observed one denoted as {rj,t}. We then compare the distribution of the observed departures {nj,t} and the Poisson sampled ones {rj,t} using two-sample K-S test [j we obtain the average p-value K-S test . RepeatiThese results verify that we cannot reject the hypothesis that the observed bike demand and supply in the Divvy system follow a Poisson distribution. However, we also make the assumption that the excess demands follow a Poisson distribution (possibly with a different rate). Given the sparsity of the excess demand data for each station and time period, the K-S test potentially fails to reject the null hypothesis due to reduced statistical power. However, it is a very reasonable assumption that the excess demand/supply will also be following the same distribution  as the observed demand/supply.Estimating excess demand of bikes in Chicago’s Divvy. Following the aforementioned approach of excess demand estimation, we can calculate the excess demand observed on the system. While the bike availability curves are just like the ones we simulated, there is one important difference. The excess demand rate in the real environment is not constant over time but it rather changes. For example, we expect the excess demand rate in the morning (rush hour) is higher than that in the late night. There are several factors that can lead to this temporal variation, ranging from people’s schedule  to weather conditions that change during the day. This temporal dependency does not allow us to use all τf intervals in the data to estimate a single, constant, excess demand. We will need to only use limited information, localized in time, to estimate the excess demand rate during a specific time interval.t1, t2) is able to inform us about the excess demand occurring in the immediately preceding interval . We can use τf = t2 − t1 is the only EDP length that we can use to calculate τm given the time-varying nature. Furthermore, we need to calculate the average inter-supply interval τs, which again needs to be temporally localized due to its time varying nature. For the setting in ta, tb and t1. Thus, we use inter-arrival intervals, i.e.,  and , to obtain td, t1) using In particular, we adjust the aforementioned approach in this section as follows. Here we still use stable). As with any Bayesian analysis, the prior can be purely subjective, or uninformative etc., but it can also be calculated by data. In our case, we can focus on a period of time around the time interval of interest and estimate the excess demand for the same periods over a week. If our measurement of the interval of interest was an extreme outlier, then the prior will shrink the final estimate. For example, let us assume that we want to calculate the excess demand rate at 9:30–10:00am on a given day, which is referred to as μ930. First, using μobs. Then using μprior. Combining these with the Bayesian average we will get our final estimate for μ930 as:The single EDP length aforementioned may cause the calculated excess demand rate to be extreme. For instance, if the bike was rented almost immediately after it was returned, then the excess demand rate would be calculated practically as infinite. While we could eliminate such observations—since most probably correspond to users that return the bike and re-rent it immediately just for time-limit purposes imposed by the operator—it is not clear what is the time threshold as a good standard to eliminate such observations . To avoid having to choose an arbitrary cutoff, we make use of the Bayesian average . The BayOf course, the choice of prior can be different, but the idea is that using this approach we can smooth extreme cases in a principled way. In the “Chicago bike sharing system does not allow for self-docking , 12. ThuThe availability curve now represents dock availability , rather than bike availability .0 dock availability means that each rack at the station is occupied by a bike.quickly the rack is being utilized again, thus, capturing, the excess demand for docks (which again is time-varying).The EDP starts with a bike departure (from a full station) and quickly ends with a bike arrival. This allows us to capture how τf still denotes EDP length (based on the definitions above), while τm still denotes average value of τf.τs still denotes the average value of inter-supply intervals, but to reiterate, based on the definitions above, in this case a supply is a bike departure. So specifically, τs means the average value of inter-departure intervals.e to denote excess demand rate of docks, which is formally defined in We use λExcess demand in different stations. As one might expect, the excess demand rates differ among different stations. The maps in Figs Excess demand and sporting events. In order to provide some context for the excess demand observed at the system, we examined the estimated excess demand near the Wrigley Field during game days. For example, at 1:20pm on July 8, 2018, there was a baseball game in Wrigley Field between the Cubs and the Reds [the Reds . There ipost-hoc, descriptive, analysis of the historical excess demand rates in a shared bike system. However, it is also important to explore the ability to perform predictions for the excess demand conditioned on various external variables. This can facilitate logistics operations, such as, rebalancing, fleet updates, etc. We define the following:The data processing described until now can facilitate a Nμ: Number of rented bikes in a 30-minute time interval of interest. This includes both bikes actually rented and