Extremely niche audience here, but
claim: everyone with sufficiently rich potential romantic interests will also necessarily be vulnerable to at least one honeytrap
proof: diagonalization argument a la Cantor, or maybe cf its indirect use in proving Rice's theorem
claim: everyone with sufficiently rich potential romantic interests will also necessarily be vulnerable to at least one honeytrap
proof: diagonalization argument a la Cantor, or maybe cf its indirect use in proving Rice's theorem
all of the posts that are like "here's how *I* would avoid a honey trap" strike me as aspirational
November 10, 2026 at 2:48 PM
Extremely niche audience here, but
claim: everyone with sufficiently rich potential romantic interests will also necessarily be vulnerable to at least one honeytrap
proof: diagonalization argument a la Cantor, or maybe cf its indirect use in proving Rice's theorem
claim: everyone with sufficiently rich potential romantic interests will also necessarily be vulnerable to at least one honeytrap
proof: diagonalization argument a la Cantor, or maybe cf its indirect use in proving Rice's theorem
A Hardware-Trained Generative Quantum Eigensolver for Sample-Based Quantum Diagonalization of Organotin Hydroxides up to 70 Qubits https://arxiv.org/abs/2611.13755
November 11, 2026 at 8:30 PM
A Hardware-Trained Generative Quantum Eigensolver for Sample-Based Quantum Diagonalization of Organotin Hydroxides up to 70 Qubits https://arxiv.org/abs/2611.13755
Gourab Panigrahi, Phani Motamarri
Accelerating matrix-free fast diagonalization and preconditioned linear solvers for higher-order finite element discretized elliptic problems on distributed GPUs
https://arxiv.org/abs/2611.14041
Accelerating matrix-free fast diagonalization and preconditioned linear solvers for higher-order finite element discretized elliptic problems on distributed GPUs
https://arxiv.org/abs/2611.14041
November 11, 2026 at 7:25 PM
Gourab Panigrahi, Phani Motamarri
Accelerating matrix-free fast diagonalization and preconditioned linear solvers for higher-order finite element discretized elliptic problems on distributed GPUs
https://arxiv.org/abs/2611.14041
Accelerating matrix-free fast diagonalization and preconditioned linear solvers for higher-order finite element discretized elliptic problems on distributed GPUs
https://arxiv.org/abs/2611.14041
Tushar Kumar Jain, Rahul Maitra, Nicholas J. Mayhall: Classical phase unwrapping enables large-time-step unitary quantum Krylov subspace diagonalization https://arxiv.org/abs/2611.14214 https://arxiv.org/pdf/2611.14214 https://arxiv.org/html/2611.14214
November 11, 2026 at 7:00 AM
Tushar Kumar Jain, Rahul Maitra, Nicholas J. Mayhall: Classical phase unwrapping enables large-time-step unitary quantum Krylov subspace diagonalization https://arxiv.org/abs/2611.14214 https://arxiv.org/pdf/2611.14214 https://arxiv.org/html/2611.14214
Kunal Kumar, et al.: A Hardware-Trained Generative Quantum Eigensolver for Sample-Based Quantum Diagonalization of Organotin Hydroxides up to 70 Qubits https://arxiv.org/abs/2611.13755 https://arxiv.org/pdf/2611.13755 https://arxiv.org/html/2611.13755
November 11, 2026 at 6:59 AM
Kunal Kumar, et al.: A Hardware-Trained Generative Quantum Eigensolver for Sample-Based Quantum Diagonalization of Organotin Hydroxides up to 70 Qubits https://arxiv.org/abs/2611.13755 https://arxiv.org/pdf/2611.13755 https://arxiv.org/html/2611.13755
Gourab Panigrahi, Phani Motamarri: Accelerating matrix-free fast diagonalization and preconditioned linear solvers for higher-order finite element discretized elliptic problems on distributed... https://arxiv.org/abs/2611.14041 https://arxiv.org/pdf/2611.14041 https://arxiv.org/html/2611.14041
November 11, 2026 at 6:49 AM
Gourab Panigrahi, Phani Motamarri: Accelerating matrix-free fast diagonalization and preconditioned linear solvers for higher-order finite element discretized elliptic problems on distributed... https://arxiv.org/abs/2611.14041 https://arxiv.org/pdf/2611.14041 https://arxiv.org/html/2611.14041
SqDMRG combines sample-based quantum diagonalization with DMRG to efficiently compute molecular ground-state energies. Demonstrated sub-kcal/mol accuracy on benzene clusters with ~30× fewer configurations than direct diagonalization, using both classical references and quantum...
