arXiv subjects

Steven Weber

Publications and source records attributed to Steven Weber.

At least 19 recordsLinked to original sources

arXiv2026

Characterization of Aluminum Microwave SQUID Multiplexers for CE$ν$NS Detection

We present the design, fabrication, and characterization of an aluminum-based six-channel microwave SQUID multiplexer ($μ$MUX) prototype for transition-edge sensor (TES) readout in the RICOCHET experiment. The device consists of aluminum coplanar-waveguide resonators and RF SQUIDs with Dolan-style Al/AlO$_x$/Al Josephson junctions. By measuring the resonator scattering parameters at a range of probe tone frequencies, powers, and flux bias points, we demonstrate agreement between the device response and existing multiplexer models. We also characterize the noise performance in both open-loop and flux-ramping modes. With a high electron mobility transistor (HEMT) amplifier, open-loop measurements yield a flux sensitivity of 1-1.5 $μΦ_0/\sqrt{Hz}$. With flux-ramp modulation, low-frequency 1/f noise is suppressed, and the flux sensitivity is around 3-4 $μΦ_0/\sqrt{Hz}$, corresponding to a current sensitivity of 24-33 $pA/\sqrt{Hz}$ at the input coil. We further demonstrate a reduction in readout noise by incorporating a Josephson traveling-wave parametric amplifier (JTWPA) between the $μ$MUX and the HEMT. This achieves an open-loop flux sensitivity of 0.3-0.6 $μΦ_0/\sqrt{Hz}$ and an effective system noise temperature below 1 K. These results establish aluminum $μ$MUX devices as a viable and extensible readout technology for low-noise cryogenic detector arrays.

physics.ins-det↗

arXiv2025

PRREACH: Probabilistic Risk Assessment Using Reachability for UAV Control

We present a new approach for designing risk-bounded controllers for Uncrewed Aerial Vehicles (UAVs). Existing frameworks for assessing risk of UAV operations rely on knowing the conditional probability of an incident occurring given different causes. Limited data for computing these probabilities makes real-world implementation of these frameworks difficult. Furthermore, existing frameworks do not include control methods for risk mitigation. Our approach relies on UAV dynamics, and employs reachability analysis for a probabilistic risk assessment over all feasible UAV trajectories. We use this holistic risk assessment to formulate a control optimization problem that minimally changes a UAV's existing control law to be bounded by an accepted risk threshold. We call our approach PRReach. Public and readily available UAV dynamics models and open source spatial data for mapping hazard outcomes enables practical implementation of PRReach for both offline pre-flight and online in-flight risk assessment and mitigation. We evaluate PRReach through simulation experiments on real-world data. Results show that PRReach controllers reduce risk by up to 24% offline, and up to 53% online from classical controllers.

eess.SY↗

arXiv2020

Star sampling with and without replacement

Star sampling (SS) is a random sampling procedure on a graph wherein each sample consists of a randomly selected vertex (the star center) and its one-hop neighbors (the star endpoints). We consider the use of star sampling to find any member of an arbitrary target set of vertices in a graph, where the figure of merit (cost) is either the expected number of samples (unit cost) or the expected number of star centers plus star endpoints (linear cost) until a vertex in the target set is encountered, either as a star center or as a star point. We analyze this performance measure on three related star sampling paradigms: SS with replacement (SSR), SS without center replacement (SSC), and SS without star replacement (SSS). We derive exact and approximate expressions for the expected unit and linear costs of SSR, SSC, and SSS on Erdos-Renyi (ER) graphs. Our results show there is i) little difference in unit cost, but ii) significant difference in linear cost, across the three paradigms. Although our results are derived for ER graphs, experiments on "real-world" graphs suggest our performance expressions are reasonably accurate for non-ER graphs.

cs.PF↗

arXiv2020

Graph search via star sampling with and without replacement

Star sampling (SS) is a random sampling procedure on a graph wherein each sample consists of a randomly selected vertex (the star center) and its (one-hop) neighbors (the star points). We consider the use of SS to find any member of a target set of vertices in a graph, where the figure of merit (cost) is either the expected number of samples (unit cost) or the expected number of star centers plus star points (linear cost) until a vertex in the target set is encountered, either as a star center or as a star point. We analyze these two performance measures on three related star sampling paradigms: SS with replacement (SSR), SS without center replacement (SSC), and SS without star replacement (SSS). Exact and approximate expressions are derived for the expected unit and linear costs of SSR, SSC, and SSS on Erdős-Rényi (ER) random graphs. The approximations are seen to be accurate. SSC/SSS are notably better than SSR under unit cost for low-density ER graphs, while SSS is notably better than SSR/SSC under linear cost for low- to moderate-density ER graphs. Simulations on twelve "real-world" graphs shows the cost approximations to be of variable quality: the SSR and SSC approximations are uniformly accurate, while the SSS approximation, derived for an ER graph, is of variable accuracy.

