Zotero Catalogue

Relational joins are at the core of relational algebra, which in turn is the core of the standard database query language SQL. As their evaluation is expensive and very often dominated by the output size, it is an important task for database query optimisers to compute estimates on the size of joins and to find good execution plans for sequences of joins. We study these problems from a theoretical perspective, both in the worst-case model, and in an average-case model where the database is chosen according to a known probability distribution. In the former case, our first key observation is that the worst-case size of a query is characterised by the fractional edge cover number of its underlying hypergraph, a combinatorial parameter previously known to provide an upper bound. We complete the picture by proving a matching lower bound, and by showing that there exist queries for which the join-project plan suggested by the fractional edge cover approach may be substantially better than any join plan that does not use intermediate projections. On the other hand, we show that in the average-case model, every join-project plan can be turned into a plan containing no projections in such a way that the expected time to evaluate the plan increases only by a constant factor independent of the size of the database. Not surprisingly, the key combinatorial parameter in this context is the maximum density of the underlying hypergraph. We show how to make effective use of this parameter to eliminate the projections.

A lawsuit filed in federal court Thursday accuses Gomez, her mother and their Wondermind mental health startup co-founder of misrepresenting the financial health of the company to investors as it “collapsed around them.”

Diffusion models typically inject isotropic Gaussian noise, disregarding structure in the data. Motivated by the way quantum squeezed states redistribute uncertainty according to the Heisenberg uncertainty principle, we introduce Squeezed Diffusion Models (SDM), which scale noise anisotropically along the principal component of the training distribution. As squeezing enhances the signal-to-noise ratio in physics, we hypothesize that scaling noise in a data-dependent manner can better assist diffusion models in learning important data features. We study two configurations: (i) a Heisenberg diffusion model that compensates the scaling on the principal axis with inverse scaling on orthogonal directions and (ii) a standard SDM variant that scales only the principal axis. Counterintuitively, on CIFAR-10/100 and CelebA-64, mild antisqueezing - i.e. increasing variance on the principal axis - consistently improves FID by up to 15% and shifts the precision-recall frontier toward higher recall. Our results demonstrate that simple, data-aware noise shaping can deliver robust generative gains without architectural changes.

An important task in quantum computing is unitary circuit synthesis compatible with physical hardware constraints. This problem has a natural hybrid structure as local single-qubit gates are continuous variables on the Lie group $SU(2)$ while the entangling circuit structure is discrete and hardware-dependent. In this work, we use generative models to perform quantum circuit synthesis incorporating both the natural $SU(2)$ manifold geometry of quantum gates and hardware constraints that determine the overall circuit structure. Our model comprises two components: a circuit skeleton selector that chooses an entangling circuit and a diffusion model that generates quantum gates on the given circuit template by performing diffusion on the curved manifold $\mathrm{SU(2)} \simeq S^3$ itself. We demonstrate this approach with unitary compilation of physically motivated three-qubit Hamiltonian simulation targets such as the Transverse Field Ising Model and the Heisenberg-XXZ Model and show that Lie group diffusion outperforms comparable baselines. The synthesised circuits can also be customised subject to constraints, which we demonstrate by producing circuits with large and small gate rotation angles for the same target unitary evolution. We also investigate the fidelity-complexity frontier of the synthesised gates to demonstrate that the circuit selector learns to select circuits that balance fidelity with complexity rather than collapsing onto the most expansive entangling template. These results demonstrate that Lie group diffusion provides a natural generative framework for hardware-aware quantum circuit synthesis.

Physicist, Tinkerer

An important task in quantum computing is unitary circuit synthesis compatible with physical hardware constraints. This problem has a natural hybrid structure as local single-qubit gates are continuous variables on the Lie group $SU(2)$ while the entangling circuit structure is discrete and hardware-dependent. In this work, we use generative models to perform quantum circuit synthesis incorporating both the natural $SU(2)$ manifold geometry of quantum gates and hardware constraints that determine the overall circuit structure. Our model comprises two components: a circuit skeleton selector that chooses an entangling circuit and a diffusion model that generates quantum gates on the given circuit template by performing diffusion on the curved manifold $\mathrm{SU(2)} \simeq S^3$ itself. We demonstrate this approach with unitary compilation of physically motivated three-qubit Hamiltonian simulation targets such as the Transverse Field Ising Model and the Heisenberg-XXZ Model and show that Lie group diffusion outperforms comparable baselines. The synthesised circuits can also be customised subject to constraints, which we demonstrate by producing circuits with large and small gate rotation angles for the same target unitary evolution. We also investigate the fidelity-complexity frontier of the synthesised gates to demonstrate that the circuit selector learns to select circuits that balance fidelity with complexity rather than collapsing onto the most expansive entangling template. These results demonstrate that Lie group diffusion provides a natural generative framework for hardware-aware quantum circuit synthesis.

