Negative / Null Result ReportOpen accessPhysics
Yuto Urano, Xue Mengsong, Kenji Watanabe et al. · 2023 · arXiv
We investigate the valley coherence in high and low-quality monolayer MoSe2 by polarization-resolved photoluminescence spectroscopy. The observed valley coherence is on the order of 10 % regardless of the sample quality, proving that the suppression of extrinsic effects does not improve the valley coherence. The valley decoherence time estimated based on the valley coherence time and exciton lifetime is sub-picosecond at the longest, which suggests that intrinsic scattering sources, such as phonons, strongly limit the valley coherence.
Negative / Null Result ReportOpen accessComputer Science
Jose A. R. Cembranos · 2010 · arXiv
There is a non-trivial four-derivative extension of the gravitational spectrum that is free of ghosts and phenomenologically viable. It is the so called $R^2$-gravity since it is defined by the only addition of a term proportional to the square of the scalar curvature. Just the presence of this term does not improve the ultraviolet behaviour of Einstein gravity but introduces one additional scalar degree of freedom that can account for the dark matter of our Universe.
Negative / Null Result ReportOpen accessComputer Science
Anant Sahai · 2007 · arXiv
The traditional information theoretic approach to studying feedback is to consider ideal instantaneous high-rate feedback of the channel outputs to the encoder. This was acceptable in classical work because the results were negative: Shannon pointed out that even perfect feedback often does not improve capacity and in the context of symmetric DMCs, Dobrushin showed that it does not improve the fixed block-coding error exponents in the interesting high rate regime. However, it has recently been shown that perfect feedback does allow great improvements in the asymptotic tradeoff between end-to-e
Negative / Null Result ReportOpen accessPhysics
G. Seibold · 2008 · arXiv
Based on the Kotliar-Ruckenstein slave-boson scheme we develop a configuration-interaction (CI) approach which is suitable to improve the energy of symmetry-broken saddle-point solutions. The theory is applied to spin-polaron states in the Hubbard model and compared with analogous results obtained within the Hartree-Fock approximation. In addition we show that within the infinite ${\cal D}$ prescription of the Gutzwiller method a CI approach does not improve the variational result since in the thermodynamic limit matrix elements between different inhomogeneous states vanish due to an 'orthogon
Negative / Null Result ReportOpen accessComputer Science
Moo-Sung Bae, Judith A. McGovern · 1995 · arXiv
Baryon magnetic moments are calculated in the colour-dielectric model with pion and kaon loops. The only free parameter of the model is determined from the nucleon isoscalar radius, and all SU(3) symmetry breaking, including that in the quark sector, is determined by mesonic masses and decay constants. Good agreement with experiment is obtained for the ratios of the magnetic moments, but the inclusion of kaons does not improve the results. The results obtained in this approach are significantly better than any that have been obtained in hedgehog-based models.
Negative / Null Result ReportOpen accessComputer Science
Weronika Ormaniec, Michael Vollenweider, Elisa Hoskovec · 2025 · arXiv
In this paper, we explore the idea of combining GCNs into one model. To that end, we align the weights of different models layer-wise using optimal transport (OT). We present and evaluate three types of transportation costs and show that the studied fusion method consistently outperforms the performance of vanilla averaging. Finally, we present results suggesting that model fusion using OT is harder in the case of GCNs than MLPs and that incorporating the graph structure into the process does not improve the performance of the method.
Negative / Null Result ReportOpen accessComputer Science
Olivier Landon-Cardinal, Beni Yoshida, David Poulin et al. · 2015 · arXiv
A two-dimensional topologically ordered quantum memory is well protected against error if the energy gap is large compared to the temperature, but this protection does not improve as the system size increases. We review and critique some recent proposals for improving the memory time by introducing long-range interactions among anyons, noting that instability with respect to small local perturbations of the Hamiltonian is a generic problem for such proposals. We also discuss some broader issues regarding the prospects for scalable quantum memory in two-dimensional systems.