cs.NI↗

arXiv2020

The 2020s Political Economy of Machine Translation

This paper explores the hypothesis that the diversity of human languages, right now a barrier to interoperability in communication and trade, will become significantly less of a barrier as machine translation technologies are deployed over the next several years.But this new boundary-breaking technology does not reduce all boundaries equally, and it creates new challenges for the distribution of ideas and thus for innovation and economic growth.

cs.CY↗

arXiv2019

Microwave Packaging for Superconducting Qubits

Over the past two decades, the performance of superconducting quantum circuits has tremendously improved. The progress of superconducting qubits enabled a new industry branch to emerge from global technology enterprises to quantum computing startups. Here, an overview of superconducting quantum circuit microwave control is presented. Furthermore, we discuss one of the persistent engineering challenges in the field, how to control the electromagnetic environment of increasingly complex superconducting circuits such that they are simultaneously protected and efficiently controllable.

quant-ph↗

arXiv2018

Efficiency and detectability of random reactive jamming in carrier sense wireless networks

A natural basis for the detection of a wireless random reactive jammer (RRJ) is the perceived violation by the detector (typically located at the access point (AP)) of the carrier sensing protocol underpinning many wireless random access protocols (e.g., WiFi). Specifically, when the wireless medium is perceived by a station to be busy, a carrier sensing compliant station will avoid transmission while a RRJ station will often initiate transmission. However, hidden terminals (HTs), i.e., activity detected by the AP but not by the sensing station, complicate the use of carrier sensing as the basis for RRJ detection since they provide plausible deniability to a station suspected of being an RRJ. The RRJ has the dual objectives of avoiding detection and effectively disrupting communication, but there is an inherent performance tradeoff between these two objectives. In this paper we capture the behavior of both the RRJ and the compliant stations via a parsimonious Markov chain model, and pose the detection problem using the framework of Markov chain hypothesis testing. Our analysis yields the receiver operating characteristic of the detector, and the optimized behavior of the RRJ. While there has been extensive work in the literature on jamming detection, our innovation lies in leveraging carrier sensing as a natural and effective basis for detection.

cs.IT↗

arXiv2018

Common greedy wiring and rewiring heuristics do not guarantee maximum assortative graphs of given degree

We examine two greedy heuristics - wiring and rewiring - for constructing maximum assortative graphs over all simple connected graphs with a target degree sequence. Counterexamples show that natural greedy rewiring heuristics do not necessarily return a maximum assortative graph, even though it is known that the meta-graph of all simple connected graphs with given degree is connected under rewiring. Counterexamples show an elegant greedy graph wiring heuristic from the literature may fail to achieve the target degree sequence or may fail to wire a maximally assortative graph.

cs.DS↗

arXiv2017

Facilitating adoption of Internet technologies and services with externalities via cost subsidization

This paper models the temporal adoption dynamics of an abstracted Internet technology or service, where the instantaneous net value of the service perceived by each (current or potential) user / customer incorporates three key features: i) user service affinity heterogeneity, ii) a network externality, and iii) a subscription cost. Internet technologies and services with network externalities face a "chicken and egg" adoption problem in that the service requires an established customer base in order to attract new customers. In this paper we study cost subsidization as a means to "reach the knee", at which point the externality drives rapid service adoption, and thereby change the equilibrium service fractional adoption level from an initial near-zero level to a final near-one level (full adoption). We present three simple subsidy models and evaluate them under two natural performance metrics: i) the duration required for the subsidized service to reach a given target adoption level, and ii) the aggregate cost of the subsidy born by the service provide. First, we present a "two target adoption subsidy" (TTAS) that subsidizes the cost so as to keep the fraction of users with positive net utility at a (constant) target level until the actual adoption target is reached. Second, we study a special case of the above where the target ensures all users have positive net utility, corresponding to a "quickest adoption" subsidy (QAS). Third, we introduce an approximation of QAS, called AQAS, that only requires the service provider adjust the subsidy level a prescribed number of times. Fourth, we study equilibria and their stability under uniformly and normally distributed user service affinities, highlighting the unstable equilibrium in each case as the natural target adoption level for the provider. Finally, we provide a fictional case study to illustrate the results.

