This paper considers two challenges faced by practical quantum networks: the bootstrapping of seedless Quantum Random Number Generators (QRNGs) and the resilient combination of Post-Quantum Cryptography (PQC) and Quantum Key Distribution (QKD) keys. These issues are addressed using universal hash functions as strong seeded extractors, with security foundations provided by the Quantum Leftover Hash Lemma (QLHL). First, the 'randomness loop' in QRNGs -- the requirement of an initial random seed to generate further randomness -- is resolved by proposing a bootstrapping method using raw data from two independent sources of entropy, given by seedless QRNG sources. Second, it is argued that strong seeded extractors are an alternative to XOR-based key combining that presents different characteristics. Unlike XORing, our method ensures that if the combined output and one initial key are compromised, the remaining key material retains quantifiable min-entropy and remains secure in exchange of longer keys. Furthermore, the proposed method allows to bind transcript information with key material in a natural way, providing a tool to replace computationally based combiners to extend ITS securit
Device-independent (DI) quantum cryptography provides secure cryptography with minimal trust in, or characterisation of, the used quantum devices. An essential component of DI protocols is the use of randomness extractors for privacy amplification, but these typically require an initial seed of randomness that introduces a potential vulnerability. To solve this problem, the security of seedless extractors was proven in Quantum 9, 1654 (2025). The core idea was to use the Bell violation of the raw data, rather than its min-entropy, as the extractor promise. However, the large fluctuations in the Bell inequality used required many rounds to precisely estimate the Bell violation, consuming substantial randomness and making the protocol very inefficient. In this work, we present a new proof technique based on a truncation method that allows the user to estimate the protocol parameters with an asymptotically vanishing fraction of rounds and, as a consequence, achieves the optimal rate of one key bit per singlet. Notably, we prove this result using seedless extractors that can be implemented efficiently.
We release GLAN-QnA-KR, a 303,581-row openly redistributable Korean instruction-QA corpus produced via the seedless taxonomy-driven GLAN synthesis pipeline with Microsoft's Phi-3.5-MoE-instruct as the producer model (generation: 2024-12; release: 2024-12; licence: OpenRAIL). The corpus spans a flat taxonomy of 1,084 English-labelled disciplines paired with Korean question/answer text, a 100-900 difficulty scale, and a median of 313 question characters and 1,098 answer characters per record. Two properties are atypical for synthetic instruction data at this scale: (i) exact duplicate questions number only 1 in 303,581 rows and character-trigram near-duplicate clusters at Jaccard >= 0.9 number zero in a 5,000-sample probe, and (ii) a two-layer contamination audit against KMMLU, KoBEST (five sub-tasks), and HAE-RAE-Bench shows a maximum test-vs-corpus question-level character-trigram Jaccard of 0.163 with zero test items at Jaccard >= 0.7, and a maximum multilingual-E5 cosine of 0.901 with a single test item at cosine >= 0.90 and zero at >= 0.95, across 20,000 sampled GLAN questions and seven evaluation sets. At the time of release, this is, to our knowledge, the largest s
We show how to construct a complete set of lowering operators, whose successive application reduces an arbitrary Fenyman integral to a combination of master integrals. The construction builds systems of equations for generic integral indices using IBP-generating vectors. The solution to each system is a lowering operator.
Magnetic field generation and amplification techniques are popular due to their applications in several fields, including laboratory astrophysics and inertial confinement fusion. Microtube Implosion (MTI) is a scheme that amplifies a seed magnetic field by several orders of magnitude through ultraintense laser irradiation of solid targets. In this study, we conducted 2D EPOCH simulations to investigate the ability of a tetrafoil target to generate a magnetic field in the absence of a seed magnetic field. The results show that the tetrafoil target generates magnetic field intensities comparable to a hollow cylindrical aluminum target undergoing MTI with a 10kT seed. Furthermore, the configuration of the tetrafoil can be used to control the direction of the magnetic fields produced. The combined tetrafoil and microtube target sustained higher magnetic field and flux compared to both the microtube and tetrafoil targets, without the need for a seed magnetic field.
