Journal of Physics Communications

Recent proposals in quantum gravity have suggested that unknown systems can mediate entanglement between two known quantum systems, if the mediator itself is non-classical. This approach may be applicable to the brain, where speculations about quantum operations in consciousness and cognition have a long history. Proton spins of bulk water, which most likely interfere with any brain function, can act as the known quantum systems. If an unknown mediator exists, then NMR methods based on multiple quantum coherence (MQC) can act as an entanglement witness. However, there are doubts that today's NMR signals can contain quantum correlations in general, and specifically in the brain environment. Here, we used a witness protocol based on zero quantum coherence (ZQC) where we minimized the classical signals to circumvent the NMR detection limits for quantum correlation. For short repetitive periods, we found evoked signals in most parts of the brain, whereby the temporal appearance resembled heartbeat-evoked potentials (HEPs). We found that those signals had no correlates with any classical NMR contrast. Similar to HEPs, the evoked signal depended on conscious awareness. Consciousness-related or electrophysiological signals are unknown in NMR. Remarkably, these signals only appeared if the local properties of the magnetization were reduced. Our findings suggest that we may have witnessed entanglement mediated by consciousness-related brain functions. Those brain functions must then operate non-classically, which would mean that consciousness is non-classical.

Advances in optimizing thermoelectric material efficiency have seen parallel activities in theoretical and computational studies. In the current work, we calculate the exact Fermi–Dirac integrals to enable the generalization of the Wiedemann–Franz law (WF) in order to enhance the dimensionless thermoelectric figure of merit ${ZT}={\alpha }^{2}\sigma /\kappa$. This is done by optimizing the Seebeck coefficient α, the electrical conductivity σ, and the thermal conductivity κ in terms of the Lambert W, and the generalized Lambert W functions (offset log). In the calculation of the thermal conductivity κ, we include both electronic and phononic contributions. The solutions provide insight into the relevant parameter space including the physical significance of complex solutions and their dependance on the scattering parameter r and the reduced chemical potential μ*.

We summarise different aspects of the measurement problem in quantum mechanics. We argue that it is a real problem which requires a solution, and identify the properties a theory needs to solve the problem. We show that no current interpretation of quantum mechanics solves the problem, and that, being interpretations rather than extensions of quantum mechanics, they cannot solve it. Finally, we speculate what a solution of the measurement problem might be good for.

In this article, we explore the effect of two different infrared (IR) laser wavelengths on the optical properties of trapped nano-diamonds containing high-density ensembles of nitrogen vacancy (NV) centers. We investigate 975 nm and 1064nm wavelengths for trapping lasers and find that NV photoluminescence quenching is more prominent for 1064nm illumination than for 975 nm illumination when simultaneously excited with a 532 nm laser. In order to understand the underlying mechanism, we develop a rate-equation-based model that takes into account various transition probabilities. The model suggests that the findings cannot be explained only by imposing modification of the NV charge-state ratio under varied illumination wavelengths, and, thus, we speculate that the effective ionization and recombination rates associated with NV charge states for the studied samples are highly wavelength-dependent in the probed regime. Importantly, the results demonstrate that 975 nm laser is desirable for optical trapping of NV-diamonds, especially for NV-based sensing applications.

General relationship between mean Boltzmann entropy and Gibbs entropy is established. It is found that their difference is equal to fluctuation entropy, which is a Gibbs-like entropy of macroscopic quantities. The ratio of the fluctuation entropy and mean Boltzmann, or Gibbs entropy vanishes in the thermodynamic limit for a system of distinguishable and independent particles. It is argued that large fluctuation entropy clearly indicates the limit where standard statistical approach should be modified, or extended using other methods like renormalization group.

Physics-Informed Neural Networks (PINNs) have been a promising machine learning model for evaluating various physical problems. Despite their success in solving many types of partial differential equations (PDEs), some problems have been found to be difficult to learn, implying that the baseline PINNs is biased towards learning the governing PDEs while relatively neglecting given initial or boundary conditions. In this work, we propose Dynamically Normalized Physics-Informed Neural Networks (DN-PINNs), a method to train PINNs while evenly distributing multiple back-propagated gradient components. DN-PINNs determine the relative weights assigned to initial or boundary condition losses based on gradient norms, and the weights are updated dynamically during training. Through several numerical experiments, we demonstrate that DN-PINNs effectively avoids the imbalance in multiple gradients and improves the inference accuracy while keeping the additional computational cost within a reasonable range. Furthermore, we compare DN-PINNs with other PINNs variants and empirically show that DN-PINNs is competitive with or outperforms them. In addition, since DN-PINN uses exponential decay to update the relative weight, the weights obtained are biased toward the initial values. We study this initialization bias and show that a simple bias correction technique can alleviate this problem.

