Negative / Null Result ReportOpen accessMathematics
Kevin Barreto, Jiwon Kang, Sang-hyun Kim et al. · 2026 · arXiv
Answering a question of Erdős and Graham, we show that the double exponential growth condition $\limsup_{n\to\infty}a_n^{1/φ^n}=\infty$ for a strictly increasing sequence of positive integers $\{a_n\}_{n=1}^\infty$ is sufficient for the series $\sum_{n=1}^\infty 1/(a_n a_{n+1})$ to have an irrational sum; here $φ$ denotes the golden ratio. We also provide a positive generalization to $\sum_{n=1}^\infty 1/(a_n^{w_0}\cdots a_{n+d-1}^{w_{d-1}})$, and a negative result showing that some of its instances are essentially optimal. The original problem was autonomously solved by the AI agent \emph{Ale
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Andrew Fish, Alexei Lisitsa · 2014 · arXiv
We explore the application of automated reasoning techniques to unknot detection, a classical problem of computational topology. We adopt a two-pronged experimental approach, using a theorem prover to try to establish a positive result (i.e. that a knot is the unknot), whilst simultaneously using a model finder to try to establish a negative result (i.e. that the knot is not the unknot). The theorem proving approach utilises equational reasoning, whilst the model finder searches for a minimal size counter-model. We present and compare experimental data using the involutary quandle of the knot,
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A. Rubbia, P. Sala · 2002 · arXiv
The possibility to improve the CERN to Gran Sasso neutrino beam performances for theta_{13} searches is investigated. We show that by an appropriate optimization of the target and focusing optics of the present CNGS design, we can increase the flux of low energy neutrinos by about a factor 5 compared to the current tau optimized focalisation. With the ICARUS 2.35 kton detector at LNGS and in case of negative result, this would allow to improve the limit to sin^22 theta_{13} by an order of magnitude better than the current limit of CHOOZ at Delta m^2 approximately 3 times 10^{-3} eV^2 within 5
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Aarón Villanueva, Peyman Najafi, Hilbert J. Kappen · 2022 · arXiv
We study quantum annealing for combinatorial optimization with Hamiltonian $H = z H_f + H_0$ where $H_f$ is diagonal, $H_0=-|φ\rangle \langle φ|$ is the equal superposition state projector and $z$ the annealing parameter. We analytically compute the minimal spectral gap as $\mathcal{O}(1/\sqrt{N})$ with $N$ the total number of states and its location $z_*$. We show that quantum speed-up requires an annealing schedule which demands a precise knowledge of $z_*$, which can be computed only if the density of states of the optimization problem is known. However, in general the density of states is
View details →Negative / Null Result ReportOpen accessMathematics
Itai Benjamini, Alexander Shamov, Barak Weiss · 2026 · arXiv
We present an open problem about non-colliding freely moving hard disks in the Euclidean plane, together with related positive and negative partial results. The open problem is stated in a non-degenerate form: velocities are required to be pairwise distinct and their speeds are required to be uniformly bounded away from infinity. The positive deterministic result gives a bounded, injective, non-colliding velocity assignment for the integer lattice; after a common velocity shift, the speeds are also bounded away from zero. The negative result shows that no bounded continuous vector field on the
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Michał Pilipczuk · 2011 · arXiv
We introduce a variant of modal logic, dubbed EXISTENTIAL COUNTING MODAL LOGIC (ECML), which captures a vast majority of problems known to be tractable in single exponential time when parameterized by treewidth. It appears that all these results can be subsumed by the theorem that model checking of ECML admits an algorithm with such complexity. We extend ECML by adding connectivity requirements and, using the Cut&Count technique introduced by Cygan et al. [4], prove that problems expressible in the extension are also tractable in single exponential time when parameterized by treewidth; however
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Ramon Lapiedra, Juan Antonio Morales-Lladosa · 2013 · arXiv
Recently, some Lema{î}tre-Tolman-Bondi metrics have been considered as models alternative to the dark energy within the Friedmann-Lema{î}tre-Robertson-Walker universes. The vanishing of the intrinsic energy of these metrics is examined since such a vanishing, in the present case and in general, could be interpreted as a necessary condition to consider the possibility of the quantum creation of a metric. More specifically, this vanishing is examined in the particular case where the Lema{î}tre-Tolman-Bondi metrics behave asymptotically like a Friedmann-Lema{î}tre-Robertson-Walker universe. Final
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M. B. Bell, S. P. Comeau · 2003 · arXiv
