Tootfinder

This https://arxiv.org/abs/2402.08551 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Nonstabilizerness of Permutationally Invariant Systems
Typical measures of nonstabilizerness of a system of $N$ qubits require computing $4^N$ expectation values, one for each Pauli string in the Pauli group, over a state of dimension $2^N$. For permutationally invariant systems, this exponential overhead can be reduced to just $O(N^3)$ expectation values on a state with a dimension $O(N)$. We exploit this simplification to study the nonstabilizerness phase transitions of systems with hundreds of qubits.

What is your expectation for the COMMERCIAL success of Starlink?

NFL Insider Gives Shocking Update On Cowboys’ Dak Prescott https://www.yardbarker.com/nfl/articles/nfl_insider_gives_shocking_update_on_cowboys_dak_prescott/s1_17150_40059501

NFL Insider Gives Shocking Update On Cowboys’ Dak Prescott
Dallas Cowboys quarterback Dak Prescott is entering the final year of his deal, and the general expectation is that the Cowboys will ultimately give him an extension this offseason. There are more reasons than one for Dallas to do just that. Of course, the primary cause is to keep Prescott locked up for the long haul. He just led the NFL with 36 touchdown passes and finished second in MVP voting, so in spite of his lack of playoff success, he has proven that he can be a franchise quarterback. B…

NFL Writer Makes Surprising Prediction For Raiders’ QB Competition https://www.yardbarker.com/nfl/articles/nfl_writer_makes_surprising_prediction_for_raiders_qb_competition/s1_17150_40330904

NFL Writer Makes Surprising Prediction For Raiders’ QB Competition
The general expectation is that Aidan O’Connell will enter the season as the Las Vegas Raiders‘ starting quarterback. O’Connell replaced Jimmy Garoppolo as the starter last year, and while he certainly had some growing pains, he ended the 2023 campaign on a high note, throwing eight touchdowns and no interceptions over his last four games. However, Cody Benjamin of CBS Sports thinks O’Connell will begin 2024 on the bench and is projecting that free-agent addition Gardner Minshew will be…

This https://arxiv.org/abs/2309.14246 has been replaced.
link: https://scholar.google.com/scholar?q=a

Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning
Deployment in hazardous environments requires robots to understand the risks associated with their actions and movements to prevent accidents. Despite its importance, these risks are not explicitly modeled by currently deployed locomotion controllers for legged robots. In this work, we propose a risk sensitive locomotion training method employing distributional reinforcement learning to consider safety explicitly. Instead of relying on a value expectation, we estimate the complete value distrib…

Sources: the expectation at Paramount Global is that neither of the two offers in play, Skydance-RedBird and Sony Pictures-Apollo, will come to fruition (Todd Spangler/Variety)
https://variety.com/2024/biz/news/paramount-global-rej…

Paramount Global May Not Skydance, Sony-Apollo M&A Offers
After months of M&A talks, Paramount Global and controlling shareholder Shari Redstone might be going it alone after all.

The user shares their experience of bombing their final interview with a company after two successful rounds. Despite no expectation of technical questions, they froze when asked, only remembering the answers post-interview. They seek others' experiences and coping strategies. https://reddit.com/r/cybersecurity/comments/1cjoyj4/

General Procedure to Provide High-Probability Guarantees for Stochastic Saddle Point Problems
Dongyang Li, Haobin Li, Junyu Zhang
https://arxiv.org/abs/2405.03219

General Procedure to Provide High-Probability Guarantees for Stochastic Saddle Point Problems
This paper considers smooth strongly convex and strongly concave (SC-SC) stochastic saddle point (SSP) problems. Suppose there is an arbitrary oracle that in expectation returns an $ε$-solution in the sense of certain gaps, which can be the duality gap or its weaker variants. We propose a general PB-SSP framework to guarantee an $ε$ small duality gap solution with high probability via only $\mathcal{O}\big(\log \frac{1}{p}\cdot\text{poly}(\log κ)\big)$ calls of this oracle, where $p\in(0,1)$…

This https://arxiv.org/abs/2401.07347 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Neutrino-antineutrino Asymmetry of C$ν$B on the Surface of the Round Earth
It has been claimed that the coherent scattering of relic neutrinos with the Earth will result in a neutrino-antineutrino asymmetry of $\mathcal{O}(10^{-4})$ on the Earth surface, which is five orders of magnitude larger than the naive model expectation. In this work we show that this overdensity was overestimated for the perfectly round Earth by solving the exact solution with partial waves. The maximal asymmetry after summing over all the angular modes is only around $10^{-8}$ above the groun…

my expectation about what will happen was right, it seems.

This https://arxiv.org/abs/2402.14791 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Amplified Amplitude Estimation: Exploiting Prior Knowledge to Improve Estimates of Expectation Values
We provide a method for estimating the expectation value of an operator that can utilize prior knowledge to accelerate the learning process on a quantum computer. Specifically, suppose we have an operator that can be expressed as a concise sum of projectors whose expectation values we know a priori to be $O(ε)$. In that case, we can estimate the expectation value of the entire operator within error $ε$ using a number of quantum operations that scales as $O(1/\sqrtε)$. We then show how this c…

Expectation Entropy as a Password Strength Metric
Khan Reaz, Gerhard Wunder
https://arxiv.org/abs/2404.16853 https://arxiv.org/pdf/24…

Expectation Entropy as a Password Strength Metric
The classical combinatorics-based password strength formula provides a result in tens of bits, whereas the NIST Entropy Estimation Suite give a result between 0 and 1 for Min-entropy. In this work, we present a newly developed metric -- Expectation entropy that can be applied to estimate the strength of any random or random-like password. Expectation entropy provides the strength of a password on the same scale as an entropy estimation tool. Having an 'Expectation entropy' of a certain value, f…

Chargers' Joey Bosa says 'expectation' is for Jim Harbaugh to turn team around: 'All he wants to do is win'

https://www.cbssport…

Chargers' Joey Bosa says 'expectation' is for Jim Harbaugh to turn team around: 'All he wants to do is win'
Bosa said Harbaugh is 'genuine' and 'loves football more than anything

NFL Insider Gives Shocking Update On Cowboys’ Dak Prescott https://www.yardbarker.com/nfl/articles/nfl_insider_gives_shocking_update_on_cowboys_dak_prescott/s1_17150_40059501

NFL Insider Gives Shocking Update On Cowboys’ Dak Prescott
Dallas Cowboys quarterback Dak Prescott is entering the final year of his deal, and the general expectation is that the Cowboys will ultimately give him an extension this offseason. There are more reasons than one for Dallas to do just that. Of course, the primary cause is to keep Prescott locked up for the long haul. He just led the NFL with 36 touchdown passes and finished second in MVP voting, so in spite of his lack of playoff success, he has proven that he can be a franchise quarterback. B…

This https://arxiv.org/abs/2208.05316 has been replaced.
link: https://scholar.google.com/scholar?q=a

Welfare ordering of voting weight allocations
This paper studies the allocation of voting weights in a committee representing groups of different sizes. We introduce a partial ordering of weight allocations based on stochastic comparison of social welfare. We show that when the number of groups is sufficiently large, this ordering asymptotically coincides with the total ordering induced by the cosine proportionality between the weights and the group sizes. A corollary is that a class of expectation-form objective functions, including expec…

I'm getting the Gita's "Perform action without expectation of its fruits" tattooed on my inner right arm either in Sanskrit or Tamil.

