The double slit experiment and the time reversed fire alarm

We advance a new viewpoint on the connection between the thermodynamical and cosmological arrows of time, which can be traced via the properties of cosmic microwave background (CMB) radiation. We show that in the Friedmann–Robertson–Walker universe with negative curvature there is a necessary ingredient for the existence of the thermodynamical arrow of time. It is based on the dynamical instability of motion along null geodesics in a hyperbolic space. Together with special (de-correlated) initial conditions, this mechanism is sufficient for the thermodynamical arrow, whereas the special initial conditions alone are able to generate only a pre-arrow of time. Since the negatively curved space will expand forever, this provides a direct connection between the thermodynamical and cosmological arrows of time. The structural stability of the geodesic flows on hyperbolic spaces and hence the robustness of the proposed mechanism is especially stressed. We then point out that the main relations of equilibrium statistical thermodynamics (including the second law) do not necessarily depend on any arrow of time. Finally we formulate a curvature anthropic principle, which stipulates the negative curvature as a necessary condition for the time-asymmetric universe with an observer. CMB has to carry the signature of this principle as well.

Aiming at the high false alarm rate when using single sensor to detect fire in aircraft cabin, a multisensor data fusion method is proposed to detect fire. First, the weights of multiple factors, that is, temperature, smoke concentration, CO concentration, and infrared ray intensity in the event of fire, were calculated by using the improved analytic hierarchy process (AHP) method on each sensor node of wireless sensor network, and the probability of fire event in the cabin was evaluated by multivariable‐weighted fusion method. Second, based on the mutual support among the evaluation data of fire probabilities of each node, the adaptive weight coefficient is assigned to each evaluation value, and the weighted fusion of all evaluation values of each node is conducted to obtain the fire probability. In the end, compared to the threshold of probability, the fire alarm is determined. Comparing the proposed algorithm to the grey fuzzy neural network fusion algorithm and fuzzy logic fusion algorithm in terms of the time consumption for fire detection and sending alarm and the accuracy of fire alarm perspectives, the experiments demonstrate that the proposed fire detection algorithm can detect the fire within 10s and reduce the false alarm rate to less than 0.5%, which verifies the superiority of the algorithm in promptness and accuracy. In the meanwhile, the fault tolerance of the algorithm is proved as well.

In this study, a double-slit experiment was simulated with only classical-mechanics assumptions to demonstrate that the phenomena associated with this experiment can be explained by classical mechanics. The experiment was conducted with the particle nature intact, by performing observations that did not affect the particle motion while recording the particle position at each simulation step. Only one experimental particle was assumed per session to prevent external effects. Nevertheless, wave patterns, which have previously been thought to occur only quantum-mechanically, were observed on the inspection plate. This study focused on proving that classical mechanics can explain the double-slit wave pattern.

The irreversible process of ‘wave packet collapse’ in quantum measurement contradicts the reversible characteristics of the Schrödinger equation and the entire quantum mechanics. This contradiction is actually the origin of measurement problems in quantum mechanics. How to resolve this contradiction is related to the understanding of some philosophical concepts. The Copenhagen School embraces the reversible/irreversible contradictions in quantum measurement through the principle of complementarity. Both von Neumann's measurement hypothesis and Everett's many world explanation adhere to the ‘universal position of the Schrödinger equation’, but due to their detachment from the thermodynamic mechanism analysis of quantum measurement processes, they fall into the dilemma of subjectivism or possible state materialization in ontology. Decoherence theory is a natural extension of dissipative structure theory in quantum mechanics, which helps to solve quantum measurement problems by combining the study of classical conversion mechanisms between reversibility and irreversibility in statistical mechanics. Due to the common statistical roots of the time arrow problem in classical mechanics and quantum mechanics, decoherence theory cannot be seen as a measurement theory that fully implements the ‘universal Schrödinger position’. Many contradictions in quantum mechanics may need to be cleverly resolved through various contradictions in classical physics.

