According to the no-cloning theorem it is impossible to create an independent and identical copy of an arbitrary unknown quantum state. We cannot delete any quantum information as well. All changes in time of the state vector in quantum mechanics are described by the action of unitary operators. Accordingly, there must be an operator performing a deleting operation. The operator must be a zero matrix in order to nullify quantum information totally in all cases. But a zero matrix is not a uninaty or hermitian matrix. Therefore there is no such unitary operator that can delete information.

   This might be proven in another way. Let us imagine the double-slit thought experiment where interference exists when we do not know about the system and interference does not when we know about the system. Assume we have a storage where the data is stored and the experiment is being conducted with knowing about the system. Suppose we destroy the storage. What does the screen in the experiment show us? Quantum mechanics tells us that there must not be interference. Should it appear after the data is destroyed? Since the wave function has collapsed it cannot be restored. If there is a chance to delete the information in the experiment, it means that the wave function must go back to the initial state and show us interference, which is a contradiction.

   Based on the foregoing, we will consider the quantum eraser experiment. In that experiment information is neither erased nor disappeared. It is being changed. That is the key point. We increase entropy. If there is a 50 per cent chance to get interference then the entropy = 1 (max value). The same with a spin. If we change spins of elementary particles, for example in the Stern–Gerlach experiment with different axes measurements, we do not delete the information about the states of particles, we increase the entropy. Changing does not equal deleting. 

This article discusses the lexical analyzer, which is an integral part of any compiler.

The task of the lexical analyzer is to split the source code of the program into tokens.

So for example the code

print(1 + 2)

will be tokenized as
print, (, 1, +, 2 and )

N1Loader is designed to provide a simple way for avoiding N+1 issues
of any kind. Gladly, it's super easy to integrate with your GraphQL
API. Without further delay, let's look at a simple but yet detailed
example.

Different navigation message protocols are used for different navigation signal type. This is true even for a single system like NAVSTAR GPS. For example, L1C/A signals have a LNAV protocol, while L2C and L5 signals utilize a CNAV protocol. The newest L1C signal will use CNAV-2. 

The protocol defines a data distribution into frames, subframes, the subframes structure, transmission intervals, data resolution and so on. 

A navigation receiver use the navigation message data flow for several purposes:

1. The data flow allows to resolve a code ambiguity and set the signal time.

2. Ephemeris and clock values are used for the satellite position calculation, pseudorange corrections and coordinates computation.

3. The received data flow and navigation message data can be used for navigation symbols prediction. As result, we can use the wipe-off technique, expand discriminators and significantly increase tracking sensitivity:

Positive Hack Days 11 will begin in a matter of weeks. This international forum on practical security will be held on May 18–19 in Moscow.

As per tradition, PHDays will have three big tracks dedicated to countering attacks (defensive), protection through attack (offensive), and the impact of cybersecurity on business. It is our pleasure to present the first talks.

So you want to learn more about game engines and write one yourself? That's awesome! To help you on your journey, here are some recommendations of C++ libraries and dependencies that will help you hit the ground running.

Hearing is one of the few basic senses that we humans have along with the other our abilities to see, smell, taste and touch. If we couldn't hear, the world as we know it would be less interesting and colorful to us. It would be a total silence - a scary thing, even to imagine. And speaking makes our life so much fun, because what else can be better than talking to our friends and family? Also, we're able to listen to our favorite music wherever we are, thanks to computers and headphones. With the help of tiny microphones integrated into our phones and laptops we are now able to talk to the people around the world from any place with an Internet connection. But computer hardware alone isn't enough - it is computer software that really defines the way how and when the hardware should operate. Operating Systems provide the means for that to the apps that want to use computer's audio capabilities. In real use-cases audio data usually goes the long way from one end to another, being transformed and (un)compressed on-the-fly, attenuated, filtered, and so on. But in the end it all comes down to just 2 basic processes: playing the sound or recording it.

Today we're going to discuss how to make use of the API that popular OS provide: this is an essential knowledge if you want to create an app yourself which works with audio I/O. But there's just one problem standing on our way: there is no single API that all OS support. In fact, there are completely different API, different approaches, slightly different logic. We could just use some library which solves all those problems for us, but in that case we won't understand what's really going on under the hood - what's the point? But humans are built the way that we sometimes want to dig a little bit deeper, to learn a little bit more than what just lies on the surface. That's why we're going to learn the API that OS provide by default: ALSA (Linux), PulseAudio (Linux), WASAPI (Windows), OSS (FreeBSD), CoreAudio (macOS).

