​=(α∣0⟩+β∣1⟩)(γ∣0⟩+δ∣1⟩)=αγ∣00⟩+αδ∣01⟩+βγ∣10⟩+βδ∣11⟩.​

we apply a Hadamard gate

equal

the

What does it mean for a matrix UUU to be unitary? It’s easiest to answer this question algebraically, where it simply means that U†U=IU^\dagger U = IU†U=I, that is, the adjoint of UUU, denoted U†U^\daggerU†, times UUU, is equal to the identity matrix. That adjoint is, recall, the complex transpose of UUU:

The programming language was started as a side project by Dutch programmer Guido van Rossum.

The language for writing React. Reason's creator also created ReactJS, whose first prototypes were written in SML, a distant cousin of OCaml. We've transcribed ReactML into ReactJS for wide adoption. A few years later, we're now iterating on the future of ReactJS through ReasonReact.

the main reason we built a new multiprocess architecture is that Chromium's multiprocess support was never contributed to the WebKit project. It has always lived in the separate Chromium tree, making it pretty hard to use for non-Chrome purposes.Before we wrote a single line of what would become WebKit2 we directly asked Google folks if they would be willing to contribute their multiprocess support back to WebKit, so that we could build on it. They said no.

I'd say that "dump" in the CS sense, both as noun and verb, is merely another application of its preexisting meanings even without the vulgar one, particularly the ones related to unloading/releasing contents. (For example, "dump truck".)

For some geeky reason, the computer programming world has long maintained a tradition of using words in new ways, with a studied obliviousness to their prior, rude meanings: for example, 'dump'. 'Falsey' is merely another word in this long, and quite useful, tradition.

the CMfg paradigm and concept provides a collaborative network environment (the Cloud) where users can select the suitable manufacturing services from the Cloud and dynamically assemble them into a virtual manufacturing solution to execute a selected manufacturing task

Doing something programatically generally means that you can do it using source code, rather than via direct user interaction or a macro.

The reason SO users explicitly say "programmatically" is to reaffirm that they're asking "programming code" questions and not "IT-style" questions

The Women Who Contributed to Science but Were Buried in Footnotes

He thought that networked digital computing could release and channel neural power in the same way that physics had released and channeled nuclear power, but to far more beneficial effect.

Holographic computing made possible

One is the linked list of lines you mention. I believe this is intended to solve a display problem that TECO (the original language in which Emacs was implemented) had solved differently using the "gap" data structure. The fundamental issue was that if you have a buffer represented as a single block of contiguous text, then insertion on a character-by-character basis can be O(n2), each time you insert a character, you have to copy the entire subsequent buffer over one space.

Lisp macros were also useful for the definition of new control structures, as well as new data structures. In ZWEI, we created a new iterative control structure called charmap, which iterates over characters in an interval. Intervals are stored as doubly-linked lists of arrays, and the starting point might be in the middle of one array and the ending point might be in the middle of another array. The code to perform this iteration was not trivial, and someone reading it might easily not understand the function it was performing, even though that function was the conceptually simple one of iterating over characters. So we created a macro called charmap that expands into the double-loop code to iterate over the characters. It is simple and obvious, and is used in many places, greatly reducing the size of the code and making the functionality obvious at a glance.

It became policy to avoid abbreviations in most cases. In ZWEI, we made a list of several words that were used extremely often, and established 'official' abbreviations for them, and always used only those abbreviations. ... Words not on this list were always spelled out in full.

The use of the mouse is still considered experimental. We know of several editors which depend highly on the use of a mouse for input, but we are not convinced that it is better than a keyboard; after more people start using ZWEI, it will be interesting to see how many of them make heavy use of the mouse and how many hardly use it at all.

Since ZWEI is written in Lisp and lives in the Lisp environment of the Lisp machine, it is in a very good position to interface closely with other elements of that environment.

ZWEI is display-oriented: the text the user is editing is actually displayed (this is relevant because many editors of the time often showed out-of-date text due to efficiency and bandwidth restrictions, putting the burden on the user to imagine what their text looks like currently).

Some paragraphs are devoted to what must have been a novel concept at the time for such a system: that the Lisp Machine was a personal system, not time-shared, and this gave rise to features not viable on time-sharing systems, due to the fact that the user was not contending with other users for resources.

“... applications and services that facilitate collective action and social interaction online with rich exchange of multimedia information and evolution of aggregate knowledge...” [48]

In particular, the fact that most users are only now beginning to experience the ubicomp vision and integrate this new, unique class of technology into their work practices suggests that another change in focus may be on the horizon: “[T]he shift from user-centered design to context-based design corresponds with recent developments in pervasive, ubiquitous computing networks and in the appliances that connect with them, which are radically changing our relationships with personal computing devices” (Gay & Hembrooke, 2003)

Activities also span place; that is, it is common for work to take place outside of the immediate office environment. However, current office technologies sometimes present a very different view of information across different physical and virtual settings.