bikes attempted to be rented but there was no availability.Total bike demand volume Nλ: Number of returned bikes in a 30-minute time interval of interest. Again this includes both bikes actually returned, as well as, bikes attempted to be returned to a full station.Total dock demand volume Z = Nμ − Nλ: Difference between total bike demand volume and total dock demand volume in the same 30-minute time interval of interest.Net total demand volume Z during a specific time interval. We choose Z as our dependent variable since it provides direct insights for the bike operator to decide the number of bikes to be rebalanced. Therefore, we need to estimate the bike and dock demand volumes during each 30-minute period in our data. However, it is important to note that these total demand volumes, include both the observed from the trip logs demand, as well as the excess demand that is not directly captured in these data. In particular, we perform the following steps for each 30-minute interval in our data:In this section, we develop a predictive model for the net total demand volume at a station during a 30-minutes interval; i.e., build a predictive model for Calculate observed demand volumes: We obtain the number of observed departures, which is equal to the observed bike demand volume Calculate the excess demand rate: As per the discussion in the previous section, we also identify EDPs from bike and dock availability to calculate bike and dock excess demand rates μe and λe respectively.Convert rate to volume: If a time duration with the existence of excess demand  is located inside our 30-minute interval of interest, we denote the length of that duration for bike, dock excess demand as Nμ, Nλ, Z as:Using the above, we finally calculate Following the above process, we are able to obtain the net total demand volumes in the Divvy system for each 30-minute interval during the 2018 year.To build our prediction model for the net total demand volume, we consider a set of variables that are expected to be correlated with the demand for bikes and docks. More specifically, we use the independent variables listed in Z. We also explore and evaluate the predictive performance of a feed forward neural network and XGBoost on the same set of features.Each data record used to build our model describes a 30-minute interval of observations. Given that the weather data are only available on the top of the hour, we interpolate them for the half hour interval. Having identified the covariates to use in our model, we start by exploring two generalized linear models, namely, Poisson regression and Skellam regression. With the first approach, we model the total demand volumes for the bike and dock demand independently, while with the second approach we model directly their difference, i.e., the net total demand Z, an intuitive approach would be to predict the total bike departures Nμ and bike arrivals Nλ, and then calculate Z = Nμ − Nλ. Bike departures and arrivals have been widely modeled as Poisson flows [X as:To estimate on flows , 28–33, α and b are obtained through maximum likelihood estimation. We can also estimate the distribution for the dependent variable Y as:The parameters In our case, we have two processes that we need to model, namely the bike demand and the dock demand. Therefore, we learn two separate regression models using the covariates described above. For the rest of the paper, we will refer to this model as the “Two-Poisson regression” model.Nμ and total dock demand volume Nλ of a station can be up to 0.885), and in these situations the estimations will be biased [Z through a Skellam distribution since it represents the difference between two Poisson distributions [X, Y) ∼ BP, where λ3 captures the covariance between X and Y, then their difference Z = X − Y follows the Skellam distribution:Iz(x) is the modified Bessel function. What we can observe is that the distribution does not depend on the covariance (λ3) of the two Poisson distributions [The Two-Poisson regression model assumes that the two processes—rentals and returns—are independent and hence, we can model them separately. However, this is not necessarily the case . Predicting the net total demand for (particularly) the peak-hour periods is very important for the bike share system operator for various management operations, such as conduct an effective rebalancing. For learning each model, we split the data from all 300 stations and use 80% of the them to train the model, 10% as the validation set to optimize the regularization shrinking parameter, and the remaining 10% for out-of-sample evaluation. All models use L1 regularization, while we use the mean squared error (MSE) as our loss. The Skellam model training process follows the regression training setup in “Typically “peak-hours” for a transportation system include weekdays morning (7am-9:30am) and evening commute (4pm-6:30pm). However, for a bike sharing system there is also seasonality, especially during the summer months . Our datBaseline models. We compare our proposed modeling (Skellam regression) with the following four baselines: (i) two independent Poisson models (Section “Poisson regression”), (ii) a feed forward neural network, (iii) XGBoost, (iv) constant prediction. They are referred to as “Two-Poisson”, “Neural”, “XGBoost”, “Constant”, respectively in Z of those records, either btemp1, = 6.57 for bike demand and btemp2, = 6.90 for dock demand  demand. However, what if even by simply using the observed demand to train our models, we can still get a good prediction for