cs.SI↗

arXiv2017

On Multi-source Networks: Enumeration, Rate Region Computation, and Hierarchy

Recent algorithmic developments have enabled computers to automatically determine and prove the capacity regions of small hypergraph networks under network coding. A structural theory relating network coding problems of different sizes is developed to make best use of this newfound computational capability. A formal notion of network minimality is developed which removes components of a network coding problem that are inessential to its core complexity. Equivalence between different network coding problems under relabeling is formalized via group actions, an algorithm which can directly list single representatives from each equivalence class of minimal networks up to a prescribed network size is presented. This algorithm, together with rate region software, is leveraged to create a database containing the rate regions for all minimal network coding problems with five or fewer sources and edges, a collection of 744119 equivalence classes representing more than 9 million networks. In order to best learn from this database, and to leverage it to infer rate regions and their characteristics of networks at scale, a hierarchy between different network coding problems is created with a new theory of combinations and embedding operators.

cs.IT↗

arXiv2017

Properties of an Aloha-like stability region

A well-known inner bound on the stability region of the finite-user slotted Aloha protocol is the set of all arrival rates for which there exists some choice of the contention probabilities such that the associated worst-case service rate for each user exceeds the user's arrival rate, denoted $Λ$. Although testing membership in $Λ$ of a given arrival rate can be posed as a convex program, it is nonetheless of interest to understand the properties of this set. In this paper we develop new results of this nature, including $i)$ an equivalence between membership in $Λ$ and the existence of a positive root of a given polynomial, $ii)$ a method to construct a vector of contention probabilities to stabilize any stabilizable arrival rate vector, $iii)$ the volume of $Λ$, $iv)$ explicit polyhedral, spherical, and ellipsoid inner and outer bounds on $Λ$, and $v)$ characterization of the generalized convexity properties of a natural ``excess rate'' function associated with $Λ$, including the convexity of the set of contention probabilities that stabilize a given arrival rate vector.

cs.IT↗

arXiv2017

Delay on broadcast erasure channels under random linear combinations

We consider a transmitter broadcasting random linear combinations (over a field of size $d$) formed from a block of $c$ packets to a collection of $n$ receivers, where the channels between the transmitter and each receiver are independent erasure channels with reception probabilities $\mathbf{q} = (q_1,\ldots,q_n)$. We establish several properties of the random delay until all $n$ receivers have recovered all $c$ packets, denoted $Y_{n:n}^{(c)}$. First, we provide lower and upper bounds, exact expressions, and a recurrence for the moments of $Y_{n:n}^{(c)}$. Second, we study the delay per packet $Y_{n:n}^{(c)}/c$ as a function of $c$, including the asymptotic delay (as $c \to \infty$), and monotonicity (in $c$) properties of the delay per packet. Third, we employ extreme value theory to investigate $Y_{n:n}^{(c)}$ as a function of $n$ (as $n \to \infty$). Several results are new, some results are extensions of existing results, and some results are proofs of known results using new (probabilistic) proof techniques.

cs.IT↗

arXiv2016

On protocol and physical interference models in Poisson wireless networks

This paper analyzes the connection between the protocol and physical interference models in the setting of Poisson wireless networks. A transmission is successful under the protocol model if there are no interferers within a parameterized guard zone around the receiver, while a transmission is successful under the physical model if the signal to interference plus noise ratio (SINR) at the receiver is above a threshold. The parameterized protocol model forms a family of decision rules for predicting the success or failure of the same transmission attempt under the physical model. For Poisson wireless networks, we employ stochastic geometry to determine the prior, evidence, and posterior distributions associated with this estimation problem. With this in hand, we proceed to develop five sets of results: i) the maximum correlation of protocol and physical model success indicators, ii) the minimum Bayes risk in estimating physical success from a protocol observation, iii) the receiver operating characteristic (ROC) of false rejection (Type I) and false acceptance (Type II) probabilities, iv) the impact of Rayleigh fading vs. no fading on the correlation and ROC, and v) the impact of multiple prior protocol model observations in the setting of a wireless network with a fixed set of nodes in which the nodes employ the slotted Aloha protocol in each time slot.

