arXiv preprints from January 1, 2026 through September 8, 2026 — 13:06:38 EST
The supermembrane action is non-linear and a priori non-renormalizable. Still, some quantities in this theory may be free of log UV divergences and thus defined unambiguously. To explore this possibility we compute the energy of an M2 brane wrapped on a 2-torus in flat 11d space to two loops in the inverse-tension expansion. The...
Extreme-ultraviolet (XUV) spectroscopy represents an important new direction in precision physics, with potential applications ranging from the metrology of fundamental constants to tests of physics beyond the Standard Model. However, the application of quantum control methods for precision spectroscopy remains an open challenge in...
Low-spin excited states in $^{68}$Zn have been studied at the High Intensity Gamma-Ray Source (HI$γ$S) from the ground state up to the particle emission threshold using the nuclear resonance fluorescence technique (NRF) and the newly developed Clover Array. Low-spin levels were excited by linearly-polarized, $2.90 - 9.79$ MeV photon...
Lithium (Li) diffusion is commonly used to form $n^{+}$ contacts in high-purity germanium (HPGe) detectors, but the final electrically active donor profile can be sensitive to the post-diffusion thermal history. Li was introduced into HPGe coupons using a lithium-in-oil suspension and diffused for $30~\mathrm{min}$ at nominal...
Despite the fundamental role of Jahn-Teller effects of first and second order in shaping structural and electronic properties, there is hardly any observation in angle-resolved photoemission of solids. In oxide and halide perovskites, band structure replicas have occasionally been reported as fingerprints of Jahn-Teller effects, but...
We prove that minimum Riesz $s$-energy subset selection in the Euclidean plane is NP-complete already for the fixed exponent $s=2$. To our knowledge, this is the first Euclidean hardness result for exact Riesz-energy subset selection in which both the ambient dimension and the exponent are fixed. The reduction uses Barahona's planar...
Systematic trading rests on one article of faith: that regularities found in the past persist. We state it as a time-invariant mechanism driven by an unobserved latent state, and show that it leaves a researcher five constants to declare --- the recurrence bound $Lambda$ at a block length $b$, the invariance defect $epsilon_0$ of the...
KellyBoost is a single multi-output XGBoost model whose softmax output is the portfolio: with y the vector of per-asset holding-period returns, the training loss is - log(1 + w y), the negative log growth rate, so the fitted model is the growth-optimal (Kelly) allocation conditioned on the features. The objective is exact rather than...
Option prices are prices of insurance, so the risk-neutral probabilities they imply overstate physical crash risk. A power utility pricing kernel undoes the premium. But finitely many contracts trade, each at a bid and an ask, and many distributions fit inside the spreads. Each implies its own crash probability and expected loss below...
Tick-level trade-and-quote data for the Tokyo Stock Exchange is distributed through the Nikkei NEEDS service as thousands of zipped CSV archives spanning four data types with era-dependent schemas and Japanese-language layouts. We present tse_tick, an open-source Python library that converts these raw archives into clean, typed Polars...
In this paper we propose a new formulation of the Bayesian Filter as used in the discrete-time Markov-Switching-Multifractal (MSM) model of volatility based on existing permutation symmetry within the likelihood structure. We show both analytically and empirically that such a formulation leads to a reduction in time complexity from...
Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific investment preferences. We study whether a model's overall investment stance can be calibrated to a specified direction and strength. We introduce an investment-bias dial, an...
The stability of markets hosting leveraged exchange-traded products is governed not by any single product's loop gain but by the spectral radius of a loop-gain matrix, and scalar per-product monitoring underestimates system feedback by construction. Recent work measures the self-reinforcement of a leveraged fund's daily close...
A companion paper \cite{ItkinDF2026} introduced the Diagonal Frog (DF) positivity-preserving schemes for anisotropic Fokker--Planck equations, advancing each directional substep by a Krylov-computed matrix exponential, which dominates the cost. Replacing that exponential by a rational map $r(γL)$ reduces the substep to a banded solve,...
W-shaped smiles appear in near-expiry options around binary events such as earnings, and have been associated with bimodal risk-neutral densities. The three-parameter eSSVI slice cannot produce them. This paper defines WSVI, a parametric family for implied volatility that admits negative at-the-forward curvature and bimodal implied...
We consider reflexivity in hierarchical causal systems in which higher-level states constrain the lower-level dynamics that remain admissible [Wilcox and Gebbie (2014),Gebbie (2026)]. We ask how such state-dependent top-down constraints are realised when local activity is event driven while causal claims are made in calendar time. If...
Implied volatility surfaces summarise the option market and are central to many financial applications. Forecasting their future evolution requires modelling two-dimensional geometry, temporal dependence, and predictive uncertainty while preserving economic admissibility. We propose a conditional latent diffusion framework for...
At 15-minute horizons, directional mean reversion is far stronger and more pervasive in cryptocurrency markets than in US equities: scored under one matched, strictly out-of-sample protocol, 90% of 183 Binance pairs carry significant directional reversal against 2.7% of 187 US stocks and ETFs, in every focal coin-year since 2021. The...
We study discrete-time asset pricing with bid-ask spreads and model uncertainty. The family of probability measures enters the no-arbitrage condition through the union of its supports. In the single-period setting, we establish fundamental theorems of asset pricing with and without short-sale constraints. In the unconstrained market,...
Emile Durkheim's Suicide: A Study in Sociology (1897) predates much of the statistical machinery that quantitative modellers now take for granted. Yet, working with sparse and imperfect observational data, Durkheim repeatedly arrives at practices that remain remarkably relevant to modern modelling. This paper revisits Suicide from the...
Basket options are difficult to value under correlated lognormal dynamics because weighted sums and differences of lognormal variables have no tractable distribution. This paper develops a probability-based four-moment framework that separates the exact pricing representation from the distributional approximation. A change of measure...
Group-based reinforcement learning methods such as GRPO for large language models avoid training a critic by sampling multiple responses for each prompt. A reliable critic could instead estimate token-level advantages from one response, but standard critic-based training recipes are often unstable. We study this instability and...
An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control wants a short horizon, memory wants an unbounded one. ReWorld separates the two during training and bounds them at inference. Mixed per-head attention windows confine most heads to...
Modern software systems accumulate technical debt over decades of development, which makes migration expensive and largely manual. As coding agents become increasingly capable at bug fixing, can they autonomously perform such migrations? Existing benchmarks cannot answer this question because they evaluate only behavioural...
Road traffic injuries remain a major challenge in low- and middle-income countries, where proactive road safety auditing is limited by incomplete crash records, shortages of qualified auditors, and the high cost of large-scale field inspections. To address this problem, we propose Expert-Grounded Distillation (EGD), a novel artificial...