We prove several new results for seedless condensers in the context of three related classes of sources: Non-Oblivious Symbol Fixing (NOSF) sources, online NOSF (oNOSF) sources [AORSV, EUROCRYPT'20], and adversarial Chor-Goldreich (aCG) source [DMOZ, STOC'23]. We think of these sources as a sequence of random variables $\mathbf{X}=\mathbf{X}_1,\dots,\mathbf{X}_\ell$ on $\ell$ symbols where at least $g$ out of these $\ell$ symbols are "good" (i.e., have some min-entropy requirement), denoted as a $(g,\ell)$-source, and the remaining "bad" $\ell-g$ symbols may adversarially depend on these $g$ good blocks. The difference between each of these sources is realized by restrictions on the power of the adversary. Prior to our work, the only known seedless condenser upper or lower bound in these settings is due to [DMOZ, STOC'23], where they explicitly construct a seedless condenser for a restricted subset of $(g,\ell)$-aCG sources. We show: 1) oNOSF sources a) When $g\leq\ell/2$, we prove that condensing with error 0.99 above rate $\frac{1}{\lfloor \ell/g \rfloor}$ is impossible. In fact, we show that this is tight. b) For $g> \ell/2$, we show the existence of excellent condensers for
Device-independent (DI) quantum cryptography aims at providing secure cryptography with minimal trust in, or characterisation of, the underlying quantum devices. A key step in DI protocols is randomness extraction (or privacy amplification), which typically requires a \textit{seed} of additional bits with sufficient entropy and statistical independence from any bits generated during the protocol. In this work, we propose a method for extraction in DI protocols that does not require a seed and is secure against computationally unbounded quantum adversaries. The core idea is to use the Bell violation of the raw data, rather than its min-entropy, as the extractor promise. We present a complete security proof in a model where the experiment uses memoryless measurement devices acting on an arbitrary joint (across all rounds) state. Our results mark a first step in this alternative, seedless, approach to extraction in DI protocols.
Quantum-proof randomness extraction is essential for handling quantum side information possessed by a quantum adversary, which is widely applied in various quantum cryptography tasks. In this study, we introduce a real-time two-source quantum randomness extractor against quantum side information. Our extractor is tailored for forward block sources, a novel category of min-entropy sources introduced in this work. These sources retain the flexibility to accommodate a broad range of quantum random number generators. Our online algorithms demonstrate the extraction of a constant fraction of min-entropy from two infinitely long independent forward block sources. Moreover, our extractor is inherently block-wise parallelizable, presenting a practical and efficient solution for the timely extraction of high-quality randomness. Applying our extractors to the raw data of one of the most commonly used quantum random number generators, we achieve a simulated extraction speed as high as 64 Gbps.
Gravitational-wave bursts are observable as bright clusters of pixels in spectrograms of strain power. Clustering algorithms can be used to identify candidate gravitational-wave events. Clusters are often identified by grouping together seed pixels in which the power exceeds some threshold. If the gravitational-wave signal is long-lived, however, the excess power may be spread out over many pixels, none of which are bright enough to become seeds. Without seeds, the problem of detection through clustering becomes more complicated. In this paper we investigate seedless clustering algorithms in searches for long-lived narrowband gravitational-wave bursts. Using four astrophysically motivated test waveforms, we compare a seedless clustering algorithm to two algorithms using seeds. We find that the seedless algorithm can detect gravitational-wave signals (at fixed false-alarm and false-dismissal rate) at distances between 150-200% greater than those achieved with the seed-based clustering algorithms, corresponding to significantly increased detection volumes: 420-740%. This improvement in sensitivity may extend the reach of second-generation detectors such as Advanced LIGO and Advanced
Compact binary coalescences are a promising source of gravitational waves for second-generation interferometric gravitational-wave detectors. Although matched filtering is the optimal search method for well-modeled systems, alternative detection strategies can be used to guard against theoretical errors (e.g., involving new physics and/or assumptions about spin/eccentricity) while providing a measure of redundancy. In previous work, we showed how "seedless clustering" can be used to detect long-lived gravitational-wave transients in both targeted and all-sky searches. In this paper, we apply seedless clustering to the problem of low-mass ($M_\text{total}\leq10M_\odot$) compact binary coalescences for both spinning and eccentric systems. We show that seedless clustering provides a robust and computationally efficient method for detecting low-mass compact binaries.