I have decided, as a #selfhost with just two other people on my instance, that I'm going to limit threads.net following the example of @… quoted below. I didn't know that you can “unlimit” specific accounts! This is an interesting option.
For other a…

This https://arxiv.org/abs/2301.01726 has been replaced.
link: https://scholar.google.com/scholar?q=a

Anisotropic Quantum Hall Droplets
We study two-dimensional (2D) droplets of noninteracting electrons in a strong magnetic field, placed in a confining potential with arbitrary shape. Using semiclassical methods adapted to the lowest Landau level, we obtain near-Gaussian energy eigenstates that are localized on level curves of the potential and have a position-dependent height. This one-particle insight allows us to deduce explicit formulas for expectation values of local many-body observables, such as density and current, in th…

An Expectation-Maximization Relaxed Method for Privacy Funnel
Lingyi Chen, Jiachuan Ye, Shitong Wu, Huihui Wu, Hao Wu, Wenyi Zhang
https://arxiv.org/abs/2405.00616

An Expectation-Maximization Relaxed Method for Privacy Funnel
The privacy funnel (PF) gives a framework of privacy-preserving data release, where the goal is to release useful data while also limiting the exposure of associated sensitive information. This framework has garnered significant interest due to its broad applications in characterization of the privacy-utility tradeoff. Hence, there is a strong motivation to develop numerical methods with high precision and theoretical convergence guarantees. In this paper, we propose a novel relaxation variant …

The user shares their experience of bombing their final interview with a company after two successful rounds. Despite no expectation of technical questions, they froze when asked, only remembering the answers post-interview. They seek others' experiences and coping strategies. https://reddit.com/r/cybersecurity/comments/1cjoyj4/

This https://arxiv.org/abs/2309.14380 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

The Possibility of Tachyons as Soliton Solutions in 3+1 Dimensions via k-field Models
Tachyons or hypothetical faster-than-light (FTL) particles would fail the principle of causality. Such particles may only be imagined when they have no energy and momentum and, thus, no observable interaction. In this paper, we show that the classical relativistic field theory with non-standard Lagrangian densities (k-field models) does not rule out the existence of FTL particle-like solutions (solitons) with zero energy and momentum in 3+1 dimensions. However, contrary to our expectation, we s…

This https://arxiv.org/abs/2308.03431 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Approximate propagation of normal distributions for stochastic optimal control of nonsmooth systems
We present a method for the approximate propagation of mean and covariance of a probability distribution through ordinary differential equations (ODE) with discontinous right-hand side. For piecewise affine systems, a normalization of the propagated probability distribution at every time step allows us to analytically compute the expectation integrals of the mean and covariance dynamics while explicitly taking into account the discontinuity. This leads to a natural smoothing of the discontinuit…

Piecewise Linear Expectation Analysis via $k$-Induction for Probabilistic Programs
Tengshun Yang, Hongfei Fu, Jingyu Ke, Naijun Zhan, Shiyang Wu
https://arxiv.org/abs/2403.17567 <…

Piecewise Linear Expectation Analysis via $k$-Induction for Probabilistic Programs
Quantitative analysis of probabilistic programs aims at deriving tight numerical bounds for probabilistic properties such as expectation and assertion probability, and plays a crucial role in the verification of probabilistic programs. Along this line of research, most existing works consider numerical bounds over the whole state space monolithically and do not consider piecewise bounds. Clearly, monolithic bounds are either conservative, or not expressive and succinct enough in general. To der…

Cowboys’ DeMarvion Overshown Gives Injury Update On Himself https://www.yardbarker.com/nfl/articles/cowboys_demarvion_overshown_gives_injury_update_on_himself/s1_17150_40062717

Cowboys’ DeMarvion Overshown Gives Injury Update On Himself
When the Dallas Cowboys took linebacker DeMarvion Overshown in the third round of the NFL Draft last spring, the expectation was that he would be a significant contributor to the team’s defense. Instead, he ended up tearing his ACL in his second preseason game, thus ending his rookie campaign before it even began. Last week, Cowboys executive vice president Stephen Jones said that Overshown will likely be ready for training camp, and on Tuesday, the University of Texas product provided an upd…

This https://arxiv.org/abs/2401.07347 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Neutrino-antineutrino Asymmetry of C$ν$B on the Surface of the Round Earth
It has been claimed that the coherent scattering of relic neutrinos with the Earth will result in a neutrino-antineutrino asymmetry of $\mathcal{O}(10^{-4})$ on the Earth surface, which is five orders of magnitude larger than the naive model expectation. In this work we show that this overdensity was overestimated for the perfectly round Earth by solving the exact solution with partial waves. The maximal asymmetry after summing over all the angular modes is only around $10^{-8}$ above the groun…

The pizzelle maker died after only 10 pizzelle. No idea what happened. Got two more decent ones then two spongy discards.
Grabbed the vafler maker to try to salvage the rest of the batch. Dry chocolate Norwegian waffles were my expectation.
I got oddly puffy pizzelle hearts (roughly four pizzelle to a waffle). Frankly, an experiment I’ve always wanted to try (but I still want my pizzelle maker back).

#Excess_Mortality
In our quest for a fair expectation of mortality in the absence of respiratory disease and heat waves, let's be a bit presumptuous and heuristically unscientific, and end with a prediction.
Let's consider summer months medians from weeks 17-38 (Mai-Sept).

GCEPNet: Graph Convolution-Enhanced Expectation Propagation for Massive MIMO Detection
Qincheng Lu, Sitao Luan, Xiao-Wen Chang
https://arxiv.org/abs/2404.14886

GCEPNet: Graph Convolution-Enhanced Expectation Propagation for Massive MIMO Detection
Massive MIMO (multiple-input multiple-output) detection is an important topic in wireless communication and various machine learning based methods have been developed recently for this task. Expectation propagation (EP) and its variants are widely used for MIMO detection and have achieved the best performance. However, EP-based solvers fail to capture the correlation between unknown variables, leading to loss of information, and in addition, they are computationally expensive. In this paper, we…

This https://arxiv.org/abs/2211.13289 has been replaced.
link: https://scholar.google.com/scholar?q=a

Shapley Curves: A Smoothing Perspective
This paper fills the limited statistical understanding of Shapley values as a variable importance measure from a nonparametric (or smoothing) perspective. We introduce population-level \textit{Shapley curves} to measure the true variable importance, determined by the conditional expectation function and the distribution of covariates. Having defined the estimand, we derive minimax convergence rates and asymptotic normality under general conditions for the two leading estimation strategies. For …

"Lately I’ve started to argue that we should never refer to single projects as mutual aid. After all, mutual aid describes a relationship, it is a pattern that stretches across entire ecosystems. And it’s one of the most revolutionary concepts and practices at the heart of anarchism, and of stateless societies throughout history. With the explosion of “mutual aid projects” in the wake of the pandemic, it’s only healthy to worry about leftists1 and NGOs stealing the word from us and watering it down into a hip new form of charity, the way they systematically try to steal subversive concepts from us and pacify them, stabilize them, as they’re doing with transformative justice and abolition, intersectional and queer, as they did a long time ago with socialism (which referred to all currents of anticapitalism, until 1876 when a certain academic broke solidarity and destroyed a growing tool of internationalist organizing to keep from losing control over it...)
[...]
Scarcity and lack of care make us afraid in a way that roots deeply in our bodies and hearts. If we find something free, we take it, maybe we take a whole lot of it so we can stockpile, and we don’t look back. And we’ll take it again and again and again—whether it’s food or love or medical supplies or respect—before we notice the expectation that there isn’t going to be any tomorrow, the deep-seated belief that we don’t deserve this thing… before we’re able to stop, and turn around, and notice the person taking care of us, and give back."