SqDMRG: Sample-Based Quantum Diagonalization with Density Matrix Renormalization
arxiv.org
November 5, 2026 at 6:38 AM
SqDMRG combines sample-based quantum diagonalization with DMRG to efficiently compute molecular ground-state energies. Demonstrated sub-kcal/mol accuracy on benzene clusters with ~30× fewer configurations than direct diagonalization, using both classical references and quantum...
Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy https://arxiv.org/abs/2611.04496
November 5, 2026 at 12:30 AM
Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy https://arxiv.org/abs/2611.04496
Researchers introduced SqDMRG, combining sample-based quantum diagonalization with the density matrix renormalization group. The method demonstrated high accuracy on benzene pentamer and decamer clusters using both classical and quantum samples from the IBM Quantum…
#QuantumComputing #Dmrg #Sqdmrg
#QuantumComputing #Dmrg #Sqdmrg
SqDMRG achieves sub-kcal/mol accuracy
Source: arXiv quant-ph
realfeedapp.com
November 5, 2026 at 12:40 PM
Researchers introduced SqDMRG, combining sample-based quantum diagonalization with the density matrix renormalization group. The method demonstrated high accuracy on benzene pentamer and decamer clusters using both classical and quantum samples from the IBM Quantum…
#QuantumComputing #Dmrg #Sqdmrg
#QuantumComputing #Dmrg #Sqdmrg
Generative transformer models can be trained directly using quantum hardware to produce highly efficient molecular state-preparation circuits, achieving accurate SQD ground-state energies on previously unseen molecules with up to 70 qubits.
arxiv.org/abs/2611.13755
arxiv.org/abs/2611.13755
A Hardware-Trained Generative Quantum Eigensolver for Sample-Based Quantum Diagonalization of Organotin Hydroxides up to 70 Qubits
Quantum hardware can provide feedback for training circuit generators beyond the reach of exact classical simulation. We train generative quantum eigensolver (GQE) policies, transformers conditioned o...
arxiv.org
November 11, 2026 at 2:21 PM
Generative transformer models can be trained directly using quantum hardware to produce highly efficient molecular state-preparation circuits, achieving accurate SQD ground-state energies on previously unseen molecules with up to 70 qubits.
arxiv.org/abs/2611.13755
arxiv.org/abs/2611.13755
Sample-based Quantum Diagonalization via Density Matrix Renormalization Group
https://arxiv.org/pdf/2611.05975
Yuto Sugimoto, Tomonori Shirakawa, Yukio Kawashima, Toshinari Itoko, Seiji Yunoki.
https://arxiv.org/pdf/2611.05975
Yuto Sugimoto, Tomonori Shirakawa, Yukio Kawashima, Toshinari Itoko, Seiji Yunoki.
https://arxiv.org/abs/2611.05975
arXiv abstract link
arxiv.org
November 5, 2026 at 9:32 AM
Sample-based Quantum Diagonalization via Density Matrix Renormalization Group
https://arxiv.org/pdf/2611.05975
Yuto Sugimoto, Tomonori Shirakawa, Yukio Kawashima, Toshinari Itoko, Seiji Yunoki.
https://arxiv.org/pdf/2611.05975
Yuto Sugimoto, Tomonori Shirakawa, Yukio Kawashima, Toshinari Itoko, Seiji Yunoki.
Yuto Sugimoto, Tomonori Shirakawa, Yukio Kawashima, Toshinari Itoko, Seiji Yunoki: Sample-based Quantum Diagonalization via Density Matrix Renormalization Group https://arxiv.org/abs/2611.05975 https://arxiv.org/pdf/2611.05975 https://arxiv.org/html/2611.05975
November 5, 2026 at 6:59 AM
Yuto Sugimoto, Tomonori Shirakawa, Yukio Kawashima, Toshinari Itoko, Seiji Yunoki: Sample-based Quantum Diagonalization via Density Matrix Renormalization Group https://arxiv.org/abs/2611.05975 https://arxiv.org/pdf/2611.05975 https://arxiv.org/html/2611.05975
Broken-symmetry unrestricted Hartree-Fock references dramatically improve sample-based quantum diagonalization accuracy for iron-sulfur clusters, achieving sub-mHa agreement with DMRG benchmarks—demonstrating that reference-state preparation, not subspace size alone, drives ac...
Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy
arxiv.org
November 4, 2026 at 5:21 AM
Broken-symmetry unrestricted Hartree-Fock references dramatically improve sample-based quantum diagonalization accuracy for iron-sulfur clusters, achieving sub-mHa agreement with DMRG benchmarks—demonstrating that reference-state preparation, not subspace size alone, drives ac...