the net total demand. To examine this we build our model using only the observed demand when we train the model. We then evaluate the predictions on the test set and the results are presented in For the results we presented above, we use the total demand As we can see, when training our models using the total demand . This type of demand is not directly recorded in bike trip logs. Key to our approach for estimating excess demand is identifying temporal segments in the bike availability data, that include changes in the availability from zero to non-zero. Through simulations, we verify the ability of our approach to estimate the excess demand present in the system. Consequently we apply our approach on data obtained from Chicago’s Divvy bike sharing system to estimate the excess demand present in Divvy system. To predict the net total demand (which includes the observed and excess demand), we learn a Skellam regression model through maximum likelihood estimation, which shows advantages over other alternative models, both in terms of predictive performance and interpretability. Moreover, our Skellam regression model, as a generalized linear model, allows us to get a better estimation of the uncertainty of our prediction, since we essentially obtain the whole probability distribution of our dependent variable.Although we mainly use bike availability records to estimate the excess demand, additional data sources can potentially improve the excess demand estimation. For example, a customer of the bike sharing system may use the corresponding mobile application to explore the bike availability of stations near her location. This search itself is a signal of bike demand, and in the case where there are no available bikes nearby we can consider this to be part of the excess demand. Of course, a good understanding of the way the corresponding app operates is required, since for example if a local search is performed every time the app is turned on this is not necessarily an indicator of demand in the area. However, similar data are hard to be obtained as they are only available to the bike sharing operator. Furthermore, as implied from the results in our analysis of a specific baseball game at Wigley field, excess demand on one station might lead to spillover demand on nearby stations. When focusing on the whole bike sharing system this might lead to double counting—once as the excess demand of a station and once as the observed demand of another station. Our framework can be further improved by extending it so one can avoid this potential double counting of  demand.Finally, while in this paper we focus on excess demand in docked bike sharing systems, excess demand also exists in dockless systems. In this setting we only need to consider the excess demand of renting bikes since bikes can be returned anywhere. However, this also means that there are no predefined stations. The lack of well-defined locations of bike demand provides additional challenges in analyzing these situations. The analysis should most probably focus on pre-defined areas within the city. However, identifying the spatial granularity needed is not a trivial task.S1 Text(PDF)Click here for additional data file.S2 Text(PDF)Click here for additional data file.


Modernization in China is accompanied by some specific features: aging, individualization, the emergence of the nuclear family, and changing filial piety. While young Chinese people are still the main caregivers for older adults, understanding the attitudes of young Chinese people toward aging and living independently in the context of modernization is important because it relates to future elderly care problems in China. By using in-depth interviews and qualitative methods, 45 participants were enrolled in the study, 38 (84.44%) were women and 37 (82.22%) had no siblings. The ages ranged from 17 to 25 years . Results revealed that participants held diverse attitudes about older adults, but the general attitudes were that older adults are lonely, financially disadvantaged, have poor social support, lack hobbies, and care about their children more than themselves. Chinese college students were affected both by traditional filial piety and individualism; however, of the two, they seemed put greater value on independence. Moreover, traditional filial piety is changing in a modern direction, affected by Western ideas of individualism: the status of the senior is diminishing, and living with one’s parents is no longer regarded as a necessary component. Implications concerning age stereotypes, elderly care policies, and strategies are discussed. Modernization is a broad concept that refers to major social changes that occur when a preindustrial society develops economically, such as industrialization, urbanization, and bureaucratization . Since tSecond, Western technology, political systems, and culture became a referential frame for the modernization of China . AlthougThird, modernization changed the power relationships in Chinese society . ModerniFourth, modernization leads to the breakdown of the traditional extended family and the emergence of the “individualistic nuclear” family . Yan 20. Nowadayxiao) is an important cultural concept in traditional China and other Eastern countries. It requires children to make sacrifices for their parents to ensure the continuation of their parents’ happiness—not only by respecting older generations but also by taking care of aging parents by living together  were women and 37 (82.22%) had no siblings. The ages ranged from 17 to 