The Bernstein-Vazirani (BV) algorithm is frequently taught as a canonical example of quantum parallelism, yet the standard interference-based explanation often obscures its underlying simplicity. We present a geometric reframing in which the Hadamard gate "wrapping" acts as a global basis rotation rather than a generator of computational complexity. This perspective reveals that the algorithm is effectively a classical linear computation over GF(2) performed in the conjugate Fourier basis, with the apparent parallelism arising from coordinate transformation. Building on Mermin's earlier pedagogical shortcut, which presented a 'classical' circuit equivalent but stopped short of explicitly labeling it as such, we elevate this to a formal geometric framework. In the extension, we distinguish between globally rotated circuits -- which we reveal as classical linear computations -- and topologically twisted circuits that generate quantum entanglement. We introduce a pedagogical taxonomy distinguishing (1) pure computational-basis circuits, (2) globally rotated circuits (exemplified by Bernstein-Vazirani), and (3) topologically twisted circuits involving non-aligned subsystem bases. This framework allows viewing the Gottesman-Knill theorem from a new angle, extends students' understanding of phase kickback and the 'Ricochet Property'. Furthermore, it provides a more intuitive starting point for explaining Bell-pair extensions through concrete circuit derivations and Qiskit simulations suitable for undergraduate quantum information courses. The outlook explores how this geometric view paves the way for understanding entanglement as topological twists.
Lucas Q. Galvão, Anna Beatriz M. de Souza, Alexandre Oliveira S. Santos
et al.
Quantum computing enables the efficient resolution of complex problems, often outperforming classical methods across various applications. In 2009, Harrow, Hassidim and Lloyd proposed an algorithm for solving linear systems of equations, demonstrating exponential speedup (under ideal conditions) with a complexity of $poly(\log N)$, in contrast to classical approaches, which in the general case exhibit a complexity of $O(N^3)$, although they can achieve $O(N)$ in specific cases involving sparse matrices. This algorithm holds promise for advancements in machine learning, the solution of differential equations, linear regression, and cryptographic analysis. However, its structure is intricate, and there is a notable lack of detailed instructional materials in the literature. In this context, this paper presents a tutorial addressing the physical and mathematical foundations of the HHL algorithm, aimed at undergraduate students, explaining its theoretical construction and its implementation for solving linear equation systems. After discussing the underlying mathematical and physical concepts, we present numerical examples that illustrate the evolution of the quantum circuit. Finally, the algorithm's complexity, limitations, and future prospects are analyzed. The examples are compared with their classical simulations, allowing for an operational assessment of the algorithm's performance.
Among the many perplexing results of quantum mechanics is one that contradicts a result from introductory physics: the possibility of finding a quantum particle in a region that would be forbidden classically by energy conservation. An especially interesting example of this phenomenon with practical applications is quantum tunneling. Here we investigate the reasons for this puzzling result by focusing on the difference between how quantities like kinetic and potential energy are represented mathematically in classical and quantum mechanics. In quantum mechanics, physical observables, like energy, are represented by operators rather than real numbers. The consequences of this difference will be illustrated explicitly using a toy model in which the kinetic and potential energy operators are represented by $2 \times 2$ matrices, which do not commute like their classical analogs. This model will then illustrate how classically perplexing results, like a quantum particle being found in the forbidden region, can arise.
Luis Medrano Navarro, Luis Martín Moreno, Sergio G Rodrigo
The research in Artificial Intelligence methods with potential applications in science has become an essential task in the scientific community last years. Physics Informed Neural Networks (PINNs) is one of this methods and represent a contemporary technique that is based on the fundamentals of neural networks to solve differential equations. These kind of networks have the potential to improve or complement classical numerical methods in computational physics, making them an exciting area of study. In this paper, we introduce PINNs at an elementary level, mainly oriented to physics education so making them suitable for educational purposes at both undergraduate and graduate levels. PINNs can be used to create virtual simulations and educational tools that aid in understating complex physical concepts and processes where differential equations are involved. By combining the power of neural networks with physics principles, PINNs can provide an interactive and engaging learning experience that can improve students' understanding and retention of physics concepts in higher education.
Balance (Counterfeit coin) puzzles have been part of recreational mathematics for a few decades. A particular type of Counterfeit coin puzzle is known in the literature as the "Beam balance puzzle". An abstract solution to it is provided by Iwama et.al as a modification of the Bernstein-Vazirani algorithm, making use of quantum parallelism and entanglement. Moreover, during this pandemic, group testing has proved to be an efficient algorithm to save time and cost of testing specimens for the presence of infection. In this article, we propose a "Binary Spring Balance" (BSB) puzzle, to facilitate a unified picture of the counterfeit coin problem and the testing for infection problem, as both aim to reduce the number of queries. We then showcase two solutions to the BSB problem, one using bits and other using classical-qubits ('cebits") for querying. Both solutions are demonstrated using circuits. In this pursuit, we develop a modified optical implementation of Bernstein-Vazirani algorithm using only polarizers (no need of beam splitters), which has surprisingly not yet been proposed earlier. Under the pretext of this demonstration we question why we have not yet developed testing mechanisms inspired by Bernstein-Vazirani algorithm for the pandemic, as they solve the problem in single query, they have no issues related to prevalence of infection in the population, nor are they plagued by the issue of dilution of samples due to pooling. The modified implementation of Bernstein-Vazirani algorithm using polarizers can also be a cost-effective demonstration in an undergraduate lab.