Physicist, Tinkerer

Launch guarded GPU jobs or turn editable examples into LoRA, QLoRA, and Full supervised fine-tunes on RunPod or Prime Intellect.

A 250-country audit shows OpenAI's new cyber verification gate exactly matches US export Country Groups D:1 and D:5, rows Georgia inherited from the Soviet Union.

The Near-Earth Object Wide-field Infrared Explorer (NEOWISE) mission provides a decade of all-sky time-series data at 3.4 and 4.6 μm and an unprecedented…

A Ramp Labs writeup on using KV cache compaction to share memory efficiently across multi-agent systems.

Learn how Python serialization vulnerabilities in Pickle can lead to remote code execution and how to mitigate the risks effectively.

One of my favourite ways to take an ordinary day and give it some extra meaning, or make it more memorable, is to turn the day into a “tasting” day.

After declining for a decade, participation in tackle football has started to tick back up, thanks to safety changes. But a landmark study raises fresh concerns.

After declining for a decade, participation in tackle football has started to tick back up, thanks to safety changes. But a landmark study raises fresh concerns.

Because of its pale color, the Egyptians associated silver with the moon, ritual purity, and the bones of the gods.

I say this reasonably often about places I visit, regardless of what continent they’re on, but Egypt definitely felt like India.

Psychology is the scientific study of the mind and behavior. Its subject matter includes the behavior of humans and nonhumans, both conscious and unconscious phenomena, and mental processes such as thoughts, feelings, and motives. Psychology is an academic discipline of broad scope, crossing the boundaries between the natural and social sciences. A professional practitioner or researcher involved in the discipline is called a psychologist. Some psychologists can also be classified as behavioral or cognitive scientists. Some psychologists attempt to understand the role of mental functions in individual and social behavior. Others explore the physiological and neurobiological processes that underlie cognitive functions and behaviors. Biological psychologists seek an understanding of the emergent properties of brains, linking the discipline to neuroscience. As social scientists, psychologists aim to understand the behavior of individuals and groups. As part of an interdisciplinary field, psychologists are involved in research on perception, cognition, attention, emotion, intelligence, subjective experiences, motivation, brain functioning, and personality. Psychologists' interests extend to interpersonal relationships, psychological resilience, family resilience, and other areas within social psychology. They also consider the unconscious mind. Research psychologists employ empirical methods to infer causal and correlational relationships between psychosocial variables. Some, but not all, clinical and counseling psychologists rely on symbolic interpretation. While psychological knowledge is often applied to the assessment and treatment of mental health problems, it is also directed towards understanding and solving problems in several spheres of human activity. By many accounts, psychology ultimately aims to benefit society. Many psychologists are involved in some therapeutic role, practicing psychotherapy in clinical, counseling, or school settings. Other psychologists conduct scientific research on a wide range of topics related to mental processes and behavior. Typically, the latter group of psychologists works in academic settings (e.g., universities, medical schools, or hospitals). Another group of psychologists is employed in industrial and organizational settings. Yet others are involved in work on human development, aging, sports, health, forensic science, education, and the media.

Weird may refer to:

Coupling and fertility are falling. In Finland, Mexico, Peru, South Korea, Thailand, Turkey and the US, both metrics point downwards.

This is a brief note about resumes and hiring. At Terraform Industries, I’ve been doing a lot of recruiting recently and it’s helped me crystallize a few ideas I’ve had in this ar…

No drilling required

How to build, run and maintain an A+ engineering team across multiple projects with nothing but Google Sheets and a 10-minute closeout rule. Lucie Nurdin, PhD. Lucie is the Reactor Lead Engineer at…

[Continuing our series of posts from Terraform team members. Terraform is actively hiring for a range of roles. Send us your best one pager!] I’m Chandhana Sathishkumar and I have an odd curi…

Trying to reflect on years 1-15...

Independent research on cognition, computing, and education.

The whole OpenAI/Hugging Face story in plain English

Collective intelligence can emerge when individuals coordinate through a shared environment, allowing local actions to accumulate into durable social organization. Language-model agents offer a new substrate for this process, yet most multi-agent systems rely on direct conversation, predefined roles, or centralized workflows. It remains unclear whether decentralized agents can build functional technologies and outperform independent search. Here, initially homogeneous LLM agents in SwarmWorld self-organize without assigned roles or recipes into evolving technological societies. Agents explore a spatial environment, process resources, test materials, construct persistent artifacts, and write executable controllers evaluated by a deterministic simulator under unseen disturbances after the agents are removed. SwarmWorld splits cognition from consequence: agents propose architectures and controllers within fixed action and material schemas, while the simulated world determines function. Shared societies develop broader, more resilient technological portfolios than a strong best-of-N isolated-search baseline, although isolated search remains competitive for the strongest artifact. Agents differentiate into exploration, construction, maintenance, and coordination behaviors, transitioning as the world matures. Technologies accumulate through collaborative construction, executable inheritance, and persistent agent-artifact networks, with most reuse beginning through physical observation rather than communication. Explicit cultural mechanisms amplify collaboration and organization, but functional benefits depend on outcome and timescale. Physical stigmergy alone supports capable societies, while interaction drives persistent technological ecologies rather than universally superior individual inventions.