25 years . More characteristics are shown in YZh , JT , and TL  served as the primary research team; and YZu  and QH  provided an outside audit to check on the findings of the research team. In qualitative research, it is crucial that researchers address possible biases that might contaminate the coding and analysis of the data . AlthougFor readers to evaluate the validity of results, we share the attitudes of the research team: YZh said she agreed that living independently with children is not necessarily bad for old parents, but it could be an active choice of old parents; JT said she thinks being old is unimaginable and lonely, she wants to be with family when she is old, so she also wants to accompany her parents when they are old; TL said he wants to be a filial son and wants to have his own career, but he thinks the two are not contradictory, because living a good life is another kind of filiality. YZu said she believes that young Chinese should respect seniors, but it was unnecessary that they should live together because there will be lots of familial conflicts by living together; and QH said she thinks people could age gracefully and be productive and old parents should not live together with children, when old parents could not take care of themselves, children could hire senior workers to take care of their parents.A demographic form about age, hometown, etc., was provided to interviewees to fulfill before interviews. Semi-structured interview protocols were used with all interviews. Modifications were made after several interviews. Questions in the final protocol are: (1) Motivations to attend this study, e.g., “Why do you want to attend this study?” (2) Attitudes toward older adults and aging, e.g., “What are your perceptions of older adults and aging?” (3) Attitudes toward living independently, e.g., “What are your perceptions of older adults living without children?,” and (4) Coping with aging in the future, e.g., “What will you do when your parents/you become old in the future?”Each member of the primary research team interviewed 15 participants in Chinese. Each interview lasted from 20 to 50 min. After an interview was finished, it was transcribed  and analyzed in a week by the interviewer. Transcripts were assigned a code number to maintain confidentiality.Data were managed and analyzed according to Consensus Qualitative Research Methods CQR;  in NVivoBefore coding a certain transcript, a research member read the transcript briefly and created a case summary, which included about 200 words describing the attitudes of aging and living independently of the participant, as well as the reader’s initial ideas and feelings after reading the transcript. Although The primary team members examined the first three transcripts individually and placed each block of data related to the same idea into initial themes. Later transcripts were coded according to these initial themes, but when initial themes were not applicable, either theme was modified or a new theme was generated. Disagreements about themes and how to block the data were discussed until the team reached a consensus, which was audited by YZu and QH and then reviewed again on the basis of their comments. Four major themes were identified: (1) diverse attitudes toward older adults, (2) perceptions of reasons that lead to unhappiness/happiness in old age, (3) attitudes toward living with and without children, and (4) attitudes and coping strategies when parents/themselves are old. Results were translated into English.After blocking data into themes, the three primary team members independently read data within a given theme and coded them sentence by sentence. Each member then categorized codes and devised hierarchical categories. After that, the team met as a group to discuss their codebooks and to arrive at a consensus about the categories and how to word them. The themes and categories were continually modified throughout the process to reflect the team’s ongoing understanding of the data.Codebooks were then sent to the two auditors (YZu and QH) who read them, suggested additions and deletions and returned them to the primary team for further discussion and revision. The primary team then reviewed each case to make sure they had been consistent over time and to be certain that they had remained true to the participants’ perspectives. Revisions were made to the themes and about what was included in the themes for each case. The team added notes where appropriate to help them remember issues and questions that occurred to them, but these were not directly stated in the data. Then every case was examined again by the team members, who arrived at a consensus over changes.Using the consensus versions of the codebooks, the primary team met and conducted cross-analysis for all transcripts. The purpose of doing the cross-analyses was to compare the codebooks to determine consistency across the transcripts. We also wanted to ensure that we were applying the same criteria across transcripts.We reviewed each theme separately and evaluated categories. When a category was identified for certain cases, we returned to the raw data to determine whether the same category also fits other cases. During this process, the team developed dimensions for some categories. The team then calculated the number of participants who mentioned a certain dimension of each category for comparison, although some researchers did not support counting exact numbers because participants were not asked the same questions in the same way; therefore, counting