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arXiv:2604.06466v1 Announce Type: new Abstract: We unite two of the most widely used approaches for strongly damped, non-Markovian open quantum dynamics, the Hierarchical Equations of Motion (HEOM) an…
arXiv:2604.06461v1 Announce Type: new Abstract: We introduce a systematic protocol for constructing quantum Hilbert-space-fragmented Hamiltonians, whose Krylov-sector structure, unlike in classically …
arXiv:2604.06457v1 Announce Type: new Abstract: Although quantum random number generators rely on the inherent indeterminism of quantum mechanics, ensuring that the numbers produced are secure remains…
arXiv:2604.06455v1 Announce Type: new Abstract: We develop a dissipative extension of classical mechanics based on a complex, and more generally quaternionic, action principle that endows every classi…
arXiv:2604.06450v1 Announce Type: new Abstract: A basic model is provided that places active, intentional choices by biological organisms on a solid physical footing. The model is provisionally called…
arXiv:2604.06412v1 Announce Type: new Abstract: Complex numbers are central to the formulation of quantum mechanics, yet their role as a genuine resource is only beginning to be understood. In this wo…
arXiv:2604.06410v1 Announce Type: new Abstract: Radiative coupling between quantum emitters leads to a range of spectacular emission phenomena. Dicke studied the foundations of collectively enhanced a…
arXiv:2604.06325v1 Announce Type: new Abstract: We study the task of lifting arbitrary quantum states and channels to purifications and Stinespring dilations, respectively, in both the probabilistic e…
arXiv:2604.06322v1 Announce Type: new Abstract: General relativity and quantum mechanics are incompatible at the Planck scale. This contention can be examined if a quantum computer is set to operate a…
arXiv:2604.06319v1 Announce Type: new Abstract: Quantum computer hardware is predicted to scale over hundreds of thousands of qubits coming online in the next decade. Despite significant theoretical a…
arXiv:2604.06303v1 Announce Type: new Abstract: We study the protocol of entanglement harvesting when two local probes couple to the vacuum of a real scalar quantum field with arbitrary temporal profi…
arXiv:2604.06270v1 Announce Type: new Abstract: Efficient data encoding is the main factor affecting how fast hybrid quantum-classical algorithms run, but traditional simulators spend most of their ti…
I posted the following article this morning over on PogoWasRight.org, but I have had so many people sending me links to stories about this news that I guess I should have posted it here, too, as a fut…
arXiv:2405.03420v2 Announce Type: cross Abstract: This paper introduces a novel approach to enhance the performance of pre-trained neural networks in medical image segmentation using gradient-based Ne…
arXiv:2604.07236v1 Announce Type: new Abstract: Recent LLM-based agents often place world modeling, planning, and reflection inside a single language model loop. This can produce capable behavior, but…
arXiv:2604.07165v1 Announce Type: new Abstract: Reinforcement learning for Large Language Model agents is often hindered by sparse rewards in multi-step reasoning tasks. Existing approaches like Group…
arXiv:2604.07070v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable reasoning capabilities, their potential for purpose-driven exploration in dynamic geo-spatial …
arXiv:2604.07042v1 Announce Type: new Abstract: Most research in planning focuses on generating a plan to achieve a desired set of goals. However, a goal specification can also be used to encode a pro…
arXiv:2604.07017v1 Announce Type: new Abstract: AI assistants that interact with users over time need to interpret the user's current emotional state in order to respond appropriately and personally. …
arXiv:2604.07009v1 Announce Type: new Abstract: Ensuring fairness in machine learning predictions is a critical challenge, especially when models are deployed in sensitive domains such as credit scori…
arXiv:2604.07003v1 Announce Type: new Abstract: Large language models (LLMs) has been widely used for automated negotiation, but their high computational cost and privacy risks limit deployment in pri…
arXiv:2604.06995v1 Announce Type: new Abstract: Existing Graphical User Interface (GUI) reasoning tasks remain challenging, particularly in UI understanding. Current methods typically rely on direct s…
arXiv:2604.06838v1 Announce Type: new Abstract: In this paper, we propose using Learning from Answer Sets to approximate black-box models, such as Neural Networks (NN), in the specific case of learnin…
arXiv:2604.06820v1 Announce Type: new Abstract: Large language models (LLMs) can generate persuasive narratives at scale, raising concerns about their potential use in disinformation campaigns. Assess…