The LHC @ home: How to build an electromagnet

At the LHC, the main experiment at CERN, protons and other charged particles generated during collisions are deflected using powerful electromagnets. These magnets can yield enormous B fields of several Tesla. For comparison, Earth’s magnetic field has a strenght of ~10^-4 T, a “natural” unit which is called Gauss after the guy who measured it first in 1835.  How do these magnets work exactly? In their simplest form, they are solenoids. A solenoid is a loop of wire which produces a magnetic field when an electric current is passed through it. The magnetic field generated by such a device can be calculated beforehand by this master formula: 

B = μ * n * I,

where:

• μ is the magnetic permeability of the medium
• n is the number of coils per meter
• I is the intensity of electric current measured in Ampere.

In the void, μ = 4*3.14*10^-7 = μ_0 which is an extremely small number! While air, plastic and wood have very low μ, metals usually provide a higher value. You can write this property as relative permeability w.r.t. void μ_R = μ / μ_0 or simply μ = μ_R * m_0 (easier for straightforward calculations IMHO). Just to give you some examples of μ:

• Mu-metal: 2.5 * 10^-2 (you won’t find this at home, 75% nickel, 15% iron, plus copper and molybdenum)
• Ferrite (nickel-zinc):  8 * 10^-4
• Steel: 8.75 * 10^-4
• Nickel: 1.25 * 10^-4
• Aluminium, Copper, water: 1.25 * 10^-6
• Superconductors: 0 (due to Meissner effect)

As for I, the current you can afford to use in a “homework” setting is at most 0.8A.  A 9V battery can tipically supply 0.5Ah. The number of coils per meter depends usually on the thickness of the wire and the number of layers. We will discuss it later on. All in all, what you should get from this considerations is that the B field you can create is usually quite weak. In fact, in order to produce an enormous field the LHC makes use of superconducting magnets, whose wires have a almost naught resistance thanks to this peculiar phenomenon called superconductivity. You can drive a current of several kA (!!!) in a superconducting wire! Unfortunately, at present it is practically impossible to do this at home. However, we can learn how to make a “normal” electromagnet using some stuff you can easily buy at your preferred electric shop.

• Copper wire (or better enameled copper wire)
• Some kind of metallic core for your solenoid (a screw in our example)
• Tape
• An AC/DC transformer, possibly with variable outgoing tension 1.5 – 12V, OR a series of alkaline AA (1.5V ~2000 mAh) batteries
• A compass or a glass of water + a needle
• Optional: a LED

So, let’s get it started. First of all, you have to build up your solenoid. Armed with patience, make the first round of coils. When you arrive at the end of the metallic core, put some tape to block its end, go the beginning again and start over. Iterate this several times (at least 4). Now you can attach your solenoid to the power supply you chose. Optionally, you can put a LED in series to check if the current is flowing.

Scheme of the solenoid

Solenoid made with an iron screw

In my case, the B field I can generated is (give or take):

I = V/R = 1.2V / ~10Ohm = 0.12A

B = μ * n * I = 1.25 * 10^-4 * ( 4 layers * 10 loops / 10 cm ) * 0.006A = 6 mT

For comparison, this is the  strenght of a typical fridge magnet. According to Ohm’s first law, you

should try to keep the resistance of the circuit as low as possible, avoiding a short-circuit. This is why a LED is quite useful in this place! If you can tune you transformer output voltage, set it at minimum.

Solenoid made with a nickel core

There are several ways to see the effect of your electromagnet. For instance, you

can take it close to a compass – you’ll see the needle following your magnet. Or, you could attract some iron dust. I tried with a metallic non-magnetized needle, but unfortunately my B field wasn’t strong enough to lift it. I chose to test it in a fancy way: I put some water in a candle support, and I placed a needle floating on its surface – surface tension will keep it from sinking. Then, just act as you would with a compass. It works!

Recharge a 9V NiMh battery with a Solar Panel / Constant Current Generator

Hi guys,

if you enjoyed the previous post solar-powered Arduino board, you should keep reading this one as well to improve your solar power generator. In fact, with that setup the 9V battery would decay too soon: A NiMh (Nichel – metal hydroxide) battery must be recharged with a constant current generator, a solar panel alone is not.