numbers could be misleading . NonetheAfter we interviewed the 40th participant and analyzed the transcripts, no new themes or categories were added, assuming that the data were saturated or stable. Even though To ensure greater credibility, first, each team member was conscious of her or his attitudes about aging and living independently. Second, each researcher wrote independent methodological and reflective memos about the impact of her/his attitudes on the collected data. Third, the team met on a weekly basis to discuss the degree to which the researchers attitudes might have influenced the analysis of the data and the level of openness of the participants. Fourth, the team discussed data analyses and translations weekly and reached a consensus on both the results and the translations , 2005.According to the accepted research standards incorporated by this study, the privacy of each participant interviewed has been protected. The research team did not use the real names of the participants, nor any identifiable information. All participants were aware that they were participating in a study, knew the research objectives, and consented to participate in the qualitative research. It was explained to the participants that their participation was totally voluntary and if they chose not to participate or answer certain questions there would not be any negative repercussions. Signed informed consent was obtained for both the interview and audiotaping. Two participants did not consent to be audio-taped; however, their signed consent for notetaking was obtained. At the conclusion of the interviews, the participants were thanked for their participation and contribution to the research and were offered 15 RMB (about two dollars) for participating.Results were translated into English; the team reached a consensus on both the results and translations. Quotations are followed by the identifier of the participant. For a clearer presentation of results, We divided participants’ attitudes about older adults into four categories: attitudes concerning physical/mental health, quality of life (QoL), social support, and personality of older adults. We also assigned valence to each attitude as negative, positive, neutral, or unclassifiable based on the information provided by participants and research members reached a consensus on the valence assignment.n = 5), lonely (n = 15), unhappy (n = 3), anxious (n = 2), feeling hopeless (n = 1), and useless to their families and society (n = 3); in contrast, only few participants said seniors are healthy physically (n = 2), happy (n = 5), and not lonely (n = 1).More participants held a negative attitude about the physical and mental health of seniors than those who held a positive attitude. Some participants mentioned that they think seniors are unhealthy physically  of seniors into four subcategories: overall QoL, busy with labor work, richness of leisure activities, and economic affluence.n = 7). “Even though their lives are not that colorful, with less vigor and vitality, compared to our young people, it suits them well.” (#6) However, the sentence may imply participant’s latent attitudes that colorful lives did not suit seniors.One participant said elders’ overall QoL is just so-so, not too bad, not too good; some participants said this kind of life suits seniors well . In this continuum, idle and laborious were problematic in the eyes of the participants, while at ease represented a good living status. However, six participants considered that seniors want to keep themselves busy, although they did not need to do things. From these participants’ views, laborious work is not a bad thing because it is seniors who chose to do things rather than being forced to do them.Participants’ attitudes lay on a continuum from idle (having nothing to do) to at ease (having something but not too many things to do) to laborious (having too many things to do). These attitudes were held by nearly the same number of participants (idle: n = 5); however, many participants described older individuals’ lives as in a low or medium level of richness but used different words. As for the low level of richness, some participants described it by using words like “boring” (n = 16), which reflected a negative attitude in Chinese; while some used words like “simple” (n = 11), which reflected a positive attitude in Chinese. As for a medium level of richness, some participants described it by using the word “repetitive” (n = 2), which reflected a negative attitude in Chinese; while some participants described it by using words like “regular” (n = 12), which reflected a neutral or positive attitude in Chinese.Several participants mentioned that seniors have rich leisure activities (n = 2) and poor (n = 4).Several participants mentioned the economic affluence level of seniors; however, they used words in opposition: affluent (n = 2), have nobody to talk to (n = 1), have few friends (n = 1), and have no constant companions, for example, children (n = 1).All the five participants who mentioned this category held negative attitudes concerning the social support for older adults. They said seniors have bad marital relationships (n = 7) and open (n = 1), have no hobbies (n = 6) and have many hobbies (n = 3), lazy (n = 3) and industrious (n = 6), self-centered (n = 3) and do not care about the self but only care about children and family (n = 14), dirty (n = 1) and clean (n = 1), and dependent (n = 4) and independent (n = 3). Further, seven participants mentioned thrift, one mentioned