Reflections on #MayDay, #MutualAid and #DisabilityJustice by @….
https://petergelderloos.substack.com/p/may-day

Syntactic Robustness for LLM-based Code Generation
Laboni Sarker, Mara Downing, Achintya Desai, Tevfik Bultan
https://arxiv.org/abs/2404.01535 https://

Syntactic Robustness for LLM-based Code Generation
Rapid advances in the field of Large Language Models (LLMs) have made LLM-based code generation an important area for investigation. An LLM-based code generator takes a prompt as input and produces code that implements the requirements specified in the prompt. Many software requirements include mathematical formulas that specify the expected behavior of the code to be generated. Given a code generation prompt that includes a mathematical formula, a reasonable expectation is that, if the formula…

Expectation Maximization Aided Modified Weighted Sequential Energy Detector for Distributed Cooperative Spectrum Sensing
Mohammed Rashid, Jeffrey A. Nanzer
https://arxiv.org/abs/2403.19556

Expectation Maximization Aided Modified Weighted Sequential Energy Detector for Distributed Cooperative Spectrum Sensing
Distributed cooperative spectrum sensing usually involves a group of unlicensed secondary users (SUs) collaborating to detect the primary user (PU) in the channel, and thereby opportunistically utilize it without causing interference to the PU. The conventional energy detector (ED) based spectrum sensing ignores the dynamic nature of the PU by using energy statistic only from the present sensing interval for the PU detection. However, for a dynamic PU, previous studies have shown that improved …

This https://arxiv.org/abs/2309.14380 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

The Possibility of Tachyons as Soliton Solutions in 3+1 Dimensions via k-field Models
Tachyons or hypothetical faster-than-light (FTL) particles would fail the principle of causality. Such particles may only be imagined when they have no energy and momentum and, thus, no observable interaction. In this paper, we show that the classical relativistic field theory with non-standard Lagrangian densities (k-field models) does not rule out the existence of FTL particle-like solutions (solitons) with zero energy and momentum in 3+1 dimensions. However, contrary to our expectation, we s…

This https://arxiv.org/abs/2211.14925 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Turbulent Fluid Mechanics via Nonlinear 'Mixing' of Smooth Velocity Flows With Weighted Random Fields: Stochastically Averaged Navier-Stokes Equations and Velocity Correlations
Let $\mathfrak{D}\subset\mathbb{R}^{3}$, with ${Vol}(\mathfrak{D})\sim L^{3}$, contain an incompressible fluid of viscosity $ν$ and velocity $\mathrm{U}_{i}(x,t)$ with $(x,t)\in\mathfrak{D}\times[0,\infty)$, satisfying the Navier-Stokes equations with some boundary conditions on $\partial\mathfrak{D}$ and evolving from initial Cauchy data. Now let $\mathscr{B}(x)$ be a Gaussian random field defined for all $x\in\mathfrak{D}$ with expectation $\mathbb{I\!E}\langle\mathscr{B}(x)\rangle=0$, and a…

Piecewise Linear Expectation Analysis via $k$-Induction for Probabilistic Programs
Tengshun Yang, Hongfei Fu, Jingyu Ke, Naijun Zhan, Shiyang Wu
https://arxiv.org/abs/2403.17567 <…

Piecewise Linear Expectation Analysis via $k$-Induction for Probabilistic Programs
Quantitative analysis of probabilistic programs aims at deriving tight numerical bounds for probabilistic properties such as expectation and assertion probability, and plays a crucial role in the verification of probabilistic programs. Along this line of research, most existing works consider numerical bounds over the whole state space monolithically and do not consider piecewise bounds. Clearly, monolithic bounds are either conservative, or not expressive and succinct enough in general. To der…

Algorithmic Randomness, Effective Disintegrations, and Rates of Convergence to the Truth
Simon M. Huttegger, Sean Walsh, Francesca Zaffora Blando
https://arxiv.org/abs/2403.19978 …

Algorithmic Randomness, Effective Disintegrations, and Rates of Convergence to the Truth
Lévy's Upward Theorem says that the conditional expectation of an integrable random variable converges with probability one to its true value with increasing information. In this paper, we use methods from effective probability theory to characterise the probability one set along which convergence to the truth occurs, and the rate at which the convergence occurs. We work within the setting of computable probability measures defined on computable Polish spaces and introduce a new general theory…

This https://arxiv.org/abs/2401.09998 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On the anti-concentration functions of some familiar families of distributions
Let $\{X_α\}$ be a family of random variables following a certain type of distributions with finite expectation $\mathbf{E}[X_α]$ and finite variance ${\rm Var}(X_α)$, where $α$ is a parameter. Motivated by the recent paper of Hollom and Portier (arXiv: 2306.07811v1), we study the anti-concentration function $(0, \infty)\ni y\to \inf_α\mathbf{P}\left(|X_α-\mathbf{E}[X_α]|\geq y \sqrt{{\rm Var}(X_α)}\right)$ and find its explicit expression. We show that, for certain familiar f…

There is a ton of software that is *almost* the same as some other piece of software.
It might use the same syntax/API but entirely different under the hood code, or maybe it's the same code but distributed with a different set of tools.
While this seems great, the not-exactly-identical experience causes an expectation problem.
"Great, I don't have to learn" is almost always followed by "This sucks because it's not 100% the same"
Sorry…

Ultralight Primordial Black Holes
Stefano Profumo
https://arxiv.org/abs/2405.00546 https://arxiv.org/pdf/2405.00546

Ultralight Primordial Black Holes
The fate of ultralight black holes depends on whether or not evaporation stops at or around the Planck scale. If evaporation stops, the general expectation is that a population of Planck-scale will be left over, possibly including a significant fraction of electrically charged relics. If evaporation does not stop, a runaway "explosion" would occur, with significant and potentially detectable high-energy emission. Here, I review both possibilities, with an emphasis on current status and future d…

Statistical Inference on the Cumulative Distribution Function using Judgment Post Stratification
Mina Azizi Kouhanestani, Ehsan Zamanzade, Sareh Goli
https://arxiv.org/abs/2405.01072

Statistical Inference on the Cumulative Distribution Function using Judgment Post Stratification
In this work, we discuss a general class of the estimators for the cumulative distribution function (CDF) based on judgment post stratification (JPS) sampling scheme which includes both empirical and kernel distribution functions. Specifically, we obtain the expectation of the estimators in this class and show that they are asymptotically more efficient than their competitors in simple random sampling (SRS), as long as the rankings are better than random guessing. We find a mild condition that …

Computation of the expectation value of the spin operator $\hat{S}^2$ for the Spin-Flip Bethe-Salpeter Equation
Bradford A. Barker, Arabi Seshappan, David A. Strubbe
https://arxiv.org/abs/2402.17719

