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University of Southern Denmark is hiring:
Postdoctoral fellow in quantum algorithms and quantum software

#postdoc #quantumcomputing #quantumalgorithms
November 8, 2026 at 3:58 PM
tenuretracker.bsky.social
University of Southern Denmark is hiring:
Associate Professor in Quantum Algorithms and Quantum Software

#quantumcomputing #quantumalgorithms
November 8, 2026 at 3:43 PM
tenuretracker.bsky.social
University of Southern Denmark is hiring:
Assistant Professor in Quantum Algorithms and Quantum Software

#quantumcomputing #quantumalgorithms
November 8, 2026 at 3:21 PM
informaq.bsky.social
Researchers prove unconditional quantum advantage for shallow quantum circuits in PAC distribution learning, showing constant-depth quantum circuits outperform shallow classical circuits for generative distribution learning tasks.

#QuantumAdvantage #QuantumAlgorithms #News
Unconditional Quantum Advantage in PAC Distribution Learning with Shallow Circuits
iq.fp2.dev
November 11, 2026 at 9:46 AM
informaq.bsky.social
Introduces CURE-QKSD, a classical post-processing method enabling large time steps in quantum Krylov algorithms while achieving chemical accuracy on molecular systems, eliminating ill-conditioning problems that limit current approaches.

#QuantumAlgorithms #QuantumChemistry #Research
Phase Unwrapping for Efficient Quantum Eigenvalue Extraction
arxiv.org
November 11, 2026 at 7:12 AM
tenuretracker.bsky.social
Helmholtz Information & Data Science Academy (HiDA) is hiring:
Postdoc / Scientist for the Development of Quantum Algorithms to Simulate Electron Transfer at Electrode Surfaces

#postdoc #quantumcomputing #quantumalgorithms
November 7, 2026 at 7:49 AM
markeatherly.bsky.social
Detecting Phishing in Ethereum Networks using Quantum Machine Learning

#QuantumHardware #QuantumAlgorithms #QuantumML
Detecting Phishing in Ethereum Networks using Quantum Machine Learning
This article explores the potential of Quantum Machine Learning (QML), specifically assessing a Quantum Support Vector Machine (QSVM) and a Variational Quantum Classifier (VQC) for detecting anomalies in real-world financial transaction data. While these QML methods outperform statistical methods, t
arxiv.org
November 10, 2026 at 12:52 PM
informaq.bsky.social
NQCC secures enterprise licence agreement with Phasecraft, enabling UK organizations to access advanced quantum algorithms and accelerate real-world quantum computing applications.

#QuantumSoftware #QuantumAlgorithms #News
UK NQCC and Phasecraft Expand Quantum Software Access
iq.fp2.dev
November 6, 2026 at 11:02 AM
informaq.bsky.social
QuEra, Harvard, and Anthropic research demonstrates AI can design quantum circuits requiring fewer computational resources, potentially expanding fault-tolerant quantum computer capabilities with existing hardware.

#QuantumCircuits #QuantumAlgorithms #News
AI-Designed Quantum Circuits Reduce Computational Resource Requirements
iq.fp2.dev
November 10, 2026 at 7:37 PM
informaq.bsky.social
Novel framework combines quantum amplitude estimation with game theory to achieve quadratic improvement in query complexity for Nash equilibrium computation in imperfect-information games with bounded payoffs.

#QuantumAlgorithms #GameTheory #Research
Quantum-Assisted Counterfactual Regret Minimization for Game Theory
arxiv.org
November 11, 2026 at 7:24 AM
informaq.bsky.social
Fujitsu's cardinal sine interpolation method improves quantum simulation efficiency with O(T^(1+o(1))(log(1/ε))²/ε) cost scaling, requiring no additional qubits—a practical advance for near-term quantum computers.

#QuantumSimulation #QuantumAlgorithms #News
Fujitsu's Cardinal Sine Interpolation Advances Quantum Simulation Cost Scaling
iq.fp2.dev
November 6, 2026 at 4:03 PM
informaq.bsky.social
Presents exact, ancilla-free quantum circuits for preparing uniform superpositions over arbitrary integer intervals with Θ(n) gate complexity—achieving asymptotic optimality and enabling practical quantum algorithm implementations.

#QuantumAlgorithms #QuantumCircuits #Research
Efficient Quantum Algorithm for Uniform Superposition Preparation Over Arbitrary Integer Intervals
iq.fp2.dev
November 11, 2026 at 9:29 AM
informaq.bsky.social
TU Delft researchers developed and tested quantum algorithms directly on their local quantum hardware platform, demonstrating co-designed quantum computing integration.

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Local Quantum Algorithms Integrated with TU Delft Quantum Hardware
qutech.nl
November 5, 2026 at 3:53 PM
informaq.bsky.social
Dynamic VITE uses fixed operator ordering from nested Hamiltonian commutators with residual-triggered growth, achieving 1.6–5.4× fewer circuits than adaptive methods on non-integrable systems for ground state preparation.

#QuantumAlgorithms #VQE #Research
Pool-Free Residual-Triggered Ansatz Growth for Variational Imaginary-Time Evolution
arxiv.org
November 11, 2026 at 8:20 AM
informaq.bsky.social
Google DeepMind's AI agents achieved order-of-magnitude quantum algorithm improvements through automated discovery paired with formal verification, demonstrating Q·T reductions up to 290× across plasma physics, chemistry, and drug discovery applications.