Negative / Null Result ReportOpen accessComputer Science
Lav R. Varshney, Sanjoy K. Mitter, Vivek K Goyal · 2011 · arXiv
Given the possibility of communication systems failing catastrophically, we investigate limits to communicating over channels that fail at random times. These channels are finite-state semi-Markov channels. We show that communication with arbitrarily small probability of error is not possible. Making use of results in finite blocklength channel coding, we determine sequences of blocklengths that optimize transmission volume communicated at fixed maximum message error probabilities. We provide a partial ordering of communication channels. A dynamic programming formulation is used to show the st
Negative / Null Result ReportOpen accessComputer Science
Chloë Hebborn, Pierre Capel · 2017 · arXiv
Various corrections to the eikonal approximations are studied for two- and three-body nuclear collisions with the goal to extend the range of validity of this approximation to beam energies of 10 MeV/nucleon. Wallace's correction does not improve much the elastic-scattering cross sections obtained at the usual eikonal approximation. On the contrary, a semiclassical approximation that substitutes the impact parameter by a complex distance of closest approach computed with the projectile-target optical potential efficiently corrects the eikonal approximation. This opens the possibility to analyz
Negative / Null Result ReportOpen accessComputer Science
Stefano Rini · 2012 · arXiv
Proving capacity for networks without feedback or cooperation usually involves two fundamental random coding techniques: superposition coding and binning. Although conceptually very different, these two techniques often achieve the same performance, suggesting an underlying similarity. In this correspondence we propose a new random coding technique that generalizes superposition coding and binning and provides new insight on relationship among the two With this new theoretical tool, we derive new achievable regions for three classical information theoretical models: multi-access channel, broad
Negative / Null Result ReportOpen accessComputer Science
S. Pasini, G. S. Uhrig · 2008 · arXiv
We generalize the problem of the coherent control of small quantum systems to the case where the quantum bit (qubit) is subject to a fully general rotation. Following the ideas developed in Pasini et al (2008 Phys. Rev. A 77, 032315), the systematic expansion in the shortness of the pulse is extended to the case where the pulse acts on the qubit as a general rotation around an axis of rotation varying in time. The leading and the next-leading corrections are computed. For certain pulses we prove that the general rotation does not improve on the simpler rotation with fixed axis.
Negative / Null Result ReportOpen accessComputer Science
Ian Porada, Alessandro Sordoni, Jackie Chi Kit Cheung · 2021 · arXiv
Transformer models pre-trained with a masked-language-modeling objective (e.g., BERT) encode commonsense knowledge as evidenced by behavioral probes; however, the extent to which this knowledge is acquired by systematic inference over the semantics of the pre-training corpora is an open question. To answer this question, we selectively inject verbalized knowledge into the minibatches of a BERT model during pre-training and evaluate how well the model generalizes to supported inferences. We find generalization does not improve over the course of pre-training, suggesting that commonsense knowled
Negative / Null Result ReportOpen accessComputer Science
Mohamed S. Nafea, Karim G. Seddik, Mohammed Nafie et al. · 2012 · arXiv
In this work, we analyze the diversity gain region (DGR) of the single-antenna Rayleigh fading Z-Interference channel (ZIC). More specifically, we characterize the achievable DGR of the fixed-power split Han-Kobayashi (HK) approach under these assumptions. Our characterization comes in a closed form and demonstrates that the HK scheme with only a common message is a singular case, which achieves the best DGR among all HK schemes for certain multiplexing gains. Finally, we show that generalized time sharing, with variable rate and power assignments for the common and private messages, does not
Negative / Null Result ReportOpen accessComputer Science
Yunquan Dong, Zhengchuan Chen, Shanyun Liu et al. · 2018 · arXiv
We consider an M/M/1 update-and-decide system where Poisson distributed decisions are made based on the received updates. We propose to characterize the freshness of the received updates at decision epochs with Age upon Decisions (AuD). Under the first-come-first-served policy (FCFS), the closed form average AuD is derived. We show that the average AuD of the system is determined by the arrival rate and the service rate, and is independent of the decision rate. Thus, merely increasing the decision rate does not improve the timeliness of decisions. Nevertheless, increasing the arrival rate and
Negative / Null Result ReportOpen accessPhysics
M. H. S. Amin, Dmitri V. Averin, James A. Nesteroff · 2007 · arXiv