Computation of the expectation value of the spin operator $\hat{S}^2$ for the Spin-Flip Bethe-Salpeter Equation
Spin-flip methods applied to excited-state approaches like the Bethe-Salpeter Equation allow access to the excitation energies of open-shell systems, such as molecules and defects in solids. The eigenstates of these solutions, however, are generally not eigenstates of the spin operator $\hat{S}^2$. Even for simple cases where the excitation vector is expected to be, for example, a triplet state, the value of $\langle \hat{S}^2 \rangle$ may be found to differ from 2.00; this difference is called…

This https://arxiv.org/abs/2306.09893 has been replaced.
initial toot: https://mastoxiv.page/@…

Density and current statistics in boundary-driven monitored fermionic chains
We consider a one-dimensional system of non-interacting fermions featuring both boundary driving and continuous monitoring of the bulk particle density. Due to the measurements, the expectation values of the local density and current operators are random variables whose average behavior is described by a well studied Lindblad master equation. By means of exact numerical computations, we go beyond the averaged dynamics and study their full probability distribution functions, focusing on the late…

Expectation Values of Conserved Charges in Integrable Quantum Field Theories out of Thermal Equilibrium
Michele Mazzoni, Riccardo Travaglino, Olalla A. Castro-Alvaredo
https://arxiv.org/abs/2402.14788

Expectation Values of Conserved Charges in Integrable Quantum Field Theories out of Thermal Equilibrium
In this work we present a computation of the averages of conserved charge densities and currents of (1+1)-dimensional Integrable Quantum Field Theories in Generalised Gibbs Ensembles. Our approach is based on the quasi-particle description provided by the Thermodynamic Bethe Ansatz combined with the principles of Generalised Hydrodynamics, and we focus on Non-Equilibrium Steady State averages. When considering the ultraviolet (i.e. high temperature) limit of such averages, we recover the famous…

"Lately I’ve started to argue that we should never refer to single projects as mutual aid. After all, mutual aid describes a relationship, it is a pattern that stretches across entire ecosystems. And it’s one of the most revolutionary concepts and practices at the heart of anarchism, and of stateless societies throughout history. With the explosion of “mutual aid projects” in the wake of the pandemic, it’s only healthy to worry about leftists1 and NGOs stealing the word from us and watering it down into a hip new form of charity, the way they systematically try to steal subversive concepts from us and pacify them, stabilize them, as they’re doing with transformative justice and abolition, intersectional and queer, as they did a long time ago with socialism (which referred to all currents of anticapitalism, until 1876 when a certain academic broke solidarity and destroyed a growing tool of internationalist organizing to keep from losing control over it...)
[...]
Scarcity and lack of care make us afraid in a way that roots deeply in our bodies and hearts. If we find something free, we take it, maybe we take a whole lot of it so we can stockpile, and we don’t look back. And we’ll take it again and again and again—whether it’s food or love or medical supplies or respect—before we notice the expectation that there isn’t going to be any tomorrow, the deep-seated belief that we don’t deserve this thing… before we’re able to stop, and turn around, and notice the person taking care of us, and give back."

Reflections on #MayDay, #MutualAid and #DisabilityJustice by @….
https://petergelderloos.substack.com/p/may-day

Handling Reward Misspecification in the Presence of Expectation Mismatch
Sarath Sreedharan, Malek Mechergui
https://arxiv.org/abs/2404.08791 https://

Handling Reward Misspecification in the Presence of Expectation Mismatch
Detecting and handling misspecified objectives, such as reward functions, has been widely recognized as one of the central challenges within the domain of Artificial Intelligence (AI) safety research. However, even with the recognition of the importance of this problem, we are unaware of any works that attempt to provide a clear definition for what constitutes (a) misspecified objectives and (b) successfully resolving such misspecifications. In this work, we use the theory of mind, i.e., the hu…

"If the anomaly does not stabilize by August—a reasonable expectation based on previous #ElNiño—then we will be in uncharted territory. It could imply that a warming planet is already fundamentally altering how the climate system operates, sooner than anticipated. It could also mean that statistical inferences based on past events are less reliable than we thought, adding more uncertainty t…

Climate models can’t explain 2023’s huge heat anomaly — we could be in uncharted territory
Taking into account all known factors, the planet warmed 0.2 °C more last year than climate scientists expected. More and better data are urgently needed.

Amplified Amplitude Estimation: Exploiting Prior Knowledge to Improve Estimates of Expectation Values
Sophia Simon, Matthias Degroote, Nikolaj Moll, Raffaele Santagati, Michael Streif, Nathan Wiebe
https://arxiv.org/abs/2402.14791

Amplified Amplitude Estimation: Exploiting Prior Knowledge to Improve Estimates of Expectation Values
We provide a method for estimating the expectation value of an operator that can utilize prior knowledge to accelerate the learning process on a quantum computer. Specifically, suppose we have an operator that can be expressed as a concise sum of projectors whose expectation values we know a priori to be $O(ε)$. In that case, we can estimate the expectation value of the entire operator within error $ε$ using a number of quantum operations that scales as $O(1/\sqrtε)$. We then show how this c…

FEDQ-Trust: Efficient Data-Driven Trust Prediction for Mobile Edge-Based IoT Systems
Jiahui Bai, Hai Dong, Athman Bouguettaya
https://arxiv.org/abs/2404.18356

FEDQ-Trust: Efficient Data-Driven Trust Prediction for Mobile Edge-Based IoT Systems
We introduce FEDQ-Trust, an innovative data-driven trust prediction approach designed for mobile edge-based Internet of Things (IoT) environments. The decentralized nature of mobile edge environments introduces challenges due to variations in data distribution, impacting the accuracy and training efficiency of existing distributed data-driven trust prediction models. FEDQ-Trust effectively tackles the statistical heterogeneity challenges by integrating Federated Expectation-Maximization with De…

Dak Prescott ‘Confident’ About Getting Extension Done With Cowboys https://www.yardbarker.com/nfl/articles/dak_prescott_confident_about_getting_extension_done_with_cowboys/s1_17039_40057110

Dak Prescott ‘Confident’ About Getting Extension Done With Cowboys
Dak Prescott told reporters at a Children’s Cancer Fund event on Monday that he’s “confident” in getting an extension done with the Cowboys this offseason.  “I’m definitely confident, obviously it helps the team and it’s important for the numbers. I’ve heard Jerry say that. This is a process, both sides understand that. Everything is great. It will happen,” Prescott said, per Calvin Watkins.  Prescott is set to count nearly $60 million toward the cap in 2024, so the expectat…

Conformal Risk Control for Ordinal Classification
Yunpeng Xu, Wenge Guo, Zhi Wei
https://arxiv.org/abs/2405.00417 https://arxiv.org/p…

Conformal Risk Control for Ordinal Classification
As a natural extension to the standard conformal prediction method, several conformal risk control methods have been recently developed and applied to various learning problems. In this work, we seek to control the conformal risk in expectation for ordinal classification tasks, which have broad applications to many real problems. For this purpose, we firstly formulated the ordinal classification task in the conformal risk control framework, and provided theoretic risk bounds of the risk control…