brave, and another mentioned nagging.Participants used several contradictory words/phrases to describe seniors: closed  and unhappiness in old age (n = 6). Moreover, for some participants, feeling lonely (n = 1) and losing control (n = 1) were reasons for unhappiness, while feelings of belongingness (n = 3) and being respected (n = 2) were reasons for happiness.In this category, physical health ranked first as the main reason for happiness (n = 6) and happiness in old age (n = 5). Other participants said that having hard work to do (n = 3) or having nothing to do (n = 1) were both harmful to older adults’ happiness. Not needing to work (n = 5) but having a rich life (n = 4) were reasons for perceived happiness, which, again, indicates the difference between a choice and being forced to do something. Other descriptions of happiness in old age included living a regular (n = 2), quiet and peaceful life (n = 1) without having big stressful life events (n = 4).Economy was the chief reason mentioned by several participants as a reason for unhappiness (n = 31). In this category, children’s lack of filiality was the chief reason (n = 25), including not being around, not accompanying or visiting aging parents, having bad relationships with one’s parents, or bringing shame to the family. Some participants did not separate children from other family members and they used the term “family” generally. Having family conflicts may lead to unhappiness in old age (n = 8). Other reasons mentioned by participants that made older adults unhappy were living alone (n = 4), the death of a partner (n = 1), and living in nursing home (n = 1).Over half the participants mentioned bad social support as the reason for unhappiness in old age (n = 27). Children’s filiality was the chief reason (n = 21), includes being around, accompanying or visiting aging parents, having good relationships with one’s parents, or bringing glory to the family. Having good family relationships (n = 7), having friends (n = 7), having good neighborhood relationships (n = 3), and having people to accompany them (n = 1) may also make older adults happy.In contrast, 27 participants mentioned good social support as the reason for happiness in old age (n = 27) than those who mentioned personal traits as reasons that made older adults unhappy (n = 10). “Having hobbies” ranked first in personal factors for happiness in old age (n = 15), while only three participants mentioned “having no hobbies” as a reason for unhappiness in old age. Other personal traits associated with unhappiness and happiness included being closed (n = 3) and keeping pace with the time (n = 2), respectively; not content (n = 1) and content (n = 5), respectively; pessimistic (n = 1) and optimistic (n = 5), respectively; and bad character (n = 3) and good character (n = 1), respectively. Other personal factors for happiness in old age were having an ability , having faith (n = 1), and being resilient (n = 1).Notably, more participants mentioned personal traits of seniors as reasons that made older adults happy .This category was only mentioned by one participant as a reason for unhappiness in old age. Notably, four participants said that they did not notice any older adults being unhappy; they just saw unhappy older adults in the news. However, one participant was negative about aging and said that all older adults were the same—no one is happier, and no one is unhappier.In sum, participants’ reasons for happiness and unhappiness in old age were almost the same in both content and frequency. However, participants considered personal factors  to be more important for happiness in old age as compared to unhappiness.Since traditional filial piety is deep-rooted in Chinese culture, and participants ranked children’s filiality as the chief reason for the happiness of seniors, we then analyzed participants’ attitudes toward seniors living with or without children. Participants compared the cons and pros of the two kinds of living arrangements and considered that they were different in the four categories: mental health, QoL, social support, and personality.n = 12) mentioned that elders living with children were happier than elders living without children because they have children to depend on (n = 10), were less lonely (n = 6), do not have a sense of loss (n = 2), do not need to suffer from missing their children (n = 1), and do not need to worry about their children (n = 1). Some participants said that living with children helps elders feel spiritually supported by children (n = 10), which may also help elders to feel safe (n = 1). Two participants said that, when living with children, elders need to help children do some household duties. This may bring elders a feeling of being useful. One participant said, “Living with children brings older adults a feeling of superiority because her children could take care of her” (#1). Another participant said, “Living without children may lead to some mental illness” (#3). On the contrary, only one participant stated that it is better for elders’ happiness to live separately from their children because “they have more freedom; they do not need to depend on children; [and] they can decide what to eat, to buy, when to eat, [and when] to sleep” (#41).Many participants stated that it is better for old parents’ mental health to live together with children than to live separately from children. First, some participants (Although she (grandmother of father’s side) lives with us, my parents have to work, and I have classes. We only meet