The problem of searching for unmodeled gravitational-wave bursts can be thought of as a pattern recognition problem: how to find statistically significant clusters in spectrograms of strain power when the precise signal morphology is unknown. In a previous publication, we showed how "seedless clustering" can be used to dramatically improve the sensitivity of searches for long-lived gravitational-wave transients. In order to manage the computational costs, this initial analysis focused on externally triggered searches where the source location and emission time are both known to some degree of precision. In this paper, we show how the principle of seedless clustering can be extended to facilitate computationally-feasible, all-sky searches where the direction and emission time of the source are entirely unknown. We further demonstrate that it is possible to achieve a considerable reduction in computation time by using graphical processor units (GPUs), thereby facilitating more sensitive searches.
Current cone jet algorithms, widely used at hadron colliders, take event particles as seeds in an iterative search for stable cones. A longstanding infrared (IR) unsafety issue in such algorithms is often assumed to be solvable by adding extra `midpoint' seeds, but actually is just postponed to one order higher in the coupling. A proper solution is to switch to an exact seedless cone algorithm, one that provably identifies all stable cones. The only existing approach takes N 2^N time to find jets among N particles, making it unusable at hadron level. This can be reduced to N^2 ln(N) time, leading to code (SISCone) whose speed is similar to that of public midpoint implementations. Monte Carlo tests provide a strong cross-check of an analytical proof of the IR safety of the new algorithm, and the absence of any 'R_{sep}' issue implies a good practical correspondence between parton and hadron levels. Relative to a midpoint cone, the use of an IR safe seedless algorithm leads to modest changes for inclusive jet spectra, mostly through reduced sensitivity to the underlying event, and significant changes for some multi-jet observables.
We propose a simple seedless approach to assemble millimeter sized monolayer single colloidal crystals with desired orientations at predetermined locations on an unstructured charged substrate. This approach utilizes the millimeter-ranged fluid flow on the bottom glass substrate induced by an ion exchange resin (IEX) fixed on top of the closed sample cell. This fluid flow increases with decreasing height of the sample cell and increasing radius R of the IEX. For a single inverted pump, millimeter sized monolayer single crystals of hexagonal close packing can be obtained. For two closely spaced (D ~ 4R) pumps, the formed crystals have a predefined orientation along the line connecting the two IEX. By patterning IEX into different structures, colloidal crystals of different complex patterns form. The present method paves a convenient way for fabricating high quality monolayer colloidal crystals for a variety of applications.
This writeup highlights the infrared unsafety of the "midpoint" cone jet-algorithm and provides a brief overview of why this is a serious issue. It then shows how one can build a safe (seedless) cone algorithm and discusses the potential impact on measurements.