We have studied the decoherence properties of adiabatic quantum computation (AQC) in the presence of in general non-Markovian, e.g., low-frequency, noise. The developed description of the incoherent Landau-Zener transitions shows that the global AQC maintains its properties even for decoherence larger than the minimum gap at the anticrossing of the two lowest energy levels. The more efficient local AQC, however, does not improve scaling of the computation time with the number of qubits $n$ as in the decoherence-free case. The scaling improvement requires phase coherence throughout the computat
Negative / Null Result ReportMedicine
Hansen-Lewis J, Marcus M · 2025 · American economic journal. Economic policy
Maritime shipping emits as much fine particulate matter as half of global road traffic. We are the first to measure the consequences of US maritime emissions standards on air quality, human health, racial exposure disparities, and…
View details →DOI: 10.1257/pol.20220626 Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Alexander L. Brown, Daniel G. Stephenson, Rodrigo A. Velez · 2024 · arXiv
This paper experimentally evaluates four mechanisms intended to achieve the Uniform outcome in rationing problems (Sprumont, 1991). Our benchmark is the dominant-strategy, direct-revelation mechanism of the Uniform rule. A strategically equivalent mechanism that provides non-binding feedback during the reporting period greatly improves performance. A sequential revelation mechanism produces modest improvements despite not possessing dominant strategies. A novel, obviously strategy-proof mechanism, devised by Arribillaga et al. (2023), does not improve performance. We characterize each alternat
Negative / Null Result ReportOpen accessComputer Science
G. Chiribella, G. M. D'Ariano, P. Perinotti · 2008 · arXiv
A sequential network of quantum operations is efficiently described by its quantum comb, a non-negative operator with suitable normalization constraints. Here we analyze the case of networks enjoying symmetry with respect to the action of a given group of physical transformations, introducing the notion of covariant combs and testers, and proving the basic structure theorems for these objects. As an application, we discuss the optimal alignment of reference frames (without pre-established common references) with multiple rounds of quantum communication, showing that i) allowing an arbitrary am
Negative / Null Result ReportOpen accessComputer Science
M. Viviani, A. Kievsky, S. Rosati et al. · 2001 · arXiv
We present evidence that numerically accurate quantum calculations employing modern internucleon forces do not reproduce the proton analyzing power, A_y, for p-3He elastic scattering at low energies. These calculations underpredict new measured analyzing powers by approximately 30% at E_{c.m.} = 1.20 MeV and by 40% at E_{c.m.} = 1.69 MeV, an effect analogous to a well-known problem in p-d and n-d scattering. The calculations are performed using the complex Kohn variational principle and the (correlated) Hyperspherical Harmonics technique with full treatment of the Coulomb force. The inclusion
Negative / Null Result ReportOpen accessComputer Science
Pierre Epron, Adrien Coulet, Mehwish Alam · 2026 · arXiv
Despite their strong linguistic capabilities, Large Language Models (LLMs) are computationally demanding and require substantial resources for fine-tuning, which is unadapted to privacy and budget constraints of many healthcare settings. To address this, we present an experimental analysis focused on Biomedical Named Entity Recognition using lightweight LLMs, we evaluate the impact of different output formats on model performance. The results reveal that lightweight LLMs can achieve competitive performance compared to the larger models, highlighting their potential as lightweight yet effective
Negative / Null Result ReportOpen accessComputer Science
Isabel Segura-Bedmar · 2023 · arXiv
This paper describes our participation in SemEval-2023 Task 10, whose goal is the detection of sexism in social media. We explore some of the most popular transformer models such as BERT, DistilBERT, RoBERTa, and XLNet. We also study different data augmentation techniques to increase the training dataset. During the development phase, our best results were obtained by using RoBERTa and data augmentation for tasks B and C. However, the use of synthetic data does not improve the results for task C. We participated in the three subtasks. Our approach still has much room for improvement, especiall
Negative / Null Result ReportOpen accessComputer Science
Amir Homayounirad, Enrico Liscio, Tong Wang et al. · 2025 · arXiv
Aggregating multiple annotations into a single ground truth label may hide valuable insights into annotator disagreement, particularly in tasks where subjectivity plays a crucial role. In this work, we explore methods for identifying subjectivity in recognizing the human values that motivate arguments. We evaluate two main approaches: inferring subjectivity through value prediction vs. directly identifying subjectivity. Our experiments show that direct subjectivity identification significantly improves the model performance of flagging subjective arguments. Furthermore, combining contrastive l
Negative / Null Result ReportOpen accessComputer Science
Fahd Ahmed Khan, Kamel Tourki, Mohamed-Slim Alouini et al. · 2013 · arXiv
