Results 171 to 180 of about 2,283 (206)

Application of the digital annealer unit in optimizing chemical reaction conditions for enhanced production yields. [PDF]

J Cheminform
Li SC, Wang PH, Su JW, Chiang WY, Yeh TL, Zhavoronkov A, Huang SH, Lin YC, Ou CH, Chen CY.   +9 more
europepmc   +1 more source

A versatile large-scale coherent Ising machine from microwave to visible and telecom wavelength bands. [PDF]

Light Sci Appl
Zhang H, Li J, Zhu H.
europepmc   +1 more source

Mini-scale traffic flow optimization: an iterative QUBOs approach converting from hybrid solver to pure quantum processing unit. [PDF]

Sci Rep
Salloum H, Zhanalin S, Badr AA, Kholodov Y.   +3 more
europepmc   +1 more source

Optimization of connection patterns between mobile phones and base stations using quantum annealing. [PDF]

Sci Rep
Takabayashi T, Sudo S, Aoki T, Seo S, Ohzeki M.   +4 more
europepmc   +1 more source

Pattern QUBOs: Algorithmic Construction of 3SAT-to-QUBO Transformations [PDF]

Electronics, 2023
One way of solving 3sat instances on a quantum computer is to transform the 3sat instances into instances of Quadratic Unconstrained Binary Optimizations (QUBOs), which can be used as an input for the QAOA algorithm on quantum gate systems or as an input for quantum annealers. This mapping is performed by a 3sat-to-QUBO transformation. Recently, it has
Thomas Gabor, Sebastian Feld, Claudia Linnhoff-Popien   +2 more
exaly   +6 more sources

Optimum-preserving QUBO parameter compression

Quantum Machine Intelligence
Abstract Quadratic unconstrained binary optimization (QUBO) problems are well-studied, not least because they can be approached using contemporary quantum annealing or classical hardware acceleration. However, due to limited precision and hardware noise, the effective set of feasible parameter values is severely restricted.
Sascha Mücke, Thore Gerlach
exaly   +5 more sources

On the State of QUBO Solving

Lecture notes in operations research
It is regularly claimed that quantum computers will bring breakthrough progress in solving challenging combinatorial optimization problems relevant in practice.
Thorsten Koch, Daniel Rehfeldt, Yuji Shinano   +2 more
exaly   +3 more sources