Magnetization steps in a diluted Heisenberg antiferromagnetic chain: Theory and experiments on TMMC:Cd

A theory for the equilibrium low-temperature magnetization M of a diluted Heisenberg antiferromagnetic chain is presented. The magnetization curve, M versus B, is calculated using the exact contributions of finite chains with 1 to 5 spins, and the "rise and ramp approximation" for longer chains. Some non-equilibrium effects that occur in a rapidly changing B, are also considered. Specific non-equilibrium models based on earlier treatments of the phonon bottleneck, and of spin flips associated with cross relaxation and with level crossings, are discussed. Magnetization data on powders of TMMC diluted with cadmium [i.e., (CH_3)_4NMn_xCd_(1-x)Cl_3, with 0.16<=x<=0.50 were measured at 0.55 K in 18 T superconducting magnets. The field B_1 at the first MST from pairs is used to determine the NN exchange constant, J, which changes from -5.9 K to -6.5 K as x increases from 0.16 to 0.50. The magnetization curves obtained in the superconducting magnets are compared with simulations based on the equilibrium theory. Data for the differential susceptibility, dM/dB, were taken in pulsed magnetic fields (7.4 ms duration) up to 50 T, with the powder samples in a 1.5 K liquid-helium bath. Non-equilibrium effects, which became more severe as x decreased, were observed. The non-equilibrium effects are tentatively interpreted using the "Inadequate Heat Flow Scenario," or to cross-relaxation, and crossings of energy levels, including those of excited states.Comment: 16 pages, 14 figure

Susceptibility Amplitude Ratios Near a Lifshitz Point

The susceptibility amplitude ratio in the neighborhood of a uniaxial Lifshitz point is calculated at one-loop level using field-theoretic and $\epsilon_{L}$-expansion methods. We use the Schwinger parametrization of the propagator in order to split the quadratic and quartic part of the momenta, as well as a new special symmetry point suitable for renormalization purposes. For a cubic lattice (d = 3), we find the result $\frac{C_{+}}{C_{-}} = 3.85$.Comment: 7 pages, late

Magnetization steps in Zn_(1-x)Mn_xO: Four largest exchange constants and single-ion anisotropy

Magnetization steps (MST's) from Mn pairs in several single crystals of Zn_(1-x)Mn_xO (0.0056<=x<=0.030, and in one powder (x=0.029), were observed. The largest two exchange constants, J1/kB=-18.2+/-0.5K and J1'/kB=-24.3+/-0.6K, were obtained from large peaks in the differential susceptibility, dM/dH, measured in pulsed magnetic fields, H, up to 500 kOe. These two largest J's are associated with the two inequivalent classes of nearest neighbors (NN's) in the wurtzite structure. The 29% difference between J1 and J1' is substantially larger than 13% in CdS:Mn, and 15% in CdSe:Mn. The pulsed-field data also indicate that, despite the direct contact between the samples and a superfluid-helium bath, substantial departures from thermal equilibrium occurred during the 7.4 ms pulse. The third- and fourth-largest J's were determined from the magnetization M at 20 mK, measured in dc magnetic fields H up to 90 kOe. Both field orientations H||c and H||[10-10] were studied. (The [10-10] direction is perpendicular to the c-axis, [0001].) By definition, neighbors which are not NN's are distant neighbors (DN's). The largest DN exchange constant (third-largest overall), has the value J/kB=-0.543+/-0.005K, and is associated with the DN at r=c. Because this is not the closest DN, this result implies that the J's do not decrease monotonically with the distance r. The second-largest DN exchange constant (fourth-largest overall), has the value J/kB=-0.080 K. It is associated with one of the two classes of neighbors that have a coordination number z=12, but the evidence is insufficient for a definite unique choice. The dependence of M on the direction of H gives D/kB=-0.039+/-0.008K, in fair agreement with -0.031 K from earlier EPR work.Comment: 12 pages, 10 figures. Submitted to PR

Generating a Multipliciy of Policies for Agent Steering in Crowd Simulation

Pedestrian steering algorithms range from completely procedural to entirely data-driven, but the former grossly generalize across possible human behaviors and suffer computationally, whereas the latter are limited by the burden of ever-increasing data samples. Our approach seeks the balanced middle ground by deriving a collection of machine-learned policies based on the behavior of a procedural steering algorithm through the decomposition of the space of possible steering scenarios into steering contexts. The resulting algorithm scales well in the number of contexts, the use of new data sets to create new policies, and in the number of controlled agents as the policies become a simple evaluation of the rules asserted by the machine-learning process. We also explore the use of synthetic data from an “oracle algorithm” that serves as an as-needed source of samples, which can be stochastically polled for effective coverage. We observe that our approach produces pedestrian steering similar to that of the oracle steering algorithm, but with a significant performance boost. Runtime was reduced from hours under the oracle algorithm with 10 agents to on the order of 10 frames per second (FPS) with 3000 agents. We also analyze the nature of collisions in such a framework with no explicit collision avoidance