This paper studies the impact of using outdated channel state information for relay selection on the performance of a network where two sources communicate with each other via fixed-gain amplifyand- forward relays. For a Rayleigh faded channel, closed-form expressions for the outage probability, moment generating function and symbol error rate are derived. Simulations results are also presented to corroborate the derived analytical results. It is shown that adding relays does not improve the performance if the channel is substantially outdated. Furthermore, relay location is also taken into co
Negative / Null Result ReportOpen accessComputer Science
Matthew Aitchison · 2019 · arXiv
Although reinforcement learning has made great strides recently, a continuing limitation is that it requires an extremely high number of interactions with the environment. In this paper, we explore the effectiveness of reusing experience from the experience replay buffer in the Deep Q-Learning algorithm. We test the effectiveness of applying learning update steps multiple times per environmental step in the VizDoom environment and show first, this requires a change in the learning rate, and second that it does not improve the performance of the agent. Furthermore, we show that updating less fr
Negative / Null Result ReportOpen accessMathematics
Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin et al. · 2020 · arXiv
Many instances of algorithmic bias are caused by subpopulation shifts. For example, ML models often perform worse on demographic groups that are underrepresented in the training data. In this paper, we study whether enforcing algorithmic fairness during training improves the performance of the trained model in the \emph{target domain}. On one hand, we conceive scenarios in which enforcing fairness does not improve performance in the target domain. In fact, it may even harm performance. On the other hand, we derive necessary and sufficient conditions under which enforcing algorithmic fairness l
Negative / Null Result ReportOpen accessComputer Science
John S. Van Dyke, Zackary White, Gregory Quiroz · 2024 · arXiv
Zero-noise extrapolation (ZNE), a technique to estimate quantum circuit expectation values through noise scaling and extrapolation, is well-studied in the context of quantum computing. We examine the applicability of ZNE to the field of quantum sensing. Focusing on the problem of DC magnetometry using the Ramsey protocol, we show that the sensitivity (in the sense of the minimum detectable signal) does not improve upon using ZNE in the slope detection scheme. On the other hand, signals of sufficiently large magnitude can be estimated more accurately. Our results are robust across various noise
Negative / Null Result ReportOpen accessComputer Science
Baruch Lubinsky, Bekir Genc, Tshilidzi Marwala · 2008 · arXiv
Neural networks are powerful tools for classification and regression in static environments. This paper describes a technique for creating an ensemble of neural networks that adapts dynamically to changing conditions. The model separates the input space into four regions and each network is given a weight in each region based on its performance on samples from that region. The ensemble adapts dynamically by constantly adjusting these weights based on the current performance of the networks. The data set used is a collection of financial indicators with the goal of predicting the future platinu
Negative / Null Result ReportOpen accessComputer Science
Shouman Das, Syed A. Haque, Md. Iftekhar Tanveer · 2021 · arXiv
\emph{Topological data analysis} (TDA) has recently emerged as a new technique to extract meaningful discriminitve features from high dimensional data. In this paper, we investigate the possibility of applying TDA to improve the classification accuracy of public speaking rating. We calculated \emph{persistence image vectors} for the sentence embeddings of TEDtalk data and feed this vectors as additional inputs to our machine learning models. We have found a negative result that this topological information does not improve the model accuracy significantly. In some cases, it makes the accuracy
Negative / Null Result ReportOpen accessComputer Science
Hayato Arai, Yuuya Yoshida, Masahito Hayashi · 2019 · arXiv
We address perfect discrimination of two separable states. When available states are restricted to separable states, we can theoretically consider a larger class of measurements than the class of measurements allowed in quantum theory. The framework composed of the class of separable states and the above extended class of measurements is a typical example of general probabilistic theories. In this framework, we give a necessary and sufficient condition to discriminate two separable pure states perfectly. In particular, we derive measurements explicitly to discriminate two separable pure states
Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance
Michael Pedersen · 2024 · arXiv
The present study applies observations of individual predictions of the first three releases of the US output growth rate to evaluate how the applied judgment affects prediction efficiency and accuracy as well as if judgment is persistent. While the first two issues have been assessed in other studies, there is little evidence on the formation of judgment in macroeconomic projections. Most of the forecasters produce unbiased predictions, but employing the median Bloomberg projection as baseline, it turns out that judgment generally does not improve accuracy. There seems to be persistence in th