In order to do so, we can assemble a quite simple circuit using the following components:

• LM317M or LM317LZ
• A 200Ohm trimmer
• 10Ohm resistance
• A LED to check if the current is actually flowing

The core of this circuit is the integrated three-terminal adjustable linear voltage regulator LM317. The ‘adj’ pin is a control terminal that is used to adjust the output current. So, the trick is to use a variable resistor (in our case, a trimmer with a small resistance put in front of it) to set the current at a definite value.

Constant current generator with a LM317

With an input DC voltage of max 24V, and the resistances shown in the diagram, one can obtain an output current of:

I_out = 1.2/(10 + R_trim) [A]

This current must be less than 1/10 of the battery output, e.g. for a 750mAh battery the output current must be less than 75mA. As usual, it is customary to insert a capacitor (100uF should be ok) in parallel at the input node to smooth out fast-varying voltages.

Pin diagram of a LM317LZ

Temperature Measurement using Arduino and a Thermistor

Components

• Arduino Duemilanove Board, a USB cable and of course a PC/Mac
• A 10kOhm thermistor
• A 10kOhm resistor
• A breadboard wires

Hot topic

It’g getting hotter and hotter. Is it due to global warming? Who knows, but in the meanwhile we can measure the temperature with our Arduino board and a thermistor. A thermistor is simply a type of resistor whose resistance varies with temperature. If we knew how it varies, we could extract the temperature from the measurement of the resistance (or, better, the voltage across its ends).

The Steinhart-Hart equation

In first approximation, the resistance is proportional to the temperature:

R = k(T-T0)

This can work for a narrow temperature range, but we can figure out something more accurate, up to the third order:

1/T = A + B logR + C ( logR )^3

The temperature T is expressed in Kelvin, the resistance R in Ohm and the parameters A, B and C must be determined experimentally, or taken from the datasheet.

If you want to be even more rigorous, you have to include a self-heating effect in the picture. I’ll give it as a black-box formula:

T = T(steinhart-hart) – V^2 / k*R

Where k is the dissipation constant, usually given in units of mW/degree C.

Setting things up

In this case the setup is really simple. First of all, connect the Arduino board to the computer (in my case, it’s a Mac) via the USB cable. Now, connect the GND terminal to the B line of the breadbord (use a black wire), and Arduino’s +5V output to the A line (use a red wire). Now, put the 10kOhm resistance between the (+) bus and a horizontal line. Now, connect the thermistor between the horizontal line you chose and the (-) bus, the common ground. Last but not least, connect Arduino’s Analog Input #0 to the horizontal line (X).

(+5V) —- R —- X —- Th — GND

Programme Arduino

Now, the geek part. We have to teach Arduino how to calculate the temperature and give us the answer.

#include <math.h> #define READING_PIN 0 double R1 = 10000.0; //resistance put in parallel double V_IN = 5.0; double A = 1.129148e-3; double B = 2.34125e-4; double C = 8.76741e-8; double K = 9.5; // mW/dec C – dissipation factor double SteinhartHart(double R) { // calculate temperature double logR  = log(R); double logR3 = logR * logR * logR; return 1.0 / (A + B * logR – C * logR3 ); } void setup() { Serial.begin(9600); } void loop() { double adc_raw = analogRead(READING_PIN); //Serial.println(adc_raw); double V =  adc_raw / 1024 * V_IN; Serial.print(“V =”); Serial.print(V); //calculate resistance double R_th = (R1 * V ) / (V_IN – V); Serial.print(“V   R_th = “); Serial.print(R_th); double kelvin = SteinhartHart(R_th) – V*V/(K * R_th); double celsius = kelvin – 273.15; Serial.print(“Ohm  —   T = “); Serial.print(celsius); Serial.print(“C\n”); delay(1000); }

Compile it and send it to Arduino. Open up the Serial Terminal, and enjoy the output stream.

