Bridging physical intuition and hardware efficiency for correlated electronic states: the local unitary cluster Jastrow ansatz for electronic structure.

A prominent goal in quantum chemistry is to solve the molecular electronic structure problem for ground state energy with high accuracy. While classical quantum chemistry is a relatively mature field, the accurate and scalable prediction of strongly correlated states found, , in bond breaking and polynuclear transition metal compounds remains an open problem. Within the context of a variational quantum eigensolver, we propose a new family of ansatzes which provides a more physically appropriate description of strongly correlated electrons than a unitary coupled cluster with single and double excitations (qUCCSD), with vastly reduced quantum resource requirements.

Electrodeposition as an Alternative Approach for Monolithic Integration of InSb on Silicon.

High-performance electronics would greatly benefit from a versatile III-V integration process on silicon. Unfortunately, integration using hetero epitaxy is hampered by polarity, lattice, and thermal expansion mismatch. This work proposes an alternative concept of III-V integration combining advantages of pulse electrodeposition, template-assisted selective epitaxy, and recrystallization from a melt.

Connexin36 localization along axon initial segments in the mammalian CNS.

Electrical synapses formed by gap junctions occur at a variety of neuronal subcellular sites in the mammalian central nervous system (CNS), including at somatic, dendritic and axon terminal compartments. Numerous electrophysiological studies using mice and rats, as well as computer modelling approaches, have predicted the additional occurrence of electrical synapses between axons near their emergence from neuronal somata. Here, we used immunofluorescence methods to search for localization of the neuronal gap junction-forming protein connexin36 (Cx36) along axon initial segments (AISs) labelled for the AIS marker ankyrinG.

Closed-Loop Brain Model of Neocortical Information-Based Exchange.

Here we describe an "information-based exchange" model of brain function that ascribes to neocortex, basal ganglia, and thalamus distinct network functions. The model allows us to analyze whole brain system set point measures, such as the rate and heterogeneity of transitions in striatum and neocortex, in the context of neuromodulation and other perturbations. Our closed-loop model is grounded in neuroanatomical observations, proposing a novel "Grand Loop" through neocortex, and invokes different forms of plasticity at specific tissue interfaces and their principle cell synapses to achieve these transitions.

Shortest Loops are Pacemakers in Random Networks of Electrically Coupled Axons.

High-frequency oscillations (HFOs) are an important part of brain activity in health and disease. However, their origins remain obscure and controversial. One possible mechanism depends on the presence of sparsely distributed gap junctions that electrically couple the axons of principal cells.

An Ultrascalable Solution to Large-scale Neural Tissue Simulation.

Neural tissue simulation extends requirements and constraints of previous neuronal and neural circuit simulation methods, creating a tissue coordinate system. We have developed a novel tissue volume decomposition, and a hybrid branched cable equation solver. The decomposition divides the simulation into regular tissue blocks and distributes them on a parallel multithreaded machine.

A theory of loop formation and elimination by spike timing-dependent plasticity.

We show that the local spike timing-dependent plasticity (STDP) rule has the effect of regulating the trans-synaptic weights of loops of any length within a simulated network of neurons. We show that depending on STDP's polarity, functional loops are formed or eliminated in networks driven to normal spiking conditions by random, partially correlated inputs, where functional loops comprise synaptic weights that exceed a positive threshold. We further prove that STDP is a form of loop-regulating plasticity for the case of a linear network driven by noise.

Optimization of Applications with Non-blocking Neighborhood Collectives via Multisends on the Blue Gene/P Supercomputer.

We explore the multisend interface as a data mover interface to optimize applications with neighborhood collective communication operations. One of the limitations of the current MPI 2.1 standard is that the vector collective calls require counts and displacements (zero and nonzero bytes) to be specified for all the processors in the communicator.