arXiv subjects

John Robert Burger

Publications and source records attributed to John Robert Burger.

15 recordsLinked to original sources

arXiv2016

A Theory of Consciousness Founded on Neurons That Behave Like Qubits

This paper presents a hypothesis that consciousness is a natural result of neurons that become connected recursively, and work synchronously between short and long term memories. Such neurons demonstrate qubit-like properties, each supporting a probabilistic combination of true and false at a given phase. Advantages of qubits include probabilistic modifications of cues for searching associations in long term memory, and controlled toggling for parallel, reversible computations to prioritize multiple recalls and to facilitate mathematical abilities.

q-bio.NC↗

arXiv2015

An New Type Of Artificial Brain Using Controlled Neurons

Plans for a new type of artificial brain are possible because of realistic neurons in logically structured arrays of controlled toggles, one toggle per neuron. Controlled toggles can be made to compute, in parallel, parameters of critical importance for each of several complex images recalled from associative long term memory. Controlled toggles are shown below to amount to a new type of neural network that supports autonomous behavior and action.

cs.ET↗

arXiv2012

Qubit-wannabe Neural Networks

Recurrent neurons, or "simulated" qubits, can store simultaneous true and false with probabilistic behaviors usually reserved for the qubits of quantum physics. Although possible to construct artificially, simulated qubits are intended to explain biological mysteries. It is shown below that they can simulate certain quantum computations and, although less potent than the qubits of quantum physics, they nevertheless are shown to significantly exceed the capabilities of classical deterministic circuits.

q-bio.NC↗

arXiv2011

Note on Needle in a Haystack

Introduced below is a quantum database method, not only for retrieval but also for creation. It uses a particular structure of true's and false's in a state vector of n qubits, permitting up to 2**2**n words, vastly more than for classical bits. Several copies are produced so that later they can be destructively observed and a word determined with high probability. Grover's algorithm is proposed below to read out, nondestructively the unknown contents of a given stored state vector using only one state vector.

cs.ET↗

arXiv2011

Novel Identification of Symmetric and Anti-Symmetric Quantum Functions

Procedures are given below to construct symmetric and anti-symmetric quantum functions. If hidden in an oracle, such functions can be identified exactly, without iterative interrogation. This is another example of quantum search. The resulting positive (or negative) functions also serve to uniquely reorganize a superposition of states to give a basis state for testing purposes.

quant-ph↗

arXiv2010

Artificial Brain Based on Credible Neural Circuits in a Human Brain

Neurons are individually translated into simple gates to plan a brain based on human psychology and intelligence. State machines, assumed previously learned in subconscious associative memory are shown to enable equation solving and rudimentary thinking using nanoprocessing within short term memory.

cs.AI↗

arXiv2010

XOR at a Single Vertex -- Artificial Dendrites

New to neuroscience with implications for AI, the exclusive OR, or any other Boolean gate may be biologically accomplished within a single region where active dendrites merge. This is demonstrated below using dynamic circuit analysis. Medical knowledge aside, this observation points to the possibility of specially coated conductors to accomplish artificial dendrites.

cs.NE↗

arXiv2010

The Electron Capture Hypothesis - A Challenge to Neuroscientists

Lower speed impinging ions (with hydration shells) cannot transverse ion channels once internal charge goes positive. Yet neural pulse waveforms fail to show the expected risetime distortion beginning at zero voltage. Observed waveforms cannot be explained unless electron capture is considered.

q-bio.NC↗

arXiv2010

Artificial Learning in Artificial Memories

Memory refinements are designed below to detect those sequences of actions that have been repeated a given number n. Subsequently such sequences are permitted to run without CPU involvement. This mimics human learning. Actions are rehearsed and once learned, they are performed automatically without conscious involvement.

cs.AI↗

arXiv2008

Explaining the Logical Nature of Electrical Solitons in Neural Circuits

Neurons are modeled electrically based on ferroelectric membranes thin enough to permit charge transfer, conjectured to be the tunneling result of thermally energetic ions and random electrons. These membranes can be triggered to produce electrical solitons, the main signals for brain associative memory and logical processing. Dendritic circuits are modeled, and electrical solitons are simulated to demonstrate the nature of soliton propagation, soliton reflection, the collision of solitons, as well as soliton OR gates, AND gates, XOR gates and NOT gates.

cs.NE↗

arXiv2006

Associative Memory For Reversible Programming and Charge Recovery

Presented below is an interesting type of associative memory called toggle memory based on the concept of T flip flops, as opposed to D flip flops. Toggle memory supports both reversible programming and charge recovery. Circuits designed using the principles delineated below permit matchlines to charge and discharge with near zero energy dissipation. The resulting lethargy is compensated by the massive parallelism of associative memory. Simulation indicates over 33x reduction in energy dissipation using a sinusoidal power supply at 2 MHz, assuming realistic 50 nm MOSFET models.

cs.AR↗

arXiv2005

Reversible CAM Processor Modeled After Quantum Computer Behavior

Proposed below is a reversible digital computer modeled after the natural behavior of a quantum system. Using approaches usually reserved for idealized quantum computers, the Reversible CAM, or State Vector Parallel (RSVP) processor can easily find keywords in an unstructured database (that is, it can solve a needle in a haystack problem). The RSVP processor efficiently solves a SAT (Satisfiability of Boolean Formulae) problem; also it can aid in the solution of a GP (Global Properties of Truth Table) problem. The power delay product of the RSVP processor is exponentially lower than that of a standard CAM programmed to perform similar operations.

cs.AR↗

arXiv2005

Quantum Algorithm Processors to Reveal Hamiltonian Cycles

Quantum computer versus quantum algorithm processor in CMOS are compared to find (in parallel) all Hamiltonian cycles in a graph with m edges and n vertices, each represented by k bits. A quantum computer uses quantum states analogous to CMOS registers. With efficient initialization, number of CMOS registers is proportional to (n-1)! Number of qubits in a quantum computer is approximately proportional to kn+2mn in the approach below. Using CMOS, the bits per register is about proportional to kn, which is less since bits can be irreversibly reset. In either concept, number of gates, or operations to identify Hamiltonian cycles is proportional to kmn. However, a quantum computer needs an additional exponentially large number of operations to accomplish a probabilistic readout. In contrast, CMOS is deterministic and readout is comparable to ordinary memory.

cs.AR↗

arXiv2005

Quantum Algorithm Processor For Finding Exact Divisors

Wiring diagrams are given for a quantum algorithm processor in CMOS to compute, in parallel, all divisors of an n-bit integer. Lines required in a wiring diagram are proportional to n. Execution time is proportional to the square of n.

cs.AR↗

arXiv2003

New Approachs to Quantum Computer Simulaton in a Classical Supercomputer

Classical simulation is important because it sets a benchmark for quantum computer performance. Classical simulation is currently the only way to exercise larger numbers of qubits. To achieve larger simulations, sparse matrix processing is emphasized below while trading memory for processing. It performed well within NCSA supercomputers, giving a state vector in convenient continuous portions ready for post processing.

quant-ph↗