Now it’s up to you

Probably, the temperature you’re measuring is quite unconvincing. You have to set up the coefficient according to you thermistor. This will be covered in a following post…

Solar-Powered Arduino Board

Components

• Arduino Duemilanove Board
• 12V Solar Panel
• 1N4007 Diode
• 25V 100uF Capacitor
• 9V Rechargeable Battery and connector
• A breadboard and some wires (suggested red and black)
• A multimeter to measure tensions

1) Green Power

Arduino datasheet suggests us to power it with 6-20V, being aware that the upper limit could be dangerous. It seems that 9V fits well, and it’s of course very easy to find a 9V battery in a shop. But if we really want to start our own little Green Revolution, we would like to get this electricity from some renewable source, e.g. the Sun, so we need a solar panel. It is a device made up of solar (or photovoltaic) cells, which convert light directly into electricity by the photovoltaic effect.

Now, one problem is that you can be sure that a solar panel will not provide a 9V tension constantly: As everybody know, the Sun walks through the sky during the day, and the energy that reach our panel (even given an ideal 100% conversion efficiency) changes according to the depth of air that the sun rays cross. As a matter of fact, at noon this depth is lower than at dawn or dusk. Moreover, during the night the solar panel is completely useless. So? If you’re smart enough (or if you google it), the solution is to use the solar panel to charge a 9V rechargeable battery, which in turn powers the Arduino board.

There are many solar panels on the market, so which one fits best with our Arduino board? My rule of thumb is to minimize the cost while maximizing the voltage. You can buy a 12V solar panel for ~20€, probably less. Just remember that we want to charge a 9V battery, so it’s better if our solar panel provides more than 9V.

2) Re-charging the battery

This part is the core of our little experiment. We want to wire up the board so that once the circuit is working fine, we just have to put the Arduino board in parallel to power it up.

2.1) Basic setup (wrong one)

In a circuit, electrical current (I) flows from the positive (+) outlet of the battery to the negative (-) one, just like a river flows from the mountain to the sea. Anyway, remember that in this case the charge carriers, the electrons, flows the other way around. Now, if you connect a battery to a load (e.g. a resistance), you basically deplete the battery extracting the accumulated charges. If you want to re-charge the battery, you have to push electrons inside the battery. Thus, the idea is to connect the same-sign sides of the solar panel and the battery, given that the solar panel is more positive (12V) than the battery (9V). This idea is good, but what happens during the night? The battery will send the electrons to the solar panel because now the battery (9V) is “more positive” than the panel (ideally 0V). We don’t really want that…

2.2) Basic setup (the right one)

We have to find a way to prevent this “night-effect”: The solution resides in the use of a diode. The most common function of a diode is in fact to allow an electric current in one direction (called the forward biased condition) and to block the current in the opposite direction (the reverse biased condition). Take a look at the 1N4007 diode: at one end (the cathode) there is a gray ring: The current can’t flow from this side (but you can check with a multimeter that there is a very small voltage anyway of about 0.6V). Now you are free to connect all the devices this way:

solar panel (+) —> (-) diode (+) –> (+) battery (-) –> (-) solar panel

you can convince yourself that during the night the current will not flow from the battery to the solar panel.

Circuit Schematics

3) Connecting the Arduino board

Now that we are able to charge the battery with the solar panel, we can link the Arduino board to the whole circuit. The idea is simple: connect the (+)VIN terminal of Arduino to the (+) terminal of the battery/diode, and the (-) GND terminal to the common ground of the battery/solar panel. This way, Arduino will drain current from the “more positive” generator between the battery and the solar panel. As I said before, the problem is that the current generated by the panel is not constant. A trick to “smooth out” the voltage is to insert a capacitor between the (+) and (-) terminals of Arduino.

4) A few comments before I leave

You’ve probably seen around those fantastic devices that turns solar panels towards the Sun during the day in order to maximize the energy absorption. You could do that as well, but be aware of the fact that 12V are too much for the Arduino analog inputs! Maybe we will talk about that in next post.

ATLAS: Last detector connected

The LUCID detector, which will measure the luminosity of the collisions occurring in the centre of ATLAS, was among the last pieces of the detector to get approval. In fact, the small collaboration, based in Bologna, Italy; Alberta, Canada; Lund, Sweden; and at CERN, didn’t even begin building until February of last year.

LUCID is composed of two detectors that surround the beampipe, one on each side of ATLAS, at 17 metres from the collision point. Its commissioning started June 9th and 16th, when the last two pieces of the beampipe entered the cavern with detectors attached.