On the volunteer’s dilemma I: Continuous-time decision

It is assumed that there is a group of unrelated individuals taken at random from a large population which is exposed to the same time-continuous threat of dying. Accumulated loss of each player increases as the game goes on until at least one participant volunteers to take some extra risk on its own. The risk is taken by a volunteer in order to stop the threat may or may not depend on the time of volunteering. This situation can be modeled as an n-player War of Attrition, which ends when one of the players volunteers. We called this sort of generalization, &quot;The (n-player) volunteer dilemma&quot;. Indeed, a two-player volunteer dilemma is equivalent to the original War of Attrition. It was further assumed that both the risk for the volunteer and the intensity of the risk of waiting are time dependent according to some integrable function, this instead of being constants as assumed in the original War of Attrition model of Maynard Smith. Necessary and sufficient conditions for a strategy to be a Nash strategy are given. This strategy is characterized by a time-intensity of volunteering. In the stationary case the Nash strategy is proven to be ESS

Magnetization Process of Nanoscale Iron Cluster

Low-temperature magnetization process of the nanoscale iron cluster in linearly sweeped fields is investigated by a numerical analysis of time-dependent Schr$\ddot{\rm o}$dinger equation and the quantum master equation. We introduce an effective basis method extracting important states, by which we can obtain the magnetization process effectively. We investigate the structure of the field derivative of the magnetization. We find out that the antisymmetric interaction determined from the lattice structure reproduces well the experimental results of the iron magnets and that this interaction plays an important role in the iron cluster. Deviations from the adiabatic process are also studied. In the fast sweeping case, our calculations indicate that the nonadiabatic transition dominantly occurs at the level crossing for the lowest field. In slow sweeping case, due to the influence of the thermal environment to the spin system, the field derivative of the magnetization shows an asymmetric behavior, the magnetic F$\ddot{\rm o}$hn effect, which explains the substructure of the experimental results in the pulsed field.Comment: 5 pages of text and 2 pages of 6 figures. To appear in J. Phys. Soc. Jp

Pedestrian Anomaly Detection Using Context-Sensitive Crowd Simulation

Detecting anomalies in crowd movement is an area of considerable interest for surveillance and security applications. The question we address is: What constitutes an anomalous steering choice for an individual in the group? Deviation from “normal” behavior may be defined as a subject making a steering decision the observer would not, provided the same circumstances. Since the number of possible spatial and movement configurations is huge and human steering behavior is adaptive in nature, we adopt a context-sensitive approach to assess individuals rather than assume population-wide homogeneity. When presented with spatial trajectories from processed surveillance data, our system creates a shadow simulation. The simulation then establishes the current, local context for each agent and computes a predicted steering behavior against which the person’s actual motion can be statistically compared. We demonstrate the efficacy of our technique with preliminary results using real-world tracking data from the Edinburgh Pedestrian Dataset

A computational interactome and functional annotation for the human proteome

We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function

Do correlations create an energy gap in electronic bilayers? Critical analysis of different approaches

This paper investigates the effect of correlations in electronic bilayers on the longitudinal collective mode structure. We employ the dielectric permeability constructed by means of the classical theory of moments. It is shown that the neglection of damping processes overestimates the role of correlations. We conclude that the correct account of damping processes leads to an absence of an energy gap.Comment: 4 page

Electric field dependence of thermal conductivity of a granular superconductor: Giant field-induced effects predicted

The temperature and electric field dependence of electronic contribution to the thermal conductivity (TC) of a granular superconductor is considered within a 3D model of inductive Josephson junction arrays. In addition to a low-temperature maximum of zero-field TC K(T,0) (controlled by mutual inductance L_0 and normal state resistivity R_n), the model predicts two major effects in applied electric field: (i) decrease of the linear TC, and (ii) giant enhancement of the nonlinear (i.e., grad T-dependent) TC with [K(T,E)-K(T,0)]/K(T,0) reaching 500% for parallel electric fields E=E_T (E_T=S_0|grad T| is an "intrinsic" thermoelectric field). A possiblity of experimental observation of the predicted effects in granular superconductors is discussed.Comment: 5 LaTeX pages (jetpl.sty included), 2 EPS figures. To be published in JETP Letter