The high number of QSOs around NGC 6212 allows a correlation analysis to be carried out between their redshift distribution and the redshift distributions predicted by intrinsic redshift models. We find no correlation between the QSO redshift distribution and the intrinsic redshifts predicted by Karlsson's log(1+z) = 0.089 relation. However, we find that the QSO redshift distribution is correlated with the intrinsic redshifts predicted by the relation z_{iQ} = 0.62[N-0.1M_{N}], for N = 3. We also find evidence that the observed redshifts of the QSOs contain a small cosmological redshift compon
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Adrien Boiret, Radosław Piórkowski, Janusz Schmude · 2018 · arXiv
In the past decades, classical results from algebra, including Hilbert's Basis Theorem, had various applications in formal languages, including a proof of the Ehrenfeucht Conjecture, decidability of HDT0L sequence equivalence, and decidability of the equivalence problem for functional tree-to-string transducers. In this paper, we study the scope of the algebraic methods mentioned above, particularily as applied to the equivalence problem for register automata. We provide two results, one positive, one negative. The positive result is that equivalence is decidable for MSO transformations on uno
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Amate A, Lieberman M · 2026 · Harm reduction journal
Medetomidine has recently emerged in the illicit drug supply in the United States, and lateral flow immunoassay test strips are an inexpensive and easy-to-use field screening option for detecting this highly potent sedative. However, the…
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Lukas Graf, Tobias Harks, Julian Schwarz · 2025 · arXiv
A seminal result of [Fleischer et al. and Karakostas and Kolliopulos, both FOCS 2004] states that system optimal multi-commodity static network flows are always implementable as tolled Wardrop equilibrium flows even if users have heterogeneous value-of-time sensitivities. Their proof uses LP-duality to characterize the general implementability of network flows by tolls. For the much more complex setting of $\textit{dynamic flows}$, [Graf et al., SODA 2025] identified necessary and sufficient conditions for a dynamic $s$-$d$ flow to be implementable as a tolled dynamic equilibrium. They used th
View details →Negative / Null Result ReportOpen accessMathematics
Han Huang · 2016 · arXiv
It is natural to ask whether the center of mass of a convex body $K\subset \mathbb{R}^n$ lies in its John ellipsoid $B_K$, i.e., in the maximal volume ellipsoid contained in $K$. This question is relevant to the efficiency of many algorithms for convex bodies. In this paper, we obtain an unexpected negative result. There exists a convex body $K\subset \mathbb{R}^n$ such that its center of mass does not lie in the John ellipsoid $B_K$ inflated $(1-C\sqrt{\frac{\log(n)} {n}})n$ times about the center of $B_K$. Moreover, there exists a polytope $P \subset \mathbb{R}^n$ with $O(n^2)$ facets whose
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Petra Laketa, Stanislav Nagy · 2022 · arXiv
The halfspace depth of a $d$-dimensional point $x$ with respect to a finite (or probability) Borel measure $μ$ in $\mathbb{R}^d$ is defined as the infimum of the $μ$-masses of all closed halfspaces containing $x$. A natural question is whether the halfspace depth, as a function of $x \in \mathbb{R}^d$, determines the measure $μ$ completely. In general, it turns out that this is not the case, and it is possible for two different measures to have the same halfspace depth function everywhere in $\mathbb{R}^d$. In this paper we show that despite this negative result, one can still obtain a substan
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Calvin McCarter, Nicholas Dronen · 2022 · arXiv
Fast approximations to matrix multiplication have the potential to dramatically reduce the cost of neural network inference. Recent work on approximate matrix multiplication proposed to replace costly multiplications with table-lookups by fitting a fast hash function from training data. In this work, we propose improvements to this previous work, targeted to the deep learning inference setting, where one has access to both training data and fixed (already learned) model weight matrices. We further propose a fine-tuning procedure for accelerating entire neural networks while minimizing loss in
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Xinyan Hu, Meena Jagadeesan, Michael I. Jordan et al. · 2023 · arXiv
In content recommender systems such as TikTok and YouTube, the platform's recommendation algorithm shapes content producer incentives. Many platforms employ online learning, which generates intertemporal incentives, since content produced today affects recommendations of future content. We study the game between producers and analyze the content created at equilibrium. We show that standard online learning algorithms, such as Hedge and EXP3, unfortunately incentivize producers to create low-quality content, where producers' effort approaches zero in the long run for typical learning rate sched
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Anqi Mao, Mehryar Mohri, Yutao Zhong · 2024 · arXiv
