Starting from Polchinski’s thought experiment on how to distinguish between pure and thermal states, we construct a specific system to study the interaction between qubit and cavity quantum field ...theory (QFT) in order to provide a more operational point of view. Without imposing any restrictions on the initial states of qubit and cavity QFT, we compute the evolution of the system order by order by the perturbation method. We choose Landauer’s principle, an important bound in quantum computation and quantum measurement, as the basis for the determination of the thermal state. By backtracking the initial state form, we obtain the conditions that must be satisfied by the cavity QFT: the expectation value of the annihilation operator should be zero, and the expectation value of the particle number operator should satisfy the Bose–Einstein distribution. We also discuss the difference between the thermal state and a possible alternative to the thermal state: the canonical thermal pure quantum (CTPQ) state.
A
bstract
We study the decoherence and thermalization of an Unruh-DeWitt detector linearly coupled to the free massless scalar field in flat spacetime with arbitrary dimensions
d
≥ 2. The initial ...state of the detector is chosen to be a pure state consisting of a linear superposition of ground and excited states, and we calculate the time evolution of reduced density matrix of the detector. Using perturbation method, we analytically derive the transition rate of the detector (the rate of change of the diagonal elements in the density matrix) and the decoherence rate (the rate of change of the off-diagonal elements in the density matrix). We find that the results are not the same in odd and even dimensional spacetimes, but the unitarity of the qubit is preserved in both cases. The real part of the decoherence rate is related to the transition rate, while the imaginary part may contain different forms of divergence terms in different dimensions due to the temporal order product operator and the singularities of the Wightman function for quantum field theory. We derive the recurrence formula to obtain the divergence terms in each dimension and analyze the renormalization problem.
In this paper, we study and predict flow observables in 2.76 and 5.02 A TeV Pb + Pb collisions, using the iEBE-VISHNU hybrid model with TRENTo and AMPT initial conditions and with different forms of ...the QGP transport coefficients. With properly chosen and tuned parameter sets, our model calculations can nicely describe various flow observables in 2.76 A TeV Pb + Pb collisions, as well as the measured flow harmonics of all charged hadrons in 5.02 A TeV Pb + Pb collisions. We also predict other flow observables, including
v
n
(
p
T
)
of identified particles, event-by-event
v
n
distributions, event-plane correlations, (normalized) symmetric cumulants, non-linear response coefficients and
p
T
-dependent factorization ratios, in 5.02 A TeV Pb + Pb collisions. We find many of these observables to remain approximately the same values as the ones in 2.76 A TeV Pb + Pb collisions. Our theoretical studies and predictions could shed light to the experimental investigations in the near future.
This paper presents a novel approximation-based event-triggered control of multi-input multi-output uncertain nonlinear continuous-time systems in affine form. The controller is approximated using a ...linearly parameterized neural network (NN) in the context of event-based sampling. After revisiting the NN approximation property in the context of event-based sampling, an event-triggered condition is proposed using the Lyapunov technique to reduce the network resource utilization and to generate the required number of events for the NN approximation. In addition, a novel weight update law for aperiodic tuning of the NN weights at triggered instants is proposed to relax the knowledge of complete system dynamics and to reduce the computation when compared with the traditional NN-based control. Nonetheless, a nonzero positive lower bound for the inter-event times is guaranteed to avoid the accumulation of events or Zeno behavior. For analyzing the stability, the event-triggered system is modeled as a nonlinear impulsive dynamical system and the Lyapunov technique is used to show local ultimate boundedness of all signals. Furthermore, in order to overcome the unnecessary triggered events when the system states are inside the ultimate bound, a dead-zone operator is used to reset the event-trigger errors to zero. Finally, the analytical design is substantiated with numerical results.
We shed some light on the field theory interpretation of C-metric by investigating the minimal surfaces which are homologous to the given boundary regions. The accelerating black holes change the ...asymptotic structure of the space–time. We focus on the geometry features of the minimal surface and study how deep it reaches into the bulk. The regularized area of the minimal surface is not well defined and we introduce a new quantity D(m,θ0), defined as the minimal surface divided by the area of the given boundary region, to study the system.