Vincent Hedberg, LUCID technical coordinator, and Marco Bruschi, project leader, are quick to downplay the challenges of their commissioning tasks when their detector has 40 channels compared to the millions of channels in other subdetectors. “They’d laugh us out of the house!” says Vincent. However, accessing their detector, 15 metres above the floor, in between the outer endcap muon chambers and endcap toroid magnet, was a feat in itself. “Vincent exaggerates a bit about how easy it is,” says Marco, “since the problem was to fit all the work into a very narrow allotted time, like in a Formula 1 pit stop.”

A portion of the beam shielding block is already in place on the beamline, half a cylinder with a flat top, resembling a bridge between the big muon wheel and the endcap toroid magnet. They built a platform on top of this as a work area. Without access by ladder or stairs, they had to commute to and from LUCID on cherry-picker cranes.

Connecting LUCID to all its services took more time than expected because other activities, such as the beampipe installation, were competing for work space and access to the cherry-pickers. Even so, they successfully connected the copper pipes to carry gas for detecting particles and water for cooling. They also hooked up the cables that will transmit the detector signals as well as the high and low voltage electricity that makes it run.

The bulk of the cabling was completed in the first two weeks, finishing around June 23rd, but a few difficult areas took a bit more time. According to Vincent, in an interview on July 2nd: “We finished with the last problem cable yesterday at nine o’clock.”

Testing began as soon as the first services were connected. As of July 15th, the cooling and gas systems, and high voltage were all working. “The only thing remaining is a broken LED electronics card on one side,” says Marco, “but that we will fix in the next few days. We are now preparing the read-out so that we can be fully prepared to catch the very first collisions from the LHC machine and provide luminosity measurement from day one!”

Accumulating evidence for nonstandard leptonic decays of Ds mesons

from arXiv:0803.0512v2 [hep-ph]

The measured rate for D_s -> l nu decays, where l is a muon or tau, is larger than the standard model prediction, which relies on lattice QCD, at the 3.8 sigma level. We discuss how robust the theoretical prediction is, and we show that the discrepancy with experiment may be explained by a charged Higgs boson or a leptoquark.

Dobrescu and Kronfeld show that the tree-level exchange of a spin-0 particle with mass of order 1TeV may account for the discrepancy.

[...]  A spin-0 particle of charge +1, H +, appears in models with two or more Higgs doublets. [...] The limits are satisfied for M < 500GeV.

Given that this model has not been previously studied, its 1-loop contributions to flavor-changing processes (such as b → sγ ) → need to be computed before deciding whether some fine tuning is required to evade experimental bounds.

The charge −1/3 and +2/3 exchanges correspond to leptoquarks [...] These interactions are present, for example, in R-parity violating supersymmetric models.

A ˜d scalar leptoquark of charge −1/3 may solve the Ds. At the LHC, the ˜d can be strongly produced in pairs, and the final states would be ℓ+ℓ j j , where ℓ is a τ or a µ, and j is a c-jet. The current limits on the ˜d mass from similar searches at the Tevatron are around 200 GeV.

Theory of Everything: A geometric approach to the standard model

Here is Garrett’s conclusions paragraph giving a descriptive overview of what he has accomplished:

“This paper has progressed in small steps to construct a complete picture of gravity and the standard model from the bottom up using basic elements with as few mathematical abstractions as possible. It began and ended with the description of a Clifford algebra as a graded Lie algebra, which became the fiber over a four dimensional base manifold. The connection and curvature of this bundle, along with an appropriately restricted BF action, provided a complete description of General Relativity in terms of Lie algebra valued differential forms, without use of a metric. This “trick” is equivalent to the MacDowell-Mansouri method of getting GR from an so(5) valued connection. Hamiltonian dynamics were discussed, providing a possible connecting point with the canonical approach to quantum gravity. Further tools and mathematical elements were described just before they were needed. The matrix representation of Clifford algebras was developed, as well as how spinor fields fit in with these representations. The relevant BRST method produced spinor fields with gauge operators acting on the left and right. These pieces all came together, forming a complete picture of gravity and the standard model as a single BRST extended connection. If this final picture seems very simple, it has succeeded. As a coherent picture, this work does have weaknesses. Everything takes place purely on the level of “classical” fields – but with an eye towards their use in a QFT via the methods of quantum gravity, which must be applied in a truly complete model. The BRST approach to deriving fermions from gauge symmetries, although a straightforward application of standard techniques, may be hard to swallow. If this method is unpalatable, it is perfectly acceptable to begin instead with the picture of a fundamental fermionic field as a Clifford element with gauge fields acting from the left and right in an appropriate action. The model conjectured at the very end, based on the related u(4) GUT, is yet untested and should be treated with great skepticism until further investigated. In a somewhat ironic twist, after arguing in the beginning for the more natural description of the MM bivector so(5) model in terms of mixed grade Cl1,3 vectors and bivectors, this conjectured model is composed purely of bivector gauge fields. Although the model stands on its own as a straightforward Cl8 fiber bundle construction over four dimensional base, there are many other compatible geometric descriptions. One alternative is to interpret ⇁ ̃A as the connection for a Cartan geometry with Lie group G – with a Lie subgroup, H, formed by the generators of elements other than ⇁e, and the spacetime “base” formed by G/H. Another particularly appealing interpretation is the Kaluza-Klein construction, with four compact dimensions implied by the Higgs vector, φ = −φ ψΓ ψ, and a corresponding translation of the components of ⇁ ̃A into parts of a vielbein including this higher dimensional space. The model may also be extended to encompass more traditional unification schemes, such as using a ten dimensional Clifford algebra in a so(10) GUT. All of these geometric ideas should be developed further in the context of the model described here, as they may provide valuable insights. In conclusion, and in defense of its existence, this work has concentrated on producing a clear and coherent unified picture rather than introducing novel ideas in particular areas. The answer to the question of what here is really “new” is: “as little as possible.” Rather, several standard and non-standard pieces have been brought together to form a unified whole describing the conventional standard model and gravity as simply as possible.”

see pre-print on http://arxiv.org/abs/0711.0770

ATLAS helps shed light on the retina

Technology developed for high-energy physics has led to the discovery of a retinal cell that eluded biologists for 40 years. 


The 512 electrode array, inspired by silicon microstrip detector technology in ATLAS, records the electrical activity of retinal neurones.
ATLAS expertise have crossed over to biology enabling the discovery of a retinal cell type that may help humans see motion. The research, carried out by ATLAS collaborators at the University of California, Santa Cruz, and by neurobiologists at the Salk Institute in La Jolla, California, appeared in the 10 October issue of the Journal of Neuroscience and may help open biologists’ eyes to the uses of techniques developed in high-energy physics.

At least 22 different types of primate retinal output cell are known from anatomical studies, but the functions of only a handful of these have been determined. The cells discovered have been called upsilon retinal ganglion cells and the team speculates that they are used to see moving objects and patterns. High-density electrode arrays and associated electronics, inspired by the silicon microstrip detector technology used in ATLAS to track the charged particles coming from collisions, were used to measure their distinct responses to visual images. The upsilons’ large light-sensitive areas and very sharp, rapid, and non-linear responses to changing patterns of light suggested that they were movement detectors.

The retina is the coating at the back of the eye that transforms arriving photons of light into electrical signals that it sends to the brain. The upsilon cells, part of the last layer of cells that send signals along the optic nerve, have been eluding biologists for 40 years. “These upsilon cells make up maybe a few percent of the output cells of the primate retina, and the chances of finding them are small as they’re so rare,” explains Alan Litke, senior author of the paper.

The experiment involved focusing a movie onto the retina and comparing this visual input with the electrical output from the retinal cells. Finding the rare cells required a huge number of electrodes within a small space, and so involved a miniaturisation process that was familiar to the CERN collaborators.

A critical part in the miniaturisation was amplifying, filtering, and reading out these electrode signals at high density. A set of multichannel integrated circuits, designed by ATLAS collaborator Wladyslaw Dabrowski and his team from the AGH University of Science and Technology in Krakow, Poland, allows 512 tightly packed electrodes to probe the retina, as opposed to the 61 previously, or just one of early experiments. The increase in electrodes meant a greater number of neurons could be probed at once, allowing researchers to monitor hundreds of cells at once, rather than just one or a few. “Finding one of these upsilons would be rare, and if you find a cell with unusual properties, you think maybe there’s something wrong, maybe it’s sick,” explains Alan. “What you really want to see is a mosaic of cells with similar properties and then you start to believe.”