It Takes Two: Proofs of Work for Fiat–Shamir (Benedikt Bünz, Jessica Chen, Ziyi Guan) ia.cr/2026/2326
November 9, 2026 at 1:28 AM
It Takes Two: Proofs of Work for Fiat–Shamir (Benedikt Bünz, Jessica Chen, Ziyi Guan) ia.cr/2026/2326
Kumar, Shirakawa, Kim, Wakizaka, Hamamura, Sato, Yunoki, Motta, Horii, Kobayashi: Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy https://arxiv.org/abs/2611.04496 https://arxiv.org/pdf/2611.04496 https://arxiv.org/html/2611.04496
November 4, 2026 at 6:59 AM
Kumar, Shirakawa, Kim, Wakizaka, Hamamura, Sato, Yunoki, Motta, Horii, Kobayashi: Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy https://arxiv.org/abs/2611.04496 https://arxiv.org/pdf/2611.04496 https://arxiv.org/html/2611.04496
Fractional quantum Hall effect at ν=1/2 in wide GaAs quantum wells: Subband structure, exact diagonalization, and the magnitude of the gap
https://arxiv.org/pdf/2611.01885
Sankar Das Sarma.
https://arxiv.org/pdf/2611.01885
Sankar Das Sarma.
https://arxiv.org/abs/2611.01885
arXiv abstract link
arxiv.org
November 4, 2026 at 5:29 AM
Fractional quantum Hall effect at ν=1/2 in wide GaAs quantum wells: Subband structure, exact diagonalization, and the magnitude of the gap
https://arxiv.org/pdf/2611.01885
Sankar Das Sarma.
https://arxiv.org/pdf/2611.01885
Sankar Das Sarma.
Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy
https://arxiv.org/pdf/2611.04496
Kunal Kumar, Tomonori Shirakawa, Boseong Kim, Ryo Wakizaka, Ikko Hamamura, Mitsuhisa Sato, Seiji Yunoki, Mario Motta, Hiroshi Horii, Yuri Kobayashi.
https://arxiv.org/pdf/2611.04496
Kunal Kumar, Tomonori Shirakawa, Boseong Kim, Ryo Wakizaka, Ikko Hamamura, Mitsuhisa Sato, Seiji Yunoki, Mario Motta, Hiroshi Horii, Yuri Kobayashi.
https://arxiv.org/abs/2611.04496
arXiv abstract link
arxiv.org
November 4, 2026 at 9:32 AM
Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy
https://arxiv.org/pdf/2611.04496
Kunal Kumar, Tomonori Shirakawa, Boseong Kim, Ryo Wakizaka, Ikko Hamamura, Mitsuhisa Sato, Seiji Yunoki, Mario Motta, Hiroshi Horii, Yuri Kobayashi.
https://arxiv.org/pdf/2611.04496
Kunal Kumar, Tomonori Shirakawa, Boseong Kim, Ryo Wakizaka, Ikko Hamamura, Mitsuhisa Sato, Seiji Yunoki, Mario Motta, Hiroshi Horii, Yuri Kobayashi.
Rydberg atom processors beat random sampling for quantum diagonalization
Read more:
https://quantumzeitgeist.com/rydberg-technologies-atom-processors-beat-random/
Read more:
https://quantumzeitgeist.com/rydberg-technologies-atom-processors-beat-random/
Rydberg Atom Processors Beat Random Sampling For Quantum Diagonalization
This research demonstrates Rydberg atom processors can outperform random sampling for quantum diagonalization of the Fermi-Hubbard model, even with anisotropy and next-nearest neighbor interactions.
quantumzeitgeist.com
November 2, 2026 at 10:16 AM
Rydberg atom processors beat random sampling for quantum diagonalization
Read more:
https://quantumzeitgeist.com/rydberg-technologies-atom-processors-beat-random/
Read more:
https://quantumzeitgeist.com/rydberg-technologies-atom-processors-beat-random/
Framework for deriving validated effective quantum interactions via projection, block-diagonalization, and averaging—with rigorous encoding, evolution, and reconstruction procedures for controlling complex quantum dynamics.
#QuantumEngineering #EffectiveModels #QuantumControl
#QuantumEngineering #EffectiveModels #QuantumControl
Effective Model Construction and Validation in Quantum Dynamics Engineering
iq.fp2.dev
November 3, 2026 at 3:28 PM
Framework for deriving validated effective quantum interactions via projection, block-diagonalization, and averaging—with rigorous encoding, evolution, and reconstruction procedures for controlling complex quantum dynamics.