Polarons are quasiparticles that easily form in polarizable materials due to the coupling of excess electrons or holes with ionic vibrations. These quasiparticles manifest themselves in many different ways and have a profound impact on materials properties and functionalities. Polarons have been the testing ground for the development of numerous theories, and their manifestations have been studied by many different experimental probes. This Review provides a map of the enormous amount of data and knowledge accumulated on polaron effects in materials, ranging from early studies and standard treatments to emerging experimental techniques and novel theoretical and computational approaches.

We present a theoretical formulation for studying the pH-dependent interfacial coverage of semiconductor−water interfaces through ab initio electronic structure calculations, molecular dynamics simulations, and the thermodynamic integration method. This general methodology allows one to calculate the acidity of the individual adsorption sites on the surface and consequently the pH at the point of zero charge, pHPZC, and the preferential adsorption mode of water molecules, either molecular or dissociative, at the semiconductor−water interface. The proposed method is applied to study the BiVO4(010)− water interface, yields a pHPZC in excellent agreement with the experimental characterization. Furthermore, from the calculated pKa values of the individual adsorption sites, we construct an ab initio concentration diagram of all adsorbed species at the interface as a function of the pH of the aqueous solution. The diagram clearly illustrates the pH-dependent coverage of the surface and indicates that protons are found to be significantly adsorbed (∼1% of available sites) only in highly acidic conditions. The surface is found to be mostly covered by molecularly adsorbed water molecules in a wide interval of pH values ranging from 2 to 8. Hydroxyl ions are identified as the dominant adsorbed species at pH larger than 8.2.

The solvation model proposed by Fattebert and Gygi [J. Comput. Chem. 23, 662 (2002)10.1002/jcc.10069] and Scherlis et al. [J. Chem. Phys. 124, 074103 (2006)10.1063/1.2168456] is reformulated, overcoming some of the numerical limitations encountered and extending its range of applicability. We first recast the problem in terms of induced polarization charges that act as a direct mapping of the self-consistent continuum dielectric; this allows to define a functional form for the dielectric that is well behaved both in the high-density region of the nuclear charges and in the low-density region where the electronic wavefunctions decay into the solvent. Second, we outline an iterative procedure to solve the Poisson equation for the quantum fragment embedded in the solvent that does not require multigrid algorithms, is trivially parallel, and can be applied to any Bravais crystallographic system. Last, we capture some of the non-electrostatic or cavitation terms via a combined use of the quantum volume and quantum surface [M. Cococcioni, F. Mauri, G. Ceder, and N. Marzari, Phys. Rev. Lett. 94, 145501 (2005)10.1103/PhysRevLett.94.145501] of the solute. The resulting self-consistent continuum solvation model provides a very effective and compact fit of computational and experimental data, whereby the static dielectric constant of the solvent and one parameter allow to fit the electrostatic energy provided by the polarizable continuum model with a mean absolute error of 0.3 kcal/mol on a set of 240 neutral solutes. Two parameters allow to fit experimental solvation energies on the same set with a mean absolute error of 1.3 kcal/mol. A detailed analysis of these results, broken down along different classes of chemical compounds, shows that several classes of organic compounds display very high accuracy, with solvation energies in error of 0.3-0.4 kcal/mol, whereby larger discrepancies are mostly limited to self-dissociating species and strong hydrogen-bond-forming compounds.

CBC’s reporting on terrorism, wherever it occurs, has always been guided by the principle of attribution, and like other major news organizations, it has been our practice for decades.

The curb cut effect is the phenomenon of disability-friendly features being used and appreciated by a larger group than the people they were designed for. The phenomenon is named for curb cuts – miniature ramps comprising parts of sidewalk – which were first made for wheelchair access in particular places but were also welcomed by people pushing strollers, carts or luggage. Curb cuts are now ubiquitous and no longer widely recognized as a disability-accessibility feature. Another example is hearing people using television closed captioning. The curb cut effect is a subset of universal design, which is the purposeful design of an environment so that it is accessible to all people regardless of ability or disability. The curb cut effect differs slightly from universal design, as the curb cut phenomenon is often unintentional rather than purposeful but results in a similar outcome.

A guide for fourteen-year-olds and fourteen-year-olds at heart