We study the magnetic properties of an epitaxial growth bilayer composed of ferromagnetic La0.7Sr0.3MnO3 (LSMO) and paramagnetic LaNiO3 (LNO) on SrTiO3 (STO) substrates. We find that the stack order of the bilayer heterostructure plays a key role in the interfacial coupling strength, and the coupling at the LSMO(top)/LNO(bottom) interface is much stronger than that at the LNO(top)/LSMO(bottom)....

We study the low-temperature phase of the three-dimensional ±J Ising spin glass in MigdalKadanoff approximation. At zero temperature, T = 0, the properties of the spin glass result from the ground-state degeneracy and can be elucidated using scaling arguments based on entropy. The approach to the asymptotic scaling regime is very slow, and the correct exponents are only visible beyond system si...

The antiferromagnetic Ising model in small-world networks generated from two-dimensional regular lattices has been studied. The disorder introduced by long-range connections causes frustration, which gives rise to a spin-glass phase at low temperature. Monte Carlo simulations have been carried out to study the paramagnetic to spin-glass transition, as a function of the rewiring probability p , ...

We describe an efficient computational algorithm for evaluating the ground state energy of the classical Ising Hamiltonian with linear terms on an arbitrary planar graph. The running time of the algorithm grows linearly with the number of spins and exponentially with 1/2, where 2 is the worst-case relative error. This result contrasts the well known fact that exact computation of the ground sta...

We study the off equilibrium dynamics of a mean field disordered systems which can be interpreted both as a long range interaction spin glass and as a particle in a random potential. The statics of this problem is well known and exhibits a low temperature spin glass phase with continuous replica symmetry breaking. We study the equations of off equilibrium dynamics with analytical and numerical ...

Using tempered Monte Carlo simulations, we study the the spin-glass phase of dense packings of Ising dipoles pointing along random axes. We consider systems of dipoles (i) placed on the sites of a simple cubic lattice with lattice constant d, and (ii) placed at the center of random close packed spheres of diameter d that occupy 64% of the volume. For both cases, we find a spin-glass phase below...

We address the problem of chaotic temperature dependence in disordered glassy systems at equilibrium by following states of a random-energy random-entropy model in temperature; of particular interest are the crossings of the free-energies of these states. We find that this model exhibits strong, weak or no temperature chaos depending on the value of an exponent. This allows us to write a genera...

We show that, above the critical temperature, if the dimension D of a given Ising spin glass model is sufficiently high, its free energy can be effectively expressed through the free energy of a related Ising model. When, in a large sense, D = ∞, in the paramagnetic phase and on its boundary the mapping is exact. In this limit the method provides a general and simple rule to obtain exactly the ...

We compute exactly the distribution of the occupation time in a discrete non-Markovian toy sequence that appears in various physical contexts such as the diffusion processes and Ising spin glass chains. The non-Markovian property makes the results nontrivial even for this toy sequence. The distribution is shown to have non-Gaussian tails characterized by a nontrivial large deviation function th...

We present a new approximate learning algorithm for Boltzmann Machines, using a systematic expansion of the Gibbs free energy to second order in the weights. The linear response correction to the correlations is given by the Hessian of the Gibbs free energy. The computational complexity of the algorithm is cubic in the number of neurons. We compare the performance of the exact BM learning algor...