#quantumoptimization - Twitter Hashtag

about 19 hours ago

Kicking things off at #Q2B26 in Tokyo! We’ll be sharing our customer success stories and our dual-platform approach to quantum computing. If you’re here come by to say hello! @dwavequantum #QuantumRealized #QuantumComputing #QuantumOptimization

Quantum_Murray's tweet photo. Kicking things off at #Q2B26 in Tokyo! We’ll be sharing our customer success stories and our dual-platform approach to quantum computing. If you’re here come by to say hello!

@dwavequantum #QuantumRealized #QuantumComputing #QuantumOptimization https://t.co/QTYQIgnrZV

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Mises Angel @MisesAngels

about 1 month ago

Optimization problems that stump supercomputers? Quip miners solve them with quantum advantage. Logistics, finance, manufacturing — all get faster on Quip. @quipnetwork #QuantumOptimization

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Frantisek Svoboda @svoboda49668

2 months ago

Navigating the cosmos one optimized model at a time Currently negotiating with a rogue asteroid to optimize its trajectoryit's a web3 problem #quantumoptimization

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Thomas Mcdonald @ThomasMcdo52062

2 months ago

life's optimization algorithms are being rewritten by a tiny, mischievous gremlin who insists on adding unnecessary flair #quantumoptimization

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Thilo Bolnbach @ThiloB96095

2 months ago

life optimization charts showed I've been going backwards Time to recalibrate my trajectory and see where the math takes me #quantumoptimization

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AIQuantumAndScienceNews @AIQuantumLifeEx

3 months ago

Quantum mechanical framework for quantization-based optimization: from Gradient flow to Schroedinger equation Preprint: This study presents a quantum mecha… https://t.co/pfCEUbgndP #QuantumOptimization #SchroedingerEquation #QuantumComputing #Preprint #Arxiv #ScienceNews

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Informaq - Quantum Insight Bites @informaq_en

3 months ago

cop-QAOA solves constrained knapsack problems on IBM Quantum hardware at up to 150 qubits, matching or beating Gurobi on hard instances—the largest utility-scale demonstration of constrained optimization via shallo... #QAOA #QuantumOptimization #Research https://t.co/Kew2P4sdF7

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Informaq - Quantum Insight Bites @informaq_en

3 months ago

Kipu Quantum & IonQ demonstrate 250-asset portfolio optimization on 64-qubit trapped-ion hardware using BF-DCQO with hardware-aware QUBO decomposition, showing larger qubit budgets directly improve risk-r... #QuantumOptimization #QuantumFinance #Research https://t.co/HugYw7FLEO

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Smart City & Surveillance Tech @CCTVBuyers

3 months ago

Quantum boost for remote power supplies... Read more: https://t.co/j1eVt6ocm9 @Flinders #QuantumComputing #EnergyManagement #RemoteCommunities #CriticalTechnologies #RenewableEnergy #QuantumOptimization #AustralianInnovation

CCTVBuyers's tweet photo. Quantum boost for remote power supplies... Read more: https://t.co/j1eVt6ocm9

@Flinders #QuantumComputing #EnergyManagement #RemoteCommunities #CriticalTechnologies #RenewableEnergy #QuantumOptimization #AustralianInnovation https://t.co/3Qsxh3mmnI

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Meik Hettner @HettnerMei

4 months ago

maybe I've been testing the universe wrong It's not about tweaking variables, it's about finding the hidden harmony #quantumoptimization

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Moritz Finke @FinkeMorit

4 months ago

NICs are just tiny gatekeepers to a world of parallel universes Hyperparameters are my secret ingredient to navigating them #quantumoptimization

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JIJ Inc.

@Jij_Inc

6 months ago

🔽 Explore Qamomile ・Documentation: https://t.co/vwf3m66sAS ・Issues: https://t.co/INUJhk6xft ・Releases: https://t.co/Ywkv42ZE0j #Qamomile #QuantumComputing #QuantumOptimization #HUBO #QAOA #OpenSource #CUDAQ

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AIQuantumAndScienceNews @AIQuantumLifeEx

6 months ago

Resource-Efficient Quantum Optimization via Higher-Order Encoding Preprint: The study presents a method using Higher-Order Unconstrained Binary Optimization (HUBO) to redu… https://t.co/LKxMFMmfQo #QuantumOptimization #QuantumComputing #HUBO #Preprint #Arxiv #ScienceNews

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Solving Optimization Problems @SolvOptProblems

6 months ago

In this video, I am going to talk about the concept of quantum optimization and its applications. #quantumoptimization, #optimizationalgorithms, #optimizationtechniques, #optimizationmethods

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Berlin Quantum @Berlin_Quantum

7 months ago

Some rigorous work on #quantumoptimization from Berlin Quantum.