#QuantumEngineering #EffectiveModels #QuantumControl
#QuantumEngineering #EffectiveModels #QuantumControl
Looks like there’s a public post about it now: https://www.linkedin.com/posts/shreyasramesh_qdc2026-quantumcomputing-carboncapture-share-7524511230926065664-mgV4/
#qdc2026 #quantumcomputing #carboncapture #sustainability #accenture #ibmquantum #qiskit #innovation #trappedion #quantinuum | Shreyas Ramesh
⚛️ From a geometry file to a carbon-capture plant recommendation, powered by quantum computing. 🌍 We are excited to share that Accenture’s research on using quantum computing for CO₂ capture has been selected for IBM’s Quantum Developer Conference 2026! 🎉 Our team modeled how metal-organic frameworks (MOFs) bind CO₂ using Sample-based Quantum Diagonalization (SQD) on IBM quantum hardware, alongside Quantum Phase Estimation (QPE) via Quantinuum's InQuanto and Nexus. The goal: faster, smarter discovery of materials that can pull carbon out of the air. 🌱 Huge thanks to the team and our partners at Quantinuum and IBM Quantum. See you at #QDC2026! 🚀 And do your best to meet the Accenture team in Chicago Victoria Hazoglou, Colleen McCollom and so many others. The quantum team working on this globally from India to the Americas (North and South) made this happen, Syamasundar Santosh Kumar Gopasana, Saulo Cadete Machado, Yara Rodrigues Inácio, Rohan Joydhar, Victoria Hazoglou, Kung-Chuan Hsu supported by Global MDs in Brazil and India between Daniel Gonzalez & Shubhashis Sengupta. A special thanks to our incredible partners: Vincent J. Beltrani, Scott Crowder, Nicole Beckemeyer, Brooks Barhydt, Vedangi Pathak, Ph.D., Hamed Mohammadbagherpoor, Ph.D. from IBM Quantum and IBM, and Larry Stack, Elvira Shishenina, Josh Savory, Zachary Massa from Quantinuum. #QuantumComputing #CarbonCapture #Sustainability #Accenture #IBMQuantum #Qiskit #Innovation #TrappedIon #Quantinuum Carl Dukatz, Adam Burden, Colleen H., Kaushal Mody
www.linkedin.com
November 6, 2026 at 5:56 PM
Looks like there’s a public post about it now: https://www.linkedin.com/posts/shreyasramesh_qdc2026-quantumcomputing-carboncapture-share-7524511230926065664-mgV4/
Extending Sample-based Quantum Diagonalization to Systems of Linear Equations
https://arxiv.org/pdf/2610.41708
Taha Selim.
https://arxiv.org/pdf/2610.41708
Taha Selim.
https://arxiv.org/abs/2610.41708
arXiv abstract link
arxiv.org
November 2, 2026 at 9:32 AM
Extending Sample-based Quantum Diagonalization to Systems of Linear Equations
https://arxiv.org/pdf/2610.41708
Taha Selim.
https://arxiv.org/pdf/2610.41708
Taha Selim.
Taha Selim: Extending Sample-based Quantum Diagonalization to Systems of Linear Equations https://arxiv.org/abs/2610.41708 https://arxiv.org/pdf/2610.41708 https://arxiv.org/html/2610.41708
November 2, 2026 at 7:00 AM
Taha Selim: Extending Sample-based Quantum Diagonalization to Systems of Linear Equations https://arxiv.org/abs/2610.41708 https://arxiv.org/pdf/2610.41708 https://arxiv.org/html/2610.41708
LANL and QC Ware demonstrated Sample-based Quantum Diagonalization on IBM Quantum hardware to accurately simulate strongly correlated iron oxides, achieving chemical accuracy where variational quantum eigensolvers fail due to barren plateaus.
#QuantumChemistry #HybridQuantum #MaterialsSimulation
#QuantumChemistry #HybridQuantum #MaterialsSimulation
Quantum-Classical Diagonalization Achieves Chemical Accuracy for Bulk Iron Oxide
iq.fp2.dev
October 31, 2026 at 3:57 PM
LANL and QC Ware demonstrated Sample-based Quantum Diagonalization on IBM Quantum hardware to accurately simulate strongly correlated iron oxides, achieving chemical accuracy where variational quantum eigensolvers fail due to barren plateaus.
#QuantumChemistry #HybridQuantum #MaterialsSimulation
#QuantumChemistry #HybridQuantum #MaterialsSimulation
New quantum algorithm achieves sub-quintic scaling for molecular ground-state energy estimation in weakly correlated systems using Trotterized time evolution and quantum prolate diagonalization, enabling practical applications on early fault-tolerant quantum computers.
Quantum Algorithm for Weakly Correlated Molecular Systems with Sub-Quintic Scaling
arxiv.org
November 3, 2026 at 5:19 AM
New quantum algorithm achieves sub-quintic scaling for molecular ground-state energy estimation in weakly correlated systems using Trotterized time evolution and quantum prolate diagonalization, enabling practical applications on early fault-tolerant quantum computers.