cs.IT↗

arXiv2016

On the Aloha throughput-fairness tradeoff

A well-known inner bound of the stability region of the slotted Aloha protocol on the collision channel with n users assumes worst-case service rates (all user queues non-empty). Using this inner bound as a feasible set of achievable rates, a characterization of the throughput--fairness tradeoff over this set is obtained, where throughput is defined as the sum of the individual user rates, and two definitions of fairness are considered: the Jain-Chiu-Hawe function and the sum-user alpha-fair (isoelastic) utility function. This characterization is obtained using both an equality constraint and an inequality constraint on the throughput, and properties of the optimal controls, the optimal rates, and the fairness as a function of the target throughput are established. A key fact used in all theorems is the observation that all contention probability vectors that extremize the fairness functions take at most two non-zero values.

cs.IT↗

arXiv2016

A Markov chain model for the search time for max degree nodes in a graph using a biased random walk

We consider the problem of estimating the expected time to find a maximum degree node on a graph using a (parameterized) biased random walk. For assortative graphs the positive degree correlation serves as a local gradient for which a bias towards selecting higher degree neighbors will on average reduce the search time. Unfortunately, although the expected absorption time on the graph can be written down using the theory of absorbing Markov chains, computing this time is infeasible for large graphs. With this motivation, we construct an absorbing Markov chain with a state for each degree of the graph, and observe computing the expected absorption time is now computationally feasible. Our paper finds preliminary results along the following lines: i) there are graphs for which the proposed Markov model does and graphs for which the model does not capture the absorbtion time, ii) there are graphs where random sampling outperforms biased random walks, and graphs where biased random walks are superior, and iii) the optimal bias parameter for the random walk is graph dependent, and we study the dependence on the graph assortativity.

cs.SI↗

arXiv2015

On the performance overhead tradeoff of distributed principal component analysis via data partitioning

Principal component analysis (PCA) is not only a fundamental dimension reduction method, but is also a widely used network anomaly detection technique. Traditionally, PCA is performed in a centralized manner, which has poor scalability for large distributed systems, on account of the large network bandwidth cost required to gather the distributed state at a fusion center. Consequently, several recent works have proposed various distributed PCA algorithms aiming to reduce the communication overhead incurred by PCA without losing its inferential power. This paper evaluates the tradeoff between communication cost and solution quality of two distributed PCA algorithms on a real domain name system (DNS) query dataset from a large network. We also apply the distributed PCA algorithm in the area of network anomaly detection and demonstrate that the detection accuracy of both distributed PCA-based methods has little degradation in quality, yet achieves significant savings in communication bandwidth.

cs.DC↗

arXiv2015

On the joint impact of bias and power control on downlink spectral efficiency in cellular networks

Cell biasing and downlink transmit power are two controls that may be used to improve the spectral efficiency of cellular networks. With cell biasing, each mobile user associates with the base station offering, say, the highest biased signal to interference plus noise ratio. Biasing affects the cell association decisions of mobile users, but not the received instantaneous downlink transmission rates. Adjusting the collection of downlink transmission powers can likewise affect the cell associations, but in contrast with biasing, it also directly affects the instantaneous rates. This paper investigates the joint use of both cell biasing and transmission power control and their (individual and joint) effects on the statistical properties of the collection of per-user spectral efficiencies. Our analytical results and numerical investigations demonstrate in some cases a significant performance improvement in the Pareto efficient frontiers of both a mean-variance and throughput-fairness tradeoff from using both bias and power controls over using either control alone.

cs.IT↗

arXiv2015

Utility Maximization for Single-Station User Association in Downlink Cellular Networks

We study network utility maximization (NUM) in the context of cellular single station association (SSA) policies, which assigns each mobile user (MU) to a single base station (BS). We measure an SSA policy in terms of the induced α-proportional fairness utility of each user's downlink rate, summed over all users. The general SSA NUM problem involves choosing an optimal association from MUs to BSs as well as an optimal allocation of BS resources to associated MUs. Finding an exact solution to such centralized user association problems is well-known to be NP-hard. Our contributions are as follows: i) we give an explicit solution for the optimal BS allocation for a given SSA, which establishes SSA NUM as a purely combinatiorial problem; ii) we establish the integrality gap for the association problem to be one, and prove the relaxation to be a non-convex optimization problem; iii) we provide both centralized and distributed greedy algorithms for SSA, both with and without the exchange of instantaneous rate information between users and stations. Our numerical results illustrate performance gains of three classes of solutions: i) SSA solutions obtained by greedy rounding of multi-station associations (a centralized convex program), ii) our centralized and distributed greedy algorithms with/without rate information exchanged, and iii) simple association heuristics.

cs.NI↗