Inter-relation between quantum and classical probability models is one of the most fundamental problems of quantum foundations. Nowadays this problem also plays an important role in quantum technologies, in quantum cryptography and the theory of quantum random generators. In this letter, we compare the viewpoint of Richard Feynman that the behavior of quantum particles cannot be described by classical probability theory with the viewpoint that quantum–classical inter-relation is more complicated (cf, in particular, with the tomographic model of quantum mechanics developed in detail by Vladimir Man'ko). As a basic example, we consider the two-slit experiment, which played a crucial role in quantum foundational debates at the beginning of quantum mechanics (QM). In particular, its analysis led Niels Bohr to the formulation of the principle of complementarity. First, we demonstrate that in complete accordance with Feynman's viewpoint, the probabilities for the two-slit experiment have the non-Kolmogorovian structure, since they violate one of basic laws of classical probability theory, the law of total probability (the heart of the Bayesian analysis). However, then we show that these probabilities can be embedded in a natural way into the classical (Kolmogorov, 1933) probability model. To do this, one has to take into account the randomness of selection of different experimental contexts, the joint consideration of which led Feynman to a conclusion about the non-classicality of quantum probability. We compare this embedding of non-Kolmogorovian quantum probabilities into the Kolmogorov model with well-known embeddings of non-Euclidean geometries into Euclidean space (e.g., the Poincaré disk model for the Lobachvesky plane).

The double slit experiment is iconic and widely used in classrooms to demonstrate the fundamental mystery of quantum physics. The puzzling feature is that the probability of an electron arriving at the detector when both slits are open is not the sum of the probabilities when the slits are open separately. The superposition principle of quantum mechanics tells us to add amplitudes rather than probabilities and this results in interference. This experiment defies our classical intuition that the probabilities of exclusive events add. In understanding the emergence of the classical world from the quantum one, there have been suggestions by Feynman, Diosi and Penrose that gravity is responsible for suppressing interference. This idea has been pursued in many different forms ever since, predominantly within Newtonian approaches to gravity. In this paper, we propose and theoretically analyse two ‘gedanken’ or thought experiments which lend strong support to the idea that gravity is responsible for decoherence. The first makes the point that thermal radiation can suppress interference. The second shows that in an accelerating frame, Unruh radiation does the same. Invoking the Einstein equivalence principle to relate acceleration to gravity, we support the view that gravity is responsible for decoherence.

A probabilistic environmentally assisted cracking (PEAC) model was developed to describe the propagation of primary water stress corrosion cracking for Alloy 600 in roll-transition region of steam generator (SG), a severe environmentally assisted cracking problem in pressurized water reactors (PWRs). In the PEAC model, crack growth rate (CGR) and probability of failure (POF) were obtained by adopting a Bayesian inference that decreases the uncertainties of unknown parameters and their distributions in theoretical equations. The CGR is mainly dependent on three factors: probability of detection (POD), initial crack size distribution, and stress distribution. The POD, which is a logistic link was updated with Bayesian inference based on SG inspection data. The crack size distribution, which is relative to initiation time expressed by a Weibull function, was also updated with Bayesian inference using POD. The stress distribution caused by mechanical rolling is considered to be a major contributing factor along the SG tube. It based on finite element analysis is deterministic model unlike POD and initial crack distribution. According to this model, the uncertainty of hyperparameters in the CGR which are parameters of a prior distribution was reduced, and the appropriate level of confidence was achieved by utilizing the available data. Moreover, a benchmark study for the SG tube was performed to evaluate reliability of Alloy 600 SG components in nuclear power plants. The POF was estimated from the developed PEAC model and failure criteria by taking into account the effects of inspection and repair of defective tubes. The results from this study are applied to demonstrate risk reduction in PWRs by adopting risk-informed in-service inspection.