Search for heavy neutral Higgs bosons decaying into a top quark pair in 140 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV with the ATLAS detector
ATLAS Collaboration
https://arxiv.org/abs/2404.18986 https://arxiv.org/pdf/2404.18986
arXiv:2404.18986v1 Announce Type: new
Abstract: A search for heavy pseudo-scalar ($A$) and scalar ($H$) Higgs bosons decaying into a top-quark pair ($t\bar{t}$) has been performed with 140 fb$^{-1}$ of proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider at a centre-of-mass energy of $\sqrt{s}=13$ TeV. Interference effects between the signal process and Standard Model (SM) $t\bar{t}$ production are taken into account. Final states with exactly one or exactly two electrons or muons are considered. No significant deviation from the SM prediction is observed. The results of the search are interpreted in the context of a two-Higgs-doublet model (2HDM) of type II in the alignment limit with mass-degenerate pseudo-scalar and scalar Higgs bosons ($m_A = m_H$) and the hMSSM parameterisation of the minimal supersymmetric extension of the Standard Model. Ratios of the two vacuum expectation values, $\tan\beta$, smaller than 3.49 (3.16) are excluded at 95% confidence level for $m_A = m_H = 400$ GeV in the 2HDM (hMSSM). Masses up to 1240 GeV are excluded for the lowest tested $\tan\beta$ value of 0.4 in the 2HDM. In the hMSSM, masses up to 950 GeV are excluded for $\tan\beta=1.0$. In addition, generic exclusion limits are derived separately for single scalar and pseudo-scalar states for different choices of their mass and total width.

The cultural event you've been waiting your entire life for! The thills! The chills! The awesome expectation of delays! The regretting of the inconvenience! 😏
https://wjla.com/news/local/metro-unve

Metro unveils new 8000 series trains during Fleet of the Future Expo on National Mall
Starting Wednesday, March 20 and lasting through April 3, the public can tour a mock-up of what Metro expects its future 8000 series train cars to look like.

Peer Expectation in Robust Forecast Aggregation: The Possibility/Impossibility
Yuqing Kong
https://arxiv.org/abs/2402.06062 https://a…

Peer Expectation in Robust Forecast Aggregation: The Possibility/Impossibility
Recently a growing literature study a new forecast aggregation setting where each forecaster is additionally asked ``what's your expectation for the average of other forecasters' forecasts?''. However, most theoretic results in this setting focus on the scenarios where the additional second-order information helps optimally aggregate the forecasts. Here we adopt an adversarial approach and follow the robust forecast aggregation framework proposed by Arielia, Babichenkoa, and Smorodinsky 2018. W…

Github wants me to know I have unread notifications. I apparently have one item that I'm mentioned and participating in, but it's not one of the "1-0" notifications it lists among my inbox's one message. No matter how I change the filters or views, I cannot see this one message.
I even waited for a while to get more messages on the expectation that that would reset my counter. Nope.
Have others experienced this? Does anybody have a solution?

Network Intent Decomposition and Optimization for Energy-Aware Radio Access Network
Yao Wang, Yijun Yu, Yexing Li, Dong Li, Xiaoxue Zhao, Chungang Yang
https://arxiv.org/abs/2404.18386

Network Intent Decomposition and Optimization for Energy-Aware Radio Access Network
With recent advancements in the sixth generation (6G) communication technologies, more vertical industries have encountered diverse network services. How to reduce energy consumption is critical to meet the expectation of the quality of diverse network services. In particular, the number of base stations in 6G is huge with coupled adjustable network parameters. However, the problem is complex with multiple network objectives and parameters. Network intents are difficult to map to individual net…

First-Fit Coloring of Forests in Random Arrival Model
Bart{\l}omiej Bosek, Grzegorz Gutowski, Micha{\l} Laso\'n, Jakub Przyby{\l}o
https://arxiv.org/abs/2404.17011

First-Fit Coloring of Forests in Random Arrival Model
We consider a graph coloring algorithm that processes vertices in order taken uniformly at random and assigns colors to them using First-Fit strategy. We show that this algorithm uses, in expectation, at most $(\frac{1}{2} + o(1))\cdot \ln n \,/\, \ln\ln n$ different colors to color any forest with $n$ vertices. We also construct a family of forests that shows that this bound is best possible.

Algorithmic Randomness, Effective Disintegrations, and Rates of Convergence to the Truth
Simon M. Huttegger, Sean Walsh, Francesca Zaffora Blando
https://arxiv.org/abs/2403.19978 …

Algorithmic Randomness, Effective Disintegrations, and Rates of Convergence to the Truth
Lévy's Upward Theorem says that the conditional expectation of an integrable random variable converges with probability one to its true value with increasing information. In this paper, we use methods from effective probability theory to characterise the probability one set along which convergence to the truth occurs, and the rate at which the convergence occurs. We work within the setting of computable probability measures defined on computable Polish spaces and introduce a new general theory…

I keep meeting students who feel they *must* test their variables for normality before analysis.
I tell them there's no need, & if the test tells them it's normal it's only because N is too small.
I decided to run some simulations to check, though, whether e.g., t-tests degraded more for non-normal data & small Ns.
I was a bit surprised by the result: CI coverage degrades for normal vars just as badly as other symmetric dists, but skewed distributions…

This https://arxiv.org/abs/2401.17763 has been replaced.
link: https://scholar.google.com/scholar?q=a

Convergence of Expectation-Maximization Algorithm with Mixed-Integer Optimization
The convergence of expectation-maximization (EM)-based algorithms typically requires continuity of the likelihood function with respect to all the unknown parameters (optimization variables). The requirement is not met when parameters comprise both discrete and continuous variables, making the convergence analysis nontrivial. This paper introduces a set of conditions that ensure the convergence of a specific class of EM algorithms that estimate a mixture of discrete and continuous parameters. O…

Incel CS lecturer at Waterloo
"As a result, girls mostly reject boys because their expectation has become so high that they only can accept celebrity- or influencer-type boys who have fit sexy bodies, luxury life, and a lot of cash."
Are you kidding me? That's absolutely ... actually that's pretty accurate. Checks out.

Improving flux ratio anomaly precision by measuring gravitational lens multipole moments with extended arcs
Maverick S. H. Oh, Anna Nierenberg, Daniel Gilman, Simon Birrer
https://arxiv.org/abs/2404.17124

Improving flux ratio anomaly precision by measuring gravitational lens multipole moments with extended arcs
In a strong gravitational lens, perturbations by low-mass dark matter halos can be detected by differences between the measured image fluxes relative to the expectation from a smooth model for the mass distribution which contains only the gravitational effects of the main deflector. The abundance of these low-mass structures can be used to constrain the properties of dark matter. Traditionally only the lensed quasar positions have been to predict the smooth-model flux ratios. We demonstrate tha…

Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation
Aaron Mishkin, Mert Pilanci, Mark Schmidt
https://arxiv.org/abs/2404.02378

Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation
We prove new convergence rates for a generalized version of stochastic Nesterov acceleration under interpolation conditions. Unlike previous analyses, our approach accelerates any stochastic gradient method which makes sufficient progress in expectation. The proof, which proceeds using the estimating sequences framework, applies to both convex and strongly convex functions and is easily specialized to accelerated SGD under the strong growth condition. In this special case, our analysis reduces …

The falacy of the legal concept of "reasonable expectation of privacy" in US law exemplified in this beautiful case.
Fortunately, totally useless as an argumentation in the EU legal framework (GDPR etc). So if you're sitting in the EU, this is a hoax for you!
https://mamot.fr/@ploum/111909320532…