A number of detections have been made in the past few years of gravitational waves from compact binary coalescences. While there exist well-understood waveform models for signals from compact binary coalescences, many sources of gravitational waves are not well modeled, including potential long-transient signals from a binary neutron star post-merger remnant. Searching for these sources requires robust detection algorithms that make minimal assumptions about any potential signals. In this paper, we compare two unmodeled search schemes for long-transient gravitational waves, operating on cross-power spectrograms. One is an efficient algorithm first implemented for continuous wave searches, based on a hidden Markov model. The other is a seedless clustering method, which has been used in transient gravitational wave analysis in the past. We quantify the performance of both algorithms, including sensitivity and computational cost, by simulating synthetic signals with a special focus on sources like binary neutron star post-merger remnants. We demonstrate that the hidden Markov model tracking is a good option in model-agnostic searches for low signal-to-noise ratio signals. We also show
Startups and Big Ag are using Crispr gene editing to create crops that taste better and grow on a hotter planet。 But will they find a market
Although many AI applications of interest require specialized multi-modal models, relevant data to train such models is inherently scarce or inaccessible. Filling these gaps with human annotators is prohibitively expensive, error-prone, and time-consuming, leading model builders to increasingly consider synthetic data as a scalable alternative. However, existing synthetic data generation methods often rely on manual prompts, evolutionary algorithms, or extensive seed data from the target distribution - limiting their scalability, explainability, and control. In this paper, we introduce Simula: a novel reasoning-driven framework for data generation and evaluation. It employs a seedless, agentic approach to generate synthetic datasets at scale, allowing users to define desired dataset characteristics through an explainable and controllable process that enables fine-grained resource allocation. We show the efficacy of our approach on a variety of datasets, rigorously testing both intrinsic and downstream properties. Our work (1) offers guidelines for synthetic data mechanism design, (2) provides insights into generating and evaluating synthetic data at scale, and (3) unlocks new oppor
Controlling ensembles of weakly coupled spins typically requires computationally expensive multispin optimisations. We present a compact framework that enables control of weakly coupled spin systems (of any spin), but using RF pulses optimised for a single spin-1/2. We do this by explicitly creating a GRAPE pulse with fixed 'active' evolution times using single spin-1/2 methods, and pulsing on one spin at a time. By enforcing this form uniformly across offsets ('band-schematic' pulses),chemical shift and scalar coupling evolution of the entire system can be precisely controlled. We demonstrate the approach by constructing band-schematic pulses and a continuously irradiated joint INEPT (JINEPT) that achieves band-selective transfer $I_z \rightarrow 2I_zS_z$. The framework is implemented in the software Seedless, which both rapidly generates such pulses and analyses the schematic form of arbitrary pulses, enabling robust multi-spin control, without multi-spin optimisation.
Despite advancements in machine learning for security, rule-based detection remains prevalent in Security Operations Centers due to the resource intensiveness and skill gap associated with ML solutions. While traditional rule-based methods offer efficiency, their rigidity leads to high false positives or negatives and requires continuous manual maintenance. This paper proposes a novel, two-stage hybrid framework to democratize ML-based threat detection. The first stage employs intentionally loose YARA rules for coarse-grained filtering, optimized for high recall. The second stage utilizes an ML classifier to filter out false positives from the first stage's output. To overcome data scarcity, the system leverages Simula, a seedless synthetic data generation framework, enabling security analysts to create high-quality training datasets without extensive data science expertise or pre-labeled examples. A continuous feedback loop incorporates real-time investigation results to adaptively tune the ML model, preventing rule degradation. This proposed model with active learning has been rigorously tested for a prolonged time in a production environment spanning tens of thousands of systems
Secret sharing allows a user to split a secret into many shares so that the secret can be recovered if, and only if, an authorized set of shares is collected. Although secret sharing typically does not require any computational hardness assumptions, its security does require that an adversary cannot collect an authorized set of shares. Over long periods of time where an adversary can benefit from multiple data breaches, this may become an unrealistic assumption. We initiate the systematic study of secret sharing with certified deletion in order to achieve security even against an adversary that eventually collects an authorized set of shares. In secret sharing with certified deletion, a (classical) secret is split into quantum shares which can be verifiably destroyed. We define two natural notions of security: no-signaling security and adaptive security. Next, we show how to construct (i) a secret sharing scheme with no-signaling certified deletion for any monotone access structure, and (ii) a threshold secret sharing scheme with adaptive certified deletion. Our first construction uses Bartusek and Khurana's (CRYPTO 2023) 2-out-of-2 secret sharing scheme with certified deletion as