Accurately estimating a sequence of latent variables in state observation models remains a challenging problem, particularly when maintaining coherence among consecutive estimates. While forward filtering and smoothing methods provide coherent marginal distributions, they often fail to maintain coherence in marginal MAP estimates. Existing methods efficiently handle discrete-state or Gaussian models. However, general models remain challenging. Recently, a recursive Bayesian decoder has been discussed, which effectively infers coherent state estimates in a wide range of models, including Gaussian and Gaussian mixture models. In this work, we analyze the theoretical properties and implications of this method, drawing connections to classical inference frameworks. The versatile applicability of mixture models and the prevailing advantage of the recursive Bayesian decoding method are demonstrated using the double-slit experiment. Rather than inferring the state of a quantum particle itself, we utilize interference patterns from the slit experiments to decode the movement of a non-stationary particle detector. Our findings indicate that, by appropriate modeling and inference, the fundamental uncertainty associated with quantum objects can be leveraged to decrease the induced uncertainty of states associated with classical objects. We thoroughly discuss the interpretability of the simulation results from multiple perspectives.

Philosophical questioning about the arrow of time is an active research area, but one with a long and industrious history in both physics and philosophy. This paper begins by distinguishing between a puzzle about the origin of the thermodynamic time asymmetry and questions about whether the thermodynamic time asymmetry can itself explain other temporal asymmetries. It goes on to give a brief description of how the puzzle arises in classical mechanics, followed by an interlude on whether and how quantum mechanics might change the situation. Finally, it takes a closer look at the puzzle in terms of statistical mechanics and one proposed solution.

In the era of smart home technology, early warning systems and emergency services are inevitable. To make smart homes safer, early fire alarm systems can play a significant role. Smart homes usually utilize communication, sensors, actuators, and other technologies to provide a safe and smart environment. This research work introduced a model for the fire alarm system and designed a fire alarm detection (FAD) simulator to produce a synthetic dataset. The designed simulator utilizes a variety of sensors (temperature, gas, and humidity) to simulate fire alarm scenarios based on real-world data. The produced data is investigated and analyzed to classify the possible fire behaviors based on key assumptions taken from real-world scenarios. Different classification models are used to determine an optimal classifier for fire detection. The proposed technique can identify the false alarms based on parameters like temperature, smoke, and gas values of different sensors embedded in a fire alarm detection simulator.

Forest fire has been becoming a conscious theme as it causes huge loss of life and ghastly impact on the ecological environment. Temperature sensor appropriate for large‐area distribution in forest is rising as a subject of considerable speculation to build a fire alarming network. This strategy needs power supplies that can support fire alarming sensors in long term. Herein, a concept of temperature‐arousing battery (TAB) is conceived that has no energy consumption at normal temperaturewhile becoming activated in fire scenario. The TAB is made of a thermoelectric (TE) generator deposited with exothermic and endothermic materials on its hot sink and cold sink, respectively. Learning from bombardier beetles, the exothermic reaction and endothermic reaction can only happen when the thermal‐responsive switches to isolate reactants are triggered in the event of fire occurrence. Even in an isothermal atmosphere, a remarkable temperature difference is formed between two sinks of TE generator, accordingly producing a thermoelectric voltage higher than 5.0 V and a giant power over 1.0 W, which are high enough to power a wireless signal transmitter. In the practical tests, the integrated self‐powered alarming system can transmit an electrical signal in 79 s when the TAB touches a forest fire.

In this paper, we reconsider two long-standing yet unsolved problems: the origin of the universe and the arrow of time. We show that only a closed universe is free from singularities and that the arrow of time is symmetric with respect to the universe’s maximum scale. The Wheeler–DeWitt equation is explicitly solved to obtain local dynamical times. It is shown that the thermodynamic arrow of time coincides with both the dynamical time and the cosmological (expanding universe) time. This correspondence is explicitly demonstrated in two-dimensional spacetime.