High Energy Physics processes, such as hard scattering, parton shower, and hadronization, occur at colliders around the world, e.g., the Large Hadron Collider in Europe. The various steps are also components within corresponding Monte-Carlo simulations. They are usually considered to occur in an instant and displayed in MC simulations as intricate paths hard-coded with the HepMC format. We recently developed a framework to convert HEP event records into online 3D animations, aiming for visual Monte-Carlo studies and science popularization, where the most difficult parts are about designing an event timeline and particles' movement. As a by-product, we propose here an event-time-frame format for animation data exchanging and persistence, which is potentially helpful in other visualization works. The code is maintained at https://github.com/lyazj/hepani, and the web service is available at https://ppnp.pku.edu.cn/hepani/index.html.
In this paper we present a simple dimensional analysis exercise that allows us to derive the equation for the Hawking temperature of a black hole. The exercise is intended for high school students, and it is developed from a chapter of Stephen Hawking's bestseller A Brief History of Time.
In the world of communication, nobody can be out of the fray! Since many years science communication and more in general the ability of a researcher to communicate his/her work to founding agency, policy makers, entrepreneurs and public at large, starts to be a fundamental skill of the researchers job. This skill is needed and requested to access funds and successfully disseminate the research outcome, as well as to engage society in understanding science and its benefits. Moreover, due to the large decrease of research funds and of people starting scientific carrier, researchers must be in the front line to promote the scientific culture in order to invert the dreadful trend of last years. Where are we and where are we going to? We try to answer such questions introducing successful models that can be used without huge overloads for our job. This paper reports on the experience of one of the largest and oldest project in Europe of the Marie Sklodowska-Curie Actions European Researchers' Night and describes how this project followed the evolution in science communication.
We describe a hands-on accurate demonstrator for cosmic rays realized by six high school students, whose main aim is to show the relevance and the functioning of the principal parts of a cosmic rays telescope (muon detector), with the help of two large size wooden artifacts. The first one points out how cosmic rays can be tracked in a muon telescope, while the other one shows the key avalanche process of electronic ionization that effectively allows muon detection through a photomultiplier. Incoming cosmic rays are visualized in terms of laser beams, whose 3D trajectory is highlighted by the turning on of LEDs on two orthogonal matrices. Instead the avalanche ionization process is demonstrated through the avalanche falling of glass marbles on an inclined plane, finally turning on a LED. A pictured poster accompanying the demonstrator is as well effective in assisting cosmic rays demonstration and its detection. The success of the demonstrator has been fully proven by general public during a Science Festival, the corresponding project winning the Honorable Mention in a dedicated competition.
An explanation for why hot water will sometime freeze more rapidly than cold water is offered. Two specimens of water from the same source will often have different spontaneous freezing temperatures; that is, the temperature at which freezing begins. When both specimens supercool and the spontaneous freezing temperature of the hot water is higher than that of the cold water, then the hot water will usually freeze first, if all other conditions are equal and remain so during cooling. The probability that the hot water will freeze first if it has the higher spontaneous freezing temperature will be larger for a larger difference in spontaneous freezing temperature. Heating the water may lower, raise or not change the spontaneous freezing temperature. The keys to observing hot water freezing before cold water are supercooling the water and having a significant difference in the spontaneous freezing temperature of the two water specimens. We observed hot water freezing before cold water 28 times in 28 attempts under the conditions described here.
In this pedagogical work we point out a subtle mistake that can be done by undergraduate or graduate students in the computation of the electrostatic energy of a system containing charges and perfect conductors if they naively use the image method. Specifically, we show that the naive expressions for the electrostatic energy for these systems obtained directly from the image method are wrong by a factor 1/2. We start our discussion with well known examples, namely, point charge-perfectly conducting wall and point charge-perfectly conducting sphere and then proceed to the demonstration of general results, valid for conductors of arbitrary shapes.
In this essay, I attempt to provide supporting evidence as well as some balance for the thesis on `Transforming socio-economics with a new epistemology' presented by Hollingworth and Mueller (2008). First, I review a personal highlight of my own scientific path that illustrates the power of interdisciplinarity as well as unity of the mathematical description of natural and social processes. I also argue against the claim that complex systems are in general `not susceptible to mathematical analysis, but must be understood by letting them evolve over time or with simulation analysis'. Moreover, I present evidence of the limits of the claim that scientists working within Science II do not make predictions about the future because it is too complex. I stress the potentials for a third `Quantum Science' and its associated conceptual and philosophical revolutions, and finally point out some limits of the `new' theory of networks.