Generating and detecting genuine multipartite entanglement (GME) of sizeable quantum states prepared on physical devices is an important benchmark for highlighting the progress of near-term quantum computers. A common approach to certify GME is to prepare a Greenberger-Horne-Zeilinger (GHZ) state and measure a GHZ fidelity of at least 0.5. We measure the fidelities using multiple quantum coherences of GHZ states on 11 to 27 qubits prepared on the IBM Quantum ibmq_montreal device. Combinations of quantum readout error mitigation (QREM) and parity verification error detection are applied to the states. A fidelity of 0.546 ± 0.017 was recorded for a 27-qubit GHZ state when QREM was used, demonstrating GME across the full device with a confidence level of 98.6%. We benchmarked the effect of parity verification on GHZ fidelity for two GHZ state preparation embeddings on the heavy-hexagon architecture. The results show that the effect of parity verification, while relatively modest, led to a detectable improvement of GHZ fidelity.

This research implements the idea of automation using Internet of Things (IoT) in a greenhouse environment. The development is focuses on deployment of agicultural greenhouses into small-scale level transforming it into a smart greenhouse. They are to help in monitoring the greenhouse environment conditions, water irrigation management, image collection using installed cameras as well as predicting diseases in the plants on collected leaf datasets. This research focus on development for the purpose of validating a proposed system design and architecture for a suitable IoT based monitoring for environment conditions, managing water irrigation system and a effective method for detecting leaf diseases on the plants inside a greenhouse environment.

The bulk-boundary correspondence is crucial to topological insulators. It associates the existence of boundary states (with zero energy and possessing chiral or helical properties) with the topological numbers defined in bulk. In recent years, topology has been extended to non-hermitian systems, opening a new research area called non-hermitian topological insulator. In this paper, however, we will illustrate that the bulk-boundary correspondence does not hold in these new models. This is because a prerequisite condition: 'the boundaries cannot alter most of the bulk states, so as to the topological numbers defined on them' does not hold any longer. This cuts out the correspondence between the topological numbers and the boundary states. We will illustrate that, as approaching the open boundary condition by eliminating the strength of the hopping between the two ends of a chain, a new series of exceptional points must be passed through and the topological structure of the spectrum in the complex plane has been changed. This makes the spectrum topology different for the chains with and without boundaries. We also discuss that such exotic behavior does not emerge when the open boundary is replaced by a domain-wall. So the index theorem can be applied to the systems with domain-walls but cannot be further used to those with open boundaries.

Modified effective range theory is applied as a tool to determine bound and virtual state energies in low-energy positron elastic scattering by atoms and molecules. This is achieved by the S-matrix continuation into the complex momentum plane, allowing to identify poles related to shallow energy states. The influence of the long-range polarization potential (∼r⁻⁴) on the bound and virtual-state pole positions is analyzed for noble gases and nonpolar molecules such as H₂, N₂, and CH₄. The quantitative relations between the S-matrix poles and the s-wave scattering length accounting for dipole polarization are introduced.

In this contribution a discrete variable representation (DVR) approach to calculate Franck-Condon factors (FCFs) is presented. The method is illustrated using a harmonic oscillator basis. The advantage of this approach is that it is possible to calculate FCFs associated with general potentials based on the knowledge of the harmonic oscillator theory. First the coordinate and momentum representations are introduced. Based on this concept, the DVR is proposed, which allows the Franck-Condon factors to be calculated in a simple form. This method takes advantage of the momentum as generator of translations to include the displacement of the potentials. The calculation of the FCFs is exemplified for transitions involving the ground state ${X}^{1}{{\rm{\Sigma }}}_{g}^{+}$ and the excited state a¹Π_g of the diatomic molecule ¹⁴N₂ both modelled with Morse potentials.