E-learners face a large amount of fragmented learning content during e-learning. How to extract and organize this learning content is the key to achieving the established learning target, especially ...for non-experts. Reasonably arranging the order of the learning objects to generate a well-defined learning path can help the e-learner complete the learning target efficiently and systematically. Currently, knowledge-graph-based learning path recommendation algorithms are attracting the attention of researchers in this field. However, these methods only connect learning objects using single relationships, which cannot generate diverse learning paths to satisfy different learning needs in practice. To overcome this challenge, this paper proposes a learning path recommendation model based on a multidimensional knowledge graph framework. The main contributions of this paper are as follows. Firstly, we have designed a multidimensional knowledge graph framework that separately stores learning objects organized in several classes. Then, we have proposed six main semantic relationships between learning objects in the knowledge graph. Secondly, a learning path recommendation model is designed for satisfying different learning needs based on the multidimensional knowledge graph framework, which can generate and recommend customized learning paths according to the e-learner’s target learning object. The experiment results indicate that the proposed model can generate and recommend qualified personalized learning paths to improve the learning experiences of e-learners.
A sufficiently large supercurrent can close the energy gap in a superconductor and create gapless quasiparticles through the Doppler shift of quasiparticle energy caused by finite Cooper pair ...momentum. In this gapless superconducting state, zero-energy quasiparticles reside on a segment of the normal-state Fermi surface, whereas the remaining Fermi surface is still gapped. We use quasiparticle interference to image the field-controlled Fermi surface of bismuth telluride (Bi
Te
) thin films under proximity effect from the superconductor niobium diselenide (NbSe
). A small applied in-plane magnetic field induces a screening supercurrent, which leads to finite-momentum pairing on the topological surface states of Bi
Te
. We identify distinct interference patterns that indicate a gapless superconducting state with a segmented Fermi surface. Our results reveal the strong impact of finite Cooper pair momentum on the quasiparticle spectrum.
A new class of 2D transition metal carbides, carbonitrides and nitrides, termed MXenes, has emerged as a new candidate for many applications in electronics, optoelectronics, and energy storage. Since ...their first discovery in 2011, MXenes have gathered increasingly more interest owing to their unique physical, chemical, and mechanical properties that can be tuned by different surface terminations and transition metals. In particular, the intriguing optical and electrical properties, including transparency, saturable absorption, and high conductivity, grant MXenes various roles in photodetectors, such as transparent electrodes, Schottky contacts, photoabsorbers, and plasmonic materials. Given the solution‐processability, MXenes also hold great potential for large‐scale synthesis, and thus are favored for a number of electronic and photonic device applications. In this review, recent advances in photodetectors based on 2D MXenes are summarized. Despite the fact that such applications have only recently been explored compared with other 2D materials, MXenes have shown promise in low‐cost and high‐performance photodetection.
Since their first discovery in 2011, MXenes have gained ever increasing interest. Despite their intriguing optical and electrical properties for optoelectronics, 2D MXenes have been thus far marginally explored for photodetectors. Nonetheless, the progress over the past few years cannot be ignored. In this review, the recent development of MXene photodetectors is summarized, including simple photoconductors, self‐driven photodetectors, and plasmon‐enhanced photodetectors.
This paper presents an event-triggered near optimal control of uncertain nonlinear discrete-time systems. Event-driven neurodynamic programming (NDP) is utilized to design the control policy. A ...neural network (NN)-based identifier, with event-based state and input vectors, is utilized to learn the system dynamics. An actor-critic framework is used to learn the cost function and the optimal control input. The NN weights of the identifier, the critic, and the actor NNs are tuned aperiodically once every triggered instant. An adaptive event-trigger condition to decide the trigger instants is derived. Thus, a suitable number of events are generated to ensure a desired accuracy of approximation. A near optimal performance is achieved without using value and/or policy iterations. A detailed analysis of nontrivial inter-event times with an explicit formula to show the reduction in computation is also derived. The Lyapunov technique is used in conjunction with the event-trigger condition to guarantee the ultimate boundedness of the closed-loop system. The simulation results are included to verify the performance of the controller. The net result is the development of event-driven NDP.
Transparency of textbook activities, i.e., the degree of easiness for teachers to process and comprehend them, needs to be researched in terms of both materials
design
and materials
use
. This ...article reports on a study that investigates the impact of teachers’ professional experience and transparency of textbook activities (due to materials design) on teachers’ actual perception of the transparency of materials. The study adopted a mixed-methods design and collected quantitative data via a five-point scale survey from 115 secondary school teachers as well as interview data from 15 informants. Data analysis reveals that both teachers’ professional experience and transparency of textbook activities affect the degree of easiness teachers perceived as they understand and interpret the activities for pedagogical purposes. However, discrepancy exists between transparency in materials design and transparency in teachers’ perception. Lack of pedagogical knowledge about the relationship between teaching objectives, steps, and assessment and strong existing cognitive schemata developed from the stereotype of processing a familar set of teaching materials might hamper teachers’ perception of transparency.
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