in the evenings. [In] a whole day, what can she do at home? She could not read; she could not watch TV. The only thing she could do is sit there” (#1).Two participants said that whether an older adult is happy depends on whether his/her children are filial rather than whether his/her children are living with them. Moreover, eight participants stated that being old is lonely, regardless of who you live with, because children are too busy to care for elders regularly: “The nanny with grandchildren…although she lives with children and her husband, she does all household duties. I feel she’s tired, and she’s getting older and older; her children won’t help…I think she may have some resent…but, another nanny, because she didn’t live with her children, if she wants, she could also go to visit her children. Usually, she visits neighbors, [I] feel she’s very happy” (#28).Concerning QoL, three participants said life is more colorful if children are around, another three participants said living with children gives elders things to do, and one participant said living with children enriches elders’ lives. In contrast, three participants regarded living with children as a disturbance to elders, and another three participants said it burdened elders. They said elders should be taken care of by their children; however, when living with children, some elders had to take care of their children instead : “Two participants said it is better for family relationships if elders are living with children; while one participant said that if they live together, there will be lots of mother and daughter-in-law conflicts, so it is worse for family relationships.One participant stated that living with children helps elders to be modern and keep pace with the time, although one participant said that it depended on elders and that older adults can have their own lives regardless of their living arrangement.In sum, more participants thought that living with children was better for elders’ mental health than living without children; however, there were perceived equal pros and cons concerning QoL, social support, and personal factors.Results before were general attitudes and perceptions of aging and living independently of participants, but in the last part, we invited participants to take a more “insiders”’ view, talking about their parents’ aging and their own aging, including living independently from their parents when their parents are old, and living independently from their children when they themselves are old. Below, we compare participants’ attitudes and coping strategies separately.n = 23). They said they would not let their older parents live alone (n = 16) because they would worry about them (n = 1). Ten participants said they could accept living separately from their old parents because it is an evitable trend (n = 5), they did not want to live with them (n = 2), and parents have their own lives (n = 1). Two participants said that their parents could adapt to living without children nearby when they are old. Furthermore, three participants were struggling with this issue: on the one hand, they wanted to take care of their parents; on the other hand, they wanted to have their own lives and pursue their dreams.At the time of interviews, many participants were studying away from home; however, many could not accept separating from their parents when their parents were old (n = 34) because it is an evitable trend for parents and children to live separately in the future (n = 4), they do not want to live with children (n = 9), or they do not need to live with children (n = 13). Nine participants said it is good for children to live separately because it reduces family conflicts and children can focus on individual development. Ten participants could accept living separately from children conditionally, as long as their children are living nearby (n = 5), children visit often (n = 4), children are filial (n = 1), and they have others to accompany them (n = 1). Moreover, three participants reluctantly accepted living separately from children: “if they do have to go outside to work, I can’t force them to live with me…just live my own life” (#16). Only one participant said she cannot be apart from her children when she is old because “the parent–child relationship is the most important thing in the world. Blood is thicker than water” (#42).Many participants said they can accept living without children when they are old (n = 31) was “try my best;” that is, participants would try their best to balance the needs of parents and themselves—the needs of filial piety and independence. This strategy included visiting parents often (n = 20), staying close to home (n = 6), living in the same city (n = 3), traveling with parents (n = 3), calling parents on the phone (n = 3) or video calls (n = 3), asking others to take care of parents (n = 3), and buying things for parents (n = 1). However, the “try my best” strategy implies that they would not live with their parents.Participants provided several strategies to care for aging parents. The strategy mentioned by the most participants (n = 12), which includes encouraging parents to have their own lives (n = 9): “[I] tell them to find some hobbies or go outside” (#2) and move to the city where the participants might live (n = 3): “Maybe I’ll pick them up if I’m living in a city someday. I’ll try not to let them live alone” (#4).The second strategy was to change parents (n = 10); that is, participants will make choices about how to take care of parents according to varied