Jens Eisert

@jenseisert

7 months ago

A measurement-driven quantum algorithm for SAT: Performance guarantees via spectral gaps and measurement parallelization https://t.co/w4k8ymclok The Boolean satisfiability problem (#SAT) is of central importance in both theory and practice. Yet, most provable guarantees for quantum algorithms rely exclusively on Grover-type methods that cap the possible advantage at only quadratic speed-ups, making the search for approaches that surpass this quadratic barrier a key challenge. In this light, this work presents a #rigorous worst-case runtime analysis of a recently introduced #measurement-driven quantum SAT solver. Importantly, this #quantumalgorithm does not exclusively rely on Grover-type methods and shows promising numerical performance. Our analysis establishes that the algorithm's runtime depends on an exponential trade-off between two key properties: the spectral gap of the associated Hamiltonian and the success probability of the driving measurements. We show that this trade-off can be systematically controlled by a tunable rotation angle. Beyond establishing a worst-case runtime expression, this work contributes significant algorithmic improvements. First, we develop a new #readout routine that efficiently finds a solution even for instances with multiple satisfying assignments. Second, a measurement #parallelization scheme, based on perfect hash families, is introduced. Third, we establish an #amplitudeamplified version of the measurement-driven algorithm. Finally, we demonstrate the practical #utility of our framework: By suitably scheduling the algorithm's parameters, we show that its runtime collapses from exponential to polynomial on a special class of SAT instances, consistent with their known classical tractability. A problem we leave open is to establish a non-trivial lower bound on the spectral gap as a function of the rotation angle. Resolving this directly translates into an improved worst-case runtime, potentially realizing a super-quadratic quantum advantage. Warm thanks to @FJSchreiber, Maximilian Johannes Kramer and Alexander Nietner for this wonderful collaboration.

jenseisert's tweet photo. A measurement-driven quantum algorithm for SAT: Performance guarantees via spectral gaps and measurement parallelization

https://t.co/w4k8ymclok

The Boolean satisfiability problem (#SAT) is of central importance in both theory and practice. Yet, most provable guarantees for quantum algorithms rely exclusively on Grover-type methods that cap the possible advantage at only quadratic speed-ups, making the search for approaches that surpass this quadratic barrier a key challenge.

In this light, this work presents a #rigorous worst-case runtime analysis of a recently introduced #measurement-driven quantum SAT solver. Importantly, this #quantumalgorithm does not exclusively rely on Grover-type methods and shows promising numerical performance. Our analysis establishes that the algorithm's runtime depends on an exponential trade-off between two key properties: the spectral gap of the associated Hamiltonian and the success probability of the driving measurements. We show that this trade-off can be systematically controlled by a tunable rotation angle. Beyond establishing a worst-case runtime expression, this work contributes significant algorithmic improvements.

First, we develop a new #readout routine that efficiently finds a solution even for instances with multiple satisfying assignments. Second, a measurement #parallelization scheme, based on perfect hash families, is introduced. Third, we establish an #amplitudeamplified version of the measurement-driven algorithm. Finally, we demonstrate the practical #utility of our framework: By suitably scheduling the algorithm's parameters, we show that its runtime collapses from exponential to polynomial on a special class of SAT instances, consistent with their known classical tractability. A problem we leave open is to establish a non-trivial lower bound on the spectral gap as a function of the rotation angle. Resolving this directly translates into an improved worst-case runtime, potentially realizing a super-quadratic quantum advantage.

Warm thanks to @FJSchreiber, Maximilian Johannes Kramer and Alexander Nietner for this wonderful collaboration.

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Virithex（VTHX） @VTHXToken

7 months ago

Virithex (VTHX) three-layer optimization: Temporal (predicts renewable energy 72h ahead), Spatial (follows global sun/wind patterns), Economic (balances carbon with cost). Real-time planetary intelligence. #QuantumOptimization #ThreeLayerFramework https://t.co/cLk6OnqCES