In this article, we explore the effect of two different infrared (IR) laser wavelengths on the optical properties of trapped nano-diamonds containing high-density ensembles of nitrogen vacancy (NV) centers. We investigate 975 nm and 1064nm wavelengths for trapping lasers and find that NV photoluminescence quenching is more prominent for 1064nm illumination than for 975 nm illumination when simultaneously excited with a 532 nm laser. In order to understand the underlying mechanism, we develop a rate-equation-based model that takes into account various transition probabilities. The model suggests that the findings cannot be explained only by imposing modification of the NV charge-state ratio under varied illumination wavelengths, and, thus, we speculate that the effective ionization and recombination rates associated with NV charge states for the studied samples are highly wavelength-dependent in the probed regime. Importantly, the results demonstrate that 975 nm laser is desirable for optical trapping of NV-diamonds, especially for NV-based sensing applications.

Modified effective range theory is applied as a tool to determine bound and virtual state energies in low-energy positron elastic scattering by atoms and molecules. This is achieved by the S-matrix continuation into the complex momentum plane, allowing to identify poles related to shallow energy states. The influence of the long-range polarization potential (∼r⁻⁴) on the bound and virtual-state pole positions is analyzed for noble gases and nonpolar molecules such as H₂, N₂, and CH₄. The quantitative relations between the S-matrix poles and the s-wave scattering length accounting for dipole polarization are introduced.

A non-conserving zero-range process with extensive creation, annihilation and hopping rates is subjected to local resetting. The model is formulated on a large, fully-connected network of states. The states are equipped with a (bounded) fitness level: particles are added to each state at a rate proportional to the fitness level of the state. Moreover, particles are annihilated at a constant rate, and hop at a fixed rate to a uniformly-drawn state in the network. This model has been interpreted in terms of population dynamics: the fitness is the reproductive fitness in a haploid population, and the hopping process models mutation. It has also been interpreted as a model of network growth with a fixed set of nodes (in which particles occupying a state are interpreted as links pointing to this state). In the absence of resetting, the model is known to reach a steady state, which in a certain limit may exhibit a condensate at maximum fitness. If the model is subjected to global resetting by annihilating all particles at Poisson-distributed times, there is no condensation in the steady state. If the system is subjected to local resetting, the occupation numbers of each state are reset to zero at independent random times. These times are distributed according to a Poisson process whose rate (the resetting rate) depends on the fitness. We derive the evolution equation satisfied by the probability law of the occupation numbers. We calculate the average occupation numbers in the steady state. The existence of a condensate is found to depend on the local behavior of the resetting rate at maximum fitness: if the resetting rate vanishes at least linearly at high fitness, a condensate appears at maximum fitness in the limit where the sum of the annihilation and hopping rates is equal to the maximum fitness.

From the viewpoint of the Bose–Einstein condensation (BEC) of the fermion system, the maximum geminal of the second-order reduced density matrix of the superconducting state exactly corresponds to the Cooper pair. In this paper the entanglement entropy (EE) for the maximum geminal of the BCS ground state is evaluated. The EE behaves logarithmically with respect to the number of the maximum geminal. Furthermore, the disappearance point of superconductivity is defined on the basis of the fermion BEC. In the superconducting ground state, almost all electrons in the energy width of the gap parameter near the Fermi level are condensed as a maximum geminal. They suddenly change to normal electrons with a finite gap of the EE at the disappearance point like a first-order phase transition.

This work provides a current, critical view of the application of MAss-selective Neutron SpEctroscopy (MANSE) to nanocomposite materials. MANSE is a unique technique made possible owing to the existence of the pulsed neutron sources. At present, the only operating MANSE spectrometer in the world, VESUVIO, is located at the ISIS Neutron and Muon Source in the UK. We start by providing a brief description of the neutron Compton scattering, the anatomy of a mass-selective neutron spectrometer, and the experimental data treatment. We continue by briefly outlining the main quantum mechanical concepts, models and approximations relevant both to the ab initio prediction and experimental measurement of main MANSE observables. Next, we present several recent exemplars chosen to highlight the use of MANSE in the field of nanocomposites. Our examples include, in chronological order, encapsulated nanoparticles in amorphous silica gel, bioactive glass-ionomer cement, Cu-Ti-C composites, and sodium carboxymethyl starch-based binders in the presence of a mineral matrix. We close by providing our view of the ongoing and future challenges and opportunities in the mass-selective neutron investigation of NQEs in nanocomposite materials.

