Results 51 to 60 of about 2,742,325 (160)

Highly‐Uniform Passive Crossbar Arrays of Resistive Switching Random Access Memory (RRAM) for In‐Memory Computing Applications

Advanced Electronic Materials, Volume 12, Issue 18, 21 September 2026.
Passive resistive memory arrays promise efficient in‐memory computing but suffer from sneak paths and programming variability. Here, highly uniform 32 × 32 passive RRAM crossbars are programmed with multilevel precision below 3% error and 99.5% yield.
S. Ricci, P. Mannocci, M. Porzani, D. Bridarolli, F. Carletti, M. Farronato, D. Ielmini   +6 more
wiley   +1 more source

A framework for automatically setting multiple penalty weights in Quadratic Unconstrained Binary Optimization [PDF]

This paper proposes a novel framework for automatically setting penalty weights in the Quadratic Unconstrained Binary Optimization (QUBO) to handle problems with multiple constraints. Quantum computing and quantum-inspired methods have gained prominence,
Alberto Moraglio (21060269), Jiajie Liu (21044159)   +1 more
core   +3 more sources

QUBO Formulations and Quantum Optimization for the Multi-Dimensional Knapsack Problem With Conflict, Forcing, and Precedence Constraints

IEEE Access
Constrained knapsack variants are well-suited for QUBO-based quantum optimization, but adding logical relations can inflate the binary model and complicate penalty selection.
Evren Guney, Joachim Ehrenthal
doaj   +1 more source

Drone Delivery Packing Problem on a Neutral‐Atom Quantum Computer

Advanced Quantum Technologies, Volume 9, Issue 9, September 2026.
This research models the Drone Delivery Packing Problem as a battery‐constrained graph partitioning. We use Pasqal's Fresnel QPU to sample time‐feasible single‐drone schedules, with tunable delivery targets via hardware parameters, and enforce battery limits by greedy post‐processing.
Sara Tarquini, Matteo Vandelli, Francesco Ferrari, Daniele Dragoni, Francesco Tudisco   +4 more
wiley   +1 more source

Generating hard quadratic unconstrained binary optimization instances via the method of combining bit reduction and duplication technique

Quadratic Unconstrained Binary Optimization (QUBO) is a combinatorial optimization problem defined by an energy function that consists of a quadratic formula involving multiple binary variables.
Li, Xiaotian, Nakano, Koji, Itou, Yasuaki, Kato, Takumi, Kawamata, Yuya, Tsukiyama, Shunsuke   +5 more
core   +1 more source

A QUBO Formulation for Multi‐Material Topology Optimization With Quantum Annealing

International Journal for Numerical Methods in Engineering, Volume 127, Issue 16, 30 August 2026.
ABSTRACT Multi‐material topology optimization (MMTO) seeks the optimal distribution of multiple materials within a given design domain to maximize structural performance. However, due to the high complexity of the solution space, MMTO problems are often trapped in local optima. To address this issue, a quantum annealing‐based MMTO framework is proposed.
Kenshin Nakano, Koji Nishiguchi, Junji Kato   +2 more
wiley   +1 more source

Construction of SubQUBOs by K-Means Clustering of QUBO Variables

IEEE Access
Ising machines are specialized solvers for combinatorial optimization problems (COPs), which are typically formulated as quadratic unconstrained binary optimization (QUBO) models.
Yuko Kamishima, Shuta Kikuchi, Shu Tanaka   +2 more
doaj   +1 more source

Computing the Molecular Ground State Energy in a Restricted Active Space Using Quantum Annealing

Advanced Quantum Technologies, Volume 9, Issue 7, July 2026.
Can modern quantum annealers tackle realistic molecular problems? By combining XBK Hamiltonian mappings, next‐generation D‐Wave hardware, and advanced annealing protocols, significantly larger molecular instances become accessible with improved energy accuracy.
Stefano Bruni, Enrico Prati
wiley   +1 more source

QUBO Simplification by Singular Value Decomposition and Coefficient Elimination for Ising Machines

IEEE Access
Ising machines, including quantum annealing machines, can efficiently solve combinatorial optimization problems by formulating them as Quadratic Unconstrained Binary Optimization (QUBO). However, it is known that the solving performance of Ising machines
Shinnosuke Inaba, Takeru Ota, Nozomu Togawa   +2 more
doaj   +1 more source

Continuous black-box optimization with an Ising machine and random subspace coding

Physical Review Research, 2022
A black-box optimization algorithm such as Bayesian optimization finds the extremum of an unknown function by alternating the inference of the underlying function and optimization of an acquisition function.
Syun Izawa, Koki Kitai, Shu Tanaka, Ryo Tamura, Koji Tsuda   +4 more
doaj   +1 more source