ATLAS expertise was also employed in designing the software, which had to be designed from scratch as the amount of data collected was a huge step up for traditional neurobiology, though small compared to LHC standards. Dumitru Petrusca, one of the main software developers of the ATLANTIS event display program for ATLAS, undertook this task and was the first author of the upsilon paper.

Thanks to this software and technology, the neurobiologists, in collaboration with the physicists, are able to look at the bigger picture to gain a more complete idea of the vision process. “Traditionally, neurobiologists looked at just one neuron at a time. But to understand how a neural system, such as the retina or the brain, really works, we need to see the patterns of electrical activity generated by many neurons. Just like in ATLAS it would be near impossible to get at the underlying physics by looking at just one particle per event. You want to see the whole event because then you can say, for instance, there are two jets of particles with this total mass, and that’s the decay of the Higgs.”

For Alan, the processing and encoding of information is just one part of the puzzle of how the retina works. Another is how it gets wired up: “It’s a three-dimensional wiring problem. The upsilon cell connects to all these other cells and layers and we want to find out how the cells know where to go, how they connect to one another and make the right connection. It would be like the thousands of cables in ATLAS growing out of the pit and finding their way to the right control room, rack of electronics, crate and finally module, all on their own.”

Related projects include retinal prosthesis: using electrode array technology to electrically stimulate retinal output cells, using input from a video camera, to bypass the degraded photoreceptors in patients with macular degeneration. Small arrays that give some basic vision are already being trialled in six blind patients by Mark Humayun and his team at the University of Southern California.

This result may open up further opportunities for transferring expertise and techniques from high-energy physics to biology. “It’s not just the upsilon, it’s the combination of the technique and the discovery,” says Alan. “Biologists are rarely aware of the technologies developed for high energy physics, so one way to bring this to the attention of the neurobiological community is to have an interesting neurobiological result. Now we’ll see where it takes us.”

Ideas that spring from the meeting of minds

Progress is not often a scientific activity alone, but is helped on its way by chance meetings and cafeteria conversations. Whilst working at SLAC and watching his children learn to walk, talk and develop, Alan Litke wondered how silicon microstrip detector technology could be applied to understanding the fascinating depths of the brain, but without a scientist’s “six degrees of Kevin Bacon” the research wouldn’t have happened. “I had some pretty crazy ideas, but in the end one of the post-docs in my group had a neighbour who was a neurobiologist at Stanford and who was working in the lab of someone who was one of the world experts on the retina. So I started to help in any way I could.” And he hasn’t looked back. In the past some of the best science has comes from collaborations with those outside a tradition and this one has already made great steps in unravelling the mysteries of the retina.

Doubly Special Relativity

 

Doubly-special relativity — also called deformed special relativity or, by some, extra-special relativity — is a modified theory of special relativity in which there is not only an observer-independent maximum velocity (the speed of light), but an observer-independent minimum length (the Plank length).

This was first proposed in a paper by Giovanni Amelino-Camelia, though it is at least implicit in a paper by Paul Merriam. An alternate approach to doubly-special relativity theory, inspired by that of Amelino-Camelia, was proposed later by João Magueijo and Lee Smolin. There exist proposals that these theories may be related to loop quantum gravity.

One of the motivations for this work is the observation of high-energy cosmic rays that appear to violate the Greisen-Zatsepin-Kuzmin limit: the so-called Oh-My-God particles.

The theory is highly speculative as of first publishing in 2002. The theory is built using a well-established approach in theoretical physics named invariance under transformation, which is colloquially (even in science) called relativistic. Nevertheless the theory is not considered a promising approach by a majority of members of the high-energy physics community.