The idea that activities may exist at different levels of granularity is not a new one. Boer, van Baalen & Kumar (2002) provide a model explaining how an activity at one level of analysis may be modeled as an action—a component of an activity—at another. This holds true for individual users, as in the example provided above, but is even more pronounced when a single activity is viewed from multiple participants’ perspectives.

Additionally, activities need to be represented in such a way that their contents can be shared, with the caveats that individual participants in an activity may have very different perceptions of the activity, they may bring different resources to play over the course of the activity, and, particularly for large activities in which many individual users participate, users themselves may come and go over the life of the activity.

Recognizing the mediating role of the digital work environment in enabling users to meaningfully collaborate is a critical step to ensuring the success of these systems.

User studies and intuition both suggest that the activities that a knowledge worker engages in change—sometimes dramatically—over time. Projects and milestones come and go, and the tools and information resources used within an activity often change over time as well. Furthermore, activities completed in the past and their outcomes often impact activities in the present, and ongoing activities will, in turn, affect activities that will be undertaken in the future. Capturing activity over the course of time has long been a problem for desktop computing.

Supporting the multifaceted aspects of activity in a ubicomp environment becomes a much more complex proposition. If activity is to be used as a unifying organizational structure across a wide variety of devices such as traditional desktop and laptop computers, PDAs, mobile telephones, personal-server style devices (Want et al., 2002), shared public displays, etc., then those devices must all be able to share a common set of activity representations and use those representations as the organizational cornerstone for the user experience they provide. Additionally, the activity representations must be versatile enough to encompass the kinds of work for which each of these kinds of devices are used

The challenges exist due in large part to the inherent complexity of human activity, the technical affordances of the computing tools used in work practice, and the nature of (and culture surrounding) knowledge work.

We describe five challenges for matching computation to activity. These are: •Activities are multifaceted, involving a heterogeneous collection of work artifacts; •Activities are dynamic, emphasizing the continuation and evolution of work artifacts in contrast to closure and archiving; •Activities are collaborative, in the creation, communication, and dissemination of work artifacts; •Activities exist at different levels of granularity, due to varying durations, complexity and ownership; and •Activities exist across places, including physical boundaries, virtual boundaries of information security and access, and fixed and mobile settings.

One of the largest-scalestudies exploring this problem was undertaken at the University of Wash-ington (Fidel et al., 2000), where researchers investigated the information-seeking behavior of teams from two different companies, Boeing andMicrosoft (Poltrock et al., 2003). They found that each team had differentcommunication and information-seeking practices, and that current infor-mation systems are oriented toward individual rather than collaborativeinformation-seeking activities. In practice, though, information seeking isoften embedded in collaboration

SomeIoT applications might require very short response time, somemight involve private data, and some might produce a largequantity of data which could be a heavy load for networks

distributed constructs like Learning Record Stores and xAPI fitting easily within their mental models

As in Slow Food—with its unhygienic soil, disorderly farmers’ markets, and inconvenient seasons—the annoyances of Slow Computing have become pleasures. With community-made software, there’s no one to blame but us, the community. We’re not perfect, but we’re working on it.

Now,thesuggestedexecutiontimeforaBASICprogrammaticsolutiontoPuzzle15is7minutes,4seconds.That'sontheVectra.IfyouareprogrammingonaTandy1000,youcouldexpectthesameprogramtoexecuteinabout28minutes.So,ifyoursolutiontakesoveranhour,youmighttrytospeeditupsomewhat.

The success of Arduino has had the perhaps retrograde effect of convincing an entire generation that the way to sense and actuate the physical world is through imperative method calls in C++, shuffling bits and writing to ports, instead of in an environment designed around signal processing, control theory, and rapid and visible exploration. As a result, software engineers find a fluid, responsive programming experience on the screen, and a crude and clumsy programming experience in the world.

this week’s announcement by Google that a machine made by a Canadian company, D-Wave Systems, which is marketed as “the world’s first commercial quantum computer”, had shown spectacular speed gains over conventional computers. “For a specific, carefully crafted proof-of-concept problem,” Google’s Hartmut Neven reported, “we achieved a 100-million-fold speed-up.”

The Coming of OERRelated to the enthusiasm for digital instructional resources,four-fifths (81percent) of the survey participants agreethat “Open Source textbooks/Open Education Resource(OER) content “will be an important source for instructional resources in five yea

Shared information

Over the last twenty years, the open source community has provided more and more software on which the world’s High Performance Computing (HPC) systems depend for performance and productivity. The community has invested millions of dollars and years of effort to build key components. But although the investments in these separate software elements have been tremendously valuable, a great deal of productivity has also been lost be cause of the lack of planning, coordination, and key integration of technologies necessary to make them work together smoothly and efficiently, both within individual PetaScale systems and between different systems. It seems clear that this completely unco ordinated development model will not provide the software needed to support the unprecedented parallelism required for peta/exascale computation on millions of cores, or the flexibility required to exploit new hardware models and features, such as transact ional memory, speculative execution, and GPUs. This report describes the work of the community to prepare for the challenges of exascale computing, ultimately combing their efforts in a coordinated International Exascale Software Project.