We present a detailed study of $H$-consistency bounds for regression. We first present new theorems that generalize the tools previously given to establish $H$-consistency bounds. This generalization proves essential for analyzing $H$-consistency bounds specific to regression. Next, we prove a series of novel $H$-consistency bounds for surrogate loss functions of the squared loss, under the assumption of a symmetric distribution and a bounded hypothesis set. This includes positive results for the Huber loss, all $\ell_p$ losses, $p \geq 1$, the squared $ε$-insensitive loss, as well as a negati
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Hans-Joachim Böckenhauer, Elisabet Burjons, Martin Raszyk et al. · 2018 · arXiv
Parameterized complexity allows us to analyze the time complexity of problems with respect to a natural parameter depending on the problem. Reoptimization looks for solutions or approximations for problem instances when given solutions to neighboring instances. We try to combine both techniques, in order to better classify the complexity of problems in the parameterized setting. Specifically, we see that some problems in the class of compositional problems, which do not have polynomial kernels under standard complexity-theoretic assumptions, do have polynomial kernels under reoptimization for
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G. Maciejewski · 2022 · arXiv
Uninterrupted observations from space-borne telescopes provide the photometric precision that is required to detect shallow transits of small planets missed by ground-based surveys. We used data from the Transiting Exoplanet Survey Satellite (TESS) to search for nearby planetary companions in 12 planetary systems with hot Jupiters: HD 2685, Qatar-10, WASP-4, WASP-48, WASP-58, WASP-91, WASP-120, WASP-121, WASP-122, WASP-140, XO-6, and XO-7. We also applied the transit timing method based on homogeneously determined mid-transit times in order to search for non-transiting companions that could gr
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Ali Çivril · 2017 · arXiv
It is well known that sparse approximation problem is \textsf{NP}-hard under general dictionaries. Several algorithms have been devised and analyzed in the past decade under various assumptions on the \emph{coherence} $μ$ of the dictionary represented by an $M \times N$ matrix from which a subset of $k$ column vectors is selected. All these results assume $μ=O(k^{-1})$. This article is an attempt to bridge the big gap between the negative result of \textsf{NP}-hardness under general dictionaries and the positive results under this restrictive assumption. In particular, it suggests that the afo
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Yossi Arjevani, Ohad Shamir · 2016 · arXiv
Finite-sum optimization problems are ubiquitous in machine learning, and are commonly solved using first-order methods which rely on gradient computations. Recently, there has been growing interest in \emph{second-order} methods, which rely on both gradients and Hessians. In principle, second-order methods can require much fewer iterations than first-order methods, and hold the promise for more efficient algorithms. Although computing and manipulating Hessians is prohibitive for high-dimensional problems in general, the Hessians of individual functions in finite-sum problems can often be effic
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Guy Van den Broeck, Adnan Darwiche · 2013 · arXiv
Lifted inference algorithms exploit symmetries in probabilistic models to speed up inference. They show impressive performance when calculating unconditional probabilities in relational models, but often resort to non-lifted inference when computing conditional probabilities. The reason is that conditioning on evidence breaks many of the model's symmetries, which can preempt standard lifting techniques. Recent theoretical results show, for example, that conditioning on evidence which corresponds to binary relations is #P-hard, suggesting that no lifting is to be expected in the worst case. In
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Davin Choo, Kirankumar Shiragur · 2023 · arXiv
Recovering causal relationships from data is an important problem. Using observational data, one can typically only recover causal graphs up to a Markov equivalence class and additional assumptions or interventional data are needed for complete recovery. In this work, under some standard assumptions, we study causal graph discovery via adaptive interventions with node-dependent interventional costs. For this setting, we show that no algorithm can achieve an approximation guarantee that is asymptotically better than linear in the number of vertices with respect to the verification number; a wel
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Valerio Varricchio, Brian Paden, Dmitry Yershov et al. · 2017 · arXiv
Nearest-neighbor search dominates the asymptotic complexity of sampling-based motion planning algorithms and is often addressed with k-d tree data structures. While it is generally believed that the expected complexity of nearest-neighbor queries is $O(log(N))$ in the size of the tree, this paper reveals that when a classic k-d tree approach is used with sub-Riemannian metrics, the expected query complexity is in fact $Θ(N^p \log(N))$ for a number $p \in [0, 1)$ determined by the degree of nonholonomy of the system. These metrics arise naturally in nonholonomic mechanical systems, including cl