DSR is based upon a generalization of symmetry to quantum groups. The Poincaré symmetry of ordinary special relativity is deformed into some noncommutative symmetry and Minkowski space is deformed into some noncommutative space. This theory is not a violation of Poincaré symmetry as much as a deformation of it and this symmetry is exact. This deformation is scale dependent in the sense that the deformation is huge at the Planck scale but negligible at much larger length scales. Many models which are significantly Lorentz violating at the Planck scale are also significantly Lorentz violating in the infrared limit because of nasty radiative corrections. Without any exact Lorentz symmetry to protect them, such Lorentz violating terms will be generated with abandon by quantum corrections. However, DSR models do not succumb to this difficulty since the deformed symmetry is exact and will protect the theory from unwanted radiative corrections — assuming the absence of quantum anomalies.

Jafari and Shariati have constructed canonical transformations that relate both the doubly-special relativity theories of Amelino-Camelia and of Magueijo and Smolin to ordinary special relativity. They claim that doubly-special relativity is therefore only a complicated set of coordinates for an old and simple theory. However, all theories are related to free theories by canonical transformations. Therefore supporters of doubly-special relativity may claim that while it is equivalent to ordinary relativity, the momentum and energy coordinates of doubly-special relativity are those that appear in the usual form of the standard model interactions. This implies that ordinary special relativity and doubly-special relativity make distinct physical predictions in high energy processes, and in particular the derivation of the Greisen-Zatsepin-Kuzmin limit is not valid if one asserts that quantum electrodynamics takes its usual Maxwell form only in the coordinate systems of doubly-special relativity.

Literature

• Fabio Cardone[1], Roberto Mignani , Energy and Geometry: An Introduction to Deformed Special Relativity, World Scientific 2004, ISBN 981-238-728-5

External references

• Giovanni Amelino-Camelia, “Doubly-Special Relativity: First Results and Key Open Problems.” Int. J. Mod. Phys. D11 (2002) 1643. Online copy at http://arxiv.org/abs/gr-qc/0210063
• Giovanni Amelino-Camelia, Doubly-Special Relativity.’ http://lanl.arxiv.org/abs/gr-qc/0207049, a non-technical review
• Nosratollah Jafari, Ahmad Shariati, Doubly Special Relativity: A New Relativity or Not? http://arxiv.org/abs/gr-qc/0602075

[CERN] A word from the DG: LHC commissionning enters the home straight

A word from the DG: LHC commissionning 
enters the home straight

 

In an age of blogs there are seemingly no secrets, so by the time Lyn Evans gave his talk on the status of LHC commissioning on 13 September, everyone seemed to know about plug-in modules, beam position monitors and transmitters embedded in ping-pong balls. All the on-line speculation made for interesting reading, and is a clear sign of the growing interest there is in CERN as we approach LHC start-up. We are now entering the final phase of commissioning, and things are going well given the unprecedented complexity of the task in hand.

Following the cool-down, powering and warm-up of Sector 7-8 earlier this year, we have learned a great deal about what it means to commission the LHC. There have inevitably been hitches, including the plug-in modules, or PIMs. When the LHC is cooled down, each sector shrinks by about 10 metres in length, and this has to be absorbed by bellows between components and a system of sliding copper fingers (PIM) that ensure electrical connectivity around the ring. When warming up Sector 7-8, a small number of fingers buckled as the machine expanded and are being repaired. The problem is understood, and concerns only a small percentage of the PIMs. To identify precisely where the problem occurs, an ingenious system involving blowing an object like a ping-pong ball with a 40 MHz transmitter (the frequency of the beam bunches seen by the position monitors) along the beam pipe has been devised.

Lessons learned from Sector 7-8 are being put into practice in other sectors. A second sector has been rapidly cooled to 80 degrees above absolute zero, a third is undergoing pressure tests, and testing of the remaining five sectors will now start at the rate of one every two weeks. In the sectors currently under test, vacuum leaks have been isolated and are also being repaired.

Meanwhile, the repair of the LHC’s inner triplet magnets is complete. A team from CERN, Fermilab, KEK and the Lawrence Berkeley National Laboratory has successfully completed the repairs. So far, three of the eight triplets have been installed and successfully pressure-tested in the tunnel. The remaining triplets are in the process of installation and pressure testing.

All of this is business as usual when bringing a new particle accelerator on-line. There are inevitably hurdles to be overcome, but so far there have been no show stoppers. We can all look forward to the LHC producing its first physics in 2008.

Robert Aymar