Conformal Risk Control for Ordinal Classification
Yunpeng Xu, Wenge Guo, Zhi Wei
https://arxiv.org/abs/2405.00417 https://arxiv.org/p…

Conformal Risk Control for Ordinal Classification
As a natural extension to the standard conformal prediction method, several conformal risk control methods have been recently developed and applied to various learning problems. In this work, we seek to control the conformal risk in expectation for ordinal classification tasks, which have broad applications to many real problems. For this purpose, we firstly formulated the ordinal classification task in the conformal risk control framework, and provided theoretic risk bounds of the risk control…

This https://arxiv.org/abs/2403.19587 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Taming the Interactive Particle Langevin Algorithm -- the superlinear case
Recent advances in stochastic optimization have yielded the interactive particle Langevin algorithm (IPLA), which leverages the notion of interacting particle systems (IPS) to efficiently sample from approximate posterior densities. This becomes particularly crucial within the framework of Expectation-Maximization (EM), where the E-step is computationally challenging or even intractable. Although prior research has focused on scenarios involving convex cases with gradients of log densities that…

Non-parametric estimation for the stochastic wave equation
Eric Ziebell
https://arxiv.org/abs/2404.18823 https://arxiv.org/pdf/2404.1…

Non-parametric estimation for the stochastic wave equation
The spatially dependent wave speed of a stochastic wave equation driven by space-time white noise is estimated using the local observation scheme. Given a fixed time horizon, we prove asymptotic normality for an augmented maximum likelihood estimator as the resolution level of the observations tends to zero. We show that the expectation and variance of the observed Fisher information are intrinsically related to the kinetic energy within an associated deterministic wave equation and prove an as…

A novel decision fusion approach for sale price prediction using Elastic Net and MOPSO
Amir Eshaghi Chaleshtori
https://arxiv.org/abs/2403.20033 https://…

A novel decision fusion approach for sale price prediction using Elastic Net and MOPSO
Price prediction algorithms propose prices for every product or service according to market trends, projected demand, and other characteristics, including government rules, international transactions, and speculation and expectation. As the dependent variable in price prediction, it is affected by several independent and correlated variables which may challenge the price prediction. To overcome this challenge, machine learning algorithms allow more accurate price prediction without explicitly m…

Difficult control is related to instability in biologically inspired Boolean networks
Bryan C. Daniels, Enrico Borriello
https://arxiv.org/abs/2402.18757 h…

Difficult control is related to instability in biologically inspired Boolean networks
Previous work in Boolean dynamical networks has suggested that the number of components that must be controlled to select an existing attractor is typically set by the number of attractors admitted by the dynamics, with no dependence on the size of the network. Here we study the rare cases of networks that defy this expectation, with attractors that require controlling most nodes. We find empirically that unstable fixed points are the primary recurring characteristic of networks that prove more…

Boom and bust cycles due to pseudospectra of matrices with unimodular spectra
Junaid Majeed Bhat, Ja\v{s} Bensa, Marko \v{Z}nidari\v{c}
https://arxiv.org/abs/2402.19201

Boom and bust cycles due to pseudospectra of matrices with unimodular spectra
We discuss dynamics obtained by increasing powers of non-normal matrices that are roots of the identity, and therefore have all eigenvalues on the unit circle. Naively, one would expect that the expectation value of such powers cannot grow as one increases the power. We demonstrate that, rather counterintuitively, a completely opposite behavior is possible. In the limit of infinitely large matrices one can have an exponential growth. For finite matrices this exponential growth is a part of repe…

This https://arxiv.org/abs/2402.14788 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Expectation Values of Conserved Charges in Integrable Quantum Field Theories out of Thermal Equilibrium
In this work we present a computation of the averages of conserved charge densities and currents of (1+1)-dimensional Integrable Quantum Field Theories in Generalised Gibbs Ensembles. Our approach is based on the quasi-particle description provided by the Thermodynamic Bethe Ansatz combined with the principles of Generalised Hydrodynamics, and we focus on Non-Equilibrium Steady State averages. When considering the ultraviolet (i.e. high temperature) limit of such averages, we recover the famous…

Anomalous diffusion and factor ordering in (1 1)-dimensional Lorentzian quantum gravity
Elijah Sanderson, Rachel Lash Maitra, AJ Liberatore
https://arxiv.org/abs/2405.00594

Anomalous diffusion and factor ordering in (1+1)-dimensional Lorentzian quantum gravity
Using properties of diffusion according to a quantum heat kernel constructed as an expectation over classical heat kernels on $S^1$, we probe the non-manifold-like nature of quantized space in a model of (1+1)-dimensional quantum gravity. By computing the mean squared displacement of a diffusing particle, we find that diffusion is anomalous, behaving similarly to that on a porous substrate, network, or fractal over short distances. The walk dimension of the path for a particle diffusing in quan…

"It sounds like at first #Threads users who opt into federation will be able to see likes and boosts of their posts from non-Threads accounts, but replies won't come through yet. Again, annoying, but will surely be fixed in time. My expectation here is that one draw of federating will be your increased reach to more people, so broadcasting your posts to more people will have value to some…&…

Towards a turnkey approach to unbiased Monte Carlo estimation of smooth functions of expectations
Nicolas Chopin, Francesca R. Crucinio, Sumeetpal S. Singh
https://arxiv.org/abs/2403.20313

Towards a turnkey approach to unbiased Monte Carlo estimation of smooth functions of expectations
Given a smooth function $f$, we develop a general approach to turn Monte Carlo samples with expectation $m$ into an unbiased estimate of $f(m)$. Specifically, we develop estimators that are based on randomly truncating the Taylor series expansion of $f$ and estimating the coefficients of the truncated series. We derive their properties and propose a strategy to set their tuning parameters -- which depend on $m$ -- automatically, with a view to make the whole approach simple to use. …

Search for the Z boson decay to $\tau\tau\mu\mu$ in proton-proton collisions at $\sqrt{s}$ = 13 TeV
CMS Collaboration
https://arxiv.org/abs/2404.18298 http…

Search for the Z boson decay to $ττμμ$ in proton-proton collisions at $\sqrt{s}$ = 13 TeV
The first search for the Z boson decay to $ττμμ$ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138 fb$^{-1}$. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.9 times the standard model expectation is placed on the ratio of the Z $\to$ $ττμμ$ to Z $\to$ 4$μ$ br…

This https://arxiv.org/abs/2401.11056 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Analytical results for the Quantum Alternating Operator Ansatz with Grover Mixer
An important property of QAOA with Grover mixer is that its expectation value is invariant over any permutation of states. As a consequence, the algorithm is independent of the structure of the problem. If, on the one hand, this characteristic raises serious doubts about the capacity of the algorithm to overcome the bound of the unstructured search problem, on the other hand, it can pave the way to its analytical study. In this sense, a prior work introduced a statistical approach to analyze GM…

Improving flux ratio anomaly precision by measuring gravitational lens multipole moments with extended arcs
Maverick S. H. Oh, Anna Nierenberg, Daniel Gilman, Simon Birrer
https://arxiv.org/abs/2404.17124