Virtual reality (VR) enables the study of visually-guided behavior in situations that are otherwise not amenable to laboratory research. An example is a fire evacuation scenario, in which building occupants have to find their way to safety through smoke and flames, identify safe egress routes, and avoid threats. First, however, it must be determined whether evacuation behavior in VR is comparable to that in a real environment. We are thus initially studying participant responses to a fire alarm in matched virtual and real environments. The present experiment investigates how the decision to evacuate is influenced by visual cues about a neighbor’s behavior. In the Control group, a lone participant is exposed to a fire alarm while performing a bogus task. In the Passive group, a participant performs the same task with a confederate who ignores the fire alarm. In the Active group, the confederate immediately leaves the room when the fire alarm sounds. The gender of the participant is crossed with the gender of the confederate. 75 participants experience the scenario in a real environment (25 per group), and 75 others in a matched virtual environment presented in a wireless head mounted display (HMD), with avatars of the confederates. In the real environment, two-thirds of participants in the Control group evacuated the room. In the Active group, nearly all did so, whereas in the Passive group all but one did. More female than male participants evacuated in the Control group, but there were no other gender effects. Data collection in the virtual environment is in progress, and will be completed by spring. The findings thus far demonstrate a very strong influence of neighbor behavior on a participant’s evacuation decision. The results will provide answers to the much-debated question of whether evacuation behavior is similar in virtual and real environments. Meeting abstract presented at VSS 2015

Fire exclusion in historically frequent-fire forests of the southwestern United States has altered forest structure and increased the probability of high-severity fire. Warmer and drier conditions, coupled with dispersal distance limitations, are impeding tree seedling establishment and survival following high-severity fire. High-severity patches are commonly dominated by non-forest vegetation, a state that can be reinforced by subsequent fire events. We sought to determine the influence of fire probability on post-fire vegetation development in a severely burned landscape in New Mexico, USA. We used LANDIS-II to simulate three fire probability scenarios—historical fire probability, contemporary fire probability, and the mean of the two—with contemporary climate. As fire probability increased, the mean size of the largest fires and the mean landscape fire severity increased. These changes in fire characteristics resulted in decreased total aboveground biomass and photosynthetic capacity on the landscape after 50 years. Additionally, the distribution of individual species biomass shifted, with early successional species, especially those that resprout after fire, increasing as a fraction of total biomass with increasing fire occurrence. Counter to empirical data, our simulations did not show a conifer establishment limitation, suggesting a source of uncertainty that will need to be addressed to improve projections of forest dynamics under future climate. Even without limited conifer regeneration, continued increases in fire frequency are likely to favor resprouting species and result in a loss of forest biomass and ecosystem productivity in this southwestern forest landscape.

Taking Nabokov’sPale Fireas its tutor text, this chapter seeks to demonstrate that narrative functions as a complex or dynamic system. Due to the novel’s nonlinear and multiply configured format, a series of dissipative structures is provoked whereby states near equilibrium, on reaching states far from equilibrium under the weight of multiple causality, putting the system “beyond the threshold of stability” and “at the edge of chaos,” perpetually self-organize. Taking a cue from nonequilibrium thermodynamics, instabilities, it is argued, are inherent to narrative discourse. This calls into question the pertinence of the logic of linearity (“event A causes event B”) as well as the scope of such postulates as the isomorphic relation between sequence and narrative as a whole, a postulate that frames narrative as a closed system following the principle of conservation of energy in classical mechanics. As the poem “Pale Fire” in Nabokov’s novel advances linearly, it is constantly disrupted by the “Commentary” which is related to the poem only tangentially, each text fragmenting the other and self-organizing into new meanings. The effect is to render salient in narrative discourse the complexity science principles (in addition to those mentioned above) of irreversibility (the “arrow of time”) vs. reversibility, sensitivity to initial conditions, negative vs. positive feedback and the symmetry-breaking effects of bifurcation. The manifestation of these principles in Nabokov’s novel raises fundamental questions about the structuring of narrative, but also about the conceptual framework through which narrative at large might be approached.