Results 111 to 120 of about 1,206,642 (268)

Advances in Josephson Junction Materials and Processes Toward Practical Quantum Computing

open access: yesAdvanced Science, EarlyView.
Emerging materials for quantum computing, including crystalline materials, two‐dimensional van der Waals materials, two‐dimensional electron gas systems, ferromagnets, and unconventional (e.g., d‐wave) superconductors, offer opportunities to engineer next‐generation Josephson junctions.
Hyunseong Kim   +11 more
wiley   +1 more source

Hamiltonian Cycles in Products of Graphs

open access: yes, 1975
Let V(G) and E(G) denote the vertex set and the edge set of a graph G; let Kn denote the complete graph with n vertices and let Kn, m denote the complete bipartite graph on n and m vertices. A Hamiltonian cycle (Hamiltonian path, respectively) in a graph
Joseph Zaks
core   +1 more source

Enumeration of Hamiltonian Cycles and Paths in a Graph [PDF]

open access: yesProceedings of the American Mathematical Society, 1991
First, we show that the determinant of a given matrix can be expanded by its principal minors together with a set of arbitrary parameters. The enumeration of Hamiltonian cycles and paths in a graph is then carried out by an algebraic method. Three types of nonalgebraic representation are formulated.
openaire   +2 more sources

Perspective: Quantum Computing on Magnetic Racetrack

open access: yesAdvanced Electronic Materials, EarlyView.
Magnetic domain walls emerge as mobile qubits on quantum racetracks, where chirality encodes quantum information and current‐driven motion enables flying‐qubit functionality. This Perspective outlines the physical principles, gate mechanisms, material requirements, and experimental roadmap for realizing scalable quantum computing with magnetic textures,
Ji Zou, Jelena Klinovaja, Daniel Loss
wiley   +1 more source

Evolution of Physical Intelligence Across Scales

open access: yesAdvanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu   +7 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy   +8 more
wiley   +1 more source

Hamiltonian path and Hamiltonian cycle are solvable in polynomial time in graphs of bounded independence number [PDF]

open access: yes
A Hamiltonian path (a Hamiltonian cycle) in a graph is a path (a cycle, respectively) that traverses all of its vertices. The problems of deciding their existence in an input graph are well-known to be NP-complete, in fact, they belong to the first ...
Jedličková, Nikola, Kratochvíl, Jan
core  

FBSDEs with time delayed generators:L-P-solutions, differentiability, representation formulas and path regularity [PDF]

open access: yes, 2011
We extend the work of Delong and Imkeller (2010) [6,7] concerning backward stochastic differential equations with time delayed generators (delay BSDEs). We give moment and a priori estimates in general L-p-spaces and provide sufficient conditions for the
Gonçalo dos Reis   +5 more
core   +1 more source

Absolute Differences Along Hamiltonian Paths

open access: yesThe Electronic Journal of Combinatorics, 2015
We prove that if the vertices of a complete graph are labeled with the elements of an arithmetic progression, then for any given vertex there is a Hamiltonian path starting at this vertex such that the absolute values of the differences of consecutive vertices along the path are pairwise distinct.
openaire   +3 more sources

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

open access: yesAdvanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison   +4 more
wiley   +1 more source

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