situations. For example, “if I have a good development, I will take parents over to the place I live; if I have a bad development, I will go back to the place my parents live” (#43).The third strategy was the “if…then” strategy (n = 3). They said they would give up their career in big cities to go back home and accompany their parents when they are old. One participant said that no matter what happens, she will not live with her parents when her parents became old (#25); and one participant said he will try to reach an agreement with his parents about their living arrangement (#12).The fourth strategy was to change themselves (n = 29), when they are old, they will depend on themselves for happiness. Only two participants said that they would try to educate children to be filial to ensure happiness. Many participants said they would get hobbies (n = 22), such as traveling, handcrafts, music, and painting. Some participants (n = 10) said they would make friends expand their social circle beyond their children. Five participants said they would have a good socioeconomic status because that determines QoL.According to most participants  Theory of Attitude Change argues that individuals are motivated to reduce the conflicts between traditional and modern cultures by changing their attitudes to semi-traditional or semi-modern: more “important” traditional concepts will change in a traditional direction, while the “un-important” concepts will change in a modern direction , 1972. SFor example, some participants said regardless of who you live with, being old is lonely because children are too busy to take care of the old parents. Instead, seniors had to take care of their children if they were living together. It seems that the relationship between children and parents is changing in a direction as suggested by modernization theory that modernization diminishes the status of seniors , 1986. MIn conclusion, our results suggest that Chinese college students are affected both by traditional filial piety and individualism; however, of the two, they seem place greater value on independence. Moreover, traditional filial piety is changing in a modern direction, affected by Western ideas of individualism: the status of older people is diminishing, and living with one’s parents is not regarded as a necessary component.The study had several implications. First, our results suggested that young Chinese people held generally negative attitudes toward aging in four dimensions: physical/mental health, QoL, social support, and personal factors rather than in the two dimensions of the Stereotype Content Model—warmth and competence . FurtherThis study had some limitations. Its main limitation is sample bias. As a qualitative study, it only enrolled a small number of participants. Specifically, participants came from a university in Shanghai, were in their 20s and many of their parents were in their 40s, and most of them were female and an only child. Therefore, this study’s generalizability is limited and its results cannot be generalized to other groups. This limitation may be inevitable for all qualitative research. Here, qualitative research findings are not intended to be generalized, but rather they aim to shed light on the attitudes or experiences of participants, revealing other voices. Our research also aims to share the various attitudes toward aging and living with parents of Chinese youth; however, whether these voices are representative of all Chinese youth is still questionable. The risk of sample bias means that we should be cautious about our conclusions, which could be reexamined by quantitative studies in the future. Second, we presented some information that we think may affect the validity of the results, such as participants’ motivation for taking part in the study and researchers’ gender, age, expectations, and bias; however, how they may affect this study’s validity is unclear. Future qualitative methodology studies could explore these aspects more deeply. Yet, providing background information is still important for readers to grasp the context of the “story.” Third, participants answered questions about their assumed attitudes and coping strategies when their parents and themselves get old; longitudinal studies that address participants’ attitude changes in the future should be considered.Despite these limitations, this study advanced an exploration of the attitudes of young Chinese adults about aging and living independently and, more specifically and deeply, helped to better understand Chinese youth undergoing social change. The study also suggested other dimensions of age stereotyping and methods to study stereotypes, pointing out the potentially negative effect of active aging on ageism and future elderly care models and strategies.yanzhangpsy@126.com.The datasets presented in this article are not readily available because some interviews may include identifiable personal information. Requests to access the datasets should be directed to YZ, The studies involving human participants were reviewed and approved by East China Normal University. The patients/participants provided their written informed consent to participate in this study.YZh contributed on research design, interviews, data analysis, and manuscript writing. JW contributed on research design, theory construction, and manuscript revising. YZu contributed on participants recruitments, interviews, and data analysis. QH contributed on interviews and data analysis. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.