Tootfinder

“For voters opposed to Reform UK, tactical voting represents the most obvious counterstrategy – one of the explanations for the lopsided result in the Caerphilly byelection (which used FPTP). But to be effective, tactical voting requires clear information: voters must know which party has the best chance of defeating Reform UK in their own constituency."
Reform holds 11% lead over Plaid Cymru in Westminster election poll, as centre left vote fragments in Wales

Reform holds 11% lead over Plaid Cymru in Westminster election poll, as centre left vote fragments in Wales
Martin Shipton Reform UK has an 11 point lead over Plaid Cymru in the latest YouGov/Cardiff University opinion poll for Westminster voting intentions, as centre-left support becomes increasingly fragmented across multiple parties amid an increase in support for the Greens. The latest poll conducted by YouGov for Cardiff University shows Reform UK at 30%, while […]

Semi-parametric Markov models for multi-type point patterns
Ib Thorsgaard Jensen, Jean-Fran\c{c}ois Coeurjolly, Rasmus Waagepetersen
https://arxiv.org/abs/2510.11226 https://

Semi-parametric Markov models for multi-type point patterns
Multi-type Markov point processes offer a flexible framework for modelling complex multi-type point patterns where it is pertinent to capture both interactions between points as well as large scale trends depending on observed covariates. However, estimation of interaction and covariate effects may be seriously biased in the presence of unobserved spatial confounders. In this paper we introduce a new class of semi-parametric Markov point processes that adjusts for spatial confounding through a …

Entanglement dynamics and performance of two-qubit gates for superconducting qubits under non-Markovian effects
Kiyoto Nakamura, Joachim Ankerhold
https://arxiv.org/abs/2510.05872

Entanglement dynamics and performance of two-qubit gates for superconducting qubits under non-Markovian effects
Within a numerically exact simulation technique, the dissipative dynamics of a two-qubit architecture is considered in which each qubit couples to its individual noise source (reservoir). The goal is to reveal the role of subtle qubit-reservoir correlations including non-Markovian processes as a prerequisite to guide further improvements of quantum computing devices. This paper addresses the following three topics. First, we examine the validity of the rotating wave approximation imposed previo…

Restoring detailed balance in non-Hermitian Markov processes
Tim Van Wesemael, Gilberto Nakamura, Jan Baetens, Odemir M. Bruno, Alexandre S. Martinez, Christophe Deroulers
https://arxiv.org/abs/2510.09467

Restoring detailed balance in non-Hermitian Markov processes
Stochastic processes out-of-equilibrium often involve asymmetric contributions that break detailed balance and lead to non-monotonic entropy production, limiting thermodynamic interpretations and inference techniques. Here we use Dyson maps to restore monotonic entropy growth in those processes, allowing the use of standard tools from statistical physics, providing a general and computationally tractable method applicable to a broad class of Markovian systems.

Generalized Fokker-Planck equation for the active Brownian motion
Sanju S Pillai, M Muhsin, M Sahoo
https://arxiv.org/abs/2510.12240 https://arxiv.org/pdf/…

Generalized Fokker-Planck equation for the active Brownian motion
We investigate the dynamics of an inertial active Ornstein-Uhlenbeck particle suspended in a non-Markovian environment. The particle is additionally subjected to external forces, such as harmonic confinement and a magnetic field. Motivated by the importance of understanding the non-Markovian behavior of complex environments, we examine the impact of a viscoelastic medium by employing the Jeffrey fluid framework for modeling the particle motion, which effectively captures both viscous and elasti…

#MarciBrickhouse
Season 9 Episode 3 "Sharks, Lies & Videotape"
#RandomBaywatch #lvdlpx

Q-Learning with Shift-Aware Upper Confidence Bound in Non-Stationary Reinforcement Learning
Ha Manh Bui, Felix Parker, Kimia Ghobadi, Anqi Liu
https://arxiv.org/abs/2510.03181 h…

Q-Learning with Shift-Aware Upper Confidence Bound in Non-Stationary Reinforcement Learning
We study the Non-Stationary Reinforcement Learning (RL) under distribution shifts in both finite-horizon episodic and infinite-horizon discounted Markov Decision Processes (MDPs). In the finite-horizon case, the transition functions may suddenly change at a particular episode. In the infinite-horizon setting, such changes can occur at an arbitrary time step during the agent's interaction with the environment. While the Q-learning Upper Confidence Bound algorithm (QUCB) can discover a proper pol…

A Structural Theory of Quantum Metastability: Markov Properties and Area Laws
Thiago Bergamaschi, Chi-Fang Chen, Umesh Vazirani
https://arxiv.org/abs/2510.08538 https://

A Structural Theory of Quantum Metastability: Markov Properties and Area Laws
Statistical mechanics assumes that a quantum many-body system at low temperature can be effectively described by its Gibbs state. However, many complex quantum systems exist only as metastable states of dissipative open system dynamics, which appear stable and robust yet deviate substantially from true thermal equilibrium. In this work, we model metastable states as approximate stationary states of a quasi-local, (KMS)-detailed-balanced master equation representing Markovian system-bath interac…

NHS forewarns us about reduced eligibility for COVID jab. Won't end well.
"National Booking Service: Hello Mark [don't be so familiar - Dr Burton to you!].
The rules about who can get the free COVID-19 vaccine have changed this year. You may not be offered it on the day if you're not in a priority group. Staff will confirm on the day. Check here:

COVID-19 vaccine
NHS information about the COVID-19 vaccine, including what the vaccine helps protect against, who should have it and when, how to get it and side effects.

Supervised Machine Learning for Predicting Open Quantum System Dynamics and Detecting Non-Markovian Memory Effects
Ali Abu-Nada, Subhashish Banerjee
https://arxiv.org/abs/2509.22758

Supervised Machine Learning for Predicting Open Quantum System Dynamics and Detecting Non-Markovian Memory Effects
We present a \emph{novel} and scalable supervised machine learning framework to predict open-quantum system dynamics and detect non-Markovian memory using only local ancilla measurements. A system qubit is coherently coupled to an ancilla via a symmetric XY Hamiltonian; the ancilla interacts with a noisy environment and is the only qubit we measure. A feedforward neural network, trained on short sliding windows of supplementary data from the past, forecasts the observable system $\langle Z_{(S)…