The first quarter of the year 2022 has passed; now, it is time to look at the events of Q1 in terms of mitigated DDoS activity and recorded BGP incidents.

Some time ago we discussed how to easy and fast setup 2FA using Google Authenticator API. In this article we describe how to make this working using Microsoft Authenticator app!

In-app messages are targeted notifications sent to customers/ users while they are active on the website or mobile application. They are a very effective way to engage customers as they are already within the application looking for specific information. In-app chat applications help connect better with the users and improve user retention as they are timely and targeted. 

There is a list of well-known electronics design tools for Android which can be found in every review for the last 10 years: “Electrodoc”, “Every Circuit”, “Droid Tesla”, “Electronics Toolbox”, “RF & Microwave Toolbox” and so on. Also, there is a lot of trash on the market that turns finding a good tool into a quest.

This short review is about an unknown but cool tool “Circuit Calculator” working on Android devices and intended for professional electronics designers.

In previous post I've described an example of kogito-based microservice on quarkus in native mode, containing one embedded pmml model with decision tree. While it can be successfully used for prototyping purposes, in the real life microservice might contain several prediction models. From the first view I've got an impression, that inclusion of several models should be a trivial extension of the prototype with one model. We were completely wrong in our assumption, that's the reason, why I've decided to write this post. Another reason, is absence of guides, in which 2 (or more models) are put inside DMN diagrams in kogito framework.

Very often we've heard that some frameworks fit together so good, that they are considered as "match made in heaven". In this article I would like to share our experience regarding integration of those frameworks.

In our last article we made a bunch of promises about our speech synthesis.

After a lot of hard work we finally have delivered upon these promises:

• Model size reduced 2x;
• New models are 10x faster;
• We added flags to control stress;
• Now the models can make proper pauses;
• High quality voice added (and unlimited "random" voices);
• All speakers squeezed into the same model;
• Input length limitations lifted, now models can work with paragraphs of text;
• Pauses, speed and pitch can be controlled via SSML;
• Sampling rates of 8, 24 or 48 kHz are supported;
• Models are much more stable — they do not omit words anymore;

This is a truly break-through achievement for us and we are not planning to stop anytime soon. We will be adding as many languages as possible shortly (the CIS languages, English, European languages, Hindic languages). Also we are still planning to make our models additional 2-5x faster.

We are also planning to add phonemes and a new model for stress, as well as to reduce the minimum amount of audio required to train a high-quality voice to 5 — 15 minutes.

As usual you can try our model in our repo or in colab.

Quick reminder for those, who would like to broaden their horizons: there is “PyCon DE Berlin 2022 ” coming up already next week!

Recently I've received an interesting request from a client about one of our Django projects.
He asked if it would be possible to show an inline component above other fields in the Django admin panel.

At the beginning I thought, that there shouldn't be any issue with that.
Though there was no easy solution other then installing another battery to the project. My gut feeling told me, there were another way around that problem.

In this article, there is the work with the PYD 1588 digital Infrared passive motion sensor introduced. The PYD 1588 is a serial opposed format, two element detector based on pyroceramic produced by the Excelitas Technologies. This sensor represents a low-power (3.0 uA with 1.8 V source voltage as in the documentation said) passive component with two sensible elements, which measure the thermal infrared radiation stream.

The signal is converted to a digital value using Sigma-Delta and DSP techniques. A configurable motion detection unit is implemented, which can generate an interrupt recognized by the external microcontroller (MCU) in case motion is detected. The motion detection unit contributes to significant device energy efficiency increasing via putting the MCU to a low-power sleep mode with no periodic raw data request and its analyzing necessity.

There has been a lot of debate going on among iOS developers with regards to the comparison between SwiftUI and UIKit. Have you been planning to develop a chat app for iOS and are confused as to which framework you should opt for?

Fret not! We have got your back. In this article, we shall discuss all the relevant aspects revolving around these two and compare them in detail. Stay with us and read on! 

As iOS developers, you must be knowing about both the UIKit and Swift UI frameworks. However, we would like to provide you with a quick overview to refresh your understanding. Let's take them up one by one

In this article, I will tell you about a-few-years journey of scaling the Elasticsearch cluster in production environment, which is one of the vital elements of the iPrice technology stack. 
I will describe challenges we encountered and how we approached them.

In this article, we would like to compare the core mathematical bases of the two most popular theories and associative theory.