engage Quantum

The Quan­tum Leap
ele­Qtron devel­ops and oper­ates quan­tum com­put­ers. Our next-gen­er­a­tion com­put­ing machines will be able to solve prob­lems in chem­istry, life sci­ences, logis­tics and finance that even the best con­ven­tion­al super­com­put­ers can­not han­dle To do this, we com­pute with the quan­tum states of atoms (qubits), shield­ed from inter­fer­ence. The ground­break­ing con­cept we have devel­oped, called MAGIC, allows these qubits to be con­trolled reli­ably and pre­cise­ly using estab­lished, inex­pen­sive and minia­tur­iz­able high-fre­quen­cy tech­nol­o­gy. Join us in the quan­tum revolution! 
Then and Now

Capabilities and Applications

The prob­lem of opti­miz­ing func­tions has occu­pied sci­en­tists for a long time. Often, how­ev­er, the search for the best solu­tion is tri­al and error. Quan­tum par­al­lelism allows test­ing many solu­tions simul­ta­ne­ous­ly and thus find­ing the best solu­tion much faster. This makes it pos­si­ble to tack­le prob­lems that cause dif­fi­cul­ties for con­ven­tion­al com­put­ers and that are impor­tant in quan­ti­ta­tive finance, for example. 
Cal­cu­lat­ing the prop­er­ties of large mol­e­cules, due to the large num­ber of inter­act­ing par­ti­cles, is extra­or­di­nar­i­ly dif­fi­cult with­out approx­i­ma­tions. The intrin­sic par­al­lelism of a quan­tum com­put­er could cope with this chal­lenge. This is how one would imple­ment Feynman’s orig­i­nal quan­tum com­put­er pro­pos­al: Sim­u­lat­ing phys­i­cal par­ti­cles and their inter­ac­tions by ‘recre­at­ing’ this sce­nario with oth­er, more con­trol­lable particles.
Ressource-shar­ing prob­lems are com­mon in logis­tics. Is there any way for instance to opti­mize the car­go of a means of trans­port for dif­fer­ent prop­er­ties — like weight and price? Depend­ing on the exact struc­ture of the prob­lem, even small sizes can be extra­or­di­nar­i­ly dif­fi­cult to solve. Quan­tum com­put­ing, how­ev­er, will be able to address it.
Search Algo­rithms
Quan­tum search algo­rithms can search large data­bas­es much faster than con­ven­tion­al algo­rithms. From a large num­ber of pos­si­ble entries, those that ful­fill cer­tain con­di­tions are select­ed. One can even prove that quan­tum algo­rithms in prin­ci­ple search faster than exist­ing clas­si­cal algo­rithms. Thus, no clas­si­cal algo­rithm can be writ­ten that beats its quan­tum equivalent.
In par­tic­u­lar, the quan­tum Fouri­er trans­form (QFT), a quan­tum equiv­a­lent of the con­ven­tion­al Fouri­er trans­form, is used for cryp­to­graph­ic appli­ca­tions, i.e., deci­pher­ing codes. We have also already real­ized the QFT with our quan­tum computers.
Machine Learn­ing
Machine learn­ing has gained tremen­dous impor­tance in recent years and can help, for exam­ple, in pat­tern recog­ni­tion, with appli­ca­tions in research as well as in every­day and indus­try-rel­e­vant ques­tions. Quan­tum com­put­ers can dras­ti­cal­ly speed up the deci­sion-mak­ing process­es in machine learn­ing, for which we have already pre­sent­ed first results.

Quan­tum Com­put­ers can solve math­e­mat­i­cal prob­lems which con­ven­tion­al com­put­ers can­not tackle.

The small­est com­pu­ta­tion­al unit of a Quan­tum Com­put­er, just as a Bit is the small­est unit of a conen­tion­al com­put­er. A qubit, how­ev­er, can take the val­ues 0 and 1 — at the same time.

The bits of a con­ven­tion­al com­put­ers take the val­ues 1 or 0 — this is the basis for cal­cu­la­tions. The Quan­tum Com­put­er can take com­bi­na­tions (‘Super­po­si­tions’) of 1 and 0. This means that a par­al­lel cal­cu­la­tion on dif­fer­ent inputs is pos­si­ble. Sev­er­al solu­tions can be tried out at the same time, so to speak.

There are work­ing Quan­tum Com­put­ers with some dozens of qubits, and they can solve spe­cial test prob­lems which would take clas­si­cal com­put­ers much longer. Until, how­ev­er, a freely pro­gram­ma­ble Quan­tum Com­put­er is rel­e­vant for indus­tri­al appli­ca­tions, many prob­lems will have to be solved. In par­tic­u­lar the qual­i­ty of the gate oper­a­tions — the sim­plest steps of the cal­cu­la­tion — has to be increased drastically.

No! Spe­cial prob­lems of com­mer­cial and sci­en­tif­ic rel­e­vance can be attacked by so-called NISQs (Noisy Inter­me­di­ate-Scale Quan­tum Com­put­ers). These are com­put­ers with lim­it­ed qubit num­ber and gate fideli­ty. The devel­op­ment of NISQs with rel­e­vant cal­cu­la­tion pow­er is ongo­ing, and als per­mits the tech­nol­o­gy improve­ment which will be nec­es­sary for uni­ver­sal quan­tum computers.

Prob­lems in basic research, like the sim­u­la­tion of large quan­tum sys­tems; but also prob­lems from finance, chem­istry and logistics