Improving flux ratio anomaly precision by measuring gravitational lens multipole moments with extended arcs
In a strong gravitational lens, perturbations by low-mass dark matter halos can be detected by differences between the measured image fluxes relative to the expectation from a smooth model for the mass distribution which contains only the gravitational effects of the main deflector. The abundance of these low-mass structures can be used to constrain the properties of dark matter. Traditionally only the lensed quasar positions have been to predict the smooth-model flux ratios. We demonstrate tha…

Synergizing Privacy and Utility in Data Analytics Through Advanced Information Theorization
Zahir Alsulaimawi
https://arxiv.org/abs/2404.16241 https://

Synergizing Privacy and Utility in Data Analytics Through Advanced Information Theorization
This study develops a novel framework for privacy-preserving data analytics, addressing the critical challenge of balancing data utility with privacy concerns. We introduce three sophisticated algorithms: a Noise-Infusion Technique tailored for high-dimensional image data, a Variational Autoencoder (VAE) for robust feature extraction while masking sensitive attributes and an Expectation Maximization (EM) approach optimized for structured data privacy. Applied to datasets such as Modified MNIST …

This https://arxiv.org/abs/2402.14788 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Expectation Values of Conserved Charges in Integrable Quantum Field Theories out of Thermal Equilibrium
In this work we present a computation of the averages of conserved charge densities and currents of (1+1)-dimensional Integrable Quantum Field Theories in Generalised Gibbs Ensembles. Our approach is based on the quasi-particle description provided by the Thermodynamic Bethe Ansatz combined with the principles of Generalised Hydrodynamics, and we focus on Non-Equilibrium Steady State averages. When considering the ultraviolet (i.e. high temperature) limit of such averages, we recover the famous…

Robustness of voting mechanisms to external information in expectation
Yiling Chen, Jessie Finocchiaro
https://arxiv.org/abs/2404.07818 https://

Robustness of voting mechanisms to external information in expectation
Analyses of voting algorithms often overlook informational externalities shaping individual votes. For example, pre-polling information often skews voters towards candidates who may not be their top choice, but who they believe would be a worthwhile recipient of their vote. In this work, we aim to understand the role of external information in voting outcomes. We study this by analyzing (1) the probability that voting outcomes align with external information, and (2) the effect of external info…

This https://arxiv.org/abs/2403.08443 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

The top eigenvalue of uniformly random trees
Let ${\mathbf T}_n$ be a uniformly random tree with vertex set $[n]=\{1,\ldots,n\}$, let $Δ_{{\mathbf T}_n}$ be the largest vertex degree in ${\mathbf T}_n$, and let $λ_1({\mathbf T}_n),\ldots,λ_n({\mathbf T}_n)$ be the eigenvalues of its adjacency matrix, arranged in decreasing order. We prove that $|λ_1({\mathbf T}_n)-\sqrt{Δ_{{\mathbf T}_n}}| \to 0$ in expectation as $n \to \infty$, and additionally prove probability tail bounds for $|λ_1({\mathbf T}_n)-\sqrt{Δ_{{\mathb…

Disentangling left and right-handed neutrino effects in $B\rightarrow K^{(*)}\nu\nu$
S. Rosauro-Alcaraz, L. P. Santos Leal
https://arxiv.org/abs/2404.17440

Disentangling left and right-handed neutrino effects in $B\rightarrow K^{(*)}νν$
The first observation of $\mathcal{B}\left(B^+\rightarrow K^+νν\right)$ by the Belle II experiment lies almost $3σ$ away from the Standard Model expectation. In this letter we study this result in the SMEFT, extended by a light right-handed neutrino. We explore the correlations between the measured decay rate and other observables, such as $\mathcal{B}\left(B\rightarrow K^*νν\right)$ and $F_L\left(B\rightarrow K^*νν\right)$, showing that they could disentangle among scenarios involving l…

Generating Context-Aware Contrastive Explanations in Rule-based Systems
Lars Herbold, Mersedeh Sadeghi, Andreas Vogelsang
https://arxiv.org/abs/2402.13000 …

Generating Context-Aware Contrastive Explanations in Rule-based Systems
Human explanations are often contrastive, meaning that they do not answer the indeterminate "Why?" question, but instead "Why P, rather than Q?". Automatically generating contrastive explanations is challenging because the contrastive event (Q) represents the expectation of a user in contrast to what happened. We present an approach that predicts a potential contrastive event in situations where a user asks for an explanation in the context of rule-based systems. Our approach analyzes a situati…

This https://arxiv.org/abs/2102.06677 has been replaced.
link: https://scholar.google.com/scholar?q=a

Codifferentials and Quasidifferentials of the Expectation of Nonsmooth Random Integrands and Two-Stage Stochastic Programming
This work is devoted to an analysis of exact penalty functions and optimality conditions for nonsmooth two-stage stochastic programming problems. To this end, we first study the co-/quasi-differentiability of the expectation of nonsmooth random integrands and obtain explicit formulae for its co- and quasidifferential under some natural assumptions on the integrand. Then we analyse exact penalty functions for a variational reformulation of two-stage stochastic programming problems and obtain suf…

This https://arxiv.org/abs/2306.03935 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Inferring interpretable dynamical generators of local quantum observables from projective measurements through machine learning
To characterize the dynamical behavior of many-body quantum systems, one is usually interested in the evolution of so-called order-parameters rather than in characterizing the full quantum state. In many situations, these quantities coincide with the expectation value of local observables, such as the magnetization or the particle density. In experiment, however, these expectation values can only be obtained with a finite degree of accuracy due to the effects of the projection noise. Here, we u…

This https://arxiv.org/abs/2208.07243 has been replaced.
link: https://scholar.google.com/scholar?q=a

Exponential Concentration in Stochastic Approximation
We analyze the behavior of stochastic approximation algorithms where iterates, in expectation, progress towards an objective at each step. When progress is proportional to the step size of the algorithm, we prove exponential concentration bounds. These tail-bounds contrast asymptotic normality results, which are more frequently associated with stochastic approximation. The methods that we develop rely on a geometric ergodicity proof. This extends a result on Markov chains due to Hajek (1982) to…

This https://arxiv.org/abs/2304.00074 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Bayesian Clustering via Fusing of Localized Densities
Bayesian clustering typically relies on mixture models, with each component interpreted as a different cluster. After defining a prior for the component parameters and weights, Markov chain Monte Carlo (MCMC) algorithms are commonly used to produce samples from the posterior distribution of the component labels. The data are then clustered by minimizing the expectation of a clustering loss function that favours similarity to the component labels. Unfortunately, although these approaches are rou…

Disentangling left and right-handed neutrino effects in $B\rightarrow K^{(*)}\nu\nu$
S. Rosauro-Alcaraz, L. P. Santos Leal
https://arxiv.org/abs/2404.17440

Disentangling left and right-handed neutrino effects in $B\rightarrow K^{(*)}νν$
The first observation of $\mathcal{B}\left(B^+\rightarrow K^+νν\right)$ by the Belle II experiment lies almost $3σ$ away from the Standard Model expectation. In this letter we study this result in the SMEFT, extended by a light right-handed neutrino. We explore the correlations between the measured decay rate and other observables, such as $\mathcal{B}\left(B\rightarrow K^*νν\right)$ and $F_L\left(B\rightarrow K^*νν\right)$, showing that they could disentangle among scenarios involving l…