Gravitoelectromagnetic analogies are somewhat ubiquitous in General Relativity, and they are often used to explain peculiar effects of Einstein's theory of gravity in terms of familiar results from classical electromagnetism. Perhaps, the best known of these analogy pertains to the similarity between the equations of electromagnetism and those of the linearized theory of General Relativity. But the analogy is somewhat deeper and ultimately rooted in the splitting of spacetime, which is preliminary to the definition of the measurement process in General Relativity. In this paper we review the various approaches that lead to the introduction of a magnetic-like part of the gravitational interaction, briefly called gravitomagnetic and, then, we provide a survey of the recent developments both from the theoretical and experimental viewpoints.

Quantum optics based on highly excited atoms, also known as Rydberg atoms, has cemented itself as a powerful platform for the manipulation of light at the few-photon level. The Rydberg blockade, resulting from the strong interaction between individual Rydberg atoms, can turn a large ensemble of atoms into a system which collectively resembles a single two-level emitter, a so-called Rydberg superatom. The coupling of this artificial emitter to a driving photonic mode is collectively enhanced by Rydberg interactions, enabling strong coherent coupling at the few-photon level in free-space. The exquisite level of control achievable through this has already demonstrated its utility in applications of quantum computing and information processing. Here, we review the derivation of the collective coupling between a Rydberg superatom and a single light mode and discuss the similarity of this free-space setup to waveguide quantum electrodynamics systems of quantum emitters coupled to photonic waveguides. We also briefly review applications of Rydberg superatoms to quantum optics such as single-photon generation and single-photon subtraction.

Radiation damage to DNA plays a central role in radiation therapy to cure cancer. The physico-chemical and biological processes involved encompass huge time and spatial scales. To obtain a comprehensive understanding on the nano and the macro scale is a very challenging tasks for experimental techniques alone. Therefore particle-scattering simulations are often applied to complement measurements and aide their interpretation, to help in the planning of experiments, to predict their outcome and to test damage models. In the last years, powerful multipurpose particle-scattering framework based on the Monte-Carlo simulation (MCS) method, such as Geant4 and Geant4-DNA, were extended by user friendly interfaces such as TOPAS and TOPAS-nBio. This shifts their applicability from the realm of dedicated specialists to a broader range of scientists. In the present review we aim to give an overview over MCS based approaches to understand radiation interaction on a broad scale, ranging from cancerous tissue, cells and their organelles including the nucleus, mitochondria and membranes, over radiosensitizer such as metallic nanoparticles, and water with additional radical scavenger, down to isolated biomolecules in the form of DNA, RNA, proteins and DNA-protein complexes. Hereby the degradation of biomolecules by direct damage from inelastic scattering processes during the physical stage, and the indirect damage caused by radicals during the chemical stage as well as some parts of the early biological response is covered. Due to their high abundance the action of hydroxyl radicals (^•OH) and secondary low energy electrons (LEE) as well as prehydrated electrons are covered in additional detail. Applications in the prediction of DNA damage, DNA repair processes, cell survival and apoptosis, influence of radiosensitizer on the dose distribution within cells and their organelles, the study of linear energy transfer (LET), the relative biological effectiveness (RBE), ion beam cancer therapy, microbeam radiation therapy (MRT), the FLASH effect, and the radiation induced bystander effect are reviewed.

Airborne particulate matter pollution is a global health problem that affects people from all demographics. To reduce the impact of such pollution and enable mitigation and policy planning, quantifying individuals' exposure to pollution is necessary. To achieve this, effective monitoring of airborne particulates is required, through monitoring of pollution hotspots and sources. Furthermore, since pollution is a global problem, which varies from urban areas to city centres, industrial facilities to inside homes, a variety of sensors might be needed. Current sensing techniques either lack species resolution on a world scale, lack real-time capabilities, or are too expensive or too large for mass deployment. However, recent work using deep learning techniques has expanded the capability of current sensors and allowed the development of new techniques that have the potential for worldwide, species specific, real-time monitoring. Here, it is proposed how deep learning can enable sensor design for the development of small, low-cost sensors for real-time monitoring of particulate matter pollution, whilst unlocking the capability for predicting future particulate events and health inference from particulates, for both individuals and the environment in general.