#QuantumAlgorithms #FormalVerification #News
Formally Verified Multi-Agent Quantum Algorithm Discovery via Lean 4
quantumcomputingreport.com
November 11, 2026 at 12:07 AM
informaq.bsky.social
Landmark open problem in quantum computing theory solved: Physical Superintelligence proved the Aaronson-Ambainis Conjecture using AI, establishing a lower bound on polynomial influence with implications for quantum query complexity.

#QuantumAlgorithms #QuantumComplexity #News
Aaronson-Ambainis Conjecture Proved Using AI
iq.fp2.dev
November 8, 2026 at 10:53 PM
markeatherly.bsky.social
An Agentic Formalization for Certified Quantum Neural Network Design

A central model in quantum machine learning is the quantum neural network (QNN), whose design requires balancing expressivity and trainability.

#QuantumHardware #QuantumAlgorithms #QuantumML
An Agentic Formalization for Certified Quantum Neural Network Design
A central model in quantum machine learning is the quantum neural network (QNN), whose design requires balancing expressivity and trainability. Technically, expressivity is studied through circuit-function analysis, such as quantum signal processing, while trainability is analyzed using dynamical-Li
arxiv.org
November 10, 2026 at 12:52 PM
informaq.bsky.social
Researchers at Quantinuum demonstrate that prioritizing error resilience over computational precision yields superior ground state preparation for quantum simulations beyond 20 qubits, challenging conventional algorithm optimization strategies.

#QuantumAlgorithms #NoiseResilience #News
Adiabatic Evolution Outperforms FFT for Quantum Ground State Preparation Beyond 20 Qubits
quantumzeitgeist.com
November 8, 2026 at 9:01 PM
informaq.bsky.social
New method achieves quantum state approximation using smaller Lie groups within expanded qubit systems, reducing computational complexity from exponential to polynomial scaling—a potential breakthrough for scalable quantum computing.

#QuantumAlgorithms #StatePreparation #News
Polynomial-Scaling Quantum State Preparation via Open Quantum Systems and Smaller Lie Groups
iq.fp2.dev
November 9, 2026 at 1:24 AM
markeatherly.bsky.social
A cryogenic neutral-atom platform with full optical access and 2-hour trap lifetime

#QuantumHardware #QuantumAlgorithms #QuantumSimulation
A cryogenic neutral-atom platform with full optical access and 2-hour trap lifetime
Neutral-atom quantum processors are rapidly scaling toward system sizes of more than ten thousand qubits, allowing for the realization of a new class of quantum computing algorithms and quantum simulation experiments. However, current neutral-atom platforms generally have to find a compromise betwee
arxiv.org
November 8, 2026 at 10:43 AM
informaq.bsky.social
Researchers developed a fully coherent quantum algorithm achieving polynomial speedup in system size and exponential speedup in spatial dimensions for PDE-constrained optimization, avoiding costly quantum state tomography.

#QuantumOptimization #QuantumAlgorithms #News
Quantum Algorithm for PDE-Constrained Optimization with Block-Encoding
iq.fp2.dev
November 7, 2026 at 10:43 PM
informaq.bsky.social
Mathematical proof establishes fundamental limits on quantum computing advantages over classical algorithms on unstructured problems, resolving the 2008 Aaronson-Ambainis conjecture through AI-assisted reasoning.

#QuantumAlgorithms #QuantumTheory #News
AI-Assisted Proof Resolves Quantum Speedup Conjecture
iq.fp2.dev
November 6, 2026 at 10:38 PM
markeatherly.bsky.social
Expressibility and trainability of a two-dimensional pairwise quantum-circuit ansatz

Parameterized quantum circuits~(PQCs) constitute a central building block of variational quantum algorithms~(VQAs) and quantum machine learning~(QML) methods.

#QuantumHardware #QuantumAlgorithms #QuantumML
Expressibility and trainability of a two-dimensional pairwise quantum-circuit ansatz
Parameterized quantum circuits~(PQCs) constitute a central building block of variational quantum algorithms~(VQAs) and quantum machine learning~(QML) methods. Existing ansatz designs often adopt hardware-agnostic or simplified 1D chain/ring entanglement patterns. However, as quantum hardware continu
arxiv.org
November 8, 2026 at 10:43 AM
informaq.bsky.social
PSI's AI system running an unreleased Anthropic model proved the Aaronson-Ambainis conjecture—a landmark theoretical result showing quantum computers cannot achieve exponential speedups on random, unstructured data, verified through Lean formal proof.

#QuantumComplexity #QuantumAlgorithms #News
PSI's AI System Proves 18-Year-Old Aaronson-Ambainis Conjecture in Quantum Complexity
quantumzeitgeist.com
November 8, 2026 at 10:08 AM
informaq.bsky.social
Researchers simplified quantum lower bound proofs for element distinctness and k-sum problems using only fundamental quantum mechanics and linear algebra principles, making complex theoretical results more accessible.

#QuantumAlgorithms #LowerBounds #News
Elementary Proofs Simplify Quantum Lower Bounds on Element Distinctness and K-Sum
iq.fp2.dev
November 6, 2026 at 7:58 PM