New explanation emerges for what Cowboys owner Jerry Jones meant by ‘all-in’ https://www.yardbarker.com/nfl/articles/new_explanation_emerges_for_what_cowboys_owner_jerry_jones_meant_by_all_in/s1_127_40163…

New explanation emerges for what Cowboys owner Jerry Jones meant by ‘all-in’
Jerry Jones created the expectation that the Dallas Cowboys were going to have an active offseason when he said the team was going “all in” on 2024, but it now looks like everyone may have misinterpreted what Jones meant. Not long after his team’s embarrassing home loss to the Green Bay Packers in the wild-card round of the playoffs, Jones vowed that the Cowboys will be “going all in” heading into next season. The 81-year-old even said that Dallas is going to focus on 2024 and “not …

This https://arxiv.org/abs/2402.08551 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Nonstabilizerness of permutationally invariant systems
Typical measures of nonstabilizerness of a system of $N$ qubits require computing $4^N$ expectation values, one for each Pauli string in the Pauli group, over a state of dimension $2^N$. In this Letter, we show that, if the system is invariant under permutations, this resource overhead can be exponentially decreased to $O(N^3)$ expectation values on a state with a dimension $O(N)$, allowing for a polynomial-time evaluation of the nonstabilizerness up to hundreds of qubits.

Sublinear expectation structure under finite states space
Shuzhen Yang, Wenqing Zhang
https://arxiv.org/abs/2403.04324 https://arxiv.…

Sublinear expectation structure under finite states space
In this study, we propose the sublinear expectation structure under finite states space. To describe an interesting "nonlinear randomized" trial, based on a convex closed domain, we introduce a family of probability measures under finite states space. Corresponding the sublinear expectation operator introduced by S. Peng, we consider the related notation under finite states space. Within the finite states framework, the sublinear expectation can be explicitly calculated by a novel repeated summ…

Infinite quantum twisting at the Cauchy horizon of rotating black holes
Christiane Klein, Mojgan Soltani, Marc Casals, Stefan Hollands
https://arxiv.org/abs/2402.14171

Infinite quantum twisting at the Cauchy horizon of rotating black holes
We present a numerical calculation of the expectation value of the quantum angular-momentum current flux density for a scalar field in the Unruh state near the inner horizon of a Kerr-de Sitter black hole. Our results indicate that this flux diverges as $V_-^{-1}$ in a suitable Kruskal coordinate such that $V_-=0$ at the inner horizon. Depending on the parameter values of the scalar field and black hole that we consider, and depending on the polar angle (latitude), this flux can have different …

A Novel Proton Decay Signature at DUNE, JUNO, and Hyper-K
Florian Domingo, Herbi K. Dreiner, Dominik K\"ohler, Saurabh Nangia, Apoorva Shah
https://arxiv.org/abs/2403.18502 <…

A Novel Proton Decay Signature at DUNE, JUNO, and Hyper-K
Proton decay, although unobserved so far, is a natural expectation when attempting to explain the baryon asymmetry of the universe. $p\to K^+\barν$ or $p\to K^+\tildeχ_1^0$, with $\tildeχ_1^0$ a light exotic neutral particle, represent possible decay channels achievable in models of physics beyond the Standard Model, such as the MSSM with trilinear R-parity-violating terms, or the Standard Model extended by a heavy neutral lepton. Among the decay products of these modes, the neutral fermions…

Should the Cowboys build the offensive line from within in 2024? https://www.yardbarker.com/nfl/articles/should_the_cowboys_build_the_offensive_line_from_within_in_2024/s1_17100_40086648

This https://arxiv.org/abs/2403.09325 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Improved Constraints on the Variation of the Weak Scale from Big Bang Nucleosynthesis
We analyze the recent EMPRESS data on the $^4$He abundance in Big Bang nucleosynthesis as a function of the Higgs vacuum expectation value $v$ and compare our calculation to the recently published work of Burns et al.~[1]. The EMPRESS result for the $^4$He abundance can be explained within $2σ$ by $0.03 \leq δv / v \leq 0.07$. However, as first noted in~[1], a Higgs VEV in this range would worsen the discrepancy between theory and experiment for the deuterium abundance significantly.

Near-optimal performance of stochastic economic MPC
Jonas Schie{\ss}l, Ruchuan Ou, Timm Faulwasser, Michael H. Baumann, Lars Gr\"une
https://arxiv.org/abs/2403.15159

Near-optimal performance of stochastic economic MPC
This paper presents first results for near optimality in expectation of the closed-loop solutions for stochastic economic MPC. The approach relies on a recently developed turnpike property for stochastic optimal control problems at an optimal stationary process, combined with techniques for analyzing time-varying economic MPC schemes. We obtain near optimality in finite time as well as overtaking and average near optimality on infinite time horizons.

Nonstabilizerness of permutationally invariant systems
G. Passarelli, R. Fazio, P. Lucignano
https://arxiv.org/abs/2402.08551 https://

Nonstabilizerness of permutationally invariant systems
Typical measures of nonstabilizerness of a system of $N$ qubits require computing $4^N$ expectation values, one for each Pauli string in the Pauli group, over a state of dimension $2^N$. In this Letter, we show that, if the system is invariant under permutations, this resource overhead can be exponentially decreased to $O(N^3)$ expectation values on a state with a dimension $O(N)$, allowing for a polynomial-time evaluation of the nonstabilizerness up to hundreds of qubits.

This https://arxiv.org/abs/2306.08931 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Stochastic Differential Equations Driven by G-Brownian Motion with Mean Reflections
In this paper, we study the mean reflected stochastic differential equations driven by G- Brownian motion, where the constraint depends on the distribution of the solution rather than on its paths. Well-posedness is achieved by first investigating the Skorokhod problem with mean reflection under the G-expectation. Two approaches to constructing the solution are introduced, both offering insights into desired properties and aiding in the application of the contraction mapping method. Additionall…

This https://arxiv.org/abs/2403.09860 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

A quantum expectation identity: Applications to statistical mechanics
In this article, we derive a useful expectation identity using the language of quantum statistical mechanics, where density matrices represent the state of knowledge about the system. This identity allows to establish relations between different quantum observables depending on a continuous parameter. Such a parameter can be contained in the observables itself (e.g. perturbative parameter) or may appear as a Lagrange multiplier (inverse temperature, chemical potential, etc.) in the density matr…

This https://arxiv.org/abs/2312.02272 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Fermionic wave packet scattering: a quantum computing approach
We propose a method to prepare Gaussian wave packets with momentum on top of the interacting ground state of a fermionic Hamiltonian. Using Givens rotation, we show how to efficiently obtain expectation values of observables throughout the evolution of the wave packets on digital quantum computers. We demonstrate our technique by applying it to the staggered lattice formulation of the Thirring model and studying the scattering of two wave packets. Monitoring the the particle density and the ent…

This https://arxiv.org/abs/2310.12726 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Error-mitigated fermionic classical shadows on noisy quantum devices
Efficiently estimating fermionic Hamiltonian expectation values is vital for simulating various physical systems. Classical shadow (CS) algorithms offer a solution by reducing the number of quantum state copies needed, but noise in quantum devices poses challenges. We propose an error-mitigated CS algorithm assuming gate-independent, time-stationary, and Markovian (GTM) noise. For $n$-qubit systems, our algorithm, which employs the easily prepared initial state $|0^n\rangle\!\langle 0^n
…