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Alejandro Alonso-Valero, Daniel Berzal-Rozalén, Felipe J. Llanes-Estrada et al. · 2024 · arXiv
We deploy the Hartree-Fock approximation for all-heavy quark hadrons, including quarkonium, baryons, tetraquarks, pentaquarks, dibaryons and up to the 12-body dibaryon-antidibaryon which completely fill the $1s$ orbital, in a unified manner, with the spinless LO Coulomb interaction and beyond. After treating the $c$ and $b$ quarks in various combinations, we delve a bit longer on $t$-quark bound states. We extend the negative result of Kuchiev, Flambaum and Shuryak on the 12-body topball to now include the NLO QCD potential. We find that none of the examined multitop states should have binding
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Jordan Awan, Ana Kenney, Matthew Reimherr et al. · 2019 · arXiv
The exponential mechanism is a fundamental tool of Differential Privacy (DP) due to its strong privacy guarantees and flexibility. We study its extension to settings with summaries based on infinite dimensional outputs such as with functional data analysis, shape analysis, and nonparametric statistics. We show that one can design the mechanism with respect to a specific base measure over the output space, such as a Guassian process. We provide a positive result that establishes a Central Limit Theorem for the exponential mechanism quite broadly. We also provide an apparent negative result, sho
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S. Albeverio, H. Gottschalk, J. -L. Wu · 2004 · arXiv
We construct Euclidean random fields $X$ over $\R^d$, by convoluting generalized white noise $F$ with some integral kernels $G$, as $X=G* F$. We study properties of Schwinger (or moment) functions of $X$. In particular, we give a general equivalent formulation of the cluster property in terms of truncated Schwinger functions which we then apply to the above fields. We present a partial negative result on the reflection positivity of convoluted generalized white noise. Furthermore, by representing the kernels $G_\a$ of the pseudo--differential operators $(-\D + m^2_0)^{-α}$ for $α\in (0,1)$ and
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Yechan Park, Yuya Sasaki · 2024 · arXiv
This paper addresses the challenge of estimating the Average Treatment Effect on the Treated Survivors (ATETS; Vikstrom et al., 2018) in the absence of long-term experimental data, utilizing available long-term observational data instead. We establish two theoretical results. First, it is impossible to obtain informative bounds for the ATETS with no model restriction and no auxiliary data. Second, to overturn this negative result, we explore as a promising avenue the recent econometric developments in combining experimental and observational data (e.g., Athey et al., 2020, 2019); we indeed fin
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Tian-Fu Chen, Jie-Hong R. Jiang · 2024 · arXiv
Boolean matching is an important problem in logic synthesis and verification. Despite being well-studied for conventional Boolean circuits, its treatment for reversible logic circuits remains largely, if not completely, missing. This work provides the first such study. Given two (black-box) reversible logic circuits that are promised to be matchable, we check their equivalences under various input/output negation and permutation conditions subject to the availability/unavailability of their inverse circuits. Notably, among other results, we show that the equivalence up to input negation and pe
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Michael Bekos, Stephen Kobourov, Michael Kaufmann et al. · 2014 · arXiv
Given an $n$-vertex graph $G$ and two positive integers $d,k \in \mathbb{N}$, the ($d,kn$)-differential coloring problem asks for a coloring of the vertices of $G$ (if one exists) with distinct numbers from 1 to $kn$ (treated as \emph{colors}), such that the minimum difference between the two colors of any adjacent vertices is at least $d$. While it was known that the problem of determining whether a general graph is ($2,n$)-differential colorable is NP-complete, our main contribution is a complete characterization of bipartite, planar and outerplanar graphs that admit ($2,kn$)-differential co
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Tobias Fissler, Yannick Hoga · 2024 · arXiv
This paper lays out a principled approach to compare copula forecasts via strictly consistent scores. We first establish the negative result that, in general, copulas fail to be elicitable, implying that copula predictions cannot sensibly be compared on their own. A notable exception is on Fréchet classes, that is, when the marginal distribution structure is given and fixed, in which case we give suitable scores for the copula forecast comparison. As a remedy for the general non-elicitability of copulas, we establish novel multi-objective scores for copula forecast along with marginal forecast
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